Preliminary Demography of
2011 Population Census
in India
Aalok Ranjan Chaurasia
Professor
‘Shyam’ Institute
82, Aradhana Nagar
Bhopal, MP-462003
India
www.shyaminstitute.in
July 2011
‘Shyam’ Institute
Mudian Ka Kuan,
Datia, MP-475661, India
91-752-2234522
www.shyaminstitute.in
Preliminary Demography of 2011 Population Census in India
© 2011 Shyam Institute
All rights reserved. No part of the publication can be reproduced or transmitted in any form or
by any means including photocopying, recording or any information storage and retrieval
system without permission in writing from MLC Foundation.
ISBN: 978-93-82411-02-4
Rs 800
In the memory
of
‘Amma’ and ‘Daddy’
Contents
1
Introduction
1
2
Population Size and Growth
15
3
Population Distribution
41
4
Age Composition
63
5
Sex Composition
83
6
Inter-state Migration
117
7
Conclusions
129
References
133
Statistical Tables
135
Provisional Population Totals
220
1
Introduction
India is the largest democracy and the second most populous country of the world. It accounted
for more than 17 per cent of the world’s population in 2010 according to the estimates prepared
by the United Nations (United Nations, 2011). This 17 per cent of the world population lives on
less than 2.5 per cent of the total land area of the planet Earth. The population of the world is
estimated to have increased at the rate of 1.22 per cent per year between 2000 and 2010, adding,
on average, about 79 million persons every year. India accounted for very close to 22 per cent of
this increase. India’s contribution to the increase in the world population has been the largest,
even larger than the contribution of China, the most populous country in the world today (United
Nations, 2011). The medium variant of population projections prepared by the Population
Division of the United Nations suggests that population of India is the most likely to increase to
1614 million by the year 2050. At that time, India will account for almost 19 per cent of the
projected world population of around 9150 million. This means that out of the projected 2854
million increase in the world population during the 50 years between 2000 and 2050, more than
571 million or almost 19 per cent will be confined to India alone. The population projections
prepared by the United Nations also suggest that by the year 2025, India is most likely to become
the most populous country of the world, surpassing China. Obviously, population stabilisation
in the world as a whole will depend, to a very significant extent, on the pace of population
transition in India in the years to come. According to the medium, most likely, variant of
population projections prepared by the United Nations, there is little possibility that Indian will
be able to achieve the goal of population stabilisation before the year 2060 and not around the
year 2045 as stipulated in the National Population Policy (Government of India, 2000).
1
Preliminary Demography of India
After the 2001 population census, Government of India has taken a number of key policy
initiatives that have relevance to the future population growth in the country. The first of these
initiatives was the National Population Policy which was announced in the year 2000 and which
aimed at achieving zero population growth in the country by the year 2045 through reducing
fertility to the replacement level by the year 2010 (Government of India, 2000). In the year 2005,
India launched the National Rural Health Mission which aimed at architectural corrections in the
public health care delivery system of the country so as to meet the health and family welfare
needs of the people, especially, people living in rural and remote areas (Government of India,
2005). At the same time, the process of economic reforms that started in 1990 continued with a
varying pace. A revival of economic reforms and better economic policies during the first decade
of the present century has accelerated the economic growth. Today, India is the second fastest
growing major economy of the world.
These facts explain the special interest with which the results of the 2011 population census in
India were awaited. Provisional results of the 2011 population census have now been released
(Government of India, 2011). These figures supply basic data about population size and growth,
population distribution and age and sex composition of the population along with the level of
literacy for the country as a whole as well as for its constituent states and Union Territories and
for districts within the states and Union Territories. The synergistic possibilities of analysing
these data in the context of planning and programming for population transition and social and
economic development in the country and its constituent administrative units are truly
remarkable. Such analysis can transform the data available through the population census into
estimates of selected indicators of demographic and development dynamics to facilitate evidencebased population and development planning and programming right up to the district level. The
importance of the population census in population and development planning may be judged
from the fact that, at the district level, population census is the only source of data for analysing
the population scenario and social and economic development situation and setting up the
priorities for social and economic development programmes and activities.
This monograph analyses the provisional data of the 2011 population census to present a first
hand perspective of the prevailing demographic situation in India and highlights the challenges
faced by the country in the context of population transition. The analysis is primarily confined
to the spatial analysis - analysis across administrative units - of selected population related issues
for which data are available through the 2011 population census. There have also been efforts
to analyse the change in selected population related variables between 2001 and 2011 for which
data at two points of time are available. At the 2001 population census, there were 35 states and
2
Introduction
Union Territories and 595 districts in the country. There has been no change in the number of
states and Union Territories at the 2011 population census but the number of districts has been
increased to 640. Analysis of the trends in some aspects of the population situation at the district
level, therefore, is not possible at present as it requires redistribution of the data collected at the
2001 population census across the 640 districts in the country as they existed at the 2011
population census.
The monograph is divided into six chapters in addition to the present introduction and the
customary epilogue. Each chapter of the monograph focusses upon one dimension of the
population situation at the country, state and district level on the basis of the provisional figures
of the 2011 population census. Chapter two of the monograph analyses the size and growth of
the population at the national, state/Union Territory and district level while the third chapter deals
with the issue of the distribution of the population across administrative units - states/Union
Territories and districts in the country. The fourth chapter carries out a preliminary analysis of
the age composition of the population whereas chapter five is devoted to the analysis of the sex
composition of the population including the sex composition of the population aged 0-6 years.
The sixth chapter of the monograph attempts a preliminary analysis of inter-state movement of
population during the period 2000 through 2011 on the basis of the estimated and enumerated
population of the country. Finally, the epilogue of the monograph highlights some salient
findings of the 2011 population census in the context of population transition and social and
economic development in the country and in its constituent states/Union Territories and districts
within the states/Union Territories.
An integral feature of the monograph is to present selected population-related indicators for all
the 640 districts of the country as they existed at the time of the 2011 population census on the
basis of provisional data of the 2011 population census. Although, the Registrar General and
Census Commissioner of India has released provisional data for all the 640 districts of the
country on the basis of the 2011 population census, yet district level analysis of these data has
been carried out in a limited sense at the state/Union Territory level only and has been released
as state/Union Territory specific Paper 1 of the 2011 population census. The Registrar General
and Census Commissioner of India has not carried out district level analysis at the national level.
Moreover, a review of the district level analysis carried out by different states and Union
Territories of the country reveals that there has been little uniformity even in the limited analysis
that has been carried out at the district level in different states and Union Territories of the
country. This monograph presents district level analysis of the provisional data of the 2011
population census for all the 640 districts of the country.
3
Preliminary Demography of India
History of the Population Census in India
The history of the population census in India dates back to ancient times. The 'Rig-Veda' reveals
that some kind of population count was maintained in the ancient India. The celebrated
'Arthashastra' by 'Kautilya' written in the 3rd Century BC prescribed the collection of population
statistics as a measure of state policy for taxation. It contained a detailed description of methods
of conducting population, economic and agricultural censuses. During the regime of the Mughal
king Akbar, the administrative report 'Ain-e-Akbari' included comprehensive data pertaining to
population, industry, wealth and many other characteristics. In the recent times, a systematic and
modern population census, in its present form, was conducted non synchronously between 1865
and 1872 in different parts of the country. This effort culminated in the population census of
1872 which is popularly labelled as the first population census in India. However, the first
synchronous census in India was held in 1881 which provided the most complete and continuous
demographic record for any comparable population. Since then, the population census is being
conducted after every ten years in the country. The unbroken series of the decennial population
census in India, now spanning more than a century, provides an extraordinary storehouse of
information for demographic analyses. The population census in India has collected information
on such aspects as population size and growth, population distribution across administrative
units, population structure, etc. The population census in India has also collected information
related to such issues as housing conditions, migration, social class and residence structure,
literacy, religion, physical deformities, sex, civil conditions, etc. Another focus area of the
population census in India has been the occupational classification. The 1881 census adopted 6
classes, 18 orders, 75 sub-orders and 480 groups of occupations, while the 1891 census adopted
a set of 478 occupations divided into 7 classes, 24 orders and 77 sub-orders which was improved
upon at the 1901 population census by 521 occupations divided into 8 classes, 24 orders and 79
sub-orders. The classification adopted at the 1901 population census also made an exhaustive
analysis of social class specific occupations.
An innovative feature of the decennial population count in India is that it has never been bounded
hand-and-foot to the tradition and has never taken shelter 'behind an official wall of infallibility'.
Rather, every population census in the country has broken new grounds without losing
comparability with the previous census. The population census in India has always paid a good
deal of attention to the contemporary situation and the requirements of the government while
trying to keep pace with advanced census quests. In short, it has never rested on its oars, but has
always been the most fruitful single source of information on population of the country and it’s
constituent political and administrative units - states and Union Territories, districts, sub-districts,
towns and villages.
4
Introduction
The first population census in the independent India was conducted in 1951. The report of the
1951 population census attempted, for the first time, analysis of the past changes in the size and
structure of the population and pointed out the implications of these changes to the level of living
of the people. The report also recommended a reduction in the birth rate for accelerating the
social and economic progress in the country. The 1951 population census also attempted, for the
first time in the history of the population census in India, an assessment of the accuracy of the
census count by carrying out the post-enumeration check.
Since 1951, information requirements of different government departments including the
Planning Commission and other agencies necessitated the expansion of the scope of the decennial
population census and the analysis of the data available through the census. A novel feature of
the 1961 population census was large number of ancillary studies relating to rural craft, fairs and
festivals and ethnographic surveys. At the 1971 population census, the census schedules were
further modified. New features of the 1971 population census included (i) data on current
fertility, (ii) internal migration, and (iii) revamping of economic questions. The main activity of
a person was ascertained according to the time the person spent as a worker producing goods and
services or as a non-worker. A new concept of 'standard urban Area' was also introduced at the
time of the 1971 population census.
The population census in India has not been a mere head count of the people. The data available
through the population census in the country have been analysed to present not only the
demographic but also the social, cultural and the economic profile of the country and its
constituent states, Union Territories and districts. The data available through the population
census have also been used for the formulation of development policies and planning and
programming of development activities and programmes. The data available from the population
census and have been widely used by national and international agencies, researchers and
scholars, journalists and philanthropists and even by the business community. The census data
have also been used for such purposes as delimitation of electoral constituencies and affirmative
action such as reservation. The data available through different population censuses have always
been analysed and interpreted in an interesting manner to highlight the demographic, social,
cultural and development diversity. These analyses and interpretations have always been products
of scholarship. A large number of experts have been associated with the analysis of the diverse
nature of the data available through the population census. These analyses have often been the
only authentic source of the social, cultural and economic conditions of the people and the
demographic dynamics, especially at the local level. The decennial population census is an
indispensable part of the statistical system in India.
5
Preliminary Demography of India
Table 1.1
Reference date and census methodology in India
Census
Reference date
Methodology
1881
17th February
de facto (Synchronous)
1891
26th February
de facto (Synchronous)
1901
1st March
de facto (Synchronous)
1911
10th March
de facto (Synchronous)
1921
18th March
de facto (Synchronous)
1931
26th February
de facto (Synchronous)
1941
1st March
Extended de facto (Synchronous)
1951
1st March
Extended de facto (Synchronous)
1961
1st March
Extended de facto (Synchronous)
1971
1st April
Extended de facto (Synchronous)
1981
1st March
Extended de facto (Synchronous)
1991
1st March
Extended de facto (Synchronous)
2001
1st March
Extended de facto (Synchronous)
2011
1st March
Extended de facto (Synchronous)
Source:
Government of India (2011).
The organisation of the decennial population census in India is governed by the Census Act of
1948. Till 1951, the organisation responsible for conducting the population census in the country
functioned like the phoenix which means that the organisation used to come into existence just
on the eve of the population census and was wounded up as soon as the census operations were
over, usually within two or three years of its creation. With the enactment of the Census Act in
1948, a permanent nucleus for conducting the population census at the national level was created
which made it possible to continue activities related to the population census even during the
inter-census period. Subsequently, permanent establishments have also been created at the state
level. However, at the district level, the phoenix approach continues to exist so that there is
hardly any capacity to analyse of the data collected during the population census at the local
(district) level. Lack of analytical capacity at the district level severely limits the use of census
data for local level planning and programming of development activities.
6
Introduction
The population census in India is conducted on the basis of extended de facto canvasser method.
In this method, data are collected from every individual by visiting the household and canvassing
the same questionnaire all over the country during a specific period. The count is then updated
to the reference date and time by conducting a revision round. In the revision round, any change
in the entries that arise on account of births, deaths and migration between the time of
enumerators, visit and the reference date/time is noted and the record is updated. This approach
is a modification of the synchronous de facto method that was used till 1931 wherein the census
count was conducted throughout the country on a single night. This method, was not only costly
but it also required mobilisation of an extremely large force of enumerators on the day of
enumeration. In a large and diverse country like India, mobilising millions of enumerators for
counting the people on one single night was found extremely challenging and so this method was
replaced by the current method in 1941.
The census operations in India are carried out in two phases. In the first phase, house listing is
done and a census of all households is carried out. The house list prepared during the listing
operation serves a sound frame for population count. On the other hand, the household census
is carried out to collect information about the purpose for which the household is used. In
addition, such information as material used in constructing the house and facilities available in
houses being used for residential purposes such as availability of drinking water, sanitation
facilities including availability of the latrine and availability of the electricity are collected. Since
1981, there has been an attempt to collect information about a specific set of household assets
available in the residential households and the use of banking facilities by household members.
This information has been used along with the information about household facilities to measure
and analyse the living conditions of the people.
Right since its inception, the population census in India has evolved as a descriptive statistical
system, conceived as a general instrument of measurement of change through decennial
operations, delineating demographic, social and economic features of India (Mitra, 1973). There
have been efforts to transform the population census in India into a professional and analytical
statistical system but these efforts could not succeed because of the strength of the original
incrustation. One reason probably and so obviously is that the population census was conceived
as an aid to the general administration system in the country and therefore has remained adjunct
to the normal administrative machinery at the district, state/Union Territory and national level.
The analysis of the huge data collected through the population census has generally been left to
individual researchers in such disciplines as demography, sociology, economics, etc. for analysis
and, therefore, utilisation of the census data remains, at best, limited.
7
Preliminary Demography of India
A unique feature of the data available through the population census is that it is distributive in
nature in the sense that the count at the national level can be distributed across states and Union
Territories and the count at the state/Union Territory level can be distributed across the districts
within the state/Union Territory. This process can be extended right up to the village/municipal
ward level. Alternatively, the count at the village/municipal ward level can be added up to the
count at the district, state/Union Territory and the national level. An implication of this
distributive property of the census data is that it is possible to estimate the contribution of the
situation at the lower level administrative units to the situation at the upper level administrative
units. For example, it is possible to estimate how the sex composition of the population in a
village or municipal ward contributes to the sex composition of the population at the district level
or the age composition of the population in a state/Union Territory contributes to the age
composition at the national level. There has however been little attempt to analyse the census
data in this context. Instead, the analysis of the census data has been confined to estimating such
indicators as the population sex ratio or the population in a certain age group. In this approach,
it is not possible to explore how the population sex ratio in a state or Union Territory influences
the population sex ratio at the national level or the age composition of the population in a village
influences the age composition of the population of the district. The preoccupation with the
description of the census data has resulted in a gross neglect of the analysis of the census data
which is necessary through the perspective of development planning and programming.
The 2011 Population Census
The population census 2011 was the 14th since 1881 and the 7th in the independent India. The
canvassing of the questionnaire of the 2011 census was done during the period 9th February 2011
through 28th February 2011 while the revision round was conducted during the period 1st March
2011 through 5th March 2011. An exception to this schedule was made in selected areas of the
country which were snow bound during the month of February. In these areas, canvassing of the
questionnaire was done during the period 11th September through 30th September 2010 while the
revision round was conducted during 1st October through 5th October 2010. The count was then
updated to the reference moment of 00:00 hours of 1st March 2011 (Government of India, 2011).
Two schedules were canvassed during the 2001 population census - house listing schedule and
household scheduled. The house listing schedule collected the following information:
• Predominant material of floor, roof and wall of the house.
• The purpose for which the house is being used.
• If used wholly or partially as residence then total number of persons normally residing in the
household and the name of the head of the household and her/his sex and social class.
8
Introduction
•
In case of residential households
<
Ownership of the household
<
Number of dwelling rooms
<
Number of married couples living in the household
<
Main source of drinking water
<
Availability of drinking water source
<
Main source of lighting
<
Latrine within the premise
<
Waste water disposal
<
Bathing facility available within the premise
<
Availability of kitchen
<
Fuel used for cooking
<
Radio/Transistor
<
Television
<
Computer/Laptop
<
Telephone/Mobile phone
<
Bicycle
<
Scooter/Motorcycle/Moped
<
Car/Jeep/Van
<
Use of banking services by household members.
On the other hand, the household schedule collected the following information for each member
of the household:
<
Name of the member of the household
<
Relationship with the head of the household
<
Sex
<
Date of birth and age
<
Current marital status
<
If married, age at marriage
<
Religion
<
Social class (Scheduled Castes/Scheduled Tribes)
<
Any disability
<
Mother tongue
<
Other languages known
<
Literacy status
<
Status of school attendance
<
Highest level of education attained
9
Preliminary Demography of India
<
<
<
<
<
<
<
<
<
<
Work status during one year prior to the census
Economic activity in which involved
Occupation
Birth place
Place of last residence
Reasons for movement
Duration of stay in the present place of residence
Total number of children currently surviving
Total number of children ever born
Live birth in the last year.
The provisional figures of the 2011 population census released by the Census Commissioner of
India include total count of the people of all ages by sex, total count of the people in the age
group 0-6 years and the total count of the people who were literate - able to read and write with
understanding. These data are available for the country as a whole, for its 35 states and Union
Territories and for its 640 districts. This information constitutes the basic data set for the present
monograph.
Methodology
The present monograph incorporates an alternative approach to the analysis of the census data
which is built upon the distributive or the additive property of census counts across the
administrative units. Since the provisional figures of the 2011 population census have been
provided up to the district level only, the approach attempts to analyse how the situation
prevailing at the district level contributes to the situation that prevails at the country level. This
is done by adopting a two-dimensional approach of the analysis. The first dimension of this
approach captures how the situation prevailing at the district is different from the situation that
prevails at the country level. This difference is a reflection of the intensity of the situation
prevailing in a district relative to the situation prevailing at the country level. The second
dimension, on the other hand, captures the extent to which the given situation prevails or the
extensiveness of the situation. A combination of intensity and extensiveness then gives an idea
about the distribution across administrative units. This approach takes into account the
distributive property of the census data and establishes the link between the situation at lower
level administrative units with the situation at the upper level administrative units. All
measurements in this approach are in relative terms - the situation in a district relative to the
situation in the country. The use of the relative measures ensures that the indicators used for the
analysis have additive and multiplicative properties.
10
Introduction
If Pc denotes the count of the people at the upper level administrative unit and Pd denotes the
count of the people at the lower level administrative units, then, it is obvious that
Pc = 3Pd
œ d0c,
(1.1)
The most simple and straightforward measure of the size or the extensiveness population in a
lower level administrative unit d in relation to other lower level administrative units may then
be defined as the proportion of the population in the lower level administrative unit to the
population in of the upper level administrative unit. In other words, a measure of the relative size
of the population or an index of the extensiveness of population in the administrative unit d may
be defined as
Edc = Pd/Pc œ d0c.
(1.2)
It is obvious that
3Edc = 1 for all d0c
(1.3)
On the other hand, the relative gravity or intensity of a demographic variable V in a lower level
administrative unit d in relation to other lower level administrative units may be defined in terms
of the ratio of the value of the variable V for the lower level administrative unit d to the value of
the variable V for the upper level administrative unit c (Vd/Vc). The relative gravity or intensity
of the demographic variable V in a lower level administrative unit in relation to other lower level
administrative units may now be measured through the index of intensiveness which is defined
as
Idc(v) = log (Vd/Vc) for all d0c.
(1.4)
where log represents the logarithm to the base 10. It is obvious that when Vd/Vc = 1, Idc(v) = 0;
when Vd/Vc > 1, Idc(v) > 0 and when Vd/Vc < 1 Id(v) < 0. When Idc(v) > 0, the variable V is more
intense in the lower level administrative unit d as compared to the upper level administrative unit
c and vice versa.
Finally, the index of the distribution of the variable V in a lower level administrative unit d is
defined in relation to the upper level administrative unit c as
Ddc(v) = (Pd/Pc )*log (Vd/Vc)
= Edc*Idc(v) œ d0c.
(1.5)
and the the index of the distribution of the variable V for the upper level administrative unit c is
then defined as
œ d0c.
Dcd(v) = 3Ddc(v)
(1.6)
The distributive indexes defined by (1.5) and (1.6) take into account both the demographic
situation and size of the in a lower level administrative unit in relation to other lower level
11
Preliminary Demography of India
administrative units and therefore may be regarded as the fuller-information measure of the
variability in the demographic phenomena across the lower level administrative units in relation
to the upper level administrative units in situation where lower level administrative units are fully
nested in the upper level administrative unit. An important feature of the index of distribution
defined by (1.6) is that it has the additive property as it is the sum of the index of distribution of
all lower level administrative units. Another property of the indexes defined by (1.5) and (1.6)
is that they weight to the relative size of the population. A lower level administrative unit have
a larger population than another lower level administrative unit will have larger impact on the
index of distribution of the upper level administrative unit even if the relative intensity of the
demographic phenomenon in the two lower level administrative units is the same and vice versa.
Conventional indicators of measuring and analysing the demographic situation, commonly used
in the description and preliminary analysis of the census data, do not have these additive and
multiplicative properties.
The above approach can be extended to a situation where there are more than two levels of
administrative units. For example, suppose that there are three levels of administrative units with
the lowest level administrative unit termed as d, middle level administrative unit termed as s, and
the upper level administrative unit termed as c. Also assume that d are nested in s and s are
nested in c. Then it is straightforward to note that
Ps = 3Pd
œ d0s, and
(1.7)
and
Pc = 3Pc
œ s0c.
(1.8)
We now define the following indicators for relative extensiveness
Eds = Pd/Ps œ d0s, and
Esc = Pc/Pc
œ s0c.
Obviously
3Eds = 1 for all d0s, and
3Esc = 1 for all s0c.
(1.9)
(1.10)
(1.11)
(1.12)
We can also define the indicators of relative gravity or intensiveness of a demographic variable
V in the following manner
Ids(v) = log (Vd/Vs) for all d0s, and
(1.13)
Isc(v) = log (Vs/Vc) for all s0c.
(1.14)
Then the index of distribution of variable V for the lowest level administrative unit d can be
defined in relation to the upper level administrative unit c as
12
Introduction
Ddc(v) = (Pd/Pc )*log (Vd/Vc)
= Edc*Idc(v) œ d0c.
(1.15)
Similarly, we can also define the index of distribution of variable V for the lowest level
administrative unit d in relation to the middle level administrative unit s as
Dds(v) = Eds*Ids(v) œ d0s,
(1.16)
and the index of distribution of variable V for the middle level administrative unit s in relation
to the upper level administrative unit c as
Dsc(v) = Esc*Isc(v) œ s0c.
(1.17)
Finally, the index of distribution of the variable V for the middle level administrative unit s can
be defined as
Dsd(v) = 3Dds(v).
(1.18)
At the same time, we can also define the index of distribution of the variable V for the upper
level administrative unit c in relation to the middle level administrative units s as
Dcs(v) = 3Dsc(v).
(1.19)
It should be clear that Dcd(v) … Dcs(v), although the index Dcd(v) can be decomposed into indexes
Dsd(v) and Dcs(v). In fact, it is easy to show that
Dcd(v) = 3Esc*Dsd(v) + 3Eds*Dcs(v).
(1.20)
Equation (1.20) shows that the distributive index Dcd(v) which measures how the variable V is
distributed across the administrative level d in relation to the demographic situation at the
administrative level c can be decomposed into how the variable V is distributed across the
administrative level d in relation to the situation at the administrative level s and how the variable
V is distributed across the administrative unit s in relation to the situation at the administrative
level c. If the upper level administrative units represents the country, middle level the state/Union
Territory and the lower level the district, then equation (1.20) makes it possible to analyse the
distribution of a demographic variable across the states and Union Territories in relation to the
situation prevailing in the state/Union Territory contributes to the distribution of a demographic
variables across the districts in relation to the situation at the country level. Similarly, equation
(1.20) also permits to assess how the distribution of a demographic variable across the
states/Union Territories in relation to the situation at the country level also contributes to the
distribution of the demographic variable across the districts in relation to the situation at the
country level. In this sense, the equation (1.20) decomposes the diversity in the distribution of
demographic variables into within states/Union Territories across district component and within
country across state/Union territory component.
13
Preliminary Demography of India
Throughout the present monograph, we apply the above approach for the analysis of the
provisional data of the 2011 population census. In addition, we also calculate and present the
conventional indicators of the demographic situation like population density, population sex
ratio, etc.
Finally, a word about units of measurement. We measure all indicators of extensiveness per 1000
population whereas all indicators of intensiveness are measured in terms of absolute ratios so that
the indicators of distribution are presented in the unit of 1000 throughout this monograph.
14
2
Population Size and Growth
The provisional figures released by the Registrar General and Census Commissioner of India
suggest that the population of India was 1,210,193,422 persons at 00:00 hours of 1st March 2011.
This means that between 2001 and 2011, around 181.578 million people were added to the
population of the country enumerated at the 2001 population census. This also means that during
the 60 years between 1951 and 2011, more than 849 million people were added to the population
of the country enumerated at the 1951 population census. By comparison, between 1901 and
1951, the net addition to the population of the country was only around 122 million.
In terms of proportions, India’s population increased by 17.653 per cent in the ten-year period
since the 2001 population census. The corresponding increase during the period 1991-2001 was
21.353 per cent which suggests that population increase in the country has continued to slow
down after attaining the highest proportionate increase of 24.80 per cent during the period 196171. The preliminary figures of the 2011 population census also suggest that the slow down in the
population increase in the country has gained momentum during the period 2001-2011. This is
a welcome finding of the 2011 population census. This slow down in population growth has
resulted in a decrease in the net addition to the population of the country decreased, although the
decrease has been marginal. This is for the first time that the net decadal increase in the
population has decreased in the country. During the period 1991-2001, the net addition to the
population of the country was around 182.312 million whereas, during the period 2001-2011, the
net addition to the population of the country was around 181.578 million (Table 2.1). As a result,
the average annual population growth rate in the country decreased from 1.935 per cent during
the period 1991-2001 to 1.626 per cent during the period 2001-2011.
15
Preliminary Demography of India
Year
Table 2.1
Population size and growth in India 1901-2011.
Population
(million)
Decadal change in population
(million)
1901
1911
1921
1931
1941
1951
1961
1971
1981
1991
2001
2011
Source:
238.396
252.093
251.321
278.977
318.661
361.088
439.235
548.160
683.329
846.303
1028.615
1210.193
13.697
-0.772
27.656
39.684
42.427
78.147
108.925
135.169
162.974
182.312
181.578
(per cent)
5.75
-0.31
11.00
14.22
13.31
21.64
24.80
24.66
23.85
21.54
17.65
Average
annual growth
rate
(per cent)
0.56
-0.03
1.04
1.33
1.25
1.96
2.22
2.20
2.14
1.95
1.63
Census reports
The decrease in the net addition to the population is perhaps the most remarkable feature of
population transition in India during the period 2001-2011. If the average annual population
growth rate in the country during the period 2001-2011 would have been the same as the average
annual population growth rate during the period 1991-2001, the population of the country would
have increased to around 1246.315 million by the year 2011and the net addition to the population
of the country during the period 2001-2011would have been almost 218 million - 56 million
more than the actual addition to the population during the period 2001-2011 as revealed through
provisional figures of the 2011 population census.
A notable feature of the provisional population figures of the 2011 population census is that they
are very close to the population projected by the Government of India for the period 2001-2011
on the basis of the results of the 2001 population census. Government of India had projected that
the population of the country will increase to 1,192,506 thousand by the year 2011 (Government
of India, 2006). Similarly, United Nations has projected that India’s population would increase
to more than 1214 million by the year 2010 (United Nations, 2011). The provisional population
figures of the 2011 population census suggest that the enumerated population of the country
exceeded the projected population by almost 18 million. During the period 1991-2001, the
enumerated population of the country exceeded the projected population by around 16 million
16
Population Size and Growth
Figure 2.1
Population (million) growth in India 1901-2001
whereas, the enumerated population exceeded the projected population by less than 9 million
during the period 1981-91 (Chaurasia and Gulati, 2008). According to the population projections
of the Government of India, the population of the country should have grown by around 1.48 per
cent per year during the period 2001-2011 which is lower than the actual average annual
population growth rate of almost 1.63 per cent during the period 2001-2011. In other words,
provisional figures of the 2011 population census suggest that the demographic transition in the
country during the period 2001-2011 has been slower than the projected one. Population
projections prepared by the Government of India are based on the assumption that the
replacement fertility will be achieved in the country by the year 2021 - not by the year 2010 as
aimed in the National Population Policy 2000 - and the total fertility rate will decline to 2.6 births
per woman of reproductive age by the year 2010. However, the average annual population growth
rate during the period 2001-2011 derived from the provisional figures of the 2011 population
census suggests that the decrease in fertility in the country has been slower than the projected one
17
Preliminary Demography of India
which means that the country will not be able to achieve replacement fertility even by the year
2021. In other words, there is only a distant possibility of achieving stable population by the year
2045 as stipulated in National Population Policy 2000. This is one of the disheartening findings
of the 2011 population census. If the actual population growth in the country would have
followed the projected path, the decrease in the net addition to the population would have been
even more substantial.
The outstanding feature of the population growth in India, however, is not the rate of growth but
the size of the population to which growth accrues. The net addition to the population of the
country during the period 2001-11 is almost the same as the population of Brazil in 2005. Brazil,
incidently, is the fifth most populous country of the world (United Nations, 2011). Between 1951
and 2001, more than 849 million people have been added to 361 million people enumerated at
the 1951 population census while almost 972 million people have been added to the population
of the country since 1901. Clearly, despite the moderately high population growth rate, India is
adding huge numbers year after year putting enormous pressure on its limited resources to meet
the survival and development needs of its people.
Population Size and Growth in States/Union Territories
Regional diversity in the growth of population in India is well known and this diversity has
persisted over time. Any discussion about the size and the growth of India’s population,
therefore, is incomplete without a discussion on differences in the size and the growth of the
population across the constituent states and Union Territories of the country. The provisional
results of the 2011 population census provide information on population size and growth for the
29 states and 6 Union Territories of the country. This information is summarised in table 2.2
which includes data on population for the year 2001 and 2011 and estimates of the indicators of
population growth - the proportionate increase in the population and average annual population
growth rate for the period 2001-11.
Since the size of the population of different states and Union Territories of the country varies
widely, population growth in different states and Union Territories of the country has contributed
differently to the growth of the population of the country as a whole. Because of the varying
population size, it is customary to group the states and Union Territories of the country into three
broad categories; major states (states with a population of at least 25 million at the 2011 census),
small states (states with a population of less than 25 million at the 2011 census), and Union
Territories. According to the 2011 population census, there were 17 states in the country with a
population of 25 million and more while the population of 12 states was less than 25 million. In
18
Population Size and Growth
addition, there are 6 Union Territories in the country all of which had a population of less than
25 million. Provisional results of the 2011 population census suggest that the 17 major states of
the country account for almost 95 per cent of the population of the country while the 12 small
states accounted for only about 5 per cent of the country’s population. Union Territories, on the
other hand, account for less than 0.3 per cent of the population of the country. Trends and
patterns of population growth in India, therefore, are primarily determined by the trends and
patterns of the population growth in the 17 major states of the country. The contribution of small
states and Union Territories to the growth of the population of the country has always been
insignificant, although trends and patterns of population growth in small states and Union
Territories are themselves an important area of interest and analysis.
According to the provisional figures of the 2011 population census, Uttar Pradesh, with a
population of almost 200 million, continues to be the most populous state of India followed by
Maharashtra and Bihar both of which have a population of more than 100 million. On the other
hand, Haryana, with a population of around 25 million has the smallest population among the
major states of the country. Other major states with a population less than 30 million at the 2011
population census are Punjab and Chhattisgarh. The total population of the 17 major states was
almost 1145 million or 94.6 percent of the population of the country. Interestingly, this
proportion has decreased during 2001-2011, although the decrease has been marginal.
Among smaller states of the country, Delhi is the most populous one with a population of almost
17 million whereas Sikkim, with a population of less than 0.61 million is the least populated one.
In addition to Delhi, there are only two small states - Jammu and Kashmir and Uttarakhand which had a population of more than 10 million at the 2011 population census. The total
population of these 12 states was around 62 million. Unlike the major states of the country, the
proportion of the population of these states to the total population of the country has increased
during the period 2001-2011.
Finally, the six Union Territories of the country had a population of more than 3.3 million at the
2011 population census with the Union Territory of Puducherry having a population of more than
1.2 million being the most populous one. In addition to Puducherry, Chandigarh is the only other
Union Territory of the country with more than 1 million population. Rest of the Union Territories
had a population of less than 0.50 million with the Union Territory of Lakshadweep being the
smallest state/Union territory of the country in terms of population size. Like the smaller states
of the country, the proportion of the population of the Union Territories to the total population
of the country has also increased during the period 2001-2011.
19
Country/State
India
Major States
Uttar Pradesh
Maharashtra
Bihar
West Bengal
Andhra Pradesh
Madhya Pradesh
Tamil Nadu
Rajasthan
Karnataka
Gujarat
Orissa
Kerala
Jharkhand
Assam
Punjab
Chhattisgarh
Haryana
Small States
Delhi
Jammu and Kashmir
Uttarakhand
Himachal Pradesh
Table 2.2
Population size and growth in India, states and Union Territories, 1991-2001
Population (million)
Population growth
1991
2001
2011
Absolute (million)
Percent
1991-2001 2001-2011 1991-2001
2001-11
2001-11 (P)
846.303
1028.737
1210.193
182.434
181.456
21.56
17.64
15.93
132.062
78.937
64.531
68.078
66.508
48.566
55.859
44.006
44.977
41.310
31.660
29.099
21.844
22.414
20.282
17.615
16.464
166.198
96.879
82.999
80.176
76.210
60.348
62.406
56.507
52.851
50.671
36.805
31.841
26.946
26.656
24.359
20.834
21.145
199.581
112.373
103.805
91.348
84.666
72.598
72.139
68.621
61.131
60.384
41.947
33.388
32.966
31.169
27.704
25.540
25.353
34.136
17.942
18.468
12.098
9.702
11.782
6.547
12.501
7.874
9.361
5.145
2.742
5.102
4.242
4.077
3.219
4.681
33.383
15.494
20.806
11.172
8.456
12.250
9.733
12.114
8.280
9.713
5.142
1.547
6.020
4.513
3.345
4.706
4.208
25.85
22.73
28.62
17.77
14.59
24.26
11.72
28.41
17.51
22.66
16.25
9.42
23.36
18.93
20.10
18.27
28.43
20.09
15.99
25.07
13.93
11.10
20.30
15.60
21.44
15.67
19.17
13.97
4.86
22.34
16.93
13.73
22.59
19.90
20.80
16.29
17.74
11.63
11.19
19.64
8.07
20.04
12.43
16.48
10.72
8.55
16.80
14.68
13.63
16.44
20.31
9.421
7.719
7.051
5.171
13.851
10.144
8.489
6.078
16.753
12.549
10.117
6.857
4.430
2.425
1.438
0.907
2.902
2.405
1.628
0.779
47.02
31.42
20.39
17.54
20.95
23.71
19.18
12.82
33.22
15.52
17.12
11.77
20
Country/State
Population (million)
1991
2001
2011
Tripura
Meghalaya
Manipur
Nagaland
Goa
Arunachal Pradesh
Mizoram
Sikkim
Union Territories
Puducherry
Chandigarh
Andaman and Nikobar
Dadra and Nagar Haveli
Daman and Diu
Lakshadweep
2.757
1.775
1.837
1.210
1.170
0.865
0.690
0.406
3.199
2.319
2.294
1.990
1.348
1.098
0.889
0.541
3.671
2.964
2.722
1.981
1.458
1.383
1.091
0.608
0.808
0.642
0.281
0.138
0.102
0.052
0.974
0.901
0.356
0.220
0.158
0.061
1.244
1.055
0.380
0.343
0.243
0.064
Source:
Population growth
Absolute (million)
Percent
1991-2001 2001-2011 1991-2001
2001-11
2001-11 (P)
0.442
0.472
16.03
14.75
13.03
0.544
0.645
30.65
27.81
13.03
0.457
0.428
24.88
18.66
13.02
0.780
-0.009
64.46
-0.45
13.01
0.178
0.110
15.21
8.16
31.12
0.233
0.285
26.94
25.96
13.03
0.199
0.202
28.84
22.72
12.99
0.135
0.067
33.25
12.38
13.16
0.166
0.259
0.075
0.082
0.056
0.009
Author’s calculations
21
0.270
0.154
0.024
0.123
0.085
0.003
20.54
40.34
26.69
59.42
54.90
17.31
27.72
17.09
6.74
55.91
53.80
4.92
42.76
59.67
38.70
60.55
70.67
25.31
Preliminary Demography of India
Figure 2.2
Population growth in states/Union Territories
Among the major states of the country, the population growth has been the most rapid in Bihar
followed by Chhattisgarh and Jharkhand. These are the only three major states where the average
annual population growth rate of more than 2 per cent per year was estimated. These three states
constitute a geographical continuity. The average annual population growth rate has also been
more than 2 per cent in Jammu and Kashmir, Meghalaya, Manipur, Arunachal Pradesh and
Mizoram during the period under reference. Four of these five states are located in the northeastern part of the country. These states are small states and the rapid population growth in these
states has only a minor impact on the population growth in the country as a whole.
22
Population Size and Growth
Table 2.3
Average annual population growth rate in India and states/Union Territories
Country/State
Average annual growth rate (Per cent)
1991-2001
2001-2011
2001-2011(P)
India
1.951
1.624
1.478
Major States
Uttar Pradesh
2.299
1.83
1.890
Maharashtra
2.048
1.484
1.509
Bihar
2.517
2.237
1.633
West Bengal
1.636
1.304
1.100
Andhra Pradesh
1.362
1.052
1.060
Madhya Pradesh
2.172
1.848
1.793
Tamil Nadu
1.108
1.449
0.776
Rajasthan
2.500
1.942
1.826
Karnataka
1.613
1.455
1.171
Gujarat
2.042
1.754
1.525
Orissa
1.506
1.308
1.018
Kerala
0.901
0.474
0.820
Jharkhand
2.099
2.017
1.553
Assam
1.733
1.564
1.370
Punjab
1.832
1.287
1.277
Chhattisgarh
1.678
2.037
1.522
Haryana
2.502
1.815
1.849
Small States
Delhi
3.854
1.903
2.868
Jammu and Kashmir
2.732
2.128
1.443
Uttarakhand
1.856
1.754
1.581
Himachal Pradesh
1.616
1.205
1.112
Tripura
1.488
1.376
1.225
Meghalaya
2.673
2.455
1.225
Manipur
1.651
1.71
1.224
Nagaland
4.975
-0.048
1.223
Goa
1.414
0.785
2.709
Arunachal Pradesh
2.385
2.305
1.225
Mizoram
2.529
2.052
1.221
Sikkim
2.868
1.165
1.236
Union Territories
Puducherry
1.872
2.447
3.560
Chandigarh
3.385
1.579
4.679
Andaman and Nikobar
2.370
0.647
3.272
Dadra and Nagar Haveli
4.686
4.414
4.734
Daman and Diu
4.389
4.288
5.345
Lakshadweep
1.539
0.604
2.256
Source:
Author’s calculations
23
Preliminary Demography of India
Figure 2.3
Average annual population growth rate (per cent) during 2001-2011
in states and Union Territories
24
Population Size and Growth
Provisional results of the 2011 population census suggest that population growth has also been
quite rapid in Rajasthan, Madhya Pradesh, Uttar Pradesh and Haryana. In these states, population
increased at an average annual growth rate of more than 1.8 per cent per year during the period
under reference which is well above the population growth rate of the country as a whole. All
these states are the major states of the country and, along with Bihar, Chhattisgarh and
Jharkhand, these states accounted for more than 93 million of the 181 million or more than 50
per cent increase in the population of the country during the period 2001-2011.
On the other hand, Nagaland is the only state in the country which has recorded a negative
population growth during the period under reference. During the period 1991-2001, the
population of Nagaland increased by a whopping 64.5 million but, during 2001-2011, the
population of the state decreased by a small number. This appears to be a very conspicuous
finding of the provisional results of the 2011 population census. Moreover, there are only two
states - Kerala and Goa - and two Union Territories - Andaman and Nikobar and Lakshadweep where the average annual growth rate during 2001-2011 is estimated to be less than 1 per cent.
Another encouraging feature of the provisional results of the 2011 population census is that the
growth in population has slowed down in all but three states and Union Territories of the country
during the period 2001-2011 as compared to the period 1991-2001 (Table 2.3). The three states
where the average annual population growth rate appears to have increased during the period
2001-2011 compared to the period 1991-2001 are Tamil Nadu, Chhattisgarh and Manipur.
Among these states, Tamil Nadu recorded a very low growth rate during the period 1991-2001
whereas the growth rate in Chhattisgarh and Manipur was more than 2 per cent per year. It
appears that rapid population growth situation has continued in these two states during the period
2001-2011 also.
The situation is however not so encouraging when the population growth estimated on the basis
of provisional figures of the 2011 population census is compared with the projected population
growth based on the projected population for the year 2011. This comparison suggests that in 20
states and Union Territories of the country, the actual population growth has been faster than the
projected population growth rate with the difference being the largest in Tamil Nadu followed
by Bihar among the major states of the country (Table 2.3). In these states and Union Territories,
actual population transition during the period 2001-2011 has been slower than the projected one.
At the same time, in 9 out the 12 small states, the actual population growth rate based on the
provisional figures of the 2011 population census has been faster than the project one whereas
in all Union Territories of the country, the actual population growth during 2001-2011 has been
25
Preliminary Demography of India
Figure 2.4
Average annual population growth rate 1991-2001 and 2001-2011
slower than the projected one. This comparison suggests that the pace of population transition
in the country during the period 2001-2011 has been slower than what was projected or expected.
Obviously, the population transition scenario in the country and in most of the states, as revealed
through the provisional figures of the 2011 population census, does not appear to be very
encouraging. It is obvious from the table 2.3 that the country has missed the projected target of
an average annual population growth rate for the period 2001-2011, set on the basis of the results
of the 2001 population census. This means that the country will take more time to achieve the
goal of population stabilisation.
There has been considerable variation in population growth rates across the states/Union
Territories with acceleration in some states and Union Territories during 2001-2011 as compared
to 1991-2001 and slowdown in others. This is shown in figure 2.4 which compares the average
population growth rate registered in 1991-2001 with the average population growth registered
in 2001-2011. Deviation from the 45-degree line indicates the extent of change in the average
annual population growth rate between 1991-2001 and 2001-2011. Most of the states fall very
close to the 45-degree line. The deviation from the line is marked in Andaman and Nikobar,
Sikkim, Chandigarh, Delhi and Nagaland and in Tamil Nadu, Chhattisgarh, Manipur and
Puducherry. In the first group of states and Union Territories, average annual population growth
26
Population Size and Growth
rate has slowed down during the period 2001-2011 as compared to the average annual growth
rate during 1991-2001 with the change in the average annual population growth rate being the
most typical in Nagaland. In the second group of states and Union Territories, it has accelerated.
In other states, the average annual population growth rate registered during the period 2001-2011
is very close to that predicted on the basis of the average annual population growth rate recorded
during the period 1991-2001. This suggests that, although, the population growth rate in the
states and Union Territories of the country has shown a decline on the basis of the provisional
results of the 2011 population census, this decline appears to be, at best, a normal pattern in most
of the states and Union Territories. There are only a few marked deviations.
Provisional results of the 2011 population census also suggest that more than 45 per cent increase
in the population of the country during the decade 2001-2011 has been confined to only five
states - Uttar Pradesh, Bihar, Madhya Pradesh, Rajasthan, Jharkhand and Chhattisgarh. These
states accounted for around 40 per cent of the population of the country at the 2001 population
census but very close to 50 per cent of the increase in the population of the country during the
period 2001-2011. As the result, these states now account for almost 42 per cent of the
population of the country which indicates that an increasing proportion of population of the
country is getting concentrated in these states. The contribution of these states to the total
increase in the population of the country as a whole during 2001-2011 has been larger than that
at the 2001population census. This contribution has also increased in Haryana, Delhi, Jammu and
Kashmir, Uttarakhand, Meghalaya, Manipur, Arunachal Pradesh, Puducherry, Mizoram, Dadra
and Nagar Haveli, and Daman and Diu which indicates an increase in the concentration of
population in these states/Union Territories. However, these states/Union Territories contribute
only a small proportion to the population of the country.
Alternative Estimates of Population Growth
It is possible to have alternative estimates of population growth in the country during the period
2001-2011 on the basis of the information about birth and death rates available through the
sample registration system (SRS) and on the assumption that net migration at the national level
is an insignificant proportion to the natural increase in the population. Using the population
enumerated at the 2001 population census and estimates of the birth rate and the death rate
available through the sample registration system, it is possible to estimate the increase in the
population for different years of the period 2001-2011 as a result of the difference in the birth rate
and the death rate. This annual increase in population provides an alternative estimate of the
population in 2011 under the assumption that net international migration in the country
constitutes an insignificant proportion of the natural increase.
27
Preliminary Demography of India
There are two problems in the application of the above approach to arrive at the estimates of
population growth in the country during the period 2001-2011. The first problem is that the
estimates of the birth rate and the death rate from the sample registration system are available up
to the year 2009 only. The second problem is associated with the omission rate at the 2001
population census and under reporting of births and deaths in the sample registration system for
which adjustments need to be made.
Table 2.4
Alternative estimates of population (million) in India 2011.
Adjustments in SRS estimates
No adjustments in the estimates of the birth rate
and the death rate
Adjustment in the birth rate but no adjustment in
the death rate
Adjustments as per Bhat (2002)
Source:
Adjustment in the 2001 census count
due to omission
No adjustment
Adjusted for the
omission rate
1206.535
1217.949
1211.666
1222.724
1218.587
1229.167
Author’s calculations
As regards the omission rate at the 2001 population census, the post enumeration survey
conducted by the Registrar General of India has revealed a net omission rate of 23.3 per 1000
population (Government of India, 2006). This means that the population in 2001 needs to be
inflated by 2.33 per cent which means that India’s population in 2001 was around 1053 million
and not 1029 million. On the other hand, estimates of the birth rate and the death rate obtained
from the system are generally believed to be quite accurate. An investigation conducted in 198081 suggested an omission rate of 3.1 per cent at all India level in case of births (Government of
India, 1983) which decreased to 1.8 per cent in 1985 (Government of India, 1988) whereas
another inquiry conducted in 1991 suggested that deaths in the system have marginally been over
reported (Swamy et al, 1992). On the other hand, Bhat (2002) has estimated that births in the
sample registration system are under reported by about 7 per cent while deaths by around 8-9 per
cent through a different approach.
We have estimated birth rate and death rate for 2009 and 2010 on the basis of linear regression
of birth and death rates obtained from the sample registration system on time for the period 2001
through 2008. The regression exercise provided a very good fit with R2=0.99 in case of the birth
28
Population Size and Growth
rate and 0.85 in case of the death rate. We have also calculated the estimated population in the
year 2011 after making adjustments in the population of the country in 2001 for the estimated
net omission rate as well as for different estimates of under reporting in the birth rate and the
death rate available through the sample registration system.
Results of the estimation exercise are given in table 2.4. When no adjustment related to the
omission rate and under reporting of births and deaths in the sample registration system is made,
the estimated population for the year 2011 comes out to be marginally less than the enumerated
population of the 2011 population census. However, when adjustments in the birth rate and death
rate suggested by the Government of India are taken into consideration and when the population
enumerated at the 2001 population census is not adjusted for the net omission rate at the 2001
population census, the population of the country for the year 2011 is estimated to be 1211.7
million which is very close to the provisional population figures of the 2011 population census.
When adjustment for the net omission rate is made in the population enumerated at the 2001
population census, the population of the country is estimated to be more than 1222 million in the
year. Finally, when no adjustments are made in the birth rate, the 2011 population is estimated
to be 1207 million which suggests that there is some under reporting of births in the sample
registration system. It is obvious that when the net omission rate of the 2001 population census
and the under reporting of births and deaths in the sample registration system is taken into
account, there appears substantial under count at the 2011 population census. Finally, when the
estimates of under reporting of births and deaths in the sample registration system are taken into
consideration, the estimated population in the year 2011 is around 1229 million. Table 2.4
suggests that there is some under count of the population at the 2011 population census also,
although the magnitude of the under count does not appear to be substantial given the size of the
population of the country.
We have carried out a similar exercise for the states and Union Territories of the country.
Estimates of the birth rate and the death rate for the period 2001 through 2009 are available
through the sample registration system for 31 of the 35 states and Union Territories of the
country. The exceptions are Chhattisgarh, Jharkhand, Nagaland and Uttarakhand for which
annual estimates of the birth rate and the death rate are available for the period 2004 through
2009 only. We have estimated the birth rate and the death rate for those years of the period 20012010 for which direct estimates of these rates are not available the sample registration system by
assuming a linear time trend in the two rates and then used the enumerated population at the 2001
population census to estimate the population in 2011. We have carried out this exercise for all
the 35 states and Union Territories of the country.
29
Preliminary Demography of India
Table 2.5
Enumerated and estimated population of states and Union Territories, 2011
State
Uttar Pradesh
Rajasthan
Kerala
Madhya Pradesh
Andhra Pradesh
Assam
Nagaland
Bihar
Andaman and Nikobar
Sikkim
Lakshadweep
Himachal Pradesh
Goa
Chandigarh
Orissa
Daman and Diu
Dadra and Nagar Haveli
Haryana
Mizoram
Arunachal Pradesh
Tripura
Manipur
Puducherry
Meghalaya
Punjab
Chhattisgarh
Uttarakhand
Jharkhand
West Bengal
Karnataka
Gujarat
Delhi
Jammu and Kashmir
Maharashtra
Tamil Nadu
Source:
Population 2011
Enumerated
Estimated
(Million)
(Million)
199.582
206.417
68.621
70.473
33.388
34.863
72.598
73.996
84.666
85.927
31.169
31.454
1.981
2.253
103.805
103.965
0.38
0.401
0.608
0.625
0.064
0.068
6.857
6.855
1.458
1.447
1.055
1.017
41.947
41.904
0.243
0.182
0.343
0.278
25.353
25.281
1.091
1.010
1.383
1.296
3.671
3.544
2.722
2.553
1.244
1.072
2.964
2.768
27.704
27.406
25.54
25.213
10.117
9.766
32.966
32.591
91.348
90.864
61.131
60.605
60.384
59.847
16.753
15.934
12.549
11.600
112.373
109.480
72.139
68.728
Author’s calculations
30
Difference
Absolute
Per cent
(Million)
-6.835
-3.425
-1.852
-2.699
-1.475
-4.418
-1.399
-1.927
-1.261
-1.489
-0.285
-0.914
-0.273
-13.781
-0.16
-0.154
-0.021
-5.526
-0.018
-2.961
-0.004
-6.250
0.001
0.015
0.011
0.754
0.038
3.602
0.044
0.105
0.061
25.103
0.065
18.950
0.072
0.284
0.081
7.424
0.087
6.291
0.127
3.460
0.169
6.209
0.172
13.826
0.196
6.613
0.298
1.076
0.327
1.280
0.351
3.469
0.375
1.138
0.484
0.530
0.526
0.860
0.537
0.889
0.82
4.895
0.949
7.562
2.893
2.574
3.411
4.728
Population Size and Growth
Results of the exercise are presented in table 2.5. In some states of the country, the estimated
population for the year 2011 has been found to be larger than the population enumerated at the
2011 population census while in others the estimated population is found to be less than the
enumerated population. Uttar Pradesh tops the list in terms of the difference between the
enumerated and estimated population for the year 2011. The enumerated population in Uttar
Pradesh has been found to be almost 7 million less than the estimated population in the year
2011. On the other hand, in Tamil Nadu, the enumerated population has been found to be almost
3.5 million more than the estimated population whereas in Maharashtra, the enumerated
population has been found to be almost 3 million more than the estimated population. In Dadra
and Nagar Haveli, Daman and Diu, and Puducherry, the difference between the enumerated and
the estimated population has been found to be very substantial. By contrast, in Bihar, Himachal
Pradesh, Goa and Orissa, the difference between the enumerated and the estimated population
has been found to be very small.
The difference between the enumerated population and the population estimated on the basis of
the annual estimates of the birth rate and the death rate derived from the sample registration
system in a state/Union Territory is a reflection of the movement of the population across the
states/Union territories of the country. In those states and Union territories where the enumerated
population is less than the estimated one, it appears that the population has moved out of the
state/Union Territory during the period 2001-2011. Similarly, in states/Union Territories where
the enumerated population is larger than the estimated one, it can be assumed that population has
moved into the state/Union Territory during this period. In this sense, it can be argued that there
has been movement of the people out of Uttar Pradesh, Rajasthan, Kerala and Madhya Pradesh
whereas in Tamil Nadu, Maharashtra, Jammu and Kashmir, Delhi, etc., there has been inward
movement of the people during the period 2001-2011. This assessment, of course, is based on
the assumption that the omission rate at the 2001 and the 2011 population census is almost the
same and the estimates of the birth rate and the death rate available through the sample
registration system reflect the prevailing levels of fertility and mortality in the country and in its
states and Union Territories. Another assumption associated with this assessment is that the net
international migration from the country is either zero or an insignificant proportion of the total
population of the country as has been the case here. In any case, a comparison of the enumerated
and the estimated population of the country and states/Union Territories suggests that inter-state
movement of the population in the country remains quite substantial for a host of factors and
conditions most of which are well known. More attention to this important aspect of the
population stock in the country and in its constituent states/Union Territories is discussed in
Chapter six of the monograph.
31
Preliminary Demography of India
Population Size and Growth in Districts
The provisional data of the 2011 population census also provide the population count in 640
districts of the country as they existed at the time of the 2011 population census. The population
of the districts enumerated at the 2011 population census is given in table 2.A along with the
population at the 2001 population census, the proportionate increase in population during 20012011 and the average annual population growth rate during this period. According to the
provisional figures of the 2011 population census, district Thane in Maharashtra is the most
populous district of the country with a population of more than 11 million. The only other district
having a population of more than 10 million at the 2011 population census is the Twenty Four
Parganas district in West Bengal. By contrast, district Dibang Valley in Arunachal Pradesh is the
least populated district in the country with a population of less than eight thousand.
In majority of the districts of the country, the population enumerated at the 2011 population
census ranges between 1-3 million. There are 195 districts where the enumerated population is
less than 1 million whereas in 57 districts, the population is enumerated to be 4 million and more
at the 2011 population census. There are however 21 districts in the country which can be termed
as very large districts in terms of the size of the population. In these districts, the population
enumerated at the 2011 population census was 5 million and more. Twelve out of these 21
districts are located in only two states of the country - West Bengal and Maharashtra.
Like the size of the population, the growth of the population during the period 2001-2011 has
also been found to vary widely across the districts of the country. The average annual population
growth rate has been found to be the most rapid in district Kurung Kumey of Arunachal Pradesh
where population increased at a rate of more than 7 per cent per year during the decade 20012011 resulting in a proportionate increase of more than 110 per cent between 2001 and 2011. In
all there are 23 districts in the country where population growth has been the fastest in the
country during the period 2001-2011. In these districts, population increased at an average annual
rate of more than 3 per cent per year during the period under reference. On the other hand, in 21
districts of the country, population growth has been negative during the period under reference
with the most rapid decrease in the population recorded in district Longleng of Nagaland where
the population decreased at an average annual rate of more than 11 per cent per year leading to
a proportionate decrease of more than 68 per cent according to the provisional figures of the 2011
population census. In six out of eleven districts in Nagaland, population growth has been
negative during the period 2001 through 2011. As a result, Nagaland is the only state/Union
Territory in the country where population, instead of increasing, decreased during the period
2001-2011.
32
Population Size and Growth
State
AN Islands
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chandigarh
Chhattisgarh
Dadra & Nagar Haveli
Daman and Diu
Delhi
Goa
Gujarat
Haryana
Himachal Pradesh
Jammu and Kashmir
Jharkhand
Karnataka
Kerala
Lakshadweep
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
Orissa
Puducherry
Punjab
Rajasthan
Sikkim
Tamil Nadu
Tripura
Uttar Pradesh
Uttarakhand
West Bengal
India
Source:
Table 2.6
Districts by population size, 2011
Population (million)
<1
1-2
2-3
3-4
3
0
0
0
0
0
7
6
16
0
0
0
12
14
1
0
3
10
10
9
0
1
0
0
8
6
2
1
1
0
0
0
2
0
0
0
3
1
4
1
2
0
0
0
4
7
10
2
6
15
0
0
11
1
0
0
18
4
0
0
8
11
5
0
2
20
6
0
1
4
4
4
1
0
0
0
10
31
8
1
1
12
9
5
9
0
0
0
7
0
0
0
8
0
0
0
11
0
0
0
10
14
5
1
4
0
0
0
10
5
4
1
2
17
9
4
4
0
0
0
3
13
7
8
3
1
0
0
2
22
14
19
10
3
0
0
0
2
2
5
195
214
107
67
30.5
33.4
16.7
10.5
Author’s calculations
33
$4
0
10
0
0
6
0
1
0
0
0
0
3
0
0
0
0
2
1
0
0
8
0
0
0
0
0
0
0
1
0
1
0
14
0
10
57
8.9
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Preliminary Demography of India
Table 2.7
Districts with the highest population growth rate
and districts with the negative population growth during 2001-2011
Districts with highest growth rate
Districts with negative population growth
State/Union
Territory
District
State/Union
Territory
District
Arunachal Pradesh
Kurung Kumey
Nagaland
Longleng
Puducherry
Yanam
Nagaland
Kiphire
Haryana
Gurgaon
Delhi
New Delhi
Daman & Diu
Daman
Nagaland
Mokochung
Dadra & Nagar
Haveli
Dadra and Nagar
Haveli
Andaman and
Nicobar Islands
Nicobars
Uttar Pradesh
Gautam Budh Nagar
Delhi
Central
Arunachal Pradesh
Upper Subansiri
Nagaland
Zunheboto
Arunachal Pradesh
Lower Subansiri
Maharashtra
Mumbai
Andhra Pradesh
Rangareddy
Himachal Pradesh
Lahul & Spiti
Karnataka
Bangalore
Maharashtra
Ratnagiri
Arunachal Pradesh
Papum Pare
Nagaland
Mon
Gujarat
Surat
Tamil Nadu
The Nilgiris
Meghalaya
South Garo Hills
Kerala
Pathanamthitta
Chhattisgarh
Kabeerdham
Maharashtra
Sindhdurg
Uttar Pradesh
Ghaziabad
Nagaland
Peren
Tamil Nadu
Kancheepurum
Kerala
Idduki
Haryana
Mewat
West Bengal
Kolkata
Jammu & Kashmir
Anantnag
Uttarakhand
Almora
Arunachal Pradesh
East Kameng
Uttarakhand
Garhwal
Mizoram
Mamit
Karnataka
Chikmanglur
Jammu and Kashmir
Ganderbal
Maharashtra
Thane
Andaman & Nicobar
Islands
North and Middle
Andaman
Tamil Nadu
Thiruvallur
Source:
Author’s calculations
34
Population Size and Growth
Figure 2.5
Distribution of districts across states by size of the population (million), 2011
In more than half of the districts of the country (55 per cent), average annual population growth
rate during the period 2001-2011 ranged between 1-2 per cent per year according to the
provisional figures of the 2011 population census whereas in 91 districts, the growth of the
population was on average less than 1 per cent per year. By comparison, there are 23 districts in
the country where the growth of population during the period 2001-2011 has been very rapid 3 per cent per year and higher. Out of these 23 districts, 5 are located in Arunachal Pradesh. In
Haryana, Jammu and Kashmir, Tamil Nadu and Uttar Pradesh, population growth has been very
rapid in two districts each.
35
Preliminary Demography of India
Figure 2.6
Distribution of districts across states by
average annual population growth rate (per cent), 2001-2011
In all, in 174 or more than 27 per cent districts of the country, population growth has been rapid
during the period 2001-2011 as the average annual population growth rate has been 2 per cent
per year and more, on average, in these districts according to the provisional results of the 2011
population census. By contrast, in 112 or about 18 per cent districts of the country, population
growth has been either negative or very slow, less than 1 per cent per year, on average, during
this period. In Kerala, in all but one district, the average annual population growth rate has been
less than 1 per cent per year during 2001-2011.
36
Population Size and Growth
Table 2.8
Districts by average annual population growth rate, 2001-2011
State
Average annual population growth rate (per cent)
<0
0-1
1-2
2-3
$3
Total
AN Islands
2
0
1
0
0
3
Andhra Pradesh
0
13
9
0
1
23
Arunachal Pradesh
0
4
6
1
5
16
Assam
0
4
20
3
0
27
Bihar
0
0
11
27
0
38
Chandigarh
0
0
1
0
0
1
Chhattisgarh
0
1
13
3
1
18
Dadra and Nagar Haveli
0
0
0
0
1
1
Daman and Diu
0
0
1
0
1
2
Delhi
2
0
4
3
0
9
Goa
0
2
0
0
0
2
Gujarat
0
4
17
4
1
26
Haryana
0
1
15
3
2
21
Himachal Pradesh
1
2
9
0
0
12
Jammu and Kashmir
0
1
8
11
2
22
Jharkhand
0
0
9
15
0
24
Karnataka
1
14
12
2
1
30
Kerala
2
11
1
0
0
14
Lakshadweep
0
1
0
0
0
1
Madhya Pradesh
0
0
34
16
0
50
Maharashtra
3
9
18
4
1
35
Manipur
0
0
6
3
0
9
Meghalaya
0
0
0
6
1
7
Mizoram
0
0
4
3
1
8
Nagaland
6
2
0
3
0
11
Orissa
0
2
27
1
0
30
Puducherry
0
0
2
1
1
4
Punjab
0
5
14
1
0
20
Rajasthan
0
1
18
14
0
33
Sikkim
0
1
3
0
0
4
Tamil Nadu
1
6
22
1
2
32
Tripura
0
0
3
1
0
4
Uttar Pradesh
0
1
48
20
2
71
Uttarakhand
2
5
2
4
0
13
West Bengal
1
1
16
1
0
19
India
21
91
354
151
23
640
3.3
14.2
55.3
23.7
3.6
100.0
Source:
Population census 2011.
37
Preliminary Demography of India
Figure 2.7
Average annual population growth rate (per cent) in districts, 2011
38
Population Size and Growth
The growth of population is influenced by both the natural increase in the population resulting
from the difference in the birth rate and the death rate and the net migration rate. Provisional
figures of the 2011 population census do not provide data necessary to estimate the birth rate and
the death rate as well as migration rate during the period 2001-2011 to analyse further the factors
responsible especially for very rapid population growth in some of the districts of the country and
negative population growth in other districts. However, some speculative analysis may still be
carried out on the basis of the provisional figures of the 2011 population census.
Among the 23 districts of the country where the average annual population growth rate has been
more than 3 per cent per year during the period 2001-2011, seven districts are either metropolitan
districts or districts adjoining metropolitan districts. These are Bangalore in Karnataka, Thane
in Maharashtra which is next to Mumbai, Rangareddy in Andhra Pradesh which is adjacent to
Hyderabad, Gurgaon in Haryana and Gautam Budh Nagar and Ghaziabad in Uttar Pradesh which
are adjacent to Delhi. In addition, district Surat in Gujarat is a very highly industrialised district
while district Mewat adjoins district Faridabad, a highly industrialised district in Haryana which
also adjoins Delhi. Except one or two exceptions, these districts are also highly industrialised and
hence urbanised districts. As such, it appears that the rapid population growth witnessed in these
districts during the period between 2001 and 2011 is largely due to heavy to very heavy inmigration of the working age population to these districts in search of better employment and
livelihood opportunities. Being highly industrialised and urbanised, there is little possibility that
rapid population growth in these districts is the result of a rapid natural increase in population
resulting from the high birth rate and the high death rate. In-migration, on a large scale, to these
districts appears to be the primary reason for the observed rapid population growth in these
districts.
On the other hand, population growth has also been very rapid in seven districts in the northeastern region of the country. Out of these seven districts, five - East Kameng, Papum Pare,
Lower Subansiri, Upper Subansiri and Kurung Kumey - are in Arunachal Pradesh while the sixth
- Mamit - is in Mizoram and the seventh - South Garo Hills - is in Meghalaya. These districts are
amongst the least developed districts of the country. It appears, that rapid population growth
witnessed in these districts is largely due to a rapid natural increase in population resulting from
the high birth rate and the high death rate.
Other districts where rapid population growth has been recorded during the period 2001-2011 Thiruvallur and Kancheepuram in Tamil Nadu, Kabeerdham in Chhattisgarh, Dadra and Nagar
Haveli, Daman in the Union Territory of Daman and Diu, and Ganderbal and Anantnag in
39
Preliminary Demography of India
Jammu and Kashmir - both natural increase conditions and the large scale in-migration may be
responsible for the rapid population growth that has been witnessed during the period 2001-2011.
At present very little is known about the reasons behind very rapid population growth in these
districts. Once detailed data from the 2011 population census are available, it would be possible
to analyse, in detail, the factors that have contributed to the rapid population growth in these
districts.
40
3
Population Distribution
The administrative divisions of India - states, Union Territories and districts within states and
Union Territories - vary widely in terms of both the size of the population and the geographic
area. As such, the distribution of the population across administrative units is not even but is
dense in some administrative areas and sparse in others. This uneven distribution of population
across administrative divisions of the country is a result of a range of factors. First, the
administrative divisions - state or Union Territory or district or even a village - do not have the
same geographical area. Second, within an administrative unit, such environmental factors as
mountains and deserts, etc. affect the distribution of the population. Similarly, factors associated
with social and economic development processes like industrialisation and urbanisation as well
as factors like the productivity of the land, also influence the distribution of population across
the administrative units.
The most commonly used indicator of analysing the distribution of the population is the
population density which is defined as the number of inhabitants per unit area. If all
administrative units within a country have the same area, then variation in the population density
across administrative units is the same as the variation in population across administrative units.
When area varies across the administrative units, variation in population density reflects both,
variation in the size of the population and variation in the area across the administrative units.
Population density, therefore, is not a good indicator of population distribution as it is influenced
by both the population as well as area of the administrative unit. Another problem with the
population density as a measure of population distribution is that it does not have additive and
multiplicative properties.
41
Preliminary Demography of India
Population density of a district d is nothing but the population of the district d with respect to the
area of the district d. If X denotes the population density, then following the approach outlined
in Chapter 1, we have the following measures of population distribution
Ddc(x) = (Pd/Pc )*log (Xd/Xc)
= Edc*Idc(x) œ d0c.
(3.1)
Similarly,
Dds(x) = Eds*Ids(x) œ d0s, and
(3.2)
Dsc(x) = Esc*Isc(x) œ s0c.
(3.3)
Finally, we define the index of distribution of the population in the country as a whole as
Dcd(x) = 3Ddc(x).
(3.4)
Similarly, we may also define
Dsd(x) = 3Dds(x), and
(3.5)
Dcs(x) = 3Dsc(x).
(3.6)
It is now easy to show that
Dcd(x) = 3Esc*Dsd(x) + 3Eds*Dcs(x).
(3.7)
It is obvious that if all the districts of the country have the same ratio of the population to the area
as the ratio of the population to the area for the country as a whole, Dcd(x) = 0. Moreover, the
index Dcd(x) is independent of the unit of measurement of the population or the area as it is based
on ratios not absolute values.
The advantage of using the index Dcd(x) to measure the distribution of population across
administrative units should be obvious. The index Dcd(x) is logically related to the index Dsd(x)
and the index Dcs(x). Population density does not have this property as it does not take into
account the variability in population distribution within administrative units. It assumes that the
population is distributed uniformly across the area within the administrative unit. It is also clear
that Dcd(x) can be decomposed into within state/Union Territory and between states/Union
Territories components. The within state/Union Territory component is determined by the
distribution of the population across districts within the states/Union Territories whereas the
second component is determined by the distribution of the population across the states/Union
Territories within the country. It is obvious that if the population density of a district d as is the
same as the population density of the state/Union Territory as a whole, Dsd(x) = 0. Similarly, if
the population density of a state/Union Territory is the same as the population density of the
country as a whole is the same as the area of the state/Union Territory as proportion to the area
of the country, Dcs(x) = 0. The index Dcd(x) takes into account both the intensiveness and the
extensiveness of population at the district level.
42
Population Distribution
Population Distribution in India
For India as a whole, the population density is estimated to be 382 persons per square kilometre
according to the provisional figures of the 2011 population census. The corresponding figure at
the 2001 population census was 325 persons per square kilometre. Thus, there were, on average,
57 more persons inhabited in every square kilometre in the country at the 2011 population census
as compared to the corresponding number at the 2001 population census. India accounts for only
2.4 per cent of the world surface area of 135.79 million square kilometres whereas it supports and
sustains 17.5 per cent of the world population. Among the ten most populous countries of the
world, only Bangladesh has a population density higher than the population density in India
(Government of India, 2011). An increase in the density of the population implies an increase in
the pressure of the population on natural resources and environment through increased resources
demand and increase in the wastes generated. This is a cause of concern as it has implications
in the context of sustainable social and economic development.
On the other hand, the index of population distribution for the country as a whole, based on the
distribution of the population across the districts of the country, Dcd(x), is estimated to be around
195 according to the provisional figures of the 2011 population census. As discussed earlier, this
index is the weighted sum of the index of intensiveness, Idc(x), of all the 640 districts of the
country with weights being equal to the ratio of the population of the district to the population
of the country or the index of extensiveness, Edc. The index of population distribution Dcd(x)
reflects the variability in population distribution across the districts within the country. If all
districts have the same population density as the population density of the country as a whole,
then the Dcd(x) = 0 irrespective of the distribution of the population of the country across the
districts. The index Dcd(x) is a fuller measure of population distribution across the districts of the
country in the sense that it also takes into account the relative distribution of the population
across the districts.
It is possible to decompose the index Dcd(x) in to two components - distribution of the population
across the districts within the state/Union territory or the within state component and distribution
of the population across the states/Union Territories within the country or between states/Union
Territory component - according to equation 3.7. This decomposition exercise suggests that
variation in population distribution between states/Union Territories account for about 53 per
cent of the total variation in population distribution across the country whereas variation in
population distribution across districts within states/Union Territories account for about 47 per
cent of the total variation. This the variability in population distribution across the districts in the
country is almost equally divided into within and between state/Union Territory components.
43
Preliminary Demography of India
Population Distribution across States/Union Territories
The provisional figures of the 2011 population census suggest that the population density varies
widely across the states/Union Territories of the country. The National Capital Territory of Delhi
has the highest population density amongst the states/Union Territories of the country with
almost 11,300 persons living in 1 square kilometre of area, on average. On the other hand,
population density has been estimated to be the lowest in Arunachal Pradesh where only 17
persons were living in 1 square kilometre of area, on average, at the time of the 2011 population
census. Population density has also been found to be very high in the Union Territory of
Chandigarh (9252) and in Puducherry (2598), Daman and Diu (2169), Lakshadweep (2013) and
Dadra and Nagar Haveli (698) - all Union Territories with very small geographic area. Among
the major states of the country - states with a population of at least 25 million at the 2011
population census - population density has been found to be the highest in Bihar (1102) followed
by West Bengal (1029), Kerala (859) and Uttar Pradesh (828).
The distribution of the population at the state/Union Territory level can be analysed in two
context. The first context is how the population is distributed across districts within a
state/Union Territory. This context is measured by the index Dsd(x) which is defined by equation
(3.3). The second context, on the other hand, is how the population across states/Union
Territories is distributed within the country. This context is measured by the index Dcs(x) which
is defined by equation (3.4). The two indexes can be combined to arrive at the index Dcd(x)
according to the equation (3.7).
Values of the indexes Dsd(x) and Dcs(x) are given in table 3.1 along with the population density
in each state/Union territory of the country and the index Esc which reflects the proportionate
distribution of the population of the country across the states/Union Territories. and Isc(x). With
reference to the country as a whole, the index of population distribution has been found to be the
highest in Uttar Pradesh followed by Bihar, West Bengal and Delhi. The highest index of
population distribution in Uttar Pradesh is because of a very large value of the index Esc as the
state accounted for almost 16.5 per cent of the population of the country at the 2011 population
census. Similarly, Bihar accounted for almost 9 per cent of the population of the country because
of which the state has the second highest index of population distribution in the country. By
contrast, a very high index of population distribution in the National Capital Territory of Delhi
is mainly because of a very high index of the intensiveness of population as it accounts for less
than 1.4 per cent of the population of the country at the 2011 population census. The population
density in the National Capital Territory of Delhi is the highest in the country - more than 11,200
persons per square kilometre which is more than 10 times the population density in Uttar
44
Population Distribution
Pradesh. The exceptionally high population density in the National Capital Territory of Delhi is
however restricted to a very small population relative to the population of the country and
therefore the index of population distribution in Delhi is not the highest in the country. In Uttar
Pradesh, Bihar and West Bengal, on the other hand, population density is only moderately high,
yet the index of population distribution is amongst the highest in the country mainly because the
population of these states is very large relative to other states and Union Territories of the
country.
Population density has also been found to be high to very high in a number of Union Territories
of the country. However, the index of population distribution is not high in these Union
Territories because they have very low index of the extensiveness of population. These Union
Territories accounted for a very small proportion of the population of the country at the 2011
population census. As such, the concentration of the population or the intensiveness of
population in these Union Territories have a very small, almost insignificant impact on the index
of population distribution in the country as a whole.
By comparison, the index Dsc(x) has been found to be the lowest in Rajasthan followed by
Madhya Pradesh, although Arunachal Pradesh which has the lowest population density. In fact,
the index Ecs is very low in Arunachal Pradesh as the population of the state accounts for just
around 0.1 per cent of the population of the country whereas Ecs is comparatively large in
Rajasthan and Madhya Pradesh. Clearly, the ranking of states/Union Territories of the country
by the index Dsc(x) is different from the ranking by the population density. The reason is that the
index of population distribution incorporates the variation in population size across states/Union
Territories whereas population density does not incorporates the variation in the population size
across the states and Union Territories.
Table 3.1 also suggests that the index of population distribution, Dsc(x), is negative in 19
states/Union Territories which account for around 47 per cent of the population of the country.
A negative index of population distribution means that these states/Union Territories have a
lower population density than the national average. On the other hand, the index of population
distribution was positive in 16 states/Union Territories of the country which means that the
population density in these states/Union Territories is higher than the national average. These 16
states/Union Territories accounted for almost 53 per cent of the population of the country at the
2011 population census. As a result, the index of the population distribution is positive for the
country as a whole which means that majority of the population of the country is living in high
population density areas.
45
Preliminary Demography of India
Table 3.1
Indexes of population distribution in India and states/Union Territories, 2011
Country/State
Population
Esc(x)
Dsd(x)
Dsc(x)
Dcd(x)
density
Andaman and Nikobar
47
0.314
0.020
-0.285
-0.266
Andhra Pradesh
308
69.960
6.264
-6.499
-0.235
Arunachal Pradesh
17
1.142
0.143
-1.558
-1.414
Assam
398
25.756
2.254
0.478
2.732
Bihar
1049
85.775
2.951
37.690
40.641
Chandigarh
9252
0.872
0.000
1.207
1.207
Chhattisgarh
189
21.104
1.556
-6.437
-4.881
Dadra and Nagar Haveli
698
0.283
0.000
0.074
0.074
Daman and Diu
2169
0.201
0.004
0.152
0.156
Delhi
11282
13.843
1.882
20.366
22.248
Goa
394
1.205
0.009
0.017
0.026
Gujarat
308
49.896
7.085
-4.596
2.489
Haryana
530
20.950
0.451
2.994
3.446
Himachal Pradesh
123
5.666
1.259
-2.780
-1.521
Jammu and Kashmir
125
10.369
4.805
-5.034
-0.229
Jharkhand
414
27.240
1.488
0.966
2.453
Karnataka
319
50.513
6.943
-3.923
3.019
Kerala
863
27.589
1.252
9.787
11.038
Lakshadweep
2013
0.053
0.000
0.038
0.038
Madhya Pradesh
235
59.988
2.478
-12.555
-10.077
Maharashtra
365
92.855
18.819
-1.739
17.079
Manipur
122
2.249
0.784
-1.114
-0.330
Meghalaya
133
2.449
0.130
-1.124
-0.994
Mizoram
52
0.902
0.050
-0.781
-0.731
Nagaland
120
1.637
0.145
-0.819
-0.674
Orissa
269
34.662
2.544
-5.235
-2.690
Puducherry
2529
1.028
0.036
0.845
0.881
Punjab
550
22.892
0.584
3.645
4.229
Rajasthan
200
56.703
5.855
-15.872
-10.018
Sikkim
86
0.502
0.151
-0.326
-0.175
Tamil Nadu
556
59.609
6.482
9.763
16.244
Tripura
350
3.033
0.152
-0.113
0.039
Uttar Pradesh
829
164.917
6.619
55.599
62.219
Uttarakhand
189
8.360
1.623
-2.550
-0.927
West Bengal
1024
75.482
7.503
32.377
39.880
India
102.657
92.230
194.978
Source:
Remarks:
Author’s calculations
For the definition of the indexes, see text
46
Population Distribution
Figure 3.1
Population density (per square kilometre) in states, 2011
47
Preliminary Demography of India
Figure 3.2
Index of extensiveness of population distribution in states/Union Territories
48
Population Distribution
Figure 3.4
Index of population distribution in states/Union Territories, 2011
49
Preliminary Demography of India
On the other hand, the index of population distribution across districts within states/Union
Territories or the index Dsd(x) has been found to be the highest in Maharashtra (18.819) followed
by Gujarat (7.085) and Karnataka (6.943) which shows that the variability in the distribution of
population across districts is the highest in these states. By contrast, this index has been found
to be zero in Chandigarh, Dadra and Nagar Haveli and Lakshadweep as there is only one district
in these Union Territories and hence no variability in the distribution of population across
districts. Among the major states, the index has also been found to be very low, very close to
zero, in Haryana (0.451), Punjab (0.584), Kerala (1.252) and Chhattisgarh (1.556). In these states,
variability in the population distribution across the constituent districts is the lowest in the
country.
Combining the indexes Dsd(x) and Dcs(x), according to the equation (3.7) for each state and then
adding the values for all the states and Union Territories gives the index of population
distribution, Dcd(x) for the country. Table 3.1 gives the share of different states and Union
Territories to the index of population distribution, Dcd(x) for the country which reflects the
variability in the distribution of population across districts. It may be seen from the table, and as
already discussed, Uttar Pradesh accounts for the largest share of the index of population
distribution at the country level followed by Bihar, West Bengal and Delhi. Uttar Pradesh and
Bihar, alone, accounts for almost 53 per cent of the total variation in the distribution of the
population across the districts of the country. By comparison, the share of small states and Union
Territories to the index of population distribution for the country as a whole is very small mainly
because their population constitutes a small proportion of the population of the country.
Population Distribution across Districts
Estimates of the index of the population distribution, Ddc(x), index of extensiveness Edc(x) and
the index of intensiveness Idc(x) for each of the 640 districts of the country are presented in the
appendix table 3.A along with the estimates of population density and the share of the population
of the district to the population of the country for each district. In all, in around one third (209)
districts of the country, the population density has been estimated to be more than 600 persons
per square kilometre at the 2011 population census. More than half of these 209 districts, are
located in only five states of the country - Uttar Pradesh (59), Bihar (35), West Bengal (16),
Kerala (11) and Delhi (9). All the districts in the National Capital Territory of Delhi, 16 out of
19 districts in West Bengal, 35 out of 38 districts in Bihar and 11 out of 14 districts in Kerala had
a population density of more than 600 persons per square kilometre according to the provisional
figures of the 2011 population census. These states are the most densely population states of the
country.
50
Population Distribution
The population density has been found to be the highest in district Mumbai of Maharashtra where
more than 45 thousand people were found to be living, on average, in one square kilometre
according to the provisional figures of the 2011 population census. In addition to district
Mumbai, there are 10 more districts in the country where a population density of more than 10
thousand persons per square kilometre has been estimated on the basis of the provisional data of
the 2011 population census. These districts are, in order of the population density, North East
district (43091) and North West district (28087) in Delhi, Chennai in Tamil Nadu (26903),
Kolkata (24252) Central district (23147) and West district (22603) in Delhi, Hyderabad (18480),
Mumbai Suburban (17477) in Maharashtra and North (14973) and South (10935 districts of
Delhi. Moreover, the population density has been found to be exceptionally high in South West
and New Delhi districts of the National Capital Territory of Delhi and in Chandigarh where the
population living in one square kilometre ranged from 5000 to 10000 according to the
provisional population figures of the 2011 population census. In the National Capital Territory
of Delhi, the population density has been found to be more than 5000 persons per square
kilometres in 8 out of 9 districts. Even in the ninth district (East district) also, the population
density has been found to be very close to 4000 persons per square kilometre.
On the other hand, in 95 districts of the country, the population density has been found to be less
than 150 persons per square kilometre. These districts include 38 districts where the population
density has been found to be less than 50 persons per square kilometre according to the 2011
population census. District Dibang Valley in Arunachal Pradesh has the distinction of having the
lowest population density of just 1 person per square kilometre in the country. In Anjaw, Tirup
Upper Siang Valley districts of Arunachal Pradesh and in district Lahul and Spiti in Himachal
Pradesh, the population density has been estimated to be less than 5 persons per square kilometre
according to the provisional figures of the 2011 population census.
Out of the 95 districts of the country where the population density is estimated to be the lowest
in the country on the basis of the provisional figures of the 2011 population census, 61 or almost
one third districts are located in eight states - Arunachal Pradesh (16), Mizoram (8), Andaman
and Nicobar Islands (3), Nagaland (9), Chhattisgarh (8), Uttarakhand (7), Manipur (5) and
Meghalaya (5). In Andaman and Nicobar Islands, Arunachal Pradesh and Mizoram, population
density has been estimated to be less than 150 persons per square kilometre in all the districts.
In Nagaland, population density has been found to be less than 150 persons per square kilometre
in 9 out of 11 districts while in Meghalaya, very low population density is estimated in 5 out of
7 districts. All these states are located in the north-eastern part of the country which is full of
forests and mountains.
51
Preliminary Demography of India
Table 3.2
Districts by population density (per square kilometre), 2011
State/Union Territory
Population density
< 150
150-300 300-450 450-600
$ 600
AN Islands
3
0
0
0
0
Andhra Pradesh
0
11
7
4
1
Arunachal Pradesh
16
0
0
0
0
Assam
2
3
8
7
7
Bihar
1
0
0
2
35
Chandigarh
0
0
0
0
1
Chhattisgarh
8
6
4
0
0
Dadra and Nagar Haveli
0
0
0
0
1
Daman and Diu
0
0
0
0
2
Delhi
0
0
0
0
9
Goa
0
0
1
1
0
Gujarat
2
10
3
6
5
Haryana
0
0
4
7
10
Himachal Pradesh
4
5
3
0
0
Jammu and Kashmir
4
6
4
3
5
Jharkhand
0
7
7
3
7
Karnataka
2
15
11
1
1
Kerala
0
1
1
1
11
Lakshadweep
0
0
0
0
1
Madhya Pradesh
3
39
5
1
2
Maharashtra
1
18
10
2
4
Manipur
5
0
0
1
3
Meghalaya
5
2
0
0
0
Mizoram
8
0
0
0
0
Nagaland
9
1
1
0
0
Orissa
6
15
1
2
6
Puducherry
0
0
0
0
4
Punjab
0
0
8
7
5
Rajasthan
6
14
9
3
1
Sikkim
2
2
0
0
0
Tamil Nadu
0
1
13
6
12
Tripura
1
1
1
1
0
Uttar Pradesh
0
3
5
4
59
Uttarakhand
7
3
0
2
1
West Bengal
0
0
0
3
16
India
95
163
106
67
209
14.8
25.5
16.6
10.5
32.7
Source:
Author’s calculations
52
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Population Distribution
Figure 3.5
Population density in districts of India, 2011
53
Preliminary Demography of India
The distribution of districts according to indexes Edc(x), Idc(x), and Ddc(x) is given in tables 3.3,
3.4 and 3.5 respectively. The ten districts of the country which have the highest value of Ddc(x)
are, in order, Mumbai Suburban in Maharashtra, Bangalore in Karnataka, Chennai in Tamil
Nadu, North Twenty Four Parganas in West Bengal, Kolkata in West Bengal, North-West
District in Delhi, Hyderabad in Andhra Pradesh, Mumbai in Maharashtra, Thane in Maharashtra
and North-East District in Delhi. All these districts, except district North Twenty Four Parganas
in West Bengal, are metropolitan districts with almost cent per cent urban population. In seven
of these ten districts - Mumbai suburban, Chennai, Kolkata, North-West Delhi, Hyderabad,
Mumbai and North-East Delhi - very high value of Ddc(x) is primarily due to very high values of
the index of intensiveness in population distribution, Idc(x) whereas in Bangalore and North
Twenty Four Parganas districts, the very high value of the index of population distribution is
primarily due to very high value of the index of extensiveness, Edc(x), which is amongst the
highest in the country.
On the other hand, the lowest value of the index Ddc(x) has been estimated in district Kuchchh
in Gujarat. Other districts with lowest level of the index Ddc(x) are five districts of Rajasthan Barmer, Bikaner, Jodhpur in, Nagaur and Churu - three districts of Andhra Pradesh - Anantpur,
Mahbubnagar and Adilabad - and Surguja in Chhattisgarh. In these districts, interestingly, the
lowest index of population distribution is not because of the lowest levels of the index of
intensiveness of population distribution in the country but because of the fact that moderately low
levels of the index of intensiveness in population distribution in these districts are associated with
moderately high levels of the index of the extensiveness of population distribution so that the
product of the two is the lowest in the country. The index of the intensiveness of population
distribution has actually been found to be the lowest in six districts of Arunachal Pradesh Dibang Valley, Anjaw, Upper Siang, Upper Subansiri, West Kameng and West Siang - two
districts of Jammu and Kashmir - Leh and Kargil - and Lahul and Spiti in Himachal Pradesh and
North Sikkim in Sikkim. However, the index of the extensiveness of population distribution, Edc
in these districts is also amongst the lowest in the country so that the product of the two or the
index of population distribution, Ddc(x), is not the lowest in these districts. The index of
intensiveness of the population distribution, Idc(x), is actually a surrogate of the concentration of
the population in the district relative to the area but it does not take into consideration the size
of the population over which this intensity or concentration of the population prevails. The index
of population distribution, Ddc(x), on the other hand, takes into consideration both the
concentration of the population, measured in terms of the index Idc(x) and the size of the
population, measured in terms of the index of extensiveness, over which this concentration
prevails.
54
Population Distribution
State/Union Territory
AN Islands
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chandigarh
Chhattisgarh
Dadra and Nagar Haveli
Daman and Diu
Delhi
Goa
Gujarat
Haryana
Himachal Pradesh
Jammu and Kashmir
Jharkhand
Karnataka
Kerala
Lakshadweep
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
Orissa
Puducherry
Punjab
Rajasthan
Sikkim
Tamil Nadu
Tripura
Uttar Pradesh
Uttarakhand
West Bengal
India
Source:
Table 3.3
Districts by the index Edc, 2011
Edc
< 0.5
0.5-1.5
1.5-2.5
2.5-3.5
3
0
0
0
0
0
7
11
16
0
0
0
2
22
3
0
0
11
12
9
0
1
0
0
3
11
2
2
1
0
0
0
2
0
0
0
2
2
4
1
0
2
0
0
3
8
10
3
1
20
0
0
9
3
0
0
14
8
0
0
3
15
6
0
1
17
10
0
0
4
5
5
1
0
0
0
1
37
11
1
0
11
12
5
9
0
0
0
5
2
0
0
8
0
0
0
11
0
0
0
5
18
6
1
3
1
0
0
2
12
5
1
0
16
12
4
4
0
0
0
1
12
10
8
1
3
0
0
0
19
20
21
6
6
1
0
0
1
4
4
117
262
140
76
18.3
40.9
21.9
11.9
Author’s calculations
55
$3.5
0
5
0
0
6
0
0
0
0
0
0
2
0
0
0
0
2
0
0
0
7
0
0
0
0
0
0
0
1
0
1
0
11
0
10
45
7.0
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Preliminary Demography of India
Figure 3.6
Distribution of the index Edc across districts, 2011
56
Population Distribution
Table 3.4
Distribution of districts by the index Idc(x), 2011
State/Union Territory
Idc(x)
<-0.25 -0.25 to 0 0 to 0.25 0.25 to 0.50
AN Islands
3
0
0
0
Andhra Pradesh
5
9
8
0
Arunachal Pradesh
16
0
0
0
Assam
3
5
15
3
Bihar
1
0
3
20
Chandigarh
0
0
0
0
Chhattisgarh
12
4
2
0
Dadra and Nagar Haveli
0
0
0
1
Daman and Diu
0
0
0
0
Delhi
0
0
0
0
Goa
0
1
1
0
Gujarat
6
9
8
2
Haryana
0
3
12
6
Himachal Pradesh
6
5
1
0
Jammu and Kashmir
7
7
3
5
Jharkhand
4
6
10
3
Karnataka
7
17
5
0
Kerala
0
1
4
6
Lakshadweep
0
0
0
0
Madhya Pradesh
25
19
4
2
Maharashtra
6
22
4
1
Manipur
5
0
2
2
Meghalaya
6
1
0
0
Mizoram
8
0
0
0
Nagaland
9
1
1
0
Orissa
12
9
7
2
Puducherry
0
0
0
0
Punjab
0
3
13
4
Rajasthan
14
13
5
0
Sikkim
3
1
0
0
Tamil Nadu
0
10
14
7
Tripura
1
1
2
0
Uttar Pradesh
0
6
11
42
Uttarakhand
9
1
2
1
West Bengal
0
0
5
8
India
168
154
142
115
26.3
24.1
22.2
18.0
Source:
Author’s calculations
57
$0.50
0
1
0
1
14
1
0
0
2
9
0
1
0
0
0
1
1
3
1
0
2
0
0
0
0
0
4
0
1
0
1
0
12
0
6
61
9.5
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Preliminary Demography of India
Figure 3.7
Distribution of the index Idc(x)in districts of India, 2011
58
Population Distribution
Table 3.5
Distribution of districts by the index Ddc(x), 2011
State/Union Territory
Ddc(x)
<-0.5
-0.5 to 0 0 to 0.5
0.5-1.0
$1.0
AN Islands
0
3
0
0
0
Andhra Pradesh
8
6
8
0
1
Arunachal Pradesh
0
16
0
0
0
Assam
0
9
15
3
0
Bihar
0
1
8
11
18
Chandigarh
0
0
0
0
1
Chhattisgarh
2
14
2
0
0
Dadra and Nagar Haveli
0
0
1
0
0
Daman and Diu
0
0
2
0
0
Delhi
0
0
1
1
7
Goa
0
1
1
0
0
Gujarat
3
12
8
1
2
Haryana
0
4
16
1
0
Himachal Pradesh
0
11
1
0
0
Jammu and Kashmir
0
14
8
0
0
Jharkhand
0
10
13
0
1
Karnataka
1
24
4
0
1
Kerala
0
2
3
3
6
Lakshadweep
0
0
1
0
0
Madhya Pradesh
3
42
3
2
0
Maharashtra
5
23
3
0
4
Manipur
0
5
4
0
0
Meghalaya
0
7
0
0
0
Mizoram
0
8
0
0
0
Nagaland
0
10
1
0
0
Orissa
0
21
7
2
0
Puducherry
0
0
3
1
0
Punjab
0
3
14
2
1
Rajasthan
11
16
5
0
1
Sikkim
0
4
0
0
0
Tamil Nadu
0
11
11
7
3
Tripura
0
2
2
0
0
Uttar Pradesh
0
6
19
24
22
Uttarakhand
0
10
2
1
0
West Bengal
0
0
4
5
10
India
33
295
170
64
78
5.2
46.1
26.6
10.0
12.2
Source:
Author’s calculations
59
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Preliminary Demography of India
Figure 3.8
Index of population distribution in districts of India, 2011
60
Population Distribution
The inter-district variations in the index of population distribution is the result of both interdistrict variation in the index of extensiveness of population and inter-district variation in the
index of intensiveness of population. The index of extensiveness of population varies from a low
of 0.048 per 1000 population in district Dibang Valley of Arunachal Pradesh to a high of 66.467
per 1000 population in district Thane in Maharashtra. In 117 districts of the country, the
extensiveness of population, measured in terms of the index Edc(x) has been found to be very low
(Table 3.3). In these districts, population as proportion of the population of the country is
amongst the lowest in the country according to the 2011 population census. More than half of
these districts are located in six states of the country - Arunachal Pradesh (16), Jammu and
Kashmir (14), Nagaland (11), Manipur (9), Mizoram (8) and Uttarakhand (6). In all districts of
Arunachal Pradesh, Manipur, Mizoram and Nagaland, the index of extensiveness has been found
to be less than 0.50 per 1000 population at the 2001 population census. These four states
constitute the north-eastern border of the country. Besides these four states, the index of
extensiveness of population has also been found to be amongst the lowest in the country in all
the three districts of the Union Territory of Andaman and Nicobar islands. The index of the
extensiveness of population has also been found to be extremely low in the border districts of
Jammu and kashmir and Uttarakhand.
By contrast, there are 45 districts in the country where the extensiveness of population found to
be amongst the highest in the country. All these districts have an index of extensiveness of
population at least 3.50 per 1000 population. All but six of these districts are located in the just
five states of the country - Uttar Pradesh (11), West Bengal (10), Maharashtra (7), Bihar (6) and
Andhra Pradesh (5). In addition, in two districts of Gujarat and Karnataka and one district of
Rajasthan and Tamil Nadu, the index of extensiveness of population has been found to be among
the highest in the country. The population of these districts as proportion to the population of the
country is the largest among all districts of the country.
The index of intensiveness of population, on the other hand, varies from a low of -2.256 in
district Dibang Valley of Arunachal Pradesh to a high of 2.133 in district Mumbai in
Maharashtra. There are 61 districts where the index of intensiveness of the population has been
found to be amongst the highest in the country. In all these districts, the population is at least
three times the area of the district. Most of these districts are located in only four states - Bihar
(14), Uttar Pradesh (12), Delhi (9) and West Bengal (6). In these districts, there is a very heavy
concentration of the population. All districts of the National Capital Territory of Delhi have a
very high index of the intensiveness of population distribution as population density in all the 9
is more than 5000 persons per square kilometre.
61
Preliminary Demography of India
On the other hand, in 168 districts of the country, the index of intensiveness of the population
has been found to be very low. In these districts, the population enumerated at the 2011
population census is only about 55 per cent or less of the geographical area of the district. More
than half of these districts are located in Madhya Pradesh (25), Arunachal Pradesh (16),
Rajasthan (12), Chhattisgarh (12), Orissa (12) and Uttarakhand (9). In Madhya Pradesh, the index
of the intensiveness of the population has been found to be very low in 25 of the 50 districts in
the state. In Andaman and Nicobar Islands, Mizoram, Meghalaya, Nagaland and Sikkim also,
the index of the intensiveness of the population, measured in terms of the index Idc(x) has been
estimated to be very low either in all or in majority of the districts.
62
4
Age Composition
Age composition of the population is one of the basic demographic variables. It is intertwined
with all other demographic variables. It affects and is affected by the three determinants of
population growth - fertility, mortality and migration. The age composition of the population is
directly related to different stages of demographic transition. The early stage of demographic
transition is characterised by high birth rate and high death rate. The age structure of a population
at the early stage of demographic transition is typically young - a large proportion of population
is in the younger ages - so that the population pyramid is triangular in shape with a large base and
a thin top. As demographic transition advances, first the death rate and then the birth rate
decreases. A decrease in the death rate is normally associated with a decrease in the death rate
of the child population also so that a decrease in the death rate leads to an increase in the
proportion of the child population to the total population if the birth rate remains unchanged. In
the third stage of demographic transition, the birth rate starts decreasing which results in a
decrease in the number of births and the base of the population pyramid starts shrinking. The
continued decrease in the death rate and the birth rate results in continued shrinking of the base
of the population pyramid and its bulging in the middle ages. Further advancement in
demographic transition results in the upward movement of the bulge in the population pyramid
and it turns more and more rectangular in shape. When very low levels of the birth rate and the
death rate persist for a long period, the shape of the population pyramid again turns triangular but
with a very narrow base and a broad top which implies that most of the population is
concentrated in the old ages. An analysis of the age composition of the population, therefore,
provides an idea about the stage of the demographic transition.
63
Preliminary Demography of India
The age composition of the population is also influenced by the patterns of migration. Although,
people of all ages and both sexes can migrate, yet, the available evidence suggests that, like
fertility and mortality, migration is also age-selective. In general, migration is quite common
among men of early working ages who migrate in search of either better livelihood opportunities
or for education and learning and has an impact on the age composition of the population.
The provisional figures of the 2011 population census do not provide information about the age
composition of the population according to the conventional quinquennial age groups. However,
these figures provide information about the population below 7 years of age for the combined
population as well as separately for males and females for all the 35 states and Union Territories
and for all the 640 districts of the country. This information provides an opportunity to have a
preliminary analysis of the age composition of the population. This analysis also provides the
first hand information about the stage of age structure transition in different states/Union
Territories of the country as well as in different districts of the country. It may be pointed out here
that population census is the only source of information about the age composition of the
population at the district level in the country.
Two indexes of the age composition of the population can be calculated on the basis of the
provisional figures of the 2011 population census. The first is the proportion of the population
aged 0-6 years to the total population while the second is the ratio of the population aged 0-6
years to the population aged 7 years and above. If P denotes the total population, P6 the
population aged 0-6 years and P7 the population aged 7 years, then the proportion of the
population 0-6 years to the total population C is defined as
C = P6/P
(4.1)
whereas the age composition index (A) may be defined as the ratio of the population aged 0-6
years to the population aged 7 years, or
A = P6/P7
(4.2)
The index A is better than the index C in the sense that in the calculation of the index C, the
population aged 0-6 years appears in both numerator and denominator whereas the numerator and
the denominator in the calculation of the index A are mutually exclusive. The indexes C and A
however have the limitation that they do not have additive and multiplicative properties. As such,
it is not possible to analyse how prevailing level of the index C or A in a district contributes to
the index C or A of the state/Union Territory or the country as a whole. In other words, these
indexes do not take into account the distributive property of the data available through the
population census.
64
Age Composition
In order to take into account the distributive property of the data available through the population
census, we follow the approach outlined in chapter 1 and develop relative measures of age
composition on the basis of the index A of the age composition defined by the equation (4.2).
We define the deviations of the age composition index A, in district d from the age composition
index A for the country and for the state as
Idc(a) = log (Ad/Ac) for all d0c,
(4.3)
Ids(a) = log (Ad/As) for all d0s, and
(4.4)
Isc(a) = log (As/Ac) for all s0c.
(4.5)
Then the distribution indexes of the age composition (D) in district d are defined as
Ddc(a) = Edc *Idc(a) for all d0c,
(4.6)
Dds(a) = Eds *Ids(a) for all d0s, and
(4.7)
Dsc(a) = Esc *Isc(a) for all s0c
(4.8)
and the distribution indexes of the age composition at the country and the state/Union Territory
level may then be defined as
Dcd(a) = 3Ddc(a) for all d0c,
(4.9)
Dcs(a) = 3Dsc(a) for all s0c, and
(4.10)
Dsd(a) = 3Dds(a) for all d0s,
(4.11)
Finally, it is easy to see that
Dcd(a) = 3Eds(a)*Dcs(a) + 3Esc(a)* Dsd(a)
(4.12)
The distributive index of age composition in districts d, Ddc(a), is a relative index of age
composition in district d relative to the age composition of the country as a whole. It tells the
extent to which the age composition index of the district d, the index A, deviates from the age
composition index of the country as a whole and to what proportion of the population, this
deviation applies. Thus, the distributive index Ddc(a) takes into account both the extent of the
deviation of the age composition index and the extensiveness of this deviation which is measured
in terms of the proportionate distribution of the population across the districts and states/Union
Territories of the country. The advantage of the index Ddc(a), as discussed in Chapter 1, is that
it can be decomposed into two components. One component of the index is related to the
distribution of the age composition index A across the districts within the state/Union Territory
while the second component is related to the distribution of the index across the states/Union
Territories within the country. Conventional measures of age composition like the proportion of
population aged 0-6 years to the total population or the age composition index A - ratio of the
population aged 0-6 years to the population aged 7 years and above - or any other similar index
of age composition do not have these additive and distributive property which is inherent in the
census data.
65
Preliminary Demography of India
Age Composition of Population in India
According to the provisional figures of the 2011 population census, total population aged 0-6
years in India was 158.789 million at 00:00 hours of 1st March 2011. The corresponding number
at the 2001 population census was 163.82 million which suggests that population aged 0-6 years
in the country decreased marginally - by approximately 5 million or about 3 per cent - during the
ten-year period between 2001 and 2011. At the same time, the population aged 7 years and
above in the country increased by approximately 187 million - from around 864.79 million in
2001 to around 1051.40 million in 2011 or by almost 22 per cent during this period. As a result,
the age composition index, the index A, decreased from around 19 per cent in 2001 to around 15
per cent in 2011 in the country. This is another encouraging finding of the 2011 population
census. However, it may be pointed out that the decrease in the age composition index has largely
been the result of the increase in the population aged 7 years and above and not the result of the
decrease in the population aged 0-6 years.
A marginal decrease in the population aged 0-6 years may be attributed to the net effect of the
decrease in the number of live births as a result of the decrease in the birth rate and an increase
in the population aged 0-6 years as the result of the decrease in the death rate in this age group.
The provisional figures of the 2011 population census suggest that the decrease in the number
of live births in the country during the period 2001-2011 has largely been compensated by the
increase in the population of 0-6 years of age as the result of the decrease in the death rate in this
age group so that there has been only a marginal change in the population aged 0-6 years. On the
other hand, a relatively faster increase in the population aged 7 years and above may be attributed
to the decrease in the death rate in the population aged 7 years and above and to the momentum
effect, the effect of the high birth rate in the past on the growth of the population (Table 4.1). The
provisional figures of the 2011 population census do not provide any idea about mortality in the
population aged 7 years and above but the information available through the sample registration
system gives no indication about any accelerated decrease in mortality in the population aged 7
years and above in the country. It therefore appears that the increase in the population aged 7
years and above in the country during the period 2001-2011 has primarily been due to the
momentum effect - the broad base of the population pyramid moving upwards with time which
appears to have contributed to a rapid increase in the proportion of the population aged 7 years
and above during the period 2001-2011. In any case, it is apparent from the table 4.1 that the
population of the country continues to be young and the associated population pyramid remains
typically triangular in shape. At the same time, it is also apparent from the provisional figures of
the 2011 population census that there has been only a marginal change in the age composition
of the population.
66
Age Composition
Figure 4.1
Age composition of population in India
The age composition index A may be perceived as a crude indicator of the age structure of the
population. It is obvious that the higher is this ratio, the younger is the age structure of the
population and the larger are the resources requirements for meeting the development needs of
children 0-6 years of age in terms of their survival, growth and development as well as in terms
of their productive utilisation and participation in the social and economic production system,
housing and shelter needs, etc. in the years to come when they enter into the productively active
life or the adulthood. On the other hand, a low value of the index A suggests that the proportion
of the population aged 7 years and above is relatively high. In this context, the age composition
index A reflects the implications of the age structure of the population on the social and
economic production system and on social and economic development processes. At the same
time, the index A also reflects the transition in the demographic processes as it is well known that
the age structure of the population is essentially a reflection of the transition in fertility and
mortality and the patterns of migration.
67
Preliminary Demography of India
Table 4.1
Age composition of the population in India
Age group
Population
(million)
Change
2001
2011
Absolute
(million)
Proportionate
(per cent)
< 7 years
163.82
(15.92)
158.789
(13.12)
-5.031
-3.07
$7 years
864.79
(84.08)
1051.404
(86.88)
186.614
21.58
1028.61
(100.00)
1210.193
(100.00)
181.583
17.65
0.189
0.151
All
Index A = P6/P7
Distributive index of age
composition
Remarks:
Source:
10.593
Figures in parentheses denote percentages. For the definition of the distribution index
of age composition, see text.
Author’s calculations
The provisional figures of the 2011 population census also suggest that the distribution index of
age composition, Dcd(a) was around 10.593 per 1000 population in the year 2011 for the country
as a whole. This index reflects the distribution of the age composition of the population measured
in terms of the age composition index A across the districts of the country. Nearly 70 per cent
of this index is accounted by the index Dcs(a) which reflects the distribution of the index of the
age composition of the population (index A) across the states/Union Territories while the
remaining 30 per cent is accounted by the index Dsd(a) which reflects the distribution of the index
of the age composition of the population across districts within the states/Union Territories of
the country. This implies that the age structure of the population varies more across the
states/Union Territories of the country as compared to the variation in the age structure of the
population across districts within the same state/Union Territory. This is expected as the
states/Union Territories of the country are at different stages of demographic transition which has
a reflection in terms of the age composition of the population. However, within a state/Union
Territory, the variation in the age composition of the population, as measured by the index A,
appears to be relatively small.
68
Age Composition
Figure 4.2
Age composition of population in India by sex
The provisional figures of the 2011 population census also provide information about the
population aged 0-6 years by the sex of the child. This information suggests that male children
outnumbered female children by more than 7 million or by more than 8 per cent in the age group
0-6 years whereas male population outnumbered female population by more than 30 million or
by about 5 per cent in the age group 7 years and above. The male-female difference in the
population of children aged 0-6 years is influenced by the sex ratio at birth and differentials
mortality by sex whereas male-female difference in the population aged 7 years and above
depends upon the sex ratio at 7 years of age and differential mortality by sex in the age group 7
years and above. The sex ratio at birth is favourable to males so that there are more male births
than female births. If female mortality is higher than the male mortality in the age group 0-6
years, then there would be relatively lesser number of female survivors than male survivors in
the age group 0-6 years. As a result, males will outnumber females in the age group 0-6 years as
is the case in India.
69
Preliminary Demography of India
Table 4.2
Age composition of the population in India by sex, 2011
Age group
Population
(million)
Difference
Male
Female
Absolute
(million)
Proportionate
(per cent)
< 7 years
82.952
75.837
-7.115
-8.58
$7 years
540.772
510.632
-30.14
-5.57
All
623.724
586.469
-37.255
-5.97
0.153
0.149
Index A = P6/P7
Source:
2011 population census
The very fact that the age structure of the male population in the country is younger than that of
the female population is reflected through the age composition index A which is higher for males
as compared to females, although the gap is not very large. Table 4.2 suggests that for every 1000
males aged 7 years and above, there were more than 153 males aged 0-6 years in the country
according to the 2011 population census. The corresponding number for females was only 149.
A part of this difference is due to the difference in the proportion of males aged 0-6 years to total
males and proportion of females aged 0-6 years to total females. One way to remove this
structure effect is to calculate males aged 0-6 years and females aged 0-6 years as proportion to
the average of the male and female population aged 7 years and above and than calculate the
male-female difference. It is possible to separate the structure effect from the level effect by
decomposing the observed difference in the male and female age composition index in the
following manner:
Im - If = (am - af)*pf + (pm - pf)*af +(am - af)*(pm - pf)
(4.13)
where
Im = age composite index for males = M6/M7,
If = age composition index for female = F6/F7
am = M6/((M7+F7)/2)
af = F6/((M7+F7)/2)
pm = ((M7+F7)/2)/M7
pf = ((M7+F7)/2)/F7
and M stands for the enumerated male population while F stands for the enumerated female
population.
70
Age Composition
The first term on the right side of the equation (4.13) gives difference in the age composition
index when the effect of the male-female difference in the proportion of population 7 years and
above is removed or when the proportion of males and the proportion of females aged 0-6 years
are calculated on the basis of the average male and female population aged 7 years and above.
On the other hand, the second term on the right side of the equation (4.13) reflects the difference
in the age composition index accounted by the male-female difference in the proportion of the
population 7 years and above. Finally, the third term is an interaction term which reflects the
combined effect of the difference in the level and the difference in the structure effects.
Application of the decomposition formula (4.13) to India suggests that when the male and female
population aged 0-6 years is calculated as the ratio of the average male and female population
aged 7 years and above, the male-female difference in the proportion of the population aged 0-6
years is around 14 per 1000 population - 158 per 1000 in males compared to only 144 per 1000
in females. This difference is highly unfavourable to females and suggests that males aged 0-6
years substantially outnumber females aged 0-6 years in the country. A part of this difference
may be due to male-female difference in the number live births or the male-female difference in
the birth rate. At the same time, this difference may also be the result of male-female difference
in mortality in the age group 0-6 years. An understanding of the determinants of the observed
difference between the number of males aged 0-6 years and the number of females aged 0-6 years
requires estimates of male and female birth rate and male and female death rate in the age group
0-6 years which are currently not available through the provisional figures of the 2011 population
census.
Age Composition across States/Union Territories
Estimates of the index age composition (index A) for the states and Union Territories of the
country are given in table 4.3 for the year 2001 and 2011. The index has been found to be the
lowest in Goa and the highest in Meghalaya. The index has also been found to be very high in
Bihar, Jammu and Kashmir and Jharkhand but very low in Kerala, Andhra Pradesh and
Karnataka. The wide variation in the index A across the states/Union Territories of the country
suggests that the age structure of the population varies widely across the states/Union territories
of the country which is a reflection of the fact that different states/Union Territories of the
country are at different stages of demographic transition. Estimates of the index of the age
composition (index A), presented in table 4.3, suggest that the demographic transition in states
like Bihar, Jammu Kashmir and Jharkhand is yet to pick up the momentum whereas the transition
appears to be fairly advanced in states like Kerala, Andhra Pradesh and Karnataka and very
advanced in Goa.
71
Preliminary Demography of India
Table 4.3
Index of age composition (index A) in states and Union Territories, 2001-2011
Country/State
Population 0-6 years as proportion to the population
7 years and above
2001
2011
Difference
India
0.189
0.151
-0.038
Andaman and Nikobar
0.144
0.116
-0.028
Andhra Pradesh
0.154
0.114
-0.040
Arunachal Pradesh
0.231
0.172
-0.059
Assam
0.203
0.169
-0.034
Bihar
0.254
0.218
-0.036
Chandigarh
0.147
0.126
-0.021
Chhattisgarh
0.206
0.163
-0.043
Dadra and Nagar Haveli
0.223
0.168
-0.055
Daman and Diu
0.150
0.119
-0.031
Delhi
0.170
0.133
-0.037
Goa
0.121
0.106
-0.015
Gujarat
0.175
0.142
-0.033
Haryana
0.187
0.150
-0.037
Himachal Pradesh
0.150
0.125
-0.025
Jammu and Kashmir
0.172
0.191
0.019
Jharkhand
0.225
0.189
-0.036
Karnataka
0.157
0.126
-0.031
Kerala
0.135
0.111
-0.024
Lakshadweep
0.176
0.124
-0.052
Madhya Pradesh
0.218
0.170
-0.048
Maharashtra
0.164
0.129
-0.035
Manipur
0.155
0.149
-0.006
Meghalaya
0.253
0.231
-0.022
Mizoram
0.193
0.179
-0.014
Nagaland
0.170
0.169
-0.001
Orissa
0.170
0.136
-0.034
Puducherry
0.137
0.114
-0.023
Punjab
0.150
0.119
-0.031
Rajasthan
0.232
0.181
-0.051
Sikkim
0.169
0.112
-0.057
Tamil Nadu
0.131
0.106
-0.025
Tripura
0.158
0.138
-0.020
Uttar Pradesh
0.235
0.175
-0.060
Uttarakhand
0.191
0.151
-0.040
West Bengal
0.166
0.124
-0.042
Source:
Author’s calculations
72
Age Composition
Figure 4.1
Distribution of index A across
states/Union Territories in India, 2011
73
Preliminary Demography of India
Table 4.3 also suggests that the index of age composition has decreased in all the states/Union
Territories of the country during the period 2001-2011 except the state of Jammu and Kashmir.
However, the magnitude of the decrease varies across the states/Union Territories. The decrease
in the index has been the most rapid in Uttar Pradesh followed by Arunachal Pradesh, Sikkim,
Lakshadweep and Dadra and Nagar Haveli in that order. By contrast, there has been little change
in the index in Nagaland, Manipur, Mizoram and Goa. Out of these four states, Goa has the
lowest index of age composition in the country. In the remaining three states, there is a need to
explore the reasons behind the stagnation in the transition in the age structure of the population
as revealed through the provisional results of the 2011 population census. Similarly, there is also
a need to explore the reasons for the reversal of the transition in the age structure of the
population In Jammu and Kashmir where the index A increased from around 17 per cent in 2001
to more than 19 per cent in 2011.
Table 4.4 gives the estimates of distributive indexes of the age composition across the
states/Union Territories of the country. The distributive index of the age composition for a
state/Union Territory can be estimated in two ways - in relation to the index of age composition
of the country as a whole (the index Dsc(a)) and in relation to the index of the age composition
of the districts within the state/Union Territory (the index Dds(a)). The index Dsc(a) has been
found to vary from a high of 13.68 in Bihar to a low of -9.24 in Tamil Nadu. In Bihar, the index
of age composition has been found to be more than 1.44 times the corresponding index for the
country as a whole. At the same time, Bihar accounted for more than 8.5 per cent of the
population of the country. By contrast, the index of age composition in Tamil Nadu was less than
0.70 times the index at the national which implies that the proportion of the population aged 0-6
years to the total population in the state is the lowest in the country. Tamil Nadu accounted for
around 6 per cent of the population of the country at the 2011 population census. Besides Bihar,
Uttar Pradesh is the only other state/Union Territory in the country where a very high value of
the index Dsc(a) has been estimated. On the other hand, at the other extreme of the scale of the
distributive index of the age composition are Andhra Pradesh, West Bengal and Maharashtra. All
the three states accounts for a large proportion of the population of the country.
Table 4.4 also gives the estimates of the distributive index Dsd(a) captures the distribution of the
age composition index across the districts within the states/Union Territories. Combining the
index Dsc(a) with the index Dsd(a) according to equation (4.12) gives the state share to the index
Dcd(a). This exercise suggests that Bihar and Uttar Pradesh account for the largest share of the
distribution of the index of the age composition across the districts of the country irrespective
of the direction of the index.
74
Age Composition
Table 4.4
Distributive indexes of age composition of population in states and Union Territories, 2011
Country/State
Andaman and Nikobar
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chandigarh
Chhattisgarh
Dadra and Nagar Haveli
Daman and Diu
Delhi
Goa
Gujarat
Haryana
Himachal Pradesh
Jammu and Kashmir
Jharkhand
Karnataka
Kerala
Lakshadweep
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
Orissa
Puducherry
Punjab
Rajasthan
Sikkim
Tamil Nadu
Tripura
Uttar Pradesh
Uttarakhand
West Bengal
India
Source:
Esc
0.314
69.960
1.143
25.756
85.775
0.872
21.104
0.283
0.201
13.843
1.205
49.896
20.950
5.666
10.369
27.241
50.513
27.589
0.053
59.988
92.855
2.249
2.449
0.902
1.637
34.662
1.028
22.892
56.703
0.502
59.609
3.033
164.917
8.360
75.482
Dsc(a)
0.000
-0.128
-0.005
-0.151
-0.096
0.000
-0.030
0.000
0.000
-0.012
-0.001
-0.224
-0.097
-0.009
-0.119
-0.099
-0.283
-0.135
0.000
-0.178
-0.333
-0.006
-0.008
-0.003
-0.010
-0.179
0.000
-0.012
-0.132
0.000
-0.076
-0.009
-0.361
-0.012
-0.555
Author’s calculations
75
Dcd(a)
-0.036
-8.758
0.059
1.122
13.585
-0.069
0.682
0.013
-0.021
-0.763
-0.187
-1.606
-0.188
-0.467
0.928
2.548
-4.202
-3.878
-0.005
2.905
-6.660
-0.018
0.444
0.063
0.069
-1.710
-0.125
-2.399
4.294
-0.066
-9.320
-0.132
10.201
-0.007
-6.890
10.593
Preliminary Demography of India
Figure 4.2
Distributive index of age composition in
Indian states/Union Territories, 2011
76
Age Composition
Age Composition across Districts
District level estimates of the index of age composition (index A) are given in table 4.A while
table 4.5 presents the distribution of districts according to this index across the states/Union
Territories of the country. In all but 127 districts of the country, the index A varies within the
narrow range of 0.100 to 0.200 which implies that in most of the districts of the country,
population aged 0-6 years are 10-20 per cent of the population 7 years and above. There are 29
districts where the index A is estimated to be less than 0.100 which implies that population aged
0-6 years in these districts is less than 10 per cent of the population 7 years and above. Most of
these districts are located in Karnataka (4), Kerala (7) and Tamil Nadu (9).
On the other hand, in 98 districts of the country, population aged 0-6 years is estimated to be
more than 20 per cent of the population 7 years and above. Most of these districts are located in
Bihar (31), Jammu and Kashmir (11), Jharkhand (10) Rajasthan (8), Uttar Pradesh (8),
Meghalaya (6) and Madhya Pradesh (6). Out of these 98 districts, there are 9 districts where the
ratio of the population aged 0-6 years to the population aged 7 years and above has been
estimated to be at least 25 per cent. These nine districts are Araria, Khagaria and Kishanganj in
Bihar, Badgam and Kupwara in Jammu and Kashmir, Jaintia Hills and West Khasi Hills in
Meghalaya, Mewat in Haryana, and Jhabua in Madhya Pradesh.
Table 4.A also presents estimates of the distributive index of the age composition for all the 640
districts of the country. The distribution of districts according to the distributive index of age
composition in different states/Union Territories is given in table 4.7. There are 20 districts in
the country where the distributive index of age composition has been found to be very low which
suggests that the ratio of the population aged 0-6 years to the population aged 7 years and above
(the index A) in these districts is well below the corresponding index at the national level.
District North Twenty Four Parganas in West Bengal has the distinction of having the lowest
distributive index of age composition in the country. The index A has been estimated to be 0.098
in this districts which is just around 65 per cent of the corresponding index at the national level.
At the same time, the total population of the district at the 2011 population census was more than
1 million so that the distributive index of age composition in the district is estimated to be the
highest in the country. In fact, the index A has been the lowest in district Kolkata of West Bengal
- just around 47 per cent of the index at the national level. However, population of district
Kolkata accounts for only about 0.37 per cent of the population of the country at the 2011
population so that the distributive index of age composition of the population in district Kolkata
is estimated to be the third lowest in the country - next to North Twenty Four Parganas in West
Bengal and Mumbai Suburban in Maharashtra.
77
Preliminary Demography of India
Table 4.5
Distribution of districts by the index A, 2011
State
Index A
< 0.10 0.10-0.15 0.15-0.20 0.20-0.25
AN Islands
0
3
0
0
Andhra Pradesh
2
21
0
0
Arunachal Pradesh
0
4
8
4
Assam
0
8
16
3
Bihar
0
0
7
28
Chandigarh
0
1
0
0
Chhattisgarh
0
5
12
1
Dadra and Nagar Haveli
0
0
1
0
Daman and Diu
0
2
0
0
Delhi
1
7
1
0
Goa
0
2
0
0
Gujarat
0
18
6
2
Haryana
0
16
4
0
Himachal Pradesh
0
11
1
0
Jammu and Kashmir
1
4
6
9
Jharkhand
0
1
13
10
Karnataka
4
19
7
0
Kerala
7
6
1
0
Lakshadweep
0
1
0
0
Madhya Pradesh
0
11
33
5
Maharashtra
2
25
8
0
Manipur
0
7
2
0
Meghalaya
0
0
1
4
Mizoram
0
1
4
3
Nagaland
0
2
5
4
Orissa
0
19
10
1
Puducherry
0
4
0
0
Punjab
0
20
0
0
Rajasthan
0
2
23
8
Sikkim
0
4
0
0
Tamil Nadu
9
23
0
0
Tripura
0
2
2
0
Uttar Pradesh
0
4
59
8
Uttarakhand
0
7
6
0
West Bengal
2
13
4
0
India
28
273
240
90
4.4
42.7
37.5
14.1
Source:
Author’s calculations
78
$ 0.25
0
0
0
0
3
0
0
0
0
0
0
0
1
0
2
0
0
0
0
1
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
9
1.4
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Age Composition
Figure 4.3
Proportion of population aged 0-6 years to the population aged 7 years and above
in districts of India, 2011
79
Preliminary Demography of India
Table 4.6
Distribution of districts by the index Ddc(a), 2011
State
Dcd(a)
< -0.05 -0.05 to -0.025 -0.025 to 0 0 to 0.025 $ 0.025 Total
AN Islands
0
0
3
0
0
3
Andhra Pradesh
6
11
6
0
0
23
Arunachal Pradesh
0
0
6
10
0
16
Assam
0
0
9
17
1
27
Bihar
0
0
0
11
27
38
Chandigarh
0
0
1
0
0
1
Chhattisgarh
0
0
5
13
0
18
Dadra and Nagar Haveli
0
0
0
1
0
1
Daman and Diu
0
0
2
0
0
2
Delhi
0
0
8
1
0
9
Goa
0
0
2
0
0
2
Gujarat
0
3
15
6
2
26
Haryana
0
0
17
3
1
21
Himachal Pradesh
0
0
11
1
0
12
Jammu and Kashmir
0
0
5
17
0
22
Jharkhand
0
0
1
22
1
24
Karnataka
1
5
17
7
0
30
Kerala
2
7
4
1
0
14
Lakshadweep
0
0
1
0
0
1
Madhya Pradesh
0
0
11
39
0
50
Maharashtra
4
5
18
8
0
35
Manipur
0
0
7
2
0
9
Meghalaya
0
0
0
7
0
7
Mizoram
0
0
1
7
0
8
Nagaland
0
0
3
8
0
11
Orissa
0
2
17
11
0
30
Puducherry
0
0
4
0
0
4
Punjab
0
2
18
0
0
20
Rajasthan
0
0
3
25
5
33
Sikkim
0
0
4
0
0
4
Tamil Nadu
2
16
14
0
0
32
Tripura
0
0
2
2
0
4
Uttar Pradesh
0
2
2
56
11
71
Uttarakhand
0
0
7
6
0
13
West Bengal
5
4
6
4
0
19
India
20
57
230
285
48
640
3.1
8.9
35.9
44.5
7.5
100.0
Source:
Author’s calculations
80
Age Composition
Figure 4.4
Distributive index of age composition in
districts of India, 2011
81
Preliminary Demography of India
Most of the districts in which the distributive index of age composition has been estimated to be
amongst the lowest in the country are located in Andhra Pradesh (6), West Bengal (5) and
Maharashtra (4). Other districts with the very low distributive index of age composition are
located in Kerala (2), Tamil Nadu (2) and Karnataka (1). Some of these districts are highly
urbanised districts - Mumbai Suburban, Kolkata, Bangalore, Chennai, Thane, Coimbatore,
Mumbai, Pune, etc. One reason for the very low distributive index of age composition in these
districts may be very high proportion of the population aged 7 years and above as a result of the
large scale in-migration of working age population. The proportion of population aged 0-6 years
may also be very low in these districts because of low fertility.
At the other extreme of the scale, there are 48 districts in the country where the distributive index
of age composition has been estimated to be very high - the highest in the country - with district
Purba Champaran in Bihar topping the list. The index A in this district has been estimated to be
0.243 which is around 60 per cent higher than the index at the national level. Out of these 48
districts, 27 are located in Bihar alone. In addition, 11 districts in Uttar Pradesh, 5 districts in
Rajasthan, 2 districts in Gujarat and 1 district each in Assam, Haryana and Jharkhand also have
a very high distributive index of age composition, well above the national average. The very high
distributive index of age composition in these districts reflects either high fertility or some
substantial out migration of the working age population.
In all, out of the 640 districts of the country which existed at the time of 2011 population census,
the distributive index of age composition has been found to be negative in 303 (48 per cent)
districts whereas the index has been positive in 333 (52 per cent) districts. In all the 38 districts
of Bihar and in all the 7 districts of Meghalaya, the distributive index of age composition has
been found to be positive. Other states where the distributive index of age composition has been
found to be negative in majority of districts are: Assam (18 out of 27 districts), Chhattisgarh (13
out of 18 districts), Jammu and Kashmir (17 out of 22 districts), Jharkhand (23 out of 24
districts), Madhya Pradesh (39 out of 50 districts), Nagaland (8 out of 11 districts), Rajasthan (30
out of 33 districts), and Uttar Pradesh (67 out of 71 districts). On the other hand, out of the 333
districts where the distributive index of age composition has been found to be positive, 260
districts (78 per cent) are located in these 11 states. All these states are located in the central or
in the north-eastern part of the country except the state of Jammu and Kashmir. In 10
states/Union Territories, there is no district where the distributive index of age composition has
been negative. These states and Union Territories are Andhra Pradesh, Goa, Punjab, Sikkim,
Tamil Nadu, Andaman and Nicobar Islands, Chandigarh, Daman and Diu, Lakshadweep and
Puducherry.
82
5
Sex Composition
The personal characteristic of sex holds an important position in demographic studies for a
number of reasons. The sex composition of the population, in conjunction with the age structure,
is an important determining factor in population growth as it has relevance to all the three
components of growth. First, procreation is confined to females of a specific age group only.
Second, the risk of death varies by sex and age of the individual. Third, migration - in or out is always sex and age selective. As such, the sex composition of the population influences the
demographic transition process. In addition, separate data for males and females are important
for the evaluation and completeness of the census count. The sex composition of population also
affects social and economic relationship within a community thereby influencing social roles and
cultural patterns and affecting patterns of migration. Imbalances in the sex composition of the
population have implications to patterns of marriage which has relevance to fertility in a country
like India where marriage signals the beginning of the socially accepted sexually active
reproductive period.
Three measures are generally used to measure and analyse the sex composition of the population.
The first is the masculinity proportion which is defined as the proportion of the male population
to the total population. The second measure is the population sex ratio which is defined as the
ratio of male to female population. The third measure, on the other hand, is the excess (or deficit)
of males as proportion to the total population. The three measures are inter-related. If M denotes
the masculinity proportion, S denotes the sex ratio, and X denotes the excess of males as
proportion to the total population, then it is straightforward to show that
83
Preliminary Demography of India
M = S/(1+S)
S = M/(1-M)
X = M - (1-M)
(5.1)
(5.2)
(5.3)
X = (S-1)/(S+1)
(5.4)
and
The three measures of the sex composition of the population described above have been defined
in reference to males. They can also be defined in terms of females. Thus the femininity
proportion is the ratio of the female population to the total population whereas the sex ratio is
the ratio of the female population to the male population which is sometimes termed as the
femininity ratio to distinguish it from the masculinity ratio. Similarly, the sex composition of the
population may also be measured in terms of the excess (or deficit) of females as proportion to
the total population. It may however be noted that the measures of sex composition based on
males as the reference are complementary to measures of sex composition based on females as
the reference and one can be obtained from the other.
The three measures of sex composition of the population described above are absolute measures.
They do not have the additive property which can link the sex composition of the population in
the lower level administrative units with the sex composition of the population in the upper level
administrative units. A more rational approach is to use the relative measure of the sex
composition in which the sex composition of the population in an administrative unit is
expressed in relation to the sex composition of the population in other administrative units. Thus,
in relation to the sex composition of the population of the country as a whole, the indexes of the
intensity of sex composition may be defined as
Idc(s) = log (Sd/Sc) for all d0c.
(5.5)
Ids(s) = log (Sd/Ss) for all d0s, and
(5.6)
Isc(s) = log (Ss/Sc) for all s0c.
(5.7)
Then the indexes of sex composition may be defined as
Ddc(s) = Edc*Idc(s)
(5.8)
Dds(s) = Eds*Ids(s)
(5.9)
Dsc(s) = Esc*Isc(s)
(5.10)
Finally, the indexes of sex composition for the country and the state/Union Territory are defined
as
Dcd(s) = 3Ddc(s)
(5.11)
Dsd(s) = 3Dds(s)
(5.12)
Dcs(s) = 3Dsc(s).
(5.13)
84
Sex Composition
Finally, it is easy to show that
Dcd(s) = 3Esc(s)*Isd(s) + 3Eds(s)*Ics(s)
(5.14)
which decomposes the index of sex composition at the country level into between states/Union
Territories and within state/Union Territory components of the sex composition of the
population.
In India, the sex composition of the population is traditionally measured in terms of the
femininity ratio or the ratio of the female population to the male population. United Nations and
most of the developed countries, on the other hand, use the masculinity ratio which is defined as
the ratio of the male population to the female population to measure the sex composition of the
population. Following the Indian tradition, we have also used, throughout this chapter, the
femininity ratio to measure the ratio of the population of the two sexes at the district as well as
at the state and country level. The femininity ratio is defined as the ratio of the female population
to the male population.
In the absence of migration or in the situation where the net migration is either zero or
insignificant to the natural increase in the population, the sex composition of the population is
determined by the sex ratio at birth and the differential mortality of the two sexes. It is well
known that the sex ratio at birth is favourable to males. The global average sex ratio at birth is
generally assumed to be around 105 male live births for every 100 female live births or around
952 female live births for every 1000 male live births. In India, however, the sex ratio at birth is
estimated to be around 112 male live births for every 100 live births or around 893 female live
births for every 1000 male live births. It has also been observed that the sex ratio at birth in India
varies widely across constituent states/Union Territories and districts. The sex ratio at birth in
India, measured in terms of the ratio of the male live births to female live births is estimated to
be the third highest in the world, next only to China and Armenia. The abnormally high ratio of
the male live births to the female live births in India is a major contributing factor to the
abnormally high ratio of male to female population in the country.
In addition to the sex composition of the live births, the sex composition of the population is also
influenced by differential mortality of the two sexes which varies by age. Since the mortality of
the two sexes varies by age in all populations, the ratio of the population of the two sexes always
deviates from the ratio of the live births of the two sexes or the sex ratio at birth. Moreover,
mortality of different sexes is affected by a host of social, cultural, environmental and health
related factors so that the population sex ratio is also influenced by the prevailing social, cultural
and health related factors.
85
Preliminary Demography of India
Sex Composition of the Population in India
The provisional figures of 2011 population census provide the count of males and females in the
country as well as in its constituent states, Union Territories and districts for the total population
as well as for the population aged 0-6 years and population aged 7 years and above. This
information suggests that there were around 940 females for every 1000 males in the country at
the time of 2011 population census. The good sign is that the improvement in the population sex
ratio that was observed at the 2001 population census has also continued at the 2011 population
census (Figure 5.1). Although, the population sex ratio in India still continues to be well below
the global average of 984 females per 1000 males (Government of India 2011).
Historically, India has experienced a fall in the population sex ratio continuously for 90 years
between 1901 and 1991. At the 1901 population census, India had a population sex ratio of 972
females for every 1000 males. This number decreased to an all-time low of just 927 females for
every 1000 males at the 1991 population census. The decrease in the population sex ratio was
almost continuous throughout this period except during 1941-51 and 1971-81. The gain in the
population sex ratio in 1951 is generally attributed to the displacement of the population after the
partition of the country in 1947. On the other hand, the gain in the population sex ratio in 1981
has been attributed to some improvements in the situation of women in the country. In fact, it is
only after 1991 that the trend in the population sex ratio in the country appears to have been
reversed. Between 1991 and 2001, the population sex ratio in the country, measured in terms of
the number of females per 1000 males, improved by 6 points whereas this improvement was of
7 points during the period 2001-2011 according to the provisional figures of the 2011 population
census. This suggests that there has been a marginal acceleration in the rate of improvement in
the sex ratio of the population during the period 2001-11 as compared to the period 1991-2001.
This is one of the welcome features of the 2011 population census.
The provisional figures of the 2011 population census also permit calculating the sex ratio in the
population aged 0-6 years and the sex ratio in the population aged 7 years and above. Unlike the
trend in the sex ratio in the population all ages combined, the sex ratio in the population aged 0-6
years is decreasing right since 1961 and this decrease has continued during the period 2001-2011
also. This decrease in the sex ratio in the population aged 0-6 years may be because of the
decrease in the sex ratio at birth or because of the increase in mortality of female population aged
0-6 years compared to the male population or both. The provisional figures of the 2011
population census do not permit analysis of the factors responsible for the decrease in the sex
ratio in the population aged 0-6 years. There is a general apprehension that increasing prevalence
of sex selective abortions has distorted the sex ratio at birth making it more and more
86
Sex Composition
Figure 5.1
Sex ratio (females per 1000 males) in India, 1901-2011
unfavourable to the female live births and this distortion appears to be the primary reason behind
the continued decrease in the sex ratio of population aged 0-6 years. There may also be a
possibility that either the decrease in the female mortality in the age group 0-6 years has been
slower than the decrease in the male mortality in the age group 0-6 years during the period under
reference or the decrease in the female mortality in the age group 0-6 years has stagnated. The
life tables prepared by the Government of India on the basis of the sample registration system do
indicate a slow down in the decrease and even a slight increase in female mortality in the
population below five years of age in the country in recent years (Chaurasia, 2010) which may
have some impact on the sex ratio in the population aged 0-6 years. In any case, a sex ratio of just
914 females aged 0-6 years for every 1000 males aged 0-6 years in the country estimated on the
basis of provisional figures of the 2011 population census is the lowest sex ratio ever recorded
in the country.
87
Preliminary Demography of India
Table 5.1
Females per 1000 males in India, states and Union Territories, 2001-2011
Country/State/
Total population
0-6 years
7 years and above
2011
2001
2011
2001
2011
2001
Union Territory
India
940
933
914
927
944
934
Andaman & Nicobar Islands
878
846
966
957
868
831
Andhra Pradesh
992
978
943
961
997
981
Arunachal Pradesh
920
893
960
964
913
878
Assam
954
935
957
965
953
929
Bihar
916
919
933
942
912
914
Chandigarh
818
777
867
845
812
767
Chhattisgarh
991
989
964
975
995
992
Dadra & Nagar Haveli
775
812
924
979
752
779
Daman & Diu
618
710
909
926
589
682
Delhi
866
821
866
868
866
813
Goa
968
961
920
938
973
964
Gujarat
918
920
886
883
923
927
Haryana
877
861
830
819
885
869
Himachal Pradesh
974
968
906
896
983
980
Jammu & Kashmir
883
892
859
941
887
884
Jharkhand
947
941
943
965
948
935
Karnataka
968
965
943
946
971
968
Kerala
1084
1058
959
960
1099
1072
Lakshadweep
946
948
908
959
951
946
Madhya Pradesh
930
919
912
932
933
916
Maharashtra
925
922
883
913
931
924
Manipur
987
974
934
957
995
977
Meghalaya
986
972
970
973
989
971
Mizoram
975
935
971
964
976
930
Nagaland
931
900
944
964
929
890
Orissa
978
972
934
953
985
976
Puducherry
1038
1001
965
967
1047
1006
Punjab
893
876
846
798
899
888
Rajasthan
926
921
883
909
935
923
Sikkim
889
875
944
963
883
861
Tamil Nadu
995
987
946
942
1000
993
Tripura
961
948
953
966
962
945
Uttar Pradesh
908
898
899
916
910
894
Uttarakhand
963
962
886
908
975
973
West Bengal
947
934
950
960
946
929
Source:
Author’s calculations
88
Sex Composition
Figure 5.2
Females per 1000 males
in states and Union Territories, 2011
89
Preliminary Demography of India
Figure 5.3
Females per 1000 males in population aged 0-6 years
in states/Union Territories, 2011
90
Sex Composition
Figure 5.4
Females per 1000 males in population aged 7 years and above
in states and Union Territories, 2011
91
Preliminary Demography of India
On the other hand the sex ratio in the population aged 7 years and above has shown an increasing
trend in the country during the period 2001-2011. At the 2011 population census, there were 934
females for every 1000 males in the country. This number has increased to 944 females for every
1000 males at the 2011 population census - an increase of 10 points for every 1000 males. This
increase in the sex ratio in the population aged 7 years and above suggests that there has been a
relatively faster reduction in the mortality of females aged 7 years and above in the country as
compared to the reduction in the mortality of males aged 7 years and above during the period
2001-2011.
The index of the sex composition of the population, Dcd(s) for the country has been found to be
very close to zero in the total population but quite substantial in the population aged 0-6 years
and the population aged 7 years and above. The index is negative in the total population and in
population aged 7 years and above. A negative value of the index implies that males outnumber
females in majority of the population while a positive value implies that females outnumber
males relative to the sex ratio at the national level. Since the index Dcd(s) is the sum of the index
of sex composition, Ddc(s), in all the 640 districts of the country, this means that the sum of all
negative values of the index Ddc(s) is almost the same as the sum of all positive values of the
index in the total population but not in the population aged 0-6 years and the population aged 7
years and above. Variation in the index of sex composition across the districts of the country in
relation of the sex composition at the national level will be discussed at length in the following
sections.
Sex Ratio in States/Union Territories
Estimates of the sex ratio (females per 1000 males) for the states and Union Territories of India
are given in table 5.1 for the total population as well as separately for the population aged 0-6
years and the population aged 7 years and above for the years 2001 and 2011. Wide variation in
the sex ratio across the states and Union Territories of the country is very much evident from the
table in the three population groups. For the total population, the sex ratio has been found to vary
from just 618 females per 1000 males in Daman and Diu to 1084 females per 1000 males in
Kerala according to the provisional figures of the 2011 population census. In addition to Kerala,
Puducherry is the only other state/Union Territory in the country where there were more females
than males at the 2011 population census. On the other hand, there are nine states/Union
Territories in the country where the sex ratio of the population has been found to be extremely
low, less than 900 females per 1000 males. All these states, except Haryana, are either small
states or Union Territories which account for only a very small proportion of the population of
the country.
92
Sex Composition
As regards the sex ratio in the population aged 0-6 years, there is no state in the country where
there were more females aged 0-6 years than males aged 0-6 years at the 2011 population census.
The highest number of females for every 1000 males in the population aged 0-6 years has been
estimated in Mizoram where there were 971 females aged 0-6 years for every 1000 males aged
0-6 years according to the 2011 population census. In addition to Mizoram, there are nine
states/Union Territories where the sex ratio in the population aged 0-6 years has been found to
be at least 950 females for every 1000 males in the year 2011. Six of these ten states/Union
Territories are located in the north-eastern part of the country. By contrast, there are 10
states/Union Territories of the country, where the sex ratio in the population aged 0-6 years has
been estimated to be less than 900 females per 1000 males on the basis of the provisional data
available through the 2011 population census. The sex ratio in the population aged 0-6 years has
been found to be the lowest in Haryana where there were only 830 females aged 0-6 years for
every 1000 males aged 0-6 years at the 2011 population census. Other states/Union Territories
where the sex ratio in the population aged 0-6 years has been found to be less than 900 females
per 1000 males at the 2011 population census are Punjab (846), Jammu and Kashmir (859), Delhi
(866), Chandigarh (867), Maharashtra (883), Rajasthan (883), Gujarat (886), Uttarakhand (886)
and Uttar Pradesh (899).
Finally, the sex ratio in population aged 7 years and above has been found to be the highest in
Kerala (1099 females per 1000 males aged 7 years and above) followed by Puducherry. These
are the only two states in the country where there were more females aged 7 years and above than
males aged 7 years and above. Moreover, in Tamil Nadu, the number of females aged 7 years and
above were found to be almost the same as the number of males aged 7 years and above so that
the sex ratio in the population aged 7 years and above is very close to 1000 females aged 7 years
and above for every 1000 males aged 7 years and above. By comparison the sex ratio in
population aged 7 years and above has been found to be extremely low in the Union Territory of
Daman and Diu where there were only 589 females aged 7 years and above for every 1000 males
aged 7 years and above at the 2011 population census. In all, in nine states/Union Territories of
the country, the sex ratio in the population aged 7 years and above has been found to be less than
900 females for every 1000 males. All these states are either small states or Union Territories of
the country except the states of Haryana and Punjab. As such, the impact of the prevailing sex
ratio in these states/Union Territories to the sex ratio of the country is insignificant. In any case,
a sex ratio in the population aged 7 years and above in these states and Union Territories which
is extremely unfavourable to females requires an in-depth exploration of the factors and
conditions that may be responsible for the sex ratio in the population aged 7 years and above as
revealed through the 2011 population census.
93
Preliminary Demography of India
Table 5.2
Index Ddc(s) in India and states/Union Territories, 2011
Country/State/
Population
Population
Population
Union Territory
All ages
0-6 years
7 years and above
Andaman & Nicobar Islands
-0.009
0.007
-0.012
Andhra Pradesh
1.617
0.951
1.659
Arunachal Pradesh
-0.011
0.025
-0.017
Assam
0.157
0.526
0.104
Bihar
-0.986
0.719
-1.296
Chandigarh
-0.053
-0.020
-0.057
Chhattisgarh
0.482
0.482
0.484
Dadra & Nagar Haveli
-0.024
0.001
-0.028
Daman & Diu
-0.037
-0.001
-0.042
Delhi
-0.492
-0.323
-0.518
Goa
0.015
0.003
0.016
Gujarat
-0.521
-0.741
-0.496
Haryana
-0.633
-0.916
-0.596
Himachal Pradesh
0.086
-0.024
0.097
Jammu & Kashmir
-0.286
-0.293
-0.278
Jharkhand
0.084
0.345
0.046
Karnataka
0.644
0.705
0.622
Kerala
1.704
0.570
1.818
Lakshadweep
0.000
0.000
0.000
Madhya Pradesh
-0.284
-0.074
-0.306
Maharashtra
-0.641
-1.298
-0.565
Manipur
0.047
0.020
0.051
Meghalaya
0.050
0.062
0.050
Mizoram
0.014
0.024
0.013
Nagaland
-0.007
0.025
-0.012
Orissa
0.600
0.275
0.639
Puducherry
0.044
0.024
0.046
Punjab
-0.513
-0.762
-0.492
Rajasthan
-0.365
-0.897
-0.257
Sikkim
-0.012
0.007
-0.015
Tamil Nadu
1.466
0.908
1.493
Tripura
0.029
0.053
0.025
Uttar Pradesh
-2.496
-1.246
-2.684
Uttarakhand
0.086
-0.114
0.115
West Bengal
0.219
1.222
0.071
India
-0.024
0.247
-0.318
Source:
Author’s calculations
94
Sex Composition
Figure 5.5
Index of sex composition in population of all ages
in states and Union Territories, 2011
95
Preliminary Demography of India
Figure 5.6
Index of sex composition in population aged 0-6 years
in states and Union Territories, 2011
96
Sex Composition
Figure 5.7
Index of sex composition in population aged 7 years and above
in states and Union Territories, 2011
97
Preliminary Demography of India
During the period 2001-2011, the population sex ratio turned more favourable to females and it
has increased in all but six states/Union Territories of the country. The six states/Union
Territories where the population sex ratio has decreased during the period under reference are
Bihar, Dadra and Nagar Haveli, Daman and Diu, Gujarat, Jammu and Kashmir, and
Lakshadweep. In Bihar, Gujarat and Lakshadweep, there has been only a marginal decrease in
the population sex ratio but the decrease has been very substantial in Daman and Diu where the
number of females per 1000 males decreased from 710 in 2001 to 618 in 2011. In Dadra and
Nagar Haveli also, the number of females per 1000 males decreased from 812 in 2001 to 775 in
2011. On the other hand, the increase in the population sex ratio was maximum in Delhi where
the number of females per 1000 males increased from 821 to 866 between 2001 and 2011. Other
states/Union Territories where there has been a substantial increase in the population sex ratio
are: Chandigarh, Mizoram, Puducherry, Andaman and Nicobar Islands, Arunachal Pradesh and
Kerala. Interestingly, in all major states of the country, except Kerala, there has not been any
significant change in the population sex ratio during the period under reference.
Unlike the population sex ratio, the sex ratio in the population aged 0-6 years decreased in all but
8 states/Union Territories of the country. The states/Union Territories where the sex ratio in the
population ages 0-6 years has improved during 2001 through 2011 are Andaman and Nicobar
Islands, Chandigarh, Gujarat, Haryana, Himachal Pradesh, Mizoram, Punjab and Tamil Nadu.
The gain in the sex ratio in the population aged 0-6 years has been the maximum in Punjab where
the number of females per 1000 males in the age group 0-6 years increased from 798 in 2001 to
846 in 2011. By contrast, in Haryana, the number of females per 1000 males in the age group 0-6
years recorded and the increase of only 11 points during this period. On the other hand, the
decrease in the sex ratio in the population aged 0-6 years has been very sharp in Jammu and
Kashmir and Dadra and Nagar Haveli. In Jammu and Kashmir, the sex ratio in the population
aged 0-6 years decreased from 941 in 2001 to 859 in 2011. This very rapid decrease in the sex
ratio in the population aged 0-6 years appears to be largely responsible for the decrease in the sex
ratio of the total population.
Finally, the sex ratio in the population aged 7 years and above increased in all but only four
states/Union Territories of the country. In Bihar, Dadra and Nagar Haveli, Daman and Diu and
Gujarat, the sex ratio has decreased between 2001 and 2011. In Dadra and Nagar Haveli and
Daman and Diu, the decrease in the sex ratio in the population aged 7 years and above has been
quite substantial but the decrease has been only marginal in Bihar and Gujarat. In Daman and
Diu, the sex ratio in the population aged 7 years and above decrease by a whopping 92 points from 682 females to 590 during the ten years between 2001 through 2011.
98
Sex Composition
Table 5.2 presents estimates of the index of sex composition for the states/Union Territories of
the country in the three population groups - total population, population aged 0-6 years and
population aged 7 years and above. For the total population, the index has been found to be
negative in 17 states/Union Territories which means that the ratio of females to males in these
states/Union Territories is smaller than that of the country as a whole. In the Union Territory of
Puducherry, the value of the index has been found to be zero whereas in the remaining
states/Union Territories, the index is positive which implies that the ratio of females to males in
these states/Union Territories is higher than that of the country as a whole. In the population aged
0-6 years, on the other hand, the index has been found to be negative in only 13 states/Union
Territories whereas in case of population aged 7 years and above, the index is negative again in
17 states/Union Territories.
For the total population, the index of sex composition varies from the highest in Kerala to the
lowest in Uttar Pradesh. In addition to Kerala, the index of sex composition has also been found
to be very high in Andhra Pradesh and Tamil Nadu. By comparison, the index has been found
to be exceptionally low in Bihar, Haryana and Maharashtra in addition to Uttar Pradesh. On the
other hand, the index of sex composition in the population aged 0-6 years was the highest in
West Bengal followed by Bihar whereas it was the lowest in Uttar Pradesh again. Other
states/Union Territories where the index of sex composition for the population aged 0-6 years
has been found to be very low at the 2011 population census are Maharashtra, Rajasthan and
Haryana. Similarly, the index of sex composition in the population aged 7 years and above has
been found to be the highest in Kerala followed by Tamil Nadu and Andhra Pradesh but was the
lowest in Uttar Pradesh followed by Bihar.
The states/Union Territories of the country can be grouped into four categories on the basis of
the index of sex composition in different population groups. The first category comprises of 16
states/Union Territories where the index is positive in all the three age groups. The second
category comprises of 10 states/Union Territories where the index is negative in all the three age
groups. The third category comprises of 7 states/Union Territories where the index is negative
in population of all ages and in population aged 7 years and above but positive in the population
aged 0-6 years. Finally, the fourth category comprises of only two states/Union Territories where
the index is positive in population of all ages and population aged 7 years and above but negative
in the population aged 0-6 years. Geographic continuity is very much apparent in the distribution
of the states/Union Territories according to these four categories. The index of sex composition
of the population is positive in all the southern and in most of the eastern states/Union Territories
of the country.
99
Preliminary Demography of India
Sex Composition in Districts
Among the districts of the country, the sex ratio varies widely in the total population as well as
in the population aged 0-6 years and the population aged 7 years and above. As regards the sex
ratio in the total population, there are 10 districts in the country where the number of females per
1000 males was enumerated to be more than 1100 at the 2011 population census. District Mahe
in Puducherry tops the districts of the country in terms of the most favourable sex ratio to females
as there were 1176 females for every 1000 males in the district at the 2011 population census.
Other districts where there were at least 1100 women for every 1000 men are Almora
(Uttarakhand), Kannur (Kerala), Pathanamthitta (Kerala), Ratnagiri (Maharashtra), Rudraprayag
(Uttarakhand), Kollam (Kerala), Thrissur (Kerala), Garhwal (Uttarakhand) and Alappuzha
(Kerala). On the other hand, district Daman in the Union Territory of Daman and Diu has the
lowest sex ratio in the country. There were only 533 females for every 1000 males in this district
according to the provisional figures of 2011 population census. Besides district Daman, district
Leh in Jammu and Kashmir is the only other district in the country with a sex ratio of less than
600 females for every 1000 males. In addition, in seven districts of the country, number of
females per 1000 males has been found to be less than 800 at the 2011 population census. These
districts are Tawang and West Kameng in Arunachal Pradesh, North District in Sikkim, Kargil
in Jammu and Kashmir, Dadra and Nagar Haveli, Nicobars in Andaman and Nicobar Islands and
Surat in Gujarat.
Table 5.3 gives the distribution of districts in different states/Union Territories by the level of the
sex ratio. In all, there are 145 districts in the country where number of females per 1000 males
have been enumerated to be less than 900. Most of these districts are located in Uttar Pradesh
(38), Haryana (19), Punjab (15), Jammu and Kashmir (14), Bihar (11) and Madhya Pradesh (10).
On the other hand, There are 98 districts where females out numbered males at the 2011
population census. Most of these districts are located in Tamil Nadu (15), Kerala (14), Andhra
Pradesh (11) and Orissa (10). In all the 14 districts of Kerala, females outnumbered males at the
2011 population census. Among the major states of the country, there was no district in five
states - Assam, Haryana, Punjab, Rajasthan and West Bengal - where females out numbered
males at the 2011 population census.
The within state, inter-district variability in the population sex ratio appears to be the highest in
Madhya Pradesh. In two districts of the state, there were less than 850 females for every 1000
males at the 2011 population census whereas in 4 districts females outnumbered males. Other
states where inter-district variability in the population sex ratio is quite substantial are Arunachal
Pradesh, Himachal Pradesh and Maharashtra.
100
Sex Composition
As regards inter-district variations in the sex ratio in the population aged 0-6 years is concerned,
the highest sex ratio has been estimated in district Lahul and Spiti in Himachal Pradesh where
there were 1013 females aged 0-6 years for every 1000 males aged 0-6 years at the 2011
population census. On the other hand, the sex ratio was the lowest in Jhajhjhar district in
Rajasthan where there were only 774 females aged 0-6 years for every 1000 males aged 0-6
years. In all, there are only three districts in the country where females outnumber males in the
age group 0-6 years. These districts are Dakshin Bastar (Dantewada) in Chhattisgarh, Tawang
in Arunachal Pradesh and Lahul and Spiti in Himachal Pradesh. On the other hand in 61 districts
of the country, there were less than 850 females 0-6 years for every 1000 males aged 0-6 years
at the 2011 population census. Most of these districts are located in Haryana (18), Punjab (11),
Jammu and Kashmir (7), Maharashtra (7) and Uttar Pradesh (6). In Haryana, the sex ratio in the
population aged 0-6 years has been found to be extremely unfavourable to females in 18 of the
21 districts. There has been some improvement in the sex ratio in the population aged 0-6 years
in Haryana and Punjab in recent years but still the sex ratio in the population aged 0-6 years
remains heavily unfavourable to females.
Compared to the sex ratio in the population aged 0-6 years, the sex ratio in the population aged
7 years and above appears to be more favourable to females. The highest sex ratio in this age
group is estimated to be in district Mahe of Puducherry where there were 1206 females aged 7
years and above for every 1000 males aged 7 years and above. In all, there were 116 districts in
the country where there were more females aged 7 years and above than males aged 7 years and
above at the 2011 population census. Most of these districts are located in Andhra Pradesh (13),
Chhattisgarh (10), Kerala (14), Orissa (10), Tamil Nadu (18) and Uttarakhand (10). In all the
districts of Kerala, females aged 7 years and above outnumbered males 7 years and above at the
2011 population census.
On the other side, there are 144 districts in the country where the sex ratio in the population aged
7 years and above remains highly unfavourable to females. In these districts, there were less than
900 females aged 7 years and above for every 1000 males aged 7 years and above. These districts
are mainly located in Uttar Pradesh (38), Haryana (16), Bihar (15), Jammu and Kashmir (15)
Punjab (12) and Madhya Pradesh (10). In 23 districts, the sex ratio in the population aged 7 years
and above has been found to be even less than 850 females for every 1000 males. These 23
districts include four districts of Arunachal Pradesh, three districts of Jammu and Kashmir and
two districts each in Uttar Pradesh, Rajasthan, Madhya Pradesh and Delhi. In Gujarat, Himachal
Pradesh and Maharashtra also, the sex ratio in the population aged 7 years and above has been
found to be less than 850 females for every 1000 males in one district each.
101
Preliminary Demography of India
Table 5.3
Distribution of districts by sex ratio in total population, 2011
State/Union Territory
Number of females per 1000 males
< 850
850-900 900-950 950-1000 $1000
AN Islands
1
1
1
0
0
Andhra Pradesh
0
0
1
11
11
Arunachal Pradesh
4
1
6
3
2
Assam
0
0
9
18
0
Bihar
0
11
25
1
1
Chandigarh
1
0
0
0
0
Chhattisgarh
0
0
0
11
7
Dadra and Nagar Haveli
1
0
0
0
0
Daman and Diu
1
0
0
0
1
Delhi
2
7
0
0
0
Goa
0
0
0
2
0
Gujarat
1
0
18
5
2
Haryana
0
19
2
0
0
Himachal Pradesh
1
1
4
3
3
Jammu and Kashmir
3
11
6
2
0
Jharkhand
0
0
13
10
1
Karnataka
0
0
2
23
5
Kerala
0
0
0
0
14
Lakshadweep
0
0
1
0
0
Madhya Pradesh
2
8
19
17
4
Maharashtra
1
2
21
9
2
Manipur
0
0
3
3
3
Meghalaya
0
0
1
4
2
Mizoram
0
0
3
4
1
Nagaland
0
1
6
4
0
Orissa
0
0
4
16
10
Puducherry
0
0
0
0
4
Punjab
0
15
3
2
0
Rajasthan
2
6
16
9
0
Sikkim
1
1
2
0
0
Tamil Nadu
0
0
1
16
15
Tripura
0
0
1
3
0
Uttar Pradesh
0
38
20
10
3
Uttarakhand
0
1
3
2
7
West Bengal
0
1
9
9
0
India
21
124
200
197
98
3.3
19.4
31.3
30.8
15.3
Source:
Author’s calculations
102
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Sex Composition
Figure 5.8
Females per 1000 males in districts, 2011
103
Preliminary Demography of India
Table 5.4
Distribution of districts by sex ratio in population aged 0-6 years
State/Union Territory
Number of females per 1000 males
< 850
850-900 900-950 950-1000 $1000
AN Islands
0
0
0
3
0
Andhra Pradesh
0
0
15
8
0
Arunachal Pradesh
1
0
3
11
1
Assam
0
0
5
22
0
Bihar
0
2
29
7
0
Chandigarh
0
1
0
0
0
Chhattisgarh
0
0
2
15
1
Dadra and Nagar Haveli
0
0
1
0
0
Daman and Diu
0
0
2
0
0
Delhi
1
7
1
0
0
Goa
0
0
2
0
0
Gujarat
3
13
9
1
0
Haryana
18
2
1
0
0
Himachal Pradesh
0
5
4
2
1
Jammu and Kashmir
7
9
5
1
0
Jharkhand
0
0
12
12
0
Karnataka
0
0
19
11
0
Kerala
0
0
2
12
0
Lakshadweep
0
0
1
0
0
Madhya Pradesh
3
8
34
5
0
Maharashtra
7
14
13
1
0
Manipur
0
0
9
0
0
Meghalaya
0
0
0
7
0
Mizoram
0
0
2
6
0
Nagaland
0
2
3
6
0
Orissa
0
4
15
11
0
Puducherry
0
0
1
3
0
Punjab
11
9
0
0
0
Rajasthan
3
21
9
0
0
Sikkim
0
1
3
0
0
Tamil Nadu
0
2
12
18
0
Tripura
0
0
2
2
0
Uttar Pradesh
6
27
36
2
0
Uttarakhand
1
9
3
0
0
West Bengal
0
0
13
6
0
India
61
136
268
172
3
9.5
21.3
41.9
26.9
0.5
Source:
Author’s calculations
104
Total
3
23
16
27
38
1
18
1
2
9
2
26
21
12
22
24
30
14
1
50
35
9
7
8
11
30
4
20
33
4
32
4
71
13
19
640
100.0
Sex Composition
Figure 5.9
Females per 1000 males in population aged 0-6 years in districts, 2011
105
Preliminary Demography of India
Table 5.5
Distribution of districts by sex ratio in population aged 7 years and above
State/Union Territory
Number of females per 1000 males
< 850
850-900 900-950 950-1000 $1000
Total
AN Islands
1
1
1
0
0
3
Andhra Pradesh
0
0
1
9
13
23
Arunachal Pradesh
4
2
5
3
2
16
Assam
0
0
11
16
0
27
Bihar
0
15
20
2
1
38
Chandigarh
1
0
0
0
0
1
Chhattisgarh
0
0
0
8
10
18
Dadra and Nagar Haveli
1
0
0
0
0
1
Daman and Diu
1
0
0
0
1
2
Delhi
2
7
0
0
0
9
Goa
0
0
0
2
0
2
Gujarat
1
0
16
7
2
26
Haryana
0
16
5
0
0
21
Himachal Pradesh
1
1
4
3
3
12
Jammu and Kashmir
3
12
4
3
0
22
Jharkhand
0
0
12
9
3
24
Karnataka
0
0
2
23
5
30
Kerala
0
0
0
0
14
14
Lakshadweep
0
0
0
1
0
1
Madhya Pradesh
2
8
18
17
5
50
Maharashtra
1
2
17
12
3
35
Manipur
0
0
2
3
4
9
Meghalaya
0
0
2
3
2
7
Mizoram
0
0
3
4
1
8
Nagaland
0
1
6
4
0
11
Orissa
0
0
3
17
10
30
Puducherry
0
0
0
0
4
4
Punjab
0
12
6
2
0
20
Rajasthan
2
5
11
12
3
33
Sikkim
1
1
2
0
0
4
Tamil Nadu
0
0
1
13
18
32
Tripura
0
0
1
3
0
4
Uttar Pradesh
2
36
19
10
4
71
Uttarakhand
0
1
3
1
8
13
West Bengal
0
1
9
9
0
19
India
23
121
184
196
116
640
3.6
18.9
28.8
30.6
18.1
100.0
Source:
Author’s calculations
106
Sex Composition
Figure 5.10
Females per 1000 males in population aged 7 years and above in districts, 2011
107
Preliminary Demography of India
Table 5.B presents the estimates of the index of sex composition for the districts of the country
as derived from the provisional figures of the 2011 population census while table 5.6 presents
the distribution of districts by states/Union Territories according to the index of sex composition
in the total population. The index of sex composition as defined by the equation (5.11) is the
weighted sum of the index of the intensity of sex composition at the district level where the
intensity of the sex composition is defined as the ratio of the female population to the male
population in the district to the corresponding ratio at the national level and weight is the index
of extensiveness of population in the district. When the the ratio of the female population to the
male population in a district is the same as the ratio of the female to male population in the
country as a whole, the index of the intensity of the sex composition is zero. The larger or smaller
is the ratio of female to male population from the corresponding ratio at the national level, the
higher or the lower is the index of the intensiveness of the sex composition in the district relative
to the sex composition for the country as a whole.
The analysis based on the provisional figures of the 2011 population census suggests that in 291
districts of the country, the index of sex composition has been found to be negative which means
that the ratio of the female population to the male population or the sex ratio in these districts is
lower than the national average. In addition, the sex ratio in the population has been estimated
to be very low in 57 districts of the country. Most of the districts with very low sex ratio of the
total population are located in Uttar Pradesh (25) and Bihar (9). In four districts of the National
Capital Territory of Delhi also, the index of sex composition has been found to be very low
according to provisional figures of the 2011 population census which means that the population
sex ratio in these districts is substantially lower than the corresponding ratio in the country as a
whole.
On the other hand, the index of the sex composition has been estimated to be higher than the
national average in 349 districts of the country and very high in 60 districts. This means that the
sex ratio in these districts is higher than the sex ratio at the national level. Most of the districts
with very high index of sex composition are located in only three states/Union Territories of the
country - Andhra Pradesh (20), Kerala (12) and Tamil Nadu (11). All the three states are located
in the southern part of the country. The situation is interesting in Uttar Pradesh where the index
of sex composition has been found to be very low in 25 districts and, at the same time, very high
in 5 districts according to the provisional figures of the 2011 population census. Districts with
a very low index of sex composition are located in the eastern part of the state whereas districts
with a very high index of sex composition are located in the western part of the state (Figure
5.11).
108
Sex Composition
Table 5.6
Index of sex composition in the total population
State/Union Territory
Index of sex composition
< -0.10 -0.10 to -0.05 -0.05 to 0 0 to 0.05
AN Islands
0
0
3
0
Andhra Pradesh
0
0
0
3
Arunachal Pradesh
0
0
10
6
Assam
0
0
3
24
Bihar
1
8
25
2
Chandigarh
0
1
0
0
Chhattisgarh
0
0
0
16
Dadra and Nagar Haveli
0
0
1
0
Daman and Diu
0
0
1
1
Delhi
1
3
5
0
Goa
0
0
0
2
Gujarat
2
0
14
10
Haryana
0
2
19
0
Himachal Pradesh
0
0
5
7
Jammu and Kashmir
0
0
20
2
Jharkhand
0
0
7
17
Karnataka
1
0
0
26
Kerala
0
0
0
2
Lakshadweep
0
0
0
1
Madhya Pradesh
0
3
23
23
Maharashtra
4
0
13
16
Manipur
0
0
2
7
Meghalaya
0
0
0
7
Mizoram
0
0
1
7
Nagaland
0
0
7
4
Orissa
0
0
2
26
Puducherry
0
0
0
4
Punjab
0
2
16
2
Rajasthan
0
3
15
15
Sikkim
0
0
4
0
Tamil Nadu
0
0
0
21
Tripura
0
0
0
4
Uttar Pradesh
7
17
30
12
Uttarakhand
0
0
4
9
West Bengal
0
1
4
14
India
16
40
234
290
2.5
6.3
36.6
45.3
Source:
Author’s calculations
109
$0.05 Total
0
3
20
23
0
16
0
27
2
38
0
1
2
18
0
1
0
2
0
9
0
2
0
26
0
21
0
12
0
22
0
24
3
30
12
14
0
1
1
50
2
35
0
9
0
7
0
8
0
11
2
30
0
4
0
20
0
33
0
4
11
32
0
4
5
71
0
13
0
19
60
640
9.4 100.0
Preliminary Demography of India
Figure 5.11
Index of sex composition in total population
in districts of India, 2011
110
Sex Composition
Table 5.7
Index of sex composition in the population aged 0-6 years
State/Union Territory
Index of sex composition
< -0.10 -0.10 to -0.05 -0.05 to 0 0 to 0.05
AN Islands
0
0
0
3
Andhra Pradesh
0
0
1
18
Arunachal Pradesh
0
0
1
15
Assam
0
0
0
25
Bihar
0
0
4
26
Chandigarh
0
0
1
0
Chhattisgarh
0
0
0
15
Dadra and Nagar Haveli
0
0
0
1
Daman and Diu
0
0
1
1
Delhi
0
2
7
0
Goa
0
0
1
1
Gujarat
2
1
16
7
Haryana
0
6
15
0
Himachal Pradesh
0
0
6
6
Jammu and Kashmir
0
2
14
6
Jharkhand
0
0
1
23
Karnataka
0
0
0
29
Kerala
0
0
0
13
Lakshadweep
0
0
1
0
Madhya Pradesh
0
3
18
29
Maharashtra
5
5
13
12
Manipur
0
0
1
8
Meghalaya
0
0
0
7
Mizoram
0
0
0
8
Nagaland
0
0
2
9
Orissa
0
0
6
24
Puducherry
0
0
0
4
Punjab
0
5
15
0
Rajasthan
1
5
22
5
Sikkim
0
0
1
3
Tamil Nadu
0
0
5
25
Tripura
0
0
0
4
Uttar Pradesh
5
6
35
23
Uttarakhand
0
0
11
2
West Bengal
0
0
0
11
India
13
35
198
363
2.0
5.5
30.9
56.7
Source:
Author’s calculations.
111
$0.05 Total
0
3
4
23
0
16
2
27
8
38
0
1
3
18
0
1
0
2
0
9
0
2
0
26
0
21
0
12
0
22
0
24
1
30
1
14
0
1
0
50
0
35
0
9
0
7
0
8
0
11
0
30
0
4
0
20
0
33
0
4
2
32
0
4
2
71
0
13
8
19
31
640
4.8 100.0
Preliminary Demography of India
Figure 5.12
Index of sex composition in population aged 0-6 years
in districts of India, 2011
112
Sex Composition
Table 5.8
Index of sex composition in population aged 7 years and above
State/Union Territory
Index of sex composition
< -0.10 -0.10 to -0.05 -0.05 to 0 0 to 0.05 $0.05 Total
AN Islands
0
0
3
0
0
3
Andhra Pradesh
0
0
1
1
21
23
Arunachal Pradesh
0
0
10
6
0
16
Assam
0
0
6
21
0
27
Bihar
1
9
25
1
2
38
Chandigarh
0
1
0
0
0
1
Chhattisgarh
0
0
0
16
2
18
Dadra and Nagar Haveli
0
0
1
0
0
1
Daman and Diu
0
0
1
1
0
2
Delhi
2
3
4
0
0
9
Goa
0
0
0
2
0
2
Gujarat
1
1
13
11
0
26
Haryana
0
1
20
0
0
21
Himachal Pradesh
0
0
5
7
0
12
Jammu and Kashmir
0
0
19
3
0
22
Jharkhand
0
0
7
17
0
24
Karnataka
1
0
0
26
3
30
Kerala
0
0
0
2
12
14
Lakshadweep
0
0
0
1
0
1
Madhya Pradesh
0
3
23
23
1
50
Maharashtra
4
0
11
18
2
35
Manipur
0
0
2
7
0
9
Meghalaya
0
0
1
6
0
7
Mizoram
0
0
3
5
0
8
Nagaland
0
0
7
4
0
11
Orissa
0
0
2
26
2
30
Puducherry
0
0
0
4
0
4
Punjab
1
1
16
2
0
20
Rajasthan
0
3
13
17
0
33
Sikkim
0
0
4
0
0
4
Tamil Nadu
0
0
0
19
13
32
Tripura
0
0
1
3
0
4
Uttar Pradesh
9
20
26
11
5
71
Uttarakhand
0
0
5
8
0
13
West Bengal
0
1
6
12
0
19
India
19
43
235
280
63
640
3.0
6.7
36.7
43.8
9.8 100.0
Source:
Author’s calculations
113
Preliminary Demography of India
Figure 5.13
Index of sex composition in population aged 7 years and above
in districts of India, 2011
114
Sex Composition
The distribution of the districts of the country according to the index of sex composition in the
population aged 0-6 years is given in table 5.7. According to the provisional figures of the 2011
population census, the index of sex composition has been found to be very low in 48 districts of
the country most which are located in Uttar Pradesh (11), Maharashtra (10), Haryana (6),
Rajasthan (6) and Punjab (5). In these districts, the sex ratio in the population aged 0-6 years is
substantially lower than the corresponding ratio in the country as a whole. In these districts, there
is a significant deficit of female children aged 0-6 years compared to the male children 0-6 years
of age, compared to the situation at the national level. On the other hand, the index of sex
composition has been found to be very high in 31 districts most of which are located in Bihar (8),
West Bengal (8) Andhra Pradesh (4) and Chhattisgarh (3). This means that the sex ratio of
population aged 0-6 years in these districts is significantly higher than the corresponding ratio
at the national level which indicates towards some substantial deficit of male children 0-6 years
of age compared to the situation at the national level.
Lastly, table 5.8 gives the distribution of the districts across the states/Union Territories of the
country according to the index of sex composition in the population aged 7 years and above.
This index has been calculated by taking the proportionate distribution of the population aged
7 years and above as weights. It may be seen from the table that the index of sex composition in
population aged 7 years and above was very low in 60 districts and very high in 65 districts
according to the 2011 population census. Most of the districts with a very low index of sex
composition in population aged 7 years and above are located in Uttar Pradesh (28), Bihar (10),
Delhi and Maharashtra (4 each) and Madhya Pradesh and Rajasthan (3 each). On the other hand,
most of the districts with a very high index of sex composition in the population aged 7 years and
above are located in Andhra Pradesh (21), Tamil Nadu (15), Kerala (12) and Uttar Pradesh (5).
An important factor affecting the sex composition of the population in the states/Union
Territories as well as in the districts of the country is the inter-state and inter-district migration
of the population in addition to sex ratio at birth and sex differentials in mortality. It is well
known that migration for any cause is always age and sex selective. This age and sex selectivity
implies that migration influences not only the sex ratio in the population of all ages combined
but also the sex ratio in the population of different age groups. As such, variations in the sex ratio
of the total population as well as the sex ratio in different age groups need to be analysed in the
context of variations in the sex ratio at birth, sex differentials in mortality in different age groups
and age and sex patterns of migration across the districts and state/Union Territories. The
provisional figures of the 2011 population census do not provide data which make it possible to
estimate the sex ratio at birth as well as mortality by sex and age and the age and sex structure
115
Preliminary Demography of India
of inter-state and inter-district migration. As such, it is not possible to explore the factors which
are responsible for the observed inter-state and inter-district variability in the sex ratio in the
population as a whole and in population of different age groups as revealed through the
provisional figures of the 2011 population census. It is however expected that once detailed data
of the 2011 population census are available, it will be possible to entangle the mystery of the sex
ratio of the population in the country.
116
6
Patterns of Inter-state Migration
Migration in India is not new. Historical accounts show that people have moved in search of
work, in response to environmental shocks and stresses, to escape religious persecution and
political conflict. However improved communication and transport networks, conflicts over
natural resources and new economic opportunities have created unprecedented levels of mobility.
In recent years, an important reason behind the movement of the people in India has been unequal
development across states and Union Territories of the country. Available evidence suggests that
Delhi and the states of Gujarat and Maharashtra are top destinations for the inter-state movement
of the labour force.
Estimates of inter-state migration in India are derived mainly from two sources - population
census and the National Sample Survey. Both the population census and the National Sample
Survey use the birth place and enumeration place data to estimate the migrant population in every
state and Union Territory of the country. According to the population census 2001, around 30 per
cent of the country’s population or around 307 million people were migrants. Of these, nearly
a third had migrated during the period 1991-2001. The 2001 population census also revealed that
there were 65.4 million female migrants and 32.8 million male migrants in the country and
majority (42.4 million) of the females migrated because of marriage whereas majority of males
(12.3 million) migrated for work and employment. The 2001 population census also suggested
that the inter-state migration in the country had grown by more than 53 per cent. Total number
of inter-state migrants was 42.3 million and Uttar Pradesh (-2.6 million) and Bihar (-1.7 million)
were the two states with the largest net out-migration.
117
Preliminary Demography of India
At the 2011 population census, the following questions related to migration were asked from
each individual:
1. Place of birth of the individual if the individual is not born at the place of enumeration. On
the basis of the answer to this question, it is possible to classify the enumerated population
into two groups:
1) migrants, defined as persons who are enumerated in a place different from the place
where they were born, and
2) non-migrants, defined as persons who are enumerated at the place where they were born.
2. For all migrant - persons who were born at a place other than the place of enumeration, the
following questions were asked:
a. Place of the last residence and whether the place of last residence was rural or urban.
b. Reasons for migration from the place of last residence to the place of enumeration.
Reasons included, 1) work or employment, 2) business, 3) education, 4) marriage, 5)
moved after birth, 6) moved with household and 7) other reasons.
c. Duration of stay in the place of enumeration since migration.
The birth-place enumeration-place data available through the population census can be used to
estimate life time migrants. At the same time, these data at two population censuses provide a
way of estimating the balance of inter-census migration. These data also help to analyse the net
balance into two components - net migration among persons from outside the administrative area
and net migration among persons born inside the administrative area. Answers of the above
questions can be analysed to estimate lifetime migrants. However, the provisional figures of the
2011 population census do not provide data related to the movement of the population and
reasons behind movement. It is however, possible to make a preliminary assessment of net
migratory flows across the states and Union Territories of the country during the period 20012011 using the indirect approach which is also termed as the vital statistics method (Shryock and
Siegel, 1976; United Nations, 1970). This approach is based on the concept that the population
increase between two points of time in any administrative area is the result of the natural increase
in the population (excess of live births over deaths during the period) and the net migratory
movement. If an estimate of the natural increase in the population of an administrative area
during the period under reference is available, then the difference between the enumerated and
the expected population gives an estimate of the net increase in the population due to migration.
Thus, if the estimates of the birth rate and the death rate for an administrative area are available
for different years of the period under reference, estimates of the natural increase in the
population can be made and the difference between the enumerated population and the estimated
population provides an idea about the net migratory flow.
118
Inter-state Migration
Using the aforesaid approach, we have made an attempt to estimate net migratory flows across
the states and Union Territories of the country during the period 2001-2011on the basis of the
provisional figures or the 2011 population census, population of states and Union Territories at
the 2001 population census and annual estimates of birth rate and death rate for India and for
each of its 35 states and Union Territories available through the sample registration system. The
following steps were involved in the estimation of the net migratory flows for each of the 35
states and Union Territories of the country:
Step 1. Using the final population totals of the 2001 population census as the base and
estimates of the birth rate and the death rate for different years of the period 2001 through 2010
available through the sample registration system, the expected population for the country and for
each of its 35 states and Union Territories for the year 2011 was estimated. Estimates of birth rate
and death rate for country and for its constituent states and Union Territories were however
available up to the year 2009 only. Linear regression analysis was used to estimate the birth rate
and the death rate for the year 2010.
Step 2. The estimated population so obtained was then compared with the provisional
population of the country and the provisional population of each of the 35 states and Union
Territories as revealed through the 2011 population census. It was assumed that the net
international migration from the country relative to its population is very small, almost
negligible. It was also assumed that the net omission rate in the 2001 and the 2011 population
census is more or less the same. In the 2001 population census, a net omission rate of 23.3 per
1000 population was estimated on the basis of the post enumeration survey (Government of India
2008).
Step 3. Using the difference between the enumerated and the estimated population, the crude
net migration rate (CNMR) was calculated for each state and Union Territory of the country for
the period 2001-2011. The crude net migration rate is defined as the ratio of the net migration
(in or out) in a state/Union Territory divided by the enumerated population of that state/Union
Territory and is presented as a multiple of 1000.
Like the population density, the crude net migration rate is also not a good indicator of migratory
flow across administrative or geographical units as it does not have multiplicative and additive
properties. Moreover, the crude net migration rate defined above does not give any idea about
the extent - magnitude as well as direction - of the internal migration in an administrative or
geographical unit. For example, the crude net migration rate can be calculated at the state/Union
territory level but the crude net migration rates estimated for different states and Union territories
of the country provide no idea about internal migration in the country as a whole. At the country
level, the crude net migration rate can be calculated in the international context only.
119
Preliminary Demography of India
One way to develop an alternative index of internal migration is to follow the approach used in
developing the index of population distribution across administrative or geographical areas. This
approach essentially combines a measure of extensiveness and a measure of intensiveness to
arrive at an index which takes into consideration both the extensiveness and intensiveness of the
distribution across administrative or geographical units. In the context of net migration across
states and Union territories, we develop an index of the extensiveness and an index of the
intensiveness of the movement of the population across states and Union Territories of the
country. To this end, let
Pcj =
Enumerated population of the state/Union Territory j,
Psj =
Population of the state/Union Territory j estimated on the basis of annual
estimates of the birth rate and the death rate.
The extensiveness of net migration for the state/Union Territory j is now defined as
Mej =
2*(*Pcj - Psj*/3*Pcj - Psj*)
(6.1)
while the intensiveness of net migration for the state/Union Territory j is defined as
Mij =
log (Pcj/Psj)
(6.2)
and the index of net migration for the state/Union Territory j is defined as
Mj =
Mej * Mij
(6.3)
Finally, the index of net internal migration for the country as a whole is defined as
M =
3Mj for all j.
(6.4)
Notice that when Pcj = Psj, Mj = 0 and the net migration for the state or Union Territory j is zero.
On the other hand when Pcj > Psj, Mj > 0 which indicates that there is net in-migration to the
state/Union Territory j. Similarly, when Pcj < Psj, Mj < 0 which means that there is net outmigration from the state/Union Territory j. Finally, the sum of Mj for all states and Union
Territories gives an idea about the magnitude and direction of internal migration in the country.
Notice that M is the weighted sum of Mj with weights equal to the index of the extensiveness of
inter-state migration.
Inter-state Migratory Flows in India
According to the provisional results of the 2011 population census, the enumerated population
of India was 1210.194 million whereas the estimated population based on the 2001 population
and the birth rate and the death rate for different years of the period 2001-2011 available through
the sample registration system was 1211.682 million (Table 6.1). This means that, at the country
level, the difference between the enumerated and the estimated population was only around 1.482
million or just 0.12 per cent which may be assumed to be negligible. In other words, the
population of the country was almost closed to the international migration during the period
120
Inter-state Migration
2001-2011. In order to make sure that the enumerated and the estimated population in the year
2011 are the same, we have adjusted the estimated population on a pro-rata basis. It is obvious
that this adjustment is very small.
We have carried out the similar exercise for all the states and Union Territories of the country.
This exercise has revealed that there has been net out-migration from 11 states/Union Territories
of the country while there has been net in-migration in the remaining states/Union territories
during the period 2001-2011. The total net out-migration from the 11 states/Union Territories
of the country during the 10-year period between 2001 and 2011was more than 12.83 million.
This was also the net in-migration in the 24 states and Union Territories of the country during
the same period. The 11 states and Union Territories where there was net out-migration during
the period 2001-2011 are, in order, Uttar Pradesh (6.58 million), Rajasthan (1.77 million), Kerala
(1.43 million), Madhya Pradesh (1.31 million), Andhra Pradesh (1.16 million), Nagaland (0.27
million), Assam (0.25 million). In addition, there was net out migration in Andaman and Nicobar
Islands, Sikkim, Lakshadweep and Bihar also but the quantum of net out migration was very
small. In Bihar, the net out migration during the period 2001-2011 is estimated to be
insignificant. This is in quite contrast to the situation during the period 1991-2001 when a very
substantial out migration from Bihar was observed. There are indications that there have been
significant return migration in Bihar during the period 2001-2011.
On the other hand, states and Union Territories where the in-migration was substantial during
the period 2001-2011 are, in order, Tamil Nadu (3.50 million), Maharashtra (3.03 million,
Jammu and Kashmir (0.96 million), Delhi (0.84 million), Karnataka (0.61 million), Gujarat (0.60
million and West Bengal (0.60 million). Some substantial net in-migration has also been
estimated in the newly created states of Jharkhand (0.42 million), Chhattisgarh (0.36 million) and
Uttarakhand (0.17 million). There has also been some very heavy in-migration to the Union
Territories of Dadra and Nagar Haveli (0.36 million) and Daman and Diu (0.20 million). These
patterns of inter-state migration revealed through the provisional figures of the 2011 population
census are on the expected lines. The migration streams revealed through the present analysis are
traditional migration streams. It appears that there has been little change in these migratory
streams during the period 2001-2011.
Table 6.1 also gives estimates of the crude net migration rate and the index of migration for the
states and Union Territories of the country. The crude net in-migration rate has been estimated
to be around 250 per 1000 population in the Union Territory of Daman and Diu which confirms
that there has been very substantial in-migration to this Union Territory during the period 2001121
Preliminary Demography of India
2011. Other states/Union Territories where the crude net in-migration was substantial during this
period are Dadra and Nagar Haveli (190), Puducherry (139), Jammu and Kashmir (76), Mizoram
(76), Arunachal Pradesh (64) and Manipur (63). Daman and Diu, Dadra and Nagar Haveli and
Puducherry are small Union Territories and even a small number of in-migrants to these Union
Territories lead to high net in-migration rates. At the same time, substantially high crude net inmigration rates in Jammu and Kashmir, Mizoram, Arunachal Pradesh and Manipur need further
analysis. Incidentally, the heavy net in-migration reported in Arunachal Pradesh, Manipur and
Mizoram is associated with a heavy net out-migration from Nagaland.
On the other hand, the crude net out-migration rate has been found to be around 136 per 1000
population in Nagaland meaning a very heavy net out migration from the state and which is the
lowest in the country. The crude net migration rate has also been found to be quite substantial
in Kerala. In Uttar Pradesh, the crude net migration rate has been found to be around 33 per 1000
population despite very heavy out migration from the state.
Regional patterns in inter-state migration are also clear from the table 6.1. In the north western
states of Jammu and Kashmir, Punjab, Uttarakhand and Delhi, there are clear indications of
substantial in-migration. The same is true for Manipur, Mizoram, Meghalaya and Tripura in the
north-east, Maharashtra, Daman and Diu and Dadra and Nagar Haveli in the west and Tamil
Nadu and Puducherry in the south. On the other hand, there has been some substantial outmigration from Madhya Pradesh, Rajasthan and Uttar Pradesh, all located in central India. These
three states are also amongst the least developed states of the country. The out-migration from
these states appears to be the out migration of the labour force in search of better livelihood and
employment opportunities. A similar situation appears to prevail in Andhra Pradesh where the
labour force appears to have moved in large numbers to Tamil Nadu and Maharashtra in search
of better livelihood opportunities. There has also been substantial out migration from Kerala
during the period under reference. Kerala has traditionally been an out migration state and this
tradition appears to have continued even today.
Out migration from Bihar during the period 2001-2011 has been estimated to be to be very small,
almost negligible. This trend is in quite contrast to the trend during the period 1991-2001 when
a very heavy out migration from the state was reported on the basis of the results of the 2001
population census. There are indications that there have been significant return migration to the
state, especially after the change in the political government. In any case, the preliminary results
of the 2011 population census suggest further investigation and analysis of in- and out-migration
from Bihar during the period 2001-2011.
122
Inter-state Migration
Figure 6.1
Crude net migration rate in states and Union Territories, 2011
123
Preliminary Demography of India
Table 6.1
Inter-state migration in India based on 2011 population census
Country/
Enumerated Estimated Adjusted
Net
state
population population population migration
2011
2011
2011
(million)
(million)
(million)
(million)
India
1210.194 1211.682 1210.194
Uttar Pradesh
199.582
206.417
206.164
-6.582
Kerala
33.388
34.863
34.820
-1.433
Rajasthan
68.621
70.473
70.386
-1.765
Nagaland
1.981
2.253
2.250
-0.270
Madhya Pradesh
72.598
73.996
73.906
-1.308
Andhra Pradesh
84.666
85.927
85.821
-1.156
Assam
31.169
31.454
31.415
-0.246
Andaman & Nicobar Islands
0.380
0.401
0.400
-0.020
Sikkim
0.608
0.625
0.625
-0.017
Lakshadweep
0.064
0.068
0.068
-0.004
Bihar
103.805
103.965
103.837
-0.033
Himachal Pradesh
6.857
6.855
6.847
0.010
Goa
1.458
1.447
1.445
0.012
Orissa
41.947
41.904
41.852
0.095
Haryana
25.353
25.281
25.250
0.103
Chandigarh
1.055
1.017
1.015
0.039
West Bengal
91.348
90.864
90.752
0.596
Punjab
27.704
27.406
27.372
0.332
Tripura
3.671
3.544
3.539
0.132
Chhattisgarh
25.540
25.213
25.182
0.358
Jharkhand
32.966
32.591
32.551
0.415
Arunachal Pradesh
1.383
1.296
1.294
0.088
Karnataka
61.131
60.605
60.530
0.601
Gujarat
60.384
59.847
59.773
0.610
Mizoram
1.091
1.010
1.009
0.083
Manipur
2.722
2.553
2.550
0.172
Uttarakhand
10.117
9.766
9.754
0.363
Dadra and Nagar Haveli
0.343
0.278
0.278
0.065
Meghalaya
2.964
2.768
2.765
0.199
Daman and Diu
0.243
0.182
0.182
0.061
Puducherry
1.244
1.072
1.071
0.173
Delhi
16.753
15.934
15.914
0.839
Jammu and Kashmir
12.549
11.600
11.586
0.963
Maharashtra
112.373
109.480
109.345
3.028
Tamil Nadu
72.139
68.728
68.644
3.495
Source:
Author’s calculations
124
(CNMR)
(per 1000)
-32.98
-42.91
-25.72
-136.25
-18.02
-13.65
-7.89
-53.40
-27.81
-60.55
-0.32
1.39
8.45
2.27
4.07
37.36
6.52
11.99
35.89
14.03
12.58
63.94
9.82
10.11
75.62
63.08
35.87
189.87
67.15
252.09
139.29
50.09
76.75
26.94
48.45
Inter-state Migration
Figure 6.2
Migration index in states and Union Territories, 2011
125
Preliminary Demography of India
Table 6.2
Migration index in India and states, 2011
Country/
Net migration
Index of
Index of
state
during
extensiveness intensiveness
2001-2011
(Mej)
(Mij)
(million)
India
-12.832
Uttar Pradesh
-6.582
0.5129
-0.0141
Kerala
-1.433
0.1116
-0.0182
Rajasthan
-1.765
0.1375
-0.0110
Nagaland
-0.270
0.0210
-0.0555
Madhya Pradesh
-1.308
0.1019
-0.0078
Andhra Pradesh
-1.156
0.0900
-0.0059
Assam
-0.246
0.0192
-0.0034
Andaman and Nicobar Islands
-0.020
0.0016
-0.0226
Sikkim
-0.017
0.0013
-0.0119
Lakshadweep
-0.004
0.0003
-0.0255
Bihar
-0.033
0.0026
-0.0001
Himachal Pradesh
0.010
0.0007
0.0006
Goa
0.012
0.0010
0.0037
Orissa
0.095
0.0074
0.0010
Haryana
0.103
0.0080
0.0018
Chandigarh
0.039
0.0031
0.0165
West Bengal
0.596
0.0464
0.0028
Punjab
0.332
0.0259
0.0052
Tripura
0.132
0.0103
0.0159
Chhattisgarh
0.358
0.0279
0.0061
Jharkhand
0.415
0.0323
0.0055
Arunachal Pradesh
0.088
0.0069
0.0287
Karnataka
0.601
0.0468
0.0043
Gujarat
0.610
0.0476
0.0044
Mizoram
0.083
0.0064
0.0341
Manipur
0.172
0.0134
0.0283
Uttarakhand
0.363
0.0283
0.0159
Dadra and Nagar Haveli
0.065
0.0051
0.0914
Meghalaya
0.199
0.0155
0.0302
Daman and Diu
0.061
0.0048
0.1261
Puducherry
0.173
0.0135
0.0651
Delhi
0.839
0.0654
0.0223
Jammu and Kashmir
0.963
0.0751
0.0347
Maharashtra
3.028
0.2359
0.0119
Tamil Nadu
3.495
0.2724
0.0220
Source:
Author’s calculations
126
Index of net
migration
(Mj)
-7.227
-2.037
-1.517
-1.167
-0.790
-0.530
-0.065
-0.036
-0.016
-0.008
0.000
0.000
0.004
0.007
0.014
0.051
0.132
0.136
0.163
0.171
0.178
0.198
0.201
0.210
0.220
0.379
0.449
0.464
0.468
0.602
0.880
1.459
2.603
2.798
5.875
Inter-state Migration
Table 6.2 presents estimates of the index of net migration for the states and Union Territories of
the country along with the index of extensiveness of migration and the index of the intensity of
the net migration defined above. The index of extensiveness of migration suggests that Uttar
Pradesh alone accounted for more than half of the total migratory flow in the country during the
period 2001-2011. At the same time, the index of the intensity of net migration in the state is
negative which means that the state has experienced net out migration during the period under
reference. Although, the index of the intensity of net migration in the state is low in comparison
to other states and Union Territories of the country, yet because of the very large share of the
migratory flow, the index of net migration for the state has been the lowest amongst all states and
Union Territories of the country (-7.2 per 1000 net migrants) indicating that the net out migration
from the state has been the largest in the country. Similarly, Tamil Nadu accounted for about 27
per cent of the net migrants in the country and the positive sign of the index of net migration
intensity suggests that the state has experienced substantial net in-migration during the period
under reference. Like Uttar Pradesh, Tamil Nadu also does not have a high index of the intensity
of net migration but the index of the extensiveness of het migration in the state is very high so
that the index of net migration is the highest in the country.
On the other hand, the index of the migration intensity has been found to be the highest in the
Union Territories of Daman and Diu and Dadra and Nagar Haveli. The Union Territory of
Daman and Diu, the net in-migration during the period 2001 through 2011 is estimated to be
more than 25 per cent of the population enumerated at the 2011 population census. In the Union
Territory of Dadra and Nagar Haveli, on the other hand, this proportion has been estimated to be
very close to 19 per cent. However, this high net in-migration intensity in these Union Territories
has been associated with a very low index of migration extensiveness so that the index of net
migration in these Union Territories is estimated to be very low. Obviously, the index of
migration calculated in table 6.2, takes into consideration both the severity or the intensity of net
migration and the extensiveness or the spread of the net migration across geographical or
administrative area. By contrast, the crude net migration rate takes into consideration only one
dimension of net migratory flow.
The approach adopted for the analysis of net migratory flows across states and Union territories
can also be applied to analyse net migratory flows across the districts. However, there is no other
source of estimating the birth rate and the death rate for the districts other than the population
census. One potential source of estimating district level birth and death rates in the country is the
civil registration system. However, there is serious under reporting of births and deaths under the
system despite the fact that registration of all births and deaths is compulsory under the Birth and
127
Preliminary Demography of India
Death Registration Act of 1967. In the absence of district level estimates of birth and death rates,
assessment of inter-district migratory flows is not possible. The only way of estimating patterns
of migration at the district level in the country is the analysis of the birth-place, enumerationplace data which is not yet available through the 2011 population census.
128
7
Epilogue
Population census in India, essentially, remains a descriptive statistical system, originally evolved
more than 150 years ago, and confined to delineating demographic, social and economic features
of the population. It continues to be adjunct to the normal administrative machinery and is ridden
piggyback of the public administration system. It remains an undertaking that instructs and
informs the administrator either at the national level or at the local level and gives the
administrative system a feel of the features and textures of the population stock - the size and the
structure of the population. Because of this preoccupation with the description of the statistical
and demographic information, there has rarely been any serious attempt to develop an analytical
system based on the huge data collected through population census at every 10 years of interval
to support population and development planning and programming directed towards the
development needs of the people and to facilitate monitoring and assessment of the impact of
development programmes and activities. The lack of the analytical rigour remains perhaps the
weakest component of the population census in India. As a result, the huge data collected during
each census remains largely unanalysed, especially at the lower levels of public administration
system where these data are the only source for analysing population and its growth and
distribution as well as its various social, cultural and economic characteristics. In order to meet
the information needs of the decentralised development planning, it is imperative that the huge
data available through the population census on a regular basis are analysed in a systematic
manner so as to reflect the population and development situation right up to the grass roots level.
There is however little orientation to this direction within the population census system in the
country.
129
Preliminary Demography of India
The routine, descriptive nature of the Indian population census is well reflected in the manner
the provisional results of the 2011 population census have been released. The Paper 1 of the 2011
population census released by the Registrar General and Census Commissioner of India for the
country as a whole. This paper contains the data collected during the 2011 population census for
the country as a whole and for its constituent states and Union Territories. On the other hand, for
the states and Union Territories of the country, state and Union Territory specific Paper 1 has
been released by the Census Commissioner of the specific state/ Union Territory. Interestingly,
no attempt has been made to present the data for the 640 districts of the country at one place and
in one publication. Even the papers presented by the Registrar General and Census Commissioner
of India and by Census Commissioner of different states/Union Territories present only a routine
description of the population situation in the country or in the specific state/Union Territory.
There have been little attempts to analyse even the preliminary results of the census in the context
of the population and in the context of social and economic development at the national, or
state/Union Territory or district level.
In this monograph, we have made an attempt to analyse the provisional figures of the 2011
population census in the context of information needs for decentralised district development
planning and programming as well as in the context of analysing the population and development
situation at the country, state/Union Territory and district level. In addition to estimating and
presenting conventional demographic indicators, we have also attempted to analyse spatial
patterns of the demographic situation across the 35 states/Union Territories and 640 districts of
the country as they existed at the time of the 2011 population census to present a national
perspective of demographic scenario of the country. It is expected that the present monograph
will serve as an important information support to decentralised district development planning in
the country.
The analysis of the provisional population data available through the 2001 population census
presented in the present monograph does not depict a very rosy picture of population transition
in the country and in its constituent states/Union Territories and districts. It appears that there has
been only a marginal change in the population scenario of the country during the 10-year period
between 2001-2011. There are unmistakable signs that population transition in India has
progressed and the average rate of population growth in the country has decrease at a faster pace
than before during the period 2001 through 2011. It also appears that, for the first time, the net
decadal addition to the population has decreased. Similarly, the decrease in the population aged
0-6 years indicates towards continued reduction in fertility in the country. However, the actual
growth of population between 2001 and 2011 has been faster than the population growth
130
Epilogue
projected by the Government of India on the basis of the results of the 2001 population census
and observed trends in fertility and mortality. Obviously, efforts to moderate the growth of the
population during 2001-2011 appear to have fallen short of the projected, most likely, path.
Provisional results of the 2011 population census also indicate that there is little possibility of
realising the expectations laid down in the National Population Policy 2000 and there is little
probability that the country will be able to reach stable population by the year 2045. The
provisional figures of the 2001 population census do not provide any indication that the country
will be able to achieve the cherished goal of population stabilisation by the year 2045 or even by
the year 2050 as enshrined in the National Population Policy 2000 until and unless serious efforts
are made to reinvigorate population stabilisation efforts in the country.
The provisional figures of the 2011 population census permit only a crude analysis of the age and
sex structure of the population. Even this analysis does not provide any solace as far as the
demographic transition in the country is concerned. There is every evidence to suggest that the
population of the country remains young and there appears very little transition in the age and
sex structure of the population. The analysis also depicts some extreme patterns of age and sex
composition of the population across the districts of the country that need further investigation
and analysis. At the same time, the provisional figures of the 2011 population census suggest a
rapid increase in the population aged 7 years and above which has implications for social and
economic development planning. Moreover, the inter-district variability in the demographic
situation revealed through the present analysis justifies the current emphasis on a decentralised
approach to population and development planning for meeting the development needs of the
people. The district level indicators of the age and sex structure of the population are expected
to be useful for planning, monitoring and evaluating population and development related
programmes at the districts level.
Another important observation of the analysis of the provisional figures of the 2011 population
census presented in this monograph is that out-migration from states like Uttar Pradesh,
Rajasthan, Madhya Pradesh and Andhra Pradesh continues unabated. Very little is currently
known about the demographic, social and economic characteristics of the migrant population in
the country as the detailed data about patterns of migration and demographic, social and
economic characteristics of the migrant population are not yet available through the 2011
population census. It is however generally believed that most of this out migration from the states
like Uttar Pradesh, Madhya Pradesh and Rajasthan is the distress migration of unskilled and
semi-skilled labour force in search of better livelihood opportunities as these three states remain
amongst the least developed states of the country. This distress migration has important
131
Preliminary Demography of India
implications to social and economic development processes at both the place of origin and at the
place of the destination. There are indications to suggest that the population of the country is
increasingly getting concentrated in selected pockets. Implications of such migratory flows need
to be explored in depth.
The provisional results of the 2011 population census do not provide the information necessary
to analyse the determinants of population growth - fertility, mortality and migration - and social
and economic characteristics of the population. Once detailed information is available through
the 2011 population census and from other sources, it would be possible to carry out a detailed
analysis of factors that have contributed to the population growth revealed through the 2011
population census. It will also be possible to analyse the contribution of population momentum
to the future population growth as more and more of the future population growth in India will
be the result of the momentum built in the age structure of the population. Evidence available
from the sample registration system and from other sources suggests that more and more states
and Union Territories in the country will be reaching replacement fertility in the years to come
and population momentum will therefore be primarily driving the future population growth in
the country. As of now, the provisional results of the 2011 population census present a mixed
scenario - good signs but bad omens.
132
References
Bhat PN Mari (2002) Completeness of India’s sample registration system: An assessment using
general growth balance method. Population Studies 56(2): 119-134.
Chaurasia Aalok Ranjan (2010) Mortality transition in India: 1985-2005. Asian Population
Studies 6(1): 47-68.
Chaurasia Alok Ranjan, Gulati SC (2008) India: The State of Population 2007. New Delhi,
National Population Commission and Oxford University Press.
Government of India (1983) Report on intensive enquiry conducted in a sub-sample of SRS units
(1980-81). New Delhi, Registrar General. Occasional Paper No. 2 of 1983.
Government of India (1988) Report on intensive enquiry conducted in a sub-sample of SRS
Units. New Delhi, Registrar General. Occasional Paper No. 1 of 1988.
Government of India (2000) National Population Policy 2000. New Delhi, Ministry of Health
and Family Welfare.
Government of India (2005) National Rural Health Mission. New Delhi, Ministry of Health and
Family Welfare.
Government of India (2006) Census of India 2001. Population Projections for India and States
2001-2026. Report of the Technical Group of Population Projections. New Delhi, Ministry
of Health and Family Welfare. National Commission on Population.
Government of India (2006) Census of India 2001. Report of the Post Enumeration Survey. New
Delhi, Office of the Registrar General and Census Commissioner.
Government of India (2011) Census of India 2011. Provisional Population Totals. Paper 1 of
2011. India, Series 1. New Delhi, Registrar General and Census Commissioner of India.
133
Preliminary Demography of India
Mitra A (1973) The census of India: Past and future. In A Bose, DB Gupta, G Raichaudhuri
(Eds) Population Statistics in India. Data Base of Indian Economy, Volume III. New Delhi,
Vikas Publishing House.
Shryock HS, Siegel J’S (1976) The Methods and Materials of Demography. New York,
Academic Press.
Swamy VS, Saxena AK, Palmore JA, Mishra V, Rele JR, Luther NY (1992) Evaluation of the
Sample Registration System using indirect estimates of fertility and mortality. New Delhi,
Office of the Registrar General and Census Commission of India. Occasional Paper 3 of
1992.
United Nations (1970) Manuals on Methods of Estimation. Manual VI: Methods of Measuring
Internal Migration. New York, Department of Economic and Social Affairs. Population
Studies No. 47.
United Nations (2011) World Population Prospects. 2011 Revision. New York, Department of
Economic and Social Affairs. Population Division.
134
Statistical Tables
Table 2.A
Population size and growth in districts of India
State/Union Territory/
Total population
Proportionate
District
increase
Andaman and Nicobars Islands
Nicobars
North & Middle Andaman
South Andaman
Andhra Pradesh
Adilabad
Anantapur
Chittoor
East Godavari
Guntur
Hyderabad
Karimnagar
Khammam
Krishna
Kurnool
Mahbubnagar
Medak
Nalgonda
Nizamabad
Prakasam
Rangareddy
Sri Potti Sriramulu Nellore
Srikakulam
Visakhapatnam
Vizianagaram
Warangal
West Godavari
Y.S.R.
Arunachal Pradesh
Anjaw
Changlang
Dibang Valley
East Kameng
East Siang
Kurung Kumey
Lohit
Lower Dibang Valley
Lower Subansiri
2011
2001
36819
105539
237586
42068
105613
208471
-12.48
-0.07
13.97
-1.33
-0.01
1.31
2737738
4083315
4170468
5151549
4889230
4010238
3811738
2798214
4529009
4046601
4042191
3031877
3483648
2552073
3392764
5296396
2966082
2699471
4288113
2342868
3522644
3934782
2884524
2488003
3640478
3745875
2601797
4901420
4465144
3829753
3491822
2578927
4187841
3529494
3513934
2670097
3247982
2668564
2345685
3059423
3575064
2537593
3832336
2249254
3246004
3803517
10.04
12.16
11.33
98.00
-0.25
-10.19
-0.47
-19.86
75.62
-3.37
14.53
-13.72
30.47
-21.43
27.14
125.79
-3.05
-24.49
68.98
-38.87
56.61
21.22
-24.16
0.96
1.15
1.07
6.83
-0.02
-1.07
-0.05
-2.21
5.63
-0.34
1.36
-1.48
2.66
-2.41
2.40
8.14
-0.31
-2.81
5.25
-4.92
4.49
1.92
-2.77
21089
147951
7948
78413
99019
89717
145538
53986
82839
18536
125422
7272
57179
87397
42518
124991
50448
55726
13.77
17.96
9.30
37.14
13.30
111.01
16.44
7.01
48.65
1.29
1.65
0.89
3.16
1.25
7.47
1.52
0.68
3.96
135
2001-2011
Average
annual
growth rate
2001-2011
Preliminary Demography of India
State/Union Territory/
District
Papum Pare
Tawang
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam
Baksa
Barpeta
Bongaigaon
Cachar
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
Tinsukia
Udalguri
Bihar
Araria
Arwal
Aurangabad
Banka
Total population
Proportionate
increase
2011
176385
49950
111997
35289
83205
87013
112272
2001
122003
38924
100326
55346
33363
74599
103918
953773
1693190
732639
1736319
481818
908090
688077
1948632
1327748
213529
1008959
1058674
659260
1091295
1517202
1260419
965280
1217002
886999
1040644
957853
2826006
769919
1150253
1925975
1316948
832769
857947
1394755
612665
1444921
433061
759858
571944
1566396
1185072
188079
822035
946279
542872
999221
1311698
1059578
813311
1007976
843243
889010
776256
2314629
689053
1051736
1665125
1150062
758746
11.17
21.40
19.58
20.17
11.26
19.51
20.30
24.40
12.04
13.53
22.74
11.88
21.44
9.21
15.67
18.95
18.69
20.74
5.19
17.06
23.39
22.09
11.74
9.37
15.67
14.51
9.76
1.06
1.94
1.79
1.84
1.07
1.78
1.85
2.18
1.14
1.27
2.05
1.12
1.94
0.88
1.46
1.74
1.71
1.88
0.51
1.57
2.10
2.00
1.11
0.90
1.46
1.36
0.93
2806200
699563
2511243
2029339
2158608
587826
2013055
1608773
30.00
19.01
24.75
26.14
2.62
1.74
2.21
2.32
136
2001-2011
44.57
28.33
11.63
-36.24
149.39
16.64
8.04
Average
annual
growth rate
2001-2011
3.69
2.49
1.1
-4.50
9.14
1.54
0.77
Statistical Tables
State/Union Territory/
District
Begusarai
Bhagalpur
Bhojpur
Buxar
Darbhanga
Gaya
Gopalganj
Jamui
Jehanabad
Kaimur (Bhabua)
Katihar
Khagaria
Kishanganj
Lakhisarai
Madhepura
Madhubani
Munger
Muzaffarpur
Nalanda
Nawada
Pashchim Champaran
Patna
Purba Champaran
Purnia
Rohtas
Saharsa
Samastipur
Saran
Sheikhpura
Sheohar
Sitamarhi
Siwan
Supaul
Vaishali
Chandigarh
Chandigarh
Chhattisgarh
Bastar
Bijapur
Bilaspur
Total population
Proportionate
increase
2011
2954367
3032226
2720155
1707643
3921971
4379383
2558037
1756078
1124176
1626900
3068149
1657599
1690948
1000717
1994618
4476044
1359054
4778610
2872523
2216653
3922780
5772804
5082868
3273127
2962593
1897102
4254782
3943098
634927
656916
3419622
3318176
2228397
3495249
2001
2349366
2423172
2243144
1402396
3295789
3473428
2152638
1398796
926489
1289074
2392638
1280354
1296348
802225
1526646
3575281
1137797
3746714
2370528
1809696
3043466
4718592
3939773
2543942
2450748
1508182
3394793
3248701
525502
515961
2682720
2714349
1732578
2718421
1054686
900635
17.10
1.58
1411644
255180
2662077
1198067
234637
1998355
17.83
8.76
33.21
1.64
0.84
2.87
137
2001-2011
25.75
25.13
21.27
21.77
19.00
26.08
18.83
25.54
21.34
26.21
28.23
29.46
30.44
24.74
30.65
25.19
19.45
27.54
21.18
22.49
28.89
22.34
29.01
28.66
20.89
25.79
25.33
21.37
20.82
27.32
27.47
22.25
28.62
28.58
Average
annual
growth rate
2001-2011
2.29
2.24
1.93
1.97
1.74
2.32
1.73
2.27
1.93
2.33
2.49
2.58
2.66
2.21
2.67
2.25
1.78
2.43
1.92
2.03
2.54
2.02
2.55
2.52
1.90
2.29
2.26
1.94
1.89
2.42
2.43
2.01
2.52
2.51
Preliminary Demography of India
State/Union Territory/
District
Dakshin Bastar Dantewada
Dhamtari
Durg
Janjgir - Champa
Jashpur
Kabeerdham
Korba
Koriya
Mahasamund
Narayanpur
Raigarh
Raipur
Rajnandgaon
Surguja
Uttar Bastar Kanker
Dadra and Nagar Haveli
Dadra & Nagar Haveli
Daman and Diu
Daman
Diu
Delhi
Central
East
New Delhi
North
North East
North West
South
South West
West
Goa
North Goa
South Goa
Gujarat
Ahmadabad
Amreli
Anand
Banas Kantha
Bharuch
Bhavnagar
Total population
Proportionate
increase
2011
532791
799199
3343079
1620632
852043
822239
1206563
659039
1032275
140206
1493627
4062160
1537520
2361329
748593
2001
476119
706591
2810436
1317431
743160
584552
1011823
586327
860257
117337
1265529
3016930
1283224
1972094
650934
342853
220490
55.50
4.41
190855
52056
113989
44215
67.43
17.73
5.15
1.63
578671
1707725
133713
883418
2240749
3651261
2733752
2292363
2531583
646385
1463583
179112
781525
1768061
2860869
2267023
1755041
2128908
-10.48
16.68
-25.35
13.04
26.73
27.63
20.59
30.62
18.91
-1.11
1.54
-2.92
1.23
2.37
2.44
1.87
2.67
1.73
817761
639962
758573
589095
7.80
8.63
0.75
0.83
7208200
1513614
2090276
3116045
1550822
2877961
5893164
1393918
1856872
2504244
1370656
2469630
22.31
8.59
12.57
24.43
13.14
16.53
2.01
0.82
1.18
2.19
1.23
1.53
138
2001-2011
11.90
13.11
18.95
23.01
14.65
40.66
19.25
12.40
20.00
19.49
18.02
34.65
19.82
19.74
15.00
Average
annual
growth rate
2001-2011
1.12
1.23
1.74
2.07
1.37
3.41
1.76
1.17
1.82
1.78
1.66
2.97
1.81
1.80
1.40
Statistical Tables
State/Union Territory/
District
Dohad
Gandhinagar
Jamnagar
Junagadh
Kachchh
Kheda
Mahesana
Narmada
Navsari
Panch Mahals
Patan
Porbandar
Rajkot
Sabar Kantha
Surat
Surendranagar
Tapi
The Dangs
Vadodara
Valsad
Haryana
Ambala
Bhiwani
Faridabad
Fatehabad
Gurgaon
Hisar
Jhajhjhar
Jind
Kaithal
Karnal
Kurukshetra
Mahendragarh
Mewat
Palwal
Panchkula
Panipat
Rewari
Rohtak
Sirsa
Total population
2011
2126558
1387478
2159130
2742291
2090313
2298934
2027727
590379
1330711
2388267
1342746
586062
3799770
2427346
6079231
1755873
806489
226769
4157568
1703068
2001
1636433
1237168
1904278
2448173
1583225
2037894
1844856
514404
1229463
2025277
1182709
536835
3169881
2082531
4275540
1515148
719634
186729
3641802
1410553
1136784
1629109
1798954
941522
1514085
1742815
956907
1332042
1072861
1506323
964231
921680
1089406
1040493
558890
1202811
896129
1058683
1295114
1014442
1425043
1365430
806167
870514
1537145
880076
1189854
946169
1274169
825470
812554
789768
829144
468396
967434
765334
940132
1116670
139
Proportionate
increase
2001-2011
29.95
12.15
13.38
12.01
32.03
12.81
9.91
14.77
8.24
17.92
13.53
9.17
19.87
16.56
42.19
15.89
12.07
21.44
14.16
20.74
12.06
14.32
31.75
16.79
73.93
13.38
8.73
11.95
13.39
18.22
16.81
13.43
37.94
25.49
19.32
24.33
17.09
12.61
15.98
Average
annual
growth rate
2001-2011
2.62
1.15
1.26
1.13
2.78
1.21
0.95
1.38
0.79
1.65
1.27
0.88
1.81
1.53
3.52
1.47
1.14
1.94
1.32
1.88
1.14
1.34
2.76
1.55
5.53
1.26
0.84
1.13
1.26
1.67
1.55
1.26
3.22
2.27
1.77
2.18
1.58
1.19
1.48
Preliminary Demography of India
State/Union Territory/
District
Sonipat
Yamunanagar
Himachal Pradesh
Bilaspur
Chamba
Hamirpur
Kangra
Kinnaur
Kullu
Lahul & Spiti
Mandi
Shimla
Sirmaur
Solan
Una
Jammu and Kashmir
Anantnag
Badgam
Bandipore
Baramula
Doda
Ganderbal
Jammu
Kargil
Kathua
Kishtwar
Kulgam
Kupwara
Leh(Ladakh)
Pulwama
Punch
Rajouri
Ramban
Reasi
Samba
Shupiyan
Srinagar
Udhampur
Jharkhand
Bokaro
Total population
Proportionate
increase
2011
1480080
1214162
2001
1279129
1041663
382056
518844
454293
1507223
84298
437474
31528
999518
813384
530164
576670
521057
340885
460887
412700
1339030
78334
381571
33224
901344
722502
458593
500557
448273
12.08
12.58
10.08
12.56
7.61
14.65
-5.10
10.89
12.58
15.61
15.21
16.24
1.14
1.18
0.96
1.18
0.73
1.37
-0.52
1.03
1.18
1.45
1.42
1.50
1070144
735753
385099
1015503
409576
297003
1526406
143388
615711
231037
422786
875564
147104
570060
476820
619266
283313
314714
318611
265960
1269751
555357
778408
607181
304886
843892
320256
217907
1357077
119307
511455
190843
394026
650393
117232
441275
372613
483284
214944
247694
272539
211332
1027670
459486
37.48
21.18
26.31
20.34
27.89
36.30
12.48
20.18
20.38
21.06
7.30
34.62
25.48
29.18
27.97
28.14
31.81
27.06
16.90
25.85
23.56
20.86
3.18
1.92
2.34
1.85
2.46
3.10
1.18
1.84
1.86
1.91
0.70
2.97
2.27
2.56
2.47
2.48
2.76
2.39
1.56
2.30
2.12
1.90
2061918
1777669
15.99
1.48
140
2001-2011
15.71
16.56
Average
annual
growth rate
2001-2011
1.46
1.53
Statistical Tables
State/Union Territory/
District
Chatra
Deoghar
Dhanbad
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Jamtara
Khunti
Kodarma
Latehar
Lohardaga
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Saraikela-Kharsawan
Simdega
Karnataka
Bagalkot
Bangalore
Bangalore Rural
Belgaum
Bellary
Bidar
Bijapur
Chamarajanagar
Chikkaballapura
Chikmagalur
Chitradurga
Dakshina Kannada
Davanagere
Dharwad
Gadag
Gulbarga
Total population
2011
1042304
1491879
2682662
1321096
1322387
2445203
1311382
1025656
1734005
790207
530299
717169
725673
461738
899200
1936319
1501619
2291032
949159
2912022
1150038
1063458
599813
2001
808113
1165348
2397160
1106538
1035461
1905402
1047932
832445
1378930
653064
434814
540892
560885
364520
701678
1537493
1233971
1983062
839518
2350300
927749
848865
514331
1890826
9588910
987257
4778439
2532383
1700018
2175102
1020962
1254377
1137753
1660378
2083625
1946905
1846993
1065235
2564892
1651954
6537299
850937
4214534
2027204
1502314
1806863
965449
1149013
1140948
1517852
1897655
1790916
1604267
971841
2174743
141
Proportionate
increase
2001-2011
28.98
28.02
11.91
19.39
27.71
28.33
25.14
23.21
25.75
21.00
21.96
32.59
29.38
26.67
28.15
25.94
21.69
15.53
13.06
23.90
23.96
25.28
16.62
14.46
46.68
16.02
13.38
24.92
13.16
20.38
5.75
9.17
-0.28
9.39
9.80
8.71
15.13
9.61
17.94
Average
annual
growth rate
2001-2011
2.54
2.47
1.13
1.77
2.45
2.49
2.24
2.09
2.29
1.91
1.99
2.82
2.58
2.36
2.48
2.31
1.96
1.44
1.23
2.14
2.15
2.25
1.54
1.35
3.83
1.49
1.26
2.23
1.24
1.85
0.56
0.88
-0.03
0.90
0.93
0.84
1.41
0.92
1.65
Preliminary Demography of India
State/Union Territory/
District
Hassan
Haveri
Kodagu
Kolar
Koppal
Mandya
Mysore
Raichur
Ramanagara
Shimoga
Tumkur
Udupi
Uttara Kannada
Yadgir
Kerala
Alappuzha
Ernakulam
Idukki
Kannur
Kasaragod
Kollam
Kottayam
Kozhikode
Malappuram
Palakkad
Pathanamthitta
Thiruvananthapuram
Thrissur
Wayanad
Lakshadweep
Lakshadweep
Madhya Pradesh
Alirajpur
Anuppur
Ashoknagar
Balaghat
Barwani
Betul
Bhind
Bhopal
Total population
Proportionate
increase
2011
1776221
1598506
554762
1540231
1391292
1808680
2994744
1924773
1082739
1755512
2681449
1177908
1436847
1172985
2001
1721645
1439058
548563
1387096
1196090
1763706
2641101
1669795
1030591
1642507
2584778
1112283
1353601
956212
2121943
3279860
1107453
2525637
1302600
2629703
1979384
3089543
4110956
2810892
1195537
3307284
3110327
816558
2109160
3105798
1129221
2408956
1204078
2585208
1953646
2879131
3625471
2617482
1234016
3234356
2974232
780619
0.61
5.60
-1.93
4.84
8.18
1.72
1.32
7.31
13.39
7.39
-3.12
2.25
4.58
4.60
0.06
0.55
-0.19
0.47
0.79
0.17
0.13
0.71
1.26
0.71
-0.32
0.22
0.45
0.45
64429
60650
6.23
0.60
728677
749521
844979
1701156
1385659
1575247
1703562
2368145
610282
667427
689216
1497496
1086791
1395259
1427965
1842914
19.40
12.30
22.60
13.60
27.50
12.90
19.30
28.50
1.77
1.16
2.04
1.28
2.43
1.21
1.76
2.51
142
2001-2011
3.17
11.08
1.13
11.04
16.32
2.55
13.39
15.27
5.06
6.88
3.74
5.90
6.15
22.67
Average
annual
growth rate
2001-2011
0.31
1.05
0.11
1.05
1.51
0.25
1.26
1.42
0.49
0.67
0.37
0.57
0.60
2.04
Statistical Tables
State/Union Territory/
District
Burhanpur
Chhatarpur
Chhindwara
Damoh
Datia
Dewas
Dhar
Dindori
East Nimar
Guna
Gwalior
Harda
Hoshangabad
Indore
Jabalpur
Jhabua
Katni
Mandla
Mandsaur
Morena
Narsimhapur
Neemuch
Panna
Raisen
Rajgarh
Ratlam
Rewa
Sagar
Satna
Sehore
Seoni
Shahdol
Shajapur
Sheopur
Shivpuri
Sidhi
Singrauli
Tikamgarh
Ujjain
Umaria
Total population
2011
756993
1762857
2090306
1263703
786375
1563107
2184672
704218
1309443
1240938
2030543
570302
1240975
3272335
2460714
1024091
1291684
1053522
1339832
1965137
1092141
825958
1016028
1331699
1546541
1454483
2363744
2378295
2228619
1311008
1378876
1064989
1512353
687952
1725818
1126515
1178132
1444920
1986597
643579
143
2001
635061
1475194
1849828
1083793
664168
1308039
1740775
580559
1078619
977887
1632269
474461
1083821
2465965
2150974
784143
1063990
894331
1183597
1592494
958018
725798
856685
1124746
1254291
1215107
1973075
2022360
1869647
1079019
1166562
907919
1290404
559311
1406535
910683
920416
1203097
1711109
516102
Proportionate
increase
2001-2011
19.20
19.50
13.00
16.60
18.40
19.50
25.50
21.30
21.40
26.90
24.40
20.20
14.50
32.70
14.40
30.60
21.40
17.80
13.20
23.40
14.00
13.80
18.60
18.40
23.30
19.70
19.80
17.60
19.20
21.50
18.20
17.30
17.20
23.00
22.70
23.70
28.00
20.10
16.10
24.70
Average
annual
growth rate
2001-2011
1.76
1.78
1.22
1.54
1.69
1.78
2.27
1.93
1.94
2.38
2.18
1.84
1.35
2.83
1.35
2.67
1.94
1.64
1.24
2.10
1.31
1.29
1.71
1.69
2.09
1.80
1.81
1.62
1.76
1.95
1.67
1.60
1.59
2.07
2.05
2.13
2.47
1.83
1.49
2.21
Preliminary Demography of India
State/Union Territory/
District
Vidisha
West Nimar
Maharashtra
Ahmadnagar
Akola
Amravati
Aurangabad
Bhandara
Bid
Buldana
Chandrapur
Dhule
Gadchiroli
Gondiya
Hingoli
Jalgaon
Jalna
Kolhapur
Latur
Mumbai
Mumbai Suburban
Nagpur
Nanded
Nandurbar
Nashik
Osmanabad
Parbhani
Pune
Raigarh
Ratnagiri
Sangli
Satara
Sindhudurg
Solapur
Thane
Wardha
Washim
Yavatmal
Manipur
Bishnupur
Total population
Proportionate
increase
2011
1458212
1872413
2001
1215177
1524766
4543083
1818617
2887826
3695928
1198810
2585962
2588039
2194262
2048781
1071795
1322331
1178973
4224442
1958483
3874015
2455543
3145966
9332481
4653171
3356566
1646177
6109052
1660311
1835982
9426959
2635394
1612672
2820575
3003922
848868
4315527
11054131
1296157
1196714
2775457
4040642
1630239
2607160
2897013
1136146
2161250
2232480
2071101
1707947
970294
1200707
987160
3682690
1612980
3523162
2080285
3338031
8640419
4067637
2876259
1311709
4993796
1486586
1527715
7232555
2207929
1696777
2583524
2808994
868825
3849543
8131849
1236736
1020216
2458271
12.43
11.56
10.77
27.58
5.52
19.65
15.93
5.95
19.96
10.46
10.13
19.43
14.71
21.42
9.96
18.04
-5.75
8.01
14.39
16.70
25.50
22.33
11.69
20.18
30.34
19.36
-4.96
9.18
6.94
-2.30
12.10
35.94
4.80
17.30
12.90
1.17
1.09
1.02
2.44
0.54
1.79
1.48
0.58
1.82
0.99
0.96
1.78
1.37
1.94
0.95
1.66
-0.59
0.77
1.34
1.54
2.27
2.02
1.11
1.84
2.65
1.77
-0.51
0.88
0.67
-0.23
1.14
3.07
0.47
1.60
1.21
240363
208368
15.36
1.43
144
2001-2011
20.00
22.80
Average
annual
growth rate
2001-2011
1.82
2.05
Statistical Tables
State/Union Territory/
District
Chandel
Churachandpur
Imphal East
Imphal West
Senapati
Tamenglong
Thoubal
Ukhrul
Meghalaya
East Garo Hills
East Khasi Hills
Jaintia Hills
Ribhoi
South Garo Hills
West Garo Hills
West Khasi Hills
Mizoram
Aizawl
Champhai
Kolasib
Lawngtlai
Lunglei
Mamit
Saiha
Serchhip
Nagaland
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Orissa
Anugul
Balangir
Total population
Proportionate
increase
2011
144028
271274
452661
514683
354972
140143
420517
183115
2001
118327
227905
394876
444382
156513
111499
364140
140778
317618
824059
392852
258380
142574
642923
385601
250582
660923
299108
192790
100980
518390
296049
26.75
24.68
31.34
34.02
41.19
24.02
30.25
2.37
2.21
2.73
2.93
3.45
2.15
2.64
404054
125370
83054
117444
154094
85757
56366
64875
325676
108392
65960
73620
137223
62785
61056
53861
24.07
15.66
25.92
59.53
12.29
36.59
-7.68
20.45
2.16
1.46
2.30
4.67
1.16
3.12
-0.80
1.86
379769
74033
270063
50593
193171
250671
94954
163294
196801
166239
141014
309024
106136
213259
158300
232085
260652
96825
148195
150365
161223
153955
22.89
-30.25
26.64
-68.04
-16.77
-3.83
-1.93
10.19
30.88
3.11
-8.41
2.06
-3.60
2.36
-11.41
-1.84
-0.39
-0.20
0.97
2.69
0.31
-0.88
1271703
1648574
1140003
1337194
11.55
23.29
1.09
2.09
145
2001-2011
21.72
19.03
14.63
15.82
126.80
25.69
15.48
30.07
Average
annual
growth rate
2001-2011
1.97
1.74
1.37
1.47
8.19
2.29
1.44
2.63
Preliminary Demography of India
State/Union Territory/
District
Baleshwar
Bargarh
Baudh
Bhadrak
Cuttack
Debagarh
Dhenkanal
Gajapati
Ganjam
Jagatsinghapur
Jajapur
Jharsuguda
Kalahandi
Kandhamal
Kendrapara
Kendujhar
Khordha
Koraput
Malkangiri
Mayurbhanj
Nabarangapur
Nayagarh
Nuapada
Puri
Rayagada
Sambalpur
Subarnapur
Sundargarh
Puducherry
Karaikal
Mahe
Puducherry
Yanam
Punjab
Amritsar
Barnala
Bathinda
Faridkot
Fatehgarh Sahib
Firozpur
Total population
Proportionate
increase
2011
2317419
1478833
439917
1506522
2618708
312164
1192948
575880
3520151
1136604
1826275
579499
1573054
731952
1439891
1802777
2246341
1376934
612727
2513895
1218762
962215
606490
1697983
961959
1044410
652107
2080664
2001
2024508
1346336
373372
1333749
2341094
274108
1066878
518837
3160635
1057629
1624341
509716
1335494
648201
1302005
1561990
1877395
1180637
504198
2223456
1025766
864516
530690
1502682
831109
935613
541835
1830673
200314
41934
946600
55616
170791
36828
735332
31394
17.29
13.86
28.73
77.15
1.59
1.30
2.53
5.72
2490891
596294
1388859
618008
599814
2026831
2156989
526948
1183317
550907
538481
1746064
15.48
13.16
17.37
12.18
11.39
16.08
1.44
1.24
1.60
1.15
1.08
1.49
146
2001-2011
14.47
9.84
17.82
12.95
11.86
13.88
11.82
10.99
11.37
7.47
12.43
13.69
17.79
12.92
10.59
15.42
19.65
16.63
21.53
13.06
18.81
11.30
14.28
13.00
15.74
11.63
20.35
13.66
Average
annual
growth rate
2001-2011
1.35
0.94
1.64
1.22
1.12
1.30
1.12
1.04
1.08
0.72
1.17
1.28
1.64
1.22
1.01
1.43
1.79
1.54
1.95
1.23
1.72
1.07
1.34
1.22
1.46
1.10
1.85
1.28
Statistical Tables
State/Union Territory/
District
Gurdaspur
Hoshiarpur
Jalandhar
Kapurthala
Ludhiana
Mansa
Moga
Muktsar
Patiala
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Shahid Bhagat Singh Nagar
Tarn Taran
Rajasthan
Ajmer
Alwar
Banswara
Baran
Barmer
Bharatpur
Bhilwara
Bikaner
Bundi
Chittaurgarh
Churu
Dausa
Dhaulpur
Dungarpur
Ganganagar
Hanumangarh
Jaipur
Jaisalmer
Jalor
Jhalawar
Jhunjhunun
Jodhpur
Karauli
Kota
Nagaur
Total population
2011
2299026
1582793
2181753
817668
3487882
768808
992289
902702
1892282
683349
986147
1654408
614362
1120070
2001
2103409
1481322
1962714
754515
3032941
688773
894760
777521
1584826
628829
746968
1473204
587456
939026
2584913
3671999
1798194
1223921
2604453
2549121
2410459
2367745
1113725
1544392
2041172
1637226
1207293
1388906
1969520
1779650
6663971
672008
1830151
1411327
2139658
3685681
1458459
1950491
3309234
2178420
2991445
1420599
1021466
1964883
2099943
2021010
1902109
962597
1330340
1696030
1323011
983298
1107669
1789497
1517955
5250942
508250
1448936
1180335
1913655
2886429
1205936
1568675
2775039
147
Proportionate
increase
2001-2011
9.30
6.85
11.16
8.37
15.00
11.62
10.90
16.10
19.40
8.67
32.02
12.30
4.58
19.28
18.66
22.75
26.58
19.82
32.55
21.39
19.27
24.48
15.70
16.09
20.35
23.75
22.78
25.39
10.06
17.24
26.91
32.22
26.31
19.57
11.81
27.69
20.94
24.34
19.25
Average
annual
growth rate
2001-2011
0.89
0.66
1.06
0.80
1.40
1.10
1.03
1.49
1.77
0.83
2.78
1.16
0.45
1.76
1.71
2.05
2.36
1.81
2.82
1.94
1.76
2.19
1.46
1.49
1.85
2.13
2.05
2.26
0.96
1.59
2.38
2.79
2.34
1.79
1.12
2.44
1.90
2.18
1.76
Preliminary Demography of India
State/Union Territory/
District
Pali
Pratapgarh
Rajsamand
Sawai Madhopur
Sikar
Sirohi
Tonk
Udaipur
Sikkim
East District
North District
South District
West District
Tamil Nadu
Ariyalur
Chennai
Coimbatore
Cuddalore
Dharmapuri
Dindigul
Erode
Kancheepuram
Kanniyakumari
Karur
Krishnagiri
Madurai
Nagapattinam
Namakkal
Perambalur
Pudukkottai
Ramanathapuram
Salem
Sivaganga
Thanjavur
The Nilgiris
Theni
Thiruvallur
Thiruvarur
Thoothukkudi
Tiruchirappalli
Total population
Proportionate
increase
2011
2038533
868231
1158283
1338114
2677737
1037185
1421711
3067549
2001
1820281
706798
982512
1117050
2287882
851128
1211720
2481234
281293
43354
146742
136299
245040
41030
131525
123256
14.79
5.66
11.57
10.58
1.38
0.55
1.09
1.01
752481
4681087
3472578
2600880
1502900
2161367
2259608
3990897
1863174
1076588
1883731
3041038
1614069
1721179
564511
1618725
1337560
3480008
1341250
2402781
735071
1243684
3725697
1268094
1738376
2713858
695524
4343645
2916620
2285395
1295182
1923014
2016582
2877468
1676034
935686
1561118
2578201
1488839
1493462
493646
1459601
1187604
3016346
1155356
2216138
762141
1093950
2754756
1169474
1592769
2418366
8.19
7.77
19.06
13.80
16.04
12.39
12.05
38.69
11.17
15.06
20.67
17.95
8.41
15.25
14.36
10.90
12.63
15.37
16.09
8.42
-3.55
13.69
35.25
8.43
9.14
12.22
0.79
0.75
1.74
1.29
1.49
1.17
1.14
3.27
1.06
1.40
1.88
1.65
0.81
1.42
1.34
1.03
1.19
1.43
1.49
0.81
-0.36
1.28
3.02
0.81
0.87
1.15
148
2001-2011
11.99
22.84
17.89
19.79
17.04
21.86
17.33
23.63
Average
annual
growth rate
2001-2011
1.13
2.06
1.65
1.81
1.57
1.98
1.60
2.12
Statistical Tables
State/Union Territory/
District
Tirunelveli
Tiruppur
Tiruvannamalai
Vellore
Viluppuram
Virudhunagar
Tripura
Dhalai
North Tripura
South Tripura
West Tripura
Uttar Pradesh
Agra
Aligarh
Allahabad
Ambedkar Nagar
Auraiya
Azamgarh
Baghpat
Bahraich
Ballia
Balrampur
Banda
Bara Banki
Bareilly
Basti
Bijnor
Budaun
Bulandshahr
Chandauli
Chitrakoot
Deoria
Etah
Etawah
Faizabad
Farrukhabad
Fatehpur
Firozabad
Gautam Buddha Nagar
Ghaziabad
Total population
Proportionate
increase
2011
3072880
2471222
2468965
3928106
3463284
1943309
2001
2703492
1920154
2186125
3477317
2960373
1751301
377988
693281
875144
1724619
307868
590913
767440
1532982
22.78
17.32
14.03
12.50
2.05
1.60
1.31
1.18
4380793
3673849
5959798
2398709
1372287
4616509
1302156
3478257
3223642
2149066
1799541
3257983
4465344
2461056
3683896
3712738
3498507
1952713
990626
3098637
1761152
1579160
2468371
1887577
2632684
2496761
1674714
4661452
3620436
2992286
4936105
2026876
1179993
3939916
1163991
2381072
2761620
1682350
1537334
2673581
3618589
2084814
3131619
3069426
2913122
1643251
766225
2712650
1531703
1338871
2088928
1570408
2308384
2052958
1202030
3290586
21.00
22.78
20.74
18.35
16.30
17.17
11.87
46.08
16.73
27.74
17.06
21.86
23.40
18.05
17.64
20.96
20.09
18.83
29.29
14.23
14.98
17.95
18.16
20.20
14.05
21.62
39.32
41.66
1.91
2.05
1.88
1.68
1.51
1.58
1.12
3.79
1.55
2.45
1.57
1.98
2.10
1.66
1.62
1.90
1.83
1.73
2.57
1.33
1.40
1.65
1.67
1.84
1.31
1.96
3.32
3.48
149
2001-2011
13.66
28.70
12.94
12.96
16.99
10.96
Average
annual
growth rate
2001-2011
1.28
2.52
1.22
1.22
1.57
1.04
Preliminary Demography of India
State/Union Territory/
District
Ghazipur
Gonda
Gorakhpur
Hamirpur
Hardoi
Jalaun
Jaunpur
Jhansi
Jyotiba Phule Nagar
Kannauj
Kanpur Dehat
Kanpur Nagar
Kanshiram Nagar
Kaushambi
Kheri
Kushinagar
Lalitpur
Lucknow
Mahamaya Nagar
Mahoba
Mahrajganj
Mainpuri
Mathura
Mau
Meerut
Mirzapur
Moradabad
Muzaffarnagar
Pilibhit
Pratapgarh
Rae Bareli
Rampur
Saharanpur
Sant Kabir Nagar
Sant Ravidas Nagar (Bhadohi)
Shahjahanpur
Shrawasti
Siddharthnagar
Sitapur
Sonbhadra
Total population
2011
3622727
3431386
4436275
1104021
4091380
1670718
4476072
2000755
1838771
1658005
1795092
4572951
1438156
1596909
4013634
3560830
1218002
4588455
1565678
876055
2665292
1847194
2541894
2205170
3447405
2494533
4773138
4138605
2037225
3173752
3404004
2335398
3464228
1714300
1554203
3002376
1114615
2553526
4474446
1862612
150
2001
3037582
2765586
3769456
1043724
3398306
1454452
3911679
1744931
1499068
1388923
1563336
4167999
1228668
1293154
3207232
2893196
977734
3647834
1336031
708447
2173878
1596718
2074516
1853997
2997361
2116042
3810983
3543362
1645183
2731174
2872335
1923739
2896863
1420226
1353705
2547855
1176391
2040085
3619661
1463519
Proportionate
increase
2001-2011
19.26
24.07
17.69
5.78
20.39
14.87
14.43
14.66
22.66
19.37
14.82
9.72
17.05
23.49
25.14
23.08
24.57
25.79
17.19
23.66
22.61
15.69
22.53
18.94
15.01
17.89
25.25
16.80
23.83
16.20
18.51
21.40
19.59
20.71
14.81
17.84
-5.25
25.17
23.62
27.27
Average
annual
growth rate
2001-2011
1.76
2.16
1.63
0.56
1.86
1.39
1.35
1.37
2.04
1.77
1.38
0.93
1.57
2.11
2.24
2.08
2.2
2.29
1.59
2.12
2.04
1.46
2.03
1.73
1.40
1.65
2.25
1.55
2.14
1.50
1.70
1.94
1.79
1.88
1.38
1.64
-0.54
2.24
2.12
2.41
Statistical Tables
State/Union Territory/
District
Sultanpur
Unnao
Varanasi
Uttarakhand
Almora
Bageshwar
Chamoli
Champawat
Dehradun
Garhwal
Hardwar
Nainital
Pithoragarh
Rudraprayag
Tehri Garhwal
Udham Singh Nagar
Uttarkashi
West Bengal
Bankura
Barddhaman
Birbhum
Dakshin Dinajpur
Darjiling
Haora
Hugli
Jalpaiguri
Koch Bihar
Kolkata
Maldah
Murshidabad
Nadia
North Twenty Four Parganas
Paschim Medinipur
Purba Medinipur
Puruliya
South Twenty Four Parganas
Uttar Dinajpur
Total population
Proportionate
increase
2011
3790922
3110595
3682194
2001
3214832
2700324
3138671
621927
259840
391114
259315
1698560
686527
1927029
955128
485993
236857
616409
1648367
329686
630567
249462
370359
224542
1282143
697078
1447187
762909
462289
227439
604747
1235614
295013
-1.37
4.16
5.60
15.49
32.48
-1.51
33.16
25.20
5.13
4.14
1.93
33.40
11.75
-0.14
0.41
0.55
1.44
2.81
-0.15
2.86
2.25
0.50
0.41
0.19
2.88
1.11
3596292
7723663
3502387
1670931
1842034
4841638
5520389
3869675
2822780
4486679
3997970
7102430
5168488
10082852
5943300
5094238
2927965
8153176
3000849
3192695
6895514
3015422
1503178
1609172
4273099
5041976
3401173
2479155
4572876
3290468
5866569
4604827
8934286
5193411
4417377
2536516
6906689
2441794
12.64
12.01
16.15
11.16
14.47
13.31
9.49
13.77
13.86
-1.88
21.50
21.07
12.24
12.86
14.44
15.32
15.43
18.05
22.90
1.19
1.13
1.50
1.06
1.35
1.25
0.91
1.29
1.30
-0.19
1.95
1.91
1.15
1.21
1.35
1.43
1.44
1.66
2.06
151
2001-2011
17.92
15.19
17.32
Average
annual
growth rate
2001-2011
1.65
1.41
1.60
Preliminary Demography of India
Table 3.A
Indexes of population distribution in districts of India, 2011
State/Union Territory/
Edc(x)
Idc(x)
Ddc(x)
District
Andaman and Nicobar Islands
Nicobars
0.03
-1.28
-0.039
North & Middle Andaman
0.087
-1.070
-0.093
South Andaman
0.196
-0.680
-0.133
Andhra Pradesh
Adilabad
2.262
-0.351
-0.794
Anantapur
3.374
-0.252
-0.850
Chittoor
3.446
-0.141
-0.488
East Godavari
4.257
0.097
0.413
Guntur
4.040
0.051
0.208
Hyderabad
3.314
1.686
5.585
Karimnagar
3.150
-0.073
-0.229
Khammam
2.312
-0.339
-0.784
Krishna
3.742
0.134
0.501
Kurnool
3.344
-0.221
-0.739
Mahbubnagar
3.340
-0.240
-0.802
Medak
2.505
-0.086
-0.216
Nalgonda
2.879
-0.193
-0.555
Nizamabad
2.451
0.016
0.040
Prakasam
2.109
-0.291
-0.613
Rangareddy
2.803
0.049
0.136
Sri Potti Sriramulu Nellore
4.376
-0.103
-0.452
Srikakulam
2.231
0.084
0.187
Visakhapatnam
3.543
0.003
0.012
Vizianagaram
1.936
-0.027
-0.052
Warangal
2.911
-0.143
-0.417
West Godavari
3.251
0.125
0.406
Y.S.R.
2.384
-0.307
-0.733
Arunachal Pradesh
Anjaw
0.017
-2.104
-0.037
Changlang
0.122
-1.076
-0.132
Dibang Valley
0.007
-2.581
-0.017
East Kameng
0.065
-1.302
-0.084
East Siang
0.082
-1.150
-0.094
Kurung Kumey
0.074
-1.405
-0.104
Lohit
0.120
-1.134
-0.136
Lower Dibang Valley
0.045
-1.435
-0.064
Lower Subansiri
0.068
-1.201
-0.082
Papum Pare
0.146
-0.874
-0.127
Tawang
0.041
-1.219
-0.050
152
Population
density
20
32
80
170
213
275
477
429
18480
322
175
519
229
219
313
245
195
426
300
396
462
384
358
274
508
188
3
32
1
19
27
15
28
14
24
51
23
Statistical Tables
State/Union Territory/
District
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam
Baksa
Barpeta
Bongaigaon
Cachar
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
Tinsukia
Udalguri
Bihar
Araria
Arwal
Aurangabad
Banka
Begusarai
Bhagalpur
Bhojpur
Buxar
Edc(x)
Idc(x)
Ddc(x)
0.093
0.029
0.069
0.072
0.093
-0.909
-1.882
-1.502
-1.502
-1.467
-0.084
-0.055
-0.103
-0.108
-0.136
Population
density
47
5
12
12
13
0.788
1.399
0.605
1.435
0.398
0.750
0.569
1.610
1.097
0.176
0.834
0.875
0.545
0.902
1.254
1.042
0.798
1.006
0.733
0.860
0.791
2.335
0.636
0.950
1.591
1.088
0.688
0.095
0.220
0.047
0.081
-0.194
0.110
-0.253
0.487
0.013
-0.938
0.162
-0.101
0.115
0.002
0.058
0.722
-0.613
0.247
-0.134
0.079
0.210
0.271
0.301
0.053
-0.019
-0.041
0.115
0.075
0.307
0.029
0.116
-0.077
0.082
-0.144
0.785
0.014
-0.165
0.135
-0.089
0.063
0.002
0.073
0.752
-0.489
0.248
-0.098
0.068
0.166
0.632
0.192
0.051
-0.030
-0.044
0.079
475
632
425
459
244
491
213
1171
393
44
553
302
497
383
436
2010
93
673
280
457
618
711
763
431
365
347
497
2.319
0.578
2.075
1.677
2.441
2.506
2.248
1.411
0.415
-0.421
0.300
0.246
0.607
0.491
0.460
0.441
0.963
-0.243
0.622
0.413
1.481
1.230
1.034
0.622
992
145
760
672
1541
1180
1100
1052
153
Preliminary Demography of India
State/Union Territory/
District
Darbhanga
Gaya
Gopalganj
Jamui
Jehanabad
Kaimur (Bhabua)
Katihar
Khagaria
Kishanganj
Lakhisarai
Madhepura
Madhubani
Munger
Muzaffarpur
Nalanda
Nawada
Pashchim Champaran
Patna
Purba Champaran
Purnia
Rohtas
Saharsa
Samastipur
Saran
Sheikhpura
Sheohar
Sitamarhi
Siwan
Supaul
Vaishali
Chandigarh
Chandigarh
Chhattisgarh
Bastar
Bijapur
Bilaspur
Dakshin Bastar Dantewada
Dhamtari
Durg
Janjgir - Champa
Jashpur
Kabeerdham
Edc(x)
Idc(x)
Ddc(x)
3.241
3.619
2.114
1.451
0.929
1.344
2.535
1.370
1.397
0.827
1.648
3.699
1.123
3.949
2.374
1.832
3.241
4.770
4.200
2.705
2.448
1.568
3.516
3.258
0.525
0.543
2.826
2.742
1.841
2.888
0.655
0.363
0.519
0.172
0.274
0.458
0.421
0.112
0.372
0.330
0.467
0.526
0.400
0.597
0.505
0.368
0.294
0.675
0.526
0.425
0.305
0.466
0.585
0.593
0.383
0.590
0.611
0.594
0.385
0.654
2.122
1.314
1.096
0.250
0.255
0.616
1.066
0.153
0.520
0.273
0.769
1.944
0.449
2.356
1.199
0.674
0.953
3.219
2.210
1.149
0.747
0.730
2.055
1.932
0.201
0.320
1.725
1.627
0.709
1.887
Population
density
1722
880
1258
567
716
1095
1004
493
898
814
1116
1279
958
1506
1220
890
750
1803
1281
1014
770
1115
1465
1493
922
1483
1555
1495
925
1717
0.872
1.385
1.207
9252
1.166
0.211
2.200
0.440
0.660
2.762
1.339
0.704
0.679
-0.435
-0.990
-0.073
-0.810
-0.208
0.011
0.043
-0.417
-0.291
-0.507
-0.209
-0.161
-0.357
-0.138
0.030
0.058
-0.293
-0.198
140
39
322
59
236
391
421
146
195
154
Statistical Tables
State/Union Territory/
District
Korba
Koriya
Mahasamund
Narayanpur
Raigarh
Raipur
Rajnandgaon
Surguja
Uttar Bastar Kanker
Dadra and Nagar Haveli
Dadra & Nagar Haveli
Daman and Diu
Daman
Diu
Delhi
Central
East
New Delhi
North
North East
North West
South
South West
West
Goa
North Goa
South Goa
Gujarat
Ahmadabad
Amreli
Anand
Banas Kantha
Bharuch
Bhavnagar
Dohad
Gandhinagar
Jamnagar
Junagadh
Kachchh
Kheda
Mahesana
Narmada
Edc(x)
Idc(x)
Ddc(x)
0.997
0.545
0.853
0.116
1.234
3.357
1.270
1.951
0.619
-0.319
-0.581
-0.247
-1.280
-0.257
-0.090
-0.300
-0.405
-0.520
-0.318
-0.317
-0.210
-0.148
-0.317
-0.302
-0.381
-0.790
-0.322
0.283
0.263
0.074
698
0.158
0.043
0.842
0.533
0.133
0.023
2651
1301
0.478
1.411
0.110
0.730
1.852
3.017
2.259
1.894
2.092
1.783
1.008
1.203
1.594
2.053
1.867
1.458
1.182
1.773
0.853
1.422
0.133
1.164
3.802
5.634
3.293
2.240
3.709
23147
3881
6078
14973
43091
28087
10935
5803
22603
0.676
0.529
0.092
-0.069
0.062
-0.036
471
326
5.956
1.251
1.727
2.575
1.281
2.378
1.757
1.146
1.784
2.266
1.727
1.900
1.676
0.488
0.368
-0.269
0.271
-0.119
-0.205
-0.122
0.184
0.238
-0.397
-0.090
-0.918
0.152
0.083
-0.251
2.193
-0.337
0.468
-0.306
-0.262
-0.290
0.323
0.273
-0.707
-0.204
-1.586
0.289
0.140
-0.122
890
205
711
290
238
288
582
660
153
310
46
541
462
214
155
Population
density
183
100
216
20
211
310
191
150
115
Preliminary Demography of India
State/Union Territory/
District
Navsari
Panch Mahals
Patan
Porbandar
Rajkot
Sabar Kantha
Surat
Surendranagar
Tapi
The Dangs
Vadodara
Valsad
Haryana
Ambala
Bhiwani
Faridabad
Fatehabad
Gurgaon
Hisar
Jhajjar
Jind
Kaithal
Karnal
Kurukshetra
Mahendragarh
Mewat
Palwal
Panchkula
Panipat
Rewari
Rohtak
Sirsa
Sonipat
Yamunanagar
Himachal Pradesh
Bilaspur
Chamba
Hamirpur
Kangra
Kinnaur
Kullu
Lahul & Spiti
Edc(x)
Idc(x)
Ddc(x)
1.100
1.973
1.110
0.484
3.140
2.006
5.023
1.451
0.666
0.187
3.435
1.407
0.198
0.080
-0.212
-0.175
-0.051
-0.065
0.557
-0.358
-0.185
-0.471
0.160
0.168
0.218
0.157
-0.235
-0.085
-0.160
-0.131
2.800
-0.520
-0.123
-0.088
0.550
0.236
0.939
1.346
1.487
0.778
1.251
1.440
0.791
1.101
0.887
1.245
0.797
0.762
0.900
0.860
0.462
0.994
0.740
0.875
1.070
1.223
1.003
0.279
-0.080
0.351
-0.004
0.158
0.082
0.128
0.106
0.002
0.204
0.318
0.157
0.209
0.163
0.254
0.402
0.178
0.221
-0.100
0.235
0.259
0.262
-0.108
0.521
-0.003
0.198
0.118
0.101
0.117
0.002
0.254
0.253
0.120
0.188
0.140
0.118
0.400
0.132
0.194
-0.107
0.287
0.259
725
317
855
378
549
460
512
487
383
610
792
548
617
555
685
962
575
635
303
655
691
0.316
0.429
0.375
1.245
0.070
0.361
0.026
-0.066
-0.681
0.028
-0.162
-1.462
-0.681
-2.223
-0.021
-0.292
0.010
-0.202
-0.102
-0.246
-0.058
327
79
406
263
13
79
2
156
Population
density
602
458
234
255
339
328
1376
167
249
129
551
561
Statistical Tables
State/Union Territory/
District
Mandi
Shimla
Sirmaur
Solan
Una
Jammu and Kashmir
Anantnag
Badgam
Bandipore
Baramula
Doda
Ganderbal
Jammu
Kargil
Kathua
Kishtwar
Kulgam
Kupwara
Leh(Ladakh)
Pulwama
Punch
Rajouri
Ramban
Reasi
Samba
Shupiyan
Srinagar
Udhampur
Jharkhand
Bokaro
Chatra
Deoghar
Dhanbad
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Jamtara
Khunti
Kodarma
Edc(x)
Idc(x)
Ddc(x)
0.826
0.672
0.438
0.477
0.431
-0.178
-0.381
-0.308
-0.107
-0.052
-0.147
-0.256
-0.135
-0.051
-0.022
Population
density
253
159
188
298
338
0.884
0.608
0.318
0.839
0.338
0.245
1.261
0.118
0.509
0.191
0.349
0.723
0.122
0.471
0.394
0.512
0.234
0.260
0.263
0.220
1.049
0.459
-0.007
0.149
0.467
-0.097
-0.684
0.480
0.194
-1.581
-0.216
-0.484
0.385
-0.015
-2.104
0.196
-0.126
-0.210
-0.253
-0.316
-0.079
0.349
0.266
-0.257
-0.006
0.090
0.149
-0.081
-0.231
0.118
0.245
-0.187
-0.110
-0.092
0.134
-0.011
-0.256
0.092
-0.050
-0.108
-0.059
-0.082
-0.021
0.077
0.279
-0.118
375
537
1117
305
79
1151
596
10
232
125
925
368
3
598
285
235
213
184
318
852
703
211
1.704
0.861
1.233
2.217
1.092
1.093
2.021
1.084
0.848
1.433
0.653
0.438
0.593
0.274
-0.142
0.198
0.527
-0.104
-0.067
0.115
0.213
-0.296
0.024
0.061
-0.249
0.049
0.466
-0.122
0.245
1.169
-0.114
-0.073
0.233
0.230
-0.251
0.035
0.040
-0.109
0.029
716
275
602
1284
300
327
497
622
193
403
439
215
427
157
Preliminary Demography of India
State/Union Territory/
District
Latehar
Lohardaga
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Saraikela-Kharsawan
Simdega
Karnataka
Bagalkot
Bangalore
Bangalore Rural
Belgaum
Bellary
Bidar
Bijapur
Chamarajanagar
Chikkaballapura
Chikmagalur
Chitradurga
Dakshina Kannada
Davanagere
Dharwad
Gadag
Gulbarga
Hassan
Haveri
Kodagu
Kolar
Koppal
Mandya
Mysore
Raichur
Ramanagara
Shimoga
Tumkur
Udupi
Uttara Kannada
Yadgir
Edc(x)
Idc(x)
Ddc(x)
0.600
0.382
0.743
1.600
1.241
1.893
0.784
2.406
0.950
0.879
0.496
-0.280
-0.090
0.116
-0.000
-0.261
0.230
0.254
0.165
0.276
0.010
-0.377
-0.168
-0.034
0.086
-0.000
-0.324
0.436
0.199
0.396
0.262
0.009
-0.187
Population
density
200
310
498
381
209
648
684
557
719
390
160
1.562
7.923
0.816
3.948
2.093
1.405
1.797
0.844
1.037
0.940
1.372
1.722
1.609
1.526
0.880
2.119
1.468
1.321
0.458
1.273
1.150
1.495
2.475
1.590
0.895
1.451
2.216
0.973
1.187
0.969
-0.122
1.060
0.063
-0.030
-0.104
-0.087
-0.265
-0.280
-0.107
-0.383
-0.287
0.079
-0.064
0.056
-0.221
-0.214
-0.165
-0.061
-0.451
0.003
-0.183
-0.019
0.059
-0.223
-0.100
-0.265
-0.178
-0.098
-0.435
-0.231
-0.190
8.399
0.052
-0.117
-0.218
-0.122
-0.477
-0.236
-0.111
-0.360
-0.393
0.136
-0.103
0.086
-0.195
-0.453
-0.242
-0.081
-0.207
0.004
-0.211
-0.028
0.147
-0.355
-0.089
-0.385
-0.395
-0.096
-0.517
-0.224
288
4378
441
356
300
312
207
200
298
158
197
457
329
434
229
233
261
331
135
384
250
365
437
228
303
207
253
304
140
224
158
Statistical Tables
State/Union Territory/
District
Kerala
Alappuzha
Ernakulam
Idukki
Kannur
Kasaragod
Kollam
Kottayam
Kozhikode
Malappuram
Palakkad
Pathanamthitta
Thiruvananthapuram
Thrissur
Wayanad
Lakshadweep
Lakshadweep
Madhya Pradesh
Alirajpur
Anuppur
Ashoknagar
Balaghat
Barwani
Betul
Bhind
Bhopal
Burhanpur
Chhatarpur
Chhindwara
Damoh
Datia
Dewas
Dhar
Dindori
East Nimar
Guna
Gwalior
Harda
Hoshangabad
Indore
Jabalpur
Jhabua
Edc(x)
Idc(x)
Ddc(x)
Population
density
1.753
2.710
0.915
2.087
1.076
2.173
1.636
2.553
3.397
2.323
0.988
2.733
2.570
0.675
0.595
0.465
-0.188
0.349
0.234
0.441
0.372
0.539
0.483
0.216
0.105
0.597
0.430
0.002
1.043
1.259
-0.172
0.728
0.252
0.959
0.609
1.375
1.639
0.503
0.104
1.633
1.105
0.001
1501
1111
247
852
654
1053
898
1318
1158
627
486
1509
1026
383
0.053
0.723
0.038
2013
0.602
0.619
0.698
1.406
1.145
1.302
1.408
1.957
0.626
1.457
1.727
1.044
0.650
1.292
1.805
0.582
1.082
1.025
1.678
0.471
1.025
2.704
2.033
0.846
-0.221
-0.280
-0.324
-0.316
-0.173
-0.385
0.001
0.350
-0.237
-0.274
-0.333
-0.343
-0.116
-0.233
-0.153
-0.608
-0.331
-0.293
0.067
-0.348
-0.314
0.343
0.093
-0.126
-0.133
-0.174
-0.226
-0.445
-0.198
-0.502
0.001
0.685
-0.148
-0.399
-0.576
-0.358
-0.075
-0.301
-0.276
-0.354
-0.358
-0.301
0.113
-0.164
-0.322
0.926
0.189
-0.107
229
200
181
184
256
157
382
854
221
203
177
173
292
223
268
94
178
194
445
171
185
839
472
285
159
Preliminary Demography of India
State/Union Territory/
District
Katni
Mandla
Mandsaur
Morena
Narsimhapur
Neemuch
Panna
Raisen
Rajgarh
Ratlam
Rewa
Sagar
Satna
Sehore
Seoni
Shahdol
Shajapur
Sheopur
Shivpuri
Sidhi
Singrauli
Tikamgarh
Ujjain
Umaria
Vidisha
West Nimar
Maharashtra
Ahmadnagar
Akola
Amravati
Aurangabad
Bhandara
Bid
Buldana
Chandrapur
Dhule
Gadchiroli
Gondiya
Hingoli
Jalgaon
Jalna
Kolhapur
Edc(x)
Idc(x)
Ddc(x)
1.067
0.871
1.107
1.624
0.902
0.683
0.840
1.100
1.278
1.202
1.953
1.965
1.842
1.083
1.139
0.880
1.250
0.568
1.426
0.931
0.974
1.194
1.642
0.532
1.205
1.547
-0.165
-0.321
-0.197
0.014
-0.253
-0.293
-0.429
-0.385
-0.182
-0.106
-0.008
-0.216
-0.108
-0.282
-0.385
-0.346
-0.194
-0.564
-0.356
-0.216
-0.263
-0.125
-0.068
-0.383
-0.285
-0.214
-0.176
-0.280
-0.219
0.023
-0.228
-0.200
-0.360
-0.424
-0.232
-0.127
-0.016
-0.424
-0.200
-0.306
-0.439
-0.304
-0.242
-0.321
-0.508
-0.201
-0.256
-0.149
-0.112
-0.203
-0.343
-0.331
3.754
1.503
2.386
3.054
0.991
2.137
2.139
1.813
1.693
0.886
1.093
0.974
3.491
1.618
3.201
-0.156
-0.056
-0.208
-0.018
-0.092
-0.198
-0.153
-0.298
-0.178
-0.710
-0.195
-0.165
-0.026
-0.177
0.121
-0.584
-0.084
-0.497
-0.055
-0.092
-0.422
-0.328
-0.541
-0.301
-0.629
-0.213
-0.161
-0.091
-0.286
0.388
160
Population
density
261
182
242
394
213
194
142
157
251
299
374
232
297
199
157
172
244
104
168
232
208
286
326
158
198
233
266
335
236
366
308
242
268
192
253
74
243
260
359
254
504
Statistical Tables
State/Union Territory/
District
Latur
Mumbai
Mumbai Suburban
Nagpur
Nanded
Nandurbar
Nashik
Osmanabad
Parbhani
Pune
Raigarh
Ratnagiri
Sangli
Satara
Sindhudurg
Solapur
Thane
Wardha
Washim
Yavatmal
Manipur
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Senapati
Tamenglong
Thoubal
Ukhrul
Meghalaya
East Garo Hills
East Khasi Hills
Jaintia Hills
Ribhoi
South Garo Hills
West Garo Hills
West Khasi Hills
Mizoram
Aizawl
Champhai
Kolasib
Edc(x)
Idc(x)
Ddc(x)
2.029
2.600
7.712
3.845
2.774
1.360
5.048
1.372
1.517
7.790
2.178
1.333
2.331
2.482
0.701
3.566
9.134
1.071
0.989
2.293
-0.046
2.078
1.661
0.091
-0.078
-0.068
0.013
-0.240
-0.131
0.199
-0.015
-0.288
-0.064
-0.124
-0.369
-0.119
0.482
-0.268
-0.215
-0.271
-0.093
5.401
12.811
0.351
-0.215
-0.093
0.067
-0.329
-0.199
1.549
-0.032
-0.384
-0.149
-0.307
-0.259
-0.425
4.402
-0.288
-0.213
-0.621
0.199
0.119
0.224
0.374
0.425
0.293
0.116
0.347
0.151
0.104
-0.943
-0.808
0.223
0.415
-0.545
-1.077
0.332
-0.976
0.021
-0.112
-0.181
0.084
0.177
-0.160
-0.125
0.115
-0.148
485
43
59
638
992
109
32
818
40
0.262
0.681
0.325
0.214
0.118
0.531
0.319
-0.495
-0.105
-0.569
-0.545
-0.694
-0.343
-0.715
-0.130
-0.071
-0.185
-0.116
-0.082
-0.182
-0.228
122
299
103
109
77
173
73
0.334
0.104
0.069
-0.528
-0.984
-0.804
-0.176
-0.102
-0.055
113
40
60
161
Population
density
343
45594
17477
470
319
326
393
219
282
603
368
196
329
287
163
290
1157
205
232
204
Preliminary Demography of India
State/Union Territory/
District
Lawngtlai
Lunglei
Mamit
Saiha
Serchhip
Nagaland
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Orissa
Anugul
Balangir
Baleshwar
Bargarh
Baudh
Bhadrak
Cuttack
Debagarh
Dhenkanal
Gajapati
Ganjam
Jagatsinghapur
Jajapur
Jharsuguda
Kalahandi
Kandhamal
Kendrapara
Kendujhar
Khordha
Koraput
Malkangiri
Mayurbhanj
Nabarangapur
Nayagarh
Edc(x)
Idc(x)
Ddc(x)
0.097
0.127
0.071
0.047
0.054
-0.913
-1.054
-1.120
-0.981
-0.923
-0.089
-0.134
-0.079
-0.046
-0.049
0.314
0.061
0.223
0.042
0.160
0.207
0.078
0.135
0.163
0.137
0.117
0.032
-0.810
-0.167
-0.824
-0.503
-0.434
-0.965
-0.675
-0.525
-0.572
-0.531
0.010
-0.050
-0.037
-0.034
-0.080
-0.090
-0.076
-0.091
-0.085
-0.079
-0.062
410
59
259
57
120
140
41
81
114
102
112
1.051
1.362
1.915
1.222
0.364
1.245
2.164
0.258
0.986
0.476
2.909
0.939
1.509
0.479
1.300
0.605
1.190
1.490
1.856
1.138
0.506
2.077
1.007
0.795
-0.282
-0.182
0.203
-0.178
-0.429
0.198
0.242
-0.556
-0.153
-0.457
0.051
0.252
0.218
-0.143
-0.282
-0.622
0.155
-0.245
0.321
-0.388
-0.556
-0.199
-0.219
-0.188
-0.297
-0.247
0.390
-0.218
-0.156
0.246
0.524
-0.143
-0.151
-0.218
0.149
0.237
0.329
-0.069
-0.367
-0.376
0.185
-0.365
0.596
-0.442
-0.281
-0.414
-0.221
-0.150
199
251
609
253
142
601
666
106
268
133
429
681
630
274
199
91
545
217
799
156
106
241
230
247
162
Population
density
47
34
29
40
46
Statistical Tables
State/Union Territory/
District
Nuapada
Puri
Rayagada
Sambalpur
Subarnapur
Sundargarh
Puducherry
Karaikal
Mahe
Puducherry
Yanam
Punjab
Amritsar
Barnala
Bathinda
Faridkot
Fatehgarh Sahib
Firozpur
Gurdaspur
Hoshiarpur
Jalandhar
Kapurthala
Ludhiana
Mansa
Moga
Muktsar
Patiala
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Shahid Bhagat Singh Nagar
Tarn Taran
Rajasthan
Ajmer
Alwar
Banswara
Baran
Barmer
Bharatpur
Bhilwara
Bikaner
Bundi
Edc(x)
Idc(x)
Ddc(x)
0.501
1.403
0.795
0.863
0.539
1.719
-0.385
0.107
-0.448
-0.383
-0.136
-0.251
-0.193
0.150
-0.356
-0.330
-0.073
-0.431
Population
density
157
488
136
158
279
214
0.166
0.035
0.782
0.046
0.516
1.087
0.928
0.687
0.085
0.038
0.726
0.032
1252
4659
3231
1854
2.058
0.493
1.148
0.511
0.496
1.675
1.900
1.308
1.803
0.676
2.882
0.635
0.820
0.746
1.564
0.565
0.815
1.367
0.508
0.926
0.388
0.041
0.036
0.046
0.125
-0.001
0.231
0.087
0.338
0.119
0.408
-0.037
0.066
-0.040
0.194
0.107
0.338
0.071
0.099
0.085
0.799
0.020
0.041
0.024
0.062
-0.002
0.439
0.114
0.610
0.080
1.175
-0.024
0.054
-0.030
0.303
0.061
0.275
0.097
0.050
0.079
932
419
414
424
508
380
649
466
831
501
975
350
444
348
596
488
830
449
479
464
2.136
3.034
1.486
1.011
2.152
2.106
1.992
1.957
0.920
-0.097
0.060
-0.029
-0.336
-0.619
0.121
-0.218
-0.642
-0.279
-0.208
0.183
-0.042
-0.340
-1.331
0.254
-0.435
-1.256
-0.256
305
438
357
176
92
503
231
87
201
163
Preliminary Demography of India
State/Union Territory/
District
Chittaurgarh
Churu
Dausa
Dhaulpur
Dungarpur
Ganganagar
Hanumangarh
Jaipur
Jaisalmer
Jalor
Jhalawar
Jhunjhunun
Jodhpur
Karauli
Kota
Nagaur
Pali
Pratapgarh
Rajsamand
Sawai Madhopur
Sikar
Sirohi
Tonk
Udaipur
Sikkim
East District
North District
South District
West District
Tamil Nadu
Ariyalur
Chennai
Coimbatore
Cuddalore
Dharmapuri
Dindigul
Erode
Kancheepuram
Kanniyakumari
Karur
Krishnagiri
Madurai
Edc(x)
Idc(x)
Ddc(x)
1.276
1.687
1.353
0.998
1.148
1.627
1.471
5.507
0.555
1.512
1.166
1.768
3.046
1.205
1.612
2.734
1.684
0.717
0.957
1.106
2.213
0.857
1.175
2.535
-0.428
-0.497
0.098
0.012
-0.015
-0.189
-0.433
0.195
-1.338
-0.346
-0.225
-0.024
-0.374
-0.160
-0.027
-0.310
-0.365
0.550
-0.103
-0.108
-0.042
-0.276
-0.285
-0.222
-0.546
-0.839
0.132
0.011
-0.017
-0.308
-0.636
1.075
-0.743
-0.523
-0.263
-0.042
-1.138
-0.193
-0.044
-0.847
-0.615
0.395
-0.099
-0.119
-0.092
-0.237
-0.335
-0.564
0.232
0.036
0.121
0.113
-0.112
-1.570
-0.290
-0.513
-0.026
-0.056
-0.035
-0.058
295
10
196
117
0.622
3.868
2.869
2.149
1.242
1.786
1.867
3.298
1.540
0.890
1.557
2.513
0.007
1.849
0.293
0.265
-0.060
-0.029
0.018
0.386
0.463
-0.012
-0.013
0.334
0.004
7.150
0.840
0.570
-0.075
-0.051
0.033
1.273
0.712
-0.011
-0.020
0.840
387
26903
748
702
332
357
397
927
1106
371
370
823
164
Population
density
142
121
477
391
368
247
141
598
17
172
227
361
161
264
358
187
165
1352
301
297
346
202
198
228
Statistical Tables
State/Union Territory/
District
Nagapattinam
Namakkal
Perambalur
Pudukkottai
Ramanathapuram
Salem
Sivaganga
Thanjavur
The Nilgiris
Theni
Thiruvallur
Thiruvarur
Thoothukkudi
Tiruchirappalli
Tirunelveli
Tiruppur
Tiruvannamalai
Vellore
Viluppuram
Virudhunagar
Tripura
Dhalai
North Tripura
South Tripura
West Tripura
Uttar Pradesh
Agra
Aligarh
Allahabad
Ambedkar Nagar
Auraiya
Azamgarh
Baghpat
Bahraich
Ballia
Balrampur
Banda
Bara Banki
Bareilly
Basti
Bijnor
Budaun
Edc(x)
Idc(x)
Ddc(x)
1.334
1.422
0.466
1.338
1.105
2.876
1.108
1.985
0.607
1.028
3.079
1.048
1.436
2.242
2.539
2.042
2.040
3.246
2.862
1.606
0.244
0.123
-0.072
-0.040
-0.076
0.240
-0.071
0.258
-0.122
0.055
0.440
0.146
-0.004
0.198
0.080
0.096
0.020
0.229
0.102
0.076
0.325
0.175
-0.034
-0.053
-0.084
0.691
-0.078
0.513
-0.074
0.057
1.353
0.152
-0.005
0.445
0.202
0.197
0.040
0.743
0.291
0.122
0.312
0.573
0.723
1.425
-0.406
-0.191
0.028
0.179
-0.127
-0.109
0.020
0.255
150
246
407
575
3.620
3.036
4.925
1.982
1.134
3.815
1.076
2.874
2.664
1.776
1.487
2.692
3.690
2.034
3.044
3.068
0.455
0.410
0.460
0.424
0.244
0.456
0.405
0.201
0.453
0.285
0.029
0.349
0.454
0.328
0.326
0.275
1.648
1.245
2.264
0.840
0.277
1.741
0.436
0.577
1.206
0.506
0.043
0.940
1.674
0.667
0.993
0.844
1088
980
1099
1011
669
1090
968
605
1081
735
408
852
1084
811
808
718
165
Population
density
668
506
323
348
320
663
324
691
288
433
1049
533
378
602
458
476
399
646
482
454
Preliminary Demography of India
State/Union Territory/
District
Bulandshahr
Chandauli
Chitrakoot
Deoria
Etah
Etawah
Faizabad
Farrukhabad
Fatehpur
Firozabad
Gautam Buddha Nagar
Ghaziabad
Ghazipur
Gonda
Gorakhpur
Hamirpur
Hardoi
Jalaun
Jaunpur
Jhansi
Jyotiba Phule Nagar
Kannauj
Kanpur Dehat
Kanpur Nagar
Kanshiram Nagar
Kaushambi
Kheri
Kushinagar
Lalitpur
Lucknow
Mahamaya Nagar
Mahoba
Mahrajganj
Mainpuri
Mathura
Mau
Meerut
Mirzapur
Moradabad
Muzaffarnagar
Pilibhit
Pratapgarh
Edc(x)
Idc(x)
Ddc(x)
2.891
1.614
0.819
2.560
1.455
1.305
2.040
1.560
2.175
2.063
1.384
3.852
2.994
2.835
3.666
0.912
3.381
1.381
3.699
1.653
1.519
1.370
1.483
3.779
1.188
1.320
3.317
2.942
1.006
3.792
1.294
0.724
2.202
1.526
2.100
1.822
2.849
2.061
3.944
3.420
1.683
2.623
0.392
0.302
-0.091
0.506
0.278
0.258
0.370
0.337
0.221
0.443
0.539
0.796
0.449
0.308
0.544
-0.174
0.254
-0.018
0.464
0.019
0.318
0.339
0.176
0.598
0.286
0.358
0.137
0.507
-0.198
0.678
0.370
-0.093
0.375
0.244
0.301
0.528
0.555
0.160
0.536
0.433
0.184
0.350
1.134
0.488
-0.074
1.296
0.405
0.337
0.754
0.526
0.481
0.914
0.746
3.066
1.345
0.874
1.994
-0.159
0.857
-0.024
1.714
0.031
0.483
0.464
0.260
2.259
0.339
0.472
0.454
1.491
-0.199
2.569
0.479
-0.067
0.826
0.373
0.632
0.963
1.580
0.331
2.112
1.480
0.310
0.918
166
Population
density
941
765
309
1222
724
690
893
828
634
1058
1320
2383
1073
775
1334
255
683
366
1108
398
792
832
571
1510
736
869
523
1224
242
1815
894
308
904
669
763
1287
1367
552
1308
1033
582
854
Statistical Tables
State/Union Territory/
District
Rae Bareli
Rampur
Saharanpur
Sant Kabir Nagar
Sant Ravidas Nagar
(Bhadohi)
Shahjahanpur
Shrawasti
Siddharthnagar
Sitapur
Sonbhadra
Sultanpur
Unnao
Varanasi
Uttarakhand
Almora
Bageshwar
Chamoli
Champawat
Dehradun
Garhwal
Hardwar
Nainital
Pithoragarh
Rudraprayag
Tehri Garhwal
Udham Singh Nagar
Uttarkashi
West Bengal
Bankura
Barddhaman
Birbhum
Dakshin Dinajpur
Darjiling
Haora
Hugli
Jalpaiguri
Koch Bihar
Kolkata
Maldah
Murshidabad
Nadia
Edc(x)
Idc(x)
Ddc(x)
2.813
1.930
2.863
1.417
1.284
0.287
0.413
0.392
0.494
0.628
0.808
0.797
1.121
0.700
0.807
Population
density
739
987
939
1189
1619
2.481
0.921
2.110
3.697
1.539
3.132
2.570
3.043
0.236
0.414
0.386
0.310
-0.143
0.351
0.253
0.787
0.585
0.382
0.815
1.148
-0.220
1.098
0.650
2.394
656
990
928
779
274
855
682
2333
0.514
0.215
0.323
0.214
1.404
0.567
1.592
0.789
0.402
0.196
0.509
1.362
0.272
-0.277
-0.530
-0.875
-0.418
0.159
-0.480
0.331
-0.187
-0.746
-0.485
-0.403
0.172
-0.964
-0.143
-0.114
-0.283
-0.090
0.223
-0.272
0.527
-0.148
-0.300
-0.095
-0.205
0.234
-0.262
201
112
51
146
550
126
817
248
68
125
151
566
41
2.972
6.382
2.894
1.381
1.522
4.001
4.562
3.198
2.333
3.707
3.304
5.869
4.271
0.137
0.460
0.306
0.303
0.186
0.937
0.663
0.212
0.340
1.804
0.449
0.544
0.538
0.407
2.936
0.885
0.418
0.283
3.750
3.023
0.679
0.792
6.687
1.482
3.192
2.298
523
1100
771
765
585
3300
1753
621
833
24252
1071
1334
1316
167
Preliminary Demography of India
State/Union Territory/
District
North Twenty Four Parganas
Paschim Medinipur
Purba Medinipur
Puruliya
South Twenty Four Parganas
Uttar Dinajpur
Source:
Author’s calculations.
Edc(x)
Idc(x)
Ddc(x)
8.332
4.911
4.209
2.419
6.737
2.480
0.810
0.202
0.446
0.089
0.332
0.394
6.750
0.993
1.877
0.215
2.237
0.976
168
Population
density
2462
607
1065
468
819
944
Statistical Tables
Table 4.A
Indicators of age composition of population in districts of India, 2011
State/Union Territory
Index C
Index A
Dds(a)
District
Andaman and Nicobar Islands
Nicobars
0.115
0.130
4.668
North & Middle Andaman
0.110
0.124
8.075
South Andaman
0.099
0.110
-13.430
Andhra Pradesh
Adilabad
0.108
0.121
0.892
Anantapur
0.105
0.117
0.559
Chittoor
0.101
0.113
-0.144
East Godavari
0.096
0.106
-1.926
Guntur
0.095
0.105
-1.892
Hyderabad
0.105
0.117
0.561
Karimnagar
0.085
0.093
-4.021
Khammam
0.096
0.106
-1.042
Krishna
0.090
0.099
-3.279
Kurnool
0.118
0.134
3.365
Mahbubnagar
0.124
0.142
4.576
Medak
0.115
0.130
2.082
Nalgonda
0.102
0.113
-0.038
Nizamabad
0.105
0.117
0.425
Prakasam
0.106
0.119
0.777
Rangareddy
0.112
0.127
2.932
Sri Potti Sriramulu Nellore
0.097
0.107
-0.883
Srikakulam
0.098
0.109
-0.578
Visakhapatnam
0.100
0.111
-0.480
Vizianagaram
0.099
0.109
-0.463
Warangal
0.092
0.101
-2.060
West Godavari
0.092
0.102
-2.230
Y.S.R.
0.109
0.122
1.034
Arunachal Pradesh
Anjaw
0.161
0.192
0.718
Changlang
0.172
0.208
8.879
Dibang Valley
0.139
0.161
-0.158
East Kameng
0.179
0.217
5.778
East Siang
0.122
0.139
-6.508
Kurung Kumey
0.173
0.209
5.582
Lohit
0.162
0.194
5.448
Lower Dibang Valley
0.143
0.167
-0.515
Lower Subansiri
0.121
0.137
-5.869
Papum Pare
0.134
0.155
-5.706
Tawang
0.113
0.127
-4.741
169
Ddc(a)
-0.002
-0.007
-0.027
-0.217
-0.377
-0.435
-0.660
-0.631
-0.369
-0.670
-0.358
-0.691
-0.177
-0.092
-0.163
-0.358
-0.230
-0.291
-0.335
-0.364
-0.316
-0.471
-0.271
-0.503
-0.557
-0.222
0.002
0.017
0.000
0.010
-0.003
0.011
0.013
0.002
-0.003
0.002
-0.003
Preliminary Demography of India
State/Union Territory
District
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam
Baksa
Barpeta
Bongaigaon
Cachar
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
Tinsukia
Udalguri
Bihar
Araria
Arwal
Aurangabad
Banka
Begusarai
Bhagalpur
Bhojpur
Buxar
Index C
Index A
Dds(a)
Ddc(a)
0.172
0.131
0.136
0.131
0.123
0.208
0.151
0.157
0.151
0.141
6.788
-1.441
-2.305
-3.566
-7.022
0.013
-0.000
0.001
-0.000
-0.003
0.123
0.166
0.155
0.142
0.146
0.165
0.145
0.184
0.117
0.149
0.164
0.121
0.166
0.108
0.129
0.096
0.190
0.167
0.149
0.145
0.166
0.158
0.118
0.116
0.139
0.133
0.131
0.140
0.199
0.184
0.166
0.170
0.197
0.169
0.226
0.132
0.175
0.197
0.138
0.199
0.121
0.147
0.106
0.235
0.200
0.175
0.170
0.199
0.188
0.133
0.132
0.161
0.153
0.151
-2.485
3.771
0.843
-0.508
0.049
1.940
0.012
7.820
-4.585
0.095
2.107
-3.007
1.500
-5.141
-2.910
-8.264
4.433
2.870
0.388
0.029
2.174
4.040
-2.556
-4.019
-1.320
-1.816
-1.321
-0.025
0.166
0.052
0.058
0.021
0.087
0.028
0.281
-0.064
0.011
0.095
-0.034
0.066
-0.088
-0.013
-0.161
0.154
0.124
0.046
0.043
0.095
0.219
-0.034
-0.057
0.045
0.007
-0.000
0.201
0.177
0.174
0.179
0.180
0.176
0.162
0.168
0.252
0.215
0.211
0.218
0.220
0.213
0.193
0.202
1.681
-0.044
-0.330
-0.021
0.100
-0.301
-1.364
-0.546
0.514
0.088
0.303
0.266
0.398
0.374
0.241
0.178
170
Statistical Tables
State/Union Territory
District
Darbhanga
Gaya
Gopalganj
Jamui
Jehanabad
Kaimur (Bhabua)
Katihar
Khagaria
Kishanganj
Lakhisarai
Madhepura
Madhubani
Munger
Muzaffarpur
Nalanda
Nawada
Pashchim Champaran
Patna
Purba Champaran
Purnia
Rohtas
Saharsa
Samastipur
Saran
Sheikhpura
Sheohar
Sitamarhi
Siwan
Supaul
Vaishali
Chandigarh
Chandigarh
Chhattisgarh
Bastar
Bijapur
Bilaspur
Dakshin Bastar Dantewada
Dhamtari
Durg
Janjgir - Champa
Jashpur
Kabeerdham
Index C
Index A
Dds(a)
Ddc(a)
0.179
0.174
0.171
0.178
0.173
0.179
0.196
0.209
0.202
0.182
0.199
0.174
0.163
0.171
0.174
0.166
0.192
0.157
0.195
0.197
0.166
0.199
0.184
0.167
0.186
0.190
0.188
0.161
0.190
0.169
0.218
0.211
0.206
0.217
0.208
0.219
0.244
0.265
0.253
0.223
0.249
0.211
0.194
0.206
0.211
0.199
0.238
0.186
0.243
0.245
0.200
0.248
0.226
0.200
0.229
0.235
0.232
0.191
0.235
0.204
-0.031
-0.617
-0.606
-0.026
-0.211
0.016
1.443
1.348
1.065
0.087
1.103
-0.630
-0.658
-1.093
-0.379
-0.868
1.418
-3.828
2.302
1.595
-1.092
1.035
0.635
-1.421
0.128
0.204
0.885
-1.816
0.709
-0.991
0.514
0.524
0.285
0.229
0.130
0.216
0.528
0.334
0.314
0.139
0.357
0.536
0.123
0.536
0.346
0.218
0.639
0.432
0.867
0.568
0.297
0.339
0.615
0.398
0.095
0.104
0.527
0.282
0.354
0.376
0.112
0.126
0.000
-0.069
0.151
0.157
0.151
0.143
0.126
0.126
0.135
0.141
0.171
0.178
0.186
0.177
0.168
0.144
0.144
0.156
0.164
0.207
2.014
0.560
3.713
0.235
-1.708
-7.076
-1.185
0.072
3.290
0.082
0.019
0.153
0.020
-0.014
-0.056
0.020
0.025
0.092
171
Preliminary Demography of India
State/Union Territory
District
Korba
Koriya
Mahasamund
Narayanpur
Raigarh
Raipur
Rajnandgaon
Surguja
Uttar Bastar Kanker
Dadra and Nagar Haveli
Dadra & Nagar Haveli
Daman and Diu
Daman
Diu
Delhi
Central
East
New Delhi
North
North East
North West
South
South West
West
Goa
North Goa
South Goa
Gujarat
Ahmadabad
Amreli
Anand
Banas Kantha
Bharuch
Bhavnagar
Dohad
Gandhinagar
Jamnagar
Junagadh
Kachchh
Kheda
Mahesana
Narmada
Index C
Index A
Dds(a)
Ddc(a)
0.140
0.141
0.127
0.163
0.128
0.140
0.134
0.157
0.130
0.162
0.165
0.146
0.195
0.147
0.163
0.155
0.187
0.150
-0.124
0.108
-1.979
0.418
-2.677
-0.083
-1.348
5.443
-1.101
0.031
0.021
-0.013
0.013
-0.015
0.112
0.014
0.181
-0.002
0.143
0.168
0.000
0.013
0.102
0.122
0.114
0.139
-15.038
13.936
-0.019
-0.002
0.104
0.111
0.086
0.114
0.132
0.121
0.118
0.115
0.112
0.117
0.125
0.095
0.129
0.152
0.138
0.134
0.129
0.126
-2.019
-2.905
-1.191
-0.766
7.755
3.384
0.429
-1.720
-3.854
-0.054
-0.117
-0.022
-0.050
0.007
-0.117
-0.117
-0.127
-0.167
0.092
0.101
0.101
0.112
-11.001
10.563
-0.118
-0.069
0.111
0.111
0.117
0.160
0.110
0.128
0.189
0.115
0.118
0.110
0.148
0.121
0.112
0.127
0.125
0.125
0.132
0.191
0.124
0.147
0.234
0.130
0.133
0.123
0.174
0.137
0.126
0.146
-6.422
-1.326
-1.072
6.642
-1.526
0.801
7.656
-0.877
-0.941
-2.714
3.110
-0.537
-1.654
0.128
-0.485
-0.101
-0.101
0.260
-0.112
-0.026
0.333
-0.076
-0.096
-0.198
0.107
-0.079
-0.129
-0.007
172
Statistical Tables
State/Union Territory
District
Navsari
Panch Mahals
Patan
Porbandar
Rajkot
Sabar Kantha
Surat
Surendranagar
Tapi
The Dangs
Vadodara
Valsad
Haryana
Ambala
Bhiwani
Faridabad
Fatehabad
Gurgaon
Hisar
Jhajjar
Jind
Kaithal
Karnal
Kurukshetra
Mahendragarh
Mewat
Panchkula
Palwal
Panipat
Rewari
Rohtak
Sirsa
Sonipat
Yamunanagar
Himachal Pradesh
Bilaspur
Chamba
Hamirpur
Kangra
Kinnaur
Kullu
Lahul & Spiti
Index C
Index A
Dds(a)
Ddc(a)
0.097
0.146
0.134
0.109
0.112
0.139
0.117
0.133
0.105
0.174
0.114
0.121
0.108
0.171
0.154
0.122
0.126
0.161
0.132
0.154
0.117
0.210
0.129
0.138
-2.614
3.241
0.817
-0.624
-3.291
2.276
-2.965
1.044
-1.105
0.643
-2.847
-0.338
-0.161
0.107
0.010
-0.045
-0.251
0.058
-0.287
0.012
-0.074
0.027
-0.237
-0.056
0.109
0.126
0.132
0.126
0.131
0.121
0.121
0.124
0.126
0.129
0.120
0.119
0.223
0.117
0.165
0.137
0.125
0.119
0.119
0.127
0.118
0.122
0.145
0.152
0.144
0.150
0.138
0.138
0.141
0.144
0.148
0.136
0.135
0.287
0.132
0.198
0.159
0.143
0.134
0.134
0.145
0.134
-3.974
-0.901
0.606
-0.617
0.132
-2.416
-1.295
-1.343
-0.677
-0.232
-1.589
-1.564
12.195
-1.192
4.972
1.233
-0.674
-1.923
-2.356
-0.698
-2.326
-0.087
-0.025
0.006
-0.016
-0.003
-0.057
-0.031
-0.033
-0.018
-0.010
-0.037
-0.036
0.252
-0.027
0.100
0.022
-0.017
-0.044
-0.054
-0.020
-0.053
0.109
0.134
0.105
0.107
0.095
0.114
0.095
0.122
0.154
0.117
0.119
0.105
0.129
0.105
-0.615
6.851
-1.906
-4.596
-0.964
0.824
-0.356
-0.029
0.004
-0.041
-0.127
-0.011
-0.025
-0.004
173
Preliminary Demography of India
State/Union Territory
District
Mandi
Shimla
Sirmaur
Solan
Una
Jammu and Kashmir
Anantnag
Badgam
Bandipore
Baramula
Doda
Ganderbal
Jammu
Kargil
Kathua
Kishtwar
Kulgam
Kupwara
Leh(Ladakh)
Pulwama
Punch
Rajouri
Ramban
Reasi
Samba
Shupiyan
Srinagar
Udhampur
Jharkhand
Bokaro
Chatra
Deoghar
Dhanbad
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Jamtara
Khunti
Kodarma
Index C
Index A
Dds(a)
Ddc(a)
0.110
0.099
0.128
0.115
0.112
0.124
0.110
0.147
0.130
0.126
-0.895
-6.618
5.350
1.327
0.096
-0.072
-0.092
-0.005
-0.031
-0.034
0.193
0.207
0.157
0.159
0.173
0.170
0.105
0.142
0.130
0.169
0.166
0.225
0.080
0.171
0.176
0.191
0.193
0.177
0.119
0.151
0.123
0.149
0.239
0.261
0.186
0.190
0.210
0.205
0.117
0.166
0.150
0.204
0.200
0.290
0.087
0.207
0.214
0.237
0.240
0.216
0.135
0.178
0.140
0.175
8.367
7.999
-0.342
-0.182
1.365
0.756
-25.776
-0.687
-5.147
0.539
0.674
12.753
-3.972
1.602
1.928
4.643
2.241
1.341
-3.760
-0.605
-13.570
-1.658
0.176
0.144
0.029
0.083
0.048
0.033
-0.140
0.005
-0.002
0.025
0.042
0.205
-0.029
0.064
0.060
0.100
0.047
0.040
-0.012
0.016
-0.035
0.029
0.138
0.181
0.176
0.137
0.161
0.177
0.184
0.179
0.164
0.158
0.163
0.157
0.179
0.160
0.221
0.214
0.159
0.192
0.215
0.226
0.218
0.196
0.187
0.194
0.186
0.218
-4.514
2.153
2.446
-6.157
0.296
2.220
5.759
2.485
0.515
-0.204
0.285
-0.092
1.366
0.043
0.142
0.186
0.048
0.114
0.167
0.353
0.173
0.096
0.134
0.071
0.040
0.095
174
Statistical Tables
State/Union Territory
District
Latehar
Lohardaga
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Saraikela-Kharsawan
Simdega
Karnataka
Bagalkot
Bangalore
Bangalore Rural
Belgaum
Bellary
Bidar
Bijapur
Chamarajanagar
Chikkaballapura
Chikmagalur
Chitradurga
Dakshina Kannada
Davanagere
Dharwad
Gadag
Gulbarga
Hassan
Haveri
Kodagu
Kolar
Koppal
Mandya
Mysore
Raichur
Ramanagara
Shimoga
Tumkur
Udupi
Uttara Kannada
Yadgir
Index C
Index A
Dds(a)
Ddc(a)
0.183
0.164
0.195
0.163
0.169
0.125
0.138
0.133
0.188
0.144
0.152
0.224
0.196
0.242
0.195
0.204
0.143
0.160
0.154
0.232
0.169
0.180
1.624
0.226
2.948
0.865
1.487
-8.437
-2.110
-7.897
3.101
-1.583
-0.401
0.102
0.043
0.152
0.179
0.161
-0.046
0.019
0.019
0.177
0.042
0.037
0.140
0.103
0.103
0.127
0.135
0.128
0.140
0.093
0.099
0.089
0.107
0.097
0.106
0.114
0.119
0.137
0.088
0.117
0.095
0.105
0.140
0.090
0.095
0.142
0.094
0.101
0.094
0.085
0.102
0.158
0.162
0.115
0.115
0.145
0.156
0.146
0.162
0.102
0.110
0.097
0.120
0.108
0.119
0.128
0.136
0.159
0.096
0.133
0.105
0.117
0.162
0.098
0.106
0.165
0.104
0.112
0.104
0.093
0.113
0.188
3.352
-6.433
-0.643
4.708
3.801
1.768
3.859
-1.520
-1.200
-2.118
-0.613
-2.353
-0.833
0.217
0.541
4.211
-3.463
0.593
-0.730
-0.797
2.473
-3.199
-3.818
3.659
-1.531
-1.493
-3.728
-2.530
-1.092
3.319
0.048
-0.940
-0.096
-0.069
0.030
-0.020
0.055
-0.142
-0.141
-0.180
-0.137
-0.252
-0.167
-0.107
-0.041
0.048
-0.289
-0.073
-0.072
-0.139
0.036
-0.278
-0.385
0.061
-0.147
-0.188
-0.360
-0.203
-0.147
0.092
175
Preliminary Demography of India
State/Union Territory
District
Kerala
Alappuzha
Ernakulam
Idukki
Kannur
Kasaragod
Kollam
Kottayam
Kozhikode
Malappuram
Palakkad
Pathanamthitta
Thiruvananthapuram
Thrissur
Wayanad
Lakshadweep
Lakshadweep
Madhya Pradesh
Alirajpur
Anuppur
Ashoknagar
Balaghat
Barwani
Betul
Bhind
Bhopal
Burhanpur
Chhatarpur
Chhindwara
Damoh
Datia
Dewas
Dhar
Dindori
East Nimar
Guna
Gwalior
Harda
Hoshangabad
Indore
Jabalpur
Jhabua
Index C
Index A
Dds(a)
Ddc(a)
0.088
0.088
0.090
0.105
0.115
0.091
0.085
0.105
0.134
0.103
0.077
0.088
0.093
0.110
0.096
0.097
0.099
0.117
0.129
0.100
0.093
0.117
0.155
0.114
0.083
0.096
0.102
0.123
-3.857
-5.678
-1.528
1.979
2.680
-3.573
-4.415
2.283
18.217
1.241
-4.473
-5.894
-3.047
1.176
-0.344
-0.524
-0.166
-0.229
-0.072
-0.393
-0.344
-0.283
0.042
-0.281
-0.257
-0.533
-0.433
-0.059
0.110
0.124
0.000
-0.005
0.198
0.137
0.162
0.122
0.188
0.132
0.142
0.124
0.159
0.158
0.128
0.148
0.139
0.143
0.160
0.151
0.155
0.162
0.125
0.144
0.130
0.125
0.117
0.203
0.246
0.159
0.193
0.138
0.232
0.152
0.165
0.141
0.189
0.188
0.147
0.174
0.161
0.167
0.190
0.179
0.184
0.194
0.143
0.168
0.150
0.142
0.132
0.255
1.614
-0.291
0.641
-2.093
2.584
-1.084
-0.290
-2.614
0.471
1.077
-1.847
0.175
-0.258
-0.187
1.474
0.206
0.608
0.981
-2.102
-0.033
-0.953
-3.488
-3.695
2.478
0.128
0.014
0.074
-0.053
0.214
0.002
0.055
-0.056
0.060
0.139
-0.022
0.064
0.018
0.055
0.181
0.042
0.092
0.112
-0.040
0.022
-0.004
-0.070
-0.117
0.192
176
Statistical Tables
State/Union Territory
District
Katni
Mandla
Mandsaur
Morena
Narsimhapur
Neemuch
Panna
Raisen
Rajgarh
Ratlam
Rewa
Sagar
Satna
Sehore
Seoni
Shahdol
Shajapur
Sheopur
Shivpuri
Sidhi
Singrauli
Tikamgarh
Ujjain
Umaria
Vidisha
West Nimar
Maharashtra
Ahmadnagar
Akola
Amravati
Aurangabad
Bhandara
Bid
Buldana
Chandrapur
Dhule
Gadchiroli
Gondiya
Hingoli
Jalgaon
Jalna
Kolhapur
Index C
Index A
Dds(a)
Ddc(a)
0.146
0.137
0.130
0.152
0.128
0.128
0.158
0.153
0.146
0.146
0.144
0.148
0.144
0.149
0.128
0.145
0.141
0.168
0.163
0.168
0.173
0.155
0.133
0.155
0.158
0.157
0.171
0.159
0.149
0.180
0.146
0.147
0.188
0.181
0.171
0.171
0.168
0.173
0.169
0.175
0.146
0.169
0.164
0.202
0.194
0.201
0.210
0.183
0.154
0.183
0.188
0.186
0.035
-0.408
-1.053
0.655
-0.982
-0.735
0.616
0.485
0.046
0.032
-0.131
0.275
-0.096
0.206
-1.228
-0.038
-0.324
0.708
1.373
1.137
1.480
0.639
-1.202
0.279
0.876
1.020
0.057
0.020
-0.006
0.123
-0.013
-0.009
0.080
0.086
0.068
0.064
0.092
0.117
0.089
0.068
-0.015
0.043
0.045
0.072
0.156
0.116
0.139
0.100
0.012
0.044
0.114
0.141
0.118
0.113
0.104
0.140
0.103
0.133
0.125
0.102
0.128
0.107
0.103
0.137
0.122
0.144
0.102
0.134
0.128
0.116
0.163
0.114
0.153
0.143
0.114
0.146
0.120
0.115
0.158
0.138
0.168
0.114
0.673
-0.072
-1.209
3.292
-0.566
1.730
1.044
-1.084
0.988
-0.292
-0.602
0.928
1.144
1.987
-1.917
-0.193
-0.109
-0.275
0.098
-0.120
0.015
-0.049
-0.224
-0.024
-0.087
-0.130
0.020
-0.132
0.074
-0.396
177
Preliminary Demography of India
State/Union Territory
District
Latur
Mumbai
Mumbai Suburban
Nagpur
Nanded
Nandurbar
Nashik
Osmanabad
Parbhani
Pune
Raigarh
Ratnagiri
Sangli
Satara
Sindhudurg
Solapur
Thane
Wardha
Washim
Yavatmal
Manipur
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Senapati
Tamenglong
Thoubal
Ukhrul
Meghalaya
East Garo Hills
East Khasi Hills
Jaintia Hills
Ribhoi
South Garo Hills
West Garo Hills
West Khasi Hills
Mizoram
Aizawl
Champhai
Kolasib
Index C
Index A
Dds(a)
Ddc(a)
0.125
0.083
0.094
0.104
0.132
0.140
0.132
0.120
0.137
0.113
0.110
0.093
0.105
0.102
0.081
0.120
0.114
0.096
0.123
0.115
0.143
0.091
0.104
0.116
0.153
0.163
0.152
0.137
0.159
0.128
0.124
0.102
0.117
0.114
0.088
0.137
0.128
0.106
0.141
0.131
0.989
-4.261
-7.898
-2.001
2.172
1.501
3.830
0.361
1.478
-0.406
-0.422
-1.458
-1.088
-1.433
-1.258
0.983
-0.261
-0.974
0.393
0.118
-0.046
-0.573
-1.259
-0.448
0.013
0.047
0.012
-0.060
0.034
-0.568
-0.188
-0.226
-0.260
-0.302
-0.165
-0.152
-0.647
-0.163
-0.031
-0.145
0.124
0.115
0.127
0.134
0.113
0.128
0.129
0.159
0.125
0.142
0.129
0.146
0.155
0.128
0.147
0.148
0.189
0.143
-1.964
-3.272
-1.021
2.803
-12.814
-0.891
-0.165
16.024
-1.163
-0.006
-0.008
-0.004
0.004
-0.031
-0.004
-0.001
0.034
-0.003
0.180
0.163
0.221
0.200
0.192
0.174
0.225
0.219
0.195
0.283
0.249
0.238
0.211
0.290
-2.441
-20.435
11.752
2.906
0.633
-8.355
12.849
0.042
0.075
0.089
0.046
0.023
0.077
0.090
0.129
0.176
0.153
0.149
0.214
0.181
-29.641
8.863
0.310
-0.002
0.016
0.005
178
Statistical Tables
State/Union Territory
District
Lawngtlai
Lunglei
Mamit
Saiha
Serchhip
Nagaland
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Orissa
Anugul
Balangir
Baleshwar
Bargarh
Baudh
Bhadrak
Cuttack
Debagarh
Dhenkanal
Gajapati
Ganjam
Jagatsinghapur
Jajapur
Jharsuguda
Kalahandi
Kandhamal
Kendrapara
Kendujhar
Khordha
Koraput
Malkangiri
Mayurbhanj
Nabarangapur
Nayagarh
Index C
Index A
Dds(a)
Ddc(a)
0.186
0.153
0.173
0.162
0.140
0.228
0.181
0.209
0.194
0.163
11.319
0.659
5.293
1.810
-2.433
0.017
0.010
0.010
0.005
0.002
0.131
0.194
0.134
0.175
0.104
0.158
0.160
0.169
0.177
0.118
0.143
0.150
0.240
0.155
0.212
0.116
0.187
0.191
0.203
0.216
0.134
0.166
-9.696
5.725
-5.197
2.525
-15.956
5.720
2.567
6.588
10.610
-8.345
-0.464
-0.001
0.012
0.002
0.006
-0.018
0.019
0.008
0.017
0.025
-0.007
0.005
0.115
0.126
0.118
0.106
0.134
0.117
0.096
0.124
0.111
0.144
0.113
0.091
0.114
0.107
0.136
0.145
0.107
0.141
0.099
0.157
0.172
0.134
0.166
0.105
0.129
0.144
0.134
0.118
0.155
0.133
0.106
0.141
0.125
0.168
0.127
0.100
0.128
0.119
0.158
0.170
0.119
0.164
0.110
0.186
0.208
0.155
0.199
0.118
-0.697
0.871
-0.371
-2.210
0.587
-0.402
-6.821
0.111
-1.070
1.237
-2.481
-3.631
-1.198
-0.798
2.346
1.670
-2.002
3.386
-5.046
4.386
2.685
3.358
4.735
-1.470
-0.071
-0.030
-0.097
-0.131
0.004
-0.069
-0.332
-0.008
-0.081
0.022
-0.214
-0.167
-0.108
-0.049
0.024
0.031
-0.122
0.052
-0.257
0.102
0.071
0.025
0.120
-0.086
179
Preliminary Demography of India
State/Union Territory
District
Nuapada
Puri
Rayagada
Sambalpur
Subarnapur
Sundargarh
Puducherry
Karaikal
Mahe
Puducherry
Yanam
Punjab
Amritsar
Barnala
Bathinda
Faridkot
Fatehgarh Sahib
Firozpur
Gurdaspur
Hoshiarpur
Jalandhar
Kapurthala
Ludhiana
Mansa
Moga
Muktsar
Patiala
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Shahid Bhagat Singh Nagar
Tarn Taran
Rajasthan
Ajmer
Alwar
Banswara
Baran
Barmer
Bharatpur
Bhilwara
Bikaner
Bundi
Index C
Index A
Dds(a)
Ddc(a)
0.140
0.097
0.147
0.108
0.117
0.120
0.163
0.107
0.172
0.121
0.133
0.136
1.108
-4.239
2.307
-1.274
-0.173
-0.074
0.016
-0.209
0.045
-0.082
-0.030
-0.078
0.108
0.109
0.101
0.108
0.121
0.123
0.112
0.121
3.816
1.061
-6.245
1.177
-0.016
-0.003
-0.101
-0.004
0.107
0.106
0.105
0.108
0.101
0.119
0.105
0.103
0.098
0.101
0.104
0.106
0.103
0.113
0.108
0.102
0.111
0.106
0.099
0.116
0.120
0.118
0.117
0.121
0.113
0.135
0.117
0.114
0.108
0.112
0.116
0.119
0.115
0.127
0.121
0.113
0.125
0.118
0.109
0.131
0.351
-0.053
-0.345
0.173
-0.493
4.100
-0.525
-0.954
-3.115
-0.702
-1.208
-0.027
-0.465
0.993
0.653
-0.499
0.739
-0.094
-0.804
1.738
-0.207
-0.053
-0.128
-0.049
-0.063
-0.081
-0.210
-0.158
-0.259
-0.087
-0.328
-0.067
-0.096
-0.055
-0.148
-0.070
-0.068
-0.145
-0.071
-0.057
0.145
0.158
0.179
0.147
0.192
0.169
0.148
0.167
0.142
0.170
0.188
0.218
0.172
0.237
0.203
0.173
0.200
0.165
-1.047
0.880
2.108
-0.391
4.479
1.903
-0.633
1.506
-0.625
0.107
0.287
0.235
0.057
0.422
0.272
0.120
0.238
0.036
180
Statistical Tables
State/Union Territory
District
Chittaurgarh
Churu
Dausa
Dhaulpur
Dungarpur
Ganganagar
Hanumangarh
Jaipur
Jaisalmer
Jalor
Jhalawar
Jhunjhunun
Jodhpur
Karauli
Kota
Nagaur
Pali
Pratapgarh
Rajsamand
Sawai Madhopur
Sikar
Sirohi
Tonk
Udaipur
Sikkim
East District
North District
South District
West District
Tamil Nadu
Ariyalur
Chennai
Coimbatore
Cuddalore
Dharmapuri
Dindigul
Erode
Kancheepuram
Kanniyakumari
Karur
Krishnagiri
Madurai
Index C
Index A
Dds(a)
Ddc(a)
0.136
0.154
0.157
0.179
0.173
0.128
0.131
0.137
0.194
0.171
0.145
0.133
0.161
0.164
0.127
0.151
0.144
0.171
0.150
0.149
0.140
0.166
0.141
0.163
0.157
0.182
0.186
0.217
0.208
0.147
0.151
0.159
0.241
0.207
0.169
0.154
0.192
0.196
0.146
0.177
0.168
0.207
0.177
0.174
0.163
0.198
0.165
0.194
-1.388
0.067
0.298
1.409
1.254
-2.579
-2.056
-5.403
1.219
1.567
-0.595
-2.177
1.374
0.767
-2.631
-0.394
-0.955
0.738
-0.166
-0.300
-1.729
0.611
-0.841
1.403
0.021
0.135
0.122
0.158
0.161
-0.019
-0.002
0.123
0.112
0.207
0.057
0.015
0.316
0.138
-0.023
0.191
0.077
0.098
0.065
0.069
0.075
0.102
0.044
0.277
0.094
0.103
0.103
0.110
0.104
0.115
0.114
0.123
-13.821
0.950
2.516
9.562
-0.037
-0.004
-0.015
-0.010
0.102
0.089
0.085
0.100
0.108
0.093
0.080
0.099
0.087
0.092
0.108
0.094
0.114
0.098
0.093
0.111
0.121
0.102
0.087
0.110
0.095
0.101
0.121
0.104
0.328
-2.071
-2.663
0.818
1.219
-0.462
-2.618
1.014
-1.171
-0.278
1.561
-0.249
-0.077
-0.723
-0.604
-0.284
-0.120
-0.305
-0.446
-0.451
-0.309
-0.154
-0.148
-0.404
181
Preliminary Demography of India
State/Union Territory
District
Nagapattinam
Namakkal
Perambalur
Pudukkottai
Ramanathapuram
Salem
Sivaganga
Thanjavur
The Nilgiris
Theni
Thiruvallur
Thiruvarur
Thoothukkudi
Tiruchirappalli
Tirunelveli
Tiruppur
Tiruvannamalai
Vellore
Viluppuram
Virudhunagar
Tripura
Dhalai
North Tripura
South Tripura
West Tripura
Uttar Pradesh
Agra
Aligarh
Allahabad
Ambedkar Nagar
Auraiya
Azamgarh
Baghpat
Bahraich
Ballia
Balrampur
Banda
Bara Banki
Bareilly
Basti
Bijnor
Budaun
Index C
Index A
Dds(a)
Ddc(a)
0.096
0.082
0.099
0.105
0.095
0.093
0.095
0.093
0.084
0.089
0.099
0.091
0.098
0.093
0.098
0.090
0.104
0.104
0.109
0.094
0.106
0.089
0.110
0.117
0.105
0.102
0.105
0.103
0.092
0.098
0.110
0.100
0.109
0.103
0.109
0.098
0.116
0.115
0.123
0.104
0.019
-1.808
0.137
1.013
-0.027
-0.671
-0.036
-0.404
-0.636
-0.571
0.942
-0.444
0.300
-0.404
0.522
-1.047
1.364
2.101
3.116
-0.177
-0.206
-0.328
-0.064
-0.147
-0.173
-0.486
-0.174
-0.332
-0.132
-0.193
-0.421
-0.189
-0.205
-0.372
-0.363
-0.379
-0.235
-0.378
-0.258
-0.260
0.144
0.139
0.124
0.107
0.168
0.161
0.142
0.120
8.970
12.915
3.239
-28.088
0.015
0.016
-0.019
-0.143
0.146
0.151
0.140
0.135
0.141
0.147
0.145
0.183
0.139
0.179
0.161
0.155
0.150
0.151
0.149
0.174
0.171
0.178
0.162
0.156
0.165
0.173
0.170
0.224
0.162
0.218
0.192
0.183
0.176
0.178
0.175
0.211
-0.235
0.140
-0.967
-0.585
-0.183
-0.118
-0.085
1.851
-0.553
1.037
0.361
0.321
0.078
0.098
0.010
1.522
0.193
0.217
0.156
0.031
0.042
0.225
0.055
0.489
0.079
0.285
0.155
0.225
0.249
0.146
0.197
0.447
182
Statistical Tables
State/Union Territory
District
Bulandshahr
Chandauli
Chitrakoot
Deoria
Etah
Etawah
Faizabad
Farrukhabad
Fatehpur
Firozabad
Gautam Buddha Nagar
Ghaziabad
Ghazipur
Gonda
Gorakhpur
Hamirpur
Hardoi
Jalaun
Jaunpur
Jhansi
Jyotiba Phule Nagar
Kannauj
Kanpur Dehat
Kanpur Nagar
Kanshiram Nagar
Kaushambi
Kheri
Kushinagar
Lalitpur
Lucknow
Mahamaya Nagar
Mahoba
Mahrajganj
Mainpuri
Mathura
Mau
Meerut
Mirzapur
Moradabad
Muzaffarnagar
Pilibhit
Pratapgarh
Index C
Index A
0.154
0.156
0.173
0.144
0.158
0.139
0.141
0.155
0.143
0.148
0.146
0.142
0.149
0.159
0.134
0.135
0.162
0.131
0.144
0.125
0.158
0.152
0.136
0.106
0.170
0.165
0.161
0.155
0.169
0.114
0.154
0.142
0.151
0.149
0.156
0.149
0.142
0.157
0.160
0.152
0.146
0.135
0.182
0.185
0.209
0.168
0.187
0.162
0.164
0.184
0.167
0.174
0.172
0.166
0.175
0.189
0.155
0.155
0.193
0.151
0.168
0.142
0.188
0.179
0.157
0.119
0.205
0.198
0.191
0.183
0.204
0.128
0.181
0.166
0.178
0.175
0.185
0.174
0.165
0.187
0.190
0.180
0.171
0.156
183
Dds(a)
0.280
0.225
0.386
-0.284
0.257
-0.265
-0.362
0.196
-0.264
-0.034
-0.073
-0.542
-0.019
0.582
-1.170
-0.284
0.885
-0.533
-0.413
-0.903
0.292
0.078
-0.418
-3.880
0.498
0.421
0.775
0.356
0.401
-3.099
0.121
-0.101
0.087
0.008
0.307
-0.017
-0.442
0.347
0.867
0.236
-0.110
-0.807
Ddc(a)
0.231
0.140
0.116
0.117
0.136
0.040
0.071
0.132
0.096
0.127
0.077
0.157
0.189
0.278
0.042
0.012
0.362
0.001
0.169
-0.043
0.145
0.101
0.026
-0.398
0.158
0.154
0.340
0.247
0.131
-0.268
0.103
0.030
0.155
0.099
0.185
0.114
0.110
0.189
0.396
0.258
0.090
0.035
Preliminary Demography of India
State/Union Territory
District
Rae Bareli
Rampur
Saharanpur
Sant Kabir Nagar
Sant Ravidas Nagar
Shahjahanpur
Shrawasti
Siddharthnagar
Sitapur
Sonbhadra
Sultanpur
Unnao
Varanasi
Uttarakhand
Almora
Bageshwar
Chamoli
Champawat
Dehradun
Garhwal
Hardwar
Nainital
Pithoragarh
Rudraprayag
Tehri Garhwal
Udham Singh Nagar
Uttarkashi
West Bengal
Bankura
Barddhaman
Birbhum
Dakshin Dinajpur
Darjiling
Haora
Hugli
Jalpaiguri
Koch Bihar
Kolkata
Maldah
Murshidabad
Nadia
North 24 Parganas
Index C
Index A
Dds(a)
Ddc(a)
0.135
0.159
0.146
0.159
0.157
0.163
0.182
0.182
0.164
0.166
0.142
0.134
0.130
0.157
0.188
0.171
0.189
0.186
0.194
0.222
0.223
0.196
0.199
0.166
0.155
0.149
-0.824
0.375
-0.186
0.280
0.210
0.685
0.579
1.349
1.093
0.517
-0.443
-0.828
-1.271
0.044
0.185
0.153
0.137
0.117
0.272
0.155
0.358
0.417
0.184
0.128
0.028
-0.015
0.125
0.133
0.130
0.141
0.116
0.120
0.148
0.128
0.129
0.128
0.134
0.136
0.136
0.143
0.154
0.149
0.164
0.131
0.136
0.173
0.147
0.149
0.146
0.154
0.157
0.158
-1.420
0.194
-0.235
0.902
-10.648
-3.162
11.179
-1.239
-0.350
-0.343
0.544
2.573
0.626
-0.012
0.002
-0.002
0.008
-0.088
-0.026
0.094
-0.010
-0.003
-0.003
0.005
0.022
0.005
0.113
0.102
0.124
0.107
0.098
0.103
0.091
0.115
0.118
0.067
0.148
0.138
0.098
0.090
0.127
0.114
0.141
0.120
0.108
0.115
0.101
0.130
0.133
0.072
0.173
0.160
0.109
0.098
0.349
-3.325
2.091
-0.324
-1.211
-1.921
-5.587
0.790
0.934
-11.777
6.278
8.476
-3.372
-11.309
-0.223
-0.787
-0.085
-0.140
-0.219
-0.481
-0.805
-0.209
-0.125
-1.200
0.197
0.147
-0.613
-1.553
184
Statistical Tables
State/Union Territory
Index C
District
Paschim Medinipur
0.112
Purba Medinipur
0.111
Puruliya
0.134
South 24 Parganas
0.120
Uttar Dinajpur
0.157
Source:
Author’s calculations
Index A
0.126
0.125
0.155
0.136
0.186
185
Dds(a)
0.250
0.087
3.078
3.441
5.706
Ddc(a)
-0.393
-0.347
0.029
-0.306
0.223
Preliminary Demography of India
Table 5.A
Sex ratio in districts of India, 2011
State/Union Territory/
Females per 1000 males
All ages
0-6 years
7 years and above
District
Andaman and Nicorbar Islands
Nicobars
778
961
757
North & Middle Andaman
925
977
919
South Andaman
874
961
865
Andhra Pradesh
Adilabad
1003
942
1010
Anantapur
977
927
984
Chittoor
1002
931
1010
East Godavari
1005
969
1009
Guntur
1003
948
1009
Hyderabad
943
938
943
Karimnagar
1009
937
1016
Khammam
1010
958
1016
Krishna
997
953
1001
Kurnool
984
937
990
Mahbubnagar
975
932
982
Medak
989
954
994
Nalgonda
982
921
989
Nizamabad
1038
946
1049
Prakasam
981
932
987
Rangareddy
955
947
956
Sri Potti Sriramulu Nellore
986
945
991
Srikakulam
1014
953
1021
Visakhapatnam
1003
961
1008
Vizianagaram
1016
955
1023
Warangal
994
912
1003
West Godavari
1004
970
1008
Y.S.R.
984
919
992
Arunachal Pradesh
Anjaw
805
954
779
Changlang
914
954
906
Dibang Valley
808
831
804
East Kameng
1012
970
1021
East Siang
962
984
959
Kurung Kumey
1029
978
1040
Lohit
901
954
892
Lower Dibang Valley
919
945
915
Lower Subansiri
975
969
976
Papum Pare
950
963
948
Tawang
701
1005
669
186
Statistical Tables
State/Union Territory/
District
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam
Baksa
Barpeta
Bongaigaon
Cachar
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
Tinsukia
Udalguri
Bihar
Araria
Arwal
Aurangabad
Banka
Begusarai
Bhagalpur
Bhojpur
Buxar
Females per 1000 males
All ages
0-6 years
7 years and above
931
950
927
891
968
880
982
968
985
755
965
728
916
928
915
187
967
951
961
958
969
923
949
952
952
931
962
961
946
956
946
922
956
961
958
965
974
962
945
951
946
948
966
962
955
965
955
958
941
945
965
957
956
954
961
948
963
962
994
916
958
951
958
950
958
963
957
958
971
965
968
950
960
959
971
920
950
949
952
927
964
961
946
955
944
915
966
961
959
967
978
963
943
951
944
945
966
921
927
916
907
894
879
900
922
954
941
945
939
911
934
915
925
913
925
910
900
890
867
897
922
Preliminary Demography of India
State/Union Territory/
District
Darbhanga
Gaya
Gopalganj
Jamui
Jehanabad
Kaimur (Bhabua)
Katihar
Khagaria
Kishanganj
Lakhisarai
Madhepura
Madhubani
Munger
Muzaffarpur
Nalanda
Nawada
Pashchim Champaran
Patna
Purba Champaran
Purnia
Rohtas
Saharsa
Samastipur
Saran
Sheikhpura
Sheohar
Sitamarhi
Siwan
Supaul
Vaishali
Chandigarh
Chandigarh
Chhattisgarh
Bastar
Bijapur
Bilaspur
Dakshin Bastar Dantewada
Dhamtari
Durg
Janjgir - Champa
Jashpur
Kabeerdham
Females per 1000 males
All ages
0-6 years
7 years and above
910
928
907
932
959
926
1015
945
1030
921
956
913
918
918
918
919
939
915
916
956
907
883
912
876
946
966
941
900
915
897
914
923
911
925
931
924
879
925
870
898
917
894
921
929
919
936
985
926
906
950
896
892
899
891
901
923
896
930
953
925
914
925
912
906
928
900
909
941
902
949
922
954
926
940
923
890
925
882
899
932
892
984
934
994
925
942
921
892
894
892
818
867
812
1024
982
972
1022
1012
988
986
1004
997
991
978
957
1005
969
958
945
974
973
1030
982
975
1024
1018
993
992
1010
1003
188
Statistical Tables
State/Union Territory/
District
Korba
Koriya
Mahasamund
Narayanpur
Raigarh
Raipur
Rajnandgaon
Surguja
Uttar Bastar Kanker
Dadra and Nagar Haveli
Dadra & Nagar Haveli
Daman and Diu
Daman
Diu
Delhi
Central
East
New Delhi
North
North East
North West
South
South West
West
Goa
North Goa
South Goa
Gujarat
Ahmadabad
Amreli
Anand
Banas Kantha
Bharuch
Bhavnagar
Dohad
Gandhinagar
Jamnagar
Junagadh
Kachchh
Kheda
Mahesana
Narmada
Females per 1000 males
All ages
0-6 years
7 years and above
971
964
972
971
968
972
1018
960
1027
998
975
1002
993
943
1001
983
965
986
1017
976
1024
976
955
980
1007
975
1012
775
924
752
533
1030
905
923
500
1046
892
883
811
871
886
862
859
836
876
902
870
884
872
875
863
878
836
867
890
885
804
870
887
862
857
836
877
959
980
911
930
964
986
903
964
921
936
924
931
986
920
938
952
907
937
925
960
859
879
877
890
914
885
937
847
898
904
913
887
845
937
909
975
927
946
926
938
998
930
943
959
905
944
936
963
189
Preliminary Demography of India
State/Union Territory/
District
Navsari
Panch Mahals
Patan
Porbandar
Rajkot
Sabar Kantha
Surat
Surendranagar
Tapi
The Dangs
Vadodara
Valsad
Haryana
Ambala
Bhiwani
Faridabad
Fatehabad
Gurgaon
Hisar
Jhajjar
Jind
Kaithal
Karnal
Kurukshetra
Mahendragarh
Mewat
Panchkula
Palwal
Panipat
Rewari
Rohtak
Sirsa
Sonipat
Yamunanagar
Himachal Pradesh
Bilaspur
Chamba
Hamirpur
Kangra
Kinnaur
Kullu
Lahul & Spiti
Females per 1000 males
All ages
0-6 years
7 years and above
961
921
966
945
923
949
935
884
943
947
894
954
924
854
933
950
899
959
788
836
782
929
889
935
1004
944
1012
1007
963
1017
934
894
939
926
926
926
882
884
871
903
853
871
861
870
880
886
889
894
906
870
879
861
898
868
896
853
877
807
831
842
845
826
849
774
835
821
820
817
778
903
850
862
833
784
807
852
790
825
892
892
875
911
857
874
873
875
889
896
900
911
907
872
882
865
915
877
901
862
884
981
989
1096
1013
818
950
916
893
950
881
873
953
962
1013
993
995
1124
1032
805
949
906
190
Statistical Tables
State/Union Territory/
District
Mandi
Shimla
Sirmaur
Solan
Una
Jammu and Kashmir
Anantnag
Badgam
Bandipore
Baramula
Doda
Ganderbal
Jammu
Kargil
Kathua
Kishtwar
Kulgam
Kupwara
Leh(Ladakh)
Pulwama
Punch
Rajouri
Ramban
Reasi
Samba
Shupiyan
Srinagar
Udhampur
Jharkhand
Bokaro
Chatra
Deoghar
Dhanbad
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Jamtara
Khunti
Kodarma
Females per 1000 males
All ages
0-6 years
7 years and above
1012
913
1025
916
922
915
915
931
913
884
899
882
977
870
991
191
937
883
911
873
922
869
871
775
877
917
951
843
583
913
890
863
901
891
886
951
879
863
831
832
893
866
932
863
795
978
836
922
882
854
944
836
895
837
931
921
787
883
869
887
964
897
914
874
920
870
881
745
884
916
966
840
558
930
889
869
894
885
900
964
881
859
916
951
921
908
974
933
943
933
993
946
959
994
949
912
963
939
917
957
958
934
953
955
924
948
951
944
916
949
917
907
977
928
945
928
1000
950
961
1002
950
Preliminary Demography of India
State/Union Territory/
District
Latehar
Lohardaga
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Saraikela-Kharsawan
Simdega
Karnataka
Bagalkot
Bangalore
Bangalore Rural
Belgaum
Bellary
Bidar
Bijapur
Chamarajanagar
Chikkaballapura
Chikmagalur
Chitradurga
Dakshina Kannada
Davanagere
Dharwad
Gadag
Gulbarga
Hassan
Haveri
Kodagu
Kolar
Koppal
Mandya
Mysore
Raichur
Ramanagara
Shimoga
Tumkur
Udupi
Uttara Kannada
Yadgir
Females per 1000 males
All ages
0-6 years
7 years and above
964
964
964
985
961
990
985
965
989
929
947
925
1004
980
1009
949
922
953
921
926
920
950
937
952
948
955
946
958
937
961
1000
975
1005
984
908
945
969
978
952
954
989
968
1005
969
1018
967
967
978
962
1005
951
1019
976
983
989
982
992
976
995
979
1093
975
984
192
929
941
947
931
954
935
930
942
945
963
933
946
931
942
944
935
964
945
977
955
953
934
956
949
960
960
952
955
947
942
994
904
945
974
982
955
958
994
970
1009
973
1026
972
970
983
967
1009
952
1024
979
988
994
984
999
977
999
982
1106
979
993
Statistical Tables
State/Union Territory/
District
Kerala
Alappuzha
Ernakulam
Idukki
Kannur
Kasaragod
Kollam
Kottayam
Kozhikode
Malappuram
Palakkad
Pathanamthitta
Thiruvananthapuram
Thrissur
Wayanad
Lakshadweep
Lakshadweep
Madhya Pradesh
Alirajpur
Anuppur
Ashoknagar
Balaghat
Barwani
Betul
Bhind
Bhopal
Burhanpur
Chhatarpur
Chhindwara
Damoh
Datia
Dewas
Dhar
Dindori
East Nimar
Guna
Gwalior
Harda
Hoshangabad
Indore
Jabalpur
Jhabua
Females per 1000 males
All ages
0-6 years
7 years and above
1100
1028
1006
1133
1079
1113
1040
1097
1096
1067
1129
1088
1109
1035
947
954
958
962
960
960
957
963
960
962
964
967
948
960
1116
1035
1011
1155
1095
1129
1048
1114
1119
1079
1144
1100
1127
1044
946
908
951
1009
975
900
1021
981
970
838
911
951
884
966
913
875
941
961
1004
944
910
862
932
912
924
925
989
971
943
914
961
940
949
835
916
921
894
950
931
852
907
913
970
931
901
832
921
911
892
916
934
1018
980
898
1029
990
973
838
910
957
882
968
910
879
947
970
1011
947
912
866
934
912
929
926
1004
193
Preliminary Demography of India
State/Union Territory/
District
Katni
Mandla
Mandsaur
Morena
Narsimhapur
Neemuch
Panna
Raisen
Rajgarh
Ratlam
Rewa
Sagar
Satna
Sehore
Seoni
Shahdol
Shajapur
Sheopur
Shivpuri
Sidhi
Singrauli
Tikamgarh
Ujjain
Umaria
Vidisha
West Nimar
Maharashtra
Ahmadnagar
Akola
Amravati
Aurangabad
Bhandara
Bid
Buldana
Chandrapur
Dhule
Gadchiroli
Gondiya
Hingoli
Jalgaon
Jalna
Kolhapur
Females per 1000 males
All ages
0-6 years
7 years and above
948
934
951
1005
965
1011
966
921
973
839
825
842
917
900
920
959
918
965
907
910
906
899
927
895
955
916
962
973
931
980
930
883
938
896
925
891
927
907
930
918
906
920
984
954
989
968
946
971
939
913
944
902
888
905
877
889
875
952
910
961
916
921
915
901
886
904
954
919
960
953
946
954
897
922
892
963
931
970
934
942
947
917
984
912
928
959
941
975
996
935
922
929
953
194
839
900
927
848
939
801
842
945
876
956
944
868
829
847
845
948
948
950
928
989
930
941
960
951
977
1002
946
936
944
966
Statistical Tables
State/Union Territory/
District
Latur
Mumbai
Mumbai Suburban
Nagpur
Nanded
Nandurbar
Nashik
Osmanabad
Parbhani
Pune
Raigarh
Ratnagiri
Sangli
Satara
Sindhudurg
Solapur
Thane
Wardha
Washim
Yavatmal
Manipur
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Senapati
Tamenglong
Thoubal
Ukhrul
Meghalaya
East Garo Hills
East Khasi Hills
Jaintia Hills
Ribhoi
South Garo Hills
West Garo Hills
West Khasi Hills
Mizoram
Aizawl
Champhai
Kolasib
Females per 1000 males
All ages
0-6 years
7 years and above
924
872
932
838
874
835
857
910
852
948
926
951
937
897
944
972
932
978
931
882
938
920
853
930
940
866
953
910
873
915
955
924
959
1123
940
1143
964
862
977
986
881
999
1037
910
1049
932
872
941
880
918
875
946
916
950
926
859
936
947
915
951
1000
932
969
1011
1029
939
953
1006
948
919
919
945
932
943
912
941
948
921
1012
934
973
1023
1041
943
955
1017
952
968
1008
1008
951
944
979
981
975
961
969
956
973
980
975
967
1018
1019
950
938
979
983
1009
981
956
984
976
987
1013
982
951
195
Preliminary Demography of India
State/Union Territory/
District
Lawngtlai
Lunglei
Mamit
Saiha
Serchhip
Nagaland
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Orissa
Anugul
Balangir
Baleshwar
Bargarh
Baudh
Bhadrak
Cuttack
Debagarh
Dhenkanal
Gajapati
Ganjam
Jagatsinghapur
Jajapur
Jharsuguda
Kalahandi
Kandhamal
Kendrapara
Kendujhar
Khordha
Koraput
Malkangiri
Mayurbhanj
Nabarangapur
Nayagarh
Females per 1000 males
All ages
0-6 years
7 years and above
945
965
941
944
965
941
924
979
913
978
937
987
976
926
985
916
961
927
903
927
898
917
951
930
969
981
968
955
978
882
954
900
940
915
935
970
955
909
962
920
907
924
898
913
959
929
969
986
942
983
957
976
991
981
955
976
947
1042
981
967
972
951
1003
1037
1006
987
925
1031
1016
1005
1018
916
884
951
941
946
975
931
913
917
870
964
899
929
921
938
947
960
921
957
910
970
979
952
988
851
950
988
959
980
993
988
960
984
957
1055
992
971
979
953
1013
1050
1017
992
927
1043
1024
1014
1024
924
196
Statistical Tables
State/Union Territory/
District
Nuapada
Puri
Rayagada
Sambalpur
Subarnapur
Sundargarh
Puducherry
Karaikal
Mahe
Puducherry
Yanam
Punjab
Amritsar
Barnala
Bathinda
Faridkot
Fatehgarh Sahib
Firozpur
Gurdaspur
Hoshiarpur
Jalandhar
Kapurthala
Ludhiana
Mansa
Moga
Muktsar
Patiala
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Shahid Bhagat Singh Nagar
Tarn Taran
Rajasthan
Ajmer
Alwar
Banswara
Baran
Barmer
Bharatpur
Bhilwara
Bikaner
Bundi
Females per 1000 males
All ages
0-6 years
7 years and above
1020
971
1028
963
924
967
1048
955
1065
973
931
978
959
947
961
971
937
975
1048
1176
1031
1039
963
959
969
917
1059
1206
1038
1055
884
876
865
889
871
893
895
962
913
912
869
880
893
895
888
913
878
883
954
898
824
847
854
851
843
846
824
859
874
872
865
831
863
830
835
866
842
835
879
819
892
879
866
894
874
899
904
974
917
917
869
886
896
904
895
918
883
889
963
909
950
894
979
926
900
877
969
903
922
893
861
925
902
899
863
916
902
886
960
900
991
930
901
880
978
904
928
197
Preliminary Demography of India
State/Union Territory/
District
Chittaurgarh
Churu
Dausa
Dhaulpur
Dungarpur
Ganganagar
Hanumangarh
Jaipur
Jaisalmer
Jalor
Jhalawar
Jhunjhunun
Jodhpur
Karauli
Kota
Nagaur
Pali
Pratapgarh
Rajsamand
Sawai Madhopur
Sikar
Sirohi
Tonk
Udaipur
Sikkim
East District
North District
South District
West District
Tamil Nadu
Ariyalur
Chennai
Coimbatore
Cuddalore
Dharmapuri
Dindigul
Erode
Kancheepuram
Kanniyakumari
Karur
Krishnagiri
Madurai
Females per 1000 males
All ages
0-6 years
7 years and above
970
903
981
938
896
946
904
859
913
845
854
843
990
916
1006
887
854
892
906
869
912
909
859
917
849
868
845
951
891
964
945
905
952
950
831
969
915
890
920
858
844
861
906
889
909
948
888
959
987
895
1004
982
926
995
988
891
1006
894
865
899
944
841
962
938
890
948
949
882
961
958
920
965
872
769
914
941
946
897
948
950
865
755
910
940
1016
986
1001
984
946
998
992
985
1010
1015
956
990
892
964
963
895
911
942
956
967
961
946
924
939
1031
988
1005
994
950
1004
996
987
1015
1022
960
995
198
Statistical Tables
State/Union Territory/
District
Nagapattinam
Namakkal
Perambalur
Pudukkottai
Ramanathapuram
Salem
Sivaganga
Thanjavur
The Nilgiris
Theni
Thiruvallur
Thiruvarur
Thoothukkudi
Tiruchirappalli
Tirunelveli
Tiruppur
Tiruvannamalai
Vellore
Viluppuram
Virudhunagar
Tripura
Dhalai
North Tripura
South Tripura
West Tripura
Uttar Pradesh
Agra
Aligarh
Allahabad
Ambedkar Nagar
Auraiya
Azamgarh
Baghpat
Bahraich
Ballia
Balrampur
Banda
Bara Banki
Bareilly
Basti
Bijnor
Budaun
Females per 1000 males
All ages
0-6 years
7 years and above
1025
961
1032
986
913
993
1006
913
1017
1015
959
1022
977
967
978
954
917
958
1000
961
1004
1031
957
1039
1041
982
1046
990
937
995
983
954
987
1020
962
1027
1024
970
1030
1013
952
1020
1024
964
1030
988
951
992
993
932
1001
1004
944
1012
985
938
991
1009
962
1014
945
967
957
964
972
971
947
942
941
966
959
967
859
876
902
976
864
1017
858
891
933
922
863
908
883
959
913
859
835
871
902
929
895
916
837
933
897
968
898
930
900
922
870
902
864
877
902
983
859
1035
862
882
939
913
856
903
880
966
921
850
199
Preliminary Demography of India
State/Union Territory/
District
Bulandshahr
Chandauli
Chitrakoot
Deoria
Etah
Etawah
Faizabad
Farrukhabad
Fatehpur
Firozabad
Gautam Buddha Nagar
Ghaziabad
Ghazipur
Gonda
Gorakhpur
Hamirpur
Hardoi
Jalaun
Jaunpur
Jhansi
Jyotiba Phule Nagar
Kannauj
Kanpur Dehat
Kanpur Nagar
Kanshiram Nagar
Kaushambi
Kheri
Kushinagar
Lalitpur
Lucknow
Mahamaya Nagar
Mahoba
Mahrajganj
Mainpuri
Mathura
Mau
Meerut
Mirzapur
Moradabad
Muzaffarnagar
Pilibhit
Pratapgarh
Females per 1000 males
All ages
0-6 years
7 years and above
892
844
902
913
976
902
879
907
874
1013
921
1029
863
878
861
867
870
866
961
927
967
874
884
872
900
905
899
867
879
865
852
845
853
878
850
883
951
907
959
922
924
921
944
905
950
860
885
856
856
863
855
865
880
863
1018
916
1037
885
859
889
907
898
908
879
897
875
862
896
856
852
870
850
879
888
877
905
926
901
887
926
880
955
917
962
905
914
903
906
913
905
870
862
871
880
897
877
938
924
940
876
878
875
858
871
855
978
924
988
885
850
891
900
902
900
903
909
902
886
858
891
889
909
885
994
915
1007
200
Statistical Tables
State/Union Territory/
District
Rae Bareli
Rampur
Saharanpur
Sant Kabir Nagar
Sant Ravidas Nagar (Bhadohi)
Shahjahanpur
Shrawasti
Siddharthnagar
Sitapur
Sonbhadra
Sultanpur
Unnao
Varanasi
Uttarakhand
Almora
Bageshwar
Chamoli
Champawat
Dehradun
Garhwal
Hardwar
Nainital
Pithoragarh
Rudraprayag
Tehri Garhwal
Udham Singh Nagar
Uttarkashi
West Bengal
Bankura
Barddhaman
Birbhum
Dakshin Dinajpur
Darjiling
Haora
Hugli
Jalpaiguri
Koch Bihar
Kolkata
Maldah
Murshidabad
Nadia
North Twenty Four Parganas
Females per 1000 males
All ages
0-6 years
7 years and above
941
929
943
905
919
902
887
883
888
969
940
975
950
898
960
865
902
858
875
923
865
970
922
981
879
921
872
913
920
912
978
921
988
901
913
899
909
896
911
1142
1093
1021
981
902
1103
879
933
1021
1120
1078
919
959
921
901
889
870
890
899
869
891
812
899
888
896
915
1177
1127
1042
1001
903
1134
881
939
1057
1156
1111
923
966
954
943
956
954
971
935
958
954
942
899
939
957
947
949
943
947
952
948
943
964
946
949
948
930
945
963
955
947
955
942
956
955
974
931
959
955
941
897
938
956
946
950
201
Preliminary Demography of India
State/Union Territory/
District
Paschim Medinipur
Purba Medinipur
Puruliya
South Twenty Four Parganas
Uttar Dinajpur
Source:
Author’s calculations
Females per 1000 males
All ages
0-6 years
7 years and above
960
952
961
936
938
936
955
947
956
949
953
949
936
946
934
202
Statistical Tables
Table 5.B
Index of sex composition in districts of India, 2011
State/Union Territory/
Index of sex composition
All ages
0-6 years
7 years and above
District
Andaman and Nicorbar Islands
Nicobars
-0.025
0.006
-0.030
North & Middle Andaman
-0.006
0.021
-0.011
South Andaman
-0.063
0.032
-0.078
Andhra Pradesh
Adilabad
0.632
0.238
0.684
Anantapur
0.568
0.163
0.615
Chittoor
0.947
0.211
1.041
East Godavari
0.467
0.042
0.523
Guntur
1.230
0.785
1.273
Hyderabad
1.131
0.458
1.209
Karimnagar
0.036
0.298
-0.018
Khammam
0.969
0.217
1.059
Krishna
0.721
0.343
0.765
Kurnool
0.946
0.464
0.994
Mahbubnagar
0.653
0.323
0.696
Medak
0.532
0.26
0.570
Nalgonda
0.552
0.409
0.567
Nizamabad
0.537
0.075
0.593
Prakasam
0.509
0.263
0.532
Rangareddy
0.906
0.254
0.996
Sri Potti Sriramulu Nellore
0.515
0.189
0.553
Srikakulam
0.302
0.579
0.247
Visakhapatnam
0.730
0.298
0.784
Vizianagaram
0.993
0.582
1.038
Warangal
0.654
0.278
0.701
West Godavari
0.708
-0.020
0.799
Y.S.R.
0.930
0.591
0.961
Arunachal Pradesh
Anjaw
-0.012
0.004
-0.014
Changlang
-0.015
0.029
-0.021
Dibang Valley
-0.004
-0.003
-0.005
East Kameng
0.021
0.023
0.021
East Siang
0.008
0.024
0.006
Kurung Kumey
0.029
0.029
0.029
Lohit
-0.022
0.027
-0.029
Lower Dibang Valley
-0.004
0.007
-0.006
Lower Subansiri
0.011
0.016
0.010
Papum Pare
0.007
0.034
0.003
Tawang
-0.053
0.015
-0.063
203
Preliminary Demography of India
State/Union Territory/
District
Tirap
Upper Siang
Upper Subansiri
West Kameng
West Siang
Assam
Baksa
Barpeta
Bongaigaon
Cachar
Chirang
Darrang
Dhemaji
Dhubri
Dibrugarh
Dima Hasao
Goalpara
Golaghat
Hailakandi
Jorhat
Kamrup
Kamrup Metropolitan
Karbi Anglong
Karimganj
Kokrajhar
Lakhimpur
Morigaon
Nagaon
Nalbari
Sivasagar
Sonitpur
Tinsukia
Udalguri
Bihar
Araria
Arwal
Aurangabad
Banka
Begusarai
Bhagalpur
Bhojpur
Buxar
All ages
-0.004
-0.007
0.013
-0.068
-0.010
Index of sex composition
0-6 years
7 years and above
0.021
-0.007
0.007
-0.009
0.018
0.012
0.017
-0.081
0.006
-0.013
0.097
0.068
0.058
0.119
0.052
-0.059
0.023
0.086
0.060
-0.007
0.084
0.082
0.015
0.065
0.034
-0.087
0.058
0.094
0.060
0.098
0.120
0.233
0.014
0.049
0.039
0.040
0.080
0.165
0.334
0.170
0.298
0.090
0.117
0.089
0.525
0.195
0.039
0.195
0.175
0.107
0.168
0.270
0.275
0.009
0.262
0.143
0.192
0.169
0.576
0.128
0.168
0.345
0.290
0.160
0.086
0.036
0.043
0.094
0.048
-0.082
0.014
0.033
0.037
-0.014
0.072
0.066
0.004
0.046
-0.002
-0.147
0.073
0.074
0.050
0.086
0.117
0.191
-0.004
0.028
-0.005
0.002
0.068
-0.210
-0.034
-0.239
-0.265
-0.540
-0.737
-0.428
-0.119
0.655
0.097
0.393
0.264
-0.049
0.310
0.004
0.090
-0.314
-0.050
-0.319
-0.332
-0.595
-0.878
-0.482
-0.142
204
Statistical Tables
State/Union Territory/
District
Darbhanga
Gaya
Gopalganj
Jamui
Jehanabad
Kaimur (Bhabua)
Katihar
Khagaria
Kishanganj
Lakhisarai
Madhepura
Madhubani
Munger
Muzaffarpur
Nalanda
Nawada
Pashchim Champaran
Patna
Purba Champaran
Purnia
Rohtas
Saharsa
Samastipur
Saran
Sheikhpura
Sheohar
Sitamarhi
Siwan
Supaul
Vaishali
Chandigarh
Chandigarh
Chhattisgarh
Bastar
Bijapur
Bilaspur
Dakshin Bastar Dantewada
Dhamtari
Durg
Janjgir - Champa
Jashpur
Kabeerdham
All ages
-0.456
-0.140
0.699
-0.134
-0.098
-0.134
-0.285
-0.370
0.038
-0.157
-0.206
-0.260
-0.329
-0.786
-0.217
-0.038
-0.516
-1.091
-0.782
-0.128
-0.301
-0.255
-0.511
0.126
-0.034
-0.130
-0.546
0.546
-0.134
-0.656
Index of sex composition
0-6 years
7 years and above
0.285
-0.543
0.996
-0.287
0.393
0.759
0.379
-0.200
0.024
-0.110
0.213
-0.175
0.742
-0.414
-0.025
-0.405
0.517
-0.018
0.005
-0.174
0.109
-0.236
0.397
-0.333
0.068
-0.383
0.059
-0.888
0.224
-0.267
0.750
-0.147
0.797
-0.683
-0.412
-1.174
0.253
-0.894
0.724
-0.228
0.160
-0.357
0.152
-0.300
0.614
-0.651
0.145
0.142
0.089
-0.048
0.040
-0.151
0.333
-0.653
0.315
0.594
0.346
-0.189
-0.360
-0.683
-0.529
-0.172
-0.586
0.433
0.040
0.317
0.158
0.210
0.596
0.276
0.202
0.174
0.468
0.074
0.5
0.197
0.161
0.541
0.200
0.207
0.239
0.432
0.035
0.296
0.153
0.217
0.602
0.288
0.202
0.169
205
Preliminary Demography of India
State/Union Territory/
District
Korba
Koriya
Mahasamund
Narayanpur
Raigarh
Raipur
Rajnandgaon
Surguja
Uttar Bastar Kanker
Dadra and Nagar Haveli
Dadra & Nagar Haveli
Daman and Diu
Daman
Diu
Delhi
Central
East
New Delhi
North
North East
North West
South
South West
West
Goa
North Goa
South Goa
Gujarat
Ahmadabad
Amreli
Anand
Banas Kantha
Bharuch
Bhavnagar
Dohad
Gandhinagar
Jamnagar
Junagadh
Kachchh
Kheda
Mahesana
Narmada
All ages
0.139
0.077
0.295
0.030
0.292
0.643
0.434
0.314
0.184
Index of sex composition
0-6 years
7 years and above
0.246
0.125
0.146
0.067
0.175
0.313
0.040
0.029
0.161
0.312
0.840
0.618
0.367
0.445
0.448
0.302
0.173
0.186
-0.238
0.014
-0.276
-0.388
0.017
-0.006
0.002
-0.450
0.019
-0.111
-0.382
-0.071
-0.244
-0.481
-1.135
-0.883
-0.969
-0.646
-0.023
-0.260
-0.011
-0.130
-0.357
-0.704
-0.361
-0.639
-0.407
-0.126
-0.405
-0.081
-0.263
-0.500
-1.205
-0.967
-1.024
-0.689
0.056
0.096
-0.008
0.030
0.062
0.103
-1.035
0.136
-0.157
-0.045
-0.096
-0.103
0.361
-0.106
-0.022
0.127
-0.273
-0.032
-0.119
0.043
-1.369
-0.180
-0.275
-0.371
-0.002
-0.324
0.270
-0.331
-0.125
-0.096
-0.008
-0.228
-0.492
0.050
-1.004
0.179
-0.144
0.016
-0.114
-0.071
0.392
-0.075
-0.011
0.153
-0.309
-0.006
-0.068
0.042
206
Statistical Tables
State/Union Territory/
District
Navsari
Panch Mahals
Patan
Porbandar
Rajkot
Sabar Kantha
Surat
Surendranagar
Tapi
The Dangs
Vadodara
Valsad
Haryana
Ambala
Bhiwani
Faridabad
Fatehabad
Gurgaon
Hisar
Jhajjar
Jind
Kaithal
Karnal
Kurukshetra
Mahendragarh
Mewat
Panchkula
Palwal
Panipat
Rewari
Rohtak
Sirsa
Sonipat
Yamunanagar
Himachal Pradesh
Bilaspur
Chamba
Hamirpur
Kangra
Kinnaur
Kullu
Lahul & Spiti
All ages
0.107
0.044
-0.029
0.016
-0.241
0.094
-3.850
-0.076
0.190
0.056
-0.107
-0.091
Index of sex composition
0-6 years
7 years and above
0.026
0.113
0.095
0.041
-0.165
-0.008
-0.038
0.022
-0.789
-0.168
-0.159
0.135
-1.737
-4.182
-0.178
-0.060
0.074
0.205
0.056
0.057
-0.290
-0.089
0.073
-0.118
-0.261
-0.359
-0.495
-0.138
-0.532
-0.479
-0.304
-0.370
-0.254
-0.324
-0.193
-0.166
-0.144
-0.251
-0.156
-0.380
-0.150
-0.303
-0.227
-0.520
-0.303
-0.422
-0.535
-0.535
-0.256
-0.547
-0.429
-0.530
-0.409
-0.398
-0.578
-0.356
-0.485
-0.081
-0.274
-0.129
-0.418
-0.470
-0.427
-0.294
-0.751
-0.403
-0.241
-0.334
-0.488
-0.121
-0.530
-0.489
-0.272
-0.366
-0.233
-0.286
-0.170
-0.119
-0.140
-0.243
-0.162
-0.374
-0.102
-0.287
-0.219
-0.487
-0.290
0.059
0.094
0.250
0.406
-0.042
0.017
-0.003
-0.027
0.073
-0.048
-0.203
0.009
0.070
0.008
0.070
0.098
0.293
0.493
-0.050
0.008
-0.005
207
Preliminary Demography of India
State/Union Territory/
District
Mandi
Shimla
Sirmaur
Solan
Una
Jammu and Kashmir
Anantnag
Badgam
Bandipore
Baramula
Doda
Ganderbal
Jammu
Kargil
Kathua
Kishtwar
Kulgam
Kupwara
Leh(Ladakh)
Pulwama
Punch
Rajouri
Ramban
Reasi
Samba
Shupiyan
Srinagar
Udhampur
Jharkhand
Bokaro
Chatra
Deoghar
Dhanbad
Dumka
Garhwa
Giridih
Godda
Gumla
Hazaribagh
Jamtara
Khunti
Kodarma
All ages
0.264
-0.076
-0.051
-0.129
0.072
Index of sex composition
0-6 years
7 years and above
-0.006
0.301
0.020
-0.094
0.033
-0.064
-0.031
-0.145
-0.078
0.093
-0.012
-0.165
-0.044
-0.270
-0.029
-0.084
-0.418
-0.100
-0.153
-0.020
0.018
-0.344
-0.252
-0.060
-0.093
-0.191
-0.043
-0.060
-0.068
0.011
-0.306
-0.171
-0.535
-0.392
-0.039
-0.238
0.037
-0.079
-0.611
0.037
-0.195
0.009
-0.068
-0.367
0.01
-0.238
-0.049
-0.285
0.027
0.011
-0.156
-0.038
-0.217
-0.069
0.075
-0.124
-0.043
-0.272
-0.036
-0.083
-0.394
-0.120
-0.147
-0.024
0.033
-0.329
-0.294
-0.030
-0.097
-0.172
-0.052
-0.069
-0.055
0.019
-0.321
-0.185
-0.195
0.043
-0.113
-0.334
0.167
-0.035
0.023
-0.038
0.199
0.036
0.055
0.106
0.024
-0.020
0.266
0.196
0.028
0.267
0.297
0.267
0.265
0.199
0.078
0.127
0.090
0.113
-0.220
0.016
-0.150
-0.386
0.157
-0.077
0.004
-0.075
0.204
0.036
0.047
0.110
0.015
208
Statistical Tables
State/Union Territory/
District
Latehar
Lohardaga
Pakur
Palamu
Pashchimi Singhbhum
Purbi Singhbhum
Ramgarh
Ranchi
Sahibganj
Saraikela-Kharsawan
Simdega
Karnataka
Bagalkot
Bangalore
Bangalore Rural
Belgaum
Bellary
Bidar
Bijapur
Chamarajanagar
Chikkaballapura
Chikmagalur
Chitradurga
Dakshina Kannada
Davanagere
Dharwad
Gadag
Gulbarga
Hassan
Haveri
Kodagu
Kolar
Koppal
Mandya
Mysore
Raichur
Ramanagara
Shimoga
Tumkur
Udupi
Uttara Kannada
Yadgir
All ages
0.064
0.078
0.148
-0.085
0.353
0.073
-0.070
0.107
0.033
0.070
0.133
0.31
-1.200
0.019
0.512
0.356
0.077
0.116
0.184
0.129
0.271
0.177
0.593
0.198
0.184
0.151
0.214
0.426
0.066
0.161
0.207
0.224
0.327
0.463
0.366
0.143
0.358
0.391
0.635
0.188
0.193
209
Index of sex composition
0-6 years
7 years and above
0.191
0.050
0.103
0.076
0.261
0.139
0.301
-0.135
0.484
0.341
0.062
0.073
0.045
-0.086
0.262
0.085
0.257
0.009
0.105
0.066
0.160
0.13
0.112
0.780
0.098
0.299
0.396
0.131
0.145
0.077
0.112
0.143
0.099
0.187
0.101
0.173
0.111
0.221
0.228
0.171
0.095
0.192
0.218
0.094
0.350
0.279
0.137
0.235
0.280
0.120
0.141
0.154
0.342
-1.535
0.003
0.542
0.351
0.067
0.114
0.195
0.126
0.284
0.184
0.645
0.207
0.181
0.156
0.214
0.445
0.047
0.168
0.204
0.226
0.352
0.466
0.382
0.139
0.370
0.395
0.705
0.190
0.203
Preliminary Demography of India
State/Union Territory/
District
Kerala
Alappuzha
Ernakulam
Idukki
Kannur
Kasaragod
Kollam
Kottayam
Kozhikode
Malappuram
Palakkad
Pathanamthitta
Thiruvananthapuram
Thrissur
Wayanad
Lakshadweep
Lakshadweep
Madhya Pradesh
Alirajpur
Anuppur
Ashoknagar
Balaghat
Barwani
Betul
Bhind
Bhopal
Burhanpur
Chhatarpur
Chhindwara
Damoh
Datia
Dewas
Dhar
Dindori
East Nimar
Guna
Gwalior
Harda
Hoshangabad
Indore
Jabalpur
Jhabua
Index of sex composition
All ages
0-6 years
7 years and above
1.198
1.045
0.270
1.691
0.642
1.588
0.718
1.713
2.266
1.273
0.784
1.728
1.844
0.280
0.178
0.337
0.128
0.372
0.201
0.316
0.213
0.460
0.746
0.405
0.133
0.445
0.286
0.120
1.340
1.134
0.286
1.882
0.706
1.766
0.782
1.892
2.497
1.393
0.873
1.903
2.064
0.302
0.001
-0.001
0.002
0.184
0.098
-0.132
0.502
0.209
0.174
-0.705
-0.271
0.030
-0.393
0.201
-0.132
-0.203
0.006
0.168
0.167
0.020
-0.144
-0.635
-0.018
-0.135
-0.200
-0.147
0.186
0.239
0.086
-0.002
0.281
0.201
0.212
-0.602
0.013
0.022
-0.172
0.280
0.090
-0.211
-0.046
-0.010
0.172
0.101
-0.079
-0.658
0.016
-0.016
-0.279
0.018
0.123
0.182
0.100
-0.148
0.533
0.221
0.169
-0.718
-0.316
0.034
-0.420
0.189
-0.163
-0.202
0.016
0.203
0.168
0.012
-0.149
-0.633
-0.023
-0.153
-0.191
-0.176
0.206
210
Statistical Tables
State/Union Territory/
District
Katni
Mandla
Mandsaur
Morena
Narsimhapur
Neemuch
Panna
Raisen
Rajgarh
Ratlam
Rewa
Sagar
Satna
Sehore
Seoni
Shahdol
Shajapur
Sheopur
Shivpuri
Sidhi
Singrauli
Tikamgarh
Ujjain
Umaria
Vidisha
West Nimar
Maharashtra
Ahmadnagar
Akola
Amravati
Aurangabad
Bhandara
Bid
Buldana
Chandrapur
Dhule
Gadchiroli
Gondiya
Hingoli
Jalgaon
Jalna
Kolhapur
All ages
0.038
0.251
0.131
-0.800
-0.097
0.058
-0.132
-0.212
0.087
0.176
-0.096
-0.410
-0.117
-0.115
0.226
0.110
-0.006
-0.102
-0.431
0.050
-0.110
-0.218
0.107
0.031
-0.248
0.164
-0.105
0.015
0.079
-0.335
0.194
-0.283
-0.119
0.152
0.004
0.138
0.273
-0.025
-0.296
-0.082
0.192
211
Index of sex composition
0-6 years
7 years and above
0.108
0.030
0.214
0.258
0.036
0.145
-0.837
-0.789
-0.058
-0.103
0.010
0.065
-0.019
-0.146
0.075
-0.252
0.014
0.101
0.104
0.190
-0.326
-0.057
0.108
-0.483
-0.071
-0.120
-0.047
-0.123
0.205
0.229
0.145
0.107
-0.010
-0.004
-0.091
-0.101
-0.215
-0.456
-0.024
0.067
0.038
-0.126
-0.191
-0.218
0.036
0.118
0.094
0.024
0.055
-0.289
0.147
0.173
-1.267
-0.086
0.115
-1.056
0.090
-1.249
-0.731
0.203
-0.306
0.141
0.120
-0.230
-1.375
-0.591
-0.848
0.062
0.026
0.063
-0.222
0.205
-0.137
-0.029
0.136
0.049
0.134
0.291
0.007
-0.139
-0.003
0.333
Preliminary Demography of India
State/Union Territory/
District
Latur
Mumbai
Mumbai Suburban
Nagpur
Nanded
Nandurbar
Nashik
Osmanabad
Parbhani
Pune
Raigarh
Ratnagiri
Sangli
Satara
Sindhudurg
Solapur
Thane
Wardha
Washim
Yavatmal
Manipur
Bishnupur
Chandel
Churachandpur
Imphal East
Imphal West
Senapati
Tamenglong
Thoubal
Ukhrul
Meghalaya
East Garo Hills
East Khasi Hills
Jaintia Hills
Ribhoi
South Garo Hills
West Garo Hills
West Khasi Hills
Mizoram
Aizawl
Champhai
Kolasib
All ages
-0.154
-1.300
-3.100
0.139
-0.038
0.195
-0.226
-0.129
0.001
-1.118
0.146
1.027
0.255
0.512
0.299
-0.138
-2.621
0.030
-0.064
0.070
Index of sex composition
0-6 years
7 years and above
-0.396
-0.119
-0.320
-1.469
-0.109
-3.598
0.162
0.118
-0.226
-0.009
0.123
0.208
-0.788
-0.140
-0.381
-0.093
-0.374
0.059
-1.358
-1.105
0.086
0.148
0.112
1.157
-0.479
0.355
-0.316
0.626
-0.008
0.339
-0.679
-0.062
0.148
-3.065
0.006
0.028
-0.250
-0.037
0.006
0.074
0.053
-0.004
0.030
0.117
0.167
-0.002
0.007
0.101
0.005
0.004
0.002
0.031
0.032
0.050
-0.003
0.014
0.067
0.004
0.060
-0.006
0.029
0.130
0.184
-0.002
0.006
0.108
0.005
0.033
0.206
0.098
0.010
0.002
0.093
0.059
0.101
0.182
0.139
0.063
0.047
0.212
0.152
0.025
0.213
0.097
0.005
-0.003
0.079
0.050
0.103
0.019
0.005
0.105
0.039
0.026
0.103
0.017
0.002
212
Statistical Tables
State/Union Territory/
District
Lawngtlai
Lunglei
Mamit
Saiha
Serchhip
Nagaland
Dimapur
Kiphire
Kohima
Longleng
Mokokchung
Mon
Peren
Phek
Tuensang
Wokha
Zunheboto
Orissa
Anugul
Balangir
Baleshwar
Bargarh
Baudh
Bhadrak
Cuttack
Debagarh
Dhenkanal
Gajapati
Ganjam
Jagatsinghapur
Jajapur
Jharsuguda
Kalahandi
Kandhamal
Kendrapara
Kendujhar
Khordha
Koraput
Malkangiri
Mayurbhanj
Nabarangapur
Nayagarh
All ages
0.002
0.002
-0.005
0.008
0.009
Index of sex composition
0-6 years
7 years and above
0.032
-0.002
0.035
-0.002
0.028
-0.010
0.006
0.009
0.003
0.010
-0.035
0.006
-0.013
-0.007
-0.010
-0.041
-0.009
0.007
-0.008
0.018
0.022
0.078
0.017
0.067
-0.009
0.023
-0.017
0.012
0.001
0.022
0.032
0.024
-0.052
0.005
-0.025
-0.007
-0.015
-0.044
-0.011
0.009
-0.011
0.016
0.022
0.008
0.263
0.144
0.199
0.082
0.228
0.151
0.041
0.032
0.212
0.530
0.116
0.218
0.024
0.367
0.256
0.351
0.316
-0.132
0.457
0.171
0.603
0.346
-0.090
-0.132
0.222
0.214
0.147
0.103
0.086
-0.006
0.003
-0.179
0.121
-0.186
0.046
0.039
0.043
0.205
0.143
0.032
0.317
-0.026
0.352
0.199
0.378
0.427
-0.200
0.026
0.268
0.129
0.202
0.079
0.246
0.162
0.047
0.061
0.227
0.630
0.121
0.241
0.019
0.392
0.275
0.394
0.318
-0.158
0.477
0.170
0.638
0.339
-0.077
213
Preliminary Demography of India
State/Union Territory/
District
Nuapada
Puri
Rayagada
Sambalpur
Subarnapur
Sundargarh
Puducherry
Karaikal
Mahe
Puducherry
Yanam
Punjab
Amritsar
Barnala
Bathinda
Faridkot
Fatehgarh Sahib
Firozpur
Gurdaspur
Hoshiarpur
Jalandhar
Kapurthala
Ludhiana
Mansa
Moga
Muktsar
Patiala
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Shahid Bhagat Singh Nagar
Tarn Taran
Rajasthan
Ajmer
Alwar
Banswara
Baran
Barmer
Bharatpur
Bhilwara
Bikaner
Bundi
All ages
0.176
0.142
0.375
0.127
0.046
0.239
Index of sex composition
0-6 years
7 years and above
0.140
0.182
0.047
0.149
0.170
0.408
0.055
0.135
0.073
0.041
0.171
0.246
0.078
0.034
0.312
0.020
0.030
0.006
0.153
0.000
0.085
0.038
0.332
0.023
-0.551
-0.151
-0.418
-0.124
-0.165
-0.377
-0.404
0.127
-0.231
-0.090
-0.987
-0.182
-0.185
-0.159
0.032
-0.386
-0.073
-0.373
-0.241
-0.186
-0.757
-0.131
-0.271
-0.131
-0.135
-0.509
-0.689
-0.276
-0.264
-0.108
-0.555
-0.211
-0.162
-0.270
-0.066
-0.508
-0.104
-0.434
-0.245
-0.392
-0.528
-0.157
-0.446
-0.125
-0.172
-0.360
-0.369
0.182
-0.236
-0.090
-1.065
-0.181
-0.192
-0.144
0.044
-0.374
-0.071
-0.370
-0.243
-0.158
0.091
-0.667
0.259
-0.067
-0.405
-0.635
0.256
-0.339
-0.077
-0.243
-0.947
0.101
-0.063
-0.227
-0.680
0.020
-0.146
-0.134
0.146
-0.612
0.294
-0.066
-0.411
-0.615
0.297
-0.357
-0.067
214
Statistical Tables
State/Union Territory/
District
Chittaurgarh
Churu
Dausa
Dhaulpur
Dungarpur
Ganganagar
Hanumangarh
Jaipur
Jaisalmer
Jalor
Jhalawar
Jhunjhunun
Jodhpur
Karauli
Kota
Nagaur
Pali
Pratapgarh
Rajsamand
Sawai Madhopur
Sikar
Sirohi
Tonk
Udaipur
Sikkim
East District
North District
South District
West District
Tamil Nadu
Ariyalur
Chennai
Coimbatore
Cuddalore
Dharmapuri
Dindigul
Erode
Kancheepuram
Kanniyakumari
Karur
Krishnagiri
Madurai
All ages
0.171
-0.020
-0.230
-0.463
0.255
-0.412
-0.236
-0.808
-0.245
0.077
0.025
0.077
-0.356
-0.479
-0.257
0.098
0.355
0.137
0.205
-0.243
0.043
-0.008
0.048
0.204
Index of sex composition
0-6 years
7 years and above
-0.073
0.209
-0.171
0.009
-0.436
-0.194
-0.402
-0.464
0.010
0.300
-0.469
-0.404
-0.321
-0.224
-1.572
-0.688
-0.185
-0.248
-0.224
0.132
-0.054
0.039
-0.742
0.201
-0.432
-0.330
-0.526
-0.466
-0.190
-0.268
-0.401
0.181
-0.174
0.439
0.053
0.154
-0.122
0.258
-0.299
-0.232
-0.854
0.181
-0.126
0.015
-0.199
0.087
0.084
0.235
-0.076
-0.031
-0.015
0.000
0.025
-0.002
0.015
0.016
-0.093
-0.036
-0.020
-0.002
0.208
0.789
0.781
0.421
0.030
0.460
0.436
0.669
0.481
0.294
0.111
0.560
-0.052
0.609
0.420
-0.152
-0.016
0.165
0.221
0.603
0.221
0.093
0.061
0.212
0.245
0.790
0.814
0.497
0.032
0.493
0.454
0.662
0.509
0.319
0.112
0.598
215
Preliminary Demography of India
State/Union Territory/
District
Nagapattinam
Namakkal
Perambalur
Pudukkottai
Ramanathapuram
Salem
Sivaganga
Thanjavur
The Nilgiris
Theni
Thiruvallur
Thiruvarur
Thoothukkudi
Tiruchirappalli
Tirunelveli
Tiruppur
Tiruvannamalai
Vellore
Viluppuram
Virudhunagar
Tripura
Dhalai
North Tripura
South Tripura
West Tripura
Uttar Pradesh
Agra
Aligarh
Allahabad
Ambedkar Nagar
Auraiya
Azamgarh
Baghpat
Bahraich
Ballia
Balrampur
Banda
Bara Banki
Bareilly
Basti
Bijnor
Budaun
All ages
0.498
0.292
0.137
0.444
0.184
0.187
0.297
0.793
0.268
0.231
0.598
0.373
0.532
0.730
0.935
0.440
0.485
0.931
0.576
0.490
Index of sex composition
0-6 years
7 years and above
0.209
0.534
-0.005
0.326
-0.002
0.155
0.220
0.472
0.196
0.175
0.025
0.193
0.173
0.309
0.283
0.858
0.121
0.286
0.075
0.247
0.435
0.607
0.160
0.398
0.276
0.563
0.280
0.784
0.433
0.998
0.238
0.457
0.135
0.529
0.361
1.003
0.269
0.612
0.253
0.516
0.007
0.070
0.056
0.157
0.091
0.159
0.106
0.151
-0.005
0.057
0.048
0.152
-1.415
-0.936
-0.889
0.317
-0.416
1.292
-0.426
-0.666
-0.088
-0.149
-0.556
-0.414
-1.008
0.176
-0.390
-1.205
-1.593
-0.739
-0.300
0.140
-0.115
0.029
-0.459
0.353
-0.231
0.600
-0.141
0.241
-0.289
0.083
-0.749
-0.237
-1.380
-0.956
-0.972
0.345
-0.459
1.493
-0.419
-0.796
-0.063
-0.248
-0.612
-0.503
-1.105
0.197
-0.327
-1.331
216
Statistical Tables
State/Union Territory/
District
Bulandshahr
Chandauli
Chitrakoot
Deoria
Etah
Etawah
Faizabad
Farrukhabad
Fatehpur
Firozabad
Gautam Buddha Nagar
Ghaziabad
Ghazipur
Gonda
Gorakhpur
Hamirpur
Hardoi
Jalaun
Jaunpur
Jhansi
Jyotiba Phule Nagar
Kannauj
Kanpur Dehat
Kanpur Nagar
Kanshiram Nagar
Kaushambi
Kheri
Kushinagar
Lalitpur
Lucknow
Mahamaya Nagar
Mahoba
Mahrajganj
Mainpuri
Mathura
Mau
Meerut
Mirzapur
Moradabad
Muzaffarnagar
Pilibhit
Pratapgarh
All ages
-0.655
-0.207
-0.238
0.824
-0.539
-0.461
0.197
-0.498
-0.413
-0.724
-0.596
-1.141
0.151
-0.246
0.067
-0.354
-1.377
-0.439
-0.500
1.282
-0.434
-0.239
-0.403
-0.563
-1.617
-0.350
-0.217
-0.837
0.201
-0.167
-0.619
-0.024
-0.208
-0.473
-0.840
0.311
-0.754
-0.391
-0.694
-0.885
-0.411
0.635
217
Index of sex composition
0-6 years
7 years and above
-1.182
-0.565
0.541
-0.313
-0.039
-0.263
0.084
0.941
-0.306
-0.569
-0.297
-0.484
0.132
0.210
-0.270
-0.527
-0.110
-0.454
-0.402
-0.767
-0.529
-0.602
-1.326
-1.107
-0.118
0.200
0.155
-0.294
-0.160
0.103
-0.134
-0.386
-1.040
-1.411
-0.387
-0.442
-0.228
-0.541
0.030
1.479
-0.423
-0.437
-0.138
-0.248
-0.130
-0.440
-0.138
-0.626
-0.663
-1.776
-0.195
-0.366
0.096
-0.256
0.228
-0.982
0.039
0.237
-0.002
-0.186
-0.023
-0.720
0.114
-0.038
-0.066
-0.228
-0.304
-0.494
-0.526
-0.880
0.093
0.349
-0.976
-0.716
-0.139
-0.420
-0.112
-0.764
-1.089
-0.843
-0.045
-0.462
0.010
0.731
Preliminary Demography of India
State/Union Territory/
District
Rae Bareli
Rampur
Saharanpur
Sant Kabir Nagar
Sant Ravidas Nagar (Bhadohi)
Shahjahanpur
Shrawasti
Siddharthnagar
Sitapur
Sonbhadra
Sultanpur
Unnao
Varanasi
Uttarakhand
Almora
Bageshwar
Chamoli
Champawat
Dehradun
Garhwal
Hardwar
Nainital
Pithoragarh
Rudraprayag
Tehri Garhwal
Udham Singh Nagar
Uttarkashi
West Bengal
Bankura
Barddhaman
Birbhum
Dakshin Dinajpur
Darjiling
Haora
Hugli
Jalpaiguri
Koch Bihar
Kolkata
Maldah
Murshidabad
Nadia
North Twenty Four Parganas
All ages
0.015
-0.324
-0.724
0.187
0.055
-0.904
-0.286
0.288
-1.073
-0.194
0.539
-0.476
-0.444
Index of sex composition
0-6 years
7 years and above
0.199
-0.011
0.049
-0.372
-0.483
-0.753
0.209
0.190
-0.119
0.087
-0.182
-1.000
0.051
-0.329
0.111
0.332
0.137
-1.236
0.057
-0.223
0.110
0.609
-0.012
-0.545
-0.261
-0.472
0.433
0.141
0.115
0.040
-0.256
0.394
-0.464
-0.027
0.144
0.148
0.303
-0.134
0.023
0.016
-0.014
-0.038
-0.049
-0.146
-0.038
-0.399
-0.087
-0.203
-0.014
-0.067
-0.124
0.001
0.496
0.164
0.138
0.053
-0.276
0.458
-0.470
-0.018
0.196
0.173
0.359
-0.135
0.026
0.187
0.077
0.202
0.087
0.209
-0.102
0.374
0.206
0.018
-0.723
-0.015
0.444
0.126
0.352
0.345
0.756
0.484
0.177
0.153
0.717
0.478
0.449
0.331
0.140
0.526
1.395
0.600
0.881
0.154
-0.055
0.156
0.068
0.210
-0.244
0.330
0.161
-0.034
-0.892
-0.088
0.307
0.031
0.216
218
Statistical Tables
State/Union Territory/
District
Paschim Medinipur
Purba Medinipur
Puruliya
South Twenty Four Parganas
Uttar Dinajpur
Source:
Author’s calculations
All ages
0.438
-0.080
0.164
0.278
-0.052
219
Index of sex composition
0-6 years
7 years and above
0.728
0.379
0.401
-0.166
0.376
0.133
1.100
0.141
0.435
-0.115
Country/State/Union Territory
District
India
Jammu & Kashmir
Kupwara
Badgam
Leh(Ladakh)
Kargil
Punch
Rajouri
Kathua
Baramula
Bandipore
Srinagar
Ganderbal
Pulwama
Shupiyan
Anantnag
Kulgam
Doda
Ramban
Kishtwar
Udhampur
Reasi
Jammu
Samba
Himachal Pradesh
Chamba
Person
1210193422
12548926
875564
735753
147104
143388
476820
619266
615711
1015503
385099
1269751
297003
570060
265960
1070144
422786
409576
283313
231037
555357
314714
1526406
318611
6856509
518844
Provisional population totals, 2011
Population
Male
Female
623724248
586469174
6665561
5883365
475126
400438
390705
345048
92907
54197
80791
62597
252240
224580
332424
286842
327953
287758
542171
473332
201531
183568
675667
594084
158900
138103
297988
272072
136302
129658
552404
517740
216672
206114
213091
196485
149032
134281
120496
110541
298094
257263
166392
148322
815727
710679
168948
149663
3473892
3382617
260848
257996
220
Person
158789287
2008642
196983
152241
11816
20407
84112
118514
80157
161841
60325
155875
50551
97642
40271
206338
70331
71038
54745
39124
82638
55805
159868
38020
763864
69409
Population (0-6 years)
Male
Female
82952135
75837152
1080662
927980
106247
90736
83100
69141
6079
5737
10319
10088
44390
39722
64503
54011
43648
36509
86711
75130
31868
28457
83408
72467
27127
23424
53176
44466
21381
18890
112661
93677
37364
32967
36772
34266
28354
26391
20357
18767
43801
38837
29051
26754
89067
70801
21278
16742
400681
363183
35591
33818
Country/State/Union Territory
District
Kangra
Lahul & Spiti
Kullu
Mandi
Hamirpur
Una
Bilaspur
Solan
Sirmaur
Shimla
Kinnaur
Punjab
Gurdaspur
Kapurthala
Jalandhar
Hoshiarpur
Shahid Bhagat Singh Nagar
Fatehgarh Sahib
Ludhiana
Moga
Firozpur
Muktsar
Faridkot
Bathinda
Mansa
Patiala
Person
1507223
31528
437474
999518
454293
521057
382056
576670
530164
813384
84298
27704236
2299026
817668
2181753
1582793
614362
599814
3487882
992289
2026831
902702
618008
1388859
768808
1892282
Provisional population totals, 2011
Population
Male
Female
748559
758664
16455
15073
224320
213154
496787
502731
216742
237551
263541
257516
192827
189229
306162
270508
276801
253363
424486
388898
46364
37934
14634819
13069417
1212995
1086031
427659
390009
1140536
1041217
806921
775872
314415
299947
320603
279211
1866203
1621679
524289
468000
1070812
956019
476300
426402
327121
290887
744875
643984
408921
359887
1002112
890170
221
Person
160865
2994
50041
109963
47708
58200
41612
66349
67958
80778
7987
2941570
240945
82657
213460
162368
60523
60761
363086
102574
241319
102028
66675
145391
81466
204905
Population (0-6 years)
Male
Female
85888
74977
1487
1507
25504
24537
57496
52467
25357
22351
31117
27083
21983
19629
34948
31401
35202
32756
42018
38760
4090
3897
1593262
1348308
132133
108812
44160
38497
113916
99544
87333
75035
32217
28306
32972
27789
194734
168352
55059
47515
130701
110618
55759
46269
36022
30653
78420
66971
44481
36985
111667
93238
Country/State/Union Territory
District
Amritsar
Tarn Taran
Rupnagar
Sahibzada Ajit Singh Nagar
Sangrur
Barnala
Chandigarh
Chandigarh
Uttarakhand
Uttarkashi
Chamoli
Rudraprayag
Tehri Garhwal
Dehradun
Garhwal
Pithoragarh
Bageshwar
Almora
Champawat
Nainital
Udham Singh Nagar
Hardwar
Haryana
Panchkula
Ambala
Yamunanagar
Person
2490891
1120070
683349
986147
1654408
596294
1054686
1054686
10116752
329686
391114
236857
616409
1698560
686527
485993
259840
621927
259315
955128
1648367
1927029
25353081
558890
1136784
1214162
Provisional population totals, 2011
Population
Male
Female
1322088
1168803
590239
529831
357265
326084
524989
461158
878628
775780
317848
278446
580282
474404
580282
474404
5154178
4962574
168335
161351
193572
197542
111747
125110
296604
319805
893222
805338
326406
360121
240427
245566
124121
135719
290414
331513
130881
128434
494115
461013
858906
789461
1025428
901601
13505130
11847951
298919
259971
604044
532740
646801
567361
222
Person
266608
129863
69593
109263
175095
62990
117953
117953
1328844
44995
50753
30212
82422
196298
82099
62911
34650
77991
36531
122199
223445
284338
3297724
65180
123534
143189
Population (0-6 years)
Male
Female
146158
120450
71400
58463
37302
32291
59311
49952
95418
79677
34099
28891
63187
54766
63187
54766
704769
624075
23494
21501
26861
23892
15910
14302
43667
38755
103874
92424
43233
38866
34710
28201
18232
16418
40601
37390
19532
16999
64626
57573
117856
105589
152173
132165
1802047
1495677
35224
29956
68365
55169
78471
64718
Country/State/Union Territory
District
Kurukshetra
Kaithal
Karnal
Panipat
Sonipat
Jind
Fatehabad
Sirsa
Hisar
Bhiwani
Rohtak
Jhajjar
Mahendragarh
Rewari
Gurgaon
Mewat
Faridabad
Palwal
Delhi
North West
North
North East
East
New Delhi
Central
West
Person
964231
1072861
1506323
1202811
1480080
1332042
941522
1295114
1742815
1629109
1058683
956907
921680
896129
1514085
1089406
1798954
1040493
16753235
3651261
883418
2240749
1707725
133713
578671
2531583
Provisional population totals, 2011
Population
Male
Female
510370
453861
570595
502266
798840
707483
646324
556487
798948
681132
712254
619788
494834
446688
683242
611872
931535
811280
864616
764493
566708
491975
514303
442604
486553
435127
472254
423875
817274
696811
571480
517926
961532
837422
553704
486789
8976410
7776825
1960677
1690584
472260
411158
1188307
1052442
906721
801004
73846
59867
305926
272745
1349685
1181898
223
Person
115291
135136
194403
164778
187955
164579
118446
153495
211204
206023
125490
116160
109928
112184
197816
243206
238028
171699
1970510
443195
100879
296224
189519
11549
60385
282678
Population (0-6 years)
Male
63462
74217
106809
89881
105001
89702
64203
82862
114238
112491
69433
65485
61827
62874
108312
127786
129216
92188
1055735
237941
53888
157999
101371
6131
31752
151379
Female
51829
60919
87594
74897
82954
74877
54243
70633
96966
93532
56057
50675
48101
49310
89504
115420
108812
79511
914775
205254
46991
138225
88148
5418
28633
131299
Country/State/Union Territory
District
South West
South
Rajasthan
Ganganagar
Hanumangarh
Bikaner
Churu
Jhunjhunun
Alwar
Bharatpur
Dhaulpur
Karauli
Sawai Madhopur
Dausa
Jaipur
Sikar
Nagaur
Jodhpur
Jaisalmer
Barmer
Jalor
Sirohi
Pali
Ajmer
Tonk
Bundi
Person
2292363
2733752
68621012
1969520
1779650
2367745
2041172
2139658
3671999
2549121
1207293
1458459
1338114
1637226
6663971
2677737
3309234
3685681
672008
2604453
1830151
1037185
2038533
2584913
1421711
1113725
Provisional population totals, 2011
Population
Male
Female
1248700
1043663
1470288
1263464
35620086
33000926
1043730
925790
933660
845990
1243916
1123829
1053375
987797
1097390
1042268
1938929
1733070
1357896
1191225
654344
552949
784943
673516
706558
631556
859821
777405
3490787
3173184
1377120
1300617
1698760
1610474
1924326
1761355
363346
308662
1370494
1233959
937918
892233
535115
502070
1025895
1012638
1325911
1259002
729390
692321
579385
534340
224
Person
262815
323266
10504916
252376
232933
394396
313852
285395
580388
430833
215567
239449
198777
256802
914327
375752
498585
592959
130400
499328
313808
171699
293002
374745
200963
158088
Population (0-6 years)
Male
Female
143112
119703
172162
151104
5580212
4924704
136111
116265
124606
108327
207364
187032
165521
148331
155842
129553
311819
268569
231265
199568
116276
99291
129872
109577
106564
92213
138121
118681
491960
422367
204065
171687
264118
234467
313704
279255
69809
60591
262925
236403
165979
147829
90849
80850
154656
138346
197987
176758
106799
94164
83809
74279
Country/State/Union Territory
District
Bhilwara
Rajsamand
Dungarpur
Banswara
Chittaurgarh
Kota
Baran
Jhalawar
Udaipur
Pratapgarh
Uttar Pradesh
Saharanpur
Muzaffarnagar
Bijnor
Moradabad
Rampur
Jyotiba Phule Nagar
Meerut
Baghpat
Ghaziabad
Gautam Buddha Nagar
Bulandshahr
Aligarh
Mahamaya Nagar
Mathura
Agra
Person
2410459
1158283
1388906
1798194
1544392
1950491
1223921
1411327
3067549
868231
199581477
3464228
4138605
3683896
4773138
2335398
1838771
3447405
1302156
4661452
1674714
3498507
3673849
1565678
2541894
4380793
Provisional population totals, 2011
Population
Male
Female
1224483
1185976
582670
575613
698069
690837
908755
889439
784054
760338
1023153
927338
635495
588426
725667
685660
1566781
1500768
437950
430281
104596415
94985062
1835740
1628488
2194540
1944065
1925787
1758109
2508299
2264839
1226175
1109223
964319
874452
1829192
1618213
700724
601432
2481803
2179649
904505
770209
1848643
1649864
1958536
1715313
837446
728232
1368445
1173449
2356104
2024689
225
Person
356230
173944
239608
321288
209376
248585
179496
204140
499072
148753
29728235
505263
630329
549305
763000
370259
291320
488271
189088
663367
245232
537624
555429
240376
396853
638983
Population (0-6 years)
Male
Female
185917
170313
91977
81967
125077
114531
166923
154365
110047
99329
131595
116990
94348
85148
107132
97008
259948
239124
77227
71526
15653175
14075060
268356
236907
339201
291128
293785
255520
399613
363387
192981
177278
153448
137872
263961
224310
102953
86135
358621
304746
132925
112307
291617
246007
296894
258535
129098
111278
212111
184742
348298
290685
Country/State/Union Territory
District
Firozabad
Mainpuri
Budaun
Bareilly
Pilibhit
Shahjahanpur
Kheri
Sitapur
Hardoi
Unnao
Lucknow
Rae Bareli
Farrukhabad
Kannauj
Etawah
Auraiya
Kanpur Dehat
Kanpur Nagar
Jalaun
Jhansi
Lalitpur
Hamirpur
Mahoba
Banda
Chitrakoot
Fatehpur
Person
2496761
1847194
3712738
4465344
2037225
3002376
4013634
4474446
4091380
3110595
4588455
3404004
1887577
1658005
1579160
1372287
1795092
4572951
1670718
2000755
1218002
1104021
876055
1799541
990626
2632684
Provisional population totals, 2011
Population
Male
Female
1337141
1159620
984892
862302
1997242
1715496
2371454
2093890
1078525
958700
1610182
1392194
2126782
1886852
2380666
2093780
2204264
1887116
1636295
1474300
2407897
2180558
1753344
1650660
1007479
880098
882546
775459
845893
733267
736144
636143
964284
830808
2469114
2103837
895804
774914
1061310
939445
639392
578610
593576
510445
465937
410118
966123
833418
527101
463525
1385556
1247128
226
Person
369940
275616
647664
669681
297116
488615
644410
732695
662807
417145
521815
460898
292791
251533
220220
193969
243919
484529
219378
249154
206018
148557
124719
289764
171468
377020
Population (0-6 years)
Male
196925
146750
340501
352479
155624
256917
334562
381510
355722
218024
272810
238963
155414
132588
117748
102380
128679
259156
116678
134015
107644
78829
65751
152656
89927
197960
Female
173015
128866
307163
317202
141492
231698
309848
351185
307085
199121
249005
221935
137377
118945
102472
91589
115240
225373
102700
115139
98374
69728
58968
137108
81541
179060
Country/State/Union Territory
District
Pratapgarh
Kaushambi
Allahabad
Bara Banki
Faizabad
Ambedkar Nagar
Sultanpur
Bahraich
Shrawasti
Balrampur
Gonda
Siddharthnagar
Basti
Sant Kabir Nagar
Mahrajganj
Gorakhpur
Kushinagar
Deoria
Azamgarh
Mau
Ballia
Jaunpur
Ghazipur
Chandauli
Varanasi
Sant Ravidas Nagar (Bhadohi)
Person
3173752
1596909
5959798
3257983
2468371
2398709
3790922
3478257
1114615
2149066
3431386
2553526
2461056
1714300
2665292
4436275
3560830
3098637
4616509
2205170
3223642
4476072
3622727
1952713
3682194
1554203
Provisional population totals, 2011
Population
Male
Female
1591480
1582272
838095
758814
3133479
2826319
1707951
1550032
1258455
1209916
1214225
1184484
1916297
1874625
1838988
1639269
594318
520297
1117984
1031082
1785629
1645757
1296046
1257480
1256158
1204898
870547
843753
1375367
1289925
2281763
2154512
1821242
1739588
1539608
1559029
2289336
2327173
1114888
1090282
1667557
1556085
2217635
2258437
1856584
1766143
1020789
931924
1928641
1753553
797164
757039
227
Person
427623
263467
832870
504272
347080
324550
539347
635383
202667
385308
545944
465777
372315
272117
402081
595495
551467
445259
680792
327500
448844
643020
538527
304229
478474
244012
Population (0-6 years)
Male
223300
136764
437827
261236
180112
168270
280754
328703
105412
195808
283786
242313
193740
140251
209004
312549
287733
231842
355385
170238
236586
335643
282402
153993
252332
128559
Female
204323
126703
395043
243036
166968
156280
258593
306680
97255
189500
262158
223464
178575
131866
193077
282946
263734
213417
325407
157262
212258
307377
256125
150236
226142
115453
Country/State/Union Territory
District
Mirzapur
Sonbhadra
Etah
Kanshiram Nagar
Bihar
Pashchim Champaran
Purba Champaran
Sheohar
Sitamarhi
Madhubani
Supaul
Araria
Kishanganj
Purnia
Katihar
Madhepura
Saharsa
Darbhanga
Muzaffarpur
Gopalganj
Siwan
Saran
Vaishali
Samastipur
Begusarai
Khagaria
Person
2494533
1862612
1761152
1438156
103804637
3922780
5082868
656916
3419622
4476044
2228397
2806200
1690948
3273127
3068149
1994618
1897102
3921971
4778610
2558037
3318176
3943098
3495249
4254782
2954367
1657599
Provisional population totals, 2011
Population
Male
Female
1312822
1181711
973480
889132
945157
815995
765529
672627
54185347
49619290
2057669
1865111
2674037
2408831
347614
309302
1800441
1619181
2324984
2151060
1157815
1070582
1460878
1345322
868845
822103
1695829
1577298
1601158
1466991
1042373
952245
995502
901600
2053043
1868928
2517500
2261110
1269677
1288360
1672121
1646055
2023476
1919622
1847058
1648191
2228432
2026350
1560203
1394164
880065
777534
228
Person
392230
308921
277672
244852
18582229
753429
993569
124919
643851
779360
424411
564131
341943
644083
601745
397468
377504
700992
817709
437031
532868
657316
591634
784203
532382
347048
Population (0-6 years)
Male
Female
206168
186062
160859
148062
147841
129831
129691
115161
9615280
8966949
386320
367109
516736
476833
64892
60027
333315
310536
403516
375844
218560
205851
288728
275403
173914
168029
329865
314218
307584
294161
206647
190821
195819
181685
363597
337395
426633
391076
224717
212314
275500
257368
342060
315256
312354
279280
404068
380135
278564
253818
181528
165520
Country/State/Union Territory
District
Bhagalpur
Banka
Munger
Lakhisarai
Sheikhpura
Nalanda
Patna
Bhojpur
Buxar
Kaimur (Bhabua)
Rohtas
Aurangabad
Gaya
Nawada
Jamui
Jehanabad
Arwal
Sikkim
North District
West District
South District
East District
Arunachal Pradesh
Tawang
West Kameng
East Kameng
Person
3032226
2029339
1359054
1000717
634927
2872523
5772804
2720155
1707643
1626900
2962593
2511243
4379383
2216653
1756078
1124176
699563
607688
43354
136299
146742
281293
1382611
49950
87013
78413
Provisional population totals, 2011
Population
Male
Female
1614014
1418212
1064307
965032
723280
635774
526651
474066
329593
305334
1495577
1376946
3051117
2721687
1431722
1288433
888356
819287
847784
779116
1547856
1414737
1310867
1200376
2266865
2112518
1145123
1071530
914368
841710
586202
537974
362945
336618
321661
286027
24513
18841
70225
66074
76663
70079
150260
131033
720232
662379
29361
20589
49568
37445
38974
39439
229
Person
532307
362548
221026
182234
118228
501046
905708
440847
286969
291785
493047
438065
762507
367231
313455
193946
123684
61077
4479
14957
15070
26571
202759
5630
11404
13997
Population (0-6 years)
Male
275248
186986
114841
95154
60952
259703
476906
230267
149097
150490
256108
225256
389247
184990
160287
101103
63728
31418
2361
7669
7737
13651
103430
2808
5803
7106
Female
257059
175562
106185
87080
57276
241343
428802
210580
137872
141295
236939
212809
373260
182241
153168
92843
59956
29659
2118
7288
7333
12920
99329
2822
5601
6891
Country/State/Union Territory
District
Papum Pare
Upper Subansiri
West Siang
East Siang
Upper Siang
Changlang
Tirap
Lower Subansiri
Kurung Kumey
Dibang Valley
Lower Dibang Valley
Lohit
Anjaw
Nagaland
Mon
Mokokchung
Zunheboto
Wokha
Dimapur
Phek
Tuensang
Longleng
Kiphire
Kohima
Peren
Person
176385
83205
112272
99019
35289
147951
111997
82839
89717
7948
53986
145538
21089
1980602
250671
193171
141014
166239
379769
163294
196801
50593
74033
270063
94954
Provisional population totals, 2011
Population
Male
Female
90447
85938
41974
41231
58589
53683
50467
48552
18657
16632
77289
70662
57992
54005
41935
40904
44226
45491
4396
3552
28127
25859
76544
68994
11686
9403
1025707
954895
132062
118609
100229
92942
71169
69845
84429
81810
198163
181606
83684
79610
101977
94824
26588
24005
37758
36275
140118
129945
49530
45424
230
Person
23675
11312
13859
12115
4627
25478
19317
9991
15540
1104
7714
23606
3390
285981
39538
20046
20101
19673
49595
27538
34931
8846
14335
36157
15221
Population (0-6 years)
Male
12060
5747
7187
6106
2351
13042
9904
5074
7856
603
3966
12082
1735
147111
20808
10260
10283
9985
25197
14377
18048
4700
7331
18277
7845
Female
11615
5565
6672
6009
2276
12436
9413
4917
7684
501
3748
11524
1655
138870
18730
9786
9818
9688
24398
13161
16883
4146
7004
17880
7376
Country/State/Union Territory
District
Manipur
Senapati
Tamenglong
Churachandpur
Bishnupur
Thoubal
Imphal West
Imphal East
Ukhrul
Chandel
Mizoram
Mamit
Kolasib
Aizawl
Champhai
Serchhip
Lunglei
Lawngtlai
Saiha
Tripura
West Tripura
South Tripura
Dhalai
North Tripura
Meghalaya
West Garo Hills
Person
2721756
354972
140143
271274
240363
420517
514683
452661
183115
144028
1091014
85757
83054
404054
125370
64875
154094
117444
56366
3671032
1724619
875144
377988
693281
2964007
642923
Provisional population totals, 2011
Population
Male
Female
1369764
1351992
183081
171891
71762
68381
137748
133526
120185
120178
209674
210843
253628
261055
225130
227531
94013
89102
74543
69485
552339
538675
44567
41190
42456
40598
201072
202982
63299
62071
32824
32051
79252
74842
60379
57065
28490
27876
1871867
1799165
877930
846689
447124
428020
194342
183646
352471
340810
1492668
1471339
324900
318023
231
Person
353237
45442
18072
34490
29831
66953
58239
60760
22954
16496
165536
14817
12702
52324
22068
9082
23594
21795
9154
444055
184656
108805
54416
96178
555822
112115
Population (0-6 years)
Male
182684
23766
9310
17731
15543
34365
29972
31451
11951
8595
83965
7487
6394
26375
11170
4716
12007
11091
4725
227354
95085
55876
27600
48793
282189
56637
Female
170553
21676
8762
16759
14288
32588
28267
29309
11003
7901
81571
7330
6308
25949
10898
4366
11587
10704
4429
216701
89571
52929
26816
47385
273633
55478
Country/State/Union Territory
District
East Garo Hills
South Garo Hills
West Khasi Hills
Ribhoi
East Khasi Hills
Jaintia Hills
Assam
Kokrajhar
Dhubri
Goalpara
Barpeta
Morigaon
Nagaon
Sonitpur
Lakhimpur
Dhemaji
Tinsukia
Dibrugarh
Sivasagar
Jorhat
Golaghat
Karbi Anglong
Dima Hasao
Cachar
Karimganj
Hailakandi
Person
317618
142574
385601
258380
824059
392852
31169272
886999
1948632
1008959
1693190
957853
2826006
1925975
1040644
688077
1316948
1327748
1150253
1091295
1058674
965280
213529
1736319
1217002
659260
Provisional population totals, 2011
Population
Male
Female
161372
156246
73322
69252
194628
190973
132445
125935
410360
413699
195641
197211
15954927
15214345
452965
434034
998346
950286
514162
494797
867891
825299
485328
472525
1440307
1385699
989919
936056
529484
511160
353043
335034
675986
640962
680114
647634
589454
560799
557944
533351
539949
518725
493482
471798
110566
102963
886616
849703
620722
596280
338766
320494
232
Person
57064
27401
86626
51547
134395
86674
4511307
131865
358841
165762
280506
159088
446238
267238
150880
99692
175038
154912
133858
117515
128395
183862
31758
246826
203203
109537
Population (0-6 years)
Male
Female
28886
28178
13886
13515
43867
42759
26353
25194
68548
65847
44012
42662
2305088
2206219
67584
64281
182662
176179
84818
80944
143487
137019
81567
77521
227853
218385
136458
130780
77064
73816
51266
48426
88790
86248
79146
75766
68392
65466
59859
57656
65472
62923
95971
87891
16239
15519
126223
120603
103760
99443
56244
53293
Country/State/Union Territory
District
Bongaigaon
Chirang
Kamrup
Kamrup Metropolitan
Nalbari
Baksa
Darrang
Udalguri
West Bengal
Darjiling
Jalpaiguri
Koch Bihar
Uttar Dinajpur
Dakshin Dinajpur
Maldah
Murshidabad
Birbhum
Barddhaman
Nadia
North Twenty Four Parganas
Hugli
Bankura
Puruliya
Haora
Kolkata
South Twenty Four Parganas
Person
732639
481818
1517202
1260419
769919
953773
908090
832769
91347736
1842034
3869675
2822780
3000849
1670931
3997970
7102430
3502387
7723663
5168488
10082852
5520389
3596292
2927965
4841638
4486679
8153176
Provisional population totals, 2011
Population
Male
Female
373590
359049
244675
237143
779608
737594
655630
604789
395804
374115
484825
468948
472134
435956
423617
409152
46927389
44420347
934796
907238
1980068
1889607
1453590
1369190
1550219
1450630
855104
815827
2061593
1936377
3629595
3472835
1791017
1711370
3975356
3748307
2655056
2513432
5172138
4910714
2819100
2701289
1840504
1755788
1497656
1430309
2502453
2339185
2362662
2124017
4182758
3970418
233
Person
113751
70177
194983
120500
90593
117400
149626
109263
10112599
180170
445025
332355
469971
178374
590237
979665
433186
788582
505995
902644
504660
405401
393562
497476
300052
976351
Population (0-6 years)
Male
Female
57874
55877
35835
34342
99397
95586
60434
60066
46156
44437
59823
57577
77096
72530
55618
53645
5187264
4925335
92728
87442
228381
216644
170598
161757
241547
228424
91564
86810
303540
286697
499040
480625
221877
211309
405057
383525
258853
247142
463502
439142
259277
245383
208632
196769
202165
191397
253337
244139
155475
144577
500011
476340
Country/State/Union Territory
District
Paschim Medinipur
Purba Medinipur
Jharkhand
Garhwa
Chatra
Kodarma
Giridih
Deoghar
Godda
Sahibganj
Pakur
Dhanbad
Bokaro
Lohardaga
Purbi Singhbhum
Palamu
Latehar
Hazaribagh
Ramgarh
Dumka
Jamtara
Ranchi
Khunti
Gumla
Simdega
Pashchimi Singhbhum
Person
5943300
5094238
32966238
1322387
1042304
717169
2445203
1491879
1311382
1150038
899200
2682662
2061918
461738
2291032
1936319
725673
1734005
949159
1321096
790207
2912022
530299
1025656
599813
1501619
Provisional population totals, 2011
Population
Male
Female
3032630
2910670
2631094
2463144
16931688
16034550
683984
638403
534209
508095
367952
349217
1258607
1186596
776741
715138
678504
632878
590390
559648
453101
446099
1405847
1276815
1076270
985648
232575
229163
1175696
1115336
1003876
932443
369534
356139
891179
842826
494037
455122
669240
651856
403450
386757
1493376
1418646
265939
264360
514730
510926
299905
299908
749314
752305
234
Person
663134
565759
5237582
233604
188620
128491
450527
262903
234807
216402
175356
367402
284353
75679
286322
316511
132730
273427
130606
212912
128460
388052
83323
168241
91297
254046
Population (0-6 years)
Male
Female
339781
323353
291899
273860
2695921
2541661
119325
114279
96108
92512
66097
62394
232924
217603
135552
127351
120246
114561
110706
105696
89219
86137
191677
175725
148733
135620
38592
37087
149006
137316
162599
153912
67593
65137
142129
131298
67816
62790
108786
104126
65950
62510
200327
187725
42707
40616
86072
82169
46230
45067
128292
125754
Country/State/Union Territory
District
Saraikela-Kharsawan
Orissa
Bargarh
Jharsuguda
Sambalpur
Debagarh
Sundargarh
Kendujhar
Mayurbhanj
Baleshwar
Bhadrak
Kendrapara
Jagatsinghapur
Cuttack
Jajapur
Dhenkanal
Anugul
Nayagarh
Khordha
Puri
Ganjam
Gajapati
Kandhamal
Baudh
Subarnapur
Balangir
Person
1063458
41947358
1478833
579499
1044410
312164
2080664
1802777
2513895
2317419
1506522
1439891
1136604
2618708
1826275
1192948
1271703
962215
2246341
1697983
3520151
575880
731952
439917
652107
1648574
Provisional population totals, 2011
Population
Male
Female
543232
520226
21201678
20745680
748332
730501
297014
282485
529424
514986
158017
154147
1055723
1024941
907135
895642
1253633
1260262
1184371
1133048
760591
745931
717695
722196
577699
558905
1339153
1279555
926058
900217
612597
580351
654898
616805
502194
460021
1166949
1079392
865209
832774
1777324
1742827
282041
293839
359401
372551
220993
218924
332897
319210
831349
817225
235
Person
153511
5035650
156185
61823
112946
38621
249020
253418
337757
274432
176793
153443
103517
251152
207310
132647
145690
101337
222275
164388
397920
82777
106379
59094
76536
206964
Population (0-6 years)
Male
Female
79235
74276
2603208
2432442
80246
75939
31907
29916
58505
54441
20149
18472
128529
120491
129494
123924
172992
164765
141412
133020
91577
85216
79869
73574
53661
49856
131259
119893
107945
99365
70927
61720
77311
68379
54759
46578
116350
105925
85444
78944
209573
188347
42141
40636
54266
52113
29928
29166
39314
37222
106090
100874
Country/State/Union Territory
District
Nuapada
Kalahandi
Rayagada
Nabarangapur
Koraput
Malkangiri
Chhattisgarh
Koriya
Surguja
Jashpur
Raigarh
Korba
Janjgir - Champa
Bilaspur
Kabeerdham
Rajnandgaon
Durg
Raipur
Mahasamund
Dhamtari
Uttar Bastar Kanker
Bastar
Narayanpur
Dakshin Bastar Dantewada
Bijapur
Person
606490
1573054
961959
1218762
1376934
612727
25540196
659039
2361329
852043
1493627
1206563
1620632
2662077
822239
1537520
3343079
4062160
1032275
799199
748593
1411644
140206
532791
255180
Provisional population totals, 2011
Population
Male
Female
300307
306183
785179
787875
469672
492287
604046
614716
677864
699070
303913
308814
12827915
12712281
334336
324703
1195145
1166184
425085
426958
749439
744188
612158
594405
816057
804575
1349928
1312149
411637
410602
762170
775350
1681521
1661558
2048856
2013304
511475
520800
397250
401949
372987
375606
697359
714285
70189
70017
263562
269229
128761
126419
236
Person
84893
214111
141167
201901
215518
105636
3584028
93249
371891
120079
191319
168437
219143
400695
140752
206372
421141
569447
131380
100575
97479
212819
22833
76450
39967
Population (0-6 years)
Male
Female
43066
41827
109977
104134
72195
68972
101577
100324
109376
106142
53369
52267
1824987
1759041
47376
45873
190191
181700
60840
59239
98473
92846
85748
82689
112656
106487
204757
195938
71348
69404
104461
101911
215065
206076
289815
279632
67038
64342
51073
49502
49344
48135
106904
105915
11561
11272
38134
38316
20203
19764
Country/State/Union Territory
District
Madhya Pradesh
Sheopur
Morena
Bhind
Gwalior
Datia
Shivpuri
Tikamgarh
Chhatarpur
Panna
Sagar
Damoh
Satna
Rewa
Umaria
Neemuch
Mandsaur
Ratlam
Ujjain
Shajapur
Dewas
Dhar
Indore
West Nimar
Barwani
Rajgarh
Person
72597565
687952
1965137
1703562
2030543
786375
1725818
1444920
1762857
1016028
2378295
1263703
2228619
2363744
643579
825958
1339832
1454483
1986597
1512353
1563107
2184672
3272335
1872413
1385659
1546541
Provisional population totals, 2011
Population
Male
Female
37612920
34984645
361685
326267
1068364
896773
926940
776622
1090647
939896
419432
366943
919405
806413
759891
685029
935906
826951
532866
483162
1254251
1124044
660478
603225
1156734
1071885
1224918
1138826
329527
314052
421640
404318
681439
658393
737365
717118
1016432
970165
779900
732453
805212
757895
1114267
1070405
1700483
1571852
953617
918796
699578
686081
791038
755503
237
Person
10548295
115577
299394
241562
254009
109000
280630
223570
279317
160884
351306
187275
321819
340727
99457
105548
173814
212009
264578
213107
223252
349262
407536
293913
261103
225662
Population (0-6 years)
Male
Female
5516957
5031338
61204
54373
164016
135378
131671
109891
138681
115328
58863
50137
148565
132065
118534
105036
147484
131833
84216
76668
182540
168766
97008
90267
168769
153050
180971
159756
51096
48361
55044
50504
90472
83342
109801
102208
137889
126689
111421
101686
117043
106209
182551
166711
215446
192090
152203
141710
134565
126538
117759
107903
Country/State/Union Territory
District
Vidisha
Bhopal
Sehore
Raisen
Betul
Harda
Hoshangabad
Katni
Jabalpur
Narsimhapur
Dindori
Mandla
Chhindwara
Seoni
Balaghat
Guna
Ashoknagar
Shahdol
Anuppur
Sidhi
Singrauli
Jhabua
Alirajpur
East Nimar
Burhanpur
Person
1458212
2368145
1311008
1331699
1575247
570302
1240975
1291684
2460714
1092141
704218
1053522
2090306
1378876
1701156
1240938
844979
1064989
749521
1126515
1178132
1024091
728677
1309443
756993
Provisional population totals, 2011
Population
Male
Female
768799
689413
1239378
1128767
683703
627305
701114
630585
799721
775526
295208
275094
648970
592005
663064
628620
1278448
1182266
569618
522523
351344
352874
525495
528027
1063302
1027004
694916
683960
841794
859362
649591
591347
444651
400328
541208
523781
379496
370025
577091
549424
614885
563247
514830
509261
362748
365929
673491
635952
388040
368953
238
Person
230714
293294
194801
203777
207282
82183
161406
188415
287433
139366
106665
144799
267351
176170
206815
201630
136680
153947
103005
188733
204255
207931
143954
203237
120141
Population (0-6 years)
Male
120023
153101
102194
105772
106353
42788
84463
97439
149988
73333
54155
73693
137105
90159
105479
106049
71424
79100
53025
98810
106355
107504
73024
105252
62557
Female
110691
140193
92607
98005
100929
39395
76943
90976
137445
66033
52510
71106
130246
86011
101336
95581
65256
74847
49980
89923
97900
100427
70930
97985
57584
Country/State/Union Territory
District
Gujarat
Kachchh
Banas Kantha
Patan
Mahesana
Sabar Kantha
Gandhinagar
Ahmadabad
Surendranagar
Rajkot
Jamnagar
Porbandar
Junagadh
Amreli
Bhavnagar
Anand
Kheda
Panch Mahals
Dohad
Vadodara
Narmada
Bharuch
The Dangs
Navsari
Valsad
Surat
Person
60383628
2090313
3116045
1342746
2027727
2427346
1387478
7208200
1755873
3799770
2159130
586062
2742291
1513614
2877961
2090276
2298934
2388267
2126558
4157568
590379
1550822
226769
1330711
1703068
6079231
Provisional population totals, 2011
Population
Male
Female
31482282
28901346
1096343
993970
1609148
1506897
694062
648684
1053337
974390
1244491
1182855
722459
665019
3787050
3421150
910266
845607
1975131
1824639
1114360
1044770
300967
285095
1404506
1337785
770651
742963
1490465
1387496
1088253
1002023
1187098
1111836
1227805
1160462
1070843
1055715
2150229
2007339
301270
289109
805945
744877
112976
113793
678423
652288
884064
819004
3399742
2679489
239
Person
7494176
310192
498790
179392
227701
337374
159378
801967
234196
424061
254066
63820
301395
168715
369460
243653
277300
348959
402903
474479
75226
170565
39387
129530
206309
710805
Population (0-6 years)
Male
Female
3974286
3519890
162116
148076
263953
234837
95215
84177
123428
104273
177699
159675
86276
73102
431421
370546
123964
110232
228713
195348
133861
120205
33687
30133
158328
143067
89782
78933
195965
173495
129791
113862
146939
130361
181428
167531
208014
194889
250513
223966
38844
36382
89119
81446
20065
19322
67427
62103
107110
99199
387131
323674
Country/State/Union Territory
District
Tapi
Daman & Diu
Diu
Daman
Dadra & Nagar Haveli
Dadra & Nagar Haveli
Maharashtra
Nandurbar
Dhule
Jalgaon
Buldana
Akola
Washim
Amravati
Wardha
Nagpur
Bhandara
Gondiya
Gadchiroli
Chandrapur
Yavatmal
Nanded
Hingoli
Parbhani
Jalna
Aurangabad
Person
806489
242911
52056
190855
342853
342853
112372972
1646177
2048781
4224442
2588039
1818617
1196714
2887826
1296157
4653171
1198810
1322331
1071795
2194262
2775457
3356566
1178973
1835982
1958483
3695928
Provisional population totals, 2011
Population
Male
Female
402398
404091
150100
92811
25639
26417
124461
66394
193178
149675
193178
149675
58361397
54011575
834866
811311
1055669
993112
2197835
2026607
1342152
1245887
936226
882391
621228
575486
1482845
1404981
665925
630232
2388558
2264613
604371
594439
662524
659807
542813
528982
1120316
1073946
1425593
1349864
1732567
1623999
609386
569587
946185
889797
1015116
943367
1928156
1767772
240
Person
84553
25880
6333
19547
49196
49196
12848375
231268
261397
513797
324389
206053
147467
299806
124536
481814
122931
136116
115104
223861
320441
444466
161086
251851
281495
516791
Population (0-6 years)
Male
Female
43497
41056
13556
12324
3294
3039
10262
9285
25575
23621
25575
23621
6822262
6026113
119694
111574
139345
122052
280915
232882
176116
148273
108425
97628
79318
68149
155572
144234
65005
59531
250223
231591
63398
59533
70015
66101
58842
56262
115090
108771
167346
153095
234249
210217
86250
74836
134971
116880
152430
129065
279582
237209
Country/State/Union Territory
District
Nashik
Thane
Mumbai Suburban
Mumbai
Raigarh
Pune
Ahmadnagar
Bid
Latur
Osmanabad
Solapur
Satara
Ratnagiri
Sindhudurg
Kolhapur
Sangli
Andhra Pradesh
Adilabad
Nizamabad
Karimnagar
Medak
Hyderabad
Rangareddy
Mahbubnagar
Nalgonda
Warangal
Person
6109052
11054131
9332481
3145966
2635394
9426959
4543083
2585962
2455543
1660311
4315527
3003922
1612672
848868
3874015
2820575
84665533
2737738
2552073
3811738
3031877
4010238
5296396
4042191
3483648
3522644
Provisional population totals, 2011
Population
Male
Female
3164261
2944791
5879387
5174744
5025165
4307316
1711650
1434316
1348089
1287305
4936362
4490597
2348802
2194281
1352468
1233494
1276262
1179281
864674
795637
2233778
2081749
1512524
1491398
759703
852969
416695
432173
1983274
1890741
1435972
1384603
42509881
42155652
1366964
1370774
1252191
1299882
1897068
1914670
1524187
1507690
2064359
1945879
2708694
2587702
2046247
1995944
1758061
1725587
1766257
1756387
241
Person
805302
1257080
876917
262229
290439
1067261
537346
344122
307726
199509
519781
307673
149486
68637
395143
295055
8642686
295811
268202
322897
348721
419500
595352
501878
354940
324410
Population (0-6 years)
Male
Female
427878
377424
655354
601726
459101
417816
139906
122323
150938
139501
569916
497345
292242
245104
191115
153007
164361
143365
107695
91814
277726
242055
163605
144068
77066
72420
35930
32707
214144
180999
158499
136556
4448330
4194356
152362
143449
137788
130414
166698
156199
178441
170280
216428
203072
305728
289624
259810
242068
184739
170201
169654
154756
Country/State/Union Territory
District
Khammam
Srikakulam
Vizianagaram
Visakhapatnam
East Godavari
West Godavari
Krishna
Guntur
Prakasam
Sri Potti Sriramulu Nellore
Y.S.R.
Kurnool
Anantapur
Chittoor
Karnataka
Belgaum
Bagalkot
Bijapur
Bidar
Raichur
Koppal
Gadag
Dharwad
Uttara Kannada
Haveri
Bellary
Person
2798214
2699471
2342868
4288113
5151549
3934782
4529009
4889230
3392764
2966082
2884524
4046601
4083315
4170468
61130704
4778439
1890826
2175102
1700018
1924773
1391292
1065235
1846993
1436847
1598506
2532383
Provisional population totals, 2011
Population
Male
Female
1391936
1406278
1340430
1359041
1161913
1180955
2140872
2147241
2569419
2582130
1963184
1971598
2268312
2260697
2441128
2448102
1712735
1680029
1493254
1472828
1454136
1430388
2040101
2006500
2064928
2018387
2083505
2086963
31057742
30072962
2427104
2351335
952902
937924
1112953
1062149
870850
829168
966493
958280
701479
689813
538477
526758
939127
907866
727424
709423
819295
779211
1280402
1251981
242
Person
267553
265404
231021
429234
492446
363536
406927
466285
360461
287368
313455
477198
426922
423165
6855801
605524
263781
303480
216885
272703
194199
127259
210194
146457
187754
341804
Population (0-6 years)
Male
Female
136637
130916
135929
129475
118149
112872
218923
210311
250086
242360
184513
179023
208341
198586
239408
226877
186581
173880
147719
139649
163371
150084
246345
230853
221539
205383
219141
204024
3527844
3327957
313599
291925
136780
127001
157212
146268
112103
104782
139917
132786
99460
94739
65464
61795
108231
101963
75225
71232
96518
91236
174946
166858
Country/State/Union Territory
District
Chitradurga
Davanagere
Shimoga
Udupi
Chikmagalur
Tumkur
Bangalore
Mandya
Hassan
Dakshina Kannada
Kodagu
Mysore
Chamarajanagar
Gulbarga
Yadgir
Kolar
Chikkaballapura
Bangalore Rural
Ramanagara
Goa
North Goa
South Goa
Lakshadweep
Lakshadweep
Kerala
Kasaragod
Person
1660378
1946905
1755512
1177908
1137753
2681449
9588910
1808680
1776221
2083625
554762
2994744
1020962
2564892
1172985
1540231
1254377
987257
1082739
1457723
817761
639962
64429
64429
33387677
1302600
Provisional population totals, 2011
Population
Male
Female
843411
816967
989602
957303
879817
875695
562896
615012
567483
570270
1354770
1326679
5025498
4563412
909441
899239
885807
890414
1032577
1051048
274725
280037
1511206
1483538
513359
507603
1307061
1257831
591104
581881
779401
760830
637504
616873
507514
479743
548060
534679
740711
717012
417536
400225
323175
316787
33106
31323
33106
31323
16021290
17366387
626617
675983
243
Person
177786
206935
176904
100579
100791
252307
988482
162147
155579
202670
52697
285956
94859
352162
185727
161877
124719
102019
101565
139495
75117
64378
7088
7088
3322247
149280
Population (0-6 years)
Male
Female
91973
85813
107181
99754
90271
86633
51448
49131
51347
49444
129253
123054
509268
479214
83846
78301
79197
76382
104169
98501
26661
26036
146192
139764
48854
46005
181955
170207
95620
90107
82814
79063
64129
60590
52400
49619
51811
49754
72669
66826
39316
35801
33353
31025
3715
3373
3715
3373
1695935
1626312
76149
73131
Country/State/Union Territory
District
Kannur
Wayanad
Kozhikode
Malappuram
Palakkad
Thrissur
Ernakulam
Idukki
Kottayam
Alappuzha
Pathanamthitta
Kollam
Thiruvananthapuram
Tamil Nadu
Thiruvallur
Chennai
Kancheepuram
Vellore
Tiruvannamalai
Viluppuram
Salem
Namakkal
Erode
The Nilgiris
Dindigul
Karur
Person
2525637
816558
3089543
4110956
2810892
3110327
3279860
1107453
1979384
2121943
1195537
2629703
3307284
72138958
3725697
4681087
3990897
3928106
2468965
3463284
3480008
1721179
2259608
735071
2161367
1076588
Provisional population totals, 2011
Population
Male
Female
1184012
1341625
401314
415244
1473028
1616515
1961014
2149942
1360067
1450825
1474665
1635662
1617602
1662258
551944
555509
970140
1009244
1010252
1111691
561620
633917
1244815
1384888
1584200
1723084
36158871
35980087
1878559
1847138
2357633
2323454
2010309
1980588
1959676
1968430
1238688
1230277
1744832
1718452
1780569
1699439
866740
854439
1134191
1125417
360170
374901
1081934
1079433
534392
542196
244
Person
265276
89720
323511
552771
288366
289126
289281
100107
168563
186022
91501
238062
290661
6894821
369854
418541
396254
406705
256299
378530
323102
140314
181188
61644
200034
98980
Population (0-6 years)
Male
Female
135189
130087
45776
43944
164800
158711
281958
270813
146947
141419
148428
140698
148047
141234
51132
48975
86113
82450
95556
90466
46582
44919
121481
116581
147777
142884
3542351
3352470
189244
180610
213084
205457
201499
194755
209168
197537
132664
123635
195294
183236
168560
154542
73345
66969
92638
88550
31099
30545
102989
97045
50855
48125
Country/State/Union Territory
District
Tiruchirappalli
Perambalur
Ariyalur
Cuddalore
Nagapattinam
Thiruvarur
Thanjavur
Pudukkottai
Sivaganga
Madurai
Theni
Virudhunagar
Ramanathapuram
Thoothukkudi
Tirunelveli
Kanniyakumari
Dharmapuri
Krishnagiri
Coimbatore
Tiruppur
Puducherry
Yanam
Puducherry
Mahe
Karaikal
Person
2713858
564511
752481
2600880
1614069
1268094
2402781
1618725
1341250
3041038
1243684
1943309
1337560
1738376
3072880
1863174
1502900
1883731
3472578
2471222
1244464
55616
946600
41934
200314
Provisional population totals, 2011
Population
Male
Female
1347863
1365995
281436
283075
373319
379162
1311151
1289729
797214
816855
627616
640478
1183112
1219669
803337
815388
670597
670653
1528308
1512730
624922
618762
967437
975872
676574
660986
858919
879457
1518595
1554285
926800
936374
772490
730410
963152
920579
1735362
1737216
1242974
1228248
610485
633979
27277
28339
466143
480457
19269
22665
97796
102518
245
Person
253633
55950
76775
260584
154543
114977
223910
169886
127682
287101
110919
183214
127447
170507
301275
161956
162118
203730
295584
221585
127610
6021
95432
4588
21569
Population (0-6 years)
Male
129947
29245
40579
137513
78826
58602
114386
86739
65123
148050
57258
93401
64790
86555
153437
82586
84840
105872
150580
113583
64932
3141
48459
2342
10990
Female
123686
26705
36196
123071
75717
56375
109524
83147
62559
139051
53661
89813
62657
83952
147838
79370
77278
97858
145004
108002
62678
2880
46973
2246
10579
Country/State/Union Territory
District
Andaman & Nicobar Islands
Nicobars
North & Middle Andaman
South Andaman
Person
379944
36819
105539
237586
Provisional population totals, 2011
Population
Male
Female
202330
177614
20705
16114
54821
50718
126804
110782
246
Person
39497
4225
11647
23625
Population (0-6 years)
Male
20094
2154
5890
12050
Female
19403
2071
5757
11575