Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
15
POVERTY AND CALORIE DEPRIVATION ACROSS SOCIO-ECONOMIC
GROUPS IN RURAL INDIA: A DISAGGREGATED ANALYSIS
Abha Gupta1 & Deepak K. Mishra2
This paper examines the linkages between calorie deprivation and poverty in rural India at a
disaggregated level. It aims to explore the trends and pattern in levels of nutrient intake across
social and economic groups. A spatial analysis at the state and NSS-region level unravels the
spatial distribution of calorie deprivation in rural India. The gap between incidence of poverty
and calorie deprivation has also been investigated. The paper also estimates the factors
influencing calorie deprivation in rural India. The study point out that nutritional deprivation is
high among marginalized social groups and regions. It is the poor, scheduled castes, scheduled
tribes, illiterate people, agricultural labourers and Muslims who are more likely to be calorie
deprived.
INTRODUCTION
Notwithstanding India’s relatively robust economic performance since the economic reforms in
early 1990’s, significant deficits in human development parameters, most notably in health and
nutrition standards, remain a cause of concern. India has the largest number of under-nourished
children in the world. Not only that prevalence of child under-nutrition in India (43 percent) much
higher than the world average (25 percent), its performance is worse than some of the poorest
economies of the world (World Food Programme 2009).This prevalence is even higher among
some socio-economic groups and regions. One of the WHO’s millennium development goal is to
reduce the number of stunted, wasted and underweight children by 2015. Only few years are left to
achieve this goal but in India still 38.4 percent children under the age of 3 are stunted, 19.1 percent
are wasted and 46 percent children are underweight (National Family Health Survey 2005-06).
There has been a sluggish decline in this percentage over a decade but this decline is unimpressive
when compared across states and different socio economic groups. Besides poor performance in
terms of some anthropometric measures, average per capita per day calorie and protein intake is
also showing a declining trend in the post economic reforms period. Consumption and expenditure
on cereal food items, which are a good source of energy has recorded a decline whereas other food
items (vegetables, fruits, meat/egg/fish, oil, milk) have shown a slightly increasing share in the
diet of the population. However, decline in calories is not seen as deterioration of health by some
researchers rather it is viewed as a sign of improvement resulted by an increase in income,
development of rural infrastructure, mechanization, urbanization, improvement in health and
change in taste and preferences (Deaton and Dreze 2009, 2010; Verma et al. 2008; Rao 2000).
Another group of scholars, however, links this with the increasing deterioration in health and
1
Research Scholar, Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal
Nehru University, New Delhi-110067. E-mail: [email protected]
2
Associate Professor, Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal
Nehru University, New Delhi-110067. E-mail: [email protected].
16
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
nutrition standards of the population (Patnaik 2004, 2007, 2010; Nasurudeen et al. 2006; Ray
2005:10; Mehta and Venkatraman 2000; Shariff and Mallick 1999; Mehta 1982).
India’s growth ‘turn around’ has not resulted in remarkable improvements in health and nutrition
outcomes, and it has raised questions on the inclusiveness of the growth process (Radhakrishna et
al. 2004). The high level of undernourishment among children (46 percent, National Family
Health survey 2005), the relatively high infant mortality rate (47/000 live births, Sample
Registration System 2010) and signs of distress among marginalized sections of the society in a
country which has witnessed remarkable growth in recent decades has been a widely discussed
issue (Dubey and Thorat 2012; Reddy and Mishra 2010). However, India’s poverty measured in
terms of head count ratio, which is a measure based on minimum calorie norm, has seen consistent
decline during this period of growth. This evidence of declining poverty is not accepted by all and
it remains a contested question (Deaton and Dreze 2009, 2010; Patnaik 2007, 2010)1. The rising
gap between official head-count ratio and share of population having less than minimum calorie
intake that formed the basis of official poverty line has been a matter of wide public concern and
debate (Dev 2005; Sen 2005; Jones and Sen 2001). This debate surrounds over the method of
poverty measurement and the focus has been on whether the official poverty line is adequate to
account for rising expenditure on health and education, which, until recently, were being provided
by the state. Most of the studies on poverty deal with the level of rural and urban poverty at the all
India and state level. This paper attempts to unravel these issues at a more disaggregated level- at
the level of NSS (National Sample Survey) regions and also in terms of various socio-economic
groups.
The broad objectives of this paper are outlined as follows:
1)
To examine changes in consumption of different food items in order to explain changes in
nutrition level.
2)
To estimate changes in level of nutrients and deficiency of different nutrients from the
recommended dietary allowances (RDA) at disaggregated level and to show the gaps
between levels of poverty and levels of nutrition deficiency.
3)
To estimate probability of being calorie deprived at disaggregated level using binary
logistic regression analysis.
From the policy perspective, the results of this paper have important implications for both the
methodology of poverty measurement and also for providing nutrition security to the vulnerable
sections of the population.
DATA AND METHODS
Data for this paper are obtained from National Sample Survey (NSS), 50th (1993-94), 61st (200405) and 66th (2009-10) Consumer Expenditure Schedules. These rounds of the survey, by the NSS
are large scale sample surveys and provide information on consumer expenditure quinquennially
as part of its “rounds”. Consumer expenditure survey gives information on quantity and value of
different goods in a household with a reference period of last 30 days for each state/UT, all India
and separately for rural and urban areas. Among these goods, information on 142 items of food are
collected which can be converted into nutrition values2.
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
17
In this paper, average per capita per day 2400 kcal has been used to show calorie deprivation
which is also used by Planning Commission to indirectly estimate head-count ratio for rural areas3.
For converting monthly household food consumption into per capita monthly consumption,
monthly household consumption is divided by household size. To get the per capita per day
consumption, per capita monthly consumption is divided by number 30. In order to show
probability of being calorie deprived across socio-economic and demographic groups, a logit
model has been fitted which is
1
1 + ݁ ି௫
P = 1/1+e-z..……………. (1)
Where P is the estimated probability, z is the predictor variable and e is the base of natural
logarithm with a value of 2.7183. After simplification, we get
ܲ=
Log z = P/1-P…………… (2)
Where (P/1-P) is called odds and log (P/1-P) is called log odds or the logit of P. Thus, equation
(2) becomes
logit P = Z…………….. (3)
The multivariate logistic function involves ‘n’ predictor variables which is represented by
P = (1/1+e-b0 + b1x1+b2x2 +……… bnxn) ………… (4)
Or,
logit P = (bo + b1x1 + b2x2 +…… bnxn)…………. (5)
The coefficients b1 represents the additive effect of one unit change in the predictor variable x1 on
the log odds of the response variable. Whereas one unit increase in the x1, holding other predictor
variable constant, multiplies the odd by the factor eb1. For this reason the quantity eb1 called the
odd ratio.
RESULTS AND DISCUSSION
Trends in Food Consumption in Rural India
Food is one of the basic needs for human survival. The variety of food that we consume
determines our nutrition behaviour in terms of calorie, protein, fat and other micronutrients. In
rural India, cereals have been the main constituents in people’s diet. Among cereals, rice recorded
an important share in total cereal consumption followed by wheat, coarse cereals, vegetables, milk
and fruits (Table 1).
During 1994-2005 the biggest decline was experienced by cereal consumption. This decline was
caused by fall particularly in coarse cereal consumption followed by rice and wheat consumption.
Pulse and milk consumption declined slightly. As far as change in consumption of ‘other food
items’ (vegetables, fruits, meat and edible oil) were concerned, highest increase was found in
vegetable consumption. Other food items recorded a slight increase in their consumption. A recent
round of NSS (66th Consumer Expenditure Survey, 2009-10) shows that cereals still hold the
highest place among all food items mainly because of higher rice consumption. However, cereal
consumption still continues to decline but the decline has been lesser during 2005-10 compared to
a decline during 1994-05. The consumption of wheat, rice and coarse cereals shows a marginal
decline. As far as consumption of ‘other food items’ (Vegetables, fruits, meat and edible oil) is
concerned, a marginal increase is seen in the consumption of these food items. From the analysis
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
18
above, it can be argued that last 15 years, often referred to as the ‘post economic reform period’,
rural India experienced a sharp decline in cereal consumption particularly coarse cereals, although
the precise linkages between economic reforms and calories deprivation needs to be examined
further. However, in recent five years (2005-2010) this decline has been minimal. The
consumption of other food items has been slightly increasing over the years but this increase is not
compensated by decline in cereals, as a result of which calorie and protein intakes are falling.
Table 1
Food Consumption Pattern and its Change in Rural India: 1994-2010
(Monthly Per Capita in kg*)
Year
Food Items
1993-94
2004-05
2009-10
Kg Change
(1994-2005)
Kg Change
(2005-2010)
13.40
4.32
6.79
12.11
4.19
6.38
11.35
4.34
6.13
-1.29
-0.13
-0.41
-0.76
0.15
-0.25
Coarse cereal
1.97
1.27
0.87
-0.70
-0.40
Pulses
0.76
0.71
0.66
-0.05
-0.05
Milk Liquid (litres)
3.94
3.87
4.08
-0.07
0.21
Vegetable
Fruits
Fruits (nos.)
Meat
Egg (nos.)
4.75
0.22
2.71
0.12
0.64
5.25
0.30
2.84
0.14
1.01
4.58
0.21
2.66
0.14
0.95
0.50
0.08
0.13
0.01
0.37
-0.67
-0.09
-0.18
0.00
-0.06
Fish
0.18
0.20
0.21
0.02
0.01
Cereal
Wheat
Rice
0.37
0.48
0.56
0.11
Edible Oil (litres)
Source: Authors' calculation from NSS 50th, 61st and 66th Consumer Expenditure Schedule.
Note: unit in kg unless otherwise specified in brackets after the food-item.
0.08
Change in Nutrient share of various Food Items and level of Poverty in Rural India
It is believed that food consumption in India has changed much which has caused overall decline
in calories. There are various factors which affect consumption of food items such as production,
availability and prices, lower level of unemployment, rise in per capita expenditure, change in
taste, climate, decline in physical activity, improvement in health status, urbanization, increased
awareness among consumers about food nutrients, access to safe drinking water, health care and
environmental hygiene for effective conversion of food into energy (Kumar et al. 2007; WHO
2003; Bansil 2003; Viswanathan 2001; Martorell and Ho 1984). A group of scholars considers this
decline in calories as a positive and anticipated development and for them this decline is not a
matter of serious concern (Radhakrishna 2005; Radhakrishna and Reddy 2004; Rao 2000). On the
other hand, Patnaik (2007) has argued that decline in calories leads to deterioration in health and
poverty and blames Planning Commission for using faulty prices to adjust poverty in India as the
reason for artificially lowering the estimates of poverty. The average per capita per day (PCPD)
calorie consumption declined from 2148 kcal to 2044 kcal between 1993/94 to 2004/05 in rural
India. On an average PCPD intake of protein also recorded a fall from 59.9 gm to 55.1 gm during
the same period (Table 2).
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
19
Table 2
Change in share of nutrients from different food items between 1993/94-2004/05
in rural India
Food Groups
Average Per capita per day intake of
Calorie (kcal)
Calorie
1993-94
2004-05
Change
809
755
-55
500
487
-13
220
140
-80
Average Per capita per day intake of
Protein (gm)
Protein
1993-94
2004-05
Change
17.5
16.3
-1.2
17.7
17.2
-0.4
6.6
4.3
-2.3
Rice
Wheat
Coarse cereals
Cereals and cereal
1530
1382
-147
41.8
37.9
substitutes
57
60
3
1.0
1.1
Root and Tubers
103
98
-5
0.0
0.0
Sugar and honey
Pulses, nuts and
106
92
-14
6.5
5.2
oilseeds
Vegetables and
44
53
10
1.9
1.7
fruits
15
16
1
2.2
2.3
Meat, eggs and fish
Milk and milk
132
131
-1
5.3
5.3
products
115
151
36
Oils and fats
Misc. food, food
47
61
14
1.1
1.5
products and
beverages
2148
2044
-104
59.9
55.1
Total
Source: Authors' calculation from NSS 50th and 61st Consumer Expenditure schedule.
-4.0
0.1
0.0
-1.3
-0.2
0.1
0.0
0.4
-4.9
As it has already been pointed out a sharp decline in cereal consumption and a slow rise in
consumption of other food items is observed from the analysis of secondary data. Table 2 clearly
shows that calorie decline has been accompanied by a decline in protein intake. The main reason
for this decline is fall in cereal calories particularly coarse cereals and pulse intake. Consumption
of oil and fat contributed in total calories but these food items are lacking in protein and are rich in
fat. As a result, all-India average fat intake has increased (Nutrition Intake, NSS 61st round
report). Besides oil & fat, miscellaneous food and beverages also contributed much in calorie and
protein consumption. Before discussing calorie deprivation and poverty at disaggregated level, it
would be appropriate first to talk about the trends at rural all-India level, which helps in
understanding the general situation of the poverty.
The levels of calorie deprivation and poverty in rural India, as presented in Table 3, shows that
around 72 percent rural population was not getting required calories (per capita per day intake of
2400 Kcal) during 1993-94 and this percent has risen to 80, an increase of 8.4 percentage points in
2004-05, whereas level of poverty has declined if we consider Planning Commission’s estimate
accurate. In 1993-94, the level of poverty was 37 percent which has declined to 28.3 percent in
2004-05. The gap between calorie poverty level and planning commission’s poverty level has
increased from 35 percentage points in 1993-94 to 52 percentage points in 2004-05, a 17.1 points
increase. This mismatch between poverty and calorie intake continues to remain a contested issue
among researchers.
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
20
Table 3
Change in Calorie Deprivation and Poverty Level in Rural India
between 1993/94 and 2004/05
Method of estimating
poverty
Percent Below 2400
Kcal
Percent Below Official
Poverty Line
Gap between Calorie
Poverty and Official
Poverty Line
1993-94
2004-05
Change between 1993/94 &
2004/05
71.60
80.0
8.40
37
28.3
-8.7
34.6
51.7
17.1
Source: Same as Table 2.
Change in level of Nutrients at disaggregated level
The Planning Commission of India has officially taken recommended calories4 of 2400 Kcal
PCPD for rural and 2100 Kcal PCPD for urban areas in order to estimate poverty5. Besides, 60
gms PCPD protein intake has also been recommended by ICMR for nutrition measurement4. Table
4 presents average PCPD intake of calories and protein and their change over a decade (1993/942004/05) with emphasis on deficit from RDA across various sections of the society. From a
demographic point of view it is found that never married persons consume lower level of calories
and protein than the married persons. In fact, this demographic group also shows highest decline
in nutrition parameters whereas widow/divorced/separated group enjoys relatively better access to
nutrition. Deficiency of calories is highest among never married persons showing 305 kcal
deficiency in 1993/94 which increased to 400 kcal during 2004/05. On the other hand are
widow/divorced/separated group whose calorie deficiency is much lower than other marital
groups. As far as deficiency of protein among marital groups is concerned, it has been higher
among never married persons than married. In rural India, different social classes show distinct
nutrition level from one another.
If we analyze family size, it is found that it is the bigger households who are suffering from lower
level of nutrition. In fact as size of a family increases, deficiency of calories and protein from
recommended tends to rise. Family consisting of 7-8 members showed a higher increase in
deficiency of calories than smaller families. In fact protein intake is quite low in these families.
Small families (1-4 members) tended to show much lower fall of calories and protein than other
family sizes. Similarly lower consumption of nutrients is found among less educated persons and
as education level rises, average calorie and protein intake also increases. Less educated persons
show a major decline in their nutrition level. Protein deficiency was much high in this group. On
the other hand are higher educated people who recorded an addition of 117 kcal in 1993/94 and
lower deficit of 17 kcal during 2004/05. This group added more protein in their diet in both
periods.
As far as religious groups are concerned, deficiency of nutrients is high among Muslims and
Christians. Least deficiency of calorie and protein was shown by ‘other’ religious people as only
223 kcal were lesser than recommendation.
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
21
Table 4
Change in level of nutrients and deficiency from recommendation between 1993/94-2004/05
among socio-economic and demographic groups in rural India
Calorie Intake
Marital Status
Never married
Married
Widowed/divorced/
separated
Household Size
1-4
5-6
7-8
Above 8
Education Group
Not Literate
Primary or below
Secondary
Higher
Religious Group
Hindu
Muslim
Christian
Others
Social Group
Scheduled Tribe
Scheduled Caste
Others
MPCE Groups (Percentile)
Lowest 5
10
20
30
40
50
60
70
80
90
95
Highest
Poverty Line
Below poverty Line
Above Poverty Line
Occupation Type
Self empl in non agr
Agricultural Labour
Other Labour
Self empl in agri
Others
Deficit from
RDA, 2400 Kcal
1993200494
05
199394
200405
2095
2194
2000
2081
305
206
2236
2129
2312
2088
2070
2091
Protein Intake
Deficit from RDA,
60 gm
1993200494
05
199394
200405
400
319
59
61
54
56
1
+1
6
4
164
271
61
56
+1
4
2199
2005
1954
1955
88
312
330
309
201
395
446
445
63
58
58
60
57
54
54
55
+3
2
2
0
3
6
6
5
2089
2162
2332
2517
1974
2031
2184
2383
311
238
68
+117
427
369
217
17
59
60
64
70
54
55
58
65
1
0
+4
+10
6
5
2
+5
2159
2041
1989
2307
2048
1979
2075
2177
241
359
411
93
352
421
325
223
60
57
52
69
55
53
53
62
0
3
8
+9
5
7
7
+2
1993
2023
2212
1895
1948
2097
407
377
188
505
452
304
54
57
62
49
53
57
6
3
+2
11
7
3
1324
1581
1717
1846
1964
2043
2150
2264
2405
2586
2798
3253
1369
1571
1676
1796
1881
1958
2038
2154
2287
2378
2570
3034
1076
819
683
554
436
357
250
136
+5
+186
+398
+853
1031
829
724
604
519
442
362
246
113
22
+170
+634
38
44
48
51
54
56
60
63
67
73
80
92
36
42
45
49
51
52
55
58
61
65
71
82
22
16
12
9
6
4
0
+3
+7
+13
+20
+32
24
18
15
11
9
8
5
2
+1
+5
+11
+22
1737
2388
1639
2202
663
12
762
198
48
67
44
59
12
+7
16
1
2076
1923
1958
2347
2233
2042
1849
1892
2181
2169
324
477
442
53
167
358
551
508
220
231
57
52
54
67
62
55
48
51
60
58
3
8
6
+7
+2
5
12
9
0
2
22
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
Source: Same as Table 2 Notes: Intakes are Average per capita per day in Kcal and metric Gram
respectively.
This religious group, on an average, added average 2 gm protein in their diet. In rural India,
Scheduled tribes (ST) and Scheduled castes (SC) are worst affected as both social groups show
lower intake of calorie as well as protein and also higher decline in nutrient intake compared to
other class people. The worst affected are the ST people who recorded highest level of calorie and
protein deficiency followed by SC in 2004-05. Calorie and protein deficiency had been lower
among 'other' social groups.
In terms of expenditure classes, it is found that it is the higher consumption expenditure groups
who are consuming sufficient calories and protein. The bottom classes suffer badly from lower
nutrient intake as well as its sharp decline. As consumption expenditure level rises, there is more
probability of consuming sufficient calories and protein. The top 20 percent showed higher intake
of calorie and protein and bottom 30 percent experienced as much as more than 500 kcal and 11
gm calorie and protein deficiency respectively during 2004/05. In terms of occupation groups in
rural areas, it is found that it is the agricultural labourers and ‘other’ labourers among which
calorie and protein intake is quite low and in fact these occupation groups also show a sharp
decline in nutrient intake over a decade. Agricultural labour and ‘other’ labourers are worst
affected occupation groups as both these groups had been unable to consume recommended intake
of calories and protein. The deficiency in the level of nutrients is much higher among agricultural
labour followed by ‘other’ labourers during 2004/05. Self employed in agriculture enjoyed better
level of nutrient intake as deficiency of calorie and protein was quite low in the same period.
Thus, from the above discussion it is found that there is significant relation between lower nutrient
consumption and socio-economic marginalization and deprivation. Never married persons, less
educated, lower Monthly per capita expenditure (MPCE) classes, SC, ST, Muslims, Agriculture
and ‘other’ labourers, big households are those sections of the society where nutrient intake is
quite low and at the same time decline in nutrient intake is considerably high among these groups.
Thus, the disaggregated picture of nutrition deficiency does not fit well with the argument that the
observed decline in calorie intake could be attributed to the diversity in the food basket of the
people as result of broader changes associated with economic development.
Level of Calorie Deprivation and Poverty
For reasons discussed above, methods of poverty estimation have been a widely discussed issue.
Even though the poverty line ensured the consumption of the normative calorie intake in 1973-74,
the rupee value of the poverty line at current prices is not sufficient for meeting the normative
requirements after other essential expenditures are taken into account (Sen 2005). As against this,
some scholars most notably Patnaik, have argued in favour of a ‘nutrition-invariant’ or ‘direct’
poverty estimate, by calculating the number of people not consuming the recommended daily
calorie intake. Some studies criticize direct method of poverty measurement through calorie and
deprivation (Deaton and Dreze, 2009; Verma et al. 2008; Dev 2005; Sen 2005; Rao, 2000). They
have highlighted the absurd results that it throws up when state level poverty estimates are carried
out. While the calorie-based approach has been termed as 'calorie fundamentalism' and has been
criticized for its narrow focus, the official poverty line based approach has been criticized for
being inconsistent with figures of calorie deprivation and malnutrition. One way of moving ahead
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
23
is to carry forward this comparison between percentage of population not having minimum
calories (on which the poverty line was based) and the official poverty estimates to a more
disaggregated level. This is what we have attempted here.
Table 5
Level of Calorie Deprivation and Poverty (Percentage) among Socio-Economic &
Demographic groups during 2004/05
Socio-Economic Demographic Groups
Calorie deprivation
Population Below Poverty line
Marital Status
82.30
31.3
Never Married
78.10
25.4
Currently Married
75.40
25.2
Widow/Divorced/Separated
Household Size
70.60
17.0
1-4
82.30
29.1
5-6
85.30
37.4
7-8
85.80
36.4
Above 8
Social Group
88.50
47.6
Scheduled Tribe
85.10
36.8
Scheduled Caste
77.10
22.7
Others
Religious Group
79.70
28.9
Hindu
84.40
29.3
Muslim
80.90
16.2
Christian
69.70
15.2
Others
Education Group
83.50
36.5
Not Literate
81.10
27.1
Primary or below
72.60
14.7
Secondary
59.70
5.0
Graduate or above
MPCE Groups (Rs.)
99.70
100.0
0-235
99.00
100.0
235-270
98.40
100.0
270-320
95.90
80.9
320-365(poverty line Rs.356.30)
92.70
Nil
365-410
89.30
Nil
410-455
83.80
Nil
455-510
77.20
Nil
510-580
67.60
Nil
580-690
57.40
Nil
690-890
43.00
Nil
890-1155
32.80
Nil
1155 & more
Occupation Type
81.60
23.5
Self employed in non agriculture
88.90
46.4
Agricultural Labour
87.40
30.4
Other Labour
73.10
21.5
Self employed in agriculture
73.80
14.0
Others
Source: Authors' calculation from NSS 61st Consumer Expenditure Schedule
Table 5 clearly shows that during 2004-05 among all groups where calorie deprivation level is
high, poverty level has also been higher. This analysis is based on gross effects and hence no
causalities are implied. It is found that never married persons report both relatively higher levels
24
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
of poverty and calorie deprivation compared to their group categories. In case of family size,
bigger the household higher is the level of calorie deprivation and poverty. Small households
covering 1-4 members experience lowest poverty and calorie deprivation level. Bigger households
(more than 7 members) perform worse on both counts. As far as social groups are concerned, it is
found that lower social groups such as ST and SC tend to have higher concentration of poverty
and calorie deprivation level, whereas the reverse is true for the 'other social group'. STs are worst
affected as poverty and calorie deprivation level is highest among them, followed by the SCs. If
we see deprivation and poverty level among the religious groups, we find that particularly
Muslims are in a worse condition as both calorie deprivation (84.4 percent) and poverty level (33
percent) are much higher among them in comparison to others. Education wise analysis shows that
it is the lower educated persons who are living in poverty and consuming lower calories than
standard norm. Higher is the education level lower is the levels of poverty and hunger. Illiterate
persons experience a highest level of poverty (36.5 percent) and calorie deprivation (83.5 percent)
level while educated people (with graduation and above) recorded lowest level of poverty (5
percent) and calorie deprivation (59.7 percent) level.
Similarly, lower the MPCE class, higher is the level of poverty and calorie deprivation. Thus,
bottom MPCE classes are unable to feed themselves even the standard calories and are living in
poverty. In terms of occupation groups, agricultural labourers perform worst on both counts
followed by ‘other’ labourer. Thus, while the official poverty measures and calorie deprivation
might show different levels of deprivation, there is a close correspondence among the two so far as
the pattern of deprivation across different groups are concerned.
INTERSTATE AND REGIONAL ANALYSIS
Inter-state variations in levels of deprivation has been one of the persistent themes in the poverty
debate in India (Deaton and Dreze 2010; Patnaik, 2007; Dev 2005). Specific to the divergence
between poverty estimates and calorie deprivation is the wide difference between the two
estimates in India's southern states. Many of the southern states have better human development,
demographic and social development indicators, and the records of state interventions in the areas
of food security, primary education and affirmative action in favour of the weaker sections are
generally considered to be better in most, if not all states of south India, particularly in comparison
with the densely populated north Indian states. In this backdrop, the fact that southern states
generally have a lower incidence of consumption poverty but a relatively higher degree of caloriedeprivation has been an important issue in the discussion. Patnaik (2007) views poverty as being
underestimated in southern states, whereas Dev (2005) argues that poverty using calorie norm in
southern states give absurd results.
Deaton and Dreze (2009) criticizes calorie norm as poverty method as this norm places all
southern states at higher deprivation level despite a fact that these states perform better in some
anthropometric measures. The incompatibility of the poverty estimates and levels of calorie
deprivation is brought out sharply in Table 6.
The discussion here has been widened by incorporating two additional indicators of deprivation
and it is important to note that southern states particularly Karnataka, Tamil Nadu, Andhra
Pradesh rank high on more than two deprivation indicators which confirm their poor performance
on selected deprivation indicators. For example, Karnataka ranks 10th in poverty level, 21st in
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
25
calorie deprivation, 12th in children underweight and 13th in BMI of women. Similarly, Tamil
Nadu ranks 12th in poverty level, 19th in calorie deprivation, and 12th in BMI of women.
Performance of Andhra Pradesh in terms of deprivation indicators is 13th in calorie deprivation,
7th in children underweight and 11th in BMI. Kerala is the only state in southern region which
perform better in all deprivation indicators. Maharashtra however record better performance in
terms of anthropometric measures but poverty (14th) and calorie deprivation (18th) level is high in
this state. On the other hand, Punjab, Himachal Pradesh, Jammu and Kashmir and Haryana are
best performing states in all deprivation measures whereas worst performance is shown by
Jharkhand, Madhya Pradesh, West Bengal, Orissa, Chhattisgarh and Bihar (Fig. 1). At the state
level, a correlation among the different indicators of deprivation is low6.
Table 6
Performance of States on selected Deprivation Indicators and their ranking during 2004-05
States
Below
poverty
Line*
Below 2400
Kcal*
Children (< 3) Under
weight#
BMI below normal
(Women)#
Jammu &
4.3 (1)
65.5 (1)
31.6 (2)
26.1 (6)
Kashmir
9 ( 2)
68.4 (4)
29.9 (1)
14.5 (3)
Punjab
10.5 (3)
83.8 (13)
40.4 (7)
37.5 (11)
Andhra Pradesh
10.5 (4)
66.3 (2)
36.4 (5)
25.8 (5)
Himachal Pradesh
Arunachal
10.9 (5)
70.9 (5)
42.1 (11)
14.3 (1)
Pradesh
13.2 (6)
67.6 (3)
41.8 (10)
32.5 (8)
Haryana
13.2 (7)
75.4 (9)
31.9 (3)
14.3 (2)
Kerala
18.3 (8)
74.5 (7)
45.9 (14)
36.5 (9)
Rajasthan
18.9 (9)
84.8 (15)
50 (17)
41.9 (15)
Gujarat
20.7 (10)
89 (21)
45.1 (12)
38.2 (13)
Karnataka
22.1 (11)
85.4 (16)
41.1 (9)
39.5 (14)
Assam
23 (12)
87.3 (19)
34.8 (4)
37.5 (12)
Tamil Nadu
28.4 (13)
78.1 (10)
46.7 (15)
44.9 (18)
West Bengal
29.6 (14)
86.9 (18)
40.1 (6)
15.4 (4)
Maharashtra
33.3 (15)
73.3 (6)
49.4 (16)
37.2 (10)
Uttar Pradesh
36.8 (16)
87.5 (20)
62.6 (20)
44.2 (17)
Madhya Pradesh
40.6 (17)
74.5 (8)
40.8 (8)
30.8 (7)
Uttaranchal
40.8 (18)
84 (14)
54.6 (18)
45.7 (19)
Chhattisgarh
42.6 (19)
78.8 (12)
59.3 (19)
45.9 (20)
Bihar
46.2 (20)
85.7 (17)
63.1 (21)
47.8 (21)
Jharkhand
46.9 (21)
78.5 (11)
45.7 (13)
43.7 (16)
Orissa
Source: * Same as Table 5, # Computed from National Family Health Survey, Fact Sheets, 2005-06
The level of nutrition (Table 7) in terms of calorie and protein intake across all major states show
that Karnataka, Tamil Nadu, Andhra Pradesh, Gujarat and Maharashtra are the states where calorie
and protein intake is quite low and in fact these states also show maximum decline in both the
nutrients between 1993-94 and 2004-5. The deficiency of calorie and protein from
recommendation is quite high in all southern states.
During 2004-05 deficiency of calorie was high in Andhra Pradesh (409 kcal), Gujarat (501 kcal),
Karnataka (538 kcal), Madhya Pradesh (472 Kcal), Maharashtra (476 kcal) and Tamil Nadu (536
kcal). In fact deficiency of protein was also larger in these states such as Andhra Pradesh (13 gm),
Assam (10 gm), Gujarat (9 gm), Karnataka (13 gm) Kerala (7 gm), Maharashtra (8 gm), Tamil
Nadu (16 gm) and West Bengal (10 gm).
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
26
This above analysis shows that calories and protein deprivations are consistently high in all
southern states except Kerala, whereas there are some states like Punjab, Himachal Pradesh,
Jammu and Kashmir, Haryana, Uttar Pradesh and Rajasthan where calorie intake recorded a slight
decline and consumption of protein is increasing during the period under consideration. In fact
states showing lower level of calorie deficiency (such as Haryana, Himachal Pradesh, Jammu and
Kashmir and Punjab) have performed better during 2004/05 and they have also recorded a larger
increase of calorie and protein in diet during the period under consideration.
Table 7
Change in level of nutrients and deficiency from recommendation between 1993/94-2004/05
across all major states in rural India
Calorie Intake
States
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Gujarat
Haryana
Himachal Pradesh
Jammu & Kashmir
Karnataka
Kerala
Madhya Pradesh
Maharashtra
Orissa
Punjab
Rajasthan
Tamil Nadu
Uttar Pradesh
West Bengal
Total
Source: Same as Table 2.
Notes: Same as Table 4
199394
2044
2126
1983
2113
1989
2486
2322
2504
2067
1956
2158
1933
2197
2414
2461
1872
2303
2210
2148
200405
1991
2316
2055
2021
1899
2212
2314
2358
1862
2113
1928
1924
2008
2219
2157
1865
2195
2065
2044
Deficit from
RDA, 2400 Kcal
1993200494
05
356
409
274
84
417
345
287
379
411
501
+86
188
78
86
+104
42
333
538
444
288
242
472
467
476
203
392
+14
181
+61
243
528
536
97
205
190
335
252
356
Protein Intake
199394
50.3
61.3
49.5
60.1
55.3
78.2
70.4
75.3
54.7
50.2
62.6
54.7
52.6
74.6
78.9
46.1
70.3
54.7
59.9
200405
47.4
59.4
50.4
54.9
50.5
67.8
67.0
62.4
47.0
53.4
53.9
51.8
46.2
64.5
67.1
43.9
64.2
50.5
55.1
Deficit from RDA,
60 gm
1993200494
05
10
13
+1
1
10
10
0
5
5
9
+18
+8
+10
+7
+15
+2
5
13
10
7
+3
6
5
8
7
14
+15
+4
+19
+7
14
16
+10
+4
5
10
0
5
A state level analysis may hide the micro level variations in calorie deprivation. There is some
heterogeneity within the states so far as nutrition deficiency is concerned. Hence, an analysis has
also been performed at NSS region level (Fig. 2) which tries to identify the regions experiencing
calorie deprivation. Out of selected 72 NSS regions, 48 regions experience higher level of
nutrition deficiency (more than 80 percent). The worst performance is shown by regions of
Madhya Pradesh which include Vindhyan and south western parts. Dry areas of Gujarat also
exhibit higher nutrition deficiency. Coastal parts of Maharashtra and southern parts of Orissa show
more than 92 percent population to be calorie deprived. The performance of regions of southern
states also does not pose a better picture.
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
Fig. 1
27
28
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
Fig. 2
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
29
Inland northern parts of Karnataka, coastal northern Tamil Nadu and south-western Andhra
Pradesh experiencing much higher level of nutrition deficiency which may be one of the reasons
of poor performance of southern states on deprivation indicators. It is clear from the figure (Fig.
2) that the regions in south India where level of calorie deprivation is relatively high form a
contiguous belt. The regions which pose a picture of relatively better nutrition sufficiency include
northern and southern parts of Punjab, Himachal Pradesh, western plains of West Bengal, Jhelum
Valley and mountainous parts of Jammu and Kashmir, central and western Uttar Pradesh.
Table 8
Logistic Regression Analysis for Showing Probability of Getting Required Calories
Variables
Social Group
Religious group
Education Level
Marital Status
Household Size
Occupation
Type
Poverty Line
Group
Regions
Variable Categories
Others (Ref)^
Scheduled Tribe
Scheduled Caste
Hindu (Ref)^
Muslim
Christian
Others
Primary or below (Ref)^
Not Literate
Secondary
Graduate or above
Currently Married (Ref)^
Never Married
Widow/Divorced/Separated
1-4 (Ref)^
5-6
7-8
Above 8
Self employed in non
agriculture (Ref)^
Agricultural Labour
Other Labour
Self employed in
agriculture
Others
Above Poverty Line (Ref)^
Below poverty Line
Central (Ref)^
North
East
North East
West
South
Beta
0.682
0.924
1.147
Sig.@
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
1
0.154
0.282
0.000
0.000
1.166
1.326
-0.524
0.000
0.592
-0.186
0.000
0.83
2.649
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
14.146
1
1.159
1.113
2.987
2.809
2.636
1.226
0.421
0.318
0.296
-0.159
-0.4
0.108
-0.32
-0.631
0.104
-0.28
0.147
0.107
1.094
1.033
0.969
0.204
Exponential Beta
1
1.524
1.375
1
1.344
0.853
0.671
1
1.114
0.726
0.532
1
1.109
0.756
1
1.978
2.52
3.15
Constant
Source: Same as Table 5.
Note:@Significance level, ≥ 0.01= 1 percent, 0.02-0.05= 5 percent, 0.06-0.1= 10 percent;
^Reference Category
Dependent Variable: Calorie Intake, 1 shows below 2400 Kcal and 0 shows 2400 & above Kcal
30
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
PROBABILITY
OF
CONSUMING
RECOMMENDED
CALORIES:
A
DISAGGREGATED ANALYSIS
In this section the factors affecting probability of consuming recommended calories have been
probed through a logistic regression (Table 8). Our results clearly show that probability of getting
recommended calories is quite low among all weaker socio-economic groups. For example, as the
family size increases, the likelihood of consuming recommended calories declines which exhibits
poor nutritional conditions of bigger households. The households covering more than 8 members
in the family exhibit higher probability (odd ratio 3.15) of being calorie deprived than the small
families having 1-4 members. Among social groups, ST are worst affected as the probability of
consuming recommended calories is very low compared to other social groups. SC people
however have lower likelihood (1.35 odd ratios) of being calorie deprived than ST (1.52 odd
ratios). Regarding religious group, Muslims suffer badly as they have higher probability of being
calorie deprived than the Hindus whereas Christians (0.853 odd ratio) and other religion people
(0.671 odd ratio) enjoy better calorie intake than the Hindus. Education level plays an important
role to determine calorie intake. It has been analysed that as the level of education increases, the
likelihood of consuming calories from the norm also rises. Highly educated people show more
chances of taking recommended calories than the other lower education group people.
Considering the probability of calorie intake among occupation groups, agricultural labourers and
other labourers have lesser probability of consuming recommended calories than the employed in
non-agriculture. Self employed in agriculture and other occupation groups have more chances of
becoming energy sufficient than those who are not self employed in agriculture. As far as poverty
level is concerned, people below the poverty line have a much higher likelihood of being calorie
deprived (14.146 odd ratios) than the Above Poverty Line category people.
The probability of consuming recommended calories across different geographical regions of rural
India show that compared to central region (covering states of Uttar Pradesh, Madhya Pradesh and
Chhattisgarh), all regions show lower likelihood to consume recommended calories. Among them
north eastern, western and southern region covering states of Gujarat, Maharashtra, Karnataka,
Tamil Nadu, Andhra Pradesh and Kerala exhibit more chances of being calorie deprived from
recommended calories. Northern and eastern states such as Punjab, Himachal Pradesh, Jammu and
Kashmir, Haryana, Rajasthan, Orissa and Bihar show lower probability of calorie deprived than
the other regions. However, these regions are prone to calorie deprivation when compared with
central region. A relatively lower likelihood of being calorie deprived is resulted by higher
consumption of cereals.
CONCLUSION
From this analysis it is found that over a decade (1994-2005) the consumption pattern of Indians
has changed significantly. Consumption of cereals, particularly coarse cereals, has declined
whereas consumption of other food items such as vegetables, fruits, milk and milk products, meat
increased slightly which have a direct bearing on nutrient intake. Due to decline in cereal
consumption and lower increase in consumption of other food items nutrient pattern in rural India
has also changed substantially. Share of cereals particularly coarse cereals to total calories has
declined whereas calories from oil and fat have increased. Since cereals are also a good source of
protein but its decline has also led to lowering down of protein. In rural India on an average per
Journal of Regional Development and Planning, Vol. 2, No. 1, 2013
31
capita per day calorie and protein intake is falling and consumption of oil and fat is increasing.
This, to some extent, is as per the expenditure of dietary transition models. However, given the
relative underperformance of India in the nutrition front, this decline in cereal consumption has
often been viewed as deterioration in the living standard of the poor. The disaggregated analysis of
calorie and nutrition deficiency in rural India carried out in this study clearly points out that
deprivation is higher among marginalized social and economic groups. It is the poor, SC and ST
groups, agricultural labourers who suffer most in terms of calorie deprivation.
There is much gap in official poverty and calorie deprivation level. We have estimated both
poverty and calorie deprivation across social groups. Those having bigger families, less education,
lower MPCE and those belonging to ST, SC, agricultural labour and other labour class, Muslims
are found to have higher levels of poverty as well as calorie deprivation. Thus, in terms of
distribution of deprivation across social and economic groups, there is a consistency between
poverty and calorie deprivation although the levels are quite different in many cases. The interstate
variations, however, does not show much consistency. The southern states particularly Karnataka,
Tamil Nadu, Andhra Pradesh perform poor on more than two deprivation indicators. Gujarat and
Maharashtra, considered as relatively developed states perform worse on both methods of poverty
measurement. On the other hand, Punjab, Himachal Pradesh, Jammu and Kashmir and Haryana
are best performing states in all deprivation measures. From a regional point of view, it is found
that most of the NSS regions having majority of population being calorie deprived than
recommendation fall in the southern, western and central parts of India. All the southern states
except Kerala and including Gujarat and Maharashtra presents maximum decline in calorie and
protein intake from the recommendation whereas Punjab, Himachal Pradesh, Jammu and Kashmir
and Haryana, Uttar Pradesh and Rajasthan show lower decline in calories and in fact increase in
protein intake. These states also show lower level of calorie deprivation and poverty.
The exercise undertaken to show probability of being calorie deprived concludes that never
married, big families, less educated, lower MPCE class, ST, SC, agricultural labour and other
labour class, Muslims, people living below poverty line and southern, north-eastern and western
states are some weaker sections and regions which are comparatively more prone to be poor and
undernourished than their respective reference categories. The debate so far has concentrated on
the observed divergence between poverty estimates and calorie deprivation. Our analysis,
however, points out that it is the relatively marginalized social and economic groups who face
greater calorie deprivation. Thus, there is an urgent need to focus on such high levels of
deprivation among the marginalized groups and regions.
_________________________________
Notes
1.
Calorie norm has officially been taken to measure poverty level in India. Per capita per day intake of
2400 kcal for rural and 2100 kcal for urban areas are the norms to estimate poverty. Planning
Commission makes adjustment in Consumer Price Index for Agricultural Labourers (CPIAL) and
Consumer Price Index for Industrial Workers (CPIIW) to the base year poverty line (1973-74) for
estimating rural and urban poverty respectively. Planning Commission’s estimation of poverty using
indirect method shows lower level of poverty whereas directly using calorie norm to measure poverty
gives a much higher level of deprivation.
32
JOURNAL OF REGIONAL DEVELOPMENT AND PLANNING
2.
Food items have been converted into nutritive values using the standard units given in report no.
513(61/1.0/6) Nutritional Intake In India (2004-2005), NSS 61st round National Sample Survey
Organisation, Ministry Of Statistics & Programme Implementation Government of India.
For further details on measurement of official poverty line in India and changes in it, see Utsa Patnaik,
2007.
Standard Calories are given in the Report of the Export Group on Estimation of Proportion and
Number of Poor. Perspective Planning Division. Planning Commission, 1993 - 2400 kcal per capita for
rural area and 2100 kcal for urban area and standard protein intake is recommended in report on
‘Nutritional Status of Rural Population’ by National Institute of Nutrition (1996) Indian Council of
Medical Research, Nutritional Status of rural population, Report of the NNMB surveys, National
Nutritional Monitoring Bureau, Hyderabad.
Official poverty has been calculated using the report of ‘Poverty Estimates For 2004-05’ Government
of India Press Information Bureau [Online at] planningcommission.nic.in/news/prmar07.pdf , Accessed
on 12/03/2010 at Jawaharlal Nehru University.
The correlation between Below poverty line (BPL) and Below 2400 kcal is 0.472 (significant at 0.05
level) which is low as compared to correlation between BPL and Children underweight below 3 (0.733,
significant at 0.01 level) and between BPL and Body Mass Index of Women (0.622, significant at 0.01
level).
3.
4.
5.
6.
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