U.S. Department of Health and Human Services

National Institutes of Health

NATIONAL INSTITUTE ON AGING

U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

census.gov

Shades of Gray: A Cross-Country Study of Health 

and Well-Being of the Older Populations in 

SAGE Countries, 2007–2010

International Population Reports

By Wan He, Mark N. Muenchrath, and Paul Kowal

Issued May 2012

P95/12-01
Acknowledgments

This report was prepared by Wan He and Mark N. Muenchrath

of the U.S. Census Bureau, and Paul Kowal of the World Health 

Organization (WHO). General direction was provided by Peter O. 

Way, former Assistant Division Chief, International Programs Center 

for Demographic and Economic Studies, Population Division. 

Enrique J. Lamas, Chief, Population Division, provided overall 

direction. Additional direction was provided by Loraine A. West, 

Acting Chief, Aging Studies Branch, Population Division, Census 

Bureau, and Somnath Chatterji, Chief, Multi-Country Studies Unit, 

Department of Health Statistics and Information Systems, WHO.

The authors are grateful to many people both within and outside 

the Census Bureau who have generously provided insight and 

assistance to the making of this report. The authors give special 

thanks to Mary Beth Kennedy, Andrea S. Miles, and Samantha 

S. Cole for providing data assistance and verifying various materials; and John T. Fitzwater, Geographic Studies Branch, Population 

Division, for creating the world map. Nirmala Naidoo, WHO, 

provided critical assistance in survey and data related information 

as well as corroborating data analysis. Jennifer Stewart Williams 

provided verification of SAS programming.

Reviewers from Census Bureau’s Population Division and National 

Institute on Aging (NIA) provided valuable comments and constructive suggestions, David E. Bloom, Eileen M. Crimmins, 

Daniel Goodkind, James P. Smith, Richard M. Suzman, and 

Stephen M. Tollman. The authors are particularly thankful for 

Bashiruddin Ahmed for his thorough review.

The sampling review was conducted by Joseph Croos, under the 

direction of Stephen E. Ash, Chief, Victimization and Expenditures 

Branch, Demographic Statistical Methods Division. 

Christine E. Geter, Linda Chen, Musbaw Alawiye, and 

Benjamin G. Dunlap, of the Census Bureau’s Administrative and 

Customer Services Division, Francis Grailand Hall, Chief, provided publication and printing management, graphics design and 

composition, and editorial review for print and electronic media. 

General direction and production management were provided by 

Claudette E. Bennett, Assistant Division Chief.

Funding for the production of this report was provided by the NIA’s 

Division of Behavioral and Social Research, Richard M. Suzman, 

Director.
Shades of Gray: A Cross-Country Study 

of Health and Well-Being of the Older 

Populations in SAGE Countries, 

2007–2010

International Population Reports

Issued May 2012

P95/12-01

U.S. Department of Commerce

John E. Bryson,

Secretary

Rebecca M. Blank,

Deputy Secretary

Economics and Statistics Administration

Vacant,

Under Secretary

for Economic Affairs

U.S. CENSUS BUREAU

Robert M. Groves,

Director
ECONOMICS

AND STATISTICS

ADMINISTRATION

SUGGESTED CITATION

Wan He, Mark N. Muenchrath, and 

Paul Kowal,

U.S. Census Bureau,

Shades of Gray: A Cross-Country 

Study of Health and Well-Being of 

the Older Populations in

SAGE Countries, 2007–2010,

U.S. Government Printing Office,

Washington, DC, 2012

Economics 

and Statistics

Administration

Vacant,

Under Secretary for 

Economic Affairs

U.S. CENSUS BUREAU

Robert M. Groves,

Director

Thomas L. Mesenbourg,

Deputy Director and 

Chief Operating Officer

Nancy A. Potok,

Associate Director

for Demographic Programs

Enrique J. Lamas,

Chief, Population Division
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 iii

Contents

Text

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Aging in SAGE Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Demographic and Socioeconomic Characteristics . . . . . . . . . . . . . . . 7

Health State and Chronic Conditions . . . . . . . . . . . . . . . . . . . . . . . . 9

Risk Factors and Preventive Health Behaviors . . . . . . . . . . . . . . . . . . 13

Disability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Life Satisfaction and Quality of Life . . . . . . . . . . . . . . . . . . . . . . . . . 21

Depression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Health Care Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Summary and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Sources of the Data and Accuracy of the Estimates . . . . . . . . . . . . . 31

Contact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Text Figures

1. SAGE Countries—China, Ghana, India, Mexico, Russia, and

 South Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2. Healthy Life Expectancy (HALE) and Life Expectancy (LE) at

 Birth by Sex: 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3. Healthy Life Expectancy (HALE) and Life Expectancy (LE) at

 Age 60 by Sex: 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

4. Widowhood for Population Aged 70 and Over by Sex:

 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

5. Mean Health Scores for Population Aged 20 and Over by

 Age: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

6. Top Three Chronic Conditions for Population Aged 50 and

 Over by Age: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

7. Behavioral Risk Factors for Population Aged 50 and Over by

 Sex: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

8. Preventive Health Behaviors Among Population Aged 50 and

 Over by Urban/Rural Residence: 2007–2010 . . . . . . . . . . . . . . 16

9. Percent Distribution of WHODASi for Population Aged 50 and

 Over: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

10. Percentage Satisfied With Life Among Population Aged 50 and

 Over by Urban/Rural Residence: 2007–2010 . . . . . . . . . . . . . . 21

11. Percent Distribution of WHOQOL for Population Aged 50 and

 Over: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

12. Percentage Feeling Depressed in Last 30 Days for Population

 Aged 50 and Over for China and India: 2007–2010 . . . . . . . . . 24

13. Percentage Feeling Depressed in Last 30 Days for Married and

 Widowed Populations Aged 50 and Over: 2007–2010 . . . . . . . 24

14. Sources for Outpatient Care Payment for People Aged 50 and

 Over: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
iv Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Text Tables

1. Population Aged 50 and Over for SAGE Countries: 2010–2050. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2. Selected Demographic and Socioeconomic Characteristics of Population Aged 50 and

 Over: 2007–2010. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3. Mean Health Scores for Population Aged 50 and Over by Selected Chronic Conditions: 2007–2010. . . . . . 12

4. Percentage With Disability for Population Aged 70 and Over by Sex, Residence, and Type: 2007–2010. . . . 17

5. Percentage Depressed by Chronic Condition Status for Population Aged 50 and Over: 2007–2010. . . . . . 23

6. Odds Ratios Predicting Likelihood to Receive Outpatient Care for Population Aged 50 and

 Over: 2007–2010. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Definition Boxes

HALE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Health State Score. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Risk Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

ADL and IADL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

WHODAS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Composite Cognition Variable. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

WHOQOL. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Depression. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Composite Wealth Variable. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Appendixes

Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1

Tables

A-1. Selected Demographic and Socioeconomic Characteristics for Population Aged 50 and Over by

 Age, Sex, and Urban/Rural Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1

A-2. General Health and Chronic Conditions for Population Aged 50 and Over by Age, Sex, and

 Urban/Rural Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-4

A-3. Behavioral Risk Factors for Population Aged 50 and Over by Age, Sex, and Urban/Rural

 Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-6

A-4. Disability for Population Aged 50 and Over by Age, Sex, and Urban/Rural Residence:

 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-9

A-5. Life Satisfaction for Population Aged 50 and Over by Age, Sex, and Urban/Rural

 Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-12

A-6. Subjective Well-Being for Population Aged 50 and Over by Age, Sex, and Urban/Rural

 Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-15

A-7. Health Care Utilization in Last 12 Months for Population Aged 50 and Over by Age, Sex, and

 Urban/Rural Residence: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-17
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 v

Appendix B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-1

Table

B-1. Standard Error for Selected Demographic and Socioeconomic Characteristics of Population Aged

 50 and Over: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-1

Appendix C. SAGE Surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-1

Selection of SAGE Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-1

SAGE Sample Size, Response Rate, and Weighting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-1

Validation of SAGE Data on Age, Sex, and Urban/Rural Residence Using Data From IDB, UN, and CIA . . . . C-3

Sampling and Representativeness of the SAGE Data Compared to LASI and Other Surveys . . . . . . . . . . . . C-3

Issues of Vignettes and Data Comparability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-5

Tables

C-1. World Bank List of Economies—SAGE Countries: 2007–2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-1

C-2. SAGE Sample Size and Response Rate by Age: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-2

C-3. Comparison of SAGE Data on Age, Sex, and Urban/Rural Residence for Population Aged 50 and

 Over With Data From IDB, UN, and CIA: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-4

C-4. India Respondent Profiles From LASI, India NSS, IHDS, WHS, and SAGE . . . . . . . . . . . . . . . . . . . . . . . C-5

C-5. Comparison of Sex Ratio and Household Size Between SAGE and China NSS . . . . . . . . . . . . . . . . . . . C-6

C-6. Question Wording, Response Categories, and Type of Administration on Mobility Difficulty in

 HRS 2007, SHARE 2006, and SAGE 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C-8

Figures

C-1. Comparisons of Vignette Ratings for Mobility From HRS and SHARE . . . . . . . . . . . . . . . . . . . . . . . . . C-7

C-2. Comparisons of Vignette Ratings for Mobility for SAGE Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . C-7
1 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Introduction

The world’s population is aging, primarily as

a function of declining fertility, coupled with

increasing life expectancy. Aging is occurring not

only in high-income countries but in middle- and

low-income countries as well.1 Moreover, the speed

of aging in middle- and low-income countries will

outpace that of the high-income countries (Kinsella

and He, 2009). Although considerable attention has 

been paid to the aging of populations around the 

world, the vast majority of this attention and related 

research has focused on higher-income countries. Yet 

about 65 percent of the world’s population 60 years 

and older lived in less developed countries in 2010,

and this proportion is projected to be 80 percent by 

the year 2050 (U.S. Census Bureau, 2012). 

The health status of the aging population is essential 

not only to those who comprise this age group, but 

also to the broader population because of the impacts 

on social and economic systems. As the older population grows not only in size, but more importantly in 

their proportion of the total population, the potential 

implications for society will be increasingly salient. 

Understanding differences in the health of older 

populations across and within countries is critical 

for planning health care services and social support 

systems, and for designing population health policies. 

However, relatively few lower-income countries have 

the age-specific health and disability data necessary 

to determine basic population health parameters. Even 

less understood is which morbidity trajectory their 

respective aging population is following—expansion 

of morbidity, where people are living longer with more 

disease and disability (Gruenberg, 1977; Schneider and 

Brody, 1983); compression of morbidity, with delays 

in the age at onset and progression of disease (Fries, 

1980, 2003); or a dynamic equilibrium where disability 

increases but is not as severe (Manton, 1982; Manton, 

Gu, and Lamb, 2006).

1 The World Bank classifies member economies into low income, 

lower-middle income, upper-middle income, and high income, according to gross national income per capita. For more information on the 

classifications as of the year 2010, see World Bank, 2011.

A major challenge in research on health differences 

across countries at older ages involves measurement of health outcomes (Banks and Smith, 2011; 

Crimmins, Garcia, and Kim, 2010; National Research 

Council, 2001). Self-reported health remains a cornerstone of health and epidemiological studies, but 

concerns about incomparability of self-reported health 

across studies and over time remains a problem for 

monitoring population health trends (Salomon, et al., 

2009). In recent decades, a number of longitudinal or 

cross-national surveys, including the U.S. Health and 

Retirement Study (HRS), the Study on Health, Ageing, 

and Retirement in Europe (SHARE), and the World 

Health Survey (WHS), used the anchoring vignette 

methodologies to improve cross-country calibration 

of self-reported health. However, adjusting for these 

reporting biases across the various higher and lower 

income countries remains problematic. More recently, 

in response to this challenge, aging research studies 

have been adding objective health measures in an 

effort to improve estimates of the true levels of health. 

As part of this greater effort, the World Health 

Organization’s (WHO) Study on global AGEing and

adult health (SAGE) is working to improve measurement strategies across countries, while recognizing 

the need for further exploration to understand what 

underpins cross-country health differences (Kowal, 

et al., 2010). SAGE was conducted in six countries—

China, Ghana, India, Mexico, Russia, and South 

Africa—across four different world regions (Figure 1).2

In addition to the consideration of geographic range 

and population size, these countries were representative of low- to upper-middle income countries and 

were at different stages of the demographic and 

epidemiological transitions (see Appendix C for more 

information on selection of SAGE countries).

2 The four world regions are based on United Nations classifications—Africa (Ghana, South Africa), Asia (China, India), Europe (Russia), 

and Latin America and the Caribbean (Mexico).
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 2

This report uses SAGE Wave 1 data (2007–2010) and 

provides an overview of the “graying” populations 

in these six middle- and low-income countries.3, 4

Analysis in this report focuses on comparisons across 

all six countries, or a subset of these countries, 

leaving in-depth, country-specific investigations to 

future reports. The report starts with Aging in SAGE 

Countries, which offers an overview of the aging 

process in these six countries, using the U.S. Census 

Bureau’s International Data Base (IDB), population projections data from the United Nations, and health data 

from the WHO. The report then presents findings from 

the SAGE data in the following sections: Demographic 

and Socioeconomic Characteristics, Health State and 

Chronic Conditions, Risk Factors and Preventive Health 

3 The SAGE Wave 1 data were collected in China in 2008–2010, 

Ghana in 2007–2008, India in 2007–2008, Mexico in 2010, Russia in 

2007–2010, and South Africa in 2007–2008. 4 According to the World Bank (2011), during 2007–2010, China 

was classified as a lower-middle income country; Ghana as low income; 

India as low to lower-middle income; and Mexico, Russia, and South 

Africa as upper-middle income countries.

Behaviors, Disability, Life Satisfaction and Quality 

of Life, Depression, and Health Care Utilization. The 

health variables are cross-examined by age (50–69, 

70 and older), sex, and urban/rural residence. The 

Summary and Discussion section provides conclusions from the SAGE data and also raises questions 

for future research. SAGE survey related information 

is included in the final section Sources of the Data and 

Accuracy of the Estimates.

The analysis in this report is based on self-reported 

responses. Estimates provided in this report are 

weighted. All comparative statements in the text

have undergone statistical testing and are significant

at the 90 percent confidence level unless noted 

otherwise. Note that not all comparisons shown in the 

figures and tables have undergone statistical testing 

and the differences between these estimates may not 

be statistically significant. Caution is needed when 

comparing data presented in the figures, text tables, 

and appendix tables.

Figure 1.

SAGE Countries: China, Ghana, India, Mexico, Russia, and South Africa

Source: U.S. Census Bureau, 2012. Map created using international boundaries from U.S. Department of State.

Russia

Russia

China

Me India xico

South Africa

Ghana
3 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Aging in SAGE Countries

While the older population is often defined as people 

aged 60 and older or 65 and older, these age cut-offs 

may not be as relevant for less developed countries 

where life expectancy at birth as of 2010 was 12 years 

lower, on average, than in more developed countries. 

Furthermore, the majority of the older population—

whether it is defined as 50-, 60-, or 70-plus years of 

age—reside in less developed countries (U.S. Census 

Bureau, 2012). 

Growth of the 50-plus population. People 50 years 

and older represented 21 percent of the combined 2010 

SAGE six-country total population and are projected 

to reach almost 40 percent in 2050, increasing from 

598 million to 1.3 billion (U.S. Census Bureau, 2012). 

More specifically, for each of the SAGE countries except 

Russia, the proportion aged 50 and over of the total 

population is projected to about double from 2010 to 

2050 (Table 1). Russia’s population aged 50 and older is 

projected to experience slower growth than other SAGE 

countries, in part because it already represented a third 

(33 percent) of total population in 2010. 

In all SAGE countries, those aged 50 and over in 

2007–2010 were also part of the post-World War II 

baby boom that resulted from peacetime following a 

protracted period of war. Additional factors contributed to the baby boom. In India, rapidly falling infant 

mortality in the early 1950s coupled with a lagging 

fertility decline, produced a large birth cohort (Bloom, 

2011). In China and Russia, government programs 

also played a role—China’s land reform of 1950–1951 

redistributed land to tenant farmers and the landless 

population, thereby creating demand for more family 

labor to farm the newly acquired land (Banister, 1987). 

Russia’s child-allowance payments offered by the former Soviet Union government in the 1950s encouraged 

couples to have more children (Heer, 1977).

Table 1.

Population Aged 50 and Over for SAGE Countries: 2010–2050

(Numbers in thousands)

2010 2020 2030 2040 2050

Percent- Percent- Percent- Percent- PercentCountry age age age age age 

of total of total of total of total of total 

Number population Number population Number population Number population Number population

China . . . . . . . . . . . 329,714 24 .8 459,245 33 .2 548,582 39 .4 622,395 45 .8 636,408 48 .8

Ghana . . . . . . . . . . 2,662 10 .9 3,957 13 .7 5,665 17 .2 8,126 22 .0 10,816 26 .9

India . . . . . . . . . . . . 191,853 16 .4 264,913 20 .0 355,586 24 .3 448,223 28 .5 540,424 32 .6

Mexico . . . . . . . . . . 19,508 17 .3 27,969 22 .4 37,837 28 .0 46,978 32 .8 54,809 37 .1

Russia . . . . . . . . . . 46,579 33 .4 48,524 36 .7 50,141 40 .4 54,024 46 .4 49,932 45 .7

South Africa . . . . . . 8,029 16 .3 9,067 18 .7 9,716 19 .9 11,587 23 .6 13,585 27 .5

Source: U S Census Bureau, International Data Base, accessed on February 27, 2012 . . .
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 4

Furthermore, 50 years old in some SAGE countries 

signifies qualification for old-age social insurance 

programs, unlike in many developed countries where 

the eligibility age is often 65 or older. For example, in 

China, the qualifying age for basic pension insurance 

is 60 years for men, 60 for professional women, 55 

for nonprofessional salaried women, and 50 for other 

categories of women; in India, the eligibility age for 

the pension scheme is 58 years; and in Russia, it is 

60 years for men and 55 for women (Social Security 

Administration, 2010b, 2011a).1 Moreover, in China, 

early retirement has been used to deal with bankruptcies, resulting in involuntary exit from the labor force 

for some men and women in their forties (Giles, Wang, 

and Cai, 2011).

Median age. The median age of a country is an indicator of population aging and is projected to continue 

increasing in all six SAGE countries. Russia’s median 

age (39 years as of 2010) is currently the highest 

among the six countries (U.S. Census Bureau, 2012). 

China follows with a median age of 35 years, and the 

remaining four countries are all less than 27 years. 

China is projected to pass Russia in 2050 with its 

median age projected to reach 49 years, with Russia 

following closely behind at 46 years. Ghana and South 

Africa are projected to remain the youngest at about 

34 years. 

Life expectancy and healthy life expectancy. 

Population health disparities across countries have 

been the subject of much debate, followed by scrutiny of the determinants behind these differences 

(Centers for Disease Control and Prevention, 2007; 

National Institute on Aging, 2007). Examination of life 

expectancies (LE) at birth and at the age of 60 illustrates differences in population health across the six 

SAGE countries. For the period 2010–2015, Mexico’s 

1 The eligibility age for old-age social insurance for Ghana is 60; 

Mexico, 65; and South Africa, 60 (Social Security Administration, 

2010a, 2011b).

LE at birth is estimated to be the highest at 77 years 

old, followed by China (74 years), Russia (68 years), 

India (65 years), Ghana (58 years), and South Africa 

(53 years) (United Nations, 2009). Life expectancy at 

the age of 60 for 2010–2015 is highest in Mexico (22 

years), followed by China (20 years), Ghana, India, and 

Russia (17 years), and South Africa (16 years) (ibid.). 

Healthy life expectancy (HALE) is the number of 

healthy years, free from disability, that a person can 

expect to live given the current trends in deaths and 

diseases (WHO, 2008a). According to the WHO 2007 

estimates of HALE at birth for both sexes combined, 

Mexico again led these six SAGE countries, with China 

following closely, then Russia, India, Ghana, and 

South Africa (67, 66, 60, 56, 50, and 48 years, respectively). HALE at the age of 60 for these six countries 

had the same order—Mexico, China, Russia, India, 

Ghana, and South Africa (16, 15, 13, 12, 11, and 10 

years, respectively). The impacts of HIV/AIDS in South 

DEFINITION OF HALE

HALE, healthy life expectancy, is a population 

health indicator that combines mortality and 

health into a single health state utility score. 

The difference between life expectancy and 

HALE is the average number of years lived 

in ill health over a person’s life. Two sets of 

time-series data are required to generate HALE 

measures: (1) age-specific mortality rates; and 

(2) age-specific measures of average health 

status (Berthelot, 2003). WHO’s Model Life Tables 

were used for the mortality component (WHO, 

2006), while death registration data, populationbased epidemiological studies, disease registers, 

and notification systems were used to estimate 

the health status component (WHO, 2008a).
5 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Africa, widespread malaria in Ghana, and alcoholism in 

Russian men are apparent in their lower LE and HALE.

The differences in HALE and LE at birth by sex for 

the SAGE countries in 2007 are illustrated in Figure 2. 

Across countries, HALE at birth ranged from a low of 

47 years for South African men, reflecting the impacts 

of HIV/AIDS, to a high of 69 years for Mexican women. 

The within-country sex gap for HALE was largest in 

Russia, with women enjoying 11 additional years of 

good health than men. Figure 3 shows the HALE and 

LE at the age of 60 by sex. The differences in HALE at 

the age of 60 favored women over men by 1 year in 

Ghana, India, and South Africa, 2 years in Mexico and 

China, and 3 years in Russia. The highest HALE at the 

Figure 2.

Healthy Life Expectancy (HALE) and Life Expectancy (LE) at Birth by Sex: 2007

Note: Healthy Life Expectancy (HALE) is the number of healthy years, free from disability, that a person can expect to live given the 

current trends in deaths and diseases.

Sources: United Nations, 2009, World Population Prospects: The 2008 Revision; World Health Organization, 2008, The Global Burden 

of Disease: 2004 Update.

Years

0 10 20 30 40 50 60 70 80

South Africa

Russia

Mexico

India

Ghana

China

Male HALE Male LE

Female HALE Female LE
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 6

age of 60 was found among Mexican women (17 years) 

and was lowest among South African men (only 10 

years).

The burden of disease. Population aging is likely 

to be accompanied by an increase in chronic disease 

burden. It is estimated that 44 percent of the total 

burden of disease in China in 2004 was from people 

aged 45 and older, and this figure is projected to 

increase to over 65 percent by the year 2030 (Chatterji, 

et al., 2008). The same figure for India in 2004 was 26 

percent, expected to rise to 46 percent by 2030. The 

recently updated Global Burden of Disease estimates 

indicate that among SAGE countries, the highest agestandardized overall disease burden per capita was in 

Ghana followed by South Africa (WHO, 2008a). Mexico 

and Russia were next with similar levels of per capita 

burden, followed by India and China at lower levels.

Figure 3.

Healthy Life Expectancy (HALE) and Life 

Expectancy (LE) at Age 60 by Sex: 2007

Note: Healthy Life Expectancy (HALE) is the number of healthy years, 

free from disability, that a person can expect to live given the current 

trends in deaths and diseases.

Sources: United Nations, 2009, World Population Prospects: The 2008 

Revision; World Health Organization, 2008, The Global Burden of 

Disease: 2004 Update.

Years

0 5 10 15 20 25

South Africa

Russia

Mexico

India

Ghana

China

Male HALE Male LE

Female HALE Female LE
7 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Demographic and Socioeconomic Characteristics

The report now focuses on findings from SAGE. The 

analysis in this report defines the older population as 

those aged 50 and over and the oldest old as 70 and 

over. SAGE data showed that the demographic and 

socioeconomic characteristics of the older population 

differed widely across the six countries (Table 2).1

While the age structure of each country was unique, 

1 The estimates from the SAGE sample may differ from population census results or estimates based on other survey samples. For 

sampling frame, weighting, and sampling and nonsampling error, see 

the Sources of the Data and Accuracy of the Estimates section. The 

standard errors for estimates listed in Table 2 are available in Table B-1. 

there were some similarities across countries. About 

half of the older population was younger than 60 years 

old in China, Mexico, and South Africa, reflecting a 

relatively younger age structure than the other SAGE 

countries. Russia stood out with a skewed distribution by sex; older women made up 61 percent of the 

total 50-and-older population. India remained largely 

a rural society, with more than two-thirds residing in 

rural areas; in contrast, the majority of older Mexicans, 

Russians, and South Africans lived in urban areas.

Table 2.

Selected Demographic and Socioeconomic Characteristics of Population Aged 50 and 

Over: 2007–2010

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Characteristic

Country

China Ghana India Mexico Russia

South 

Africa

Age

50 to 59 . . . . . . . . . . . . . . . . . . . . . . . . . . 50 .7 40 .4 44 .1 48 .1 45 .5 49 .9

60 to 69 . . . . . . . . . . . . . . . . . . . . . . . . . . 27 .5 27 .3 30 .3 25 .6 24 .7 30 .6

70 and older . . . . . . . . . . . . . . . . . . . . . . .

Sex

21 .9 32 .3 25 .6 26 .4 29 .8 19 .5

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 .9 49 .7 50 .5 46 .8 38 .9 44 .1

Female . . . . . . . . . . . . . . . . . . . . . . . . . . .

Residence

50 .1 50 .3 49 .5 53 .2 61 .1 55 .9

Urban . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 .3 40 .6 31 .2 78 .8 73 .2 64 .9

Rural . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Marital Status

55 .7 59 .4 68 .8 21 .2 26 .8 35 .1

Never married . . . . . . . . . . . . . . . . . . . . . 1 .1 1 .3 0 .7 7 .0 2 .7 14 .3

Married/cohabiting . . . . . . . . . . . . . . . . . . 85 .6 60 .6 74 .9 73 .0 58 .2 55 .9

Separated/divorced . . . . . . . . . . . . . . . . . 1 .6 12 .2 0 .5 4 .5 9 .9 5 .9

Widowed . . . . . . . . . . . . . . . . . . . . . . . . .

Educational Attainment

11 .7 25 .9 23 .9 15 .5 29 .1 23 .9

No education . . . . . . . . . . . . . . . . . . . . . . 42 .4 64 .3 61 .7 55 .6 1 .9 48 .6

Primary completed . . . . . . . . . . . . . . . . . 20 .6 10 .9 14 .8 24 .0 5 .5 22 .7

Secondary completed . . . . . . . . . . . . . . . 20 .1 4 .0 9 .9 9 .9 20 .1 14 .5

High school completed . . . . . . . . . . . . . . 12 .6 17 .1 8 .5 2 .4 53 .9 8 .4

College completed . . . . . . . . . . . . . . . . . .

Work Status

4 .2 3 .6 5 .2 8 .1 18 .5 5 .7

Currently working . . . . . . . .

bled . . . .

 . . . . . . . . . . . 50 .3 70 .1 57 .0 60 .8 40 .5 34 .8

Not working, disa . . . . . . . . . . . 3 .4 9 .9 14 .8 6 .8 – 14 .4

Not working, retired . . . . . . . . . . . . . . . . . 37 .7 13 .3 17 .0 9 .7 – 32 .2

Not working, other reason . . . . . . . . . . . .

Employment or Retirement Benefits

8 .6 6 .7 11 .1 22 .7 59 .5 18 .7

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . 36 .7 9 .5 9 .5 20 .6 42 .5 28 .9

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . 41 .6 8 .4 7 .6 23 .9 17 .4 18 .0

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 .2 27 .7 5 .9 3 .7 5 .4 11 .4

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 .9 10 .7 13 .3 6 .0 38 .2 29 .8

No benefits . . . . . . . . . . . . . . . . . . . . . . . 14 .6 27 .5 64 .7 0 .8 30 .7 9 .1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 .6 2 .2 5 .0 70 .0 1 .0 2 .4

– Represents or rounds to 0 .0 .

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010 .
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 8

Figure 4.

Widowhood for Population Aged 70 and Over by Sex: 2007–2010

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling 

error, and definitions, see www.who.int/healthinfo/systems/sage/)

17.9

45.0

12.3

69.3

16.8

74.5

17.9

53.1

24.7

70.5

13.6

60.2

China Ghana India Mexico Russia South Africa

Male Female

The older population in SAGE countries was mostly 

married with a sharp increase in widowhood for the 

oldest-old population. Older Russians had the largest 

difference in widowhood between age groups—50–69 

years old, with 17.2 percent widowed; and 70 years 

and over, at 56.9 percent (Table A-1). Widowhood was 

concentrated among oldest-old women, with higher 

levels of widowhood than men in each of the countries (Figure 4). A relatively high proportion of Indian, 

Russian, and Ghanaian women aged 70 and over were 

widowed (74.5 percent, 70.5 percent, and 69.3 percent, respectively).2 South African women aged 50 and 

older had an unusually high share of never married 

at 19.0 percent (Table A-1). Separation or divorce was 

more common among older women in Ghana (17.3 

percent) and Russia (9.6 percent).

Educational attainment differed greatly by country, 

sex, and urban/rural residence. Older Ghanaians had 

the lowest educational level among the SAGE countries, with over 64 percent of the older population having no formal education (Table 2).3 India was a close 

second with 61.7 percent lacking formal education. In 

comparison, primary education was nearly universal 

in Russia. Only 1.9 percent of older Russians had no 

formal education and nearly three out of four had a 

high school degree or higher. Consistently for all SAGE 

countries, those aged 70 and over, women, and those 

living in rural areas had an educational disadvantage, 

2 The percentages are not statistically different from each other.

3 Educational attainment used International Standard Classification 

of Education (1997) for standardizing the levels of education across 

the countries (UNESCO, 2006). Each SAGE country’s education groups/

years were converted to a standard that is represented by the categories used in this report.

each with a higher percent without formal education 

and a lower percent with a college degree, compared 

to those aged 50 to 69, men, and those living in urban 

areas, respectively (Table A-1).4

The majority of those aged 70 and over in all six countries had already transitioned from the paid workforce 

to not working (Table A-1).5 Ghana, however, still had a 

substantial share of their oldest-old population currently 

working, with about half employed. On the other hand, 

approximately two out of three oldest-old Chinese and 

South Africans had retired. Many Indians in this age 

group did not work due to a disability (25 percent).

The types of benefits older people receive from their 

current employment or the job they retired from 

varied greatly by SAGE country.6 More than six out of 

ten Indians reported receiving no benefits from their 

current work or their last job before retirement, while 

almost all older Mexicans enjoyed some benefits. 

Russians reported the highest share receiving pensions 

and cash bonuses from their employment.7 Many older 

Chinese received pensions, nearly 37 percent, yet even 

more reported receiving a combination of nonmonetary 

benefits, such as medical and food benefits.

4 The difference between South African men and women aged 50 

and over without formal education is not statistically significant. The 

difference between urban and rural Russians aged 50 and over without 

formal education and those with college education are not statistically 

significant. 5 The SAGE question on current work status was: “Have you worked 

for at least 2 days during the last 7 days?” 6 The SAGE question on job benefits was: “In this main job, do/did 

you receive any of the following benefits in addition to your payment 

in cash or in kind?” 7 The difference between Russians and Chinese receiving pensions 

is not statistically significant.
9 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Health State and Chronic Conditions

Valid, reliable, and comparable health measures are 

essential components to inform health policy and programs. Health in SAGE is viewed as a multidimensional 

attribute of individuals. Health state used in this report 

encompasses eight health domains and the composite 

score reflects the overall health state of individuals.

Among the six SAGE countries, the mean health score 

for both sexes combined ranged from 53.1 for India 

to 68.1 for China (Table A-2). Consistent across all six 

countries, men had higher health scores than women 

and urban residents higher than rural residents. The 

health score was negatively associated with age. 

Figure 5 illustrates the relationship between mean 

health scores and age for the SAGE countries and 

shows lower health scores with increasing age. China 

had the highest health score across most of the ages, 

while India had the lowest at most ages.1

1 The health scores for the 20-29 age group for India and Mexico, 

and for the 90-plus age group for China and South Africa, and for India 

and Russia are not statistically different from each other within the 

paired comparisons. Most of Mexico’s health scores are not statistically 

different when the neighboring age groups are compared.

DEFINITION OF HEALTH STATE 

SCORE

Health state scores were calculated based on 

self-reported health in eight health domains 

covering affect/emotions, cognition, interpersonal activities and relationships, mobility, pain, 

self-care, sleep/energy, and vision (Salomon, et 

al., 2003). The SAGE composite health score was 

derived from 16 responses, two questions for 

each domain, using a Rasch partial credit model 

of Item Response Theory (Wilson, Allen, and Li, 

2006). Chi-square fit statistics were calculated to 

determine how well each item contributed to a 

common global health measurement. The calibration for each of the health items was taken into 

account and the raw scores were transformed 

into a continuous cardinal scale, where a score 

of 0 represents the worst health and a maximum 

score of 100 represents the best health.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 10

China Ghana India Mexico Russia South Africa

Figure 5.

Mean Health Scores for Population Aged 20 and Over by Age: 2007–2010

Note: The composite health scores were calculated based on self-reported health in eight health domains and transformed 

into a continuous cardinal scale, where 0=worst health, 100=best health.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, 

and definitions, see www.who.int/healthinfo/systems/sage/)

Age

Health score

30

40

50

60

70

80

90

100

20 30 40 50 60 70 80 90+

Chronic diseases, or noncommunicable diseases 

(NCDs), are diseases of long duration and generally 

slow progression, and are by far the leading cause 

of mortality in the world (WHO, 2011b). Increasingly, 

NCDs are linked to poverty and socioeconomic 

disparity and are no longer considered “diseases of 

affluence” (Narayan, Li, and Koplan, 2010). The WHO 

reported that the proportion of “premature” NCD 

deaths (under 60 years old) in lower-middle income 

countries (28 percent) was more than double the proportion in high-income countries (13 percent), and in 

low-income countries (41 percent) was three times the 

high-income countries’ proportion (WHO, 2011c).

SAGE provides a wealth of information on chronic 

conditions. The respondent was asked if he or she 

was ever diagnosed with any of the following chronic 

conditions—arthritis, stroke, angina, diabetes, chronic 

lung disease, asthma, hypertension, and cataracts.2, 3

Questions on oral health and injuries were also asked. 

The respondent was then asked which medications 

or other treatment had been taken and the symptoms 

experienced for selected conditions. 

2 Depression was also asked, but will be discussed separately in a 

later section. 3 Undiagnosed diseases are not included in this report.
11 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Figure 6 identifies the top three self-reported chronic 

conditions among those aged 50–69 and 70 and over 

for each country. Hypertension was by far the most 

common health condition for both age groups.4 It was 

the top chronic condition among 50- to 69-year-olds 

in all countries except India, where it was the second 

most common. Among people 70 years and older, 

4 Although blood pressure is considered a population-level risk 

factor, hypertension as defined internationally for the purpose of this 

report is being considered a health condition and not a “risk factor.”

hypertension was the leading chronic condition in 

China, Russia, and South Africa; second in Ghana and 

Mexico; and third in India. Hypertension was most 

prevalent in Russia, where almost half of the 50- to 

69-year-olds and nearly two-thirds of the 70-and-older 

population reported being diagnosed with the condition. Arthritis was the second most common chronic 

condition among 50- to 69-year-olds and those 70 

years and older in the SAGE countries.

Figure 6.

Top Three Chronic Conditions for Population Aged 50 and Over by Age: 

2007–2010

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling 

error, and definitions, see www.who.int/healthinfo/systems/sage/)

China Ghana India Mexico Russia South Africa 

Ages 70+ 

Ages 50–69 

22.9

13.5

11.0

7.6

17.6 16.1

13.9

26.9

17.7

15.0

47.0

26.0 24.7

28.9

24.8

8.4

20.2

6.6

Angina Arthritis Cataracts Diabetes Edentulism Hypertension Injuries

China Ghana India Mexico Russia South Africa 

35.7

19.6

15.7

9.6

33.1

29.9

21.1

41.6 40.5

19.2

65.2

47.8

42.9

36.4

24.3

14.1

25.2 24.0

Note: Edentulism indicates complete loss of all natural teeth.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 12

Women were more likely to have hypertension than 

men in all six countries (Table A-2). Urban residents 

were more likely to report being diagnosed with hypertension than rural residents in all SAGE countries except 

for Mexico, where a slightly higher percentage of older 

rural residents (32.2 percent) were diagnosed with 

hypertension than older urban residents (29.8 percent).

Chronic conditions were negatively related to the 

mean health score. Table 3 displays the mean health 

score cross-tabulated by selected chronic conditions. 

In all six countries, the health score for those with a 

particular chronic condition was lower than for those 

without the same condition. The largest drop in mean 

health score for each chronic condition occurred in 

the following countries: arthritis, South Africa (11.8 

points); angina, Russia (10.9 points); diabetes, Russia 

(8.6 points); asthma, South Africa (10.2 points); and 

hypertension, South Africa (8.9 points). These results 

indicate that the most common chronic conditions had 

larger negative effects on the older population’s overall 

health for Russians and South Africans than for other 

countries.

Table 3.

Mean Health Scores for Population Aged 50 and Over by Selected Chronic Conditions: 

2007–2010

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see 

www.who.int/healthinfo/systems/sage/en/index.html)

Chronic condition

Country

China Ghana India Mexico Russia

South 

Africa

Arthritis

Without . . . . . . . . . . . . . . . . . . . . 69 .7 57 .2 54 .5 62 .9 63 .3 64 .7

With . . . . . . . . . . . . . . . . . . . . . .

Angina

 . 62 .0 49 .8 47 .1 57 .7 52 .8 52 .9

Without . . . . . . . . . . . . . . . . . . . . 68 .8 56 .4 53 .4 62 .6 63 .7 62 .3

With . . . . . . . . . . . . . . . . . . . . . .

Diabetes

 . 59 .8 49 .7 48 .4 57 .2 52 .8 53 .5

Without . . . . . . . . . . . . . . . . . . . . 68 .3 56 .3 53 .2 62 .7 60 .7 62 .5

With . . . . . . . . . . . . . . . . . . . . . .

Asthma

 . 65 .1 53 .0 51 .7 61 .1 52 .1 54 .5

Without . . . . . . . . . . . . . . . . . . . . 68 .2 56 .3 53 .7 62 .6 60 .3 62 .3

With . . . . . . . . . . . . . . . . . . . . . .

Hypertension

 . 60 .0 51 .8 45 .7 56 .4 53 .3 52 .1

Without . . . . . . . . . . . . . . . . . . . . 69 .2 56 .5 53 .7 63 .6 64 .3 64 .5

With . . . . . . . . . . . . . . . . . . . . . . . 64 .8 53 .7 50 .2 59 .9 56 .3 55 .6

Note: World Health Organizations’s health state score includes 16 responses from 8 health domains 0=worst health, 100=best health .

mean health score for those with specific chronic conditions and those without those same conditions .

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010 .

 . This table shows the 
13 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Risk Factors and Preventive Health Behaviors

Health behaviors are difficult to change, yet health 

risks are modifiable with positive effects from reduction or removal of the risk on health and health 

conditions even at older ages. The WHO stated in its 

2008–2013 action plan that the highest burden NCDs 

(cardiovascular diseases, cancers, chronic respiratory 

diseases, and diabetes) are preventable, and called 

for eliminating shared risk factors, mainly tobacco 

use, harmful alcohol consumption, unhealthy diets, 

and physical inactivity (WHO, 2009). This action plan, 

with supporting evidence and an economic case for 

action, was used during the 2011 United Nations HighLevel Meeting on Noncommunicable Diseases (United 

Nations General Assembly, 2011). 

The prevalence of current tobacco smoking is an 

important predictor of the future burden of tobaccorelated diseases, disability, and mortality, but tobacco 

consumed in any manner can be avoided (Ezzati and 

Lopez, 2004; Preston, Glei, and Wilmoth, 2010; WHO, 

2008a, 2010a). Self-reported tobacco use in SAGE 

countries was highest in India, where about half of 

older Indians (46.5 percent) were current daily smokers, compared to 8 percent of older Ghanaians, the 

lowest among the SAGE countries (Table A-3). In China 

and Russia, those aged 70 and older were more likely 

than those aged 50–69 to have never smoked. Urban 

older residents in China, Ghana, and India were less 

likely to use tobacco than their rural counterparts, 

while it was the opposite in Mexico. Men and women 

showed large differences in tobacco use. Across all six 

countries, men were much more likely than women to 

smoke, and the ratio was as high as 16 to 1 in China 

with the smallest sex difference in smoking in South 

Africa (men, 27.4 percent; women, 19.0 percent). 

Among Ghanaian men, more had given up smoking 

(past smokers) than those currently still smoking, an 

indication of a lifestyle change toward healthier behavior (Figure 7). Also, about the same percentages of 

current smokers and past smokers were recorded for 

Mexican men, signalling that half of the ever smokers 

had stopped smoking. Indian men, on the other hand, 

had the highest proportion (66.7 percent) currently 

smoking and also the lowest proportion of men who 

had quit smoking (7.4 percent). 

DEFINITION OF RISK FACTORS

SAGE used a standardized instrument for collection of behavioral risk factors based on the WHO 

STEPwise approach to Surveillance (WHO STEPS). 

This included self-reported tobacco use, alcohol 

consumption, diet, and physical activity. 

Tobacco use covered types and frequency of 

tobacco use—smoking, snuffing, or chewing, 

each day over the week prior to the interview. 

Alcohol consumption was categorized into two 

broad groups: nondrinkers and drinkers, with 

the latter subdivided according to the number 

of alcoholic drinks consumed during the week 

before the interview. Heavy drinkers were 

defined as consuming five or more standard 

drinks per day for men and four or more standard drinks per day for women.

Diet—fruit and vegetable consumption: The 

WHO recommends an intake of 400–500 grams 

per day of fruits and vegetables (excluding potatoes and other starchy tubers) for the prevention 

of chronic diseases (WHO, 2003). This roughly 

equates to a cut-off of about five daily servings 

of fruits and vegetables, which was defined 

in this report as sufficient fruit and vegetable 

intake per day.

Physical activity: The Global Physical Activity 

Questionnaire (GPAQ) was used in SAGE to measure the intensity, duration, and frequency of 

physical activity in three domains: occupational, 

transport-related, and discretionary or leisure 

time (Bull, Maslin, and Armstrong, 2009). Total 

time spent engaged in physical activity during 

a typical week, number of days per week, and 

intensity of the physical activity were considered 

when classifying it as high, moderate, or low 

level.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 14

Figure 7.

Behavioral Risk Factors for Population Aged 50 and Over by Sex: 2007–2010

Note: Smoker is defined as tobacco user who may smoke, snuff, or chew tobacco products. Heavy drinking is defined as five or 

more standard drinks per day for men and four or more standard drinks per day for women.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/)

Male current smoker Male past smoker

Female current smoker Female past smoker

0 10 20 30 40 50 60 70 80

South

 Africa

Russia

Mexico

India

Ghana

China

Male heavy drinker Male nonheavy drinker

Female heavy drinker Female nonheavy drinker

0 10 20 30 40 50 60 70 80

South

 Africa

Russia

Mexico

India

Ghana

China

Percent

Percent
15 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Heavy alcohol consumption has been related to 

increased illnesses and diseases such as neuropsychiatric disorders or infectious diseases and is associated 

with unintentional and intentional injuries (Rehm, et 

al., 2009; WHO, 2002). Furthermore, heavy drinking 

damages the physical and psychological health of the 

drinker, as well as diminish the health and well-being 

of people around the drinker (WHO, 2011a). Older 

Russian men and women stood out with a higher 

proportion of drinkers compared to their counterparts 

in other countries. Among Russian men, 14.2 percent 

were heavy drinkers and 65.8 percent were nonheavy 

drinkers. Among older Mexican men, 15.0 percent 

were heavy drinkers and 49.1 percent nonheavy drinkers. Again, sex proved to be a highly relevant predictor 

of alcohol consumption, with men much more likely 

to drink than women in all SAGE countries. A mere 1.3 

percent of Indian women were heavy and nonheavy 

drinkers combined, while the comparable share for 

Indian men was 14.1 percent. In Russia the share of 

older women who consumed alcohol (37.2 percent) 

was about half that of men.

Unhealthy diet (inadequate fruit/vegetable intake) and 

physical inactivity are the other two main behavioral 

risk factors, or conversely, adequate fruit/vegetable 

intake and moderate/high physical activity are effective preventive health behaviors (Steptoe and Wikman, 

2010; WHO/FAO, 2005). SAGE defines adequate fruit 

and vegetable intake as five servings or more per day 

(WHO, 2003). Based on the total time spent in physical activity during a typical week, the number of days, 

as well as the intensity of the physical activity, SAGE 

classified physical activity into three levels: high, 

moderate, and low (WHO, 2011a).

A relatively large proportion (64.5 percent) of China’s 

older population consumed adequate fruits and/or 

vegetables, higher than any other SAGE country; while 

its southern neighbor, India, had the lowest consumption level at 9.2 percent (Table A-3). In India, Russia, 

and South Africa, urban older residents were slightly 

more likely than rural older residents to consume 

adequate fruits and/or vegetables while the opposite 

was true for Mexicans (Figure 8). 

For physical activity, the majority of SAGE countries 

(except for South Africa) showed encouraging statistics 

for healthy behavior—most of their older population 

engaged in moderate or high levels of physical activity 

(Table A-3). Older population in South Africa reported 

the lowest levels of physical activity regardless of age 

or sex. Rural older people in Ghana and India were 

more likely than their urban counterparts to engage in 

moderate or high physical activity (Figure 8).1

1 The differences in physical activities between urban and rural 

residents in China, Mexico, Russia, and South Africa are not statistically 

significant.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 16

Figure 8.

Preventive Health Behaviors Among Population Aged 50 and Over by 

Urban/Rural Residence: 2007–2010

Note: Adequate fruit/vegetable intake is defined as five servings or more per day. Moderate or high level of physical activities is 

measured by intensity, duration, and frequency of physical activity. 

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling 

error, and definitions, see www.who.int/healthinfo/systems/sage/)

66.2 63.1

30.4 27.1

11.6 8.2

15.8

29.1

24.2

11.7

Urban Rural

24.9

35.0

China Ghana India Mexico Russia South Africa

China Ghana India Mexico Russia South Africa

Adequate fruit/vegetable intake

Moderate/high physical activity

71.7 70.9

75.4

57.6

69.7 66.0

59.1

75.6

71.3

79.2

38.3

42.4
17 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Disability

Disability is a major issue for aging populations. The 

WHO defines disability as an umbrella term for impairments, activity limitations, and participation restrictions (WHO and World Bank, 2011). SAGE asked specific 

questions on difficulties related to mobility, activities 

of daily living (ADL), instrumental activities of daily living (IADL), and cognition. In all SAGE countries, except 

China, more than three-fourths of the population aged 

50 and over had any type of disability, with as many 

as nine in ten Indians and Russians suffering from 

disabilities (Table A-4). Disability rates were higher 

among women than men in China, India, Russia, and 

South Africa, and higher among rural residents than 

urban residents in China, India, Mexico, and Russia. A 

further examination of various categories of disability 

for the 70-and-older age group reveals that difficulties 

in mobility and ADL prevailed among the oldest-old 

populations in all six SAGE countries (Table 4). The 

Table 4.

Percentage With Disability for Population Aged 70 and Over by Sex, Residence, and Type: 

2007–2010

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic Total

Sex Residence

Male Female Urban Rural

China

Mobility . . . . . . . . . . . . . . . . . . . 40 .4 36 .8 43 .6 31 .5 47 .7

ADL . . . . . . . . . . . . . . . . . . . . . . 26 .8 22 .7 30 .6 15 .0 36 .6

IADL . . . . . . . . . . . . . . . . . . . . .

Ghana

 . 9 .7 8 .6 10 .7 6 .1 12 .6

Mobility . . . . . . . . . . . . . . . . . . . 63 .4 58 .5 68 .7 64 .8 62 .6

ADL . . . . . . . . . . . . . . . . . . . . . . 65 .5 55 .8 75 .8 66 .6 64 .7

IADL . . . . . . . . . . . . . . . . . . . . .

India

 . 35 .2 26 .4 44 .7 37 .0 34 .0

Mobility . . . . . . . . . . . . . . . . . . . 72 .5 65 .1 79 .4 62 .7 77 .0

ADL . . . . . . . . . . . . . . . . . . . . . . 68 .3 58 .6 77 .1 59 .7 72 .1

IADL . . . . . . . . . . . . . . . . . . . . .

Mexico

 . 45 .0 40 .0 49 .6 34 .0 50 .0

Mobility . . . . . . . . . . . . . . . . . . . 54 .3 48 .8 58 .5 52 .4 61 .3

ADL . . . . . . . . . . . . . . . . . . . . . . 60 .5 54 .6 65 .0 59 .2 65 .2

IADL . . . . . . . . . . . . . . . . . . . . .

Russia

 . 22 .1 18 .0 25 .1 19 .3 32 .5

Mobility . . . . . . . . . . . . . . . . . . . 85 .6 81 .3 87 .5 84 .0 89 .4

ADL . . . . . . . . . . . . . . . . . . . . . . 51 .7 46 .0 54 .1 50 .9 53 .6

IADL . . . . . . . . . . . . . . . . . . . . .

South Africa

 . 31 .3 30 .3 31 .7 31 .5 30 .9

Mobility . . . . . . . . . . . . . . . . . . . 50 .7 51 .0 50 .4 51 .7 49 .2

ADL . . . . . . . . . . . . . . . . . . . . . . 54 .7 53 .5 55 .5 57 .7 50 .0

IADL . . . . . . . . . . . . . . . . . . . . . . 29 .8 32 .5 28 .0 29 .7 29 .8

Note: Activities of Daily Living (ADLs) are used to describe a set of daily self-care activities and usually assess the need for help with such personal care 

activities as eating, bathing, and dressing Instrumental Activities of Daily Living (IADL) describe somewhat higher-level functioning considered necessary to live .

independently .

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010 .
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 18

oldest-old Russians had strikingly high rates of mobility 

difficulties, regardless of sex or urban/rural residence 

(81.3 percent for men, 87.5 percent for women, 84.0 

percent for urban residents, and 89.4 percent for rural 

residents). India also had a large proportion of oldest 

old with mobility difficulties (79.4 percent for women 

and 77.0 percent for rural residents). On the other 

hand, consistent with other health conditions, China 

had the lowest proportion reporting difficulties with 

mobility, ADLs, or IADLs.

In recent decades, the concept of disability has shifted 

internationally from an individual, medical perspective 

to a social model, where disability is viewed as the 

negative aspects of the interaction between an individual (with a health condition) and that individual’s 

contextual factors (environmental and personal). To 

this end, the WHO developed a composite score to 

measure disability and health, WHO Disability 

Assessment Schedule (WHODAS), now in its second 

version. WHODAS is a well-tested instrument and 

DEFINITION OF ADL AND IADL

Activities of Daily Living (ADLs) describe a set of 

daily self-care activities and usually assess the 

need for help with personal care activities such 

as eating, bathing, and dressing. An individual’s 

ability to perform ADLs is typically considered 

normal functional status, with an inability to 

perform ADLs suggesting disability.

Instrumental Activities of Daily Living (IADL) 

describe somewhat higher-level functioning considered necessary to live independently. These 

typically assess the need for help with routine 

needs such as using transportation, housekeeping, and preparing food. In this report, a set of 

ADLs and IADLs that comprise the WHO Disability 

Assessment Schedule (WHODAS) approach was 

used to measure functioning and disability.

DEFINITION OF WHODAS

WHODAS, the WHO Disability Assessment 

Schedule, is a generic instrument to measure 

health, functioning, and disability across cultures. 

This report used the 12-item version of WHODAS 

2.0 which evaluates six domains (2 items per 

domain) of day-to-day functioning in the last 30 

days—understanding and communicating, getting 

around, self-care, getting along with people, life 

activities, and participation in society (Üstün, 

et al., 2010). Results from the 12 items were 

summed to get an overall WHODAS score, which 

was then transformed to a 0–100 scale. This 

report used an inverted score (WHODASi) with 0 

indicating maximum disability/worst functioning 

ability and 100 indicating minimum disability/

best functioning ability.
19 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

provides an assessment of the severity of the disability 

(Luciano, et al., 2010; Sousa, et al., 2010). For this 

report, to be consistent with other composite variables 

where a higher score represents better health, an 

inverted WHODAS was created and is referred to as 

WHODASi. A higher WHODASi score represents better 

functioning ability. 

The percent distribution of WHODASi scores for the 

population aged 50 and over in SAGE countries is 

displayed in Figure 9. For illustration purposes in this 

report, the 0–100 scores were divided into four groups 

(with 0–25 representing maximum disability and 

76–100 representing minimum disability). Consistent 

with the low percentages for ADL, IADL, and mobility 

difficulty, only 2.0 percent of the older Chinese were 

in the lower-than-50 group and the vast majority 

(89.0 percent) were in the highest group (76–100), 

possessing the best functioning ability. India’s 

WHODASi distribution was markedly different from the 

other countries. Its proportion of the highest group—

best functioning abilities (44.9 percent) was the lowest 

among the SAGE countries. Also, about one in six older 

Indians scored in the lower half of the scale (worst 

functioning abilities), compared with about one in ten 

in Ghana, Russia, and South Africa. The highest mean 

WHODASi score was 91.1 for China, and the lowest was 

71.3 for India, while the other four countries had mean 

WHODASi scores of around 80 (Table A-4).

Figure 9.

Percent Distribution of WHODASi for Population Aged 50 and Over: 2007–2010

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/)

Note: WHODASi is an inverted score for the World Health Organization Disability Assessment Schedule (WHODAS), 

where 0=maximum disability/worst functioning, 100=minimum disability/best functioning.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

Percent

0 10 20 30 40 50 60 70 80 90 100

South

Africa

Russia

Mexico

India

Ghana

China

0-25 26-50 51-75 76-100
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 20

Cognitive impairment contributes to decrements in 

health and functioning and is strongly related to age. 

In all six SAGE countries, a higher percentage of the 

oldest-old population had difficulty concentrating or 

remembering than their younger counterparts (Table 

A-4). The differentials are especially salient among 

those who reported having severe difficulty remembering things—only 1.6 percent of Russians aged 50–69 

as compared to 12.4 percent of those 70 years and 

older. Older Indians registered the highest percentages 

reporting severe memory difficulties, 11.0 percent of 

those 50- to 69-year-olds and 23.1 percent of those 

aged 70 and over.

SAGE also conducted three tests of cognition, and the 

test results were compiled into a composite cognition score. Consistent with the self-reported cognitive 

difficulty, older Indians had the lowest mean cognition 

score for the total 50-and-older population, 49.4, as 

well as for those 70 and older, 43.2 (Table A-4). On the 

other hand, older and oldest-old Mexicans scored the 

highest, 71.1 and 65.4, respectively. Disentangling the 

contributions of the various components of cognition 

to health, disability, and well-being is needed to assess 

where interventions would be most warranted.

DEFINITION OF COMPOSITE 

COGNITION VARIABLE

Three domains were selected to objectively 

measure cognition, with a focus on domains 

impacted in the early stages of dementia: 

assessment of attention and learning (using 

verbal recall of a word list), working memory 

(using digit span forward and backward), and 

verbal fluency (using the category fluency 

test). All three performance tests were scored 

according to standard practices for each test. 

Verbal recall was measured with a 10-word 

learning task which included immediate 

recall and delayed recall, and the results were 

calculated by correctly recalled words minus 

errors. Scoring for digit span forward and 

backward involved tabulations based on correct 

recitation of each number series for digits 

forward and backward. Verbal fluency was 

measured as the sum of all admissible words 

regarding the category of animals minus errors. 

Factor analysis was used to generate a single 

composite score.
21 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Subjective well-being includes a person’s overall 

appraisal of his or her life (global well-being) and affective state (hedonic well-being), and is an important 

aspect of older people’s health (Stone, et al., 2010). For 

this report, subjective well-being is measured using 

the 8-item WHO Quality of Life (WHOQOL) instrument 

and evaluated by responses to questions on overall life 

satisfaction and specific aspects of life. 

Using responses to single item questions, the majority 

of SAGE countries’ older populations reported being 

satisfied with their overall life.1, 2 At 79 percent, older 

Mexicans recorded the highest rate of life satisfaction, 

compared with only a little over half (57 percent) of 

older Ghanaians (Table A-5). In general, younger cohorts 

(aged 50–69) were more likely to be satisfied with their 

life than were the oldest old (aged 70 and over), especially in Russia, where the differential was 20 percentage points (67.3 percent for 50- to 69-year-olds and 

46.8 percent for those aged 70 and older). However, the 

oldest-old South Africans reported a higher level of life 

satisfaction than their younger counterparts. 

In China, Ghana, and South Africa, urban residents 

were more likely to be satisfied with their life than 

their rural counterparts (Figure 10). Urban Mexicans 

had the highest proportion of life satisfaction among 

1 The respondent was asked: “Taking all things together, how satisfied are you with your life as a whole these days?” 2 “Satisfied” in this report includes those who answered “Very satisfied” or “Satisfied” to various life satisfaction questions.

the urban older population in all six countries; eight 

in ten reported satisfaction with life as a whole. At the 

other end of the scale, only about half of rural older 

Ghanaians and South Africans were satisfied with their 

life as a whole. Older Ghanaian and Indian men were 

more likely than their female counterparts to report 

life satisfaction (Table A-5). 

Besides overall satisfaction, SAGE also asked whether 

an older person was satisfied with a wide range of life 

aspects—health, oneself, ability to perform activities of 

daily living, personal relationships, and conditions of 

living space. In general, older people were less satisfied with their health-related status (health or ability to 

perform day-to-day activities) than other aspects of life 

(Table A-5). Even though the majority of the older population in SAGE countries reported overall satisfaction 

with life, less than half felt they were in a better mood 

than their peers. A sharp contrast was found in Russia. 

Six in ten older Russians were satisfied with themselves, 

and half reported being happy in general.3 However, 

only 14 percent of them felt that they were in a better 

mood than their peers and only 11 percent believed 

they were less anxious than their peers. A similar pattern was found among older Chinese. These differences 

in perception of other people’s relative quality of life are 

worth exploring further in future research.

3 For happiness, the respondent was asked: “Taking all things 

together, how would you say you are these days? Are you...?”

Life Satisfaction and Quality of Life

Figure 10.

Percentage Satisfied With Life Among Population Aged 50 and Over by 

Urban/Rural Residence: 2007–2010

Note: "Satisfied with life" includes "very satisfied" and "satisfied" with life.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling 

error, and definitions, see www.who.int/healthinfo/systems/sage/)

69.8

62.1 61.8

53.2

67.5 65.1

80.7

70.8

60.7 62.7

Urban Rural

52.7

65.0

China Ghana India Mexico Russia South Africa
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 22

Satisfaction with life, health, and other aspects of 

life are interrelated and culture specific. A composite 

variable WHOQOL encompasses multiple aspects of 

quality of life and assesses an individual’s perceptions 

of satisfaction in the context of their culture and value 

systems, as well as their personal goals, standards, 

and concerns. Figure 11 displays the distribution of 

WHOQOL scores for each country by four groups 

(0–25, 26–50, 51–75, and 76–100; with higher scores 

indicating better quality of life). The distributions 

indicate a relatively good quality of life reported by 

older people in all SAGE countries, with a high concentration of scores above 50 (also see Table A-5). 

Interestingly, older Mexicans reported the highest life 

satisfaction, yet had the lowest mean WHOQOL score 

(48.9) among the SAGE countries. On the other hand, 

in countries with relatively high proportions of chronic 

conditions or any disability (discussed in previous sections) such as Russia and India, high-mean WHOQOL 

scores were recorded (similar scores for India, 71.6 

and for Russia, 71.4). This indicates that assessments 

of quality of life vary greatly by culture or other 

environmental factors. It also suggests older people’s 

view on how satisfied they are with their life may not 

be solely determined by, or dependent on, single item 

measures of their quality of life (Ng, et al., 2010) and 

is not directly linked to health conditions or disability. 

Future research should further explore the relationship 

between self-reported life satisfaction and composite 

variables that are designed to take into consideration 

the multiple facets of life. Happiness measures were 

included in SAGE, but are not reported here and could 

help to unravel some of the interrelationships between 

quality of life, happiness, and health.

DEFINITION OF WHOQOL

WHOQOL, the World Health Organization Quality 

of Life instruments, are a set of international, 

cross-culturally comparable tools used to assess 

quality of life and provides a measure of the evaluative component of well-being (Skevington, et 

al., 2004). The 8-item WHOQOL instrument used 

in this report used two questions in each of four 

broad domains: physical, psychological, social, 

and environmental (Schmidt, Mühlan, and Power, 

2005). Results from the 8 items were summed to 

get an overall WHOQOL score, which was then 

transformed to a 0–100 scale, with higher scores 

indicating a better quality of life. SAGE used the 

Day Reconstruction Method to measure the experienced component (happiness).

Figure 11.

Percent Distribution of WHOQOL for Population Aged 50 and Over: 2007–2010

Note: WHOQOL is the World Health Organization Quaility of Life instrument, where 0=worst, 100=best.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

Percent

0 10 20 30 40 50 60 70 80 90 100

South

Africa

Russia

Mexico

India

Ghana

China

0-25 26-50 51-75 76-100

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/)
23 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Depression

Depression is an important public-health problem and 

one of the leading causes of disease burden worldwide, due both to its relatively high lifetime prevalence 

and the significant disability that it causes (Moussavi, 

et al., 2007; WHO, 2007). Depression in SAGE was 

measured through self-reported diagnosed depression 

and through a set of symptomatic questions used to 

diagnose depression. 

The rate of depression (combining self-reported diagnosed depression and symptom-reporting) among 

SAGE countries’ 50-and-older population ranges from 

1.1 percent in China to 13.6 percent in India (Table 

A-2).1 Depression rates by age yielded mixed results—

oldest-old Ghanaians and Indians registered higher 

proportions of depression than their younger counterparts, but the opposite was found for Mexicans and 

South Africans. Older women were more likely than 

older men to be diagnosed with depression in all SAGE 

countries except South Africa. Symptom reporting of 

depression may help to determine whether the gender 

differential in depression was a true difference in levels 

of the condition or whether women tend to seek medical diagnosis and intervention more often than men.

Depression, comorbid with other chronic conditions, 

has been shown to have produced the greatest decrement in health compared with the presence of physical 

1 The rate of depression among the Mexican 50-and-older population is not statistically different from that of India.

chronic conditions alone and increase the risk of 

higher health care costs (Katon, et al., 2010; WHO, 

2007). Results from SAGE indicated that, in general, 

older people with chronic conditions were more likely 

to be depressed than those without chronic conditions 

(Table 5). Older Ghanaians with arthritis were six times 

more likely than those without the condition to be 

depressed (25.6 percent versus 4.3 percent). 

In addition to the question of whether the individual 

had ever been diagnosed with depression, SAGE 

DEFINITION OF DEPRESSION

Depression in SAGE was assessed in two 

different ways. First, respondents were asked 

if they had been diagnosed with depression. 

In addition, a set of symptomatic questions 

were also asked, which were derived from 

the World Mental Health Survey version of the 

Composite International Diagnostic Interview 

for the diagnosis of depression (Kessler and 

Üstün, 2004). The responses to the individual 

items were used in a diagnostic algorithm to 

generate the diagnosis of “Depressive Episode” 

as per the criteria specified in the International 

Classification of Diseases (WHO, 1993).

Table 5. 

Percentage Depressed by Chronic Condition Status for Population Aged 50 and Over: 

2007–2010

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see 

www.who.int/healthinfo/systems/sage/en/index.html)

Chronic condition China Ghana India Mexico Russia

South 

Africa

Arthritis

Without . . . . . . . . . . . . . . . . . . .

With . . . . . . . . . . . . . . . . . . . . . .

 .

 .

0 .8

2 .3

4 .3

25 .6

12 .8

17 .4

10 .8

9 .7

2 .6

6 .0

2 .6

4 .2

Angina

Without . . . . . . . . . . . . . . . . . . .

With . . . . . . . . . . . . . . . . . . . . . .

 .

 .

1 .0

2 .7

7 .3

3 .9

13 .1

22 .2

10 .8

9 .8

2 .5

5 .9

2 .6

11 .1

Diabetes

Without . . . . . . . . . . . . . . . . . . .

With . . . . . . . . . . . . . . . . . . . . . .

 .

 .

1 .1

1 .1

7 .1

9 .5

13 .6

13 .5

11 .3

8 .0

3 .4

5 .5

2 .8

5 .2

Asthma

Without . . . . . . . . . . . . . . . . . . .

With . . . . . . . . . . . . . . . . . . . . . .

 .

 .

1 .0

5 .0

7 .0

13 .2

12 .6

25 .9

10 .7

11 .2

3 .5

7 .9

2 .7

9 .1

Hypertension

Without . . . . . . . . . . . . . . . . . . .

With . . . . . . . . . . . . . . . . . . . . . .

 .

 .

1 .0

1 .4

6 .6

10 .6

13 .5

14 .2

11 .5

8 .9

2 .3

4 .8

2 .0

5 .4

Note: This table shows the percentage depressed for those with specific chronic conditions and those without those same conditions .

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010 .
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 24

also asked whether the respondent felt sad, low, 

or depressed in the 30 days prior to the survey. In 

contrast to the self-reported diagnosed depression, 

“feeling depressed” was reported by a much greater 

number of respondents (see Table A-6). About half of 

older Ghanaians, Indians, and South Africans reported 

feeling depressed in the previous 30 days. The 

considerable difference between the percentage with 

self-reported depression and the percentage reporting 

feeling depressed points to the need for timely 

identification and treatment of this condition.

In terms of disease burden, the two countries at 

opposite ends of the spectrum were the two neighboring Asian countries, China and India (Figure 12). 

Older Indians were about three times more likely to 

report feeling depressed than older Chinese regardless 

of age, sex, and urban/rural residence. In addition, a 

negligible proportion (1.1 percent) of the older Chinese 

reported being diagnosed with depression, compared 

with 13.6 percent of older Indians. The sharp contrast 

between these two Asian countries raises questions 

for future research on whether these dissimilarities in 

psychological distress reflect true differences in health 

conditions or perhaps also cultural differences, and 

whether they illustrate issues of access to and quality 

of mental health care. 

The protective effect of marriage for a person’s 

subjective well-being has been widely documented 

(Hughes and Waite, 2009; Lee, et al., 2001; Umberson, 

Wortman, and Kessler, 1992; Zhang and Hayward, 

2006). Widowhood is likely to lead to depression and 

higher prevalence of cardiovascular disease or other 

health conditions. The marriage protection from feeling depressed is evident in SAGE results (Figure 13).2

In all six countries, widows/widowers were more 

likely to feel depressed. Being married had the largest 

positive effect on older Russians, as the share of feeling 

depressed among those married was 20 percentage 

points lower than those who were widowed. Among 

older Indians, a notably high proportion felt depressed, 

even among those that were married (54.5 percent).

2 Because of the extremely low percentage of divorced or never 

married in SAGE samples, marriage protection in this report compares 

currently married with widowed.

Figure 12.

Percentage Feeling Depressed in Last 30 Days for Population Aged 50 and 

Over for China and India: 2007–2010

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/)

18.6

57.9 56.1

23.4

17.2

63.0

15.9

53.6

62.2 60.6

21.2

15.2

51.8

China India

1.1

13.6

21.3

Total 50–69 70+ Male Female Urban Rural Diagnosed

 with

 depression

 

Figure 13.

Percentage Feeling Depressed in Last 30 Days for Married and Widowed 

Populations Aged 50 and Over: 2007–2010

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and 

definitions, see www.who.int/healthinfo/systems/sage/)

China Ghana India Mexico Russia South Africa 

17.1

27.8

58.4

49.4

54.5

67.8

58.1

Married

43.0

29.4

48.3 45.8

55.6

Widowed

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
25 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Health Care Utilization

The increasing burden of noncommunicable diseases 

presents many people with complex symptoms and 

multiple illnesses, which challenges service delivery to respond to the growing demand for health 

care (Tollman, et al., 2008; WHO, 2008b). SAGE data 

provide information on older people’s access to health 

care—whether they had received outpatient care and/

or inpatient care, from what type of providers, and 

who was more likely to seek health care. Although this 

information does not address how responsive SAGE 

countries’ health care systems are to the needs of the 

older population, it does provide empirical knowledge 

of health care received by the older population in 

SAGE countries. 

In all SAGE countries except Mexico, the majority of 

the older population saw a doctor in the 12 months 

prior to the survey (Table A-7). Older Indians had the 

highest share receiving outpatient care (87.6 percent), 

compared with only 40.5 percent of older Mexicans. 

In Ghana and Russia, the oldest-old population was 

more likely to see a doctor than the younger old. For 

China, Ghana, India, and South Africa, women were 

more likely than men to see a doctor. For China, a 

higher percentage of rural residents than urban residents received outpatient care, while the situation was 

reversed in Ghana and India.

The majority of older patients in all SAGE countries 

except India received their outpatient care from public 

providers, such as a public clinic or health care facility, 

or a public hospital (Table A-7).1 More than eight out 

of ten older Russians went to see a public provider for 

their illnesses. For older Indian patients, in contrast, 

private providers such as a private clinic or health care 

facility, or a private hospital provided most of their 

outpatient care (61.8 percent). Home visits were rare; 

about one in ten older Ghanaian and Russian patients 

received a home visit for their medical care. Ghana 

was the only country where charity organizations or 

churches also provided medical care to older patients 

(7.0 percent).

As expected, a much smaller proportion of the older 

population received inpatient care (i.e., was hospitalized at some time during the 12 months prior to 

1 Providers for outpatient care in the SAGE questionnaire included 

private doctor’s office, private clinic or health care facility, private 

hospital, public clinic or health care facility, public hospital, charity or 

church-run clinic, charity or church-run hospital, home visit, or other.

the survey), ranging from 2.8 percent in Mexico to 

17.3 percent in Russia.2 In China, Ghana, Mexico, and 

Russia, the likelihood of hospitalization increased 

with age.

The likelihood that an older person will utilize health 

care may be determined by multiple factors, including 

demographic characteristics (age, sex, residence, and 

marital status), socioeconomic characteristics (education and wealth), and the person’s health condition 

(presence of disability and chronic conditions). The 

impact of these factors on the likelihood of an older 

person receiving health care (represented by a positive 

response to receiving outpatient care) is estimated 

through a logistic regression. An odds ratio greater 

than “1” indicates that people were more likely to see 

a doctor than the reference group, and an odds ratio 

less than “1” indicates the opposite. The odds ratios for 

each factor are shown in Table 6.

2 Providers for inpatient care in the SAGE questionnaire included 

public hospital, private hospital, charity or church-run hospital, old 

person’s home or long-term care facility, or other.

DEFINITION OF COMPOSITE 

WEALTH VARIABLE

Wealth quintiles were derived from the household ownership of durable goods (chairs, tables, 

cars, television, telephone, washing machine, 

or access to electricity), dwelling characteristics 

(type of floors, walls, and cooking stove), and 

access to services such as improved water, sanitation, and cooking fuel. A total of 21 household 

assets were included with asset lists varying 

somewhat by country. 

The resulting wealth quintiles provide an 

alternative measure of income and assets 

with set incremental levels of assets that 

are less likely to be biased by respondent 

inconsistencies. These set asset levels were 

statistically generated and are country specific. 

Using a Bayesian post-estimation (empirical 

Bayes) method, households were arranged in 

increasing order of assets. The raw continuous 

income estimates were adjusted into quintiles 

using the asset order.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 26

Table 6.

Odds Ratios Predicting Likelihood to Receive Outpatient Care for Population Aged 50 and 

Over: 2007–2010

(Data based on sample. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see 

www.who.int/healthinfo/systems/sage/en/index.html)

Variable China Ghana India Mexico Russia

South

Africa

Age (reference group: 50 to 59)

60 to 69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.99 *1.26 1.12 1.04 0.94 1.03

70 and older . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.09 **1.37 1.24 1.13 1.25 0.92

Sex (reference group: Male) . . . . . . . . . . . . . . . . . . . . ***1.18 ***1.45 *1.30 1.42 1.19 1.26

Residence (reference group: Rural) . . . . . . . . . . . . . . ***0.57 0.95 1.34 0.89 1.39 0.92

Marital Status (reference group: Not married)

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.96 1.14 1.00 1.16 0.90 0.94

Education (reference group: Primary or less than 

primary)

Secondary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.94 1.53 1.14 1.72 ***2.70 1.21

High school or above . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.05 **1.47 0.91 0.66 **2.29 0.75

Wealth Quintile (reference group: First/lowest

quintile)

Second quintile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ***1.26 *1.44 1.39 0.53 0.70 0.99

Third quintile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ***1.52 ***1.98 1.38 2.01 0.85 1.09

Fourth quintile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ***1.72 ***1.83 1.04 1.28 1.03 1.31

Fifth quintile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . **1.75 ***2.16 1.26 1.17 1.46 1.22

ADL (reference group: No ADL limitation) . . . . . . . . 0.82 1.20 0.87 1.10 **1.70 **1.64

IADL (reference group: No IADL limitation) . . . . . . . 1.14 **1.59 0.91 1.57 0.69 1.03

Mobility Limitations (reference group: No mobility 

limitation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.95 **1.41 *1.33 0.78 1.14 *1.38

Chronic Condition (reference group: No chronic 

condition)

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ***1.51 0.90 *1.41 1.16 **1.94 *1.38

Angina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.91 1.66 0.89 *0.28 **1.93 1.08

Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *1.25 **2.06 ***2.46 0.86 *2.16 ***2.35

Lung disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *1.26 0.66 1.12 0.92 1.32 1.60

Hypertension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ***1.45 ***1.83 **1.75 1.24 *1.80 ***2.42

* Significant at .05 level.

** Significant at .01 level.

*** Significant at .001 level.

Notes: Odds ratios of greater than “1” indicate that these people are more likely to receive health care compared to the reference group. Less than primary 

school includes no education.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
27 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Regression results show that consistent with the 

descriptive analysis, women are more likely than men 

to seek medical care. Wealth played an important role 

for older Chinese and Ghanaians: the higher the wealth 

quintile, the more likely the person was to seek care. 

Chronic conditions are strong determinants of an older 

person’s probability of seeing a doctor. Diabetes and 

hypertension are by far the most powerful predictors. 

Except for Mexico, people with diabetes or hypertension proved to be significantly more likely than those 

without the respective condition to see a doctor. 

Arthritis is also a strong predictor. Angina and lung 

diseases increase the odds of seeking health care in 

some but not most of the SAGE countries.

Interestingly, when health and wealth variables are 

included in the model, some demographic and socioeconomic factors did not have the significant effect 

found in the descriptive analysis. Age, urban/rural 

residence, marital status, and education did not have a 

statistically significant impact for most SAGE countries.

One of the major health care issues that older people 

face, especially those in low-income countries, is the 

mounting cost of medical services. The WHO reported 

that direct out-of-pocket payments represented more 

than 50 percent of total health expenditures in some 

low-income countries (WHO, 2010b). SAGE asked 

about sources for health care payment, including self, 

spouse/partner, son/daughter, other family member, 

nonfamily member, insurance, and free of charge. 

Figure 14 displays the distribution of outpatient care 

cost by source of payment. The six SAGE countries 

demonstrated two remarkably different patterns of 

health care cost support. In Mexico, Russia, and South 

Africa, health care to a large extent was free, particularly for older South Africans, 64.5 percent of whom 

received their health care free of charge. In contrast, in 

China, Ghana, and India, the bulk of the cost of medical care was borne by the patients themselves or their 

spouse, child, or other family/nonfamily members. 

An exceptionally high 94.0 percent of older Indians 

paid for their outpatient care out-of-pocket. The same 

was true for inpatient care payments for older Indians 

(91.7 percent) (Table A-7). This, combined with a very 

high percentage (89.9 percent) receiving medical care, 

translates into an unusually high burden of health care 

costs for older Indians.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 28

Figure 14.

Sources for Outpatient Care Payment for People Aged 50 and Over: 

2007–2010

(In percent. Data based on sample. For information on confidentiality protection, sampling error, 

nonsampling error, and definitions, see www.who.int/healthinfo/systems/sage/)

Percent

0

10

20

30

40

50

60

70

80

90

100

China Ghana India Mexico Russia South Africa

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

Self, spouse, 

or partner

alone

Child or other

family/nonfamily

member alone

Insurance 

alone

Free

Other

combination
29 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

This report has examined the health and health care 

utilization of the population aged 50 and older in the 

six countries—China, Ghana, India, Mexico, Russia, 

and South Africa—that participated in SAGE Wave 1. 

The six SAGE countries were home to 42 percent of the 

world’s 1.4 billion people aged 50 and older in 2010, 

40 percent of the 771 million aged 60 and older, and 

38 percent of the 354 million people aged 70 and older 

(U.S. Census Bureau, 2012). By virtue of the sheer size 

of the older population in these six countries and their 

share of the world’s total older population, their health 

status is certain to have a remarkable impact on the 

world’s overall disease burden and health care. 

Relatively few countries have age-specific health and 

disability data, especially for the older population 

residing in middle- and low-income countries. Even 

less commonly available are cross-cultural, crossnational comparable health data to monitor health 

levels and trends within and across countries (National 

Research Council, 2001). Yet governments are concerned about the aging of the population and health of 

their older population, as they relate to decrements in 

the productive capacities of national economies and to 

drivers of future demands on health systems (Bloom, 

et al., 2011; Economist Intelligence Unit, 2009). The 

SAGE results provide needed data for these middleand low-income countries. 

Equally important as data generation, SAGE has 

employed different research methods to address concerns about the reliability and comparability of selfreported health results, and provided data comparable 

with those collected from aging studies in high-income 

countries. The first step, a comparable health measure 

based on multiple life domains and using a common 

latent scale, was presented in this report. This report 

also noted the added value of accounting for systematic biases in survey data (Dowd and Todd, 2011; 

Grol-Prokopczyk, Freese, and Hauser, 2011). The data 

to address and adjust for these biases are available in 

the SAGE datasets (Ispány, et al., 2012).

Findings from this report show that, based on selfreporting, hypertension is a worryingly common 

chronic condition and a strong predictor for older 

people in SAGE countries to receive health care. 

Arthritis was the second most common condition for 

50- to 69-year-olds in five countries, and for those 

aged 70 and older in four countries, contributing to 

declines in mobility. Disability levels among the oldest 

old, whether measured by difficulties with ADLs or 

with mobility, exceeded 50 percent in all countries 

except China. Consistent across the six countries, 

older women had higher levels of hypertension 

and depression than older men, and in most SAGE 

countries, they had higher levels of disability than men. 

On the other hand, older men had higher health risks, 

being much more likely to smoke and drink alcohol 

than older women. Rates of self-reported diagnosed 

depression were low, but all countries recorded a 

much higher percentage of “feeling depressed” when 

measured by a single question, pointing to the need for 

attention to mental and physical health in older age.

In general, older people in SAGE countries reported 

high levels of life satisfaction, but considered themselves to be less happy than their peers, suggesting 

a dissonance between evaluative and experienced 

well-being. The science of well-being is now being 

mainstreamed in health and social policy (Beddington, 

et al., 2008; Stiglitz, Sen, and Fitoussi, 2009; United 

Nations, 2012). However, more research is needed 

to understand the interrelationships between health 

and happiness over time, across different population 

groups including older adults, and how it impacts 

health care utilization. In SAGE, age was positively 

associated with utilization of health care—the oldestold population in all six countries were more likely 

to seek both outpatient and inpatient care than the 

younger old age group. The majority of older people 

in SAGE countries (except for India) reported receiving their outpatient care from public providers. This 

finding provides critical information about health care 

accessibility in these countries and considerations for 

improving or reforming the health care system.

Beyond the individual benefits from reduction of 

health risk factors, the promotion of “aging well” and 

improved well-being may reduce lifetime health care 

expenditure (Seshamani and Gray, 2004). Preventing 

or postponing health conditions through reductions 

in smoking and harmful drinking, plus improvements 

in diet and physical activity, are important to promote 

health and well-being even at older ages (Rechel, 

et al., 2009). However, based on the results from 

SAGE, different approaches for population-based risk 

reduction will likely be needed for men and women. 

Estimates of national well-being (Kahneman, et al., 

2004), as well as closer tracking of risk factors, will 

allow the assessment of how policies affect people’s 

lives and perhaps influence allocation of resources. 

The results from this report point to differences 

across SAGE countries as well as to variations within 

countries. Many questions remain. For example, China 

and India, two neighboring Asian countries, were 

consistently at opposite ends of the spectrum—China 

Summary and Discussion
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 30

had the highest mean health score among the six 

countries and India the lowest; less than one in 

twenty-five Chinese women were currently smoking, 

while almost one-third of Indian women were current 

tobacco users; nearly three-fourths of the oldest 

Chinese registered with the category of the least 

disability, compared with only one-fourth of the 

oldest Indians; a mere 1 percent of the older Chinese 

reported being diagnosed with depression compared 

with nearly 14 percent of older Indians. These health 

differences raise a number of questions: Are these 

different health levels true differences between the two 

populations? Could the results also be a reflection of 

their cultural differences, that is, a difference in how 

the two populations respond to the same question? 

Was there an impact from the social differences in 

terms of social networks and community cohesion in 

these two countries? 1 Do the responses and outcomes 

reflect differences in health care systems and health 

care policies? Are there cohort effects?2 Many of these 

intriguing questions can be further investigated with 

more in-depth analysis, using cross-sectional and 

longitudinal data from SAGE.

Another key observation from the analysis in this 

report relates to the similarities and differences 

between the outcomes based on responses to a single 

item and the results from WHO composite variables. 

1 For an example of comparisons between China and India, see 

Bloom, et al., 2010. For a discussion on the tendency of the Chinese 

not to reveal negative feelings to people outside their family, see He, et 

al., 2007. 2 The Chinese aged 50 and older in 2007–2010 were born in 1960 

or earlier, and those aged 70 and older were born in 1940 or earlier. 

They have been through the great famine in the early 1960s and the 

Cultural Revolution from the mid-1960s to mid-1970s. Anecdotal 

observations reveal that with the economic reforms beginning in the 

1980s, many older Chinese expressed satisfaction with their life in 

comparison to what they had been through before.

The face validity of some composite measures was 

confirmed through cross-tabulations—the pattern 

of health state scores in relation to age, sex, and 

socioeconomic status, existence of chronic conditions, 

or disability prevalence using WHODASi. Other 

measures showed interesting contrast—the single 

life satisfaction question versus the 8-item WHOQOL, 

or reporting “feeling depressed” versus self-reported 

diagnosed depression. While single item questions can 

provide valuable information about an individual, the 

multidimensionality of health, well-being, and disability 

require more information than a single item can 

provide (Bowling, 2005; Kahneman and Deaton, 2010). 

Nonetheless, these similarities and differences will 

merit further exploration in the future waves of SAGE.

This report provided a summary of the health status 

and access to health care by older populations in six 

middle- and low-income countries, thereby filling 

crucial gaps in health information and measurement 

techniques in response to aging populations. These 

results contribute to increasing and ongoing efforts to 

better understand the dynamics of aging through crossnational and multidisciplinary research. As the future 

pace of population aging will likely exceed the rapid 

speed that has taken place thus far, preparations for 

an aging population need to advance now in these six 

countries, as well as in most middle- and low-income 

countries, to avoid the costs and penalties from waiting 

to respond (Suzman, 2011). Future waves of SAGE data 

collection (Wave 2 of SAGE will be implemented in 2012 

and Wave 3 is planned for 2014) will provide the longitudinal data needed to examine the trends and attempt 

to decipher some of the differences documented in this 

report and found in aging research in general. 
31 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

SAGE Data

The findings in this report are primarily based on the 

World Health Organization’s (WHO) Study on Global 

Ageing and Adult Health (SAGE) Wave 1 data collected 

in 2007–2010. The population universe covered in this 

report includes the population living in China, Ghana, 

India, Mexico, Russia, and South Africa. 

SAGE is designed as a multiwave panel study representative of the population aged 50 and older, with a 

smaller cohort of respondents aged 18–49 for comparative purposes. SAGE Wave 0 data (2002–2004) were 

collected as part of the WHO’s World Health Surveys. 

For Wave 1 (2007–2010), Ghana, India, Mexico, and 

Russia used the Wave 0 sampling frame and reinterviewed at least 50 percent of the Wave 0 respondents. 

China used a new sampling frame based on a national 

health surveillance system, and South Africa did not 

collect follow-up interviews but used the same Wave 0 

sampling frame. 

All sampling plans used multistage clustered design 

samples drawn from an updated frame. Each household and individual is, therefore, assigned a known 

nonzero probability of being selected. Household and 

individual weights were post-stratified to weight up 

to the entire number of households and 18-and-older 

population in each nation. 

SAGE is supported by the WHO and the U.S. National 

Institute on Aging (NIA) through an Interagency 

Agreement. In addition, financial or in-kind support 

has come from governments of some collaborating 

countries to their respective national studies (China 

and South Africa). The United States Agency for 

International Development funds were secured by the 

SAGE India team to increase the sample of women aged 

15–49 and to add questions about maternal and child 

health in India. Core funding for SAGE Waves 2 and 3 

have been secured through the same NIA mechanisms.

Other Data

In addition to SAGE, the U.S. Census Bureau’s 

International Data Base (IDB release June 2011) and 

U.N. Population Division’s population estimates and 

projections data (U.N. World Population Prospect 2008 

report) were also used in this report for trend analysis 

of population size and growth. WHO’s global burden of 

disease data (2004 update) were used for information 

on burden of disease and healthy life expectancy.

Sampling and Nonsampling Error

Sampling error occurs when the characteristics of a 

sample are measured instead of those of the entire 

population (as from a census). Note that samplebased estimates will vary depending on the particular 

sample selected from the population, but all attempt 

to approximate the actual figures. The SAGE estimates 

are based on this sample and approximate the actual 

estimates that would have been obtained by interviewing the entire population using the same methodology. The estimates from the 2007–2010 SAGE sample 

may also differ from estimates based on other survey 

samples of the population. Measures of the magnitude 

of sampling error reflect the variation in the estimates over all possible samples that could have been 

selected from the population using the same sampling, 

data collection, and processing methods. Estimates of 

the magnitude of sampling errors are provided in the 

form of standard error for selected SAGE demographic 

and socioeconomic estimates included in this report 

(see Table B-1). The U.S. Census Bureau recommends 

that data users incorporate this information into their 

analyses, as sampling error in survey estimates could 

impact the conclusions drawn from the results. All 

comparative statements in this report have undergone 

statistical testing, and comparisons are significant at 

the 90 percent confidence level unless noted otherwise. This means the 90 percent confidence interval 

for the difference between the estimates being compared does not include zero. 

In addition to sampling error, nonsampling errors may 

be introduced during any phase of data collection or 

processing. For example, operations such as editing, 

reviewing, or keying data from questionnaires may 

introduce error into the estimates. The primary source 

of nonsampling error and the processes instituted to 

control error in SAGE and related studies are described 

in further detail on the SAGE Web site and can be 

obtained from the WHO.

Furthermore, nonsampling error specific to the oldestold population also stems from age misreporting. 

This is due to a variety of factors, including a gross 

ignorance of the true age, lack of birth records which 

makes it difficult to confirm or disconfirm a reported 

age, reliance by some oldest people on the knowledge 

of others for their own age, digital preference (such as 

those ending in “0” or “5”), and deliberate misreporting out of the desire to share in the esteem generally 

accorded extreme old age (Hobbs, 2004; Howden and 

Meyer, 2011; Krach and Velkoff, 1999). 

Sources of the Data and Accuracy of the Estimates
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 32

Additional SAGE Survey Information

Additional SAGE survey related information is provided in Appendix C, which includes the following 

sections: Selection of SAGE Countries; SAGE Sample 

Size, Response Rate, and Weighting; Validation of 

SAGE Data on Age, Sex, and Urban/Rural Residence 

Using Data From IDB, UN, and CIA; Sampling and 

Representativeness of the SAGE Data Compared to LASI 

and Other Surveys; and Issues of Vignettes and Data 

Comparability. The WHO SAGE Web site provides more 

detailed information related to the surveys and the 

data. For inquiries and data access, contact WHO at 

<www.who.int/healthinfo/systems/sage/en

/index.html>.

Data Confidentiality

Title 13, U.S. Code, Section 9, prohibits the Census 

Bureau from publishing results from which the identity of an individual survey respondent could be 

determined. For more information on how the Census 

Bureau protects the confidentiality of data, see the 

U.S. Census Bureau Data Protection and Privacy Policy, 

available at <www.census.gov/privacy/data

_protection/>. To protect the confidentiality of data, 

the WHO limits access to SAGE for research purposes. 

For access to data, complete the SAGE User Agreement 

available at <www.who.int/healthinfo/systems/sage

/en/index1.html>.

CONTACT

U.S. Census Bureau

Demographic Call Center Staff

1-866-758-1060 (toll-free) 

Or visit <www.census.gov> for further information.

World Health Organization

Switchboard, +41 22 791 2111 (international rates apply) 

Visit <www.who.int/healthinfo/systems/sage> or write 

<sagesurvey@who.int> for more information.
33 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

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U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-1

Appendix A.

Table A-1.

Selected Demographic and Socioeconomic Characteristics for Population Aged 50 and 

Over by Age, Sex, and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and 

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and 

older Male Female Urban Rural

CHINA

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 .1 1 .1 1 .0 1 .6 0 .6 1 .1 1 .1

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 .4 91 .0 65 .3 90 .0 80 .8 86 .3 84 .7

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 .2 0 .2 0 .5 0 .2 0 .3 0 .1 0 .3

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 .6 1 .7 1 .1 1 .6 1 .5 2 .1 1 .1

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Educational Attainment

11 .7 6 .0 32 .2 6 .5 16 .9 10 .3 12 .8

No formal education or less than primary school . . . . . . . . 42 .4 35 .9 65 .7 31 .8 53 .0 21 .7 58 .9

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . . 20 .6 22 .3 14 .6 24 .0 17 .3 19 .5 21 .6

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . . 20 .1 23 .6 8 .0 23 .7 16 .6 26 .9 14 .8

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 .6 14 .3 6 .6 14 .7 10 .5 22 .5 4 .7

College/university completed . . . . . . . . . . . . . . . . . . . . . . . .

Work Status

4 .2 4 .0 5 .1 5 .9 2 .6 9 .5 0 .1

Currently working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 .3 57 .0 24 .9 57 .1 42 .9 21 .9 74 .9

Not working, disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 .4 2 .7 6 .1 3 .2 3 .6 1 .3 5 .3

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 .7 31 .1 62 .4 31 .6 44 .3 67 .5 11 .8

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . .

Employment or Retirement Benefits

8 .6 9 .1 6 .6 8 .1 9 .2 9 .4 7 .9

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 .7 34 .7 44 .2 35 .9 37 .6 72 .5 5 .7

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 .6 41 .2 43 .1 43 .0 40 .1 71 .4 15 .8

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 .2 38 .9 35 .5 38 .0 38 .4 18 .3 55 .3

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 .9 15 .6 12 .6 16 .6 13 .1 27 .3 4 .2

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 .6 14 .9 13 .1 13 .4 15 .7 5 .7 22 .2

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

GHANA

Marital Status

0 .6 0 .7 0 .6 0 .7 0 .6 0 .8 0 .5

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 .3 1 .4 1 .1 1 .2 1 .4 1 .6 1 .2

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 .8 65 .9 47 .1 84 .0 35 .9 57 .3 61 .5

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 .8 0 .9 0 .4 1 .1 0 .5 0 .9 0 .7

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 .2 13 .1 10 .4 7 .1 17 .3 14 .0 11 .0

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Educational Attainment

25 .9 18 .7 40 .9 6 .6 44 .9 26 .2 25 .6

No formal education or less than primary school . . . . . . . . 64 .3 56 .2 81 .1 53 .6 76 .2 52 .8 72 .3

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . . 10 .9 13 .2 6 .3 12 .3 9 .4 11 .9 10 .3

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . . 4 .0 5 .1 1 .8 5 .8 2 .1 6 .2 2 .5

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 .1 21 .1 8 .9 23 .2 10 .4 23 .1 12 .9

College/university completed . . . . . . . . . . . . . . . . . . . . . . . .

Work Status

3 .6 4 .4 2 .0 5 .1 2 .0 5 .9 2 .0

Currently working . . . . . . . . . . .

abled . . . . . . .

 . . . . . . . . . . . . . . . . . . . . . . 70 .1 80 .2 49 .2 73 .5 66 .4 61 .4 76 .1

Not working, dis . . . . . . . . . . . . . . . . . . . . . . 9 .9 7 .7 14 .4 7 .4 12 .7 9 .9 9 .8

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 .3 4 .8 31 .0 11 .9 14 .8 18 .3 9 .9

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . .

Employment or Retirement Benefits

6 .7 7 .3 5 .5 7 .2 6 .1 10 .4 4 .2

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 .5 10 .1 8 .4 14 .2 4 .4 16 .7 4 .6

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 .4 8 .5 8 .1 11 .6 4 .9 14 .2 4 .4

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 .7 27 .5 28 .0 28 .6 26 .6 20 .9 32 .3

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 .7 11 .2 9 .4 12 .2 9 .0 13 .1 9 .0

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 .5 27 .0 28 .6 24 .7 30 .6 25 .6 28 .8

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 .2 2 .5 1 .5 1 .9 2 .5 3 .1 1 .5
A-2 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-1.

Selected Demographic and Socioeconomic Characteristics for Population Aged 50 and 

Over by Age, Sex, and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and 

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and 

older Male Female Urban Rural

INDIA

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Educational Attainment

No formal education or less than primary school . . . . . . . .

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . .

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . .

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . .

College/university completed . . . . . . . . . . . . . . . . . . . . . . . .

Work Status

Currently working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . .

Employment or Retirement Benefits

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

MEXICO

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Educational Attainment

No formal education or less than primary school . . . . . . . .

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . .

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . .

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . .

College/university completed . . . . . . . . . . . . . . . . . . . . . . . .

Work Status

Currently working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . .

Employment or Retirement Benefits

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

0 .7

74 .9

–

0 .5

23 .9

61 .7

14 .8

9 .9

8 .5

5 .2

57 .0

14 .8

17 .0

11 .1

9 .5

7 .6

5 .9

13 .3

64 .7

5 .0

7 .0

70 .3

2 .7

4 .5

15 .5

55 .6

24 .0

9 .9

2 .4

8 .1

60 .8

6 .8

9 .7

22 .7

20 .6

23 .9

3 .7

6 .0

0 .8

70 .0

0 .8

82 .8

–

0 .4

16 .0

58 .1

15 .3

11 .7

8 .9

5 .9

65 .7

11 .7

11 .6

11 .1

8 .6

7 .7

6 .1

13 .5

64 .5

4 .8

6 .7

78 .0

3 .2

4 .3

7 .9

51 .1

25 .7

12 .0

2 .1

9 .1

72 .2

4 .3

4 .3

19 .2

19 .0

26 .6

4 .2

7 .1

0 .3

70 .6

0 .5

51 .8

–

0 .8

46 .9

71 .9

13 .2

4 .6

7 .3

3 .0

30 .3

24 .6

33 .8

11 .3

12 .4

7 .3

5 .5

12 .5

65 .1

5 .7

8 .0

47 .3

1 .5

5 .2

38 .0

68 .9

19 .1

3 .6

3 .3

5 .1

20 .7

15 .8

28 .8

34 .8

26 .3

14 .3

1 .9

2 .1

2 .5

68 .2

1 .1

91 .0

–

0 .2

7 .7

43 .2

18 .1

15 .5

14 .4

8 .8

64 .9

11 .3

17 .1

6 .7

12 .7

10 .2

5 .7

15 .4

63 .2

5 .2

2 .8

85 .2

3 .8

2 .4

5 .8

48 .9

29 .8

8 .6

2 .3

10 .4

67 .8

7 .6

9 .8

14 .7

25 .3

25 .8

2 .0

7 .4

0 .3

67 .3

0 .3

58 .4

–

0 .9

40 .4

80 .5

11 .3

4 .2

2 .5

1 .5

40 .5

22 .2

16 .9

20 .4

2 .9

2 .1

6 .5

8 .8

67 .8

4 .7

10 .7

57 .2

1 .9

6 .3

24 .0

61 .4

19 .0

11 .0

2 .5

6 .1

46 .9

5 .2

9 .6

38 .4

11 .3

20 .1

7 .1

3 .1

1 .7

75 .5

0 .3

75 .4

–

0 .5

23 .7

45 .7

18 .1

13 .4

12 .4

10 .3

51 .6

15 .1

21 .2

12 .1

17 .6

13 .7

6 .7

14 .3

54 .7

5 .9

7 .5

68 .1

2 .5

5 .2

16 .7

46 .3

28 .3

12 .3

2 .9

10 .1

59 .9

6 .7

10 .4

23 .1

24 .6

28 .5

4 .2

7 .3

1 .0

64 .3

0 .9

74 .6

–

0 .5

24 .0

68 .9

13 .3

8 .3

6 .7

2 .8

59 .3

14 .7

15 .2

10 .7

6 .0

4 .9

5 .6

12 .8

69 .0

4 .6

5 .4

78 .1

3 .5

1 .8

11 .2

89 .4

8 .3

1 .1

0 .3

0 .8

64 .6

7 .3

7 .1

21 .0

5 .0

5 .4

1 .7

0 .8

–

92 .9
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-3

Table A-1.

Selected Demographic and Socioeconomic Characteristics for Population Aged 50 and 

Over by Age, Sex, and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

RUSSIA

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 3.0 2.0 1.4 3.6 2.8 2.5

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.2 62.1 35.5 72.2 42.7 55.4 50.9

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 4.5 2.9 5.7 3.0 4.2 3.6

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.9 13.1 2.6 10.5 9.6 8.8 12.9

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.1 17.2 56.9 10.2 41.1 28.7 30.1

Educational Attainment

No formal education or less than primary school . . . . . . . 1.9 0.3 5.8 0.5 2.8 1.8 2.3

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 1.1 16.0 5.1 5.8 4.9 7.1

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . 20.1 13.7 35.0 17.5 21.7 17.7 26.7

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.9 62.9 32.9 58.1 51.3 55.2 50.5

College/university completed . . . . . . . . . . . . . . . . . . . . . . . 18.5 22.0 10.3 18.7 18.4 20.4 13.5

Work Status

Currently working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40.5 55.4 5.1 48.2 35.4 40.0 41.8

Not working, disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . 59.5 44.6 94.9 51.8 64.6 60.0 58.2

Employment or Retirement Benefits

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.5 35.5 59.7 36.0 46.8 44.7 36.5

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.4 17.2 18.0 14.8 19.1 18.1 15.7

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 4.4 8.0 4.9 5.8 5.7 4.7

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.2 37.1 40.6 34.3 40.6 39.8 33.6

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30.7 35.0 20.4 38.0 26.1 27.4 40.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.3 0.4 1.4 0.8 1.1 0.8

SOUTH AFRICA

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.3 15.9 7.5 8.4 19.0 15.0 13.0

Currently married . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.4 51.4 46.1 72.6 32.7 52.1 47.3

Cohabiting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 6.6 1.1 7.5 3.9 5.2 6.1

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 6.5 3.4 3.8 7.6 6.1 5.7

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.9 19.5 41.8 7.7 36.8 21.7 27.9

Educational Attainment

No formal education or less than primary school . . . . . . . 48.6 46.8 55.9 46.5 50.0 38.6 66.9

Primary school completed . . . . . . . . . . . . . . . . . . . . . . . . . 22.7 23.5 19.5 22.4 22.9 26.3 16.2

Secondary school completed . . . . . . . . . . . . . . . . . . . . . . 14.5 14.3 15.3 13.1 15.4 16.4 11.0

High school completed . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 9.0 6.0 9.1 8.0 11.3 3.2

College/university completed . . . . . . . . . . . . . . . . . . . . . . . 5.7 6.3 3.3 9.0 3.6 7.4 2.7

Work Status

Currently working . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34.8 39.9 12.2 43.5 27.1 35.5 33.2

Not working, disabled . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.4 16.0 7.1 15.2 13.7 14.9 13.3

Not working, retired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 23.7 69.4 22.9 40.3 31.3 34.1

Not working, other reason . . . . . . . . . . . . . . . . . . . . . . . . . 18.7 20.3 11.3 18.4 18.9 18.3 19.4

Employment or Retirement Benefits

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.9 28.5 30.6 37.7 21.1 34.5 16.4

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.0 17.7 19.3 25.1 11.7 21.2 10.9

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 11.9 9.2 12.0 10.9 11.1 12.1

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.8 31.4 23.1 36.4 24.1 34.2 20.2

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 9.5 7.2 6.8 11.1 8.2 11.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 2.4 2.2 3.0 1.9 2.4 2.4

– Represents or rounds to 0.0.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
A-4 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-2.

General Health and Chronic Conditions for Population Aged 50 and Over by Age, Sex, and 

Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

Mean Health State Score . . . . . . . . . . 68.1 70.4 59.6 70.3 65.9 71.9 65.0

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 21.3 20.2 25.2 17.2 25.3 23.2 19.7

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 2.2 5.3 3.3 2.3 3.3 2.4

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 6.0 12.3 5.6 9.2 8.9 6.1

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 6.1 5.6 8.1 5.4 6.8 9.7 3.2

Lung disease . . . . . . . . . . . . . . . . . . . . 7.5 6.1 12.7 8.9 6.2 8.3 7.0

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 1.9 1.5 3.3 2.0 1.8 2.4 1.5

Depression . . . . . . . . . . . . . . . . . . . . . 1.1 1.1 1.2 0.8 1.4 1.0 1.2

Hypertension . . . . . . . . . . . . . . . . . . . . 25.7 22.9 35.7 23.2 28.1 31.8 20.7

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 7.0 4.2 17.2 4.8 9.2 11.0 3.8

Missing all teeth/edentulism . . . . . . . . 9.0 4.9 24.0 8.1 9.8 6.5 11.0

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 6.6 7.3 6.6 6.9 4.3 8.8

GHANA

Mean Health State Score . . . . . . . . . . 56.1 59.2 49.9 58.6 53.5 58.4 54.6

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 13.8 11.0 19.6 11.5 16.3 14.1 13.7

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 2.2 4.0 2.7 2.9 4.3 1.7

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 2.8 5.2 3.0 4.3 3.8 3.4

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 3.8 3.9 3.5 3.2 4.4 6.1 2.2

Lung disease . . . . . . . . . . . . . . . . . . . . 0.5 0.5 0.7 0.6 0.5 0.8 0.3

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 3.3 2.7 4.5 3.3 3.4 3.5 3.2

Depression . . . . . . . . . . . . . . . . . . . . . 7.2 5.9 9.9 5.6 9.0 7.1 7.3

Hypertension . . . . . . . . . . . . . . . . . . . . 14.2 13.5 15.7 11.3 17.4 23.1 8.0

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 5.3 3.3 9.6 5.1 5.6 6.3 4.7

Missing all teeth/edentulism . . . . . . . . 3.0 2.0 4.9 2.6 3.4 4.0 2.2

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 7.6 6.6 6.7 8.0 6.5 7.9

INDIA

Mean Health State Score . . . . . . . . . . 53.1 55.4 46.5 56.7 49.5 56.1 51.8

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 18.4 17.6 20.8 15.5 21.4 18.1 18.6

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 2.0 1.8 2.6 2.3 1.7 2.6 1.8

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 5.0 7.7 7.1 4.3 8.3 4.6

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 7.1 7.0 7.3 8.4 5.7 11.7 4.9

Lung disease . . . . . . . . . . . . . . . . . . . . 4.6 3.9 6.7 6.5 2.7 4.7 4.6

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 7.5 6.7 9.8 9.2 5.7 8.4 7.1

Depression . . . . . . . . . . . . . . . . . . . . . 13.6 12.8 16.0 11.9 15.4 12.9 14.0

Hypertension . . . . . . . . . . . . . . . . . . . . 17.4 16.1 21.1 14.3 20.5 24.9 14.0

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 18.8 13.9 33.1 17.1 20.6 18.4 19.1

Missing all teeth/edentulism . . . . . . . . 16.3 11.7 29.9 14.6 18.1 19.0 15.1

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 11.0 11.0 10.9 9.4 12.6 9.7 11.5
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-5

Table A-2.

General Health and Chronic Conditions for Population Aged 50 and Over by Age, Sex, and 

Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

MEXICO

Mean Health State Score . . . . . . . . . . 62.4 64.0 57.9 64.7 60.5 63.6 58.4

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 9.0 6.2 17.2 4.8 12.6 9.5 7.0

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 3.1 7.8 4.5 4.1 4.8 2.7

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 2.2 4.2 1.7 3.6 3.2 1.0

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 17.6 17.7 17.5 16.7 18.4 19.3 11.4

Lung disease . . . . . . . . . . . . . . . . . . . . 3.6 2.9 5.6 3.0 4.1 4.0 2.2

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 1.8 1.4 3.0 1.0 2.5 1.9 1.6

Depression . . . . . . . . . . . . . . . . . . . . . 10.7 12.2 6.4 3.6 17.0 12.3 5.3

Hypertension . . . . . . . . . . . . . . . . . . . . 30.3 26.9 40.5 25.0 35.0 29.8 32.2

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 10.0 7.0 19.2 8.8 11.1 10.5 8.4

Missing all teeth/edentulism . . . . . . . . 21.7 15.0 41.6 16.9 25.8 20.4 26.2

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 6.0 5.6 7.0 7.1 5.0 6.1 5.4

RUSSIA

Mean Health State Score . . . . . . . . . . 60.1 64.5 49.7 63.6 57.8 60.4 59.1

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 30.1 24.7 42.9 24.9 33.5 29.9 30.8

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 3.2 8.6 5.0 4.6 5.3 3.5

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 32.5 26.0 47.8 31.0 33.5 31.3 35.9

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 7.1 6.4 8.7 5.4 8.2 7.5 6.1

Lung disease . . . . . . . . . . . . . . . . . . . . 14.6 14.1 15.7 16.5 13.4 15.4 12.5

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 2.7 2.5 3.0 2.1 3.1 2.4 3.3

Depression . . . . . . . . . . . . . . . . . . . . . 3.6 3.2 4.4 1.6 4.9 4.2 1.8

Hypertension . . . . . . . . . . . . . . . . . . . . 52.4 47.0 65.2 41.1 59.6 51.9 53.8

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 12.7 7.8 24.7 9.6 14.7 14.0 9.3

Missing all teeth/edentulism . . . . . . . . 18.0 9.3 38.3 15.4 19.6 18.2 17.3

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 6.1 4.2 5.0 5.9 6.5 3.0

SOUTH AFRICA

Mean Health State Score . . . . . . . . . . 62.0 63.5 55.9 64.5 60.0 62.6 61.0

Chronic Conditions

Arthritis . . . . . . . . . . . . . . . . . . . . . . . . 24.7 24.8 24.3 18.8 29.3 26.3 21.7

Stroke . . . . . . . . . . . . . . . . . . . . . . . . . 4.0 3.7 5.2 4.2 3.9 3.9 4.2

Angina . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 5.4 4.6 3.9 6.3 5.7 4.3

Diabetes . . . . . . . . . . . . . . . . . . . . . . . 9.2 8.4 12.4 6.9 11.0 11.1 5.6

Lung disease . . . . . . . . . . . . . . . . . . . . 2.9 2.9 2.8 2.3 3.3 2.9 2.9

Asthma . . . . . . . . . . . . . . . . . . . . . . . . 4.9 5.2 3.7 5.2 4.7 5.2 4.2

Depression . . . . . . . . . . . . . . . . . . . . . 3.0 3.2 2.1 2.9 3.1 2.5 3.9

Hypertension . . . . . . . . . . . . . . . . . . . . 30.3 28.9 36.4 25.0 34.5 32.4 26.5

Cataracts . . . . . . . . . . . . . . . . . . . . . . . 4.4 3.0 10.2 4.7 4.2 5.6 2.2

Missing all teeth/edentulism . . . . . . . . 8.5 7.1 14.1 8.1 8.7 11.1 3.5

Injuries . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 2.9 4.1 4.2 2.3 3.1 3.2

Note: WHO’s health state score includes 16 responses from 8 health domains. 0=worst health, 100=best health. Depression in SAGE was assessed by a

combination of self-reported diagnosed depression and responses to symptom questions.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
A-6 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-3.

Behavioral Risk Factors for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 27.1 28.8 20.7 51.6 2.9 21.2 31.8

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 2.5 2.4 3.0 4.5 0.6 2.1 2.9

Not current smoker . . . . . . . . . . . . . . . . . . 6.4 5.5 9.9 11.9 0.9 7.1 5.8

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 64.0 63.3 66.5 32.0 95.5 69.5 59.5

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 6.4 6.9 4.4 12.9 0.6 1.9 9.8

Infrequent heavy drinker2 . . . . . . . . . . . . . . 1.3 1.5 0.5 2.4 0.2 1.4 1.1

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 18.5 19.5 14.5 33.3 5.4 16.7 19.9

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 73.9 72.1 80.6 51.3 93.8 79.9 69.2

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 64.5 67.4 54.1 64.4 64.6 66.2 63.1

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.7 24.4 44.1 27.0 30.5 28.3 29.1

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 27.7 27.6 28.2 25.9 29.4 37.2 20.1

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.6 48.0 27.7 47.1 40.1 34.4 50.9

GHANA

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 7.6 7.1 8.7 11.3 3.7 4.1 10.2

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 2.6 2.9 2.0 3.7 1.4 2.2 2.9

Not current smoker . . . . . . . . . . . . . . . . . . 14.2 13.6 15.5 24.6 2.9 15.6 13.3

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 75.5 76.3 73.8 60.4 92.0 78.2 73.7

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 1.5 1.9 0.7 2.5 0.4 1.2 1.7

Infrequent heavy drinker2 . . . . . . . . . . . . . . 1.2 1.4 0.9 1.7 0.7 1.3 1.2

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 39.5 42.9 32.4 51.9 25.3 33.4 43.5

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 57.8 53.9 65.9 44.0 73.6 64.1 53.6

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 28.4 29.3 26.7 28.9 28.0 30.4 27.1

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.8 27.6 40.8 24.9 38.8 42.4 24.6

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 12.3 13.3 13.5 11.8 16.0 10.3

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.5 60.1 45.9 61.7 49.4 41.5 65.0

See footnotes at end of table.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-7

Table A-3.

Behavioral Risk Factors for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

INDIA

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 46.5 46.9 45.3 62.4 30.3 37.4 50.6

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 2.9 2.9 3.0 4.3 1.6 2.9 3.0

Not current smoker . . . . . . . . . . . . . . . . . . 4.8 4.1 6.7 7.4 2.2 4.6 4.9

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 45.8 46.1 44.9 26.0 66.0 55.1 41.5

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 0.2 0.3 – 0.4 – 0.1 0.2

Infrequent heavy drinker2 . . . . . . . . . . . . . . 0.4 0.4 0.3 0.7 0.1 – 0.6

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 6.6 7.2 4.8 13.0 1.2 4.1 7.8

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 92.8 92.1 94.9 85.9 98.7 95.8 91.4

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 10.2 6.5 12.1 6.3 11.6 8.2

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.3 20.0 44.3 24.7 27.9 30.3 24.4

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 23.9 22.6 27.9 22.6 25.4 28.9 21.7

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.8 57.4 27.7 52.7 46.8 40.7 53.9

MEXICO

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 13.3 14.3 10.2 18.8 8.5 15.2 6.3

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 6.9 7.7 4.6 11.1 3.2 7.8 3.7

Not current smoker . . . . . . . . . . . . . . . . . . 19.1 18.9 19.8 29.5 10.0 17.7 24.0

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 60.7 59.1 65.5 40.6 78.3 59.2 65.9

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 0.1 0.1 0.2 0.3 – 0.1 0.2

Infrequent heavy drinker2 . . . . . . . . . . . . . . 6.2 7.6 2.1 14.7 0.6 6.4 5.7

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 29.3 34.8 12.9 49.1 16.0 30.2 26.0

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 64.3 57.5 84.9 36.0 83.4 63.3 68.1

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 19.6 15.9 24.4 13.5 15.8 29.1

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.4 32.8 57.9 33.2 44.9 40.9 34.0

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 22.2 22.4 21.6 19.0 25.0 22.1 22.5

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.4 44.8 20.5 47.8 30.1 37.0 43.5

See footnotes at end of table.
A-8 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-3.

Behavioral Risk Factors for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

RUSSIA

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 19.9 26.1 5.4 44.0 4.7 18.4 24.2

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 1.2 1.2 1.3 2.4 0.5 1.6 0.2

Not current smoker . . . . . . . . . . . . . . . . . . 9.2 8.4 11.2 19.3 2.8 9.7 8.0

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 69.6 64.3 82.0 34.3 92.0 70.3 67.7

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 1.4 1.8 0.2 3.1 0.1 0.9 2.8

Infrequent heavy drinker2 . . . . . . . . . . . . . . 6.4 7.4 3.5 11.1 2.9 7.2 4.1

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 47.8 55.3 25.9 65.8 34.2 46.8 50.5

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 44.5 35.5 70.4 20.1 62.7 45.1 42.6

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 20.9 21.8 18.7 20.8 20.9 24.2 11.7

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.6 18.3 45.9 23.5 28.6 28.7 20.8

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 16.1 14.9 18.7 13.9 17.5 17.3 12.8

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.4 66.7 35.3 62.7 54.0 54.1 66.4

SOUTH AFRICA

Risk Factors

Smoking:

Current daily smoker . . . . . . . . . . . . . . . . . 19.4 19.9 17.3 22.9 16.6 19.2 19.7

Smoker, not daily . . . . . . . . . . . . . . . . . . . . 3.4 3.8 1.5 4.5 2.4 3.5 3.2

Not current smoker . . . . . . . . . . . . . . . . . . 9.5 9.0 11.6 12.9 6.8 10.4 7.9

Never smoker . . . . . . . . . . . . . . . . . . . . . . . 67.7 67.3 69.7 59.7 74.1 66.9 69.2

Alcohol:

Frequent heavy drinker1 . . . . . . . . . . . . . . . 1.0 1.1 0.6 1.3 0.8 1.0 1.0

Infrequent heavy drinker2 . . . . . . . . . . . . . . 3.0 3.4 1.2 4.7 1.7 3.3 2.3

Nonheavy drinker . . . . . . . . . . . . . . . . . . . . 11.5 12.4 7.8 17.7 6.8 11.5 11.6

Lifetime abstainer . . . . . . . . . . . . . . . . . . . . 84.5 83.1 90.3 76.3 90.7 84.2 85.0

Preventive Health Behaviors

Daily fruit and vegetable intake:

Adequate3 . . . . . . . . . . . . . . . . . . . . . . . . . 31.4 31.2 32.5 35.2 28.5 35.0 24.9

Physical activity:

Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60.3 57.7 70.7 56.8 63.0 61.7 57.6

Moderate4 . . . . . . . . . . . . . . . . . . . . . . . . . . 13.5 13.3 14.4 15.4 12.1 13.9 12.9

High4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.2 28.9 14.9 27.8 24.9 24.4 29.5

– Represents or rounds to 0.0.

1

 Heavy drinking is defined as five or more standard drinks per day for men and four or more standard drinks per day for women. Frequent heavy drinking is 3 or 

more days of heavy drinking consumed in the past 7 days.

2

 Infrequent heavy drinking is 1 or 2 days of heavy drinking consumed in the past 7 days.

3

 Adequate fruit/vegetable intake is defined as five servings per day.

4

 Moderate or high level of physical activity is measured by intensity, duration, and frequency of physical activity.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-9

Table A-4.

Disability for Population Aged 50 and Over by Age, Sex, and Urban/Rural Residence:

2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

Any Disability . . . . . . . . . . . . . . . . . . . . . . 68.1 63.3 85.4 63.7 72.5 58.4 75.8

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.0 84.3 59.6 81.8 76.1 85.3 73.9

Mild to moderate . . . . . . . . . . . . . . . . . . . . 19.6 14.9 36.5 16.5 22.6 13.9 24.1

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 0.8 3.9 1.7 1.3 0.9 1.9

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.8 95.0 80.3 92.7 91.0 93.4 90.5

Mild to moderate . . . . . . . . . . . . . . . . . . . . 7.4 4.6 17.5 6.6 8.2 5.9 8.6

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.4 2.2 0.8 0.8 0.7 0.9

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.7 54.4 41.4 57.2 46.1 61.1 44.1

Mild to moderate . . . . . . . . . . . . . . . . . . . . 45.3 43.1 53.6 40.5 50.2 37.3 51.8

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 2.5 5.0 2.3 3.7 1.7 4.1

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2 57.8 32.0 56.9 47.5 62.8 43.7

Mild to moderate . . . . . . . . . . . . . . . . . . 44.7 40.3 60.6 40.4 48.9 36.0 51.7

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 1.9 7.4 2.7 3.5 1.2 4.6

Mean cognition score . . . . . . . . . . . . . . . . 57.5 59.8 49.8 58.5 56.6 60.4 55.2

WHODASi Score1

0–25............................... 0.4 0.1 1.3 0.3 0.4 0.2 0.5

26–50.............................. 1.6 0.7 4.9 1.5 1.6 0.8 2.2

51–75.............................. 9.1 6.0 20.0 6.8 11.3 5.7 11.8

76–100............................. 89.0 93.3 73.7 91.4 86.6 93.3 85.5

Mean WHODASi score . . . . . . . . . . . . . . . 91.1 93.3 83.4 92.3 89.9 93.8 89.0

GHANA

Any Disability . . . . . . . . . . . . . . . . . . . . . . 77.9 73.0 88.1 77.8 78.0 76.6 78.8

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.6 60.4 36.6 56.4 48.5 52.9 52.5

Mild to moderate . . . . . . . . . . . . . . . . . . . . 40.1 35.0 50.5 38.2 42.2 38.9 40.9

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 4.5 12.9 5.4 9.3 8.3 6.6

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75.0 80.3 64.1 77.3 72.5 76.4 74.1

Mild to moderate . . . . . . . . . . . . . . . . . . . . 22.5 18.0 31.7 20.9 24.3 20.8 23.7

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 1.6 4.1 1.8 3.1 2.8 2.2

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.0 24.4 11.0 25.0 14.5 24.8 16.6

Mild to moderate . . . . . . . . . . . . . . . . . . . . 65.0 63.3 68.5 62.5 67.8 61.6 67.4

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.0 12.3 20.6 12.5 17.7 13.6 15.9

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.3 44.4 25.7 45.4 30.5 45.0 33.6

Mild to moderate . . . . . . . . . . . . . . . . . . 54.9 50.6 63.7 50.0 60.3 49.0 59.0

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 5.0 10.6 4.6 9.2 6.0 7.3

Mean cognition score . . . . . . . . . . . . . . . . 58.2 60.4 53.7 60.1 56.2 58.8 57.8

WHODASi Score1

0–25............................... 1.4 0.8 2.6 0.9 1.9 1.6 1.2

26–50.............................. 7.4 3.5 15.5 6.0 8.8 7.7 7.1

51–75.............................. 29.8 25.2 39.5 26.8 32.8 28.1 31.0

76–100............................. 61.4 70.5 42.3 66.3 56.6 62.6 60.6

Mean WHODASi score . . . . . . . . . . . . . . . 79.4 83.8 70.2 81.5 77.4 80.0 79.0

See footnote at end of table.
A-10 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-4.

Disability for Population Aged 50 and Over by Age, Sex, and Urban/Rural Residence:

2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

INDIA

Any Disability . . . . . . . . . . . . . . . . . . . . . . 93.4 92.1 97.3 90.4 96.5 89.9 95.0

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.0 49.7 27.5 52.9 34.9 49.5 41.5

Mild to moderate . . . . . . . . . . . . . . . . . . . . 39.1 37.4 44.1 34.1 44.3 35.3 40.9

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.8 12.8 28.5 13.0 20.8 15.2 17.6

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.2 81.8 63.7 81.5 72.8 79.0 76.3

Mild to moderate . . . . . . . . . . . . . . . . . . . . 19.2 15.9 29.0 16.2 22.3 18.6 19.5

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 2.3 7.3 2.3 4.9 2.4 4.1

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25.6 29.0 15.8 32.8 18.4 31.3 23.1

Mild to moderate . . . . . . . . . . . . . . . . . . . . 53.7 52.6 56.8 52.1 55.4 50.4 55.2

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 18.3 27.3 15.2 26.3 18.3 21.7

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.5 37.0 19.3 40.7 24.1 40.4 28.9

Mild to moderate . . . . . . . . . . . . . . . . . . 53.4 52.0 57.6 50.3 56.6 48.1 55.8

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1 11.0 23.1 9.0 19.3 11.5 15.3

Mean cognition score . . . . . . . . . . . . . . . . 49.4 50.9 43.2 52.5 46.1 52.1 48.3

WHODASi Score1

0–25............................... 2.8 1.4 6.9 1.6 4.0 1.0 3.6

26–50.............................. 12.9 9.8 22.0 9.7 16.3 10.6 14.0

51–75.............................. 39.4 37.6 44.7 33.8 45.1 39.1 39.5

76–100............................. 44.9 51.2 26.4 54.9 34.7 49.2 42.9

Mean WHODASi score . . . . . . . . . . . . . . . 71.3 74.6 61.7 75.6 66.9 74.3 69.9

MEXICO

Any Disability . . . . . . . . . . . . . . . . . . . . . . 79.1 78.9 79.7 74.8 82.9 77.0 86.7

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.5 66.8 45.7 68.2 55.7 65.2 48.2

Mild to moderate . . . . . . . . . . . . . . . . . . . . 32.7 30.1 40.5 27.1 37.6 28.9 46.5

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.8 3.1 13.8 4.7 6.7 5.9 5.3

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80.3 84.2 68.7 82.8 78.2 83.0 70.5

Mild to moderate . . . . . . . . . . . . . . . . . . . . 15.9 14.1 21.3 13.6 18.0 13.4 25.2

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 1.7 10.0 3.6 3.8 3.6 4.3

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45.9 47.0 42.4 51.1 41.3 48.3 37.0

Mild to moderate . . . . . . . . . . . . . . . . . . . . 45.4 44.3 48.5 39.4 50.6 45.5 44.8

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.8 8.7 9.1 9.5 8.1 6.2 18.2

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.0 52.9 45.4 52.8 49.5 55.0 36.6

Mild to moderate . . . . . . . . . . . . . . . . . . 47.0 45.7 50.9 45.7 48.2 43.4 60.0

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 2.0 1.3 3.8 1.5 2.3 1.6 3.4

Mean cognition score . . . . . . . . . . . . . . . . 71.1 73.1 65.4 71.7 70.6 72.0 67.8

WHODASi Score1

0–25............................... 0.7 0.2 2.0 0.6 0.8 0.6 1.1

26–50.............................. 3.9 2.0 9.4 3.4 4.4 3.8 4.6

51–75.............................. 20.8 18.6 26.9 21.8 19.9 16.6 36.2

76–100............................. 74.6 79.2 61.7 74.3 74.8 79.0 58.2

Mean WHODASi score . . . . . . . . . . . . . . . 84.8 86.8 79.0 85.9 83.7 86.3 79.2

See footnote at end of table.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-11

Table A-4.

Disability for Population Aged 50 and Over by Age, Sex, and Urban/Rural Residence:

2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

RUSSIA

Any Disability . . . . . . . . . . . . . . . . . . . . . . 91.3 88.4 98.1 88.1 93.3 90.0 94.9

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48.1 62.4 14.4 56.1 43.0 48.1 48.0

Mild to moderate . . . . . . . . . . . . . . . . . . . . 42.0 32.2 65.0 37.7 44.8 41.3 43.8

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.9 5.4 20.6 6.3 12.3 10.5 8.2

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.9 85.3 43.6 78.8 69.2 72.0 75.6

Mild to moderate . . . . . . . . . . . . . . . . . . . . 22.8 13.6 44.8 18.5 25.6 23.7 20.5

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 1.1 11.5 2.7 5.2 4.3 3.9

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.0 46.1 19.1 43.5 34.5 39.8 33.2

Mild to moderate . . . . . . . . . . . . . . . . . . . . 52.1 47.5 63.0 50.1 53.4 50.0 58.0

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.8 6.4 17.9 6.4 12.0 10.2 8.9

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 49.7 60.0 25.3 53.2 47.4 49.6 50.0

Mild to moderate . . . . . . . . . . . . . . . . . . 45.5 38.4 62.3 43.6 46.8 45.5 45.7

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 1.6 12.4 3.2 5.8 4.9 4.4

Mean cognition score . . . . . . . . . . . . . . . . 63.1 66.3 54.2 63.7 62.6 63.1 63.0

WHODASi Score1

0–25............................... 1.3 0.1 4.1 1.1 1.4 1.1 1.8

26–50.............................. 6.4 1.6 17.7 4.2 7.8 6.3 6.7

51–75.............................. 23.8 16.5 40.9 17.3 27.9 24.0 23.1

76–100............................. 68.5 81.8 37.3 77.4 62.9 68.6 68.4

Mean WHODASi score . . . . . . . . . . . . . . . 80.8 86.6 67.2 84.5 78.5 81.0 80.5

SOUTH AFRICA

Any Disability . . . . . . . . . . . . . . . . . . . . . . 75.9 73.4 86.0 69.4 80.9 75.5 76.6

Difficulty Moving Around

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66.2 70.3 49.3 70.7 62.6 68.7 61.6

Mild to moderate . . . . . . . . . . . . . . . . . . . . 27.7 24.7 40.1 24.6 30.2 25.7 31.3

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 5.0 10.5 4.7 7.2 5.5 7.1

Difficulty With Self-Care

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.5 85.5 75.2 84.4 82.7 87.0 77.0

Mild to moderate . . . . . . . . . . . . . . . . . . . . 14.7 13.4 20.1 13.8 15.4 11.6 20.5

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 1.1 4.7 1.7 1.9 1.4 2.5

Bodily Aches or Pains

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.1 37.9 28.7 40.5 32.7 36.3 35.8

Mild to moderate . . . . . . . . . . . . . . . . . . . . 51.4 50.6 54.7 50.5 52.1 51.3 51.7

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5 11.5 16.6 9.0 15.2 12.4 12.5

Cognition

Difficulty concentrating or remembering:

None . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.4 47.3 32.4 48.4 41.2 46.0 41.5

Mild to moderate . . . . . . . . . . . . . . . . . . 47.3 45.4 55.1 46.0 48.4 47.4 47.2

Severe . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 7.3 12.5 5.7 10.4 6.7 11.3

Mean cognition score . . . . . . . . . . . . . . . . 55.9 57.3 50.0 57.2 54.9 57.0 53.9

WHODASi Score1

0–25............................... 1.1 0.7 2.9 0.8 1.4 0.7 1.9

26–50.............................. 10.0 7.5 20.3 8.7 11.0 8.5 12.7

51–75.............................. 26.0 24.5 32.2 22.9 28.4 26.4 25.2

76–100............................. 62.9 67.3 44.6 67.5 59.2 64.4 60.2

Mean WHODASi score . . . . . . . . . . . . . . . 79.7 82.1 70.1 82.4 77.6 80.7 77.9

1

 WHODASi is an inverted score for WHODAS (World Health Organization Disability Assessment Schedule). 0=worst health, 100=best health.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
A-12 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A–5.

Life Satisfaction for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 65.5 66.4 62.4 66.9 64.2 69.8 62.1

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.1 59.0 50.2 60.8 53.5 61.0 54.1

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.9 71.4 64.6 71.9 67.9 74.5 66.3

Performing daily activities . . . . . . . . . . . . 69.8 72.3 60.7 71.8 67.9 75.7 65.1

Personal relationships . . . . . . . . . . . . . . . 74.9 76.4 69.3 75.0 74.8 77.0 73.2

Living conditions . . . . . . . . . . . . . . . . . . . 63.3 63.2 63.3 62.9 63.6 61.4 64.8

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 59.4 60.1 56.7 60.3 58.5 64.9 55.0

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 16.9 17.0 16.6 19.0 14.9 19.1 15.2

More free time . . . . . . . . . . . . . . . . . . . . . 15.6 14.9 17.9 16.5 14.6 14.4 16.5

Less anxious . . . . . . . . . . . . . . . . . . . . . . 16.1 15.9 16.8 18.0 14.3 18.2 14.4

More healthy . . . . . . . . . . . . . . . . . . . . . . 17.7 17.6 18.0 20.6 14.7 16.7 18.4

WHOQOL Score1

0–25.............................. 1.5 1.1 3.2 1.5 1.6 0.9 2.1

26–50............................. 31.5 30.2 36.3 29.2 33.9 25.9 36.0

51–75............................. 62.9 64.9 55.6 65.0 60.8 68.7 58.2

76–100............................ 4.1 3.8 4.9 4.3 3.8 4.5 3.7

Mean WHOQOL score................ 54.4 54.8 52.7 55.1 53.7 56.0 53.0

GHANA

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 56.7 60.5 48.9 59.7 53.5 61.8 53.2

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 57.2 63.0 45.2 63.2 50.6 60.5 54.9

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67.7 72.5 58.0 72.5 62.5 71.5 65.2

Performing daily activities . . . . . . . . . . . . 58.3 65.5 43.3 64.2 51.8 62.4 55.4

Personal relationships . . . . . . . . . . . . . . . 75.6 79.9 66.7 78.8 72.1 77.7 74.1

Living conditions . . . . . . . . . . . . . . . . . . . 59.7 60.5 57.9 61.1 58.0 63.3 57.1

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.1 65.9 57.5 66.6 59.3 64.9 61.9

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 41.7 43.3 38.3 44.1 38.9 43.7 40.2

More free time . . . . . . . . . . . . . . . . . . . . . 31.1 26.0 41.5 28.2 34.2 34.8 28.5

Less anxious . . . . . . . . . . . . . . . . . . . . . . 26.4 24.5 30.3 24.9 28.0 30.4 23.6

More healthy . . . . . . . . . . . . . . . . . . . . . . 35.6 37.5 31.7 39.2 31.7 39.0 33.3

WHOQOL Score1

0–25.............................. 0.1 0.1 0.1 – 0.1 0.1 0.1

26–50............................. 1.6 0.7 3.4 1.3 1.9 0.9 2.0

51–75............................. 74.5 71.9 79.9 74.8 74.2 70.7 77.1

76–100............................ 23.9 27.3 16.7 23.9 23.8 28.4 20.8

Mean WHOQOL score................ 72.3 73.5 69.7 71.9 72.6 73.0 71.8

See footnote at end of table.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-13

Table A–5.

Life Satisfaction for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

INDIA

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 65.8 68.4 58.5 68.7 62.9 67.5 65.1

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.8 60.0 43.4 61.5 49.9 61.5 53.2

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68.8 71.9 59.8 73.2 64.3 73.4 66.7

Performing daily activities . . . . . . . . . . . . 56.9 62.2 41.6 63.1 50.6 61.7 54.8

Personal relationships . . . . . . . . . . . . . . . 75.9 78.6 68.0 77.4 74.3 78.3 74.8

Living conditions . . . . . . . . . . . . . . . . . . . 81.6 81.8 80.8 81.8 81.3 85.4 79.8

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.5 56.0 50.1 54.0 55.1 61.6 51.3

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 40.4 40.3 40.7 43.2 37.6 43.6 39.0

More free time . . . . . . . . . . . . . . . . . . . . . 34.4 29.4 48.8 29.1 39.7 35.3 33.9

Less anxious . . . . . . . . . . . . . . . . . . . . . . 28.1 26.9 31.8 29.5 26.8 27.9 28.3

More healthy . . . . . . . . . . . . . . . . . . . . . . 26.7 27.7 24.0 28.1 25.3 32.5 24.1

WHOQOL Score1

0–25.............................. 0.1 0.1 0.1 – 0.1 0.1 –

26–50............................. 0.3 0.1 0.8 0.1 0.4 0.2 0.3

51–75............................. 71.4 68.7 79.1 65.4 77.4 64.4 74.5

76–100............................ 28.3 31.1 20.0 34.4 22.0 35.2 25.1

Mean WHOQOL score................ 71.6 72.3 69.4 72.6 70.5 72.8 71.0

MEXICO

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 78.6 77.1 83.0 83.5 74.3 80.7 70.8

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 68.7 68.1 70.5 76.2 62.2 68.8 68.3

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74.4 73.0 78.6 79.7 69.8 75.1 72.0

Performing daily activities . . . . . . . . . . . . 69.9 69.5 70.9 71.6 68.3 70.9 66.1

Personal relationships . . . . . . . . . . . . . . . 82.9 84.5 77.9 89.0 77.4 82.3 84.8

Living conditions . . . . . . . . . . . . . . . . . . . 80.5 79.6 83.3 87.2 74.7 79.2 85.2

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.5 53.7 53.0 61.3 46.7 54.4 50.4

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 28.7 28.8 28.6 33.5 24.5 31.5 18.7

More free time . . . . . . . . . . . . . . . . . . . . . 22.7 20.0 30.8 23.0 22.5 22.2 24.6

Less anxious . . . . . . . . . . . . . . . . . . . . . . 27.8 28.9 24.7 34.5 22.0 29.4 22.1

More healthy . . . . . . . . . . . . . . . . . . . . . . 26.7 28.2 22.3 32.6 21.5 27.1 25.2

WHOQOL Score1

0–25.............................. 3.0 2.3 4.9 2.2 3.7 3.0 3.1

26–50............................. 56.9 56.5 58.1 52.8 60.5 55.9 60.7

51–75............................. 36.9 39.7 29.1 41.3 33.0 37.5 34.5

76–100............................ 3.2 1.5 7.9 3.6 2.8 3.6 1.8

Mean WHOQOL score................ 48.9 48.0 51.5 50.9 47.2 49.3 47.4

See footnote at end of table.
A-14 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A–5.

Life Satisfaction for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

RUSSIA

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 61.2 67.3 46.8 65.7 58.4 60.7 62.7

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.2 49.9 27.2 50.8 38.3 45.6 36.5

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.1 70.4 52.6 74.7 59.0 66.7 60.8

Performing daily activities . . . . . . . . . . . . 61.9 73.0 35.9 71.5 55.8 65.3 52.8

Personal relationships . . . . . . . . . . . . . . . 80.6 83.5 73.8 87.1 76.5 82.6 75.3

Living conditions . . . . . . . . . . . . . . . . . . . 69.5 69.7 69.2 74.6 66.3 69.5 69.5

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 50.2 56.1 36.4 56.6 46.2 50.3 50.2

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 14.3 14.6 13.7 14.7 14.1 14.0 15.4

More free time . . . . . . . . . . . . . . . . . . . . . 22.5 17.1 35.4 22.3 22.6 23.5 19.9

Less anxious . . . . . . . . . . . . . . . . . . . . . . 11.2 9.4 15.5 12.5 10.4 11.3 11.0

More healthy . . . . . . . . . . . . . . . . . . . . . . 11.6 13.9 6.2 14.9 9.5 12.3 9.8

WHOQOL Score1

0–25.............................. 0.9 0.9 0.8 1.2 0.7 1.2 –

26–50............................. 0.6 0.3 1.4 0.3 0.8 0.8 0.3

51–75............................. 65.8 60.3 78.5 58.4 70.5 66.3 64.4

76–100............................ 32.7 38.4 19.4 40.1 28.0 31.8 35.3

Mean WHOQOL score................ 71.4 72.4 68.9 72.3 70.8 71.0 72.3

SOUTH AFRICA

Satisfied With

Life as a whole . . . . . . . . . . . . . . . . . . . . . 60.7 59.3 66.5 62.1 59.6 65.0 52.7

Health . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.4 62.5 61.9 66.2 59.4 64.6 58.2

Self . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77.0 77.3 75.6 80.8 74.0 78.4 74.3

Performing daily activities . . . . . . . . . . . . 68.8 70.6 61.3 70.8 67.2 71.5 63.7

Personal relationships . . . . . . . . . . . . . . . 80.6 81.4 77.6 82.4 79.3 83.0 76.2

Living conditions . . . . . . . . . . . . . . . . . . . 58.1 57.1 62.3 59.4 57.1 64.2 46.6

Happiness

Happy . . . . . . . . . . . . . . . . . . . . . . . . . . . 58.3 57.0 63.7 59.3 57.5 61.6 52.2

Compared to Peers

Better mood . . . . . . . . . . . . . . . . . . . . . . . 37.3 37.8 35.5 41.4 34.1 39.6 33.0

More free time . . . . . . . . . . . . . . . . . . . . . 31.5 29.7 39.2 27.3 34.8 32.5 29.7

Less anxious . . . . . . . . . . . . . . . . . . . . . . 33.2 32.5 36.2 35.9 31.1 34.8 30.2

More healthy . . . . . . . . . . . . . . . . . . . . . . 32.1 32.8 29.3 33.4 31.1 34.5 27.7

WHOQOL Score1

0–25.............................. 0.3 0.3 0.3 0.4 0.2 0.4 0.1

26–50............................. 3.9 3.8 4.3 4.0 3.8 3.9 3.7

51–75............................. 81.4 81.0 83.0 80.2 82.3 79.9 84.1

76–100............................ 14.5 15.0 12.4 15.4 13.8 15.8 12.1

Mean WHOQOL score................ 67.8 67.9 67.5 68.5 67.3 68.4 66.7

– Represents or rounds to 0.0.

1

 WHOQOL, World Health Organization Quality of Life assessment instrument, measures physical health, psychological health, social relationships, and

environment. 0=worst health, 100=best health.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-15

Table A-6.

Subjective Well-Being for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 18.6 17.2 23.4 15.9 21.2 15.2 21.3

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 18.5 17.4 22.8 15.8 21.2 15.1 21.3

Has difficulty with relationship . . . . . . . . . . . . . . 9.2 5.9 21.2 8.4 9.9 7.9 10.2

Has health-related emotional problems . . . . . . . 23.5 19.7 37.5 20.1 27.0 13.8 31.3

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 6.0 6.3 4.9 7.3 4.4 7.5

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 12.7 13.4 11.5 14.1 7.4 17.2

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 1.2 1.7 1.0 1.7 1.1 1.6

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 1.7 1.6 2.0 1.3 2.0 1.7 1.7

Feelings of hopelessness . . . . . . . . . . . . . . . . . 1.5 1.5 1.6 1.2 1.9 1.1 1.9

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.8 0.9 0.6 1.1 0.4 1.2

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.3 0.5 0.3 0.4 0.2 0.5

GHANA

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 52.0 49.2 57.8 48.3 56.0 46.9 55.6

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 58.6 55.8 64.3 56.0 61.5 52.5 62.8

Has difficulty with relationship . . . . . . . . . . . . . . 41.6 35.2 55.0 36.9 46.9 39.1 43.4

Has health-related emotional problems . . . . . . . 53.9 45.9 70.4 48.7 59.6 48.5 57.7

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . .. 14.7 13.4 17.3 11.4 18.3 14.8 14.6

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 14.6 13.2 17.5 11.7 17.8 15.8 13.8

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 8.0 11.5 6.6 12.0 9.7 8.7

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 9.0 7.7 11.6 6.7 11.5 9.2 8.9

Feelings of hopelessness . . . . . . . . . . . . . . . . . 8.0 6.8 10.6 6.3 10.0 8.0 8.0

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 4.5 3.6 6.3 3.3 5.9 4.6 4.4

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 0.8 0.6 1.3 0.7 0.9 1.0 0.7

INDIA

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 57.9 56.1 63.0 53.6 62.2 51.8 60.6

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 65.6 64.3 69.1 60.5 70.7 59.3 68.4

Has difficulty with relationship . . . . . . . . . . . . . . 48.5 44.7 59.6 41.4 55.8 45.1 50.1

Has health-related emotional problems . . . . . . . 68.3 63.8 81.4 61.0 75.8 64.0 70.3

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . . 27.8 26.8 30.8 25.4 30.3 21.9 30.5

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 34.9 33.5 39.3 32.7 37.3 29.9 37.2

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 17.0 16.1 19.6 15.6 18.5 13.4 18.8

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 17.6 16.4 21.3 13.3 22.1 16.5 18.2

Feelings of hopelessness . . . . . . . . . . . . . . . . . 12.8 12.1 14.8 10.7 15.0 13.4 12.5

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 8.5 8.1 9.8 5.7 11.4 8.2 8.7

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 1.5 1.1 2.8 0.9 2.2 0.8 1.9
A-16 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-6.

Subjective Well-Being for Population Aged 50 and Over by Age, Sex, and Urban/Rural 

Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

MEXICO

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 46.0 42.3 57.1 34.8 55.8 45.5 47.9

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 53.4 52.7 55.6 50.0 56.4 53.5 53.3

Has difficulty with relationship . . . . . . . . . . . . . . 23.4 19.8 34.0 25.7 21.3 18.9 39.5

Has health-related emotional problems . . . . . . . 48.0 47.1 50.7 43.7 51.8 45.3 58.0

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . . 19.0 19.7 17.0 7.5 29.0 22.0 7.9

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 30.3 33.1 22.3 23.4 36.4 31.0 27.9

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 15.2 17.0 10.2 3.5 24.8 17.4 7.2

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 8.5 9.0 7.3 3.5 12.7 8.9 7.1

Feelings of hopelessness . . . . . . . . . . . . . . . . . 14.1 16.0 8.7 3.9 22.5 16.2 6.2

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 10.3 12.5 4.0 2.7 16.5 12.0 4.0

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 6.2 8.2 0.3 0.2 11.1 7.5 1.0

RUSSIA

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 35.7 28.5 52.6 26.7 41.4 36.0 35.0

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 44.0 36.8 60.7 32.7 51.1 43.3 45.9

Has difficulty with relationship . . . . . . . . . . . . . . 26.9 19.1 45.3 23.1 29.3 26.6 27.7

Has health-related emotional problems . . . . . . . 83.0 78.3 94.2 76.6 87.0 82.1 85.6

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . . 17.6 17.2 18.7 11.4 21.6 19.6 12.2

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 31.0 29.6 34.3 23.0 36.1 32.3 27.3

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 4.4 7.0 2.1 7.4 6.2 2.6

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 7.7 7.0 9.5 3.1 11.0 7.7 7.9

Feelings of hopelessness . . . . . . . . . . . . . . . . . 5.0 4.3 6.8 1.5 7.5 6.1 2.4

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 3.7 3.4 4.5 1.3 5.5 4.7 1.5

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.5 0.3 0.1 0.6 0.5 0.3

SOUTH AFRICA

In Last 30 Days

Feeling sad, low, or depressed . . . . . . . . . . . . . 49.9 50.3 48.3 47.0 52.2 49.6 50.5

Feeling anxious/worried . . . . . . . . . . . . . . . . . . . 52.2 53.1 48.7 49.0 54.7 51.9 52.8

Has difficulty with relationship . . . . . . . . . . . . . . 31.0 27.5 45.5 27.7 33.7 29.2 34.4

Has health-related emotional problems . . . . . . . 50.9 46.9 66.7 45.5 55.2 51.2 50.5

In Last 12 Months

Loss of interest . . . . . . . . . . . . . . . . . . . . . . . . . 9.9 10.3 8.2 8.1 11.2 9.5 10.6

Loss of energy . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0 9.3 7.8 7.4 10.3 7.9 11.2

Loss of appetite . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 3.9 2.5 3.5 3.7 2.8 5.1

Difficulty sleeping . . . . . . . . . . . . . . . . . . . . . . . . 4.2 4.4 3.4 3.7 4.6 3.4 5.7

Feelings of hopelessness . . . . . . . . . . . . . . . . . 3.8 3.9 3.3 3.5 4.1 3.3 4.7

Thought of death . . . . . . . . . . . . . . . . . . . . . . . . 2.1 2.3 1.4 1.7 2.5 2.2 2.0

Attempted suicide . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.2 0.1 1.1 0.9 1.2 0.6

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-17

Table A-7.

Health Care Utilization in Last 12 Months for Population Aged 50 and Over by Age, Sex, 

and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

CHINA

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67.4 66.8 69.4 65.5 69.2 63.7 70.2

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 60.3 60.2 60.8 58.0 62.5 56.2 63.5

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67.1 66.4 69.8 66.2 67.9 78.7 59.4

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27.2 28.1 24.1 27.7 26.7 12.4 37.2

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.1 0.1 0.1 0.1 0.2 –

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.1 0.2 0.1 0.2 0.2 –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 5.4 5.8 5.8 5.1 8.5 3.4

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 61.0 64.7 48.9 62.2 60.0 47.4 70.2

Child or other family/nonfamily member alone . . . . 6.6 4.5 13.9 4.6 8.4 3.1 9.0

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 6.0 8.3 7.4 5.8 15.2 0.7

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 2.3 4.3 3.1 2.4 3.1 2.5

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 23.1 22.6 24.7 22.8 23.4 31.2 17.7

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 15.0 13.6 19.5 15.5 14.5 14.7 15.1

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95.6 95.1 96.8 96.2 95.0 95.5 95.6

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 4.9 3.0 3.8 5.0 4.3 4.4

Charity or church hospital . . . . . . . . . . . . . . . . . . . . – – – – – – –

Old person’s home or long-term care facility . . . . . . 0.1 – 0.2 – 0.1 0.2 –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 27.6 30.9 19.7 28.1 27.0 23.2 30.9

Child or other family/nonfamily member . . . . . . . . . 16.6 15.2 19.8 14.6 18.5 5.3 25.0

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 2.8 7.3 4.9 3.4 9.2 0.4

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.2 1.4 0.7 0.4 0.8 0.4

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 51.1 50.9 51.7 51.6 50.6 61.5 43.4

GHANA

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68.3 65.6 73.8 65.3 71.6 72.1 65.7

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 65.3 62.7 70.4 62.1 68.7 69.0 62.7

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.7 51.0 52.8 49.4 53.8 55.7 48.5

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.8 17.1 19.1 18.9 16.8 21.6 14.9

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0 6.4 8.0 6.2 7.7 6.3 7.5

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 8.9 9.3 8.9 9.2 5.4 11.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.5 16.5 10.9 16.7 12.5 11.1 17.1

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 55.6 62.1 43.5 62.3 49.0 50.4 59.5

Child or other family/nonfamily member alone . . . . 14.1 10.1 21.5 7.9 20.1 16.1 12.6

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.0 17.7 24.3 18.9 21.1 20.1 19.9

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 4.9 3.6 5.5 3.4 5.9 3.3

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 5.2 7.2 5.4 6.4 7.5 4.6

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 8.7 7.8 10.4 9.2 8.1 10.8 7.1

See footnotes at end of table.
A-18 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-7.

Health Care Utilization in Last 12 Months for Population Aged 50 and Over by Age, Sex, 

and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

GHANA—Con.

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59.3 65.5 50.0 52.2 67.8 59.0 59.6

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.1 24.6 28.5 29.5 22.2 26.7 25.5

Charity or church hospital . . . . . . . . . . . . . . . . . . . . 14.3 10.0 20.8 18.3 9.5 14.3 14.3

Old person’s home or long-term care facility . . . . . . 0.2 – 0.6 – 0.5 – 0.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 36.6 42.5 27.7 44.0 28.0 34.9 38.3

Child or other family/nonfamily member . . . . . . . . . 30.8 26.5 37.1 22.9 39.9 27.7 33.9

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.9 16.2 27.7 24.1 17.2 22.6 19.0

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 5.4 1.3 4.8 2.5 4.6 2.8

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 9.4 6.2 4.3 12.5 10.2 6.0

INDIA

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89.9 89.4 91.2 88.6 91.1 92.5 88.7

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 87.6 87.0 89.3 86.0 89.2 90.5 86.3

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.1 22.5 20.9 22.4 21.8 21.1 22.6

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.8 62.4 60.0 61.5 62.0 67.7 58.9

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.3 0.4 0.2 0.3 0.3 0.3 0.3

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 3.5 7.7 3.2 5.9 3.1 5.3

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 11.3 11.2 12.6 10.0 7.8 12.9

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 65.3 72.7 44.6 80.3 51.2 62.4 66.7

Child or other family/nonfamily member alone . . . . 28.7 21.3 49.4 14.2 42.4 29.7 28.3

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.1 – 0.1 0.1 0.3 –

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 4.7 5.5 4.1 5.7 6.1 4.4

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.1 0.4 1.2 0.7 1.5 0.7

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 11.1 10.5 12.7 11.7 10.5 12.0 10.7

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38.3 39.5 35.6 41.1 35.3 37.7 38.7

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59.4 59.4 59.6 55.1 64.2 61.5 58.3

Charity or church hospital . . . . . . . . . . . . . . . . . . . . 2.2 1.1 4.8 3.8 0.5 0.8 3.0

Old person’s home or long-term care facility . . . . . . – – – – – – –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 55.0 60.3 42.5 64.8 44.3 56.2 54.4

Child or other family/nonfamily member . . . . . . . . . 36.7 30.8 50.9 24.7 50.0 31.3 39.5

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 – 0.3 0.2 – 0.3 –

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 4.9 4.8 5.9 3.8 5.5 4.6

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 4.0 1.4 4.4 2.0 6.7 1.5

See footnotes at end of table.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 A-19

Table A-7.

Health Care Utilization in Last 12 Months for Population Aged 50 and Over by Age, Sex, 

and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

MEXICO

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.8 40.9 44.7 37.5 45.2 41.3 43.9

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 40.5 40.1 41.8 36.0 44.1 40.0 42.6

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58.3 59.4 55.3 60.6 56.9 57.4 61.8

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.6 35.1 41.1 32.5 39.3 38.3 30.5

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . – – 0.1 – – – –

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – 0.1 – 0.1 – –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.0 5.5 3.4 6.9 3.8 4.3 7.6

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 28.6 32.1 17.8 24.3 31.3 29.6 24.6

Child or other family/nonfamily member alone . . . . 9.6 6.4 19.1 7.7 10.7 10.2 7.2

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.5 16.9 19.3 27.1 11.3 17.3 18.2

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43.8 44.0 43.1 40.8 45.7 42.2 49.5

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.5 0.6 0.1 0.9 0.6 0.4

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 2.8 1.8 5.7 3.0 2.6 2.5 3.7

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.2 65.7 58.7 67.3 57.8 67.0 50.1

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36.1 34.3 37.8 29.0 42.2 33.0 43.8

Charity or church hospital . . . . . . . . . . . . . . . . . . . . – – – – – – –

Old person’s home or long-term care facility . . . . . . – – – – – – –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 – 3.4 3.7 – – 6.0

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 24.1 34.9 13.4 26.2 22.3 23.3 26.3

Child or other family/nonfamily member . . . . . . . . . 25.8 5.6 45.9 21.8 29.2 22.2 34.8

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23.9 33.8 14.0 20.0 27.2 29.2 10.4

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.5 23.7 25.3 31.2 18.7 23.4 27.3

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 2.1 1.4 0.7 2.6 1.9 1.3

RUSSIA

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.0 68.6 79.8 68.7 73.9 73.6 67.7

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 67.4 64.1 75.0 62.9 70.0 68.7 63.9

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.7 88.9 76.4 88.5 82.7 86.6 79.2

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 3.5 1.1 1.9 3.1 3.2 1.1

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – 0.1

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 7.1 21.7 8.7 13.8 9.7 18.5

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.5 0.8 0.8 0.5 0.4 1.1

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 11.6 14.9 5.2 12.9 10.9 13.5 6.2

Child or other family/nonfamily member alone . . . . 0.8 0.8 1.0 0.6 0.9 1.0 0.2

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.8 27.1 26.3 27.7 26.4 22.5 39.3

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.5 38.6 50.2 43.3 42.1 43.0 41.1

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 18.2 18.6 17.4 15.4 19.7 20.0 13.2

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 17.3 15.5 21.4 17.6 17.1 18.2 14.8

See footnotes at end of table.
A-20 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table A-7.

Health Care Utilization in Last 12 Months for Population Aged 50 and Over by Age, Sex, 

and Urban/Rural Residence: 2007–2010—Con.

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Country and characteristic

Total

Age Sex Residence

50 to 69

70 and

older Male Female Urban Rural

RUSSIA—Con.

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99.1 98.8 99.7 99.9 98.7 98.9 99.8

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.7 1.0 0.3 0.1 1.1 0.9 0.2

Charity or church hospital . . . . . . . . . . . . . . . . . . . . 0.1 0.2 – – 0.2 0.2 –

Old person’s home or long-term care facility . . . . . . – – – – – – –

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 6.1 6.4 5.7 5.1 6.8 5.8 7.3

Child or other family/nonfamily member . . . . . . . . . 2.7 1.8 4.2 1.1 3.6 3.3 0.5

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.0 38.1 24.4 37.2 30.5 33.7 30.8

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35.4 32.1 41.1 34.9 35.8 33.5 41.7

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 22.7 21.6 24.6 21.8 23.3 23.7 19.7

SOUTH AFRICA

Received Care1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.0 63.6 70.3 59.7 69.1 64.7 65.5

Received Outpatient Care2 . . . . . . . . . . . . . . . . . . 61.9 60.8 66.2 55.9 66.6 61.2 63.3

Outpatient Care Provider

Public . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.8 70.5 76.4 67.6 74.6 68.2 78.9

Private . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.2 27.1 23.2 29.8 23.9 31.1 16.6

Charity or church . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.1 – – 0.1 0.1 –

Home visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.6 0.1 0.5 0.4 0.2 0.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 1.8 0.3 2.0 1.0 0.4 3.6

Who Paid for Outpatient Care

Self, spouse, or partner alone . . . . . . . . . . . . . . . . . 24.0 25.0 20.5 27.3 21.8 23.1 25.8

Child or other family/nonfamily member alone 2.8 2.7 3.2 2.2 3.3 3.3 1.8

Insurance alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 9.1 5.0 10.2 7.0 11.5 1.9

Free alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64.5 62.6 71.3 59.3 67.9 61.5 70.4

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.5 – 1.0 – 0.6 0.1

Received Inpatient Care3 . . . . . . . . . . . . . . . . . . . . 9.0 8.5 11.1 8.5 9.4 10.3 6.3

Inpatient Care Provider

Public hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69.5 68.1 73.6 62.1 74.9 66.4 80.1

Private hospital . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.4 30.4 26.4 37.9 23.1 33.6 14.8

Charity or church hospital . . . . . . . . . . . . . . . . . . . . – – – – – – –

Old person’s home or long-term care facility . . . . . . 1.1 1.5 – – 2.0 – 5.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

Who Paid for Inpatient Care

Self, spouse, or partner . . . . . . . . . . . . . . . . . . . . . . 11.8 10.3 15.7 8.7 14.0 10.5 16.4

Child or other family/nonfamily member . . . . . . . . . 5.5 4.2 9.0 3.9 6.7 2.8 15.2

Insurance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28.3 32.4 17.2 34.1 24.0 30.3 21.0

Free . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.4 53.1 58.1 53.3 55.3 56.3 47.4

Other combination . . . . . . . . . . . . . . . . . . . . . . . . . . – – – – – – –

– Represents or rounds to 0.0.

1

 Received care includes either outpatient care or inpatient care, or both.

2

 Received outpatient care is based on responses to “the last health care facility visited.”

3

 Received inpatient care is based on responses to “the last overnight hospital stay only.”

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 B-1

Table B-1.

Standard Error for Selected Demographic and Socioeconomic Characteristics of 

Population Aged 50 and Over: 2007–2010

(In percent. Data based on sample. For information on confidentiality protection, sampling error, nonsampling error and

definitions, see www.who.int/healthinfo/systems/sage/en/index.html)

Characteristic

Country

China Ghana India Mexico Russia

South

Africa

Age

50 to 59 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 1.0 1.1 4.2 2.3 1.5

60 to 69 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.5 0.7 0.9 2.7 1.3 1.2

70 and older . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.0 1.0 1.0 2.4 1.9 0.9

Sex

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 1.0 0.7 3.3 1.5 1.6

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 1.0 0.7 3.3 1.5 1.6

Residence

Urban . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 2.3 3.7 3.5 5.6 3.3

Rural . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 2.3 3.7 3.5 5.6 3.3

Marital Status

Never married . . . . . . . . . . . . . . . . . . . . . . . . . . 0.2 0.2 0.1 1.7 0.5 1.2

Married/cohabiting . . . . . . . . . . . . . . . . . . . . . . . 0.7 1.0 0.8 3.2 3.0 1.3

Separated/divorced . . . . . . . . . . . . . . . . . . . . . . 0.2 0.7 0.1 0.9 1.9 0.6

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.8 0.8 1.8 1.8 1.2

Educational Attainment

No education . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 1.5 1.5 3.2 0.4 2.4

Primary completed . . . . . . . . . . . . . . . . . . . . . . 0.8 0.6 0.9 2.9 0.8 1.4

Secondary completed . . . . . . . . . . . . . . . . . . . . 0.6 0.5 0.7 1.8 2.4 1.1

High school completed . . . . . . . . . . . . . . . . . . . 0.6 1.0 0.7 0.7 2.5 1.3

College completed . . . . . . . . . . . . . . . . . . . . . . . 0.6 0.4 0.7 1.9 2.3 0.9

Work Status

Currently working . . . . . . . . . . . . . . . . . . . . . . . . 1.1 1.2 1.6 3.5 2.5 2.2

Not working, disabled . . . . . . . . . . . . . . . . . . . . 0.2 0.7 1.0 1.1 – 1.5

Not working, retired . . . . . . . . . . . . . . . . . . . . . . 0.8 0.8 1.0 1.6 – 1.5

Not working, other reason . . . . . . . . . . . . . . . . . 0.6 0.5 1.1 3.1 2.5 1.2

Employment or Retirement Benefits

Pension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 0.8 1.0 3.9 3.5 2.2

Medical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 0.9 1.0 3.9 2.6 1.9

Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 1.9 0.8 1.6 1.0 1.6

Cash . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 1.3 1.1 1.9 3.9 2.0

No benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.8 1.7 1.9 0.5 2.8 1.1

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.1 0.4 1.2 4.2 0.3 0.4

– Represents or rounds to 0.0.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

Appendix B.

U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 C-1

Appendix C.

SAGE SURVEYS

SAGE, Study on Global Ageing and Adult Health, is

conducted in six participating countries—China, 

Ghana, India, Mexico, Russia, and South Africa. It

is run by the World Health Organization’s (WHO)

Multi-Country Studies unit in the Information, 

Evidence, and Research Cluster as part of the unit’s 

Longitudinal Study Programme. 

Selection of SAGE Countries

SAGE countries were selected to cover a broad geographic range of low- to upper-middle-income countries; some with improving economic situations (Table 

C-1); large populations that are aging at different rates; 

countries at different stages of the demographic and 

epidemiological transitions; and government agencies 

and study teams with whom WHO had long standing 

working relationships.

SAGE Sample Size, Response Rate, and 

Weighting

SAGE is designed as a multiwave panel study representative of the population 50 years and older, and a 

smaller cohort of respondents aged 18–49 for comparison purposes. This report uses data from SAGE Wave 

1 implemented between 2007 and 2010. The targeted 

sample per country included 6,000 households consisting of 1,000 “younger” households and 5,000 “older” 

households. All household members in older households were invited to participate. See Table C-2 for 

sample size and response rate for each SAGE country.1

1 Note the response rate for Mexico is below 60 percent.

Each participating country used the Wave 0 sampling 

frame for Wave 1 (except China, which used a new 

sampling frame based on a national health surveillance 

system). All sampling plans used multistage-clustered 

design samples drawn from an updated frame. Each 

household and individual was therefore assigned a 

known nonzero probability of being selected.

Country-specific sampling and weighting methods for 

SAGE Wave 1 are as follows:

•	 China implemented a stratified, multistage cluster 

sampling design. The sample was stratified by provinces, eight in total, and is nationally representative. 

One county (four townships) from the rural regions 

and one district/city (four community blocks) from 

the urban regions were selected with probability 

proportional to size from each province and constituted the primary sampling units (PSUs). Household 

weights were post-stratified according to the 2008 

household projections by China’s Center for Disease 

Control (CDC) and individual weights were poststratified according to the 2008 population projections provided by China’s CDC, both weighted up to 

the respective totals of the eight provinces. A second set of household and individual weights were 

post-stratified to weight up to the entire households 

and 18-years-and-older population in the nation 

(excluding Hong Kong and Macau).

•	 Ghana used a stratified, multistage cluster sampling design. The sample was stratified by administrative region and type of locality (urban/rural) 

Table C-1.

World Bank List of Economies—SAGE Countries: 2007–2011

Country

2007–2010

classification

2011

classification

2007 GNI

per capita

(PPP international 

dollars)

2010 GNI

per capita

(PPP international 

dollars)

Percentage of

total burden of

disease from

noncommunicable 

conditions (Group II)

China . . . . . . . . . . . . . Lower-middle Upper-middle 5,370 7,640 69

Ghana . . . . . . . . . . . . Low Lower-middle 1,330 1,660 40

India . . . . . . . . . . . . . . Low to Lower-middle Lower-middle 2,740 3,550 50

Mexico . . . . . . . . . . . . Upper-middle Upper-middle 12,580 14,290 72

Russia . . . . . . . . . . . . Upper-middle Upper-middle 14,400 19,190 64

South Africa . . . . . . . . Upper-middle Upper-middle 9,560 10,360 33

Note: PPP is purchasing power parity.

Sources: World Bank, 2011, GNI Per Capita Ranking, Atlas Method and PPP Based, available at <http://data.worldbank.org/data-catalog

/GNI-per-capita-Atlas-and-PPP-table>, accessed on March 2, 2012. World Health Organization, 2008, The Global Burden of Disease: 2004 Update, available at 

<www.who.int/evidence/bod>, accessed on September 21, 2011.
C-2 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table C-2.

SAGE Sample Size and Response Rate by Age: 2007–2010

Country Unweighted

sample size

Percent distribution of sample Response

rate1

Cooperation

rate Unweighted Weighted 2

CHINA

 Total 50 and older . . . . 13,367 100.0 100.0 93 98

50 to 59 . . . . . . . . . . . . . . . . 5,807 43.4 50.7 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 3,968 29.7 27.5 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 2,802 21.0 17.4 (NA) (NA)

80 and older . . . . . . . . . . . . . 790 5.9 4.5 (NA) (NA)

18 to 49 . . . . . . . . . . . . . . . . 1,642 (NA) (NA) (NA) (NA)

GHANA

 Total 50 and older . . . . 4,724 100.0 100.0 80 92

50 to 59 . . . . . . . . . . . . . . . . 1,883 39.9 40.4 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 1,305 27.6 27.3 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 1,071 22.7 22.8 (NA) (NA)

80 and older . . . . . . . . . . . . . 465 9.8 9.6 (NA) (NA)

18 to 49 . . . . . . . . . . . . . . . . 839 (NA) (NA) (NA) (NA)

INDIA

 Total 50 and older . . . . 7,150 100.0 100.0 68 92

50 to 59 . . . . . . . . . . . . . . . . 3,179 44.5 44.1 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 2,456 34.4 30.3 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 1,148 16.1 19.9 (NA) (NA)

80 and older . . . . . . . . . . . . . 367 5.1 5.7 (NA) (NA)

18 to 49 . . . . . . . . . . . . . . . . 5,048 (NA) (NA) (NA) (NA)

MEXICO

 Total 50 and older . . . . 2,315 100.0 100.0 51 51

50 to 59 . . . . . . . . . . . . . . . . 434 18.8 48.1 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 937 40.5 25.6 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 619 26.7 17.8 (NA) (NA)

80 and older . . . . . . . . . . . . . 325 14.0 8.6 (NA) (NA)

18 to 49 . . . . . . . . . . . . . . . . 429 (NA) (NA) (NA) (NA)

RUSSIA

 Total 50 and older . . . . 3,938 100.0 100.0 83 88

50 to 59 . . . . . . . . . . . . . . . . 1,473 37.4 45.5 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 1,071 27.2 24.7 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 1,018 25.9 21.5 (NA) (NA)

80 and older . . . . . . . . . . . . . 376 9.6 8.3 (NA)

18 to 49 . . . . . . . . . . . . . . . . 417 (NA) (NA) (NA) (NA)

SOUTH AFRICA

 Total 50 and older . . . . 3,840 100.0 100.0 77 100

50 to 59 . . . . . . . . . . . . . . . . 1,695 44.1 49.9 (NA) (NA)

60 to 69 . . . . . . . . . . . . . . . . 1,232 32.1 30.6 (NA) (NA)

70 to 79 . . . . . . . . . . . . . . . . 662 17.2 14.0 (NA) (NA)

80 and older . . . . . . . . . . . . . 251 6.5 5.5 (NA) (NA)

18 to 49 . . . . . . . . . . . . . . . . 385 (NA) (NA) (NA) (NA)

(NA) Not available.

1

 Response rate is percentage of respondents who completed the interviews among all eligible persons, including those who were not successfully contacted.

2

 Cooperation rate is percentage of respondents who completed the interviews among all eligible persons contacted.

Note: Response rate and cooperation rate are for individuals only, not for households.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 C-3

resulting in 18 strata and is nationally representative. The 2000 Population and Housing Census 

was used as the sampling frame. A sample of 251 

 enumeration areas (EAs) was selected as the PSUs, 

with 24 households randomly selected from each 

EA. Household weights were post-stratified according to the 2010 household projections, and individual weights were post-stratified according to the 

2009 projected population estimates.

•	 India used a multistage, stratified clustered sample 

design. The sample was drawn from 19 of the 

28 states and 7 union territories and represented 

96 percent of the population. The 19 states were 

divided into six groups based on four indicators—

infant mortality rate, female literacy rate, percentage of safe deliveries, and per capita income. One 

state was randomly selected from each of the six 

groups. The sample was stratified by state and 

locality (urban/rural) resulting in 12 strata and is 

nationally representative. Household weights were 

post-stratified according to the 2006 household 

projections, and individual weights were poststratified according to the 2006 projected population estimates. A second set of household and 

individual weights were post-stratified to weight up 

to the entire households and 18-and-older population respectively in the country.

•	 Mexico used a stratified, multistage cluster 

sampling design. Strata were defined by locality 

(metropolitan, urban, rural). All World Health 

Survey (WHS)/SAGE Wave 0 individuals aged 50 

or over in the selected rural or urban PSUs and 

a random sample of 90 percent of individuals 

aged 50 or over in metropolitan PSUs who had 

been interviewed for the WHS/SAGE Wave 0 were 

included in the SAGE Wave 1 “primary” sample. A 

supplementary, random sample from urban and 

rural households was included to compensate for 

the over-representation of metropolitan strata. 

Both household and individual weights were 

post-stratified by locality according to the 2009 

population census projections.

•	 Russia used a stratified, multistage cluster sample 

design. The sample was stratified by the federal 

districts and is nationally representative. All seven 

federal districts were included and constituted 

the strata. PSUs comprised 267 atenum (polling districts) that were selected with probability 

proportional to the 18-and-older population size. 

Household weights were post-stratified by federal 

district and locality according to the 2001 population census, and individual weights were poststratified according to the 2011 mean predictive 

population estimates.

•	 South Africa used a stratified, multistage cluster 

sample design. The 50 strata selected were defined 

by provinces, locality (urban/rural), and race. 

Enumeration areas (EA) constituted the primary 

sampling units and were selected with probability 

proportional to size: the measure of size being the 

number of individuals aged 50 or over in the EA. 

Household weights were post-stratified according 

to the South African Community Survey 2007 and 

individual weights were post-stratified according to 

the 2009 medium mid-year population estimates.

A household questionnaire was used to obtain

information about the household members, dwelling,

and economic well-being (questionnaire available at

<www.who.int/healthinfo/systems/sage/en/index1

.html>). Besides data on self-reported health status, 

risk factors, and chronic diseases in the individual 

questionnaire, SAGE collected objectively-measured 

health data from health examinations, performance 

tests, and blood collection via finger-prick. Data on 

health care utilization, health expenditure, social 

networks, quality of life and well-being, and caregiving 

were collected. A proxy interview was used for individuals who were not able to complete the interview 

because of health issues. 

Validation of SAGE Data on Age, Sex, and 

Urban/Rural Residence Using Data From 

IDB, UN, and CIA

An exercise was conducted by the Census Bureau to 

validate the distributions of age, sex, and urban/rural 

residence in SAGE data using data from the Census 

Bureau’s IDB, United Nations’ (UN) population data, 

and Central Intelligence Agency’s (CIA) data on urban/

rural residence (Table C-3). Overall, SAGE distributions 

match the IDB, UN, and CIA data.
C-4 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table C-3.

Comparison of SAGE Data on Age, Sex, and Urban/Rural Residence for Population Aged 50 

and Over With Data From IDB, UN, and CIA: 2007–2010

(In percent)

Country SAGE (2007–2010)

IDB (2010) UN (2010)

CIA (2010)

Unweighted Weighted (All ages)

CHINA

Age

50 to 69 . . . . . . . . . . . . . . . . 73.1 78.1 77.2 78.3 (NA)

70 and older . . . . . . . . . . . . . 26.9 21.9 22.8 21.7 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 53.1 50.1 50.0 49.9 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 48.8 44.3 (NA) (NA) 47.0

GHANA

Age

50 to 69 . . . . . . . . . . . . . . . . 67.5 67.7 80.0 80.4 (NA)

70 and older . . . . . . . . . . . . . 32.5 32.3 20.0 19.6 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 50.3 50.3 53.0 50.8 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 40.7 40.6 (NA) (NA) 51.0

INDIA

Age

50 to 69 . . . . . . . . . . . . . . . . 78.8 74.4 80.8 81.4 (NA)

70 and older . . . . . . . . . . . . . 21.2 25.6 19.2 18.6 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 49.6 49.5 50.4 50.4 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 25.5 31.2 (NA) (NA) 30.0

MEXICO

Age

50 to 69 . . . . . . . . . . . . . . . . 59.2 73.6 75.9 76.0 (NA)

70 and older . . . . . . . . . . . . . 40.8 26.4 24.1 24.0 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 60.5 53.2 54.2 52.7 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 72.8 78.8 (NA) (NA) 78.0

RUSSIA

Age

50 to 69 . . . . . . . . . . . . . . . . 64.6 70.2 69.9 70.0 (NA)

70 and older . . . . . . . . . . . . . 35.4 29.8 30.1 30.0 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 64.6 61.1 61.7 61.2 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 75.8 73.2 (NA) (NA) 73.0

SOUTH AFRICA

Age

50 to 69 . . . . . . . . . . . . . . . . 76.2 80.5 79.2 82.9 (NA)

70 and older . . . . . . . . . . . . . 23.8 19.5 20.8 17.1 (NA)

Sex

Female . . . . . . . . . . . . . . . . . 57.4 55.9 57.1 56.5 (NA)

Urban/Rural

Urban . . . . . . . . . . . . . . . . . . 66.7 64.9 (NA) (NA) 62.0

(NA) Not available.

Sources: Study on Global Ageing and Adult Health (SAGE), 2007–2010. U.S. Census Bureau, International Data Base, <www.census.gov/population

/international/data/idb/informationGateway.php>, accessed on February 7, 2012. United Nations, Population Division of the Department of Economic and Social 

Affairs of the United Nations Secretariat, World Population Prospects: The 2010 Revision, <http://esa.un.org/unpd/wpp/index.htm>, accessed on February 7, 2012.

U.S. Central Intelligence Agency, World Factbook, <www.cia.gov/library/publications/the-world-factbook/index.html>, accessed on January 31, 2012.
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 C-5

Sampling and Representativeness of the 

SAGE Data Compared to Longitudinal Aging 

Study in India (LASI) and Other Surveys

The following two tables provide comparisons 

between SAGE and other survey data on sampling and 

representativeness of indicators other than the basic 

demographic variables of age, sex, and urban/rural 

residence. 

India respondent profiles are from the LASI, India 

National Sample Survey (India NSS), the India Human 

Development Survey (IHDS), the WHS, and SAGE. Table 

C-4 is an excerpt from Table 4 of Arokiasamy, et al., 

2011.2

Sex ratio and household size from SAGE and China’s 

National Sample Survey (China NSS) on Population 

Changes are presented in Table C-5. The survey design 

determines the differences. In SAGE—China, the main 

survey population is aged 50 and older. Because sex 

ratios usually decline with age due to differences in 

longevity between men and women, sex ratios in SAGE 

2 Arokiasamy, Perianayagam, David Bloom, Jinkook Lee, Kevin Feeney, 

and Marija Ozolins. 2011. “Longitudinal Aging Study in India: Vision, 

Design, Implementation, and Preliminary Findings,” Table 4, PGDA 

Working Paper No. 82, available at <www.hsph.harvard.edu/pgda

/working.htm>.

are expected to be lower than those for the country as 

a whole.

The more restrictive definition of “household” in 

SAGE resulted in a smaller household size. In China 

Statistical Yearbooks, a “household” is defined as members who live together at the same address, mainly 

including family members (children, siblings, or parents) but also other relatives, friends, and other members. One person living alone is also one household. 

But in SAGE, in addition to living together, household 

members are defined as those who share meals (eat 

out of the same pot) and usually stay at this address 

for at least 4 months a year. 

Issues of Vignettes and Data Comparability

SAGE used a number of methods to improve the reliability, validity, and comparability of its self-reported 

health measures, including the use of anchoring 

vignettes. The anchoring vignette technique uses the 

same questions and response categories as used for 

self-assessment of health. The vignettes are used to

fix the level of ability on a given health domain to

better distinguish between differences in self-ratings 

due to actual health differences and those due to 

Table C-4.

India Respondent Profiles From LASI, India NSS, IHDS, WHS, and SAGE

Characteristic LASI India NSS IHDS WHS SAGE

Survey year . . . . . . . . . . . . . . . . . . . . . . . . . . 2010 2004 2004–05 2003 2007–08

Total number of individuals . . . . . . . . . . . . . . 1,683 383,338 215,754 10,750 12,198

Number of individuals aged 45 and older . . . 1,451 81,146 45,074 3,706 7,841

Marital status among respondents

 45 years and older (percent):

Married . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78.0 75.8 78.2 80.7 81.5

Never married . . . . . . . . . . . . . . . . . . . . . . 1.8 1.1 0.7 1.3 0.6

Divorced . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 0.6 0.5 0.7 0.6

Widowed . . . . . . . . . . . . . . . . . . . . . . . . . . 19.1 22.5 20.6 17.3 17.3

Education among respondents

 45 years and older (percent):

No education . . . . . . . . . . . . . . . . . . . . . . . 48.2 58.6 53.2 63.4 47.6

Less than 5 years . . . . . . . . . . . . . . . . . . . . 8.1 8.6 10.7 11.2 13.2

5 to 9 years . . . . . . . . . . . . . . . . . . . . . . . . 22.0 19.5 21.0 15.0 19.8

10 years or more . . . . . . . . . . . . . . . . . . . . 21.7 13.4 15.1 10.5 19.4

Note: LASI is Longitudinal Aging Study in India, India NSS is India National Sample Survey, IHDS is India Human Development Survey, and WHS is World 

Health Survey.

Source: Arokiasamy, Perianayagam, David Bloom, Jinkook Lee, Kevin Feeney, and Marija Ozolins, 2011, “Longitudinal Aging Study in India: Vision, Design, 

Implementation, and Preliminary Findings,” Table 4, PGDA Working Paper No. 82, available at <www.hsph.harvard.edu/pgda/working.htm>.
C-6 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table C-5.

Comparison of Sex Ratio and Household Size Between SAGE and China NSS

Index

Data Sources

SAGE—China 2009 China NSS

Sex ratio:

All household members . . . . . . . . . . . . . . . 94.7 103.3

Individual respondents . . . . . . . . . . . . . . . . 86.9 103.3

Household size . . . . . . . . . . . . . . . . . . . . . . . 2.6 3.2

Notes: Sex ratio is the number of males per 100 females. China NSS is China National Sample Survey on Population Changes.

Sources: Study on Global Ageing and Adult Health (SAGE), 2007–2010; China National Bureau of Statistics, 2010, China Statistical Yearbook 2010, Table 3-7, 

Beijing: China Statistics Press.

varying norms or expectations for health (Hopkins and 

King, 2010; Salomon, Tandon, and Murray, 2004).3

SAGE also used analytical methods that adjust selfreported health based on vignette response patterns, 

the Binormal Hierarchical Ordered Probit (BIHOPIT) 

and Compound Hierarchical Ordered Probit (CHOPIT) 

models. Both are generalizations of the ordered probit 

models and allow the model cut-points to vary by 

the same covariates that the ordinal health response 

variables do. This more analytically intensive approach 

enables modelling to account for different health 

expectations—quantifying systematic reporting biases 

and amplifying the underlying patterns seen in the 

unadjusted results. The health scores compile results 

3 Hopkins, Daniel J. and Gary King. 2010. Improving Anchoring 

Vignettes: Designing Surveys to Correct Interpersonal Incomparability. Public Opinion Quarterly 1-26. doi: 10; Salomon, Joshua A., Ajay 

Tandon, and Christopher J. L. Murray. 2004. Comparability of SelfRated Health: Cross Sectional Multi-Country Survey Using Anchoring 

Vignettes. For the World Health Survey Pilot Study Collaborating Group. 

British Medical Journal 328: 258–261.

from questions in eight health domains. For this report, 

the health score was generated using Item Response 

Theory (IRT) partial credit Rasch models. IRT results are 

population independent, allowing for examination of 

results on a common scale. This level of comparability 

was the goal for presenting results in this report. The 

health scores presented in this report are comparable 

across the countries.

Techniques such as the anchoring vignettes and

use of objective health measures are used to adjust

for systematic reporting biases and improve comparability further. These results are available in other

published literature, including the SAGE Web site 

<www.who.int/healthinfo/systems/sage>. Additional 

information provided by the vignette ratings, specifically how this technique helps to describe the effects 

of different covariates on the level of the underlying 

latent variable and the cut-points on the latent variable 

scale, will be presented in peer-reviewed publications. 
U.S. Census Bureau Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 C-7

The two figures below are an illustration of systematic 

reporting biases in health, using data from the Health 

and Retirement Study (HRS), the Study on Health, 

Ageing and Retirement in Europe (SHARE), and SAGE, 

for one health domain, mobility. HRS and SHARE use 

three vignettes per domain, with only one question 

per vignette, whereas SAGE uses five vignettes per 

domain and two questions per vignette, similar to 

0 20 40 60 80 100

self

v3

v2

v1

Moderate Mild None

USA

0 20 40 60 80 100

self

v3

v2

v1

Germany

0 20 40 60 80 100

self

v3

v2

v1

Sweden

0 20 40 60 80 100

self

v3

v2

v1

Netherlands

0 20 40 60 80 100

self

v3

v2

v1

Spain

0 20 40 60 80 100

self

v3

v2

v1

Italy

0 20 40 60 80 100

self

v3

v2

v1

France

0 20 40 60 80 100

self

v3

v2

v1

Greece

0 20 40 60 80 100

self

v3

v2

v1

Belgium

Extreme Severe

Percent

Figure C-1.

Comparisons of Vignette Ratings for Mobility From HRS and SHARE

Note: “v” refers to vignette questions; “self” refers to the respondent’s own assessment of his/her health.

Sources: Health and Retirement Study (HRS); and Study on Health, Ageing, and Retirement in Europe (SHARE).

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

Moderate Mild

China

Extreme Severe

Percent

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

India

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

Ghana

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

Mexico

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

South Africa

0 20 40 60 80 100

self2

self1

v5q2

v5q1

v4q2

v4q1

v3q2

v3q1

v2q2

v2q1

v1q2

v1q1

Russia

Figure C-2.

Comparisons of Vignette Ratings for Mobility for SAGE Countries

Note: "v" refers to vignette questions; "q" refers to questions in each domain of health; "self" refers to the respondent's own assessment 

of his/her health.

Source: Study on Global Ageing and Adult Health (SAGE), 2007–2010.

None
C-8 Shades of Gray: A Cross-Country Study of Health and Well-Being of the Older Populations in SAGE Countries, 2007–2010 U.S. Census Bureau

Table C-6.

Question Wording, Response Categories, and Type of Administration on Mobility 

Difficulty in HRS 2007, SHARE 2006, and SAGE 2007–2010

Study, year Question

wording

Response

categories

Type of

administration

HRS 2007 Overall, in the last 30 days, how 

much of a problem did you have 

with moving around?

None, mild, moderate, severe, 

extreme

Self-administered

SHARE 2006 Same question as above Same as above Self-administered

SAGE 2007–2010 Same question

Plus: Overall in the last 30 days, 

how much difficulty did you have 

in vigorous activities? 

Same as above Interviewer-administered

Sources: Health and Retirement Study (HRS), 2007; Study on Health, Ageing and Retirement in Europe (SHARE), 2006; and Study on Global Ageing and 

Adult Health (SAGE), 2007–2010.

the patterns for questions about the respondent’s 

own health. In Figure C-1, v1 to v2, or v3, refer to the 

vignettes, moving from high to low levels of mobility 

(for example, a marathon runner in v1 to bed-bound 

person in v2 or v3). Table C-6 lists question wording, 

response categories, and type of administration on 

mobility difficulty comparing HRS 2007, SHARE 2006, 

and SAGE 2007–2010.

Self-reported health (self) responses are roughly similar 

in the United States from HRS, Sweden and Greece from 

SHARE, and Ghana, India, and Mexico from SAGE—with 

roughly 60 percent of respondents having no difficulties with moving around. However, the responses to 

vignettes suggest that the respondents are clearly 

using the ordinal scale quite differently in these countries. The latent scale of mobility used by respondents 

from these countries is quite different—comparing v2 

in HRS and SHARE versus v3 in SAGE (Figure C-2), for 

example—with Sweden, India, and Mexico less than 

40 percent with extreme or severe difficulties, Greece, 

Ghana, and Mexico with more than 40 percent, and the 

United States with over 60 percent reporting extreme 

or severe difficulties to the vignette.

Analyses of the measured tests data from SAGE reveal 

that a composite score on the performance measures, 

derived using factor analysis, is moderately correlated 

with the self-report (r = 0.5). For the mobility domain, 

self-reported or vignette-adjusted mobility showed

very weak correlation with timed walk at normal 

pace (r = –0.12) and with grip strength (r = 0.22). The 

differences do not seem to be driven by reporting 

biases alone, with chronic conditions and social 

networks driving some of the differences. Cross-study 

analyses would be welcome to further explore the 

underlying differences and drivers of health across 

countries.