DESCRIBING POPULATION HEALTH IN SIX
DOMAINS: COMPARABLE RESULTS FROM 66
HOUSEHOLD SURVEYS
Ritu Sadana
Ajay Tandon
Christopher JL Murray
Irina Serdobova
Yang Cao
Wan Jun Xie
Somnath Chatterji
Bedirhan L Ustün
Global Programme on Evidence for Health Policy Discussion Paper No. 43
World Health Organization
March 2002
Abstract
One of the World Health Organization's longest standing mandates is the collection and
routine reporting of information on population health. In addition to estimates of mortality
and disease, assessment of health status from population based surveys contribute to estimates
of population health. The first section of the paper briefly introduces the conceptual and
operational basis to measure health, where health is measured through six domains (affect,
cognition, pain, mobility, self-care and usual activities). The second section briefly notes that
the main objective of this paper is to report on the average levels of health by age and sex
groups for each domain of health across 66 population based surveys. The third section of
this paper describes how we have applied the hierarchical ordered probit (HOPIT) model
using vignettes to calibrate responses across survey populations, to self-reported levels of
health on six domains. The data comes from the WHO Health Survey Study 2000-2001,
from 66 population based surveys in 57 countries, representative of individuals 18 years and
older. The fourth section provides results on comparable levels of health for each domain
across populations, by age groups and sex. In order to further facilitate comparisons across
countries, age-standardized aggregated results across all age groups, by sex, are also
presented and compared to external data, such as GDP per capita (PPP) and life expectancy.
The fifth section discusses the information content of the surveys, the added-value of the
multi-dimensional approach and the comparability of responses across countries. The final
section recommends additional analyses to be conducted.
Comments on this discussion paper are most welcome and should be forwarded to:
Dr. Ritu Sadana
Evidence and Information for Policy
World Health Organization
Avenue Appia 20
CH-1211 Geneva 27
Switzerland
Email: [email protected]
I.
Introduction
1.1 BACKGROUND
The World Health Report 2000 (WHO 2000) proposed a framework defining the three
intrinsic goals to which health systems should contribute. The first intrinsic goal is
considered as the defining goal of a health system, that is, to improve health, both the average
level of population health and its distribution within a population. It is not surprising that one
of the World Health Organization’s longest standing mandates has been the collection and
routine reporting of information on population health. Along with Member States, research
institutions, and technical experts, WHO has expended considerable efforts over the past
decades to enhance the information content and comparability of population health covering
mortality and its risk factors. Over the past decade, the locus of these efforts has extended to
the improvement and standardization of methods to assess non-fatal health (covering
epidemiological estimates of morbidity and disability, and assessment of health status from
population based surveys), reflecting the conclusion that mortality alone does not provide a
complete picture of population health. Following the Global Burden of Disease Study
(Murray and Lopez 1996), more recent work includes the further development of summary
measures of population health (Murray et al. forthcoming), a critical review of the validity
and comparability of existing population based survey data on health status (Sadana et al
2000), the finalization of The International Classification of Functioning, Disability and
Health (ICF), (WHO 2001) and the implementation of the WHO Multi-Country Survey
Study on Health and Responsiveness 2000-20001 (WHO Multi-Country Survey Study)
(Üstün et al. 2001).
This paper reports on the average level of population health, focusing on the self-reported
health status in six domains assessed through 66 population-based surveys conducted in 57
countries included within the WHO Multi-Country Survey Study. The results presented in
this paper provide more comparable information on the self-reported average level of
population health across countries than was previously possible from survey data, and have
been used in subsequent analyses to estimate healthy life expectancy (Mathers et al. 2001).
1.2 MULTIPLE DOMAINS OF HEALTH
The WHO definition of health notes that health is a multi-dimensional concept. There are
potentially three sets of domains that can be specified in order to describe health and
contribute to its operational measurement: (1) core domains of health that almost all people
agree upon; (2) additional domains of health that some people consider as core domains; and
(3) other domains that are related to health and serve as good proximate measures of the
experience of health – health related domains. Based on an extensive review of existing health
state measurement instruments and health measurement literature, some 24 candidate domains
to describe health were proposed and discussed within technical consultations on measuring
health status over the past two years (Figure 3). Of these, 18 describe different aspects of
health status directly, such as affect, pain, dexterity or fertility (e.g., domains in the gray
shaded box), while the remaining six are proximate domains that indirectly assess health.
Based on the reviews, technical discussions and linkage with the ICF, six domains were
selected as domains that almost all people agree upon for inclusion across all survey modes
with the WHO Multi-Country Survey Study. These include affect, cognition, mobility, pain,
self-care and usual activities. This paper restricts its analyses to describe the average level of
health on each of these six domains, across all 66 surveys thus far analyzed.
1
Figure 1. Candidate core domains assessed to describe health across populations
Domains indirectly assessing health
Domains directly describing health
General health
Sexual activity
Discrimination/stigma
Affect*
Fertility
Participation barriers
Cognition*
Hearing
Self-care*
Communication
Speech
Shame/embarrassment
Dexterity
Vision
Social functioning
Mobility*
Breathing
Usual activities*
Pain*
Eating
Skin & bodily disfigurement
Digestion
Energy/vitality
Bodily excretion
* Domains selected for standardized health status module
It is important to stress that the ability to engage in usual activities or self-care does not
describe health per se, but limitations or performance in these areas may be associated with
lower levels of health in the domains directly describing health (e.g., proximate domains are
likely to be more highly correlated with domains that directly assess health, than domains that
directly assess health are with one another). Furthermore, although we would prefer to assess
health directly, the self-report of limitations in usual activities or self-care may be reported in
a more reliable or consistent manner, than the self-report of health in some of the other
domains. For this reason, proximate domains are often included in standardized, interview
based health status assessment instruments (McDowell and Newell 1996). Nevertheless,
other domains directly assessing health listed in Figure 1 are assessed within the in-depth
household surveys included in the WHO Multi-Country Survey. The analysis and critical
review of data on these additional domains will be presented separately.
1.3 CROSS-POPULATION COMPARABILITY
One of the main advantages of data collected through household surveys is that they provide
person or household based health statistics rather than data collected through health services
or disease registries, which are episode or event based (United Nations 1995). Self-reported
responses in household or other types of interview based survey data are therefore widely
used for assessing the health status of populations. These data typically take the form of
ordered categorical (ordinal) responses, such as excellent/ very good/ good/ poor/ bad or
none/ mild/ moderate/ severe/ extreme. One key analytical issue is that these self-reported
ordinal responses are not necessarily comparable across or even within populations primarily
because of response category cut-point shifts. This phenomenon differs from other numerous
factors -- such as differences in language or measurement error -- that may also contribute to
the difference between what is observed and what is reported within an interview, discussed
elsewhere (Sadana et al. 2000; Murray et al. 2001).
If the self-reported response results from a mapping between an underlying unobserved latent
variable (e.g., level of one domain of health, such as mobility) and categorical response
categories, cut-points are threshold levels on the latent variable that characterize the transition
from one observed categorical response to the next. If cut-points differ systematically across
populations, or even across socio-demographic groups within a population, then the observed
ordinal responses are not cross-population comparable since they will not imply the same
2
level on the underlying latent variable that we are trying to measure (Figure 2). Another way
of characterizing this problem is that, for the same level of the latent variable on any given
domain, the probability of an individual responding in any given response category is
different across populations.
Figure 2. Hypothetical shifts in response category cut-points
B
A
C
N
N
Mi
N
Mo
Mi
S
Mi
Mo
Mo
E
S
S
Cut-points
E
E
Latent mobility scale
N = None, Mi = Mild, Mo = Moderate, S = Severe, E = Extreme
The main self-report question on the domain of mobility from this survey is: "Overall in the
past 30 days, how much difficulty did you have with moving around?" Respondents are asked
to classify themselves using one of five response categories: "1=Extreme/Cannot do;
2=Severe difficulty; 3=Moderate difficulty; 4=Mild difficulty; 5=No difficulty." We can
hypothesize that cut-points may vary between populations because of different cultural or
other expectations on each domain of health. Figure 1 illustrates the case when individuals in
population C may respond with "extreme" difficulty while individuals in population A with
the same true level of mobility may respond with "mild" up to "extreme" difficulty. Given
these shifts in cut-points, the differences in the proportion of each population within each
response category are not comparable. Cut-points are also likely to vary across cultural or
socio-demographic groups, levels of health insurance or other benefits and entitlements, or
over time. For example, the cut-points for older individuals may shift as their expectations
for level of health on a particular domain diminish with age, i.e., they may under-report
difficulties. Men may be more likely to deny declines in health so that their cut-points may be
systematically shifted as compared to women, i.e., they may under-report difficulties. Contact
with health services may influence expectations for a domain and thus also shift cut-points,
i.e., difficulties may be over-reported. These hypothetical shifts in cut-points may be tested
with the appropriate methods. However, until recently, most users of data from health
interview surveys have interpreted self-reported reported responses at face value.
A recent re-analysis of 64 household interview survey data on health from 46 countries
provided further evidence suggesting cross-population cut-point shifts (Sadana et al. 2000). In
this previous analysis due to the paucity of data information on all domains of health was
combined. Although no external means to calibrate responses were included within these
existing and available data sets, the analysis documented that the information content and
comparability of the surveys were limited. Many surveys re-analysed did not meet basic
criteria, for example that a range of health states (spanning mild to severe) exist at the
population level or that health status declines with age These and other limitations prevented
valid comparisons of the level of health by age and sex groups within regions as well as
across regions. In this earlier analysis, another approach to evaluate the information content
and cross-population comparability of the level of health was to interpret the data from
3
surveys in conjunction with other, non-health data from the same countries. A scatter plot of
the per capita GDP and the average level of health for the over 65 population (males and
females combined), for each of the 46 countries included within this earlier analysis, shows
higher levels of per capita GDP are correlated with lower average levels of health. This
suggests the existence of cross-population cut-point shifts (Figure 3). Although this evidence
based on cross-sectional data is not conclusive, it does suggest that with more information,
resources and exposure to health services, population norms and expectations differ for the
same age group, and that these differences appear to contribute to the self-report of health.
This negative correlation, even if weak, is consistent with earlier findings in that countries,
regions, or socio-demographic groups that are wealthier and spend more resources on health,
also report worse levels of health (Kroeger et al. 1988; Waidmann et al 1995; Murray 1996),
where as the reverse is expected.
Figure 3. Per capita GDP (PPP) vs. Self Reported Level of Health, 65 years and older age group,
46 Countries
100
90
Level of Health
80
70
60
50
40
30
20
10
0
100
1000
10000
100000
Per Capita GDP
Bearing in mind these limitations, the data collection and analysis methods of the WHO
Multi-Country Survey are an attempt to enhance the comparability of routine assessments of
population health obtained through interview based surveys. Based on the critical evaluation
of these methods, improvements will be introduced within the next survey and analysis phase,
the World Health Survey.
II. Objectives
The main objective of this paper is to report on the average levels of health by age and sex
groups for each domain of health across 66 population based surveys within the WHO MultiCountry Survey. In doing so, we provide an empirical test of new data collection and analysis
methods developed to enhance the cross-population comparability of self-reported health. A
secondary objective is to provide descriptive data on health for input to other analyses and
estimates, such as the estimation of inequalities in the distribution of health or the calculation
of summary measures of population health.
III. Methods
4
III.1 DATA: SURVEYS, QUALITY, REPRESENTATIVENESS, SAMPLE SIZE
AND RESPONDENT CHARACTERISTICS
3.1.1 WHO Multi-Country Survey Study on Health and Responsiveness 2000-2001.
Although WHO routinely collects mortality and morbidity data, the data used within this
analyses represents the first effort by WHO to collect data on self-reported health status from
population representative surveys, in conjunction with Member States, research institutions
and survey organizations. The WHO Multi-Country Survey includes 71 surveys in 61
countries. The survey has a range of modules including: health status description, health
state valuations, responsiveness, mental health, chronic health conditions, adult mortality,
environmental factors and health financing. Information on the development of content of the
overall survey instrument, translation protocols, the various survey modes, selection of sites,
sample frames, data collection and management, and quality of the data (e.g., sample
population deviation index for age-sex groups, response rates, item missing values, test-retest
reliability coefficients, among other attributes), are detailed elsewhere (Üstün et al. 2001).
Selected aspects relevant to the data collection, analysis and interpretation of the health status
description module are amplified below.
Addressing the challenge of cross population cut-point shifts, two external means to calibrate
responses were included within the data collection component of the surveys, vignettes for
each of the domains assessed (all 66 surveys) and measured performance tests in domains
covering mobility, cognition and vision (limited to the 10 in-depth household surveys). The
results presented in this paper reflect the use of the vignette approach to calibrate responses.
Each set of vignettes provides a description of a range of fixed levels of ability on each of the
domains assessed (domains have between 6-8 vignettes). The concept of vignettes is based
on the following reasoning: (i) vignettes fix the level of ability so that variations in
categorical responses are attributable to variations in response category cut-points; (ii) the
introduction of exogenous information in the form of ratings of vignettes allows us to identify
the effects of different covariates (e.g., age, sex, education, country) on both the level of the
underlying latent variable (e.g., mobility, affect, etc.), as well as on the cut-points. See
Salomon et al (2001) for further details and assumptions on the use of vignettes as a means
for enhancing cross-population comparability. A critical evaluation of vignettes as a strategy
to calibrate responses across surveys will be presented separately (Sadana et al. 2001), as will
the use of measured performance tests (Tandon et al. 2001).
3.1.2 Surveys, Quality. Data available on health status description at the time of this
analysis covers 66 population representative surveys in 57 countries using four different
modes1. These include 10 in-depth household surveys (interviews lasting around 90 minutes
each), 27 brief household surveys (interviews lasting around 35 minutes each), 27 postal
surveys (self-administered with questionnaires similar to the brief household surveys), and 2
computer assisted telephone interviews (questionnaires similar to the brief household
surveys). Individuals interviewed reported on their own health status, i.e., individuals did not
provide proxy reports for others in the household as is the case for many other household
surveys including health modules. On average, response rates were highest for the in-depth
household surveys (84 per cent), than for the other survey modes, i.e., brief (64 per cent),
postal (46 per cent) and telephone (40 per cent). On average, respondent missing data across
all items also varied across modes, and was lowest for the brief household surveys (1.5 per
cent), followed by telephone (2.1 per cent), postal (6.8 per cent) and in-depth household (12.1
per cent). Two different survey modes were used in Canada, China, Czech Republic, Egypt,
Finland, France, Indonesia, Netherlands and Turkey. The average level of health by domain
is reported separately for each survey within this paper: a detailed investigation of differences
1
The survey instruments are available on the web: www.who.int/evidence/hhsr-survey/
5
by mode will be provided in a separate analysis. Within the 10 in-depth household surveys,
approximately 10 per cent of the sample was re-interviewed in order to estimate test-retest
reliability. Weighted Cohen's kappa statistics (corrected for chance agreement) were applied
to categorical data. The average values for questions within the six domains assessed of
health (affect, cognition, mobility, pain, self-care and usual activities) varied from 0.60 to
0.71, largely indicating substantial agreement. Variations in the reliability of survey items
appear greater across countries than across questions within the health module.
3.1.3 Sample size, Representativeness, Respondent characteristics. Table 1 lists the
country and survey mode, the mean age, the mean number of years of education, the sample
size, age groups excluded (if any) and the per cent that each survey contributes to the overall
analysis sample. For inclusion in this analysis, individuals interviewed must have responded
to at least one of the core domain questions on health status. The overall analysis sample size
is 117,192 respondents from 66 survey in 57 countries. Across all surveys, the average age is
42.0 (range 15 - 115) and the average number of years of education is 10.3 (range 0 - 30).
Sample size varies considerably across surveys: the ten in-depth household surveys
(n=59,618) contribute just over 50 per cent of the overall analysis sample. The number of
surveys included within this analysis from each of the WHO regions is as follows: AFRO
(1); AMRO (10); EMRO (7); EURO (39); SEARO (4); WPRO (5).
In general, the surveys provide data that are nationally representative of the civilian, noninstitutionalized population 18 years of age and older. Some exceptions to geographic
coverage are documented for selected surveys: Canada (both surveys exclude Yukon,
Northwest Territories or Nunavut), China (in-depth household survey: includes different
socio-economic groups from Shandong, Henan, Gansu Provinces; postal: includes Shandong
Province), Columbia (excludes a few areas making up less than 2% of the population such as
Orinoquia, the Amazonian Triangle among others), Georgia (excludes Abkhazia and
Tskhinvali regions), India (includes Andhra Pradesh State), Indonesia (household: excludes
Papua, Aceh and Maluku Provinces), Nigeria (includes Oyo State) and United Arab Emirates
(excludes most foreign workers primarily in low skilled jobs).
Based on the individuals sampled and the inclusion criteria in this analysis of the health status
description module, age groups2 with insufficient observations (<10) by survey and sex are
noted in Table 1, Column IV. These exclusions are primarily restricted to individuals 80 years
and over, with the main exceptions being Bahrain, China postal, Jordan, Oman, Republic of
Korea, United Arab Emirates and Venezuela where some exclude individuals 60 years and
over. In the overall analysis sample, the ratio of males to females is 0.88 (53.3 per cent
females and 46.7 per cent males). This ratio varies considerably across surveys. Twenty-two
surveys have a ratio greater than or equal to 1.0, with four greater than or equal to 1.5
including Czech Republic brief (1.52), Greece (1.59), Turkey household (1.72) and Republic
of Korea (3.09), where as eight surveys have a ratio less than or equal to 0.7, with four less
than or equal to 0.6 including Kyrgyzstan (0.60), Columbia (0.53), Ukraine (0.53) and
Thailand (0.43). Further details on sampling strategy, the achieved sample characteristics in
comparison to the expected characteristics based on census estimates, and sample weights for
each survey are found elsewhere (Üstün et al. 2001).
Despite these limitations in geographic, age and sex representativeness, this data set from 66
surveys across 57 countries includes the greatest number of population representative surveys
on self-reported health status using the same survey module, to date.
Table 1. Sixty-six surveys from 57 countries: sample size and respondent characteristics
I
Mean
II
Mean
III
IV
Age Groups
V
VI
2
Age groups used to present average level of health match those for input to the estimation of healthy
life expectancy: 15-29, 30-44, 45-59, 60-69, 70-79, 80+
6
Country and Survey Mode
Age (yrs) Education
(yrs)
N
Excluded
Females
Males
N
% of N
Females Males
Argentina brief
43.6
10.1
408
366 80+
Australia postal
52.8
12.2
511
674
80+
774
0.66
1185
1.01
Austria postal
50.5
11.3
523
506
Bahrain brief
34.7
11.2
349
447 60+
Belgium brief
44.2
13.5
568
531
Bulgaria brief
45.0
13.7
508
487 80+
80+
995
0.85
Canada postal
43.6
14.0
226
180 80+
80+
406
0.35
Canada telephone
44.7
14.0
195
190 70+
80+
385
0.33
Chile postal
47.7
12.2
509
521
1030
0.88
China household
39.8
9.1
4418
5023
9441
8.06
China postal
40.0
11.4
602
1371
1.17
Columbia household
40.0
7.4
3939
6019
5.14
Costa Rica brief
37.9
7.4
377
375 80+
Croatia brief
47.8
10.6
862
637
Cyprus postal
47.7
11.9
293
362 80+
Czech Republic brief
44.1
14.3
425
644 80+
80+
1069
0.91
Czech Republic postal
48.7
12.5
613
403 80+
80+
1016
0.87
Denmark postal
46.3
13.0
780
723
1503
1.28
Egypt household
39.1
8.0
2518
1967
4485
3.83
Egypt postal
36.8
13.6
675
714 80+
Estonia brief
47.6
9.8
573
Finland brief
47.2
10.0
Finland postal
50.6
11.8
France brief
43.2
France postal
45.1
Georgia household
45.8
769 60+
70+
70+
2080
80+
80+
1029
0.88
796
0.68
1099
0.94
752
0.64
1499
1.28
655
0.56
1389
1.19
427
1000
0.85
573
448
1021
0.87
797
535
1332
1.14
13.6
521
482 80+
80+
1003
0.86
11.8
360
222 80+
80+
582
0.5
12.2
5692
9846
8.4
4154
Germany brief
46.9
12.9
585
534
Greece postal
49.4
11.9
333
529 80+
80+
1119
0.95
862
0.74
1496
1.28
Hungary postal
46.6
11.2
696
800
Iceland brief
39.4
16.0
266
223 80+
80+
489
0.42
India household
40.1
3.8
2734
2398 80+
80+
5132
4.38
Indonesia household
40.0
7.5
5452
4499
9951
8.49
Indonesia postal
36.3
13.7
1284
1310 70+
80+
2594
2.21
Ireland brief
42.5
12.4
352
359 80+
80+
711
0.61
Italy brief
45.4
12.3
520
482
80+
1002
0.86
Jordan brief
34.8
10.3
407
391 70+
70+
798
0.68
Kyrgyzstan postal
43.9
12.7
669
403 80+
80+
1072
0.91
Latvia brief
48.9
11.8
338
422 80+
760
0.65
Lithuania postal
47.2
10.2
997
768
Luxembourg telephone
45.3
13.6
400
319 80+
80+
Malta brief
47.4
11.7
256
244 80+
80+
Mexico household
41.8
9.4
2576
Morocco brief
35.9
7.4
376
376 70+
Netherlands brief
44.1
13.6
591
Netherlands postal
50.5
13.6
277
New Zealand postal
48.6
13.0
969
Nigeria household
35.9
8.0
2788
Oman brief
33.5
11.4
382
1760
1765
1.51
719
0.61
500
0.43
4336
3.7
80+
752
0.64
493
80+
1084
0.92
308
80+
585
0.5
732
1701
1.45
1779
4567
3.9
884
0.75
502 60+
60+
(continued)
Table 1. Sixty-six surveys from 57 countries: sample size and respondent characteristics
(continued)
7
I
II
Mean
Mean
Age (yrs) Education
Country and Survey Mode
(yrs)
III
IV
Age Groups
Excluded
n
Females
Males
V
VI
N
% of N
Females Males
Poland postal
45.1
11.9
438
430
868
0.74
Portugal brief
45.3
8.7
557
444
1001
0.85
Republic of Korea postal
52.0
11.0
87
269 70+
Romania brief
45.4
13.7
530
521 80+
Russian Federation brief
42.7
14.9
857
744
Slovakia household
42.3
11.9
647
531
Spain brief
43.4
11.4
512
486
Sweden brief
48.1
10.2
536
463
Switzerland postal
45.9
12.4
204
265 80+
80+
469
0.4
Thailand postal
40.9
8.1
836
359 80+
70+
1195
1.02
Trinidad and Tobago postal
42.4
11.8
821
1324
1.13
Turkey household
32.5
10.2
1716
2947 80+
80+
4663
3.98
Turkey postal
34.0
9.2
1325
1072 80+
80+
2397
2.05
Ukraine postal
44.4
13.1
502
268 80+
80+
770
0.66
United Arab Emirates brief
33.8
12.9
407
451 60+
60+
858
0.73
United Kingdom postal
51.0
13.1
531
444
975
0.83
United States postal
52.7
14.1
531
657
1188
1.01
Venezuela brief
34.7
10.8
362
378 60+
740
0.63
42.0
10.3
62462
54730
53.3
46.7
Total
%
<30; 80+
356
0.3
1051
0.9
80+
1601
1.37
80+
1178
1.01
80+
998
0.85
999
0.85
503
60+
117192
100
8
III.3 QUESTIONS, RESPONSE SCALES, RECALL PERIODS
Based on the six domains assessed selected to describe health, questions assessing each
domain were selected from existing standardized surveys that have already been pilot tested
in multi-country studies (Üstün et al. in press). Table 2 lists the main question for each
domain and the number and topics of the auxiliary questions for each domain assessed. For all
questions, the recall period is the last 30 days, the most common time frame in standardized
health status assessment instruments. Questions either asked the respondent to assess the
degree to which a particular state was experienced, or the amount of difficulty associated with
a particular state, by domain.
Table 2. Main and Auxiliary Questions for Six Domains, using standard response scale
(None, Mild, Moderate, Severe, Extreme), WHO Multi-Country Survey on Health and
Responsiveness 2000-2001
Domain
Main Question
Number and Content of Auxiliary
Questions
Affect
Overall in the last 30 days, how much distress,
sadness or worry did you experience?
Cognition
Overall in the last 30 days, how much difficulty
did you have with concentrating or remembering
things?
Mobility
Overall in the last 30 days, how much difficulty
did you have with moving around?
Pain
Overall in the last 30 days, how much pain or
discomfort did you have?
Overall in the last 30 days, how much difficulty
did you have with self-care, such as washing or
dressing yourself?
Overall in the last 30 days, how much difficulty
did you have with work or household activities?
(4) time spent feeling happy and cheerful/ sad,
empty, depressed/ irritable or in a bad mood/
worried a lot
(4) difficulty in concentrating on doing something
for 10 minutes/remembering to do important
things/ analyzing and solving problems in day to
day life/ learning a new task
(4) difficulty to stand up from sitting down/moving
around inside one's home/ climbing several flights
of stairs or walking up a steep hill/ performance of
vigorous activities such as running, lifting heavy
objects, participating in strenuous sports
(1) amount of bodily pain or discomfort
Self-Care
Usual
Activities
(3) difficulty in washing your whole body/getting
dressed/staying by yourself for a few days
(3) difficulty in taking care of household
responsibilities/getting all the housework done that
you needed to do/being limited in the type of
household work
III.4 TREATMENT OF ITEM LEVEL MISSING DATA
As noted, for inclusion in the analysis on health status description, individuals interviewed
must have responded to at least one of the domain questions on health status (Table 2). If a
respondent had answered none of the domain questions, then this respondent was dropped
from the analysis: using this criteria less than 50 cases were dropped across all 66 surveys. If
a respondent had answered all six domain questions, then this respondent was considered as a
case. For all intermediary situations, i.e., individuals who had responded between one to five
of the domain questions, all were also considered as cases. Key socio-demographic
information required for all cases included age, sex and years of education, along with the
survey (i.e., country and mode of survey). For all cases, missing data concerning age, sex,
years of education and level of health on up to five of the core domain questions were
subsequently estimated using the multiple imputation method employed by the software
program AMELIA and its EMis algorithm (Honaker et al. 1999). The per cent of missing data
for the background variables imputed on average for all cases was very low across all but one
of the surveys: sex (<0.1%), age (<0.5%), and years of education (<0.1% excluding
Indonesia household, where years of education was missing for 16% of cases). Likewise, the
per cent of missing data for the main question assessing each domain of health imputed for all
cases was very low across surveys, <0.5% for each of the six main questions. Missing data at
9
the item level on auxiliary questions for each of the six domains assessed in the in-depth
household surveys (i.e., 10 of the 66 surveys), were not imputed.
III.5 ANALYSIS METHOD TO ENHANCE COMPARABILITY: ADJUSTING FOR
CROSS-POPULATION CUT-POINT SHIFTS
The analysis approach addresses the key challenge concerning the comparability of self
reported health status data collected through interview based surveys: cross-population cutpoint shifts. In conjunction with the data collection strategies that incorporate an external
means to calibrate responses, the analytical methods applied here should be viewed as a
significant improvement over previous methods used to enhance cross-population
comparability on existing data sources without external calibration methods (see Sadana et al.
2000; Tandon et al. 2001).
3.5.1 Hierarchical ordered probit (HOPIT) model. We have applied the hierarchical
ordered probit (HOPIT) model, a variant of the standard ordered probit model and to some
degree, of the partial credit model from item response theory. The key innovations in the
HOPIT model are that: (a) cut-points are allowed to be functions of explanatory variables, (b)
vignettes are used to estimate cut-points across different populations, and (c) interval
regression is applied to self-report questions in order to estimate cross-population comparable
levels of ability on any given domain. See Tandon et al. (2001) for details on the background,
development and testing of the statistical model on simulated data.
The HOPIT model is estimated using maximum likelihood techniques. In brief, there are
several components to the likelihood function. The first component utilizes information from
responses to vignettes. In this component of the likelihood function, the model assumes there
is an underlying latent variable for the set of vignettes, addressing a particular domain of
health, Y*. Each vignette v=1,…,V represents a fixed level on this latent variable, i.e.,
mobility, affect, pain, etc. This latent variable is not observed. What are observed are
categorical responses for each of the vignettes Yv. In other words, respondents evaluate each
of the vignettes using the same 5-point response category scale and with regard to the same
question as the main self-reported question for any given domain. The mapping from the
latent variable to the observed categorical responses is defined by a series of cut-points which
are allowed to differ by socio-demographic characteristics of the individual (e.g., age, sex,
years of education, and country of residence). These categorical responses are the left-hand
side variable in the first component of the HOPIT model (each vignette response being a
separate observation). On the right-hand side are dummies for each of V-1 vignettes, with the
first vignette (describing the best ability level) being set to be the absorbed category and
therefore equivalent to 0. In essence, the model fixes the level of ability on the underlying
latent variable (i.e., each domain of health) scale such that any differences in response
categories are attributed to cut-point shifts. The coefficients on these for each of V-1 vignettes
dummy variables are the fixed levels on the underlying latent variable. Mathematically, this
implies that:
Y*v = f (dummy variable for each vignette)
And the observation mechanism such that categorical response Yv is chosen:
Yv = 1 if
Yv = 2 if
…
Yv = 5 if
-¥ < Y*v < t1
t1 < Y*v < t2
t4 < Y*v < +¥
Plus,
10
t’s = f (socio-demographic characteristics)
The second component of the likelihood function utilizes information from self-report
responses. Cut-points are estimated from the vignettes section of the likelihood to calibrate
the self-report responses so as to make them cross-population comparable. In this sense, there
is parametric dependence between these two different components of the likelihood function.
The mean variable of the latent variable now refers to the individual’s latent variable and this
is assumed to be a function of socio-demographic characteristics. Mathematically,
Y*s = f (socio-demographic characteristics)
And the observation mechanism for the main self-report Ys:
Ys = 1 if
Ys = 2 if
…
Ys = 5 if
-¥ < Y*s < t1
t1 < Y*s < t2
t4 < Y*s < +¥
And,
t’s = f (socio-demographic characteristics)
3.5.2 Compound Hierarchical Ordered Probit (CHOPIT) Model (HOPIT with auxiliary
questions). The third component of the likelihood function uses information from auxiliary
questions. The mean level of the latent variable is assumed to be the same as that for the main
self-report question. Cut-points for this component are not linked to the vignettes. However,
since the scale is being set as the same as that for the main question, the cut-points are
comparable to the ones recovered for the main self-report question. Mathematically,
Y*s = f (socio-demographic characteristics)
The observation mechanism for each of the auxiliary questions Ya is such that:
Ya = 1 if
Ya = 2 if
…
Ya = 5 if
-¥ < Y*s < f1
f1 < Y*s < f2
f4 < Y*s < +¥
And,
f’s = f (socio-demographic characteristics)
In this data set, auxiliary questions exist only for the 10 in depth household surveys.
3.5.3 Random Effect. If there is an individual-level random effect in the data -- i.e., when
covariates in our model do not capture all the systematic variation in the latent variable -- then
there remains information content in the set of responses (when more than one question per
domain exists) on the level of health for each individual that has not been fully exploited, or
there are covariates missing from the model. In order to exploit the information content in the
set of responses we can make use of Bayes' theorem to obtain estimates of the mean level of
the latent variable conditional on the observed set of responses for a given individual (see
11
Tandon et al. 2001 for an evaluation of this approach using simulated data). For now within
HOPIT we assume that the random effect captures about 50 per cent of the variation in
estimated variance of the error term. Under this assumption, the posterior prediction of the Y*
for each of the six domains for all 66 surveys, conditional on the observed pattern of
responses, has been computed.
3.5.4 Evaluation of model fit. Assessing goodness-of-fit for categorical data is not
straightforward. One can compute a simple count-R² which is a measure of the proportion of
correct responses obtained for a given sample. For ordinal data, the predicted categorical
response would be the one associated with the maximum predicted probability. Other options
include a pseudo-R² measure, which in software such as STATA, is a likelihood-based
comparison of the model with all the parameters to one with only the intercept (Long and
Freese 2001). Rasch-based models use measures of fit such as "outfit" and "infit": "outfit" is
a chi-square test based on the sum of the standardized deviation of observed versus expected
values of a response. "Infit" is also a chi-square test which utilizes an information-weighted
sum by adjusting for extreme responses using weights (Write and Mok 2000). In order to
assess model fit, a standard likelihood ratio test can be used. These tests compare the loglikelihood value of the full model with a constrained version of the same model (i.e., a model
that is nested within the full model) to assess the contribution of the dropped covariates to the
likelihood function. Assume L0 is the log-likelihood value associated with the full model and
L1 is the log-likelihood value of the constrained model. Then -2(L1-L0) is distributed χ² with
d0-d1 degrees of freedom, where d0 and d1 are the model degrees of freedom associated with
the full and the constrained models on exactly the same sample, respectively (Long and
Freese 2001).
III.6 AVERAGE LEVEL OF HEALTH ON SIX DOMAINS: RESCALE, AGE
STANDARDIZATION
3.6.1 Rescale. Using the predicted level of health for each domain Y* incorporating the
individual-level random effect, we re-scale our results across surveys, for each domain
separately. This is so as the scale of the predicted level of health Y* is arbitrary and differs for
each domain. For presentation purposes we equalize the scale across populations while
maintaining the relative differences and distribution of severity within each population across
the 66 surveys. We apply a simple transformation of the predicted Y* to a 0 to 100 scale, by
domain. We truncate the end-points of the estimated level of health Y* to provide greater
stability and confidence in the comparability of end points selected. Rather than using the
observed minimum and maximum Y* per domain across all 66 surveys in the transformation,
we equate the bottom 2.5 % and top 97.5% of the distribution of predicted level of health Y*
by domain, to 0 and 100, respectively. For different sex and age-groups3, the mean value of
this estimated level is reported for all 66 surveys and for each of the six domains. The
posterior estimates of health, Y* are relative to one another and do not reflect an absolute
scale (for each domain). Comparisons of the estimated level of health may be made within
each domain of health, not across domains.
3.6.2 Age Standardization. In order to facilitate comparisons across countries, we
calculated age-standardized aggregated results for all age groups, by sex, for each of the 66
survey included within this analysis. We apply the UN Population Division 1999 revised
World Standard Population (Ahmad et al. 2000) to males and females. We then summarize
the level of health by domain across all age groups, reflecting the age groups actually
sampled, by sex and survey.
3
except for those with <10 observations as noted in Table 1 column IV.
12
III.7 EVALUATION OF METHODS
We now turn to a general evaluation of this method before presenting our results across
surveys. Unlike Tandon et al. (2001) who provide an evaluation of the HOPIT model based
on simulated data where "truth" is known, we either test or provide examples of the impact of
each step of the methods applied to the WHO Multi-Country Survey data where "truth" is
unknown. We subsequently discuss whether our methods appear to enhance the information
content and comparability of data.
The following tests or examples are provided:
·
Evidence of cut-point shifts across countries (the first component of the likelihood
function)
Posterior estimates (HOPIT with and without random effect component)
Estimated level of health: comparison of ordinal responses and estimated level of health,
by domain (the second component of the likelihood function)
Estimated level of health: HOPIT vs. HOPIT with auxiliary questions (the third
component of the likelihood function)
Model fit: likelihood ratio test for full and nested model (addressing addition of
covariates to cut-points)
·
·
·
·
3.7.1 Evidence of cut-point shifts across countries (the first component of the likelihood
function). Two null hypotheses concerning this first approach are proposed. The first is that
the response pattern on the rating of vignettes for each domain is constant across surveys.
Figure 4 illustrates the proportion of responses in each response category for each of the
seven vignettes for the domain of Self Care: in-depth household surveys in India (Andhra
Pradesh) and China (three provinces) illustrate that these proportions differ. Figure 5
summarizes these differences by illustrating the mean rating of vignettes in two other domains
assessed, Affect and Pain, for one survey from each WHO Region (AFRO: Nigeria; AMRO:
Argentina; EMRO: Jordan; EURO: Croatia; SEARO: Thailand; WPRO: Australia). For any
set of vignettes, the response distribution in each of the five categories differs by country, as
well as by other covariates (not shown), and therefore are not constant across surveys. A
critical evaluation of vignettes as a means to calibrate responses across populations within the
health status analysis is beyond the scope of this paper and will be provided elsewhere.
Figure 4. Proportion of responses in each category (in depth household surveys conducted in
India and China), seven vignettes addressing domain of Self Care
100
100
80
80
60
60
%
7
40
6
5
20
4
3
0
1
2
2
3
Re s pons e Cate gory -India
1
4
5
Se lf Care
V igne tte s
%
7
40
6
5
20
4
3
0
1
Se lf Care
vigne tte s
2
2
3
1
4
5
Re s pons e Cate gory -China
13
Figure 5. Mean ratings of Vignette Sets (one survey from each WHO Region) for Affect and Pain
5
5
4.5
4.5
4
Nigeria
3.5
A rgentina
Jordan
3
Croatia
2.5
Thailand
A ustralia
2
1.5
Mean Rating
Mean Rating
4
Nigeria
3.5
A rgentina
Jordan
3
Croatia
2.5
Thailand
A ustralia
2
1.5
1
1
1
2
3
4
Affe ct V igne tte s
5
6
1
2
3
4
5
6
7
Pain V ignette s
The second null hypothesis is that the cut-points on the latent variable for each domain do not
vary given differences in covariates (e.g., age, sex, years of education, and survey
population). In this paper, we focus on differences across survey populations. Figure 6
illustrates the distribution of mean cut-points (t1-t4) for each domain: cut-points vary by
survey. For each cut-point, each data point in the distribution represents one of the 66
surveys. The x-axis notes: t1 which is the transition from the ordinal category "extreme
difficulty" to the next best ordinal category, "severe difficulty"; t2, the transition from
"severe" to "moderate"; t3, the transition from "moderate" to "mild"; and t4, the transition
from "mild" to "no difficulty" or the best category. The y-axis represents the latent variable
scale for each domain, with the horizontal lines being the coefficients on each of the vignettes
from the first component of the likelihood function (the best vignette is set to 0). These
coefficients set the scale on the underlying latent variable across all surveys. A distribution
exists for t1-t4 and these shifts in cut-points reflect mean differences across surveys (see
Tandon et al. 2001).
Figure 7 provides further detail on the domain of cognition. From the first part of the
likelihood function, the vignette describing the best state of cognition has a coefficient of 0,
and the vignette describing the worst state of cognition, has a coefficient almost equivalent to
-4. Let us focus on a fixed level of cognition (on the y axis: -2.5). This level corresponds
roughly to the following vignette describing difficulties in concentration and memory: “Mr X
is easily distracted, and within 10 minutes of beginning a task, his attention shifts to
something else. He can remember important facts when he tries, but several times a week he
finds that he has to struggle to recollect what people have said or recent events.” On average,
individuals from Indonesia will rate this level of cognition “mild difficulty”, while individuals
from 11 other surveys (from Greece, France, Trinadad & Tobago, Chile, Luxembourg,
Belgium, Nigeria, Bulgaria, Denmark, Iceland or Netherlands) on average will rate this same
level of cognition, "moderate difficulty.” Differences across selected countries are
significant: for example, t2 for Indonesia (-2.96) vs. Netherlands (-2.33).
We interpret these differences to mean that for the populations in the 11 countries noted, on
average, they have higher standards or norms for what constitutes “mild” difficulty in
comparison to “moderate” difficulty, for cognition, in comparison to Indonesia: Indonesians
on average have lower norms -- this is why Indonesia’s cut-points are found at the lower end
of each cut-point distribution -- shown here for cut-point 2 and 3. As noted, cut-points are
14
also allowed to vary by age, years of education and sex. Appendix 1 details the mean cutpoints (t1-t4) values for all 66 surveys, for the domain of cognition.
Figure 6. Distribution of cut-points (t1-t4) and mean vignettes' coefficients
(Cognition, Mobility, Usual Activities), for each of the 66 surveys
Cognition
1
Main question - Cognition
Vignettes' Coefficients
0
-1
-2
-3
-4
-5
t1
t2
t3
cut-points
t4
t1
t2
t3
cut-points
t4
t2
t3
cut-points
t4
Mobility
1
Main question - Mobility
Vignettes' Coefficients
0
-1
-2
-3
-4
-5
Usual Activities
1
Main question - Usual Activities
Vignettes' Coefficients
0
-1
-2
-3
-4
-5
t1
Figure 6 (continued). Distribution of cut-points (t1-t4) and mean vignettes' coefficients
15
(Affect, Pain, Self-Care), for each of the 66 surveys
Affect
1
-1
Main question - Affect
Vignettes' Coefficients
0
-2
-3
-4
-5
-6
tau1
tau2
tau3
cut-points
tau4
Pain
3
1
Main question - Pain
Vignettes' Coefficients
2
0
-1
-2
-3
-4
tau1
tau2
tau1
tau2
cut-points
tau3
tau4
tau3
tau4
Self Care
1
Main question - Self Care
Vignettes' Coefficients
0
-1
-2
-3
-4
-5
cut-points
16
Figure 7. Distribution of mean cut-points, by survey: same estimated level of Cognition, different
cut-points, using vignette strategy to calibrate responses across surveys
Cognition
1
Greece, France, Trinadad & Tobago, Chile,
Luxembourg, Belgium, Nigeria, Bulgaria,
Denmark, Iceland, Netherlands
Main question - Cognition
Vignettes' Coefficients
0
-1
-2
-3
Indonesia
-4
Indonesia
-5
t1
t2
cut-points
t3
t4
Another way of looking at this same distribution of cut-points for Cognition, is that real data
can parallel the simulation by Tandon et al. (2001): here Andhra Pradesh is similar to
population A, with lower standards for what is good health, and Luxembourg is similar to
population B, with higher standards for what constitutes good health (Figure 8). Across cutpoints for both populations, we find that for each cut point spanning different levels of
cognition, Luxembourg has higher standards for cognition, before it transitions to next
"mildest" difficulty category, in comparison to individuals from Andhra Pradesh: on average,
they transition to the next "mildest" difficulty category at lower levels of cognition.
Figure 8. Distribution of mean cut-points, by survey: evidence of systematic cut-point shifts
between two survey populations (Luxembourg and India (Andhra Pradesh))
Cognition
1
LUX
0
-1
Main question - Cognition
Vignettes' Coefficients
LUX
LUX
-2
IND
LUX
IND
-3
IND
-4
IND
-5
t1
t2
cut-points
t3
t4
17
Given that Luxembourg has the highest GDP (PPP) and India, one of the lowest, among
populations included within this analysis, differences in norms, standards and expectations for
health on different domains are not surprising. Of course, other health and non health system
factors, and socio-cultural and economic correlates are likely to contribute to these differences
in mean cut-points across countries: similar results are found for the other five domains. The
interesting point is here we have evidence that collectively such differences do influence, in a
seemingly systematic way, the rating of standardized descriptions of health on different
domains, i.e., the vignettes. The new methods use this information to calibrate or adjust
people’s self-report of their own health status on the same domains, across survey
populations.
3.7.2 Estimated level of health: HOPIT with and without posterior estimates
(addressing random effect). Based on the assumption that the random effect captures about
50 per cent of the variation in estimated variance of the error term, the posterior prediction of
individual level of health is compared to the prediction of individual level of health without
this random effect component. Across all 66 surveys, the correlation of the estimated level of
health, Y* based on the prior and posterior estimates by domain, vary between 0.72 and 0.92
(i.e., Affect: 0.72; Cognition: 0.72; Pain: 0.81; Mobility: 0.84; Self Care: 0.92; Usual
Activities: 0.80.).
Tandon et al. (2001:13-14) demonstrate with a simulated data set where truth is known, the
R-squared between "True Mobility" and the predicted Y* of Mobility using the HOPIT model
only with covariates is 0.055: however, with the posterior estimate, the R-squared jumps to
0.334. They conclude that the posterior estimates significantly improves the estimation of
health in the simulated data set. For the survey data, we are unable to evaluate whether the
addition of a correction for individual random effect performs better. We have simply
assumed that the random effect captures 50 per cent of the variation, and we hypothesize that
we capture more of the systematic variation on the latent variable due to covariates not
measured.
3.7.3 Estimated level of health: comparison of ordinal responses and estimated level of
health, by domain (the second component of the likelihood function). To evaluate the
overall impact of the analysis approach applied, we compare mean ordinal responses (the five
categories) for each age and the estimated level of health Y* (based on our posterior estimates
from the HOPIT model), for all six domains assessed of health. We extend our comparison
between Luxembourg and India (Andhra Pradesh), to illustrate the difference our methods
make on the estimated level of health, across all domains. These results appear quite
remarkable (Figure 9).
Across all domains, a higher score is better health. If we only look at the self-reported ratings
using five categories (the circles on the graphs), there is not much difference in the
distribution of mean responses for each single year of age, between Luxembourg, on the left,
and Andhra Pradesh, on the right, concerning the level of self-reported health across most
domains. Most analyses on health status data from surveys stops here. However, if we
instead focus on the estimated level of health based on our new methods (the triangles), we
see that the mean levels of health tend to be lower in Andhra Pradesh than Luxembourg for
most domains, and that the drop across age4 is steeper for Andhra Pradesh across most
domains, in comparison to Luxembourg.
4
The spread of mean level of health Y* (triangles in Figure 9 most prominent in self-care) by age
reflects that in our estimate of Y* for each domain, the covariate age is divided into four categories,
rather than as a continuous variables.
18
Figure 9. Mean response on ordinal categories vs. posterior estimated level of health (Affect,
Cognition, Mobility), Luxembourg and India
Luxembourg (n=719)
India (n=5132)
2
1
40.00
50.00
Age
Mean response 5 categories
60.00
70.00
Mean Y* HOPIT & BAY R.E.
2
1
0
50.00
Age
Mean response 5 categories
60.00
70.00
0
20.00
30.00
40.00
50.00
Age
60.00
70.00
80.00
Mean Y* HOPIT & BAY R.E.
2
0
30.00
40.00
50.00
Age
Mean response 5 categories
60.00
70.00
80.00
Mean Y* HOPIT & BAY R.E.
Mean categorical response - Mobility
5
Mean Y* HOPIT & BAY R.E. Luxembourg
1
80.00
1
100
2
70.00
3
Mean Y* HOPIT & BAY R.E.
3
60.00
100
20.00
4
50.00
Age
4
80.00
5
40.00
Mean response 5 categories
Mean categorical response - Cognition
3
30.00
5
Mean Y* HOPIT & BAY R.E. Luxembourg
Mean categorical response - Cognition
4
40.00
0
20.00
100
30.00
2
80.00
5
20.00
3
Mean Y* HOPIT & BAY R.E. India
30.00
4
1
0
20.00
100
Mean Y* HOPIT & BAY R.E. India
3
Mean categorical response - Affect
4
Mean Y* HOPIT & BAY R.E.
5
100
Mean Y* HOPIT & BAY R.E. Luxembourg
Mean categorical response - Affect
5
Mean categorical response - Mobility
Mean response 5 categories
Mean Y* HOPIT & BAY R.E.
100
Mean Y* HOPIT & BAY R.E. India
Mean response 5 categories
4
3
2
1
0
20.00
30.00
40.00
50.00
Age
60.00
70.00
80.00
(continued)
19
Figure 9. Mean response on ordinal categories vs. posterior estimated level of health (Pain, Self
Care, Usual Activities), Luxembourg and India (continued)
Luxembourg (n=719)
India (n=5132)
Mean response 5 categories Mean Y* HOPIT & BAY R.E.
2
1
50.00
Age
Mean response 5 categories
60.00
Mean Y* HOPIT & BAY R.E.
2
1
0
40.00
50.00
Age
Mean response 5 categories
60.00
70.00
0
20.00
30.00
40.00
50.00
Age
60.00
70.00
80.00
Mean Y* HOPIT & BAY R.E.
2
0
30.00
40.00
50.00
Age
Mean response 5 categories
60.00
70.00
80.00
Mean Y* HOPIT & BAY R.E.
Mean categorical response - Usual Activities
5
Mean Y* HOPIT & BAY R.E. Luxembourg
1
80.00
1
100
2
70.00
3
Mean Y* HOPIT & BAY R.E.
3
60.00
100
20.00
4
50.00
Age
4
80.00
5
Mean categorical response - Usual Activities
Mean categorical response - self care
3
40.00
5
Mean Y* HOPIT & BAY R.E. Luxembourg
Mean categorical response - self care
4
30.00
Mean response 5 categories
100
30.00
0
20.00
70.00 80.00
5
20.00
2
Mean Y* HOPIT & BAY R.E. India
40.00
3
100
Mean Y* HOPIT & BAY R.E. India
30.00
4
1
0
20.00
100
Mean Y* HOPIT & BAY R.E. India
3
Mean categorical response - Pain
4
Mean Y* HOPIT & BAY R.E.
5
100
Mean Y* HOPIT & BAY R.E. Luxembourg
Mean categorical response - Pain
5
Mean response 5 categories
4
3
2
1
0
20.00
30.00
40.00
50.00
Age
60.00
70.00
80.00
Although each population rates average levels of health on domains assessed in a similar
fashion using categorical responses across ages, based on evidence of shifts in response
category cut-points, these mean ratings using ordinal categories are not comparable across
the two survey populations. That Luxembourg has higher life expectancy for both males and
females, as well as the lower incidence and prevalence of a wide range of diseases, it is not
surprising that for many domains of health, Luxembourg has higher levels in comparison to
20
Andhra Pradesh. We propose that our posterior estimates based on the HOPIT model have
greater face validity given expected differences in health status between the two countries,
than those based on the ordinal responses. Another indication that the information content of
the survey data has improved, is that the large ceiling effects (i.e., proportion of respondents
in the best ordinal response category) that are often in population based surveys have also
been reduced (for example, Luxembourg, self-care). Additional comparisons based on the
results from the HOPIT model, with those where the t1-t4 do not vary by covariates, is
underway.
3.7.4 Estimated level of health: HOPIT vs. CHOPIT (the third component of the
likelihood function). We now turn to the in-depth household surveys (n=59,618) that contain
auxiliary questions addressing each core domain of health, and consider if auxiliary questions
add information content to the estimated average level of health, Y* for each domain. We
explore this question by comparing the correlation of our prior estimates of Y* with and
without auxiliary questions, as well as comparing the distribution of the levels of health for
one domain in the 10 in-depth household surveys. For the domain of Mobility, the correlation
is 0.99 within each of the in-depth household surveys: almost no difference exists in results
between the current versions of HOPIT and CHOPIT models using the same vignettes and
covariates. For example, the cumulative frequency of different levels of mobility based on
HOPIT and CHOPIT for data from Mexico and Egypt (Figure 10) are very similar (shifted),
as is the smoothness of these distributions (e.g., a smoother distribution of the cumulative
frequency would reflect finer distinctions between different severity levels.)
Figure 10: Cumulative Frequency Distribution of different levels of Mobility, based on prior
estimates Y* from HOPIT vs. CHOPIT Models
Mexico (n=4336)
Cond. cdf of HOPIT
Egypt (n=4485)
Cond. cdf of CHOPIT
Cond. cdf of HOPIT
Cond. cdf of CHOPIT
1
Hopit Y*
Cummulative Frequency Distribution
Cummulative Frequency Distribution
1
.5
0
Chopit Y*
.5
0
0
10
20
30
40
50
60
70
Level of Mobility -- Mexico
80
90
100
0
10
20
30
40
50
60
70
Level of Mobility -- Egypt
80
A comparison of the posterior estimates from HOPIT and CHOPIT may offer different
results, and is currently being pursued. In addition, further work is under way on one hand to
investigate whether auxiliary questions add information content beyond what is contained in
the main question addressing each domain, and on the other hand gauge the minimum number
of questions required (e.g. item reduction strategies). Results in this paper across all 66
surveys are based on posterior estimates Y* reflecting the HOPIT model.
21
90
100
3.7.5 Model fit: likelihood ratio test for full and nested models (addressing addition of
covariates on the cut-points to the basic model where cut-points are invariable).
We compare the full HOPIT model with vignettes and covariates (age, sex, years of
education, and survey population) on cut-points (e.g., t1-t1), with the nested model with no
covariates on the cut-points (i.e., t1-t4 do not vary by age, sex, years of education, or survey
population) for the following two domains as an example.
Affect
χ²(280) = 8144.36
Prob > χ² = 0.000
Mobility
χ²(280) = 10013.74
Prob > χ² = 0.000
Both tests compare the log-likelihood value of the full model with the constrained version of
the model on exactly the same sample: this test shows that adding all of the covariates on the
cut-points significantly adds to the explanatory power of the model applied to either domain
of health. Across the six domains, differences across age groups are significant across most
cut-points (i.e., t1-t4). Sex and years of education are usually significant, but not always (not
shown).
IV. Results
Using the methods developed and evaluated in section 3, we have estimated the average level
of health for each of six domains assessed of health, for males and females, in six age groups
based on the self-report of health within 66 surveys from 57 countries included within the
WHO Multi-Country Survey. We also estimated the average level of health by domain for
the total population sampled in each survey, by sex, in order to facilitate comparisons across
countries. The posterior estimates of health, Y* are domain-specific, on a scale defined by the
coefficients of vignettes for each domain, and then rescaled 0 to 100, as described earlier. In
all of the figures and tables presented, 100 is the best level of self-reported health, whereas 0
is the worst5 level of self-reported health, across the 66 surveys analyzed. Comparisons of the
estimated level of health may be made within each domain of health, not across domains. A
higher level of pain actually refers to the absence of pain, which is better health.
IV.1 ESTIMATION RESULTS: HOPIT BY DOMAIN ACROSS ALL 66 SURVEYS
Before detailing the average levels of health by domain, we provide the HOPIT model
estimates on key variables (Table 3). Neither dummy variables for each survey nor covariates
across cut-points are shown (see Appendix II for the complete set of covariates and estimates,
including for each cut-point, for the domain of Cognition). The coefficients on the vignettes
fix the scale of the latent variable, with the vignette describing the best level of health in each
domain being set to 0 (see Figure 6): except for the domain of pain, the coefficients on each
vignette are in the expected order given the severity level described. The estimates on
covariates should be interpreted in relation to the absorbed categories or baseline values for
covariates (age group 15-29; 0 years of education; females; and the survey from United Arab
Emirates6). Across all domains, the estimated level of health Y* decreases for each age group,
increases with years of education, and on average is higher for males than for females (Table
3).
5
Zero is not equivalent to death but to the worst level of self-reported health reported
United Arab Emirates is the baseline country only due to its abbreviation in the analysis "ARE" and is
the first country listed in alphabetical order.
6
22
IV.2 ESTIMATED LEVEL OF HEALTH ON EACH DOMAIN, BY AGE -SEX
GROUPS
Age-specific estimates for the average level of health by domain are presented for the
following age groups, by sex: 15-29; 30-44, 45-59, 60-69, 70-79, 80 and over. Figures 11 16 each cover one domain and include all 66 surveys: Canada, China, Czech Republic,
Egypt, Finland, France, Indonesia, Netherlands and Turkey are listed twice, with the different
survey modes noted across all 66 surveys. These results across ages are grouped by the six
WHO regions. For the European Region which has the largest number of surveys included
within this analysis, countries are sub-divided into four groups of graphs.
The average level of health for each domain (affect, cognition, mobility, pain, self care and
usual activities) within age groups and trends across age groups should be reviewed
separately. For example, across age and sex groups, average levels of affect are better in
Mexico, Egypt, Indonesia, Ireland and China, in comparison to other countries in the same
region. However, the same pattern does not exist across all domains. For example, the highest
average level of mobility is not always achieved by the same country across age and sex
groups within each region. Furthermore, some domains have much greater variation across
age groups (i.e., mobility or cognition) than others (i.e., affect).
IV.3 LEVEL OF HEALTH ON EACH DOMAIN, AGGREGATED FOR THE
TOTAL SURVEY POPULATION, BY SEX
Country level age-specific estimates for health by sex were aggregated to estimate the agestandardized level of health by domain to facilitate comparison across all survey populations.
Table 4 presents these results by domain for all 66 surveys in alphabetical order by survey
population. Tables 5-10 provide these results in rank order based on the average estimated
level for males and females combined, and also include the ratio of male to female level of
health, for each domain. Figures 17-22 illustrate these results by domain, as well as compare
the average level of health for each domain between males and females with life expectancy
(Lopez et al. 2001) for males and females respectively, and the combined average for both
sexes, with per capita GDP (Evans et al. 2001).
Countries at the top and bottom across domains are similar, but not identical. For males and
females combined, the data collected through these surveys indicate that Indonesia
(household) has the highest level of self-reported affect (Table 5), followed by Ireland,
Nigeria, Germany, Luxembourg, Belgium, Spain and Mexico. The lowest self-reported level
of affect is in Kyrgystan, followed by Turkey (postal), Ukraine, Latvia, Romania, Lithuania,
Croatia, Poland, Hungary and Cyprus. Except for Costa Rica and Venezuela, males report
equal or higher levels of affect than women across all surveys: a male to female ratio of
greater than or equal to 1.15 is noted in Chile, Czech Republic (postal), Columbia, Egypt
(postal), Argentina, Morocco, Cyprus, Lithuania, Romania, Ukraine, Turkey (postal), and
Kyrgyzstan. At higher levels of average health for both sexes in this domain, the male to
female ratio tends to be smaller, than at lower average levels of affect.
For cognition (Table 6), Ireland has the highest self-reported level followed by Nigeria,
Spain, Russian Federation, Germany, Mexico, Finland, Indonesia (household), Luxembourg,
Egypt (household). The lowest self-reported level of cognition is in Kyrgystan, followed by
Turkey (postal), Trinidad & Tobago, Lithuania, Egypt (postal), Morocco, Thailand, Indonesia
(postal), Ukraine and Poland. The striking difference between estimates from Indonesia and
Egypt based on household and postal surveys requires further examination, beyond the scope
of this paper. Except for Canada (telephone), Costa Rica and Venezuela, males report equal or
higher levels of cognition than women across all surveys: a male to female ratio of greater
23
than or equal to 1.15 is noted in Egypt (household and postal), Italy, Argentina, Columbia,
India, Turkey (household and postal), China (household), United States, Romania, Croatia,
Cyprus, Bahrain, Portugal, Republic of Korea, Jordan, Poland, Ukraine, Indonesia (postal),
Thailand, Lithuania, Trinidad and Tobago, Kyrgyzstan and Morocco (at 1.63). At higher
levels of average health for both sexes in this domain, the male to female ratio tends to be
smaller, than at lower average levels of cognition.
For mobility (Table 7), Indonesia (postal and then in-depth household) has the highest selfreported level followed by Italy, Spain, Luxembourg, France (brief), Greece, Ireland and
Denmark. The lowest self-reported level of mobility is in Kyrgystan, followed by Lithuania,
Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan, Croatia, and
Slovenia. Except for Costa Rica, males report equal or higher levels of mobility than women
across all surveys: a male to female ratio of greater than or equal to 1.15 is noted in Chile,
Georgia, Iceland, Portugal, Bahrain, Republic of Korea, Russian Federation, Netherlands
(brief), Egypt (household and postal), Thailand, India, Romania, Slovakia, Croatia, Jodran,
Ukraine, Turkey (postal), Lithuania, Kyrgyzstan and Morocco (at 1.58). At higher levels of
average health for both sexes in this domain, the male to female ratio tends to be smaller, than
at lower average levels of mobility.
For pain (Table 8), United Arab Emirates has the highest self-reported absence of pain
followed by Ireland, Spain, Nigeria, China (household), Oman, Mexico, Italy, Germany, and
China (postal). The highest self-reported level of pain is in Kyrgystan, followed by Republic
of Korea, Indonesia (postal), Turkey (postal), Lithuania, Ukraine, Cyprus, Poland Egypt
(postal) and Austria. The lowest self-reported level of mobility is in Kyrgystan, followed by
Lithuania, Egypt (postal), Morocco, Turkey (postal), Czech Republic, Ukraine, Jordan,
Croatia, and Slovenia. In all surveys males report equal or higher levels of absence of pain
than women: in 29 surveys, a male to female ratio of greater than or equal to 1.15 is noted.
Those over 1.25 include Morocco (1.37), Romania (1.26), Cyprus (1.3), Lithuania (1.26),
Turkey postal (1.32), Indonesia postal (1.27) and Kyrgyzstan (1.47). At higher levels of
average health for both sexes in this domain, the male to female ratio tends to be smaller, than
at lower average levels of the absence of pain.
For self care (Table 9), Luxembourg has the highest self-reported level of self care, followed
by Nigeria, China (postal), Ireland, Sweden, Finland, Iceland, Canada (telephone),
Switzerland, and Spain. The lowest self-reported level of self care is in Kyrgystan, followed
by Turkey (postal), Egypt (postal), Morocco, Ukraine, Lithuania, Indonesia (postal),
Republic of Korea, Thailand, India. In all surveys males report equal or higher levels of self
care than women: a male to female ratio of greater than or equal to 1.15 is noted in Egypt
(household and postal), Jordan, India (1.25), Thailand, Republic of Korea, Morocco (1.27),
Turkey (postal) and Kyrgyzstan. At lower levels of average health for both sexes in this
domain, the male to female ratio tends to be greater, than at higher average levels of self care.
For usual activities (Table 10), Nigeria has the highest self-reported level of usual activities,
followed by Ireland, Spain, Luxembourg, Mexico, Argentina, France (brief), Indonesia
(household), Finland and Columbia. The lowest self-reported level of usual activities is in
Kyrgystan, followed by Ukraine, Turkey (postal), Morocco, Lithuania, Egypt (postal),
Poland, Romania, Czech Republic (postal), and Latvia. In all surveys males report equal or
higher levels of usual activities than women: in 16 surveys, a male to female ratio of greater
than or equal to 1.15 is noted. Those over 1.25 include Turkey (postal, 1.29) and Morocco
(1.51). At lower levels of average health for both sexes in this domain, the male to female
ratio tends to be greater, than at higher average levels of usual activities.
24
Table 3. Estimation results, HOPIT, by domain, across all 66 surveys (excluding dummy
variables for each survey and covariates on cut-points*)
Affect
Variable
Pain
Coefficient
Std. Err.
z
P>|z|
Vignettes
Variable
Coefficient
Std. Err.
z
P>|z|
Vignettes
vignette2
-1.890
0.011
-173.09
0.000
vignette2
-0.769
0.009
-85.32
0.000
vignette3
-2.447
0.011
-217.44
0.000
vignette3
-1.237
0.009
-134.90
0.000
vignette4
-2.618
0.011
-230.76
0.000
vignette4
-1.501
0.009
-160.59
0.000
vignette5
-3.246
0.012
-275.72
0.000
vignette5
-1.419
0.009
-153.20
0.000
vignette6
-4.293
0.013
-340.09
0.000
vignette6
-1.333
0.009
-144.77
0.000
vignette7
-2.730
0.010
-263.91
0.000
Mean
Age 30-44
-0.097
0.015
-6.33
0.000
Mean
Age 45-59
-0.305
0.017
-18.02
0.000
Age 30-44
-0.220
0.015
-14.49
0.000
Age 60+
-0.521
0.019
-27.88
0.000
Age 45-59
-0.554
0.017
-33.35
0.000
Male
0.270
0.012
23.33
0.000
Age 60+
-1.041
0.018
-57.50
0.000
Education (yrs)
0.022
0.001
15.05
0.000
Male
0.221
0.011
19.84
0.000
-1.223
0.711
-17.19
0.000
Education (yrs)
0.032
0.001
22.71
0.000
0.351
0.004
81.06
0.000
Intercept
1.389
0.079
17.60
0.000
log(s)
0.283
0.004
64.90
0.000
Intercept
log(s)
Cognition*
Variable
Coefficient
Std. Err.
z
P>|z|
Vignettes
Self Care
Variable
Coefficient
Std. Err.
z
P>|z|
vignette2
-1.703
0.011
-160.57
0.000
Vignettes
vignette3
-1.892
0.011
-177.88
0.000
vignette2
-1.901
0.011
-179.71
0.000
vignette4
-2.048
0.011
-191.49
0.000
vignette3
-2.077
0.011
-195.36
0.000
vignette5
-2.534
0.011
-231.10
0.000
vignette4
-2.488
0.011
-229.16
0.000
vignette6
-2.637
0.011
-241.02
0.000
vignette5
-2.555
0.011
-234.95
0.000
vignette7
-3.235
0.011
-287.41
0.000
vignette6
-2.827
0.011
-256.67
0.000
vignette8
-3.896
0.012
-331.09
0.000
vignette7
-3.740
0.012
-321.22
0.000
Mean
Mean
Age 30-44
-0.036
0.015
-2.46
0.014
Age 30-44
-0.218
0.025
-8.73
0.000
Age 45-59
-0.282
0.016
-17.31
0.000
Age 45-59
-0.666
0.027
-25.05
0.000
Age 60+
-0.701
0.018
-39.43
0.000
Age 60+
-1.482
0.029
-51.97
0.000
Male
0.180
0.011
16.32
0.000
Male
0.149
0.017
8.81
0.000
Education (yrs)
0.030
0.001
21.78
0.000
Education (yrs)
0.058
0.002
27.25
0.000
-0.726
0.068
-10.72
0.000
Intercept
0.619
0.107
5.77
0.000
0.242
0.005
49.67
0.000
log(s)
0.486
0.007
64.84
8.000
Intercept
log(s)
Mobility
Variable
Usual Activities
Coefficient
Std. Err.
z
P>|z|
Vignettes
Variable
Coefficient
Std. Err.
z
P>|z|
Vignettes
vignette2
-0.193
0.009
-22.13
0.000
vignette2
-1.784
0.010
-173.94
0.000
vignette3
-1.810
0.008
-227.55
0.000
vignette3
-1.953
0.010
-187.76
0.000
vignette4
-2.681
0.008
-321.06
0.000
vignette4
-1.991
0.010
-192.14
0.000
vignette5
-3.063
0.009
-358.16
0.000
vignette5
-2.272
0.010
-216.80
0.000
vignette6
-4.384
0.009
-462.84
0.000
vignette6
-2.674
0.011
-251.17
0.000
vignette7
-2.760
0.011
-257.87
0.000
vignette8
-3.409
0.011
-304.48
0.000
Mean
Age 30-44
-0.245
0.015
-15.91
0.000
Age 45-59
-0.658
0.017
-39.65
0.000
Mean
Age 60+
-1.292
0.018
-71.57
0.000
Age 30-44
-0.219
0.019
-11.55
0.000
Male
0.202
0.011
18.47
0.000
Age 45-59
-0.589
0.020
-28.75
0.000
Education (yrs)
0.039
0.001
28.86
0.000
Age 60+
-1.304
0.022
-58.79
0.000
-0.660
0.068
-9.72
0.000
Male
0.200
0.014
14.71
0.000
0.227
0.005
43.46
0.000
Education (yrs)
Intercept
log(s)
Intercept
* See Appendix II for complete set of estimates for Cognition
log(s)
0.048
0.002
28.29
0.000
-0.010
0.083
-0.13
0.901
0.443
0.005
82.51
0.000
25
Figure 11: Level of Health, Affect: Comparison of Age groups, Surveys grouped by Region,
Male and Female
Self Reported Level of Affect by Age Group, AFRO, WHO
Health & Responsiveness Surveys, 2001
100
90
80
70
60
50
40
30
male, Nigeria(h)
female,Nigeria(h)
20
10
0
15-29
A r genti na(b)
90
Canada(p)
80
Canada(t )
70
Chi l e(p)
45-59 60-69
Age groups
100
Canada(p)
80
Canada(t )
70
Chi l e(p)
Col ombi a(h)
Col ombi a(h)
50
Cos t a Ri c a(b)
40
M ex i c o(h)
30
T r i ni dad and
T obago(p)
20
Uni t ed St at es (p)
10
V enez uel a(b)
50
Cos t a Ri c a(b)
40
M ex i co(h)
30
T r i ni dad and
T obago(p)
Uni t ed St at es (p)
20
10
V enezuel a(b)
0
15-29
0
15-29 30-44 45-59 60-69 70-79
Age groups
30-44 45-59 60-69 70-79
80+
Age groups
80+
Self Reported Level of Affect by Age Group, Female,
EM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, EM RO,
WHO Health & Responsiveness Surveys, 2001
100
80+
A r gent i na(b)
90
60
60
70-79
Self Reported Level of Affect by Age Group, Female, AM RO,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, AM RO,
WHO Health & Responsiveness Surveys, 2001
100
30-44
B ahr ai n(b)
100
B ahr ai n(b)
90
90
E gypt (h)
80
70
E gypt (p)
60
80
E gy pt (h)
70
E gy pt (p)
60
J or dan(b)
50
40
M or oc c o(b)
30
Oman(b)
20
J or dan(b)
50
40
M or occ o(b)
30
Oman(b)
20
10
Uni t ed A r ab
E mi r at es (b)
0
10
Uni t ed A r ab
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29 30-44 45-59 60-69 70-79
80+
Age groups
26
Self Reported Level of Affect by Age Group, Female,
SEARO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, SEARO,
WHO Health & Responsiveness Surveys, 2001
100
100
90
I ndi a(h)
I ndi a(h)
90
80
80
70
70
I ndonesi a(h)
60
I ndonesi a(h
)
60
50
50
40
I ndonesi a(p)
40
I ndonesi a(p
)
30
30
20
20
T hai l and(p)
10
T hai l and(p)
10
0
0
15-29 30-44 45-59 60-69 70-79
15-29 30-44 45-59 60-69 70-79
80+
80+
Age groups
Age groups
Self Reported Level of Affect by Age Group, Female, EUROC, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, EUROC, WHO Health & Responsiveness Surveys, 2001
100
B ul gar i a(b)
100
90
Cr oat i a(b)
90
80
Cy pr us (p)
80
70
Cz ec h
Republ i c (b)
60
Cz ec h
Republ i c (p)
b)
Cr oat i a(b)
70
Cy pr us (p)
60
Hungar y (p)
50
40
M al t a(b)
40
30
P ol and(p)
30
20
Romani a(b)
20
10
Sl ov ak i a(h)
10
50
B ul gar i a(
Cz ec h
Republ i c (
b)
Cz ec h
Republ i c (
p)
Hungar y (p
)
M al t a(b)
0
0
15-29
30-44
45-59 60-69
Age groups
70-79
15-29
80+
Self Reported Level of Affect by Age Group, M ale, EUROE, WHO Health & Responsiveness Surveys, 2001
100
E s t oni a(b)
90
Geor gi a(h)
80
30-44
45-59 60-69
Age groups
70-79
80+
Self Reported Level of Affect by Age Group, Female, EUROE, WHO Health & Responsiveness Surveys, 2001
100
E s toni a(b)
90
Geor gi a(h)
80
K y r gy z s t an(p)
70
Lat v i a(b)
60
K y r gy z s t an(p)
70
Latv i a(b)
60
50
Li t huani a(p)
50
Li t huani a(p)
40
Rus s i an
40
Russ i an
30
T ur k ey (h)
30
T ur k ey (h)
20
T ur k ey (p)
20
T ur k ey (p)
Uk r ai ne(p)
10
Uk r ai ne(p)
Feder at i on(b)
10
0
Feder at i on(b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
80+
Age groups
27
Self Reported Level of Affect by Age Group, Female, EURON, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, EURON, WHO Health & Responsiveness Surveys, 2001
100
A us t r i a(p)
90
Denmar k (p)
80
Fi nl and(b)
70
100
A us t r i a(p)
90
Denmar k (p)
80
Fi nl and(b)
70
Fi nl and(p)
Fi nl and(p)
60
60
Ger many (b)
Ger many (b)
50
50
I c el and(b)
40
Net her l ands (b
I c el and(b)
40
Net her l ands (b
30
)
20
)
Net her l ands (p
Sweden(b)
10
Swi t z er l and(p)
0
15-29 30-44 45-59 60-69 70-79
Age groups
Fr anc e(p)
Gr eec e(p)
60
I r el and(b)
50
I t al y (b)
40
Lux embour g(t )
30
P or t ugal (b)
20
Spai n(b)
10
Uni t ed
K i ngdom(p)
0
15-29
30-44 45-59 60-69 70-79
30-44 45-59 60-69 70-79
80+
Age groups
Fr anc e(b)
70
Swi t z er l and(p)
0
15-29
B el gi um(b)
80
)
Sweden(b)
10
Self Reported Level of Affect by Age Group, Female, EUROW, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, EUROW, WHO Health & Responsiveness Surveys, 2001
90
Net her l ands (p
20
80+
100
)
30
100
B el gi um(b)
90
Fr anc e(b)
80
Fr anc e(p)
70
Gr eec e(p)
60
I r el and(b)
50
I t al y (b)
40
Lux embour g(t )
30
P or t ugal (b)
20
Spai n(b)
10
Uni t ed
K i ngdom(p)
0
15-29 30-44 45-59 60-69 70-79
80+
80+
Age groups
Age groups
Self Reported Level of Affect by Age Group, Female,
WPRO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Affect by Age Group, M ale, WPRO,
WHO Health & Responsiveness Surveys, 2001
100
100
A ust r al i a(p)
90
80
Chi na(h)
70
60
Chi na(p)
A ust r al i a(
90
p)
80
Chi na(h)
70
60
Chi na(p)
50
50
40
Newzeal and(p)
Newzeal a
40
nd(p)
30
30
20
Republ i c of
K or ea(p)
10
15-29
3044
45-59
6069
70-79
80+
Republ i c
20
of
K or ea(p)
10
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Age groups
28
Figure 12: Level of Health, Cognition: Comparison of Age groups, Surveys grouped by Region,
Male and Female
Self Reported Level of Cognition by Age Group, AFRO,
WHO Health & Responsiveness Surveys, 2001
100
male, Nigeria(h)
female,Nigeria(h)
90
80
70
60
50
40
30
20
10
0
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of Cognition by Age Group, Female,
AM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
AM RO, WHO Health & Responsiveness Surveys, 2001
100
A r gent i na (b)
100
90
Canada (p)
90
80
Canada (t )
80
70
Chi l e (p)
70
60
Col ombi a (h)
60
50
Cos t a Ri c a (b)
50
40
M ex i co (h)
40
30
T r i ni dad and
30
20
Uni t ed St at es
10
V enezuel a (b)
A r gent i na (b)
Canada (p)
Canada (t )
Chi l e (p)
Col ombi a (h)
Cos t a Ri c a
(b)
M ex i c o (h)
T r i ni dad and
T obago (p)
T obago (p)
20
Uni t ed St at es
(p)
(p)
10
V enez uel a
(b)
0
0
15-29 30-44 45-59 60-69 70-79
Age groups
15-29
80+
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of Cognition by Age Group, Female,
EM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
EM RO, WHO Health & Responsiveness Surveys, 2001
100
100
B ahr ai n (b)
90
E gy pt (h)
80
70
E gy pt (p)
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
60
60
J or dan (b)
50
40
M or oc c o (b)
30
J or dan (b)
50
40
M or oc c o (b)
30
Oman (b)
Oman (b)
20
20
10
Uni t ed A r ab
E mi r at es (b)
0
Uni t ed A r ab
10
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
80+
Age groups
29
Self Reported Level of Cognition by Age Group, Female,
SEARO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
SEARO, WHO Health & Responsiveness Surveys, 2001
100
100
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
70-79
15-29
80+
30-44
45-59
100
60-69
70-79
80+
Age groups
Age groups
Self Reported Level of Cognition by Age Group, Female,
EURO-C, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
EURO-C, WHO Health & Responsiveness Surveys, 2001
90
80
70
Hungar y (p)
100
Hungar y (p)
B ul gar i a (b)
90
B ul gar i a (b)
Cr oat i a (b)
80
Cr oat i a (b)
70
Cy pr us (p)
60
Cz ec h
Cy pr us (p)
60
Cz ec h
Republ i c (b)
50
Cz ec h
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ov ak i a (h)
Republ i c (b)
50
Cz ec h
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ov ak i a (h)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
80+
Self Reported Level of Cognition by Age Group, Female,
EURO-E, WHO Health & Responsiveness Surveys, 2001
E s t oni a (b)
90
60-69 70-79
Age groups
Self Reported Level of Cognition by Age Group, M ale,
EURO-E, WHO Health & Responsiveness Surveys, 2001
100
30-44 45-59
Geor gi a (h)
80
100
E s toni a (b)
90
Geor gi a (h)
80
K y r gy z s t an (p)
70
K y r gy z s t an (p)
70
Lat v i a (b)
60
Li t huani a (p)
50
Latv i a (b)
60
50
Li t huani a (p)
40
Rus s i an
40
Russ i an
30
T ur k ey (h)
30
T ur k ey (h)
20
T ur k ey (p)
20
T ur k ey (p)
10
Uk r ai ne (p)
10
Uk r ai ne (p)
Feder at i on (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
Feder at i on (b)
0
15-29
30-44
45-59 60-69
70-79
80+
Age groups
30
Self Reported Level of Cognition by Age Group, Female,
EURO-N, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
EURO-N, WHO Health & Responsiveness Surveys, 2001
100
A us t r i a
(p)
90
Denmar k
(p)
80
Fi nl and
(b)
70
Fi nl and
(p)
60
Ger many
(b)
50
I c el and
(b)
40
Net her l an
ds (b)
30
Net her l an
ds (p)
20
Sweden
(b)
10
Swi t z er l a
nd (p)
0
15-29
30-44
45-59 60-69 70-79
Age groups
100
A us t r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
60
Ger many (b)
50
I c el and (b)
40
Net her l ands
30
(b)
Net her l ands
20
(p)
Sweden (b)
10
Swi t z er l and
0
15-29
80+
30-44 45-59 60-69 70-79
Age groups
(p)
80+
Self Reported Level of Cognition by Age Group, Female,
EURO-W, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
EURO-W, WHO Health & Responsiveness Surveys, 2001
100
100
B el gi um (b)
B el gi um (b)
90
90
Fr anc e (b)
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
30-44 45-59 60-69 70-79
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
80+
30-44 45-59
Self Reported Level of Cognition by Age Group, Female,
WPRO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Cognition by Age Group, M ale,
WPRO, WHO Health & Responsiveness Surveys, 2001
100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
A ust r al i a (p)
Chi na (h)
20
A ust r al i a (p)
Chi na (h)
20
Chi na (p)
Newzeal and (p)
10
80+
Age groups
Age groups
30
60-69 70-79
Chi na (p)
Newzeal and (p)
10
Republ i c of K or ea (p)
Republ i c of K or ea (p)
0
0
15-29
30-44
45-59
60-69
Age groups
70-79
80+
15-29
30-44
45-59
60-69
70-79
80+
Age groups
31
Figure 13: Level of Health, Mobility: Comparison of Age groups, Surveys grouped by Region,
Male and Female
Self Reported Level of M obility by Age Group, AFRO,
WHO Health & Responsiveness Surveys, 2001
100
male, Nigeria(h)
female,Nigeria(h)
90
80
70
60
50
40
30
20
10
0
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of M obility by Age Group, Female,
AM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale,
AM RO, WHO Health & Responsiveness Surveys, 2001
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos ta Ri c a
(b)
40
M exi c o (h)
30
T r i ni dad and
T obago (p)
20
Uni ted St at es
(p)
10
V enez uel a (b)
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i co (h)
30
T r i ni dad and
T obago (p)
20
Uni t ed St at es (p)
10
V enezuel a (b)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29 30-44 45-59 60-69 70-79
80+
80+
Age groups
Self Reported Level of M obilit y by Age Group, Female,
EM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale,
EM RO, WHO Health & Responsiveness Surveys, 2001
100
100
B ahr ai n (b)
90
E gy pt (h)
80
70
E gy pt (p)
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
60
60
J or dan (b)
50
40
M or oc c o (b)
30
J or dan (b)
50
40
M or oc c o (b)
30
Oman (b)
Oman (b)
20
20
10
Uni t ed A r ab
E mi r at es (b)
0
Uni t ed A r ab
10
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
80+
Age groups
32
Self Reported Level of M obility by Age Group, Female,
SEARO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale,
SEARO, WHO Health & Responsiveness Surveys, 2001
100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
30
I ndi a (h)
I ndonesi a (h)
20
I ndonesi a (p)
10
I ndi a (h)
I ndonesi a (h)
20
I ndonesi a (p)
10
T hai l and (p)
T hai l and (p)
0
0
15-29
30-44
45-59
60-69
70-79
15-29
80+
30-44
45-59
100
60-69
70-79
80+
Age groups
Age groups
Self Reported Level of M obility by Age Group, Female,
EURO-C, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale, EUROC, WHO Health & Responsiveness Surveys, 2001
90
80
70
Hungar y (p)
100
Hungar y (p)
B ul gar i a (b)
90
B ul gar i a (b)
Cr oat i a (b)
80
Cr oat i a (b)
70
Cypr us (p)
60
Czech
Cypr us (p)
60
Czech
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
80+
Self Reported Level of M obility by Age Group, Female,
EURO-E, WHO Health & Responsiveness Surveys, 2001
E s t oni a (b)
90
60-69 70-79
Age groups
Self Reported Level of M obility by Age Group, M ale,
EURO-E, WHO Health & Responsiveness Surveys, 2001
100
30-44 45-59
Geor gi a (h)
80
100
E s t oni a (b)
90
Geor gi a (h)
80
K y r gy z s t an (p)
70
K y r gy z s t an (p)
70
Lat v i a (b)
60
Li t huani a (p)
50
Lat v i a (b)
60
Li t huani a (p)
50
40
Rus s i an
40
Rus s i an
30
T ur k ey (h)
30
T ur k ey (h)
20
T ur k ey (p)
20
T ur k ey (p)
10
Uk r ai ne (p)
10
Uk r ai ne (p)
Feder at i on (b)
0
Feder at i on (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44
45-59 60-69
70-79
80+
Age groups
33
Self Reported Level of M obility by Age Group, Female,
EURO-N, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale, EURON, WHO Healt h & Responsiveness Surveys, 2001
100
A ust r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
Ger many (b)
I cel and (b)
50
I cel and (b)
Net her l ands
40
Ger many (b)
50
40
(b)
Net her l ands
(p)
Sweden (b)
Swi t zer l and
15-29 30-44 45-59 60-69 70-79
Age groups
Net her l ands
(p)
Sweden (b)
10
Swi t zer l and
(p)
0
15-29
80+
100
B el gi um (b)
90
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
30-44 45-59 60-69 70-79
(b)
20
30-44 45-59 60-69 70-79
Age groups
100
B el gi um (b)
90
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
80+
30-44 45-59
100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
A ust r al i a (p)
Chi na (h)
A ust r al i a (p)
Chi na (h)
20
Chi na (p)
Newzeal and (p)
10
80+
Self Reported Level of M obility by Age Group, Female,
WPRO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale,
WPRO, WHO Health & Responsiveness Surveys, 2001
20
60-69 70-79
Age groups
Age groups
30
80+
Self Reported Level of M obility by Age Group, Female,
EURO-W, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of M obility by Age Group, M ale, EUROW, WHO Health & Responsiveness Surveys, 2001
15-29
Net her l ands
30
(p)
0
Fi nl and (b)
Fi nl and (p)
60
10
Denmar k (p)
80
60
Fi nl and (p)
20
A ust r i a (p)
90
70
70
30
100
Chi na (p)
Newzeal and (p)
10
Republ i c of K or ea (p)
Republ i c of K or ea (p)
0
0
15-29
30-44
45-59
60-69
Age groups
70-79
80+
15-29
30-44
45-59
60-69
70-79
80+
Age groups
34
Figure 14: Level of Health, Pain: Comparison of Age groups, Surveys grouped by Region,
Male and Female
Self Reported Level of Pain by Age Group, AFRO, WHO
Health & Responsiveness Surveys, 2001
100
male, Nigeria(h)
female,Nigeria(h)
90
80
70
60
50
40
30
20
10
0
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of Pain by Age Group, Female, AM RO,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, AM RO,
WHO Health & Responsiveness Surveys, 2001
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i co (h)
30
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i c o (h)
30
T r i ni dad and
T r i ni dad and
T obago (p)
20
T obago (p)
20
Uni t ed St at es (p)
Uni t ed St at es
10
(p)
10
V enez uel a (b)
V enezuel a (b)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
30-44 45-59
60-69 70-79
80+
Age groups
Self Reported Level of Pain by Age Group, Female, EM RO,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, EM RO,
WHO Health & Responsiveness Surveys, 2001
100
100
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
60
60
Jor dan (b)
50
40
M or occo (b)
30
Jor dan (b)
50
40
M or occo (b)
30
Oman (b)
Oman (b)
20
20
10
Uni t ed A r ab
E mi r at es (b)
0
Uni t ed A r ab
10
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
Age groups
80+
35
Self Reported Level of Pain by Age Group, Female, SEARO,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, SEARO,
WHO Health & Responsiveness Surveys, 2001
100
100
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
70-79
15-29
80+
30-44
45-59
100
60-69
70-79
80+
Age groups
Age groups
Self Report ed Level of Pain by Age Group, Female, EURO-C,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, EURO-C,
WHO Health & Responsiveness Surveys, 2001
90
80
70
Hungar y (p)
100
Hungar y (p)
B ul gar i a (b)
90
B ul gar i a (b)
Cr oat i a (b)
80
Cr oat i a (b)
70
Cypr us (p)
60
Czech
Cypr us (p)
60
Czech
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
E s t oni a (b)
90
60-69 70-79
80+
Age groups
Self Reported Level of Pain by Age Group, M ale, EURO-E,
WHO Health & Responsiveness Surveys, 2001
100
30-44 45-59
Geor gi a (h)
80
Self Reported Level of Pain by Age Group, Female, EURO-E,
WHO Health & Responsiveness Surveys, 2001
100
E s t oni a (b)
90
Geor gi a (h)
80
K y r gy z s t an (p)
70
K y r gy z s t an (p)
70
Lat v i a (b)
60
Li t huani a (p)
50
Lat v i a (b)
60
50
Li t huani a (p)
40
Rus s i an
40
Rus s i an
30
T ur k ey (h)
30
T ur k ey (h)
20
T ur k ey (p)
20
T ur k ey (p)
10
Uk r ai ne (p)
10
Uk r ai ne (p)
Feder at i on (b)
0
Feder at i on (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44
45-59 60-69
70-79
80+
Age groups
36
Self Reported Level of Pain by Age Group, Female, EURON, WHO Healt h & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, EURO-N,
WHO Health & Responsiveness Surveys, 2001
100
A ust r i a (p)
100
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
70
60
Ger many (b)
60
50
I cel and (b)
50
40
Net her l ands
40
(b)
Net her l ands
30
30
A ust r i a (p)
90
90
Denmar k (p)
80
Fi nl and (b)
Fi nl and (p)
Ger many (b)
I cel and (b)
Net her l ands
(b)
Net her l ands
(p)
Sweden (b)
20
Swi t zer l and
10
(p)
20
Sweden (b)
10
Swi t zer l and
(p)
(p)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29 30-44 45-59 60-69 70-79
Age groups
80+
Self Reported Level of Pain by Age Group, Female, EUROW, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, EURO-W,
WHO Health & Responsiveness Surveys, 2001
100
B el gi um (b)
90
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
30-44 45-59 60-69 70-79
80+
100
B el gi um (b)
90
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
80+
30-44 45-59
60-69 70-79
80+
Age groups
Age groups
Self Reported Level of Pain by Age Group, Female, WPRO,
WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Pain by Age Group, M ale, WPRO,
WHO Health & Responsiveness Surveys, 2001
100
100
A ust r al i a (p)
90
Chi na (p)
80
Newzeal and (p)
Republ i c of K or ea (p)
70
A ust r al i a (p)
90
Chi na (h)
Chi na (h)
80
Chi na (p)
70
Republ i c of K or ea (p)
Newz eal and (p)
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
Age groups
70-79
80+
15-29
30-44
45-59
60-69
70-79
80+
Age groups
37
Figure 15: Level of Health, Self Care: Comparison of Age groups, Surveys grouped by Region,
Male and Female
Self Reported Level of Self care by Age Group, AFRO,
WHO Health & Responsiveness Surveys, 2001
100
male, Nigeria(h)
female,Nigeria(h)
90
80
70
60
50
40
30
20
10
0
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of Self care by Age Group, Female,
AM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale,
AM RO, WHO Health & Responsiveness Surveys, 2001
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i co (h)
30
T r i ni dad and
T obago (p)
20
Uni t ed St at es
(p)
10
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cost a Ri c a (b)
40
M exi c o (h)
30
T r i ni dad and
T obago (p)
20
Uni ted St at es
(p)
10
V enez uel a (b)
V enezuel a (b)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
30-44
45-59 60-69
70-79
80+
Age groups
Self Reported Level of Self care by Age Group, Female,
EM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale,
EM RO, WHO Health & Responsiveness Surveys, 2001
100
100
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
60
60
Jor dan (b)
50
40
M or occo (b)
30
Jor dan (b)
50
40
M or occo (b)
30
Oman (b)
Oman (b)
20
20
10
Uni t ed A r ab
E mi r at es (b)
0
Uni t ed A r ab
10
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
Age groups
80+
38
Self Reported Level of Self care by Age Group, Female,
SEARO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale,
SEARO, WHO Health & Responsiveness Surveys, 2001
100
100
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
I ndi a (h)
90
I ndonesi a (h)
80
I ndonesi a (p)
T hai l and (p)
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
70-79
15-29
80+
30-44
45-59
100
60-69
70-79
80+
Age groups
Age groups
Self Reported Level of Self care by Age Group, Female,
EURO-C, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale, EUROC, WHO Health & Responsiveness Surveys, 2001
90
80
70
Hungar y (p)
100
Hungar y (p)
B ul gar i a (b)
90
B ul gar i a (b)
Cr oat i a (b)
80
Cr oat i a (b)
70
Cypr us (p)
60
Czech
Cypr us (p)
60
Czech
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29
80+
80+
Self Reported Level of Self care by Age Group, Female,
EURO-E, WHO Health & Responsiveness Surveys, 2001
E s t oni a (b)
90
60-69 70-79
Age groups
Self Reported Level of Self care by Age Group, M ale,
EURO-E, WHO Health & Responsiveness Surveys, 2001
100
30-44 45-59
Geor gi a (h)
80
100
E s t oni a (b)
90
Geor gi a (h)
80
K y r gy z s t an (p)
70
K y r gy z s t an (p)
70
Lat v i a (b)
60
Li t huani a (p)
50
50
Li t huani a (p)
40
Rus s i an
30
T ur k ey (h)
T ur k ey (p)
20
T ur k ey (p)
Uk r ai ne (p)
10
Uk r ai ne (p)
40
Rus s i an
30
T ur k ey (h)
20
10
Feder at i on (b)
0
Lat v i a (b)
60
Feder at i on (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44
45-59 60-69
70-79
80+
Age groups
39
Self Reported Level of Self care by Age Group, Female,
EURO-N, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale, EURON, WHO Healt h & Responsiveness Surveys, 2001
100
A ust r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
60
Ger many (b)
50
I cel and (b)
100
A ust r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
60
Ger many (b)
50
I cel and (b)
40
40
Net her l ands
Net her l ands
(b)
30
(b)
30
Net her l ands
Net her l ands
20
(p)
20
(p)
Sweden (b)
Sweden (b)
10
10
Swi t zer l and
Swi t zer l and
15-29 30-44 45-59 60-69 70-79
Age groups
(p)
0
(p)
0
15-29 30-44 45-59 60-69 70-79
Age groups
80+
80+
Self Reported Level of Self care by Age Group, Female,
EURO-W, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale, EUROW, WHO Health & Responsiveness Surveys, 2001
100
100
B el gi um (b)
B el gi um (b)
90
90
Fr anc e (b)
Fr anc e (b)
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
30-44 45-59 60-69 70-79
80
Fr anc e (p)
70
Gr eec e (p)
60
I r el and (b)
50
I t al y (b)
40
Lux embour g (t )
30
P or t ugal (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
80+
30-44 45-59
60-69 70-79
80+
Age groups
Age groups
Self Reported Level of Self care by Age Group, Female,
WPRO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Self care by Age Group, M ale,
WPRO, WHO Health & Responsiveness Surveys, 2001
100
100
A ust r al i a (p)
90
Chi na (p)
80
Newzeal and (p)
Republ i c of K or ea (p)
70
A ust r al i a (p)
90
Chi na (h)
Chi na (h)
80
Chi na (p)
70
Republ i c of K or ea (p)
Newzeal and (p)
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
Age groups
70-79
80+
15-29
30-44
45-59
60-69
70-79
80+
Age groups
40
Figure 16: Level of Health, Usual Activities: Comparison of Age groups, Surveys grouped by
Region, Male and Female
Self Reported Level of Usual Activities by Age Group,
AFRO, WHO Health & Responsiveness Surveys, 2001
100
male, Nigeria(h)
female,Nigeria(h)
90
80
70
60
50
40
30
20
10
0
15-29
30-44
45-59
60-69
70-79
80+
Age groups
Self Reported Level of Usual activities by Age Group, Female,
AM RO, WHO Health & Responsiveness Surveys, 2001
Self Reported Level of Usual activities by Age Group, M ale,
AM RO, WHO Health & Responsiveness Surveys, 2001
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i co (h)
30
T r i ni dad and
T obago (p)
20
Uni t ed St at es
(p)
10
V enezuel a (b)
100
A r gent i na (b)
90
Canada (p)
80
Canada (t )
70
Chi l e (p)
60
Col ombi a (h)
50
Cos t a Ri c a (b)
40
M ex i co (h)
30
T r i ni dad and
T obago (p)
20
Uni t ed St at es (p)
10
V enezuel a (b)
0
0
15-29
30-44 45-59 60-69 70-79
Age groups
15-29 30-44 45-59 60-69 70-79
80+
80+
Age groups
Self Reported Level of Usual activities by Age Group, M ale,
EM RO, WHO Health & Responsiveness Surveys, 2001
100
B ahr ai n (b)
90
100
Self Reported Level of Usual activities by Age Group,
Female, EM RO, WHO Health & Responsiveness Surveys,
2001
B ahr ai n (b)
90
E gypt (h)
80
70
E gypt (p)
60
E gypt (h)
80
70
E gypt (p)
60
Jor dan (b)
50
40
M or occo (b)
30
Oman (b)
20
Jor dan (b)
50
40
M or occo (b)
30
Oman (b)
20
10
Uni t ed A r ab
E mi r at es (b)
0
Uni t ed A r ab
10
E mi r at es (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44 45-59 60-69 70-79
Age groups
80+
41
Self Reported Level of Usual activities by Age Group, M ale,
SEARO, WHO Health & Responsiveness Surveys, 2001
100
100
I ndi a (h)
90
80
I ndonesi a (h)
90
I ndonesi a (p)
80
Self Reported Level of Usual activities by Age Group,
Female, SEARO, WHO Health & Responsiveness Surveys,
2001
I ndi a (h)
I ndonesi a (h)
I ndonesi a (p)
T hai l and (p)
70
T hai l and (p)
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
15-29
30-44
45-59
60-69
70-79
15-29
80+
30-44
45-59
100
60-69
70-79
80+
Age groups
Age groups
Self Reported Level of Usual activities by Age Group, M ale,
EURO-C, WHO Health & Responsiveness Surveys, 2001
90
80
Hungar y (p)
100
B ul gar i a (b)
90
B ul gar i a (b)
80
Cr oat i a (b)
70
Cypr us (p)
60
Czech
Cr oat i a (b)
70
Cypr us (p)
60
Czech
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Self Reported Level of Usual activities by Age Group,
Female, EURO-C, WHO Health & Responsiveness Surveys,
2001
Republ i c (b)
50
Czech
Republ i c (p)
40
M al t a (b)
30
P ol and (p)
20
Romani a (b)
10
Sl ovaki a (h)
Romani a (b)
10
Sl ovaki a (h)
0
15-29
30-44 45-59 60-69 70-79
Age groups
0
15-29
80+
E s t oni a (b)
90
30-44 45-59
60-69 70-79
80+
Age groups
Self Reported Level of Usual activities by Age Group, M ale,
EURO-E, WHO Health & Responsiveness Surveys, 2001
100
Hungar y (p)
Geor gi a (h)
80
100
Self Reported Level of Usual activities by Age Group,
Female, EURO-E, WHO Health & Responsiveness Surveys,
2001
E s t oni a (b)
90
Geor gi a (h)
80
K y r gy z s t an (p)
70
K y r gy z s t an (p)
70
Lat v i a (b)
60
Li t huani a (p)
50
50
Li t huani a (p)
40
Rus s i an
30
T ur k ey (h)
T ur k ey (p)
20
T ur k ey (p)
Uk r ai ne (p)
10
Uk r ai ne (p)
40
Rus s i an
30
T ur k ey (h)
20
10
Feder at i on (b)
0
Lat v i a (b)
60
Feder at i on (b)
0
15-29
30-44 45-59 60-69 70-79
Age groups
80+
15-29
30-44
45-59 60-69
70-79
80+
Age groups
42
Self Reported Level of Usual activities by A ge Group, M ale,
EURO-N, WHO Health & Responsiveness Surveys, 2001
100
A ust r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
60
Ger many (b)
50
I cel and (b)
40
Net her l ands
(b)
30
Net her l ands
(p)
20
Sweden (b)
10
Swi t zer l and
100
A ust r i a (p)
90
Denmar k (p)
80
Fi nl and (b)
70
Fi nl and (p)
60
Ger many (b)
50
I cel and (b)
40
Net her l ands
30
(b)
20
(p)
Net her l ands
Sweden (b)
10
(p)
Swi t zer l and
(p)
0
0
15-29 30-44 45-59 60-69 70-79
Age groups
Self Reported Level of Usual Activities by Age Group,
Female, EURO-N, WHO Healt h & Responsiveness Surveys,
2001
15-29 30-44 45-59 60-69 70-79
Age groups
80+
Self Reported Level of Usual activities by Age Group, M ale,
EURO-W, WHO Health & Responsiveness Surveys, 2001
100
B el gi um (b)
90
100
80+
Self Reported Level of Usual activities by Age Group,
Female, EURO-W, WHO Health & Responsiveness Surveys,
2001
B el gi um (b)
Fr anc e (b)
90
Fr anc e (b)
80
Fr anc e (p)
80
Fr anc e (p)
70
Gr eec e (p)
70
Gr eec e (p)
60
I r el and (b)
60
I r el and (b)
50
I t al y (b)
50
I t al y (b)
40
Lux embour g (t )
40
Lux embour g (t )
30
P or t ugal (b)
30
P or t ugal (b)
20
Spai n (b)
20
Spai n (b)
10
Uni t ed
K i ngdom (p)
0
15-29
30-44 45-59 60-69 70-79
10
Uni t ed
K i ngdom (p)
0
15-29
80+
30-44 45-59
Self Reported Level of Usual activities by Age Group, M ale,
WPRO, WHO Health & Responsiveness Surveys, 2001
100
100
90
90
80
80
70
70
60
60
50
50
40
40
Chi na (h)
A ust r al i a (p)
Chi na (h)
20
Chi na (p)
Newzeal and (p)
10
Self Reported Level of Usual activities by Age Group,
Female, WPRO, WHO Health & Responsiveness Surveys,
2001
30
A ust r al i a (p)
20
80+
Age groups
Age groups
30
60-69 70-79
Chi na (p)
Newzeal and (p)
10
Republ i c of K or ea (p)
Republ i c of K or ea (p)
0
0
15-29
30-44
45-59
60-69
Age groups
70-79
80+
15-29
30-44
45-59
60-69
70-79
80+
Age groups
43
Table 4. Average level of health by domain, age-standardized, 66 surveys, WHO Multi-Country Survey Study on Health and Responsiveness, 2000-2001
Affect
Survey
Argentina brief
Australia postal
Austria postal
Bahrain brief
Belgium brief
Bulgaria brief
Canada postal
Canada telephone
Chile postal
China household
China postal
Columbia household
Costa Rica brief
Croatia brief
Cyprus postal
Czech Republic brief
Czech Republic postal
Denmark postal
Egypt household
Egypt postal
Estonia brief
Finland brief
Finland postal
France brief
France postal
Georgia household
Germany brief
Greece postal
Hungary postal
Iceland brief
India household
Indonesia household
Indonesia postal
Cognition
Males
Females
59.22
73.92
67.69
71.98
87.66
69.01
73.73
68.04
71.21
82.64
64.85
65.57
56.55
53.36
56.84
71.73
67.80
84.75
83.28
59.05
65.40
83.91
72.18
83.10
78.62
63.16
87.91
62.47
52.95
77.63
78.83
95.47
72.54
49.53
71.20
67.65
63.32
79.23
61.20
67.20
67.34
61.61
76.64
60.27
56.92
57.17
47.25
48.27
71.03
57.57
76.82
76.72
50.30
57.53
77.94
64.59
75.99
71.06
55.73
82.02
58.45
51.93
72.22
72.15
90.83
65.51
Males
Mobility
Females
66.01
59.13
43.40
53.42
73.72
67.12
62.54
57.67
58.86
58.07
51.76
64.41
48.20
53.07
52.91
64.72
56.72
66.24
75.60
33.78
65.38
78.14
66.85
70.65
49.04
74.70
80.74
61.49
54.47
55.30
63.56
78.57
38.42
56.87
57.06
42.59
43.00
66.99
60.10
58.89
60.29
51.96
49.89
50.35
54.39
48.48
45.51
45.01
62.32
51.31
59.96
65.92
26.31
58.34
73.84
63.66
63.06
48.11
65.89
75.15
55.95
52.01
49.49
53.15
70.50
32.92
Males
Pain
Females
66.98
66.29
58.39
57.35
64.70
69.97
58.47
66.31
62.84
73.10
65.32
68.84
58.64
48.01
71.37
47.25
44.23
75.36
51.93
43.38
62.37
63.09
68.66
78.43
75.88
58.03
64.31
76.11
47.46
57.30
51.48
86.17
87.28
59.77
61.62
53.70
48.81
57.43
62.56
53.21
64.89
54.63
65.89
62.30
62.16
59.00
40.95
66.89
44.26
40.60
69.67
42.21
36.05
56.76
58.74
65.60
71.38
68.38
50.62
58.31
71.42
44.63
49.80
42.28
79.98
83.53
Self Care
Males
Females
60.09
65.73
43.18
76.43
64.60
60.46
58.41
68.99
63.12
80.49
73.57
59.21
47.85
46.13
40.55
59.50
54.18
57.75
69.70
44.02
54.19
67.53
54.60
72.99
69.02
59.77
75.63
66.94
48.91
61.12
71.36
70.48
26.82
51.29
63.00
39.93
63.21
54.59
54.30
51.30
66.52
55.79
72.75
66.48
50.71
47.64
39.42
31.11
57.44
48.09
50.90
60.75
35.63
46.05
61.75
49.22
64.24
59.82
52.29
67.97
59.75
45.93
54.58
60.84
63.11
21.09
Males
Usual Activities
Females
75.85
75.36
58.15
49.81
64.39
61.25
65.86
82.43
47.76
70.30
85.85
67.60
58.09
47.88
65.69
66.68
46.06
64.87
45.73
22.62
70.20
83.55
69.14
73.87
65.48
44.88
71.53
76.95
50.95
84.48
42.37
71.71
32.76
71.00
71.50
55.03
44.72
59.34
56.76
62.55
80.38
43.06
64.50
82.77
62.85
55.76
42.64
61.51
63.44
43.46
60.69
39.41
19.43
65.66
80.72
67.00
68.88
60.45
40.83
66.57
73.83
47.81
78.95
33.99
66.26
29.15
Males
Females
82.04
73.09
61.60
52.89
64.02
59.27
65.63
70.65
58.50
59.76
65.95
75.28
65.65
50.87
57.74
62.34
44.88
69.42
55.93
43.66
63.68
76.64
64.75
80.05
67.19
57.54
68.95
67.14
52.56
70.02
58.97
78.20
48.89
74.55
68.46
57.52
43.02
56.58
51.89
61.33
67.86
52.26
53.76
63.49
69.34
64.92
45.53
51.55
61.54
41.16
62.35
47.14
35.24
58.88
71.72
61.35
72.10
60.96
51.83
62.95
61.82
49.96
61.90
49.39
72.44
44.19
(continued)
44
Table 4. Average level of health by domain, age-standardized, 66 surveys, WHO Multi-Country Survey Study on Health and Responsiveness, 2000-2001 (continued)
Affect
Survey
Ireland brief
Italy brief
Jordan brief
Kyrgyzstan postal
Latvia brief
Lithuania postal
Luxembourg telephone
Malta brief
Mexico household
Morocco brief
Netherlands brief
Netherlands postal
New Zealand postal
Nigeria household
Oman brief
Poland postal
Portugal brief
Republic of Korea postal
Romania brief
Russian Federation brief
Slovakia household
Spain brief
Sweden brief
Switzerland postal
Thailand postal
Trinidad and Tobago postal
Turkey household
Turkey postal
Ukraine postal
United Arab Emirates brief
United Kingdom postal
United States postal
Venezuela brief
Cognition
Males
Females
93.90
84.79
62.58
26.95
47.90
54.62
87.79
81.56
86.08
60.99
77.32
81.91
77.11
86.94
72.46
54.48
74.96
59.24
54.86
65.75
76.88
86.59
83.41
79.29
81.68
68.92
68.68
32.07
44.46
75.25
72.41
74.18
63.99
88.01
76.50
55.17
19.56
48.13
43.76
80.28
76.33
78.85
46.44
67.83
74.82
69.62
83.55
67.78
48.13
64.14
54.63
42.30
57.89
69.22
79.16
77.56
76.82
72.78
61.25
62.14
27.02
35.29
68.67
65.92
66.95
65.89
Males
Mobility
Females
91.87
66.44
44.46
21.72
58.63
32.07
77.37
58.02
81.83
37.76
64.07
58.13
51.75
90.34
47.10
42.80
52.18
45.01
56.88
83.38
67.69
85.09
62.94
54.82
37.67
25.26
61.75
25.26
40.99
61.29
59.40
55.58
48.97
86.22
57.90
35.25
16.92
57.93
25.92
71.05
52.63
73.12
23.24
57.76
52.40
46.60
86.58
42.08
36.26
41.13
36.77
45.05
77.27
61.24
75.75
58.83
49.81
30.94
19.58
53.51
19.58
35.04
55.98
56.02
48.13
51.03
Males
Pain
Females
76.36
80.54
48.89
15.55
53.39
36.30
79.13
61.58
76.11
49.59
51.41
55.59
67.88
69.04
58.67
52.08
58.13
55.92
50.15
51.99
48.79
79.27
58.75
68.59
50.92
58.01
64.17
44.50
46.11
58.48
70.79
60.45
56.32
71.11
72.54
39.10
12.58
51.59
30.86
71.14
54.61
68.56
31.30
44.00
48.63
63.04
62.95
52.12
46.50
48.94
47.10
40.92
45.07
41.52
71.93
52.65
65.85
43.11
51.25
56.18
37.07
38.76
55.59
66.32
54.71
55.24
Self
Males
Females
83.59
78.67
67.32
20.57
51.95
35.95
66.29
65.69
78.04
52.61
48.91
56.41
67.47
79.45
77.53
41.49
61.65
22.33
50.06
56.15
58.75
84.04
61.74
60.74
65.15
61.71
62.76
34.00
38.10
83.55
60.19
51.81
68.15
76.69
68.59
58.39
13.96
52.05
28.57
56.44
59.43
69.96
38.42
41.07
50.27
61.31
76.19
71.70
35.55
51.66
20.78
39.69
48.13
51.23
75.47
55.66
58.88
54.92
54.59
54.20
25.71
32.00
79.67
52.51
45.95
68.28
Usual
Males
Females
86.06
75.73
41.59
11.17
52.03
31.90
89.24
66.85
73.34
29.13
59.23
78.56
63.22
87.81
52.75
40.64
55.27
38.95
48.65
50.80
52.65
78.46
84.49
80.71
40.34
43.39
52.51
22.43
28.30
53.74
65.48
56.84
55.45
82.46
71.06
34.93
9.64
49.10
29.33
85.40
61.73
67.75
22.93
53.20
72.03
59.49
83.61
50.39
36.61
49.11
33.62
42.57
46.66
48.52
72.76
81.51
80.13
34.88
39.34
47.88
18.80
25.23
53.63
61.75
51.73
52.52
Males
Females
82.78
69.88
50.73
25.28
43.25
40.05
82.17
68.93
81.85
41.66
58.35
66.34
64.61
88.76
52.19
42.63
57.73
58.94
47.26
51.29
53.89
82.88
66.28
68.72
50.65
55.90
62.93
27.87
27.20
61.26
69.65
71.03
65.63
76.73
61.51
41.07
20.52
43.41
35.80
75.40
62.37
75.48
27.51
49.46
58.26
58.66
86.46
44.96
38.84
48.53
50.04
38.19
43.25
47.45
74.94
59.90
67.31
43.69
51.23
55.96
21.62
22.03
57.26
65.19
65.20
64.77
45
Table 5. Average level of AFFECT, age-standardized, 66 surveys, 2000-2001
Survey
Indonesia household
Ireland brief
Nigeria household
Germany brief
Luxembourg telephone
Belgium brief
Spain brief
Mexico household
Finland brief
Denmark postal
Italy brief
Sweden brief
Egypt household
China household
France brief
Malta brief
Netherlands postal
Switzerland postal
Thailand postal
India household
Iceland brief
France postal
New Zealand postal
Slovakia household
Netherlands brief
Australia postal
United Arab Emirates brief
Czech Republic brief
United States postal
Canada postal
Oman brief
Portugal brief
United Kingdom postal
Indonesia postal
Finland postal
Canada telephone
Austria postal
Bahrain brief
Chile postal
Turkey household
Bulgaria brief
Trinidad and Tobago postal
Venezuela brief
Czech Republic postal
China postal
Russian Federation brief
Estonia brief
Columbia household
Greece postal
Georgia household
Jordan brief
Republic of Korea postal
Costa Rica brief
Egypt postal
Argentina brief
Morocco brief
Cyprus postal
Hungary postal
Poland postal
Croatia brief
Lithuania postal
Romania brief
Latvia brief
Ukraine postal
Turkey postal
Kyrgyzstan postal
Males
Females
95.5
93.9
86.9
87.9
87.8
87.7
86.6
86.1
83.9
84.8
84.8
83.4
83.3
82.6
83.1
81.6
81.9
79.3
81.7
78.8
77.6
78.6
77.1
76.9
77.3
73.9
75.3
71.7
74.2
73.7
72.5
75.0
72.4
72.5
72.2
68.0
67.7
72.0
71.2
68.7
69.0
68.9
64.0
67.8
64.9
65.7
65.4
65.6
62.5
63.2
62.6
59.2
56.6
59.1
59.2
61.0
56.8
53.0
54.5
53.4
54.6
54.9
47.9
44.5
32.1
27.0
90.8
88.0
83.5
82.0
80.3
79.2
79.2
78.8
77.9
76.8
76.5
77.6
76.7
76.6
76.0
76.3
74.8
76.8
72.8
72.1
72.2
71.1
69.6
69.2
67.8
71.2
68.7
71.0
67.0
67.2
67.8
64.1
65.9
65.5
64.6
67.3
67.6
63.3
61.6
62.1
61.2
61.2
65.9
57.6
60.3
57.9
57.5
56.9
58.5
55.7
55.2
54.6
57.2
50.3
49.5
46.4
48.3
51.9
48.1
47.2
43.8
42.3
48.1
35.3
27.0
19.6
M F Average M/F Ratio
93.1
1.05
91.0
1.07
85.2
1.04
85.0
1.07
84.0
1.09
83.4
1.11
82.9
1.09
82.5
1.09
80.9
1.08
80.8
1.10
80.6
1.11
80.5
1.08
80.0
1.09
79.6
1.08
79.5
1.09
78.9
1.07
78.4
1.09
78.1
1.03
77.2
1.12
75.5
1.09
74.9
1.07
74.8
1.11
73.4
1.11
73.1
1.11
72.6
1.14
72.6
1.04
72.0
1.10
71.4
1.01
70.6
1.11
70.5
1.10
70.1
1.07
69.6
1.17
69.2
1.10
69.0
1.11
68.4
1.12
67.7
1.01
67.7
1.00
67.7
1.14
66.4
1.16
65.4
1.11
65.1
1.13
65.1
1.13
64.9
0.97
62.7
1.18
62.6
1.08
61.8
1.14
61.5
1.14
61.2
1.15
60.5
1.07
59.4
1.13
58.9
1.13
56.9
1.08
56.9
0.99
54.7
1.17
54.4
1.20
53.7
1.31
52.6
1.18
52.4
1.02
51.3
1.13
50.3
1.13
49.2
1.25
48.6
1.30
48.0
1.00
39.9
1.26
29.5
1.19
23.3
1.38
47
Table 6. Average level of COGNITION, age-standardized, 66 surveys, 2000-2001
Survey
Ireland brief
Nigeria household
Spain brief
Russian Federation brief
Germany brief
Mexico household
Finland brief
Indonesia household
Luxembourg telephone
Egypt household
Belgium brief
Georgia household
France brief
Finland postal
Slovakia household
Bulgaria brief
Czech Republic brief
Denmark postal
Italy brief
Estonia brief
Argentina brief
Netherlands brief
Sweden brief
Canada postal
Columbia household
Canada telephone
Greece postal
United Arab Emirates brief
India household
Latvia brief
Australia postal
United Kingdom postal
Turkey household
Chile postal
Malta brief
Netherlands postal
Czech Republic postal
China household
Hungary postal
Iceland brief
Switzerland postal
United States postal
China postal
Romania brief
Venezuela brief
Croatia brief
New Zealand postal
Cyprus postal
France postal
Costa Rica brief
Bahrain brief
Portugal brief
Oman brief
Austria postal
Republic of Korea postal
Jordan brief
Poland postal
Ukraine postal
Indonesia postal
Thailand postal
Morocco brief
Egypt postal
Lithuania postal
Trinidad and Tobago postal
Turkey postal
Kyrgyzstan postal
Males
Females
91.9
90.3
85.1
83.4
80.7
81.8
78.1
78.6
77.4
75.6
73.7
74.7
70.7
66.8
67.7
67.1
64.7
66.2
66.4
65.4
66.0
64.1
62.9
62.5
64.4
57.7
61.5
61.3
63.6
58.6
59.1
59.4
61.8
58.9
58.0
58.1
56.7
58.1
54.5
55.3
54.8
55.6
51.8
56.9
49.0
53.1
51.7
52.9
49.0
48.2
53.4
52.2
47.1
43.4
45.0
44.5
42.8
41.0
38.4
37.7
37.8
33.8
32.1
25.3
25.3
21.7
86.2
86.6
75.7
77.3
75.2
73.1
73.8
70.5
71.0
65.9
67.0
65.9
63.1
63.7
61.2
60.1
62.3
60.0
57.9
58.3
56.9
57.8
58.8
58.9
54.4
60.3
55.9
56.0
53.1
57.9
57.1
56.0
53.5
52.0
52.6
52.4
51.3
49.9
52.0
49.5
49.8
48.1
50.4
45.1
51.0
45.5
46.6
45.0
48.1
48.5
43.0
41.1
42.1
42.6
36.8
35.2
36.3
35.0
32.9
30.9
23.2
26.3
25.9
19.6
19.6
16.9
M F Average M/F Ratio
89.0
1.07
88.5
1.04
80.4
1.12
80.3
1.08
77.9
1.07
77.5
1.12
76.0
1.06
74.5
1.11
74.2
1.09
70.8
1.15
70.4
1.10
70.3
1.13
66.9
1.12
65.3
1.05
64.5
1.11
63.6
1.12
63.5
1.04
63.1
1.10
62.2
1.15
61.9
1.12
61.4
1.16
60.9
1.11
60.9
1.07
60.7
1.06
59.4
1.18
59.0
0.96
58.7
1.10
58.6
1.09
58.4
1.20
58.3
1.01
58.1
1.04
57.7
1.06
57.6
1.15
55.4
1.13
55.3
1.10
55.3
1.11
54.0
1.11
54.0
1.16
53.2
1.05
52.4
1.12
52.3
1.10
51.9
1.15
51.1
1.03
51.0
1.26
50.0
0.96
49.3
1.17
49.2
1.11
49.0
1.18
48.6
1.02
48.3
0.99
48.2
1.24
46.7
1.27
44.6
1.12
43.0
1.02
40.9
1.22
39.9
1.26
39.5
1.18
38.0
1.17
35.7
1.17
34.3
1.22
30.5
1.63
30.0
1.28
29.0
1.24
22.4
1.29
22.4
1.29
19.3
1.28
48
Table 7. Average level of MOBILITY, age-standardized, 66 surveys, 2000-2001
Survey
Indonesia postal
Indonesia household
Italy brief
Spain brief
Luxembourg telephone
France brief
Greece postal
Ireland brief
Denmark postal
Mexico household
France postal
China household
Cyprus postal
United Kingdom postal
Switzerland postal
Finland postal
Bulgaria brief
Nigeria household
Canada telephone
Columbia household
New Zealand postal
Australia postal
China postal
Argentina brief
Germany brief
Belgium brief
Finland brief
Turkey household
Estonia brief
Costa Rica brief
Chile postal
Malta brief
United States postal
United Arab Emirates brief
Austria postal
Canada postal
Venezuela brief
Sweden brief
Oman brief
Trinidad and Tobago postal
Georgia household
Iceland brief
Portugal brief
Bahrain brief
Latvia brief
Netherlands postal
Republic of Korea postal
Poland postal
Russian Federation brief
Netherlands brief
Egypt household
Thailand postal
India household
Hungary postal
Czech Republic brief
Romania brief
Slovakia household
Croatia brief
Jordan brief
Ukraine postal
Czech Republic postal
Turkey postal
Morocco brief
Egypt postal
Lithuania postal
Kyrgyzstan postal
Males
Females
87.3
86.2
80.5
79.3
79.1
78.4
76.1
76.4
75.4
76.1
75.9
73.1
71.4
70.8
68.6
68.7
70.0
69.0
66.3
68.8
67.9
66.3
65.3
67.0
64.3
64.7
63.1
64.2
62.4
58.6
62.8
61.6
60.4
58.5
58.4
58.5
56.3
58.8
58.7
58.0
58.0
57.3
58.1
57.3
53.4
55.6
55.9
52.1
52.0
51.4
51.9
50.9
51.5
47.5
47.3
50.1
48.8
48.0
48.9
46.1
44.2
44.5
49.6
43.4
36.3
15.6
83.5
80.0
72.5
71.9
71.1
71.4
71.4
71.1
69.7
68.6
68.4
65.9
66.9
66.3
65.9
65.6
62.6
63.0
64.9
62.2
63.0
61.6
62.3
59.8
58.3
57.4
58.7
56.2
56.8
59.0
54.6
54.6
54.7
55.6
53.7
53.2
55.2
52.6
52.1
51.3
50.6
49.8
48.9
48.8
51.6
48.6
47.1
46.5
45.1
44.0
42.2
43.1
42.3
44.6
44.3
40.9
41.5
40.9
39.1
38.8
40.6
37.1
31.3
36.0
30.9
12.6
M F Average M/F Ratio
85.4
1.04
83.1
1.08
76.5
1.11
75.6
1.10
75.1
1.11
74.9
1.10
73.8
1.07
73.7
1.07
72.5
1.08
72.3
1.11
72.1
1.11
69.5
1.11
69.1
1.07
68.6
1.07
67.2
1.04
67.1
1.05
66.3
1.12
66.0
1.10
65.6
1.02
65.5
1.11
65.5
1.08
64.0
1.08
63.8
1.05
63.4
1.12
61.3
1.10
61.1
1.13
60.9
1.07
60.2
1.14
59.6
1.10
58.8
0.99
58.7
1.15
58.1
1.13
57.6
1.10
57.0
1.05
56.0
1.09
55.8
1.10
55.8
1.02
55.7
1.12
55.4
1.13
54.6
1.13
54.3
1.15
53.5
1.15
53.5
1.19
53.1
1.17
52.5
1.03
52.1
1.14
51.5
1.19
49.3
1.12
48.5
1.15
47.7
1.17
47.1
1.23
47.0
1.18
46.9
1.22
46.0
1.06
45.8
1.07
45.5
1.23
45.2
1.18
44.5
1.17
44.0
1.25
42.4
1.19
42.4
1.09
40.8
1.20
40.4
1.58
39.7
1.20
33.6
1.18
14.1
1.24
49
Table 8. Average level of PAIN, age-standardized, 66 surveys, 2000-2001
Survey
United Arab Emirates brief
Ireland brief
Spain brief
Nigeria household
China household
Oman brief
Mexico household
Italy brief
Germany brief
China postal
Bahrain brief
France brief
Venezuela brief
Canada telephone
Indonesia household
India household
Egypt household
Finland brief
France postal
New Zealand postal
Australia postal
Greece postal
Jordan brief
Malta brief
Luxembourg telephone
Thailand postal
Switzerland postal
Belgium brief
Chile postal
Sweden brief
Turkey household
Czech Republic brief
Trinidad and Tobago postal
Iceland brief
Bulgaria brief
Portugal brief
United Kingdom postal
Georgia household
Argentina brief
Slovakia household
Columbia household
Canada postal
Denmark postal
Netherlands postal
Russian Federation brief
Latvia brief
Finland postal
Czech Republic postal
Estonia brief
United States postal
Costa Rica brief
Hungary postal
Morocco brief
Netherlands brief
Romania brief
Croatia brief
Austria postal
Egypt postal
Poland postal
Cyprus postal
Ukraine postal
Lithuania postal
Turkey postal
Indonesia postal
Republic of Korea postal
Kyrgyzstan postal
Males
Females
83.6
83.6
84.0
79.4
80.5
77.5
78.0
78.7
75.6
73.6
76.4
73.0
68.2
69.0
70.5
71.4
69.7
67.5
69.0
67.5
65.7
66.9
67.3
65.7
66.3
65.2
60.7
64.6
63.1
61.7
62.8
59.5
61.7
61.1
60.5
61.6
60.2
59.8
60.1
58.7
59.2
58.4
57.7
56.4
56.2
51.9
54.6
54.2
54.2
51.8
47.8
48.9
52.6
48.9
50.1
46.1
43.2
44.0
41.5
40.6
38.1
36.0
34.0
26.8
22.3
20.6
79.7
76.7
75.5
76.2
72.7
71.7
70.0
68.6
68.0
66.5
63.2
64.2
68.3
66.5
63.1
60.8
60.8
61.8
59.8
61.3
63.0
59.8
58.4
59.4
56.4
54.9
58.9
54.6
55.8
55.7
54.2
57.4
54.6
54.6
54.3
51.7
52.5
52.3
51.3
51.2
50.7
51.3
50.9
50.3
48.1
52.0
49.2
48.1
46.1
45.9
47.6
45.9
38.4
41.1
39.7
39.4
39.9
35.6
35.5
31.1
32.0
28.6
25.7
21.1
20.8
14.0
M F Average M/F Ratio
81.6
1.05
80.1
1.09
79.8
1.11
77.8
1.04
76.6
1.11
74.6
1.08
74.0
1.12
73.6
1.15
71.8
1.11
70.0
1.11
69.8
1.21
68.6
1.14
68.2
1.00
67.8
1.04
66.8
1.12
66.1
1.17
65.2
1.15
64.6
1.09
64.4
1.15
64.4
1.10
64.4
1.04
63.3
1.12
62.9
1.15
62.6
1.11
61.4
1.17
60.0
1.19
59.8
1.03
59.6
1.18
59.5
1.13
58.7
1.11
58.5
1.16
58.5
1.04
58.2
1.13
57.8
1.12
57.4
1.11
56.7
1.19
56.3
1.15
56.0
1.14
55.7
1.17
55.0
1.15
55.0
1.17
54.9
1.14
54.3
1.13
53.3
1.12
52.1
1.17
52.0
1.00
51.9
1.11
51.1
1.13
50.1
1.18
48.9
1.13
47.7
1.00
47.4
1.06
45.5
1.37
45.0
1.19
44.9
1.26
42.8
1.17
41.6
1.08
39.8
1.24
38.5
1.17
35.8
1.30
35.0
1.19
32.3
1.26
29.9
1.32
24.0
1.27
21.6
1.07
17.3
1.47
50
Table 9. Average level of Self Care, age-standardized, 66 surveys, 2000-2001
Survey
Luxembourg telephone
Nigeria household
China postal
Ireland brief
Sweden brief
Finland brief
Iceland brief
Canada telephone
Switzerland postal
Spain brief
Greece postal
Netherlands postal
Australia postal
Argentina brief
Italy brief
France brief
Mexico household
Germany brief
Indonesia household
Finland postal
Estonia brief
China household
Columbia household
Czech Republic brief
Malta brief
Canada postal
United Kingdom postal
Cyprus postal
France postal
Denmark postal
Belgium brief
New Zealand postal
Bulgaria brief
Costa Rica brief
Austria postal
Netherlands brief
United States postal
Venezuela brief
United Arab Emirates brief
Portugal brief
Oman brief
Slovakia household
Latvia brief
Turkey household
Hungary postal
Russian Federation brief
Bahrain brief
Romania brief
Chile postal
Croatia brief
Czech Republic postal
Georgia household
Egypt household
Trinidad and Tobago postal
Poland postal
Jordan brief
India household
Thailand postal
Republic of Korea postal
Indonesia postal
Lithuania postal
Ukraine postal
Morocco brief
Egypt postal
Turkey postal
Kyrgyzstan postal
Males
Females
89.2
87.8
85.8
86.1
84.5
83.5
84.5
82.4
80.7
78.5
76.9
78.6
75.4
75.8
75.7
73.9
73.3
71.5
71.7
69.1
70.2
70.3
67.6
66.7
66.8
65.9
65.5
65.7
65.5
64.9
64.4
63.2
61.2
58.1
58.1
59.2
56.8
55.5
53.7
55.3
52.8
52.6
52.0
52.5
51.0
50.8
49.8
48.7
47.8
47.9
46.1
44.9
45.7
43.4
40.6
41.6
42.4
40.3
39.0
32.8
31.9
28.3
29.1
22.6
22.4
11.2
85.4
83.6
82.8
82.5
81.5
80.7
78.9
80.4
80.1
72.8
73.8
72.0
71.5
71.0
71.1
68.9
67.7
66.6
66.3
67.0
65.7
64.5
62.8
63.4
61.7
62.6
61.7
61.5
60.4
60.7
59.3
59.5
56.8
55.8
55.0
53.2
51.7
52.5
53.6
49.1
50.4
48.5
49.1
47.9
47.8
46.7
44.7
42.6
43.1
42.6
43.5
40.8
39.4
39.3
36.6
34.9
34.0
34.9
33.6
29.1
29.3
25.2
22.9
19.4
18.8
9.6
M F Average M/F Ratio
87.3
1.04
85.7
1.05
84.3
1.04
84.3
1.04
83.0
1.04
82.1
1.04
81.7
1.07
81.4
1.03
80.4
1.01
75.6
1.08
75.4
1.04
75.3
1.09
73.4
1.05
73.4
1.07
73.4
1.07
71.4
1.07
70.5
1.08
69.0
1.07
69.0
1.08
68.1
1.03
67.9
1.07
67.4
1.09
65.2
1.08
65.1
1.05
64.3
1.08
64.2
1.05
63.6
1.06
63.6
1.07
63.0
1.08
62.8
1.07
61.9
1.09
61.4
1.06
59.0
1.08
56.9
1.04
56.6
1.06
56.2
1.11
54.3
1.10
54.0
1.06
53.7
1.00
52.2
1.13
51.6
1.05
50.6
1.09
50.6
1.06
50.2
1.10
49.4
1.07
48.7
1.09
47.3
1.11
45.6
1.14
45.4
1.11
45.3
1.12
44.8
1.06
42.9
1.10
42.6
1.16
41.4
1.10
38.6
1.11
38.3
1.19
38.2
1.25
37.6
1.16
36.3
1.16
31.0
1.12
30.6
1.09
26.8
1.12
26.0
1.27
21.0
1.16
20.6
1.19
10.4
1.16
51
Table 10. Average level of Usual Activities, age-standardized, 66 surveys, 2000-2001
Survey
Nigeria household
Ireland brief
Spain brief
Luxembourg telephone
Mexico household
Argentina brief
France brief
Indonesia household
Finland brief
Columbia household
Australia postal
Canada telephone
United States postal
Switzerland postal
United Kingdom postal
Iceland brief
Germany brief
Denmark postal
Italy brief
Malta brief
Costa Rica brief
Venezuela brief
China postal
Greece postal
France postal
Canada postal
Sweden brief
Finland postal
Netherlands postal
Czech Republic brief
New Zealand postal
Estonia brief
Belgium brief
Austria postal
Turkey household
United Arab Emirates brief
China household
Bulgaria brief
Chile postal
Georgia household
Cyprus postal
Republic of Korea postal
India household
Netherlands brief
Trinidad and Tobago postal
Portugal brief
Egypt household
Hungary postal
Slovakia household
Oman brief
Croatia brief
Bahrain brief
Russian Federation brief
Thailand postal
Indonesia postal
Jordan brief
Latvia brief
Czech Republic postal
Romania brief
Poland postal
Egypt postal
Lithuania postal
Morocco brief
Turkey postal
Ukraine postal
Kyrgyzstan postal
Males
Females
88.8
82.8
82.9
82.2
81.8
82.0
80.1
78.2
76.6
75.3
73.1
70.7
71.0
68.7
69.6
70.0
69.0
69.4
69.9
68.9
65.7
65.6
66.0
67.1
67.2
65.6
66.3
64.8
66.3
62.3
64.6
63.7
64.0
61.6
62.9
61.3
59.8
59.3
58.5
57.5
57.7
58.9
59.0
58.3
55.9
57.7
55.9
52.6
53.9
52.2
50.9
52.9
51.3
50.7
48.9
50.7
43.2
44.9
47.3
42.6
43.7
40.0
41.7
27.9
27.2
25.3
86.5
76.7
74.9
75.4
75.5
74.6
72.1
72.4
71.7
69.3
68.5
67.9
65.2
67.3
65.2
61.9
62.9
62.3
61.5
62.4
64.9
64.8
63.5
61.8
61.0
61.3
59.9
61.4
58.3
61.5
58.7
58.9
56.6
57.5
56.0
57.3
53.8
51.9
52.3
51.8
51.6
50.0
49.4
49.5
51.2
48.5
47.1
50.0
47.5
45.0
45.5
43.0
43.2
43.7
44.2
41.1
43.4
41.2
38.2
38.8
35.2
35.8
27.5
21.6
22.0
20.5
M F Average M/F Ratio
87.6
1.03
79.8
1.08
78.9
1.11
78.8
1.09
78.7
1.08
78.3
1.10
76.1
1.11
75.3
1.08
74.2
1.07
72.3
1.09
70.8
1.07
69.3
1.04
68.1
1.09
68.0
1.02
67.4
1.07
66.0
1.13
66.0
1.10
65.9
1.11
65.7
1.14
65.7
1.11
65.3
1.01
65.2
1.01
64.7
1.04
64.5
1.09
64.1
1.10
63.5
1.07
63.1
1.11
63.1
1.06
62.3
1.14
61.9
1.01
61.6
1.10
61.3
1.08
60.3
1.13
59.6
1.07
59.4
1.12
59.3
1.07
56.8
1.11
55.6
1.14
55.4
1.12
54.7
1.11
54.6
1.12
54.5
1.18
54.2
1.19
53.9
1.18
53.6
1.09
53.1
1.19
51.5
1.19
51.3
1.05
50.7
1.14
48.6
1.16
48.2
1.12
48.0
1.23
47.3
1.19
47.2
1.16
46.5
1.11
45.9
1.23
43.3
1.00
43.0
1.09
42.7
1.24
40.7
1.10
39.5
1.24
37.9
1.12
34.6
1.51
24.7
1.29
24.6
1.23
22.9
1.23
52
Figure 17: Average Level of Health, age-standardized, 66 surveys: Affect
Average Level of Affect vs. Male/Female Ratio of
Affect, WHO Survey 2000-2001
Male vs. Female Self Report of Affect
WHO 2000 - 2001 Survey
1.6
100
1.5
Ratio of Male/Female
Females
90
80
70
60
50
40
30
20
10
0
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
0
100
20
Male Life Expectancy at birth (2000) vs.
Self Reported Affect
60
80
100
Female Life Expectancy at birth (2000) vs.
Self Reported Affect
World Standardized Population
World Standardized Population
100
100
90
90
80
Self Reported Affect
Self Reported Affect
40
Average Level for Males and Fem ales Com bined
Males
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Affect
Self Reported Affect
World Standardized Population
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000
15000
20000
25000
30000
35000
Per Capita GDP
53
Figure 18: Average Level of Health, age-standardized, 66 surveys: Cognition
Average Level of Cognition vs. Male/Female Ratio of
Cognition, WHO Survey 2000-2001
100
90
80
70
60
50
40
30
20
10
0
Ratio of Male/Female
1.6
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
100
0
20
Males
Self Reported Cognition
Self Reported Cognition
45
50
55
60
60
80
100
Female Life Expectancy at birth (2000) vs.
Self Reported Cognition
World Standardized Population
100
90
80
70
60
50
40
30
20
10
0
40
40
Average Level for Males and Females Combined
Male Life Expectancy at birth (2000) vs.
Self Reported Cognition
World Standardized Population
65
70
75
80
85
Life Expectancy at birth
100
90
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Cognition
World Standardized Population
Self Reported Cognition
Females
Male vs. Female Self Report of Cognition
WHO 2000 - 2001 Survey
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000 15000 20000 25000 30000 35000
Per Capita GDP
54
Figure 19: Average Level of Health, age-standardized, 66 surveys: Mobility
Average Level of Mobility vs. Male/Female Ratio of
Mobility, WHO Survey 2000-2001
1.6
100
90
80
70
60
50
40
30
20
10
0
Ratio of Male/Female
Females
Male vs. Female Self Report of Mobility
WHO 2000 - 2001 Survey
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
0
100
20
Self Reported Mobility
50
55
60
65
70
75
80
85
Life Expectancy at birth
80
100
100
90
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
Life Expectancy at birth
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Mobility
World Standardized Population
Self Reported Mobility
Self Reported Mobility
100
90
80
70
60
50
40
30
20
10
0
45
60
Female Life Expectancy at birth (2000) vs.
Self Reported Mobility
World Standardized Population
Male Life Expectancy at birth (2000) vs.
Self Reported Mobility
World Standardized Population
40
40
Average Level for Males and Females Combined
Males
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000 15000 20000 25000 30000 35000
Per Capita GDP
55
85
Figure 20: Average Level of Health, age-standardized, 66 surveys: Pain (higher level, absence of pain)
Average Level of Pain vs. Male/Female Ratio of Pain,
WHO Survey 2000-2001
100
90
80
70
60
50
40
30
20
10
0
1.6
Ratio of Male/Female
Females
Male vs. Female Self Report of Pain
WHO 2000 - 2001 Survey
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
100
0
20
Males
Self Reported Pain
50
55
60
65
70
75
80
85
Life Expectancy at birth
80
100
100
90
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Pain
World Standardized Population
Self Reported Pain
Self Reported Pain
100
90
80
70
60
50
40
30
20
10
0
45
60
Female Life Expectancy at birth (2000) vs.
Self Reported Pain
World Standardized Population
Male Life Expectancy at birth (2000) vs.
Self Reported Pain
World Standardized Population
40
40
Average Level for Males and Females Combined
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000 15000 20000 25000 30000 35000
Per Capita GDP
56
Figure 21: Average Level of Health, age-standardized, 66 surveys: Self Care
Average Level of Self-care vs. Male/Female Ratio of
Self-care, WHO Survey 2000-2001
100
90
80
70
60
50
40
30
20
10
0
1.6
Ratio of Male/Female
Females
Male vs. Female Self Report of Self-care
WHO 2000 - 2001 Survey
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
100
0
Males
Self Reported Self-care
Self Reported Self-care
100
90
80
70
60
50
40
30
20
10
0
45
50
55
60
65
40
60
80
100
Female Life Expectancy at birth (2000) vs.
Self Reported Self-care
World Standardized Population
Male Life Expectancy at birth (2000) vs.
Self Reported Self-care
World Standardized Population
40
20
Average Level for Males and Females Combined
70
75
80
85
Life Expectancy at birth
100
90
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
Self Reported Self-care
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Self-care
World Standardized Population
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000
15000
20000
25000
30000
35000
Per Capita GDP
57
Figure 22: Average Level of Health, age-standardized, 66 surveys: Usual Activities
Average Level of Usual Activities vs. Male/Female
Ratio of Usual Activities, WHO Survey 2000-2001
100
90
80
70
60
50
40
30
20
10
0
Ratio of Male/Female
1.6
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0
10
20
30
40
50
60
70
80
90
100
0
20
Males
Self Reported Usual Activities
Self Reported Usual Activities
45
50
55
60
60
80
100
Female Life Expectancy at birth (2000) vs.
Self Reported Usual Activities
World Standardized Population
100
90
80
70
60
50
40
30
20
10
0
40
40
Average Level for Males and Females Combined
Male Life Expectancy at birth (2000) vs.
Self Reported Usual Activities
World Standardized Population
65
70
75
80
85
Life Expectancy at birth
100
90
80
70
60
50
40
30
20
10
0
40
45
50
55
60
65
70
75
80
85
Life Expectancy at birth
Per Capita Gross Domestic Product (PPP 1998) vs. Self
Reported Usual Activities
World Standardized Population
Self Reported Usual Activities
Females
Male vs. Female Self Report of Usual Activities
WHO 2000 - 2001 Survey
100
90
80
70
60
50
40
30
20
10
0
0
5000
10000 15000 20000 25000 30000 35000
Per Capita GDP
58
V. Discussion
We address the main objective of this paper: whether the estimated mean levels of health by age and
sex groups, or the mean aggregate, age standardized level by sex, for six domains of health are
comparable across 66 population based surveys. Specifically, we consider whether our new data
collection and analyses methods applied to 66 surveys in 57 countries have enhanced:
·
·
the information content on health status data collected through surveys, and
the comparability of this information across survey populations.
To do so, we include a comparison of selected results from this analysis with those from our
previous approach to estimate levels of health, based on 64 existing data sets from 46 countries -data sets that did not contain a means to calibrate self-reported responses across survey populations
nor information on a range of domains (see Sadana et al. 2000).
Concerning an evaluation of the validity of our new methods using the vignette strategy to calibrate
responses, there is no gold standard or measurement of "truth" that captures all aspects of each
domain of health. Instead, several approaches to estimate validity are required as no single aspect of
validity would provide a definitive evaluation. Three basic criteria provide necessary evidence that
the new methods have enhanced the information content and comparability of health status data
collected through surveys include: (i) that the estimated levels of health should decrease as age
increases (criterion validity); (ii) that the differences in the estimated levels of health, for most
domains, should reflect expected differences within and across populations, for example between
males and females, between populations with high child and high adult mortality vs. those with low
child and adult mortality or between populations with high and low GDP per capita (face validity);
and (iii) that besides covering the key concepts of health, each of the domains assessed of health as
measured should provide unique information (content validity).
V.1 INFORMATION CONTENT
5.1.1 DIFFERENCE BETWEEN ORDINAL RESPONSE AND ESTIMATED LEVEL OF
HEALTH
In section 3.7.3, we provide illustrations comparing the ordinal response and the estimated level of
health across all domains (Figure 9) for one population from the WHO EURO A mortality sub-group
(Luxembourg) and another from the WHO SEARO D mortality sub-group (Andhra Pradesh, India).
The mean ordinal responses by age for affect, cognition, self-care and usual activities, particularly in
Luxembourg, show very little variation over age. These same mean ordinal responses are similar for
the two populations across all age groups, particularly for cognition, mobility and pain. However, the
posterior estimated levels of health across five of the six domains assessed (with the exception to
some degree of affect), shows clearly that the level of health decreases as age increases.
Furthermore, the requirement of face validity that levels of health in certain domains, such as
mobility, is significantly better in Luxembourg than in Andhra Pradesh, is met.
5.1.2 ADDED VALUE OF MULTI-DIMENSIONAL APPROACH
Based on the posterior estimated level of health, a correlation matrix of all survey data combined
shows that the four domains that directly assess health (e.g. affect, cognition, mobility, pain) clearly
provide unique information, with correlations ranging between 0.54 and 0.68. These are below 0.70,
the standard cut-off used in psychometrics to assess the similarity or difference of different constructs
(Nunnally and Bernstein 1994). As expected, domains that serve as proximate measures of health,
self-care and usual activities, are more highly correlated with each other (0.81), and more highly
correlated with mobility or pain ( 0.71 and 0.78 respectively), and less so with those directly
assessing mental health (i.e., 0.56 to 0.64 with affect or cognition). These results provide some
evidence that each of the domains that directly assess health provide unique information, that the
59
assessment of health as a multi-dimensional construct is useful in terms of the enhanced information
content. Additional tests that build on confirmatory factor analyses approaches for six domains
assessed, as more stringent tests of construct validity, are being considered.
Table 11. Correlation Matrix Across Domains, Estimated Level of Health, 66 surveys
Domain
Affect
Cognition Mobility
Pain
Self Care
Usual
Activities
1.0000
Affect
0.5558
1.0000
Cognition
0.5686
0.5435
1.0000
Mobility
0.6259
0.5989
0.6673
1.0000
Pain
0.5575
0.5867
0.7563
0.7160
1.0000
Self Care
0.5639
0.6417
0.7847
0.7117
0.8075
1.0000
Usual Activities
V.2 COMPARABILITY
5.2.1 COMPARISON OF NEW METHODS WITH PREVIOUS ANALYSES: SELECTED
RESULTS BY AGE -SEX GROUPS
We focus our comparison on two populations, one from WHO AMRO A mortality sub-region (USA)
and another from WHO WPRO B mortality sub-region (China -- selected regions as noted). Figure
23 illustrates the estimated level of health (uni-dimensional from the previous analysis)7 with our
current results (selected domains shown), across age and sex groups for both populations. The
previous analysis showed almost no decrement to full health, across all age groups from eight
provinces included from China8. The data set from the USA is the NHANES III completed in 1994.
Both surveys had extensive questions on self-reported health, using ordinal response scales.
Given the mean age group and sex results, based on our previous analysis, we did not assume that
these data were comparable, nor that the Chinese data actually reflected the health status of the
population. Furthermore, separate analysis on the NHANES III data has shown evidence of cut-point
shifts using measured performance tests to calibrate self-reported responses across socio-economic
groups, within the USA population (Iburg et al. 2002).
Our current analysis approach, with results illustrating estimates for mobility, pain and cognition, do
not show the high ceiling effects from the China in-depth household survey (sample covering
Shandong, Henana and Gansu Provinces)9. We believe, by taking into account cut-point shifts, this
data is more comparable across age and sex groups, both within each population and across the two
populations. It is interesting to note that the comparison between the two countries differs depending
upon the domain of health examined from our new analysis, i.e., mobility, pain or cognition shown.
That such differences exist provide additional evidence that a multi-dimensional approach to assess
health status may provide more comprehensive and complex insights on the health status of a
population.
7
Given limitations in existing data sets, our previous analysis was based on one, general latent variable
assessing health, rather than six domains (see Sadana et al. 2000).
8
The China Health and Nutrition Survey 1993 in eight provinces was conducted with the assistance of the
Carolina Population Centre, University of North Carolina, and is part of a longitudinal, integrated survey.
9
Two of the provinces, Shandong and Henan, overlap with the survey conducted by CPC/UNC in 1993.
60
Figure 23. Estimated levels of health, USA and selected regions of China, by age and sex groups
China, male
China, female
USA, male
USA, female
Level of health
(1999-2000 analysis)
China, m ale
China, fem ale
US A , m ale
US A , fem ale
L e ve l o f M o b ility
(2000-2001 an alys is )
100
100
80
80
60
60
40
40
20
20
0
0
0
5
15
25
35
45
55
65
15-29
75+
30-44
60-69
70-79
80+
A g e Gr o u p
Age Group
China, m ale
China, fem ale
US A, m ale
US A, fem ale
L e ve l o f Pain
(2000-2001 an alys is )
45-59
China, m ale
China, fem ale
US A , m ale
US A , fem ale
Le ve l of Cognition
(2 0 0 0 -2 0 0 1 a na lys is )
100
80
80
60
60
40
40
20
20
0
0
15-29
30-44
45-59
60-69
Ag e Gr o up
70-79
80+
1 5 -2 9
3 0 -4 4
4 5 -5 9
6 0 -6 9
7 0 -7 9
80+
Age Gr oup
61
5.2.2 SELECTED RESULTS, AGGREGATED AND AGE-STANDARIZED
We highlight the age standardized results, aggregated across age groups, by sex. Figure 24 shows the
estimated level of health (mobility shown here, see Figures 17 - 22 for all domains), and life
expectancy by sex. We document that higher levels of life expectancy are correlated with higher
estimated levels of health (+0.3), in this case for mobility, for either males or females. For the other
five domains, this correlation is positive as well. Alternatively, although the determinants of health
(mobility shown) and life expectancy are not identical, some similarity is expected, as these results
suggest (criterion validity).
Figure 24. Estimated level of health and life expectancy, for males and females, Mobility
2000-2001 analysis (57 countries, 66 surveys)
100
90
80
70
60
50
40
30
20
10
0
Level of Mobility
Level of Mobility
2000-2001 analysis (57 countries, 66 surveys)
40
50
60
70
80
Life Expectancy at birth, females
90
100
90
80
70
60
50
40
30
20
10
0
40
50
60
70
80
Life Expectancy at birth, males
Another approach to evaluate the information content and cross-population comparability of the
results is to interpret the data from surveys in conjunction with data external to health, from the same
countries. Such data may include the per capita gross domestic product or the per capita total health
expenditures (criterion validity). Figure 25 illustrates the aggregated, age standardized estimates,
averaged for both males and females, in comparison with GDP (PPP). We document that higher
levels of GDP (PPP), are correlated with higher estimated levels of health (+0.4 ), for the domain of
mobility, as expected (see Figures 17 - 22 for all domains, showing a positive correlation).
Figure 26 groups the average estimated level of health for each domain, by sex, for 51 countries into
four geographic or economic strata. For both males and females, average levels of affect, mobility,
pain, self-care and usual activities are highest in a subset of OECD member countries, followed by
Latin American countries, former Socialist economies, and then countries in the Eastern
Mediterranean area including Turkey and Kyrgystan. Only minor deviations from this pattern are
noted for cognition and pain. This pattern is not surprising and contributes to further face validity.
Although not sufficient, these and other results suggest face and criterion validity of our estimates
based on new methods. Based on our review of the new methods to collect and analyze self-reported
data on health, our confidence in the information content of interview-based surveys has increased.
We consider these results as a significant step forward in the use of self-reported data on health.
These results have been incorporated within the calculation of healthy life expectancy (Mathers et al.
2001) and in the estimation of inequalities in the distribution of health (Gakidou et al. 2001), among
other analyses.
62
Figure 25. GDP (PPP) and Estimated level of health (average for males and females)
Level of Mobility
(2000-2001 analysis)
100
90
80
70
60
50
40
30
20
10
0
100
1000
10000
100000
Per Capita GDP (PPP)
Figure 26. Multi-dimensional Health Profile, selected surveys and countries
Eas tern Mediterranean (9 countries )
Form er Socialis t (13 countries )
Latin Am erican (9 countries )
OECD s ubs et (22 countries )
90
80
Estimated Level of Health
70
60
50
40
30
20
10
0
Aff M
Aff F
Cog M
Cog F
Mob M
Mob F
Pain M
Pain F
Self M
Self F
Us ual M Usual F
Dom ains
63
VI. NEXT STEPS
The next steps will focus on three areas: (i) additional analyses on the existing data, (ii) updating of
our methods, and (iii) surveys in additional countries.
Additional analysis will include those highlighted through out the text of this paper, in order to
provide further evidence concerning validity -- both the extent to which the new methods measure
what it is intended to measure, or more broadly, the range of interpretations that cam be reasonably
attributed to the estimated levels of health, by domain. Across all 66 surveys, these analyses will
address:
·
·
more stringent tests of hypotheses stated
parameter uncertainty estimates
For the ten in-depth household surveys, these analyses will address:
·
·
·
·
measured performance tests strategy for calibration: cognition, vision, mobility
posterior estimates: comparison between HOPIT and CHOPIT
auxiliary questions: information content and item reduction strategies
classical psychometric properties concerning additional domains from the in-depth household
surveys
Along with a critical evaluation of the vignette strategy to calibrate responses, these analyses will be
an input to update the survey module on health status. This will include a revision, as necessary, of
the questions addressing each core domain of health and the corresponding set of vignettes. This
updated module, within the planned WHO World Health Survey, will then be implemented in
surveys in additional countries, particularly in the African region.
Given that the current sampling strategy includes the non-institutionalized population, the further
expansion of the sampling protocol and adaptation of methods to include representative samples of
individuals in long-term care facilities (of any type), is under consideration.
Acknowledgements
We thank the following individuals for their contributions: Nicole Valentine and Juan Pablo Ortiz
for fruitful discussions on parallel analytical efforts in the area of health system responsiveness; Josh
Salomon for the conception of the vignette adjustment strategy; Colin Mathers for contributing to the
development of the health status assessment module and comments on this manuscript; Pierre
Lewalle for his contribution in coordinating the language translation protocols, the first step towards
cross-population comparability; Can Celik for obtaining and managing data sets from survey sites;
Lydia Bendib and Maria Villanueva for their contribution in coordinating data collection across the
66 survey sites; Melroy Menezes and René Lavallée for their assistance in preparing graphs within
this manuscript; and Emre Ozaltin for comments on this manuscript.
64
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66
Appendix 1: Distribution of mean cut-points (t1-t4) on latent variable scale-Cognition, 66 surveys
Survey
36. INDh
34. IDNh
58. SVKh
12. CHNh
21. EGYh
22. EGYp
33. HUNp
52. NZLp
23. ESPb
14. COLh
53. OMNb
47. MEXh
43. LTUp
29. GBRp
7. BHRb
37. IRLb
13. CHNp
60. THAp
40. JORb
9. CANt
1. AREb
19. DEUb
55. PRTb
18. CZEp
30. GEOh
2. ARGb
17. CZEb
48. MLTb
65. USAp
24. ESTb
39. ITAb
10. CHEp
45. LVAb
35. IDNp
4. AUTp
6. BGRb
57. RUSb
32. HRVb
15. CRIb
8. CANp
42. KORp
3. AUSp
62. TURh
49. NGAh
64. UKRp
31. GRCp
59. SWEb
25. FINb
66. VENb
54. POLp
56. ROMb
63. TURp
11. CHLp
61. TTOp
46. MARb
26. FINp
28. FRAp
16. CYPp
5. BELb
51. NLDp
27. FRAb
44. LUXt
38. ISLb
50. NLDb
20. DNKp
41. KGZp
Tau 1
-4.445
-4.363
-4.343
-4.333
-4.218
-4.086
-4.040
-4.014
-3.978
-3.976
-3.960
-3.908
-3.853
-3.841
-3.832
-3.813
-3.808
-3.806
-3.794
-3.785
-3.785
-3.784
-3.780
-3.779
-3.778
-3.777
-3.767
-3.762
-3.758
-3.756
-3.755
-3.747
-3.745
-3.741
-3.741
-3.731
-3.726
-3.721
-3.690
-3.690
-3.690
-3.687
-3.675
-3.674
-3.654
-3.647
-3.641
-3.636
-3.598
-3.597
-3.546
-3.525
-3.524
-3.502
-3.501
-3.487
-3.465
-3.455
-3.450
-3.422
-3.401
-3.399
-3.391
-3.370
-3.304
-3.200
Survey
12. CHNh
58. SVKh
33. HUNp
35. IDNp
7. BHRb
52. NZLp
13. CHNp
53. OMNb
23. ESPb
1. AREb
3. AUSp
42. KORp
40. JORb
66. VENb
43. LTUp
34. IDNh
10. CHEp
9. CANt
14. COLh
37. IRLb
21. EGYh
36. INDh
39. ITAb
60. THAp
48. MLTb
64. UKRp
57. RUSb
47. MEXh
29. GBRp
65. USAp
19. DEUb
45. LVAb
17. CZEb
4. AUTp
15. CRIb
46. MARb
2. ARGb
30. GEOh
32. HRVb
56. ROMb
8. CANp
55. PRTb
22. EGYp
41. KGZp
16. CYPp
62. TURh
25. FINb
54. POLp
26. FINp
18. CZEp
59. SWEb
63. TURp
28. FRAp
24. ESTb
31. GRCp
27. FRAb
61. TTOp
11. CHLp
44. LUXt
5. BELb
49. NGAh
6. BGRb
20. DNKp
38. ISLb
51. NLDp
50. NLDb
Tau 2
-3.220
-3.145
-2.997
-2.960
-2.950
-2.938
-2.907
-2.888
-2.884
-2.874
-2.828
-2.821
-2.813
-2.811
-2.809
-2.796
-2.780
-2.775
-2.773
-2.766
-2.761
-2.758
-2.751
-2.749
-2.746
-2.742
-2.727
-2.727
-2.719
-2.713
-2.711
-2.709
-2.706
-2.682
-2.679
-2.668
-2.653
-2.650
-2.649
-2.648
-2.637
-2.627
-2.622
-2.602
-2.595
-2.573
-2.573
-2.557
-2.553
-2.547
-2.546
-2.543
-2.538
-2.531
-2.520
-2.496
-2.490
-2.479
-2.470
-2.454
-2.449
-2.432
-2.430
-2.387
-2.341
-2.334
Survey
35. IDNp
12. CHNh
7. BHRb
53. OMNb
58. SVKh
42. KORp
40. JORb
1. AREb
33. HUNp
36. INDh
48. MLTb
43. LTUp
10. CHEp
41. KGZp
39. ITAb
49. NGAh
13. CHNp
55. PRTb
52. NZLp
23. ESPb
34. IDNh
66. VENb
46. MARb
60. THAp
47. MEXh
28. FRAp
16. CYPp
4. AUTp
56. ROMb
14. COLh
64. UKRp
65. USAp
9. CANt
57. RUSb
17. CZEb
21. EGYh
45. LVAb
8. CANp
3. AUSp
37. IRLb
27. FRAb
29. GBRp
5. BELb
63. TURp
20. DNKp
26. FINp
32. HRVb
19. DEUb
25. FINb
15. CRIb
30. GEOh
54. POLp
22. EGYp
59. SWEb
62. TURh
24. ESTb
2. ARGb
61. TTOp
38. ISLb
44. LUXt
31. GRCp
18. CZEp
11. CHLp
6. BGRb
50. NLDb
51. NLDp
Tau 3
-2.525
-2.281
-2.212
-2.184
-2.083
-2.059
-2.039
-2.013
-1.972
-1.946
-1.941
-1.934
-1.931
-1.902
-1.881
-1.880
-1.870
-1.870
-1.869
-1.849
-1.838
-1.811
-1.810
-1.790
-1.785
-1.778
-1.776
-1.759
-1.757
-1.752
-1.748
-1.738
-1.735
-1.731
-1.720
-1.712
-1.712
-1.712
-1.711
-1.705
-1.695
-1.666
-1.666
-1.655
-1.645
-1.644
-1.644
-1.644
-1.640
-1.640
-1.637
-1.632
-1.627
-1.625
-1.623
-1.619
-1.603
-1.568
-1.546
-1.540
-1.526
-1.520
-1.500
-1.487
-1.412
-1.369
Survey
35. IDNp
40. JORb
53. OMNb
46. MARb
7. BHRb
12. CHNh
33. HUNp
1. AREb
14. COLh
66. VENb
36. INDh
10. CHEp
55. PRTb
48. MLTb
34. IDNh
41. KGZp
58. SVKh
15. CRIb
57. RUSb
47. MEXh
32. HRVb
23. ESPb
43. LTUp
27. FRAb
39. ITAb
30. GEOh
21. EGYh
56. ROMb
5. BELb
42. KORp
50. NLDb
4. AUTp
52. NZLp
11. CHLp
9. CANt
37. IRLb
44. LUXt
63. TURp
22. EGYp
16. CYPp
45. LVAb
62. TURh
60. THAp
2. ARGb
49. NGAh
59. SWEb
64. UKRp
17. CZEb
20. DNKp
8. CANp
28. FRAp
65. USAp
25. FINb
6. BGRb
19. DEUb
13. CHNp
3. AUSp
24. ESTb
61. TTOp
54. POLp
29. GBRp
38. ISLb
26. FINp
31. GRCp
18. CZEp
51. NLDp
Tau 4
-1.228
-1.109
-1.098
-1.074
-1.064
-1.047
-0.995
-0.959
-0.957
-0.903
-0.897
-0.883
-0.881
-0.878
-0.869
-0.857
-0.855
-0.842
-0.840
-0.833
-0.828
-0.803
-0.803
-0.797
-0.790
-0.783
-0.782
-0.778
-0.778
-0.747
-0.731
-0.731
-0.730
-0.723
-0.722
-0.712
-0.700
-0.696
-0.695
-0.693
-0.691
-0.691
-0.688
-0.687
-0.675
-0.672
-0.664
-0.630
-0.617
-0.611
-0.611
-0.605
-0.602
-0.600
-0.597
-0.591
-0.547
-0.526
-0.524
-0.522
-0.512
-0.507
-0.498
-0.477
-0.393
-0.361
67
Appendix 2: Complete estimates from HOPIT, means and cut-points, COGNITION
Vignettes
Coef.
Std. Err.
z
P>z
[95% Conf. Interval]
vignette2
-1.703
0.011
-160.57
0.000
-1.724
-1.682
vignette3
-1.892
0.011
-177.88
0.000
-1.913
-1.872
vignette4
-2.048
0.011
-191.49
0.000
-2.069
-2.027
vignette5
-2.534
0.011
-231.1
0.000
-2.555
-2.512
vignette6
-2.637
0.011
-241.02
0.000
-2.659
-2.616
vignette7
-3.235
0.011
-287.41
0.000
-3.257
-3.213
vignette8
-3.896
0.012
-331.09
0.000
-3.919
-3.873
Mean
Coef.
Std. Err.
z
P>z
[95% Conf. Interval]
_Iagedummy_2
-0.036
0.015
-2.46
0.014
-0.066
-0.007 Age 30-44
_Iagedummy_3
-0.282
0.016
-17.31
0.000
-0.314
-0.250 Age 45-59
_Iagedummy_4
-0.701
0.018
-39.43
0.000
-0.736
-0.666 Age 60+
sex
0.180
0.011
16.32
0.000
0.158
0.202 Male
educ
0.030
0.001
21.78
0.000
0.027
0.033 Education (yrs)
_Icountry_2
0.256
0.092
2.79
0.005
0.076
0.436 Argentina brief
_Icountry_3
0.109
0.083
1.31
0.189
-0.054
0.272 Australia postal
_Icountry_4
-0.277
0.083
-3.33
0.001
-0.440
-0.114 Austria postal
_Icountry_5
0.384
0.086
4.44
0.000
0.214
0.553 Belgium brief
_Icountry_6
0.177
0.086
2.05
0.040
0.008
0.347 Bulgaria brief
_Icountry_7
-0.097
0.092
-1.06
0.289
-0.277
0.083 Bahrain brief
_Icountry_8
0.128
0.110
1.16
0.247
-0.088
0.344 Canada postal
_Icountry_9
0.084
0.113
0.74
0.459
-0.137
0.304 Canada telephone
_Icountry_10
-0.036
0.105
-0.34
0.732
-0.242
0.170 Switzerland postal
_Icountry_11
0.007
0.085
0.09
0.930
-0.159
0.174 Chile postal
_Icountry_12
0.093
0.067
1.39
0.166
-0.038
0.224 China household
_Icountry_13
-0.087
0.080
-1.08
0.278
-0.245
_Icountry_14
0.259
0.069
3.77
0.000
0.124
_Icountry_15
-0.036
0.091
-0.4
0.689
-0.214
_Icountry_16
-0.111
0.094
-1.18
0.237
-0.295
0.073 Cyprus postal
_Icountry_17
0.153
0.085
1.8
0.072
-0.014
0.321 Czech Republic brief
_Icountry_18
-0.022
0.084
-0.26
0.796
-0.186
_Icountry_19
0.602
0.087
6.95
0.000
0.433
0.772 Germany brief
_Icountry_20
0.219
0.080
2.74
0.006
0.062
0.376 Denmark postal
_Icountry_21
0.574
0.071
8.13
0.000
0.435
0.712 Egypt household
_Icountry_22
-0.746
0.078
-9.6
0.000
-0.898
-0.593 Egypt postal
_Icountry_23
0.703
0.091
7.74
0.000
0.525
0.881 Spain brief
_Icountry_24
0.267
0.086
3.11
0.002
0.099
0.435 Estonia brief
_Icountry_25
0.649
0.088
7.38
0.000
0.477
0.821 Finland brief
_Icountry_26
0.309
0.081
3.8
0.000
0.149
0.468 Finland postal
_Icountry_27
0.289
0.088
3.3
0.001
0.117
0.460 France brief
_Icountry_28
-0.132
0.098
-1.35
0.177
-0.323
0.059 France postal
_Icountry_29
0.068
0.085
0.8
0.423
-0.099
0.236 United Kingdom postal
_Icountry_30
0.393
0.067
5.88
0.000
0.262
0.524 Georgia household
_Icountry_31
0.178
0.088
2.01
0.044
0.005
0.351 Greece postal
_Icountry_32
-0.113
0.078
-1.44
0.149
-0.266
0.041 Croatia brief
_Icountry_33
-0.043
0.079
-0.54
0.588
-0.198
0.112 Hungary postal
_Icountry_34
0.688
0.067
10.21
0.000
0.556
_Icountry_35
-0.576
0.073
-7.91
0.000
-0.719
-0.433 Indonesia postal
_Icountry_36
0.347
0.070
4.96
0.000
0.210
0.484 India household
_Icountry_37
0.976
0.103
9.44
0.000
0.773
1.178 Ireland brief
_Icountry_38
-0.174
0.101
-1.72
0.085
-0.373
_Icountry_39
0.203
0.087
2.34
0.019
0.033
0.070 China postal
0.393 Columbia household
0.142 Costa Rica brief
0.143 Czech Republic postal
0.820 Indonesia household
0.024 Iceland brief
0.372 Italy brief
68
_Icountry_40
-0.342
0.089
-3.84
0.000
-0.517
-0.168 Jordan brief
_Icountry_41
-1.071
0.081
-13.26
0.000
-1.229
-0.912 Kyrgyzstan postal
_Icountry_42
-0.311
0.111
-2.81
0.005
-0.528
-0.094 Republic of Korea postal
_Icountry_43
-0.663
0.075
-8.84
0.000
-0.810
-0.516 Lithuania postal
_Icountry_44
0.497
0.096
5.17
0.000
0.308
_Icountry_45
0.089
0.091
0.98
0.328
-0.089
_Icountry_46
-0.533
0.089
-6
0.000
-0.707
_Icountry_47
0.695
0.071
9.77
0.000
0.556
_Icountry_48
0.024
0.103
0.23
0.818
-0.177
_Icountry_49
1.136
0.072
15.7
0.000
0.994
1.277 Nigeria household
_Icountry_50
0.134
0.084
1.59
0.113
-0.032
0.299 Netherlands brief
_Icountry_51
-0.022
0.097
-0.22
0.823
-0.211
0.168 Netherlands postal
_Icountry_52
-0.147
0.077
-1.91
0.057
-0.298
0.004 New Zealand postal
_Icountry_53
-0.277
0.088
-3.13
0.002
-0.450
-0.104 Oman brief
_Icountry_54
-0.426
0.085
-5
0.000
-0.594
-0.259 Poland postal
_Icountry_55
-0.192
0.084
-2.28
0.022
-0.357
-0.027 Portugal brief
_Icountry_56
-0.147
0.084
-1.76
0.079
-0.312
0.017 Romania brief
_Icountry_57
0.619
0.082
7.52
0.000
0.457
0.780 Russian Federation brief
_Icountry_58
0.266
0.085
3.12
0.002
0.099
0.432 Slovakia household
_Icountry_59
0.264
0.086
3.08
0.002
0.096
_Icountry_60
-0.439
0.080
-5.5
0.000
-0.596
_Icountry_61
-0.058
0.080
-0.72
0.472
-0.216
0.100 Trinidad and Tobago postal
_Icountry_62
0.131
0.070
1.89
0.059
-0.005
0.267 Turkey household
0.685 Luxembourg telephone
0.267 Latvia brief
-0.359 Morocco brief
0.835 Mexico household
0.225 Malta brief
0.431 Sweden brief
-0.283 Thailand postal
_Icountry_63
-0.876
0.072
-12.13
0.000
-1.018
-0.735 Turkey postal
_Icountry_64
-0.479
0.088
-5.46
0.000
-0.651
-0.307 Ukraine postal
_Icountry_65
-0.094
0.082
-1.15
0.250
-0.254
_Icountry_66
-0.190
0.091
-2.08
0.037
-0.369
-0.011 Venezuela brief
_cons
-0.726
0.068
-10.72
0.000
-0.859
-0.593
Cut-point 1
Coef.
Std. Err.
z
P>z
0.066 United States postal
[95% Conf. Interval]
_Iagedummy_2
0.019
0.010
1.87
0.062
-0.001
_Iagedummy_3
0.011
0.011
0.95
0.341
-0.011
0.039 Age 30-44
_Iagedummy_4
-0.045
0.013
-3.5
0.000
-0.070
sex
-0.007
0.008
-0.86
0.388
-0.022
0.009 Male
educ
0.000
0.001
-0.37
0.713
-0.002
0.002 Education (yrs)
_Icountry_2
0.018
0.063
0.29
0.770
-0.105
0.142 Argentina brief
_Icountry_3
0.117
0.057
2.05
0.041
0.005
0.228 Australia postal
_Icountry_4
0.059
0.059
1
0.320
-0.057
0.174 Austria postal
_Icountry_5
0.348
0.056
6.24
0.000
0.238
0.457 Belgium brief
_Icountry_6
0.067
0.059
1.14
0.253
-0.048
0.182 Bulgaria brief
_Icountry_7
-0.047
0.062
-0.75
0.451
-0.168
0.075 Bahrain brief
_Icountry_8
0.107
0.074
1.45
0.148
-0.038
0.252 Canada postal
_Icountry_9
0.010
0.078
0.12
0.902
-0.144
0.163 Canada telephone
_Icountry_10
0.048
0.072
0.66
0.508
-0.093
_Icountry_11
0.274
0.057
4.76
0.000
0.161
_Icountry_12
-0.544
0.045
-11.96
0.000
-0.633
_Icountry_13
-0.022
0.056
-0.4
0.688
-0.132
_Icountry_14
-0.187
0.046
-4.05
0.000
-0.277
_Icountry_15
0.100
0.061
1.63
0.104
-0.020
_Icountry_16
0.340
0.063
5.4
0.000
0.216
_Icountry_17
0.029
0.058
0.5
0.616
-0.084
0.142 Czech Republic brief
_Icountry_18
0.022
0.058
0.38
0.704
-0.092
0.136 Czech Republic postal
_Icountry_19
0.016
0.057
0.28
0.782
-0.097
0.128 Germany brief
_Icountry_20
0.492
0.053
9.36
0.000
0.389
0.595 Denmark postal
_Icountry_21
-0.430
0.048
-8.97
0.000
-0.524
-0.336 Egypt household
0.033 Age 45-59
-0.020 Age 60+
0.189 Switzerland postal
0.386 Chile postal
-0.455 China household
0.087 China postal
-0.096 Columbia household
0.220 Costa Rica brief
0.463 Cyprus postal
69
_Icountry_22
-0.294
0.057
-5.16
0.000
-0.406
-0.182 Egypt postal
_Icountry_23
-0.180
0.061
-2.95
0.003
-0.300
-0.060 Spain brief
_Icountry_24
0.044
0.059
0.75
0.454
-0.072
0.160 Estonia brief
_Icountry_25
0.164
0.058
2.85
0.004
0.051
0.276 Finland brief
_Icountry_26
0.315
0.053
5.89
0.000
0.210
0.420 Finland postal
_Icountry_27
0.395
0.056
7.09
0.000
0.286
0.504 France brief
_Icountry_28
0.330
0.067
4.93
0.000
0.199
0.461 France postal
_Icountry_29
-0.039
0.059
-0.66
0.511
-0.155
0.077 United Kingdom postal
_Icountry_30
0.019
0.044
0.44
0.661
-0.068
0.106 Georgia household
_Icountry_31
0.151
0.060
2.52
0.012
0.034
_Icountry_32
0.078
0.053
1.46
0.144
-0.027
_Icountry_33
-0.241
0.056
-4.31
0.000
-0.350
-0.131 Hungary postal
_Icountry_34
-0.575
0.046
-12.59
0.000
-0.664
-0.485 Indonesia household
_Icountry_35
0.045
0.050
0.92
0.358
-0.052
0.143 Indonesia postal
_Icountry_36
-0.656
0.049
-13.4
0.000
-0.752
-0.560 India household
_Icountry_37
-0.015
0.064
-0.23
0.818
-0.139
0.110 Ireland brief
_Icountry_38
0.402
0.067
6.01
0.000
0.271
0.533 Iceland brief
0.268 Greece postal
0.183 Croatia brief
_Icountry_39
0.044
0.058
0.76
0.445
-0.069
0.158 Italy brief
_Icountry_40
-0.005
0.061
-0.08
0.939
-0.124
0.115 Jordan brief
_Icountry_41
0.594
0.054
11.07
0.000
0.489
_Icountry_42
0.112
0.078
1.43
0.153
-0.042
_Icountry_43
-0.056
0.052
-1.07
0.284
-0.158
_Icountry_44
0.399
0.061
6.6
0.000
0.281
_Icountry_45
0.058
0.062
0.93
0.353
-0.064
_Icountry_46
0.287
0.059
4.84
0.000
0.171
_Icountry_47
-0.116
0.047
-2.44
0.015
-0.208
_Icountry_48
0.036
0.070
0.51
0.610
-0.101
_Icountry_49
0.117
0.046
2.52
0.012
0.026
0.208 Nigeria household
_Icountry_50
0.426
0.054
7.82
0.000
0.319
0.532 Netherlands brief
_Icountry_51
0.380
0.066
5.79
0.000
0.251
0.508 Netherlands postal
_Icountry_52
-0.215
0.055
-3.91
0.000
-0.323
-0.107 New Zealand postal
_Icountry_53
-0.175
0.063
-2.76
0.006
-0.299
-0.051 Oman brief
_Icountry_54
0.201
0.058
3.46
0.001
0.087
0.315 Poland postal
_Icountry_55
0.019
0.058
0.32
0.746
-0.095
0.133 Portugal brief
_Icountry_56
0.252
0.056
4.48
0.000
0.142
0.363 Romania brief
_Icountry_57
0.072
0.053
1.35
0.177
-0.032
_Icountry_58
-0.549
0.064
-8.63
0.000
-0.673
_Icountry_59
0.158
0.057
2.77
0.006
0.046
_Icountry_60
-0.019
0.056
-0.33
0.740
-0.129
_Icountry_61
0.290
0.054
5.33
0.000
0.184
0.397 Trinidad and Tobago postal
_Icountry_62
0.113
0.046
2.45
0.014
0.023
0.204 Turkey household
_Icountry_63
0.262
0.049
5.35
0.000
0.166
0.357 Turkey postal
_Icountry_64
0.142
0.061
2.34
0.019
0.023
_Icountry_65
0.045
0.056
0.8
0.423
-0.065
_Icountry_66
_cons
Cut-Point 2
0.186
0.060
3.09
0.002
0.068
-3.787
0.046
-82.65
0.000
-3.877
Coef.
Std. Err.
z
P>z
0.699 Kyrgyzstan postal
0.265 Republic of Korea postal
0.046 Lithuania postal
0.518 Luxembourg telephone
0.180 Latvia brief
0.403 Morocco brief
-0.023 Mexico household
0.173 Malta brief
0.176 Russian Federation brief
-0.424 Slovakia household
0.270 Sweden brief
0.092 Thailand postal
0.261 Ukraine postal
0.155 United States postal
0.304 Venezuela brief
-3.697
[95% Conf. Interval]
_Iagedummy_2
0.012
0.008
1.5
0.133
-0.004
0.027 Age 30-44
_Iagedummy_3
0.039
0.009
4.4
0.000
0.021
0.056 Age 45-59
_Iagedummy_4
0.031
0.010
3.21
0.001
0.012
sex
-0.021
0.006
-3.5
0.000
-0.033
0.051 Age 60+
educ
0.001
0.001
1.52
0.130
0.000
_Icountry_2
0.216
0.050
4.32
0.000
0.118
0.314 Argentina brief
_Icountry_3
0.033
0.047
0.71
0.478
-0.059
0.126 Australia postal
-0.009 Male
0.003 Education (yrs)
70
_Icountry_4
0.180
0.047
3.82
0.000
0.088
0.272 Austria postal
_Icountry_5
0.410
0.046
8.86
0.000
0.319
0.501 Belgium brief
_Icountry_6
0.431
0.047
9.11
0.000
0.338
0.524 Bulgaria brief
_Icountry_7
-0.074
0.050
-1.46
0.144
-0.173
_Icountry_8
0.225
0.060
3.76
0.000
0.108
_Icountry_9
0.089
0.062
1.42
0.154
-0.033
_Icountry_10
0.086
0.058
1.48
0.139
-0.028
_Icountry_11
0.384
0.047
8.12
0.000
0.291
_Icountry_12
-0.348
0.036
-9.57
0.000
-0.419
_Icountry_13
-0.042
0.045
-0.94
0.345
-0.130
_Icountry_14
0.098
0.037
2.64
0.008
0.025
0.171 Columbia household
_Icountry_15
0.198
0.050
3.99
0.000
0.101
0.295 Costa Rica brief
_Icountry_16
0.268
0.053
5.05
0.000
0.164
0.372 Cyprus postal
_Icountry_17
0.158
0.047
3.4
0.001
0.067
0.250 Czech Republic brief
_Icountry_18
0.313
0.046
6.74
0.000
0.222
0.404 Czech Republic postal
_Icountry_19
0.152
0.046
3.29
0.001
0.062
0.242 Germany brief
_Icountry_20
0.433
0.044
9.78
0.000
0.346
0.519 Denmark postal
_Icountry_21
0.112
0.038
2.96
0.003
0.038
0.186 Egypt household
_Icountry_22
0.248
0.043
5.71
0.000
0.163
0.333 Egypt postal
_Icountry_23
-0.017
0.048
-0.35
0.727
-0.110
_Icountry_24
0.333
0.047
7.03
0.000
0.240
0.426 Estonia brief
_Icountry_25
0.293
0.047
6.23
0.000
0.201
0.385 Finland brief
_Icountry_26
0.307
0.044
6.93
0.000
0.220
0.394 Finland postal
_Icountry_27
0.369
0.047
7.9
0.000
0.277
0.460 France brief
_Icountry_28
0.326
0.056
5.78
0.000
0.215
0.436 France postal
_Icountry_29
0.141
0.047
2.98
0.003
0.048
0.233 United Kingdom postal
_Icountry_30
0.214
0.036
5.93
0.000
0.143
0.284 Georgia household
_Icountry_31
0.344
0.049
7.06
0.000
0.249
0.440 Greece postal
_Icountry_32
0.214
0.043
4.97
0.000
0.130
_Icountry_33
-0.132
0.044
-2.99
0.003
-0.218
_Icountry_34
0.077
0.036
2.14
0.032
0.007
_Icountry_35
-0.090
0.040
-2.23
0.025
-0.169
-0.011 Indonesia postal
_Icountry_36
0.119
0.038
3.15
0.002
0.045
0.193 India household
_Icountry_37
0.101
0.051
1.98
0.048
0.001
0.201 Ireland brief
0.025 Bahrain brief
0.343 Canada postal
0.211 Canada telephone
0.200 Switzerland postal
0.477 Chile postal
-0.277 China household
0.046 China postal
0.077 Spain brief
0.299 Croatia brief
-0.045 Hungary postal
0.148 Indonesia household
_Icountry_38
0.476
0.057
8.43
0.000
0.366
0.587 Iceland brief
_Icountry_39
0.114
0.047
2.43
0.015
0.022
0.207 Italy brief
_Icountry_40
0.062
0.050
1.25
0.210
-0.035
_Icountry_41
0.260
0.046
5.68
0.000
0.170
0.160 Jordan brief
_Icountry_42
0.044
0.064
0.68
0.495
-0.081
0.168 Republic of Korea postal
_Icountry_43
0.056
0.042
1.33
0.184
-0.027
0.139 Lithuania postal
0.350 Kyrgyzstan postal
_Icountry_44
0.392
0.051
7.74
0.000
0.293
0.491 Luxembourg telephone
_Icountry_45
0.156
0.050
3.14
0.002
0.059
0.254 Latvia brief
_Icountry_46
0.210
0.050
4.19
0.000
0.112
0.308 Morocco brief
_Icountry_47
0.142
0.038
3.75
0.000
0.068
0.216 Mexico household
_Icountry_48
0.117
0.057
2.05
0.041
0.005
0.229 Malta brief
_Icountry_49
0.427
0.038
11.31
0.000
0.353
0.501 Nigeria household
_Icountry_50
0.529
0.046
11.62
0.000
0.440
0.618 Netherlands brief
_Icountry_51
0.519
0.056
9.34
0.000
0.410
0.628 Netherlands postal
_Icountry_52
-0.078
0.044
-1.78
0.075
-0.163
0.008 New Zealand postal
_Icountry_53
-0.011
0.050
-0.22
0.827
-0.109
_Icountry_54
0.309
0.048
6.44
0.000
0.215
0.403 Poland postal
_Icountry_55
0.242
0.046
5.23
0.000
0.151
0.333 Portugal brief
_Icountry_56
0.216
0.046
4.66
0.000
0.125
0.306 Romania brief
_Icountry_57
0.136
0.043
3.15
0.002
0.051
_Icountry_58
-0.279
0.047
-5.92
0.000
-0.371
0.087 Oman brief
0.221 Russian Federation brief
-0.187 Slovakia household
71
_Icountry_59
0.318
0.047
6.8
0.000
0.226
0.410 Sweden brief
_Icountry_60
0.119
0.044
2.7
0.007
0.033
0.205 Thailand postal
_Icountry_61
0.375
0.045
8.33
0.000
0.287
0.464 Trinidad and Tobago postal
_Icountry_62
0.307
0.038
8.17
0.000
0.234
0.381 Turkey household
_Icountry_63
0.333
0.040
8.36
0.000
0.255
0.411 Turkey postal
_Icountry_64
0.120
0.050
2.4
0.017
0.022
0.218 Ukraine postal
_Icountry_65
0.146
0.045
3.22
0.001
0.057
0.235 United States postal
_Icountry_66
0.062
0.050
1.25
0.212
-0.036
-2.889
0.037
-77.15
0.000
-2.962
_cons
Cut-Point 3
Coef.
Std. Err.
z
P>z
0.160 Venezuela brief
-2.815
[95% Conf. Interval]
_Iagedummy_2
0.030
0.008
3.88
0.000
0.015
_Iagedummy_3
0.072
0.009
8.21
0.000
0.055
0.046 Age 30-44
0.090 Age 45-59
_Iagedummy_4
0.115
0.010
11.68
0.000
0.096
0.135 Age 60+
sex
-0.022
0.006
-3.56
0.000
-0.033
educ
0.002
0.001
2.54
0.011
0.000
_Icountry_2
0.391
0.050
7.87
0.000
0.294
0.489 Argentina brief
_Icountry_3
0.259
0.046
5.59
0.000
0.168
0.350 Australia postal
_Icountry_4
0.217
0.046
4.68
0.000
0.126
0.308 Austria postal
_Icountry_5
0.319
0.046
6.94
0.000
0.229
0.410 Belgium brief
_Icountry_6
0.496
0.048
10.36
0.000
0.402
0.589 Bulgaria brief
_Icountry_7
-0.196
0.048
-4.08
0.000
-0.290
-0.102 Bahrain brief
_Icountry_8
0.273
0.061
4.5
0.000
0.154
0.392 Canada postal
_Icountry_9
0.251
0.061
4.09
0.000
0.131
0.371 Canada telephone
_Icountry_10
0.055
0.058
0.95
0.340
-0.058
_Icountry_11
0.480
0.048
9.99
0.000
0.386
_Icountry_12
-0.276
0.035
-7.96
0.000
-0.344
_Icountry_13
0.128
0.044
2.93
0.003
0.042
0.213 China postal
_Icountry_14
0.253
0.036
7.07
0.000
0.183
0.323 Columbia household
_Icountry_15
0.373
0.049
7.6
0.000
0.277
0.470 Costa Rica brief
_Icountry_16
0.206
0.053
3.89
0.000
0.102
0.310 Cyprus postal
-0.010 Male
0.003 Education (yrs)
0.168 Switzerland postal
0.574 Chile postal
-0.208 China household
_Icountry_17
0.267
0.046
5.83
0.000
0.177
0.357 Czech Republic brief
_Icountry_18
0.454
0.047
9.69
0.000
0.362
0.546 Czech Republic postal
_Icountry_19
0.337
0.046
7.36
0.000
0.247
0.426 Germany brief
_Icountry_20
0.337
0.044
7.63
0.000
0.250
0.423 Denmark postal
_Icountry_21
0.294
0.037
8.05
0.000
0.223
0.366 Egypt household
_Icountry_22
0.376
0.043
8.78
0.000
0.292
0.460 Egypt postal
_Icountry_23
0.141
0.046
3.06
0.002
0.051
0.231 Spain brief
_Icountry_24
0.364
0.047
7.68
0.000
0.271
0.457 Estonia brief
_Icountry_25
0.344
0.047
7.4
0.000
0.253
0.435 Finland brief
_Icountry_26
0.329
0.044
7.4
0.000
0.242
0.416 Finland postal
_Icountry_27
0.293
0.046
6.3
0.000
0.202
0.384 France brief
_Icountry_28
0.206
0.057
3.64
0.000
0.095
0.317 France postal
_Icountry_29
0.305
0.047
6.53
0.000
0.213
0.396 United Kingdom postal
_Icountry_30
0.345
0.035
9.92
0.000
0.277
0.413 Georgia household
_Icountry_31
0.453
0.049
9.19
0.000
0.356
0.549 Greece postal
_Icountry_32
0.337
0.043
7.94
0.000
0.254
_Icountry_33
0.013
0.042
0.32
0.752
-0.069
_Icountry_34
0.168
0.035
4.83
0.000
0.100
_Icountry_35
-0.520
0.039
-13.47
0.000
-0.596
_Icountry_36
0.064
0.036
1.76
0.078
-0.007
_Icountry_37
0.286
0.051
5.62
0.000
0.186
0.421 Croatia brief
0.095 Hungary postal
0.236 Indonesia household
-0.445 Indonesia postal
0.136 India household
0.385 Ireland brief
_Icountry_38
0.445
0.058
7.74
0.000
0.333
0.558 Iceland brief
_Icountry_39
0.104
0.046
2.28
0.023
0.015
0.194 Italy brief
_Icountry_40
-0.025
0.048
-0.53
0.598
-0.120
0.069 Jordan brief
72
_Icountry_41
0.083
0.045
1.84
0.066
-0.005
_Icountry_42
-0.083
0.062
-1.34
0.181
-0.205
0.172 Kyrgyzstan postal
0.039 Republic of Korea postal
_Icountry_43
0.051
0.041
1.24
0.213
-0.029
0.131 Lithuania postal
_Icountry_44
0.440
0.051
8.63
0.000
0.340
_Icountry_45
0.267
0.049
5.43
0.000
0.171
0.363 Latvia brief
_Icountry_46
0.207
0.049
4.22
0.000
0.111
0.303 Morocco brief
_Icountry_47
0.213
0.037
5.82
0.000
0.141
0.285 Mexico household
_Icountry_48
0.041
0.056
0.73
0.464
-0.068
_Icountry_49
0.132
0.037
3.63
0.000
0.061
0.204 Nigeria household
_Icountry_50
0.573
0.046
12.47
0.000
0.483
0.663 Netherlands brief
_Icountry_51
0.604
0.058
10.47
0.000
0.491
0.717 Netherlands postal
_Icountry_52
0.107
0.042
2.55
0.011
0.025
_Icountry_53
-0.166
0.048
-3.49
0.000
-0.259
0.540 Luxembourg telephone
0.149 Malta brief
0.189 New Zealand postal
-0.073 Oman brief
_Icountry_54
0.354
0.048
7.35
0.000
0.260
0.449 Poland postal
_Icountry_55
0.121
0.045
2.67
0.008
0.032
0.210 Portugal brief
_Icountry_56
0.225
0.045
4.96
0.000
0.136
0.314 Romania brief
_Icountry_57
0.254
0.042
6.05
0.000
0.172
_Icountry_58
-0.091
0.044
-2.05
0.040
-0.178
_Icountry_59
0.357
0.046
7.71
0.000
0.267
0.448 Sweden brief
_Icountry_60
0.210
0.043
4.89
0.000
0.126
0.294 Thailand postal
_Icountry_61
0.423
0.045
9.39
0.000
0.335
0.511 Trinidad and Tobago postal
_Icountry_62
0.400
0.037
10.92
0.000
0.328
0.471 Turkey household
_Icountry_63
0.363
0.039
9.24
0.000
0.286
0.440 Turkey postal
_Icountry_64
0.235
0.049
4.75
0.000
0.138
0.332 Ukraine postal
_Icountry_65
0.230
0.045
5.15
0.000
0.142
0.317 United States postal
_Icountry_66
_cons
Cut-Point 4
0.204
0.049
4.15
0.000
0.107
-2.053
0.036
-56.98
0.000
-2.123
Coef.
Std. Err.
z
P>z
0.337 Russian Federation brief
-0.004 Slovakia household
0.300 Venezuela brief
-1.982
[95% Conf. Interval]
_Iagedummy_2
0.023
0.010
2.41
0.016
0.004
0.042 Age 30-44
_Iagedummy_3
0.075
0.011
6.96
0.000
0.054
0.096 Age 45-59
_Iagedummy_4
0.101
0.012
8.44
0.000
0.078
sex
-0.030
0.007
-4.06
0.000
-0.044
educ
0.003
0.001
3.57
0.000
0.001
0.125 Age 60+
-0.015 Male
0.005 Education (yrs)
_Icountry_2
0.257
0.061
4.24
0.000
0.138
0.376 Argentina brief
_Icountry_3
0.374
0.056
6.65
0.000
0.264
0.484 Australia postal
_Icountry_4
0.195
0.055
3.55
0.000
0.087
0.303 Austria postal
_Icountry_5
0.154
0.055
2.81
0.005
0.047
0.262 Belgium brief
_Icountry_6
0.328
0.057
5.72
0.000
0.216
0.441 Bulgaria brief
_Icountry_7
-0.099
0.057
-1.75
0.080
-0.210
0.012 Bahrain brief
_Icountry_8
0.318
0.074
4.29
0.000
0.173
0.464 Canada postal
_Icountry_9
0.209
0.075
2.79
0.005
0.062
0.355 Canada telephone
_Icountry_10
0.053
0.068
0.77
0.442
-0.081
_Icountry_11
0.206
0.056
3.68
0.000
0.096
_Icountry_12
-0.091
0.041
-2.2
0.028
-0.172
_Icountry_13
0.353
0.053
6.6
0.000
0.248
_Icountry_14
0.000
0.043
0
0.997
-0.084
_Icountry_15
0.125
0.059
2.13
0.033
0.010
0.187 Switzerland postal
0.316 Chile postal
-0.010 China household
0.458 China postal
0.083 Columbia household
0.241 Costa Rica brief
_Icountry_16
0.238
0.064
3.74
0.000
0.114
0.363 Cyprus postal
_Icountry_17
0.302
0.056
5.4
0.000
0.193
0.412 Czech Republic brief
_Icountry_18
0.529
0.057
9.21
0.000
0.416
0.641 Czech Republic postal
_Icountry_19
0.331
0.056
5.91
0.000
0.221
0.441 Germany brief
_Icountry_20
0.312
0.053
5.92
0.000
0.209
0.415 Denmark postal
_Icountry_21
0.177
0.044
4.04
0.000
0.091
0.263 Egypt household
_Icountry_22
0.253
0.051
4.94
0.000
0.152
0.353 Egypt postal
73
_Icountry_23
0.137
0.056
2.43
0.015
0.027
0.247 Spain brief
_Icountry_24
0.408
0.058
7.06
0.000
0.295
0.521 Estonia brief
_Icountry_25
0.334
0.057
5.87
0.000
0.222
0.445 Finland brief
_Icountry_26
0.424
0.054
7.82
0.000
0.317
0.530 Finland postal
_Icountry_27
0.136
0.056
2.45
0.014
0.027
0.245 France brief
_Icountry_28
0.323
0.069
4.7
0.000
0.188
0.457 France postal
_Icountry_29
0.407
0.057
7.09
0.000
0.294
0.519 United Kingdom postal
_Icountry_30
0.148
0.042
3.55
0.000
0.066
0.229 Georgia household
_Icountry_31
0.452
0.060
7.56
0.000
0.335
0.570 Greece postal
_Icountry_32
0.104
0.051
2.05
0.040
0.005
_Icountry_33
-0.060
0.050
-1.2
0.229
-0.157
_Icountry_34
0.091
0.042
2.18
0.029
0.009
_Icountry_35
-0.278
0.045
-6.11
0.000
-0.367
_Icountry_36
0.072
0.044
1.66
0.097
-0.013
_Icountry_37
0.227
0.063
3.59
0.000
0.103
0.203 Croatia brief
0.038 Hungary postal
0.172 Indonesia household
-0.189 Indonesia postal
0.158 India household
0.351 Ireland brief
_Icountry_38
0.425
0.070
6.1
0.000
0.288
0.561 Iceland brief
_Icountry_39
0.143
0.056
2.57
0.010
0.034
0.253 Italy brief
_Icountry_40
-0.147
0.056
-2.64
0.008
-0.256
_Icountry_41
0.075
0.054
1.38
0.168
-0.032
_Icountry_42
0.181
0.076
2.39
0.017
0.033
0.329 Republic of Korea postal
_Icountry_43
0.133
0.049
2.72
0.007
0.037
0.228 Lithuania postal
-0.038 Jordan brief
0.182 Kyrgyzstan postal
_Icountry_44
0.227
0.061
3.7
0.000
0.107
0.347 Luxembourg telephone
_Icountry_45
0.238
0.060
3.96
0.000
0.120
0.356 Latvia brief
_Icountry_46
-0.105
0.057
-1.83
0.067
-0.216
_Icountry_47
0.116
0.044
2.64
0.008
0.030
_Icountry_48
0.052
0.066
0.79
0.431
-0.078
_Icountry_49
0.289
0.045
6.46
0.000
0.202
0.377 Nigeria household
_Icountry_50
0.199
0.054
3.66
0.000
0.092
0.305 Netherlands brief
_Icountry_51
0.559
0.069
8.1
0.000
0.424
0.694 Netherlands postal
_Icountry_52
0.193
0.050
3.84
0.000
0.095
_Icountry_53
-0.132
0.056
-2.37
0.018
-0.240
_Icountry_54
0.413
0.059
7.04
0.000
0.298
_Icountry_55
0.063
0.055
1.15
0.251
-0.045
0.171 Portugal brief
_Icountry_56
0.151
0.055
2.75
0.006
0.043
0.258 Romania brief
_Icountry_57
0.089
0.051
1.76
0.079
-0.010
_Icountry_58
0.085
0.054
1.56
0.118
-0.021
_Icountry_59
0.261
0.055
4.71
0.000
0.152
0.370 Sweden brief
_Icountry_60
0.263
0.053
4.97
0.000
0.159
0.367 Thailand postal
_Icountry_61
0.414
0.054
7.62
0.000
0.308
0.521 Trinidad and Tobago postal
_Icountry_62
0.282
0.044
6.43
0.000
0.196
0.368 Turkey household
_Icountry_63
0.272
0.048
5.71
0.000
0.178
0.365 Turkey postal
_Icountry_64
0.264
0.059
4.45
0.000
0.148
0.381 Ukraine postal
_Icountry_65
0.310
0.054
5.75
0.000
0.204
0.416 United States postal
_Icountry_66
_cons
0.007 Morocco brief
0.203 Mexico household
0.182 Malta brief
0.292 New Zealand postal
-0.023 Oman brief
0.527 Poland postal
0.188 Russian Federation brief
0.191 Slovakia household
0.059
0.058
1.01
0.310
-0.055
-1.008
0.043
-23.68
0.000
-1.092
-0.925
0.174 Venezuela brief
0.242
0.005
49.67
0.000
0.232
0.251
s
_cons
74