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U.S. Department of Health and Human Services
National Institutes of Health
NATIONAL INSTITUTE ON AGING
An Aging World: 2015
International Population Reports
Issued March 2016
P95/16-1
By Wan He, Daniel Goodkind, and Paul Kowal
Acknowledgments
This report was prepared by Wan He and Daniel Goodkind of the U.S. Census Bureau,
and Paul Kowal of the World Health Organization's (WHO) SAGE, under the direction
of Loraine A. West, Chief, Demographic and Economic Studies Branch, and general
direction of Glenn Ferri, Assistant Division Chief, International Programs and James
D. Fitzsimmons, former Acting Assistant Division Chief, International Programs Center
for Demographic and Economic Studies, Population Division. Karen Humes, Chief,
Population Division provided overall direction.
The authors wish to give special acknowledgment to the following researchers who
graciously contributed to text boxes that focus on special and frontier research topics
in population aging: Martina Brandt, TU Dortmund University; Robert Cumming,
University of Sydney; Christian Deindl, University of Cologne; Karen I. Fredriksen-
Goldsen, University of Washington; Mary C. McEniry, University of Wisconsin-Madison;
Joel Negin, University of Sydney; and Kirstin N. Sterner, University of Oregon.
Research for and production of this report were supported under an interagency
agreement with the Division of Behavioral and Social Research, National Institute on
Aging (NIA).
The authors are grateful to many people within the Census Bureau who made this publi-
cation possible by providing literature and data search, table and graph production, verifi-
cation, and other general report preparation: Samantha Sterns Cole, Laura M. Heaton,
Mary Beth Kennedy, Robert M. Leddy, Jr., Lisa R. Lollock, Andrea Miles, Iris Poe,
and David Zaslow.
The authors give special thanks to Joshua Comenetz, Population Division, for his
thorough review. Reviewers from NIA provided valuable comments and constructive
suggestions, including: David Bloom, Harvard University; David Canning, Harvard
University; Somnath Chatterji, World Health Organization; Eileen Crimmins, University
of Southern California; Ronald D. Lee, University of California, Los Angeles, Berkeley;
Alyssa Lubet, Harvard University; Angela M. O’Rand, Duke University; John Romley,
University of Southern California; Amanda Sonnega, University of Michigan; and anony-
mous reviewers from NIA.
Statistical testing review was conducted by James Farber, Demographic Statistical
Methods Division. For cartographic work, the authors thank Steven G. Wilson and
John T. Fitzwater, Population Division.
Christine E. Geter of the Census Bureau’s Public Information Office and Linda Chen
and Faye Brock of the Center for New Media and Promotion provided publication
management, graphics design and composition, and editorial review for print and elec-
tronic media. George E. Williams of the Census Bureau's Administrative and Customer
Services Division provided printing management.
In Memory of Dr. Richard M. Suzman
The Population Division of the U.S. Census Bureau wishes to express our deep
gratitude and pay tribute to Dr. Richard M. Suzman, director of Division of
Behavioral and Social Research, National Institute on Aging, who passed away
on April 16, 2015. A pioneer and champion for the science of population aging,
Dr. Suzman played a critical role in developing the aging research program in the
Population Division. For over three decades he steadfastly supported numerous
Census Bureau publications focused on population aging trends and demographic,
socioeconomic, and health characteristics of the older populations in the United
States and the world. Enormously popular report series such as 65+ in the United
States and An Aging World are a remarkable testimony to Dr. Suzman’s dedication
to research on population aging which, in his words, is reshaping our world.
U.S. Department of Commerce
Penny Pritzker,
Secretary
Bruce H. Andrews,
Deputy Secretary
Economics and Statistics Administration
Justin Antonipillai,
Counselor, Delegated Duties of
Under Secretary for Economic Affairs
U.S. CENSUS BUREAU
John H. Thompson,
Director
P95/16-1
An Aging World: 2015 Issued March 2016
Suggested Citation
Wan He, Daniel Goodkind, and Paul Kowal
U.S. Census Bureau,
International Population Reports, P95/16-1,
An Aging World: 2015,
U.S. Government Publishing Office,
Washington, DC,
2016.
Economics and Statistics
Administration
Justin Antonipillai,
Counselor, Delegated Duties of
Under Secretary for Economic Affairs
U.S. CENSUS BUREAU
John H. Thompson,
Director
Nancy A. Potok,
Deputy Director and Chief Operating Officer
Enrique Lamas,
Associate Director for Demographic Programs
Karen Humes,
Chief, Population Division
ECONOMICS
AND STATISTICS
ADMINISTRATION
For sale by the Superintendent of Documents, U.S. Government Printing Office
Internet: bookstore.gpo.gov Phone: toll-free 866-512-1800; DC area 202-512-1800
Fax: 202-512-2250 Mail: Stop SSOP, Washington, DC 20402-0001
U.S. Census Bureau An Aging World: 2015 iii
Contents
Chapter 1. Introduction . . . . . . . . . . . . . . . . . . 1
Chapter 2. Aging Trends . . . . . . . . . . . . . . . . . 3
Growth of world's older population will continue to outpace that
of younger population over the next 35 years . . . . . . . . 3
Asia leads world regions in speed of aging and size of older
population . . . . . . . . . . . . . . . . . . . . . . 6
Africa is exceptionally young in 2015 and will remain so in the
foreseeable future . . . . . . . . . . . . . . . . . . . 6
World’s oldest countries mostly in Europe today, but some Asian
and Latin American countries are quickly catching up . . . . . 9
The two population billionaires, China and India, are on drastically
different paths of aging . . . . . . . . . . . . . . . . . 10
Some countries will experience a quadrupling of their oldest
population from 2015 to 2050 . . . . . . . . . . . . . . 11
Chapter 3. The Dynamics of Population Aging . . . . . . . . 15
Total fertility rates have dropped to or under replacement level
in all world regions but Africa . . . . . . . . . . . . . . 15
Fertility declines in Africa but majority of African countries still
have above replacement level fertility in 2050 . . . . . . . . 18
Some countries to experience simultaneous population aging
and population decline . . . . . . . . . . . . . . . . . 22
Composition of dependency ratio will continue to shift toward
older dependency . . . . . . . . . . . . . . . . . . . 23
Median ages for countries range from 15 to near 50 . . . . . . 25
Sex ratios at older ages range from less than 50 to over 100 . . . 26
Chapter 4. Life Expectancy, Health, and Mortality . . . . . . 31
Deaths from noncommunicable diseases rising . . . . . . . . 31
Life expectancy at birth exceeds 80 years in 24 countries while
it is less than 60 years in 28 countries . . . . . . . . . . . 32
Living longer from age 65 and age 80 . . . . . . . . . . . . 35
Yes, people are living longer, but how many years will be lived
in good health? . . . . . . . . . . . . . . . . . . . . 36
Big impacts, opposite directions? Smoking and obesity . . . . . 38
Change is possible! . . . . . . . . . . . . . . . . . . . 44
What doesn’t kill you, makes you . . . possibly unwell . . . . . . 45
Presence of multiple concurrent conditions increases with age . . 48
Trend of age-related disability varies by country . . . . . . . . 48
Frailty is a predisabled state . . . . . . . . . . . . . . . . 49
The U-shape of subjective well-being by age is not observed
everywhere. . . . . . . . . . . . . . . . . . . . . . 50
Chapter 5. Health Care Systems and Population Aging . . . . 65
Increasing focus on universal health care and aging. . . . . . . 65
Health systems in response to aging . . . . . . . . . . . . . 66
Health system’s response to aging in high-income countries . . . 69
Health system’s response to aging in low- and middle-income
countries . . . . . . . . . . . . . . . . . . . . . . 70
Healthcare cost for aging populations . . . . . . . . . . . . 70
Cost is one thing... . . . . . . . . . . . . . . . . . . . 71
...Ability to pay is another . . . . . . . . . . . . . . . . . 73
Long-term care needs and costs will increase . . . . . . . . . 74
Quantifying informal care and care at home . . . . . . . . . . 79
Other care options: Respite, rehabilitative, palliative, and
end-of-life care . . . . . . . . . . . . . . . . . . . . 81
iv An Aging World: 2015 U.S. Census Bureau
FIGURES
Figure 2-1. Percentage of Population Aged 65 and Over: 2015 and 2050 .............. 4
Figure 2-2. World Population by Age Group: 2015 to 2050 .............. . . . . . . 5
Figure 2-3. Young Children and Older People as a Percentage of Global Population: 1950 to 2050 .... 5
Figure 2-4. Population Aged 65 and Over by Region: 2015 to 2050 .......... . . . . . . 8
Figure 2-5. Percentage Distribution of Population Aged 65 and Over by Region: 2015 and 2050 ..... 8
Figure 2-6. The World’s 25 Oldest Countries and Areas: 2015 and 2050 . . . . . . . . . . . . . . . 10
Figure 2-7. Number of Years for Percentage Aged 65 and Older in Total Population to Triple:
Selected Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Figure 3-1. Total Fertility Rate by Region: 2015, 2030, and 2050 . . . . . . . . . . . . . . . . . 15
Figure 3-2. Population by Age and Sex for China: 2015 and 2050 . . . . . . . . . . . . . . . . . 17
Figure 3-3. Population by Age and Sex for Nigeria: 2015 and 2050 . . . . . . . . . . . . . . . . 19
Figure 3-4. Population by Age and Sex for Kenya: 2015 and 2050 . . . . . . . . . . . . . . . . . 19
Figure 3-5. Percentage Distribution of Population Aged 50 and Over by Number of Surviving Children for
Selected European Countries: 2006–2007 . . . . . . . . . . . . . . . . . . . . 20
Figure 3-6. Type of Support Received by People Aged 50 and Over in Selected European Countries by
Child Status: 2006–2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Figure 3-7. Countries With Expected Decline of at Least 1 Million in Total Population From 2015 to 2050 . 22
Figure 3-8. Dependency Ratios for the World: 2015 to 2050 . . . . . . . . . . . . . . . . . . . 24
Figure 3-9. Dependency Ratios for Indonesia and Zambia: 1980, 2015, and 2050 . . . . . . . . . . . 24
Figure 3-10. Countries With Lowest or Highest Median Age in 2015: 2015, 2030, and 2050 . . . . . . . 25
Figure 3-11. Difference Between Female and Male Populations by Age in the United States: 2010 . . . . . 26
Figure 3-12. Sex Ratio for World Total Population and Older Age Groups: 2015 . . . . . . . . . . . . 27
Figure 3-13. Sex Ratios for Population Aged 65 and Over for Bangladesh and Russia: 1990 to 2050 . . . . 28
Figure 4-1. Mean Age of Death in Global Burden of Disease Regions: 1970 and 2010 . . . . . . . . . 32
Figure 4-2. Countries With Highest and Lowest Life Expectancy at Age 65 by Sex: 2015 and 2050 . . . . 35
Chapter 6. Work and Retirement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Labor force participation rates vary sharply by age and sex . . . . . . . . . . . . . . . . . . 91
Older population in higher income countries less likely to be in labor force . . . . . . . . . . . . 92
Gender gap in labor force participation rate is narrowing . . . . . . . . . . . . . . . . . . . 95
Labor force participation among the older population continues to rise in many developed countries . . 95
Share of the older, employed population working part-time varies across countries . . . . . . . . . 98
Unemployment patterns vary across sexes and over time . . . . . . . . . . . . . . . . . . . 102
Expectations and realities—many workers uncertain about their lifestyle after retirement and many
retire earlier than expected . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Statutory retirement ages vary widely across world regions, yet tend to lump at certain ages . . . . . 108
Chapter 7. Pensions and Old Age Poverty . . . . . . . . . . . . . . . . . . . . . . . . . 115
Number of countries offering a public pension continues to rise . . . . . . . . . . . . . . . . . 115
Earnings-related pension programs are still the most common . . . . . . . . . . . . . . . . . 115
Public pension coverage greater in high-income countries . . . . . . . . . . . . . . . . . . . 117
Opinions differ on how to improve sustainability of public pension systems . . . . . . . . . . . . 119
The Chilean model undergoes further reform and some countries abandon it completely . . . . . . . 122
The bigger financial picture includes other sources of income . . . . . . . . . . . . . . . . . . 124
Families play a major support role in many societies . . . . . . . . . . . . . . . . . . . . . 126
Pensions can drastically lower poverty rates for the older population . . . . . . . . . . . . . . . 127
Chapter 8. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Population growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Health and health care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Work, retirement, and pensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Appendix A. Country Composition of World Regions . . . . . . . . . . . . . . . . . . . . 135
Appendix B. Detailed Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Appendix C. Sources and Limitations of the Data . . . . . . . . . . . . . . . . . . . . . 165
U.S. Census Bureau An Aging World: 2015 v
Figure 4-3. Drivers of Increase or Decrease in Life Expectancy at Age 60 by Sex, Region, and Income:
1980 to 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Figure 4-4. Life Expectancy (LE) and Healthy Life Years (HALE) at Age 65 by Sex for
Selected European Countries: 2012 . . . . . . . . . . . . . . . . . . . . . . . 37
Figure 4-5. Percentage Distribution of Cumulative Risk Factors Among People Aged 50 and Over
for Six Countries: 2007–2010 . . . . . . . . . . . . . . . . . . . . . . . . . 39
Figure 4-6. United States Healthy Life Expectancy at Age 65 by Sex and State: 2007–2009 . . . . . . . 40
Figure 4-7. Caloric Intake in Early Life and Diabetes in Later Life . . . . . . . . . . . . . . . . . 43
Figure 4-8. Projected 2025 Deaths by Age, Income Level, and Projection Assumptions . . . . . . . . . 44
Figure 4-9. Number of People Aged 50 and Over Living With HIV for Selected Regions: 1995 to 2013 . . . 47
Figure 4-10. Percentage With Comprehensive Knowledge About HIV and AIDS by Age and Country:
Selected Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Figure 4-11. Activity of Daily Living Limitations by Age for the United States and England: 1998 to 2008 . . 49
Figure 4-12. Well-Being and Happiness by Age and Sex in Four Regions: 2006–2010 . . . . . . . . . . 51
Figure 4-13. Age Acceleration in Liver Tissue and BMI . . . . . . . . . . . . . . . . . . . . . . 53
Figure 5-1. Proportion of Quality Measures for Which Members of Selected Groups Experienced Better,
Same, or Worse Quality of Care Compared With Reference Group in the United States: 2011 . . 69
Figure 5-2. Out-of-Pocket Health Care Expenditures as a Percentage of Household Income by Age Group
and Income Category in the United States: 2009 . . . . . . . . . . . . . . . . . . 71
Figure 5-3. Predicted Quarterly Primary Care Costs by Time to Death and Age in Italy: 2006–2009 . . . . 72
Figure 5-4. Source of Payment for Health Care Services by Type of Service for Medicare Enrollees
Aged 65 and Over in the United States: 2008 . . . . . . . . . . . . . . . . . . . 73
Figure 5-5. Financial Impacts of Having a Household Member Aged 50 and Over
in Six Middle-Income Countries: 2007–2010 . . . . . . . . . . . . . . . . . . . 74
Figure 5-6. Percentage Receiving Long-Term Care Among Population Aged 65 and Over
in Selected Countries: Circa 2011 . . . . . . . . . . . . . . . . . . . . . . . 75
Figure 5-7. Annual Growth Rate in Public Expenditure on Long-Term Care (LTC) in Institutions and at
Home in Selected Countries: 2005–2011 . . . . . . . . . . . . . . . . . . . . . 76
Figure 5-8. Cumulative Growth in Elder Care Homes in Selected Chinese Cities: 1952 to 2009 . . . . . . 77
Figure 5-9. Percentage of Population Aged 50 and Over Who Report Being Informal Caregivers
in Selected European Countries: 2010 . . . . . . . . . . . . . . . . . . . . . . 79
Figure 5-10. Percentage of Canadians Providing Care to Older Population or Receiving Care
by Age Group: 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Figure 5-11. Percentage of Women Among Informal Caregivers Aged 50 and Over
in Selected European Countries: 2010 . . . . . . . . . . . . . . . . . . . . . . 81
Figure 6-1. Labor Force Participation Rates for Population Aged 65 and Over by Sex and World Region:
2010 Estimate and 2020 Projection . . . . . . . . . . . . . . . . . . . . . . . 93
Figure 6-2. Labor Force Participation Rates for Population Aged 65 and Over
for Selected African Countries: 2011 . . . . . . . . . . . . . . . . . . . . . . 94
Figure 6-3. Labor Force Participation Rates for Men Aged 65 and Over in More Developed Countries:
1990s and 2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Figure 6-4. Labor Force Participation Rates for Women Aged 65 and Over in More Developed Countries:
1990s and 2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Figure 6-5. Labor Force Participation Rates for Men Aged 65 and Over in Less Developed Countries:
1990s and 2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Figure 6-6. Labor Force Participation Rates for Women Aged 65 and Over in Less Developed Countries:
1990s and 2012 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Figure 6-7. Employment Status of Employed Men Aged 65 and Over by Country: 2013 . . . . . . . . 100
Figure 6-8. Employment Status of Employed Women Aged 65 and Over by Country: 2013 . . . . . . . 101
Figure 6-9. Unemployment Rate for Men and Women Aged 65 and Over by Country: 2005 and 2013 . . . 102
Figure 6-10. Unemployment Rate for Men and Women Aged 55 to 64 and Over by Country:
2005 and 2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Figure 6-11. Unemployment Rates for Population Aged 25 to 54 and Aged 65 and Over for Portugal,
South Korea, United Kingdom, and United States: 2000 to 2013 . . . . . . . . . . . 105
vi An Aging World: 2015 U.S. Census Bureau
Figure 6-12. Work Plans After Retirement by Workers and Retirees for Selected Countries: 2013 . . . . . 106
Figure 6-13. Workers Who Are Not Confident About Having A Comfortable Lifestyle in Retirement
by Country: 2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Figure 6-14. Workers’ Expectations Regarding Standard of Living in Retirement in the United States
by Generation: 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Figure 6-15. Percentage Distribution of Statutory Pensionable Age by Region and Sex: 2012/2014 . . . . 109
Figure 7-1. Number of Countries With Public Old Age/Disability/Survivors Programs:
1940 to 2012/2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Figure 7-2. Contribution Rates for Old Age Social Security Programs by Country and Contributor:
2012 and 2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
Figure 7-3. Proportion of Labor Force Covered by Public Pension Systems in Each Country: 2005–2012 . . 117
Figure 7-4. Public Pension Net Replacement Rate for Median Earners by Country: 2013 . . . . . . . . 119
Figure 7-5. Total Public Benefits to Population Aged 60 and Over as a Percentage of GDP:
2010 and 2040 Projection . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Figure 7-6. Favored Options to Increase Sustainability of Government Pensions by Country: 2013 . . . . 121
Figure 7-7. Percentage of Labor Force Contributing to Individual Account Pensions by Country:
2004 and 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Figure 7-8. Income Distribution for Population Aged 65 and Over by Source and Country: 2011 . . . . . 125
Figure 7-9. Average Income Tax Rate for Ages 18–65 and Over Age 65 by Country: 2011 . . . . . . . 126
Figure 7-10. Poverty Rate for Total Population and Population Aged 65 and Over for OECD
Countries: 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Figure 7-11. Poverty Rate for Total Population and Population Aged 65 and Over for Latin America and the
Caribbean: 2005 to 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Figure 7-12. Poverty Rate Among Those Aged 60 and Over by Percentage Receiving Pension
in Latin America and the Caribbean: 2005 to 2007 . . . . . . . . . . . . . . . . . 129
TABLES
Table 2-1. World Total Population and Population Aged 65 and Over by Sex: 2015, 2030, and 2050 . . . 3
Table 2-2. Population Aged 65 and Over by Region: 2015, 2030, and 2050 . . . . . . . . . . . . . 6
Table 2-3. Countries With Percentage of Population Aged 80 and Over Projected to Quadruple: 2010–2050 . . 11
Table 3-1. Ten Lowest and Highest Total Fertility Rates for African Countries: 2015, 2030, and 2050 . . . 18
Table 3-2. Median Age by Sex and Region: 2015, 2030, and 2050 . . . . . . . . . . . . . . . . 25
Table 4-1. Age-Standardized Mortality Rates by Cause of Death, WHO Region, and Income Group: 2012 . 32
Table 4-2. Life Expectancy at Birth by Sex for World Regions: 2015 and 2050 . . . . . . . . . . . . 33
Table 4-3. Countries With Highest and Lowest Life Expectancy at Birth by Sex in 2015
and Projected for 2050 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Table 4-4. GDP per Capita and Caloric Intake in Selected Countries and Areas: 1930s and 2000s . . . . 42
Table 4-5. Disability-Adjusted Life Years (DALYs) Attributable to Chronic Noncommunicable
Diseases for World Population Aged 60 and Over: 1990 and 2010 . . . . . . . . . . . 45
Table 4-6. Odds Ratios for Effect of Age, Sex, and Educational Attainment on Multimorbidity
for World Regions: 2002–2004 . . . . . . . . . . . . . . . . . . . . . . . . . 48
Table 4-7. Disability Prevalence Rate by Age Group for Malawi: 2008 . . . . . . . . . . . . . . . 48
Table 5-1. Country Distribution of Share of Population Without Legal Health Coverage by Region . . . . 66
Table 6-1. Labor Force Participation Rates by Age and Sex in Selected Countries: 2012 . . . . . . . . 92
Table 6-2. Gender Gap in Labor Force Participation Rates for Population Aged 65 and Over
by Country: 1990s and 2012 . . . . . . . . . . . . . . . . . . . . . . . . . 95
Table 6-3. Labor Force Participation Rates for Older Workers in Selected Countries: 2001 and 2011 . . . 99
Table 7-1. Number and Percentage of Public Pension Systems by Type of Scheme and World Region . . . 116
Table 7-2. Characteristics of Latin American Individual Account Pensions: 2009 . . . . . . . . . . . 122
Table 7-3. Population Aged 65 and Over in Poverty by Pension Status for Selected Countries
in Latin America and the Caribbean: 2005 to 2007 . . . . . . . . . . . . . . . . . 129
U.S. Census Bureau An Aging World: 2015 vii
BOXES
Box 1-1. Geographic Terms in This Report . . . . . . . . . . . . . . . . . . . . . . . . . 2
Box 1-2. Population Projections Data in This Report . . . . . . . . . . . . . . . . . . . . . 2
Box 2-1. Demographic Transition and Population Aging . . . . . . . . . . . . . . . . . . . . 7
Box 2-2. Doubling of the Share of Older Population, or Is It Tripling? . . . . . . . . . . . . . . . 12
Box 3-1. China's One-Child Policy and Population Aging . . . . . . . . . . . . . . . . . . . . 16
Box 3-2. Support of Childless Older People in an Aging Europe . . . . . . . . . . . . . . . . . 20
Box 4-1. Early Life Conditions and Older Adult Health . . . . . . . . . . . . . . . . . . . . . 41
Box 4-2. The Rising Tide of Aging With HIV . . . . . . . . . . . . . . . . . . . . . . . . . 46
Box 4-3. Epigenetics of Aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Box 5-1. Global Aging and Minority Populations: Health Care Access, Quality of Care, and Use
of Services . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Box 5-2. Social Networks and Health Care Utilization . . . . . . . . . . . . . . . . . . . . . 78
Box 6-1. Impact of the Great Recession on the Older Population . . . . . . . . . . . . . . . . 104
Box 6-2. A Second Demographic Dividend?—Age Structure, Savings, and Economic Growth . . . . . . 110
Box 7-1. Defined Benefit and Defined Contribution Pensions in Selected African Countries . . . . . . 118
Box 7-2. Chile’s Second Round of Pension Reform . . . . . . . . . . . . . . . . . . . . . . 124
APPENDIX TABLES
Table B-1. Total Population, Percentage Older, and Percentage Oldest Old: 1950, 1980, 2015, and 2050 . . 137
Table B-2. Percentage Change in Population for Older Age Groups by Country: 2010 to 2030
and 2030 to 2050 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Table B-3. Median Age: 2015, 2030, and 2050 . . . . . . . . . . . . . . . . . . . . . . . . 144
Table B-4. Sex Ratio for Population 35 Years and Over by Age: 2015, 2030, and 2050 . . . . . . . . 148
Table B-5. Dependency Ratios: 2015, 2030, and 2050 . . . . . . . . . . . . . . . . . . . . . 152
Table B-6. Life Expectancy at Birth, Age 65, and Age 80 by Sex for Selected Countries: 2015 and 2050 . . 156
Table B-7. Deficits in Universal Health Protection: Share of Total Population Without Health Protection
by Country . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
Table B-8. Labor Force Participation Rates by Age, Sex, and Country: Selected Years, 1980 to 2012 . . . 160
U.S. Census Bureau An Aging World: 2015 1
CHAPTER 1.
Introduction
The world population continues to
grow older rapidly as fertility rates
have fallen to very low levels in
most world regions and people tend
to live longer. When the global pop-
ulation reached 7 billion in 2012,
562 million (or 8.0 percent) were
aged 65 and over. In 2015, 3 years
later, the older population rose by
55 million and the proportion of the
older population reached 8.5 per-
cent of the total population.1 With
the post World War II baby boom
generation in the United States and
Europe joining the older ranks in
recent years and with the acceler-
ated growth of older populations
in Asia and Latin America, the next
10 years will witness an increase
of about 236 million people aged
65 and older throughout the world.
Thereafter, from 2025 to 2050, the
older population is projected to
almost double to 1.6 billion glob-
ally, whereas the total population
will grow by just 34 percent over
the same period.
Yet the pace of aging has not been
uniform. A distinct feature of global
population aging is its uneven
speed across world regions and
development levels. Most of the
more developed countries in Europe
have been aging for decades, some
for over a century. In 2015, 1 in 6
people in the world live in a more
developed country, but more than a
third of the world population aged
65 and older and over half of the
world population aged 85 and older
live in these countries. The older
populations in more developed
1 Definitions of the older population,
youth, and working age vary across the world
because of differences in age distribution. For
the purpose of this report, unless specified
otherwise, “older population” refers to those
aged 65 and over, “youth” refers to those
under age 20, and “working-age population”
refers to ages 20 to 64.
countries are projected to continue
to grow in size, but at a much
slower pace than those in less
developed countries, particularly in
Asia and Latin America. By 2050,
less than one-fifth of the world’s
older population will reside in more
developed countries.
There are great variations within
the less developed world as well.
Asia stands out as the population
giant, given both the size of its
older population (617.1 million in
2015) and its current share of the
world older population (more than
half). By 2050, almost two-thirds
of the world’s older people will live
in Asia. Even countries experienc-
ing slower aging will see a large
increase in their older populations.
Africa, for instance, is projected
to still have a young population
in 2050 (with those at older ages
projected to be less than 7 percent
of the total regional population), yet
the projected 150.5 million older
Africans would be almost quadruple
the 40.6 million in 2015.
Population aging, while due primar-
ily to lower fertility, also reflects a
human success story of increased
longevity. Today, living to age 70
or age 80 is no longer a rarity in
many parts of the world. However,
increasing longevity has led to
new challenges: How many years
can older people expect to live in
good health? What are the chronic
diseases that they may have to
deal with? How long can they live
independently? How many of them
are still working? Will they have
sufficient economic resources to
last their lifetimes? Can they afford
health care costs? The world is fac-
ing these and many more questions
as population aging continues.
This report covers the demographic,
health, and economic aspects of
global population aging. After an
examination of past and projected
growth of the older population
and dynamics of population aging
(chapters 2 and 3), the report then
covers health, mortality, and health
care of the older population (chap-
ters 4 and 5). Finally, work, pen-
sions, and other economic charac-
teristics of older people (chapters 6
and 7) are addressed. Compared to
previous versions of the report An
Aging World, this edition is unique
for expanding the analysis of aging
trends to all countries and areas,
with an emphasis on the differ-
ences among world regions.2 Where
data are available, it also updates
the latest statistics and trends for
health and economic indicators.
This edition also includes an assess-
ment of the impact of the recent
global recession on older people’s
economic well-being. Moreover, it
includes some frontier research on
special topics of population aging in
the form of text boxes contributed
by non-Census Bureau researchers
with expertise in those fields.
More specifically, Chapter 2, “Aging
Trends,” opens the report and
examines the continuing global
aging trend and projected growth of
the population aged 65 and over. It
also discusses the variations in pop-
ulation aging among world regions
and countries. Chapter 3, “The
Dynamics of Population Aging,”
analyzes fertility decline, the main
propeller of population aging, for
regions and countries. It also exam-
ines aging indicators, including
2 Population projections data encompass
all countries and areas of the world, while
health and economic data are more limited in
coverage across countries and regions. In this
report, the term “countries” includes countries
and areas.
2 An Aging World: 2015 U.S. Census Bureau
dependency ratios, median age, and
sex ratios. Chapters 4 and 5 cover
health and health care related areas,
with Chapter 4, “Life Expectancy,
Health, and Mortality,” reporting on
extended life expectancy at birth
and at older ages, with empha-
sis on healthy life expectancy.
Chapter 4 also discusses leading
causes of death and health condi-
tions and well-being for the older
population. Chapter 5, “Health
Care Systems and Population
Aging,” covers health systems’
response to population aging,
including universal health care. It
also examines cost and affordabil-
ity of health care, long-term care,
and informal care for the older
population. The last two chapters
examine the economic well-being
of the older population. Chapter
6, “Work and Retirement,” updates
international trends in labor force
participation, with special atten-
tion to broad economic dynamics,
such as the second demographic
dividend of changing aging struc-
ture. Chapter 7, “Pensions and Old
Age Poverty,” reviews recent trends
in international pension systems,
such as their coverage of the older
population and their sustainability.
Chapter 7 also presents poverty
levels for the older population and
the crucial role of pensions. The
data used in this report draw heav-
ily from the U.S. Census Bureau’s
International Data Base, as well as
databases developed and main-
tained by organizations such as the
United Nations, the World Health
Organization, the Organisation
for Economic Co-operation and
Development, and the International
Labour Organization. The report
also incorporates data and findings
from the literature.
An Aging World: 2015 is the fifth
report in the Census Bureau’s An
Aging World series—prior reports
were published in 1987, 1993,
2001, and 2008. The Census Bureau
has produced other cross-national
reports covering aging trends and
the characteristics of the older pop-
ulation, including Aging in the Third
World (1988), Aging in Eastern
Europe and the Former Soviet Union
(1993), and Population Aging in
Sub-Saharan Africa: Demographic
Dimensions 2006. This report and
all previously released international
aging reports were commissioned
by the National Institute on Aging,
Division of Behavioral and Social
Research.
Box 1-1.
Geographic Terms in This Report
World regions in this report follow United Nations categories—Africa,
Asia, Europe, Latin America and the Caribbean, Northern America, and
Oceania—unless otherwise noted. See Appendix A for a list of coun-
tries and areas in each region.
The “more developed” and “less developed” country categories used
in this report correspond to the classification employed by the United
Nations. The “more developed” countries include all of Northern
America and Europe plus Japan, Australia, and New Zealand. The “less
developed” countries include all of Africa, all of Asia except Japan, the
Transcaucasian and Central Asian republics, all of Latin America and
the Caribbean, and all of Oceania except Australia and New Zealand.
Box 1-2.
Population Projections Data in This Report
Throughout this report, projections of population size and composition come from the Population Division
of the Census Bureau, unless otherwise indicated. As discussed further in Appendix C, these projections are
based on demographic analysis for each nation, including their population age and sex structures, compo-
nents of population change (rates of fertility, mortality, and net migration), and assumptions about the future
trajectories of population change.
Projections for countries are updated periodically as new data become available. Therefore, the data in this
report are not the latest available for every country and, by extension, for groups of countries aggregated
into regions. The impact of projection updates on indicators of population aging is generally modest and has
little effect on the overall trends described in this report.
Population projections for the United States in this report come from the Census Bureau National Projections
Data, current as of December 2014. Users may find the latest population figures for the United States at
<www.census.gov/population/projections/data/national/2014.html>. The population projections for all
other countries were current as of December 2013 and were drawn from the Census Bureau’s International
Data Base. The latest projections for countries of the world are available at <www.census.gov/population
/international/data/idb/informationGateway.php>.
U.S. Census Bureau An Aging World: 2015 3
CHAPTER 2.
Aging Trends
The world population is aging
rapidly. Today the older population
(aged 65 and over) represents 7
percent or more of the total popula-
tion in many parts of the world—
one notable exception is Africa and
parts of Asia, and Latin America
and the Caribbean (Figure 2-1). By
2050, only 33 countries are pro-
jected to have an older population
comprising less than 7 percent of
their total population, a substantial
reduction from 115 such countries
in 2015. At the same time, the
share of the older population will
exceed 21 percent in 94 countries,
including 39 countries with 28 per-
cent or more of their total popula-
tion being older.
The demographic phenomenon of
population aging is known to many,
although the variation and diversity
might surprise some. How fast will
the older populations in the world
grow in the next few decades?
What are the similarities and differ-
ences among world regions? Which
regions or countries are projected
to age the fastest? Conversely,
which regions or countries will not
experience population-aging pres-
sure in the near future?
GROWTH OF WORLD’S
OLDER POPULATION WILL
CONTINUE TO OUTPACE
THAT OF YOUNGER
POPULATION OVER THE
NEXT 35 YEARS
Among the 7.3 billion people
worldwide in 2015, an estimated
8.5 percent, or 617.1 million, are
aged 65 and older (Table 2-1). The
number of older people is projected
to increase more than 60 percent
in just 15 years—in 2030, there
will be about 1 billion older people
globally, equivalent to 12.0 percent
of the total population. The share
of older population will continue to
grow in the following 20 years—by
2050, there will be 1.6 billion older
people worldwide, representing
16.7 percent of the total world
population of 9.4 billion. This is
equivalent to an average annual
increase of 27.1 million older
people from 2015 to 2050.
In contrast to the 150 percent
expansion of the population aged
65 and over in the next 35 years,
the youth population (under age
20) is projected to remain almost
flat, 2.5 billion in 2015 and 2.6
billion in 2050 (Figure 2-2). Over
the same period, the working-age
population (aged 20 to 64) will
increase only moderately, 25.6
percent. The working-age popula-
tion share of total population will
shrink slightly in the decades to
come, largely due to the impact
of low fertility and increasing life
expectancy.
Perhaps an even more telling
illustration of the sharply different
growth trajectories of the older
and younger populations is the
converging, crossing, and then
diverging of the percentages of
older people and children under
age 5 from 1950 to 2050 (Figure
2-3).1 For the first time in human
history, people aged 65 and over
will outnumber children under age
5. This crossing is just around the
corner, before 2020. These two age
groups will then continue to grow
in opposite directions. By 2050, the
proportion of the population aged
65 and older (15.6 percent) will be
more than double that of children
under age 5 (7.2 percent). This
unique demographic phenomenon
of the “crossing” is unprecedented.
1 Data for population shares aged 65 and
over and under age 5 for 1950 to 2050 come
from the United Nations, 2013.
Table 2-1.
World Total Population and Population Aged 65 and Over by Sex: 2015, 2030, and 2050
(Numbers in millions)
Year Total population Population aged 65 and over Percentage aged 65 and over
Both sexes Male Female Both sexes Male Female Both sexes Male Female
2015. . . . . . . . . . . . . 7,253.3 3,652.0 3,601.3 617.1 274.9 342.2 8.5 7.5 9.5
2030. . . . . . . . . . . . . 8,315.8 4,176.7 4,139.1 998.7 445.2 553.4 12.0 10.7 13.4
2050. . . . . . . . . . . . . 9,376.4 4,681.7 4,694.7 1,565.8 698.5 867.3 16.7 14.9 18.5
Source: U.S. Census Bureau, 2013; International Data Base.
4 An Aging World: 2015 U.S. Census Bureau
Figure 2-1.
Percentage of Population Aged 65 and Over: 2015 and 2050
2015
2050
World percent
2015: 8.5
2050: 16.7
Percent
28.0 or more
21.0 to 27.9
14.0 to 20.9
7.0 to 13.9
Less than 7.0
Sources: U.S. Census Bureau, 2013, 2014a, 2014b; International Data Base, U.S. population estimates, and U.S. population projections.
U.S. Census Bureau An Aging World: 2015 5
Figure 2-2.
World Population by Age Group: 2015 to 2050
Source: U.S. Census Bureau, 2013; International Data Base.
20502045204020352030202520202015
(In millions)
20–24
4,186
5,256
2,554
1,566
447
2,450
617
126
0–19
65 and over
80 and over
Figure 2-3.
Young Children and Older People as a Percentage of Global Population:
1950 to 2050
Source: United Nations, 2013.
0
2
4
6
8
10
12
14
16
18
20502040203020202010200019901980197019601950
Under 5
Percent
65 and over
6 An Aging World: 2015 U.S. Census Bureau
Table 2-2.
Population Aged 65 and Over by Region: 2015, 2030, and 2050
Region Population (in millions) Percentage of regional total population
2015 2030 2050 2015 2030 2050
Africa .............................. 40.6 70.3 150.5 3.5 4.4 6.7
Asia ............................... 341.4 587.3 975.3 7.9 12.1 18.8
Europe ............................. 129.6 169.1 196.8 17.4 22.8 27.8
Latin America and the Caribbean ........ 47.0 82.5 139.2 7.6 11.8 18.6
Northern America .................... 53.9 82.4 94.6 15.1 20.7 21.4
Oceania ............................ 4.6 7.0 9.5 12.5 16.2 19.5
Source: U.S. Census Bureau, 2013; International Data Base.
ASIA LEADS WORLD
REGIONS IN SPEED OF
AGING AND SIZE OF OLDER
POPULATION
World regions vary in their par-
ticular phase of the demographic
transition and differ in their speed
of aging. Using the share of the
older population as an indicator for
aging, Europe historically has been
the oldest region. However, Asia
and Latin America are rapidly pro-
gressing through the demographic
transition and population aging.2
Less than 8 percent of Asians are
aged 65 and older in 2015 (Table
2-2), but this regional average
masks sharp variations within
Asia. While about half of the Asian
countries currently have less than
a 5 percent share for the older
population, some countries in
Asia are among the oldest in the
world. The young countries mostly
are located in South-Central Asia
(e.g., Afghanistan, 2.5 percent),
South-Eastern Asia (e.g., Laos, 3.8
percent), and Western Asia (e.g.,
Kuwait, 2.3; Yemen, 2.7 percent;
and Saudi Arabia, 3.2 percent). In
contrast, East Asia is one of the
oldest sub-regions globally, includ-
ing the oldest major country in
the world—Japan (26.6 percent).
The share of the older population
in Asia is expected to reach 12.1
2 In this report, “Latin America” and
“Latin America and the Caribbean” are used
interchangeably.
percent in 2030 and 18.8 percent
in 2050.
By comparison, Europe is further
along in the demographic transi-
tion and will remain the oldest
region through 2050, even though
the pace of aging will slow dras-
tically. In 2015, 17.4 percent of
Europeans are aged 65 or older. In
most European countries, the share
of the older population already
exceeds 14 percent. By 2050, more
than a quarter of Europeans will
be aged 65 and over, and in all
but two European countries (Faroe
Islands and Kosovo) the older
population will represent at least
20 percent of the total population.
What warrants attention is that
while population aging in Asia
currently is not as advanced as in
Europe or Northern America, its
huge population size simply can-
not be ignored (Figure 2-4). Home
to China and India—countries
with total populations exceeding
1 billion each currently—Asia’s
modest 7.9 percent share of older
population translates into 341.4
million people aged 65 and over.
They represent 55.3 percent of
the world’s total older population
(Figure 2-5). By 2050, 975.3 mil-
lion older people are projected to
be living in Asia, accounting for
nearly two-thirds (62.3 percent) of
the world’s total older population.
In addition, while the projected
speed of aging for Asia and Latin
America are similar, there are seven
times as many older people in Asia
as in Latin America in 2015, and
thus this ratio will be maintained in
2050.
Some South-Eastern and South-
Central Asian countries are still
young in 2015 (percentage of
older population less than 7),
but the size of their older popu-
lation has already surpassed 5
million—Indonesia, 16.9 million;
Bangladesh, 8.7 million; Pakistan,
8.7 million; and Vietnam, 5.5 mil-
lion. By 2050, the population aged
65 and over in these countries will
more than triple to 57.2 million,
36.6 million, 32.8 million, and 23.0
million, respectively.
AFRICA IS EXCEPTIONALLY
YOUNG IN 2015 AND
WILL REMAIN SO IN THE
FORESEEABLE FUTURE
Unlike all other regions, Africa,
the youngest region, is still largely
in the early stages of the demo-
graphic transition with high fertility
rates and a young age structure,
especially in Western, Middle, and
some Eastern African countries.
The vast majority of African coun-
tries today have less than 5 per-
cent of the total population aged
65 and over, and in 21 countries
the share is 3 percent or less (e.g.,
Ethiopia, 2.9 percent and Uganda,
2.0 percent).
U.S. Census Bureau An Aging World: 2015 7
Box 2-1.
Demographic Transition and Population Aging
The classical model of demographic transition refers to the process where a society starts with extremely
high levels of both fertility and mortality and transitions to a point where both rates are low and stable. The
demographic transition impacts both the population growth rate and the age structure of a country.
The demographic transition consists of four stages. At the start—Stage 1, both birth rates and death rates
are high. The natural increase (births minus deaths) is low, the population increases very slowly, and the
country’s age structure is young with a pyramid shape of a large number of children at the base and very
few older people at the top. In Stage 2, mortality, especially infant and child mortality, declines rapidly while
fertility lags and remains high. In this stage, population increases rapidly and the age structure becomes
younger. However, the proportion of the older population starts to grow as mortality rates decrease and
people live longer. In Stage 3, a fertility transition occurs as fertility declines rapidly, accompanied by con-
tinued yet slower declines in infant and child mortality, but accelerated mortality decline at older ages. The
population continues to grow; however, the age structure becomes even older as life expectancy continues to
improve. In Stage 4, both mortality and fertility are low and remain relatively stable, population growth flat-
tens, and the age structure becomes old. No longer is there a wide base of young children and a small tip at
the top for the older population; the shape of the age structure becomes almost rectangular.
Many factors contribute to this process, but it is generally agreed that the initial momentum starts with
improvement in public health, including basic sanitation and advancements in medicine. The increased child
survival rates, along with general improvements in socioeconomic conditions, then affect fertility behavior
through a reduction in the desired number of children. Economic explanations for a lower desired number
of children include mechanization of agriculture and expansion of the nonagrarian economy; the quantity-
quality tradeoff, that parents switch their resources from raising many offspring to a smaller number of “qual-
ity” children; and the opportunity cost for women to have children versus their own labor force participation
(Canning, 2011; Galor, 2012).
Countries vary in the timing of the onset and duration of the stages of the demographic transition. The more
developed countries, especially those in Western and Northern Europe, started the demographic transition
more than a century ago and most took many decades to complete this process. Less developed countries in
Asia and Latin America started this process only in recent decades, and for most of these countries, the tran-
sition is proceeding more quickly. A number of countries in Sub-Saharan Africa are proceeding slowly through
the fertility transition or in some cases experiencing a stall in fertility decline (Bongaarts, 2008). Researchers
point to several possible explanations for the delays in fertility decline in parts of Africa, including slow
economic development, limited improvement in female access to education, and increases in mortality due to
the AIDS epidemic (Bongaarts, 2008; Ezeh, Mberu, and Emina, 2009). On the other hand, Bangladesh serves
as an example of a country achieving major reductions in fertility from the mid-1970s to the mid-1990s
despite low levels of economic development (Cleland, et al., 1994; Khuda and Hossain, 1996).
8 An Aging World: 2015 U.S. Census Bureau
Figure 2-4.
Population Aged 65 and Over by Region: 2015 to 2050
Source: U.S. Census Bureau, 2013; International Data Base.
Millions
Africa
Asia
Northern America/
Oceania
Latin America
and the Caribbean
Europe
0
200
400
600
800
1,000
1,200
1,400
1,600
20502045204020352030202520202015
Northern
America/
Oceania
6.6%
Africa
9.6%
Latin
America
and
the Caribbean
8.9%
Europe
12.6%
Figure 2-5.
Percentage Distribution of Population Aged 65 and Over by Region:
2015 and 2050
Source: U.S. Census Bureau, 2013; International Data Base.
2015 2050
Asia
55.3%
Asia
62.3%
Northern
America/
Oceania
9.5%
Africa
6.6%
Latin
America
and
the Caribbean
7.6%
Europe
21.0%
U.S. Census Bureau An Aging World: 2015 9
Africa, as a region, is exceptional
not only for being young in 2015,
but also for being projected to
remain young over the next few
decades, largely because of sus-
tained high fertility levels leading
to a young age structure in most
Sub-Saharan countries. By 2050, the
older population share is projected
to continue below 7 percent in
Africa. For example, Malawi’s older
population represents 2.7 percent
of the total population in 2015, and
its share is projected to increase to
only 4.2 percent by 2050. Similarly,
Mozambique’s share of the older
population is projected to reach
3.3 percent in 2050, up from 2.9
percent in 2015.
It should be noted that most of
Northern Africa departs from the
African regional pattern—in Tunisia,
the older population share is pro-
jected to rise from 8.0 percent in
2015 to 24.3 percent in 2050; and
Morocco, from 6.4 percent in 2015
to 18.6 percent in 2050. A number
of Eastern African countries will
also age relatively rapidly in the
next 35 years; for example, the
older population share in Kenya is
projected to triple from 2015 (2.9
percent) to 2050 (9.2 percent).
While Africa is a young region,
some African countries already
have a large number of older
people. In 2015, the older popula-
tion exceeds 1 million in 11 African
countries, including Nigeria, 5.6
million; Egypt, 4.6 million; and
South Africa, 3.1 million. By 2050,
more than half of all African coun-
tries are projected to have more
than 1 million older people, includ-
ing 3 countries that will exceed
10 million (Nigeria, 18.8 million;
Egypt, 18.1 million; and Ethiopia,
11.5 million) and another 6 coun-
tries with more than 5 million.
WORLD’S OLDEST
COUNTRIES MOSTLY IN
EUROPE TODAY, BUT
SOME ASIAN AND LATIN
AMERICAN COUNTRIES ARE
QUICKLY CATCHING UP
The percentage of the population
aged 65 and over in 2015 ranged
from a high of 26.6 percent for
Japan to a low of around 1 per-
cent for Qatar and United Arab
Emirates. Of the world’s 25 oldest
countries and areas in 2015, 22
are in Europe, with Germany or
Italy leading the ranks of European
countries for many years (Kinsella
and He, 2009), including currently
(Figure 2-6).3 In 2050, Slovenia and
Bulgaria are projected to be the old-
est European countries.
Japan, however, is currently the
oldest nation in the world and is
projected to retain this position
through at least 2050. With the
rapid aging taking place in Asia,
South Korea, Hong Kong, and
Taiwan will join Japan at the top
of the list of oldest countries and
areas by 2050, when more than
one-third of these Asian countries’
total populations are projected
to be aged 65 and over. The oft-
mentioned European countries,
such as Germany and Italy, while
3 The list of 25 oldest countries and
areas includes countries and areas with a
total population of at least 1 million in 2015.
Some small areas/jurisdictions have high
proportions of older residents. For example,
in 2015, 30.4 percent of all residents of the
European principality of Monaco were aged
65 and over, and the share is projected to
reach 59 percent by 2050.
still among the oldest countries in
2050, will move down the list; and
Sweden, previously near the top,
will be passed by many fast-aging
countries and areas and drop to
84th in 2050.
The United States, with an older
proportion of 14.9 percent in 2015
and ranked 48th among the oldest
countries of the world, is rather
young among more developed
countries. Immigration may play a
role, as foreign-born mothers have
higher fertility levels than native
women and the foreign-born share
of births is disproportionately
higher than their share in the total
population (Livingston and Cohn,
2012).4 Even with the large infusion
of older people from the post-WWII
Baby Boom cohort (people born
between mid-1946 and 1964) that
began in 2011, the older share of
total population in 2050 (projected
to be 22.1 percent) will push the
United States down to 85th posi-
tion, in the middle range among all
countries in the world. Because of
their rapid aging, Asian countries
such as South Korea (35.9 percent),
Taiwan (34.9 percent), and Thailand
(27.4 percent), and Latin American
countries such as Cuba (28.3
percent) and Chile (23.2 percent)
are projected to be older than the
United States in 2050, even though
they are younger than the United
States in 2015. Tunisia stands out
as an African country that will rank
69th in the world in 2050 with 24.3
percent aged 65 and over (older
than the United States), up from a
97th ranking in 2015.
4 See Chapter 3 for more discussion on
fertility and population aging.
10 An Aging World: 2015 U.S. Census Bureau
Figure 2-6.
The World's 25 Oldest Countries and Areas: 2015 and 2050
Note: The list includes countries and areas with a total population of at least 1 million in 2015.
Source: U.S. Census Bureau, 2013; International Data Base.
0 10 20 30 40
Puerto Rico
Latvia
Serbia
United Kingdom
Spain
Canada
Switzerland
Netherlands
Czech Republic
Hungary
Croatia
Slovenia
France
Denmark
Portugal
Estonia
Belgium
Austria
Bulgaria
Sweden
Finland
Greece
Italy
Germany
Japan
0 10 20 30 40
Serbia
Czech Republic
Ukraine
Croatia
Hungary
Slovakia
Germany
Austria
Puerto Rico
Portugal
Italy
Spain
Latvia
Romania
Poland
Lithuania
Bosnia and Herzegovina
Greece
Estonia
Bulgaria
Slovenia
Taiwan
Hong Kong
South Korea
Japan
Asia Europe Northern America
2015 2050
Percentage of population aged 65 and over Percentage of population aged 65 and over
THE TWO POPULATION
BILLIONAIRES, CHINA
AND INDIA, ARE ON
DRASTICALLY DIFFERENT
PATHS OF AGING
In 2015, the total population of
China stands at 1.4 billion, with
India close behind at 1.3 billion.
It is projected that 10 years from
now, by 2025, India will surpass
China and become the most popu-
lous country in the world.
However, these two population
giants are on drastically different
paths of population aging, thanks
largely to different historical fertil-
ity trends. Although both China and
India introduced family planning
programs decades ago (see Box
3-2 for a discussion of the impact
of China’s program), the fertility
level in India has remained well
above the level in China since the
1970s. Historic fertility levels have
affected the pace of aging in these
two countries. In 2015, the older
population in China represents
10.1 percent of its total population,
while the share is only 6.0 percent
in India. By 2030, after India is
projected to have overtaken
China in terms of total population,
8.8 percent of India’s population
U.S. Census Bureau An Aging World: 2015 11
Table 2-3.
Countries With Percentage of Population Aged 80 and Over Projected to Quadruple:
2010–2050
Africa ............................. Cote d’Ivoire, Egypt, Libya, Mauritius, Tunisia
Asia ..............................Bahrain, Bangladesh, Brunei, Burma, Cambodia, China, India, Indonesia, Kuwait, Malaysia,
Mongolia, North Korea, Qatar, Saudi Arabia, Singapore, South Korea, Syria, Thailand, Timor-Leste,
Turkey, Turkmenistan, United Arab Emirates, Vietnam
Europe ............................ Bosnia and Herzegovina
Latin America and the Caribbean .......Brazil, Colombia, Costa Rica, Cuba, Nicaragua, Trinidad and Tobago
Northern America; Oceania ............ Papua New Guinea
Note: The list includes countries with a total population of at least 1 million in 2015.
Source: U.S. Census Bureau, 2013; International Data Base.
will be aged 65 and older, or 128.9
million people. In contrast, in the
same year, China will have nearly
twice the number and share of
older population (238.8 million
and 17.2 percent). By 2050, it is
projected that China will have 100
million more older people than
India, 348.8 million compared with
243.4 million, even though China’s
projected total population of 1.304
billion will be 352.8 million fewer
than India’s total population of
1.657 billion.
The sheer size of China’s older pop-
ulation can be further illustrated by
comparing its 65-and-older popula-
tion with the population of all ages
in some other populous countries.
In 2015, the number of older peo-
ple in China (136.9 million) exceeds
Japan’s total population (126.9 mil-
lion). In 2030, the total projected
populations of Japan plus Egypt
(231.8 million) will be smaller
than China’s projected 65-and-
older population (238.8 million).
By 2050, it will take the combined
total populations of Japan, Egypt,
Germany, and Australia (345.6 mil-
lion) to match the older population
in China (348.8 million).
SOME COUNTRIES
WILL EXPERIENCE A
QUADRUPLING OF THEIR
OLDEST POPULATION FROM
2015 TO 2050
The older population itself has
been aging, with the oldest seg-
ment growing faster than the
younger segment because of
increasing life expectancy at older
ages. In the United States, for
example, life expectancy at age 65
increased from 11.9 years in 1900–
1902 to 19.1 years in 2010, and for
age 80 from 5.3 to 9.1 years dur-
ing the same span of time (Arias,
2014). Worldwide, the population
aged 80 and over is projected to
more than triple between 2015 and
2050, from 126.5 million to 446.6
million (Figure 2-2).
The 80-and-older population in
some rapidly aging Asian and Latin
American countries will go through
remarkable growth; their share of
the total population in the next
35 years is projected to quadruple
from 2015 to 2050 (Table 2-3). In
Asia, 23 countries are projected
to experience this quadrupling. In
contrast, because the vast majority
of European countries started the
aging process long ago and now
are experiencing a slowdown in the
speed of aging, only one European
country, Bosnia and Herzegovina,
is projected to see a quadrupling of
their population aged 80 and over
during the 2015 to 2050 period.
Within the oldest populations,
those at extremely old ages (90
and older, or 100 and older) are
growing faster than their younger
counterparts in some countries,
even though they are a very small
portion of the total population.
From 1980 to 2010, U.S. census
data showed that the 90 and older
population almost tripled over
the period, compared to a dou-
bling of the population aged 65
to 89 (He and Muenchrath, 2011).
Centenarians, people aged 100 or
older, increased by 65.8 percent in
the United States during the same
period of time (Meyer, 2012). These
oldest old people are distinct from
the rest of the older population in
many sociodemographic character-
istics and are more likely to have
chronic conditions that require
long-term care, thus may consume
public resources disproportionately
and constitute a heavier burden
on informal care often provided by
families (National Institute on Aging
and U.S. Department of State,
2007; Tsai, 2010).
12 An Aging World: 2015 U.S. Census Bureau
Box 2-2.
Doubling of the Share of Older Population, or Is it Tripling?
A commonly used indicator for the speed of population aging is the number of years for a country’s popula-
tion aged 65 and over to double from 7 percent of the total population to 14 percent. It is often noted that
it took France 115 years for its share of older population to achieve this doubling, and many European and
Northern American countries waited more than half a century for this doubling to complete—Sweden, 85 years;
Australia, 73 years; and the United States, 69 years (Figure 2-7). Japan is an exception among the more devel-
oped countries. It took Japan only 25 years (1970 to 1995) to have its older population double from 7 percent
to 14 percent of its total population.
While most of the more developed countries have already completed this doubling, the less developed coun-
tries, especially those in Asia and Latin America, started this process in the 21st century and are moving at a
much faster speed. That the doubling may take only a couple of decades in China and many other Asian and
Latin American countries raises serious concerns in these countries regarding their readiness to deal with a rap-
idly aging society. As the Director-General of the World Health Organization pointed out at the United Nation’s
Second World Assembly on Ageing in 2002, “We must be aware that the developed countries became rich
before they became old, the developing countries will become old before they become rich” (Butler, 2002).
In the near future, countries may face not just doubling but tripling of the share of the older population from
7 percent to 21 percent of the total population. Japan, the oldest country in the world, achieved its tripling in
2007, and today’s older Japanese represent about 27 percent of the total population. Projections show that by
2030, a short 15 years from now, the majority of European countries (32 out of 42) will have completed this
tripling.
The tripling will take place in some rapidly aging Asian and Latin American countries at an accelerated pace.
South Korea, for example, is projected to take just 18 years for its older population to double from 7 percent to
14 percent, and half that time (9 years) to reach 21 percent. Chile’s doubling will take 26 years and just another
16 years to complete the tripling.
Figure 2-7.
Number of Years for Percentage Aged 65 and Older in Total Population to Triple:
Selected Countries
5
6
6
37
38
42
58
80
37
35
34
27
89
81
100
99
125
157
(Number of years)
South Korea (2000–2027)
China (2001–2035)
Thailand (2003–2038)
Japan (1970–2007)
Tunisia (2007–2044)
Brazil (2012–2050)
Chile (1999–2041)
Poland (1966–2024)
Hungary (1941–2021)
Spain (1947–2028)
United States (1944–2033)
Australia (1938–2037)
United Kingdom (1930–2030)
Sweden (1890–2015)
France (1865–2022) 115
85
45
73
69
45
53
45
26
21
24
25
21
23
18
13
16
17
13
12
14
11
9
27
36
20
26
55
40
42
Years to increase from
7 percent to 14 percent Years to increase from
14 percent to 21 percent
Sources: Kinsella and Gist, 1995; U.S. Census Bureau, 2013, 2014a, 2014b; International Data Base, U.S. population estimates,
and U.S. population projections.
U.S. Census Bureau An Aging World: 2015 13
Chapter 2 References
Arias, Elizabeth. 2014. United
States Life Tables, 2010.
National Vital Statistics Reports
63/7. Hyattsville, MD: National
Center for Health Statistics.
Bongaarts, John. 2008. “Fertility
Transitions in Developing
Countries: Progress or
Stagnation?” Population Council
Poverty, Gender, and Youth
Working Paper 7.
Butler, Robert N. 2002. “Guest
Editorial: Report and
Commentary From Madrid:
The United Nations World
Assembly on Ageing.” Journal
of Gerontology: Medical Sciences
57/12: M770-M771.
Canning, David. 2011. “The
Causes and Consequences of
the Demographic Transition.”
Harvard University Program on
the Global Demography of Aging
Working Paper 79.
Cleland, John, James F. Phillips,
Sajeda Amin, and G. M. Kamal.
1994. “The Determinants
of Reproductive Change in
Bangladesh: Success in a
Challenging Environment.”
Washington, DC: The World Bank.
Ezeh, Alex C., Blessing U. Mberu,
and Jacques O. Emina. 2009.
“Stall in Fertility Decline in
Eastern African Countries:
Regional analysis of patterns,
determinants, and implications.”
Philosophical Transactions of the
Royal Society B 364: 2991–3007.
Galor, Oded. 2012. “The
Demographic Transition: Causes
and Consequences.” The
Institute for the Study of Labor
(IZA) Discussion Paper 6334.
He, Wan and Mark N. Muenchrath.
2011. 90+ in the United
States: 2006–2008. American
Community Survey Reports,
ACS-17, U.S. Census Bureau.
Washington, DC: U.S.
Government Printing Office.
Khuda, Barkat-e- and Mian Bazle
Hossain. 1996. “Fertility Decline
in Bangladesh: Toward an
Understanding of Major Causes.”
Health Transition Review,
Supplement 6: 155–167.
Kinsella, Kevin and Wan He.
2009. An Aging World:
2008. International Population
Reports, P95/09-1, U.S. Census
Bureau. Washington, DC:
U.S. Government Printing Office.
Kinsella, Kevin and Yvonne J.
Gist. 1995. Older Workers,
Retirement, and Pensions:
A Comparative International
Chartbook. IPC/95-2,
U.S. Census Bureau. Washington,
DC: U.S. Government Printing
Office.
Livingston, Gretchen and D’Vera
Cohn. 2012. U.S. Birth Rate
Falls to a Record Low; Decline
Is Greatest Among Immigrants.
Pew Research Center, Social &
Demographic Trends.
Meyer, Julie. 2012. Centenarians:
2010. 2010 Census Special
Reports, C2010SR-03,
U.S. Census Bureau. Washington,
DC: U.S. Government Printing
Office.
National Institute on Aging (NIA)
and U.S. Department of State.
2007. Why Population Aging
Matters: A Global Perspective.
National Institute on Aging
of National Institutes on
Health Publication 07-6134.
Washington, DC: National
Institute on Aging of National
Institutes on Health.
Tsai, Tyjen. 2010. More Caregivers
Needed Worldwide for the
“Oldest Old.” Washington, DC:
Population Reference Bureau.
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Population Prospects: The
2012 Revision. United Nations
Population Division of the
Department of Economic and
Social Affairs.
U.S. Census Bureau. 2013.
International Data Base.
Available at <www.census.gov
/population/international/data
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_____. 2014a. Current Estimates
Data. Available at
<www.census.gov/population
/popest/data/>, accessed on
December 11, 2014.
_____. 2014b. 2014 National
Projections. Available at
<www.census.gov/population
/projections/data/national
/2014.html>, accessed on
December 11, 2014.
U.S. Census Bureau An Aging World: 2015 15
CHAPTER 3.
The Dynamics of Population Aging
Population aging can be measured
by various indicators. The primary
and most commonly used marker is
the proportion of the older popula-
tion in a society, with population
aging defined as an increasing
proportion of older people within
the age structure as discussed in
the previous chapter.
Another indicator of population
aging is the median age, the age
that divides a population into
numerically equal parts of younger
and older people. As population
aging progresses, the median age
rises. Population aging’s effect on
a country’s societal support burden
is often measured by the older
dependency ratio, the ratio of the
older population to the working-
age population.
Owing to the longer life expec-
tancy of women compared with
men (both at birth and at older
ages), the sex ratio (the number
of males per 100 females) of the
older population is often skewed
toward females. This results in a
demographic phenomenon referred
to as the excess of women, which
could have significant implications
in providing for old age care.
TOTAL FERTILITY RATES
HAVE DROPPED TO OR
UNDER REPLACEMENT
LEVEL IN ALL WORLD
REGIONS BUT AFRICA
The main demographic force
behind population aging is declin-
ing fertility rates. Populations with
high fertility tend to have a young
age distribution with a high propor-
tion of children and a low propor-
tion of older people, while those
with low fertility have the opposite,
resulting in an older society.
In many countries today, the total
fertility rate (TFR) has fallen below
the 2.1 children that a couple needs
to replace themselves.1 In 2015,
the TFR is near or below replace-
ment level in all world regions but
Africa (Figure 3-1). The more devel-
oped countries in Europe, where
fertility reduction started more
than 100 years ago, have had TFR
levels below replacement rate since
the 1970s. Currently, the average
TFR for Europe is a very low 1.6.
Interestingly, the downward trend
in the TFR throughout Europe has
recently reversed in a number of
countries, although the TFR still
remains well below replacement.
1 The total fertility rate (TFR) is defined as
the average number of children that would be
born per woman if all women lived to the end
of their childbearing years and bore children
according to a given set of age-specific
fertility rates.
Figure 3-1.
Total Fertility Rate by Region: 2015, 2030, and 2050
Source: U.S. Census Bureau, 2013; International Data Base.
OceaniaNorthern
America
Latin America
and the Caribbean
EuropeAsiaAfrica
205020302015
4.4
3.5
2.8
2.0 1.9
1.6 1.6
2.1
1.7
2.1 1.9 1.8 2.0 2.0 2.0 2.0 1.8
2.2
16 An Aging World: 2015 U.S. Census Bureau
Box 3-1.
China's One-Child Policy and Population Aging
In the early 1970s, China began to institute fertility restrictions out of concern that rapid population growth
would derail its development. A group of policies known as “later-longer-fewer” was designed to encourage
delayed childbearing after marriage, longer intervals between births, and fewer births overall. Under these
policies, China’s fertility fell dramatically from over 5 births per woman in 1972 to under 3 by 1977, the fast-
est decline ever recorded, although declines varied by province (Tien, 1984).
China introduced an even stricter policy in 1979 requiring most parents to have only one child. In 1984, due
to strong son preference, most rural couples with a first-born daughter were permitted to have a second
child. In 1991, China’s fertility fell below 2 children per woman, and since 2000 it has hovered around 1.5
(U.S. Census Bureau, 2013).
What effect have China’s birth planning policies had on population structure and aging? Experts seem unani-
mous in concluding that the “later-longer-fewer” campaign of the 1970s resulted in faster fertility declines
than would have occurred in the absence of these policies. The exact impact depends on counterfactual
assumptions of what policies might have otherwise been in place as well as the pattern of fertility decline
that might have occurred under them (Goodkind, 1992; Wang, Cai, and Gu, 2012).
Opinions are more divided about the extent to which birth restrictions are responsible for the pace of China’s
fertility decline from the 1980s forward. Many experts in recent years argue that China’s fertility is very low
due primarily to improved socioeconomic conditions and that fertility restrictions are increasingly irrelevant
for childbearing decisions (e.g., Cai, 2010).
Whatever the exact number of averted births, the impact of low fertility on China’s population may be
understood by looking at its age-sex pyramids in 2015 and 2050 (Figure 3-2). The size of each birth cohort
is determined by two factors—fertility rates at the time of birth and the number of females at childbearing
ages. The notable constriction of the 2015 population pyramid for the age groups 30 to 34 and 35 to 39
corresponds to the cohort born during the “later-longer-fewer” era of the 1970s and after the one-child policy
was instituted in 1979. The subsequent enlargement of younger cohorts (peaking at ages 25–29) is an “echo”
of the large number of females born in the late 1960s, which likely counterbalanced the reduction in fertility
caused by the one-child policy.
In 2050, the population pyramid reflects the longer term effects of China’s declining fertility. The echo
generation will be approaching older ages (60 to 64). Age groups older than 60 will likely form a heavy top
for China’s age distribution. As the smaller birth cohorts of the 1990s and 2000s reach prime working ages,
China will experience a shrinking labor force. By 2050, the population in the primary working ages, 20 to 59,
is projected to represent only 46.5 percent of the total population, down from the peak of 61.6 percent in
2011.
Note: The primary working ages 20 to 59 are used in this discussion because China’s mandatory retirement ages for the majority of salaried
workers are 60 for men and 55 for women, except for government officials or workers in heavy or hazardous industries.
Continued on next page.
U.S. Census Bureau An Aging World: 2015 17
Many less developed countries
in Asia and Latin America, on the
other hand, have experienced more
recent and rapid fertility declines
than Europe. Overall TFR levels in
Asia and Latin America decreased
by about 50 percent (from 6 to 3
children per woman) during the
period 1965 to 1995 (Kinsella and
He, 2009). As of 2015, the aver-
age TFR for both regions is at the
replacement level of 2.1, and
it is projected that the decline
will continue over the next 35
years through 2050, albeit at a
slower pace.
While the average TFR for Latin
America is 2.1, the majority of
countries in the region have below
replacement fertility rates as of
2015, with Cuba (1.5) and Brazil
(1.8) having the lowest fertility
levels. By 2050, all Latin American
countries are projected to have
fertility rates at or below 2.1. This
would be a significant achievement
in Latin America’s fertility transi-
tion, regardless of each country’s
development level today.
Asia’s current low regional TFR is
particularly impressive, consider-
ing that there are still some Asian
countries with quite high 2015
fertility levels, such as Afghanistan
Figure 3-2.
Population by Age and Sex for China: 2015 and 2050
Millions
Male Female
Source: U.S. Census Bureau, 2013; International Data Base.
2015
80 60 40 20 0
0 to 4
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 and over
20 40 60 80
Millions
Male Female
2050
80 60 40 20 0
0 to 4
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 and over
20 40 60 80
18 An Aging World: 2015 U.S. Census Bureau
Table 3-1.
Ten Lowest and Highest Total Fertility Rates for African
Countries: 2015, 2030, and 2050
2015 2030 2050
Mauritius ........ 1.8 Mauritius ........ 1.7 Mauritius ........ 1.7
Tunisia .......... 2.0 Namibia ......... 1.8 Namibia ......... 1.7
Libya ........... 2.1 Tunisia .......... 1.9 Tunisia .......... 1.7
Morocco ......... 2.1 Libya ........... 2.0 Algeria .......... 1.9
Namibia ......... 2.2 Morocco ......... 2.0 Kenya ........... 2.0
South Africa ...... 2.2 South Africa ...... 2.0 Libya ........... 2.0
Cabo Verde ...... 2.3 Botswana ........ 2.1 Morocco ......... 2.0
Botswana ........ 2.3 Kenya ........... 2.1 South Africa ...... 2.0
Lesotho ......... 2.7 Algeria .......... 2.2 Botswana ........ 2.0
Algeria .......... 2.8 Swaziland ....... 2.2 Swaziland ....... 2.0
Mozambique ..... 5.2 Nigeria .......... 4.3 Tanzania ........ 3.1
South Sudan ..... 5.3 Mali ............ 4.3 Nigeria .......... 3.3
Angola .......... 5.4 Mozambique ..... 4.4 Gabon .......... 3.3
Zambia .......... 5.7 Angola .......... 4.5 Angola .......... 3.5
Burkina Faso ..... 5.9 Uganda ......... 4.5 Mozambique ..... 3.5
Uganda ......... 5.9 Somalia ......... 4.5 Rwanda ......... 3.5
Somalia ......... 6.0 Niger ........... 4.7 Burkina Faso ..... 3.5
Mali ............ 6.1 Burkina Faso ..... 4.8 Sierra Leone ..... 3.6
Burundi ......... 6.1 Zambia .......... 5.0 Zambia .......... 3.9
Niger ........... 6.8 Burundi ......... 5.3 Burundi ......... 4.1
Notes: Total fertility rate is the average number of children that would be born per woman if all women
lived to the end of their childbearing years and bore children according to a given set of age-specific fertility
rates.
The list includes countries with a total population of at least 1 million in 2015.
Source: U.S. Census Bureau, 2013; International Data Base.
(5.3), Yemen (3.9), Iraq (3.3), and
the Philippines (3.0). These high
fertility rates are offset by excep-
tionally low fertility in countries
such as Taiwan (1.1), Hong Kong
(1.2), South Korea (1.3), Japan
(1.4), Thailand (1.5), and China
(1.6). By 2050, all 52 Asian coun-
tries are projected to have below
replacement fertility rates except
Afghanistan (2.8), Jordan (2.5),
Philippines (2.2), and Timor-Leste
(2.2).
FERTILITY DECLINES IN
AFRICA BUT MAJORITY OF
AFRICAN COUNTRIES STILL
HAVE ABOVE REPLACEMENT
LEVEL FERTILITY IN 2050
Africa’s current regional TFR stands
at 4.4, more than twice the replace-
ment level. Nevertheless, Africa
has experienced fertility decline in
the last 15 years. At the turn of the
twenty-first century, two-thirds (34)
of African countries had a TFR at
or above 5, with the TFR exceed-
ing 7 in a few of these countries
(Uganda, 7.1; Somalia and Mali,
7.2; Niger, 8.0). In 2015, 15 years
later, the fertility decline has
reduced the number of countries
with above 5 TFR to 13, and 22
other countries have a TFR between
4 and 5. In another 15 years, 2030,
it is projected that only Burundi will
maintain a fertility level above 5
and the number of countries with
a TFR between 4 and 5 will decline
to 14.
Africa’s fertility decline will con-
tinue into the middle of the cen-
tury. However, it is projected that
by 2050, two-thirds of African
countries will still have a TFR
higher than 2.1. Demographers
(Caldwell, Orubuloye, and Caldwell,
1992) point out the different path
of fertility transition followed in
Africa (“African exceptionalism”)
compared with the rest of the
world. They posit that the slow
fertility decline in Africa is the
result of the still high ideal family
size, stemming from the distinc-
tive pronatalist cultural norms of
African societies, the pervasive
fertility control regime focused on
postponement but not stopping,
and unmet need for family planning
(Moultrie, Sayi, and Timaeus, 2012;
Bongaarts and Casterline, 2013;
Casterline and El-Zeini, 2014).
Among African countries that are
projected to have the highest TFRs
in 2015, 2030, and 2050 (Table
3-1) are some populous African
countries. The 11th-ranked TFR
in 2015 is Nigeria, Africa’s most
populous country, which has a total
population of 181.6 million in 2015
and a projected 391.3 million in
U.S. Census Bureau An Aging World: 2015 19
Figure 3-3.
Population by Age and Sex for Nigeria: 2015 and 2050
Source: U.S. Census Bureau, 2013; International Data Base.
Millions
6420
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
and over
246
Male 2050 Male 2015 Female 2015 Female 2050
2050. Some other populous African
countries with fertility rates pro-
jected to continue to be high are
Ethiopia, 99.5 million in 2015 and
228.1 million in 2050; Tanzania,
51.0 million in 2015 and 118.6
million in 2050; and Mozambique,
25.3 million in 2015 and 59.0 mil-
lion in 2050.
Compared with the rest of the
world, the slow fertility transi-
tion and above-replacement level
fertility in Africa will bring about
sustained population growth and
a corresponding slow pace of
population aging in most of the
region, especially in Sub-Saharan
Africa. The age structure of most
Sub-Saharan African countries may
continue to be that of the tradi-
tional pyramid shape (see Figure
3-3 for the population distribution
by age and sex in 2015 and 2050
for Nigeria, an African society
with high fertility levels). With the
fertility transition only in the early
stages in most Sub-Saharan coun-
tries, population aging in Africa is
only on the far horizon.
It is worth noting that the cur-
rent relatively high fertility levels
in many African countries could
also produce a sizable working
age population in 2050 (see Figure
3-4 for an example). If the fertil-
ity decline accelerated, then the
proportion of the population in
the working ages could rise rela-
tive to 2015 and result in lower
dependency ratios (see discussion
Figure 3-4.
Population by Age and Sex for Kenya: 2015 and 2050
Source: U.S. Census Bureau, 2013; International Data Base.
Millions
0.8 0.6 0.4 0.2 0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
and over
0.2 0.4 0.6 0.8
Male 2050 Male 2015 Female 2015 Female 2050
20 An Aging World: 2015 U.S. Census Bureau
Box 3-2.
Support of Childless Older People in an Aging Europe
By Martina Brandt, TU Dortmund University, and Christian Deindl, University of Cologne
Western societies tend to have the highest proportion of older people (Kinsella and He, 2009) and are facing
considerable pressure on pension and health systems, including services and financial resources for old age care
(Börsch-Supan and Ludwig, 2010). An important aspect for old age support is who will provide the care, especially
Figure 3-5.
Percentage Distribution of Population Aged 50 and Over by
Number of Surviving Children for Selected European Countries: 2006–2007
0 1 2 3 4 5 or more
Percent
Note: The population with 0 surviving children includes those who never had any children and those who have outlived their children.
Source: Survey of Health, Ageing, and Retirement in Europe, release 2.5.0, May 2011.
0 20 40 60 80 100
Switzerland
Sweden
Spain
Poland
Netherlands
Italy
Ireland
Greece
Germany
France
Denmark
Czech Republic
Belgium
Austria
Continued on next page.
U.S. Census Bureau An Aging World: 2015 21
for those who are very old and have no partners. Traditionally, children are the mainstay of old age support, espe-
cially when only one parent is still living. However, people are not only living longer but also having fewer children,
with rising childlessness among the older people (Albertini and Mencarini, 2014; Hayford, 2013; Rowland, 2007).
Thus new challenges arise: Who will provide help and care to the childless older people? On what support networks
can they rely? And, what role does the state play in care provision?
Today about 10 percent of the population aged 50 and over in Europe are childless, according to data from the
Survey of Health, Ageing, and Retirement in Europe (see Börsch-Supan et al., 2011 for details), ranging from 5 to
15 percent in individual countries (Figure 3-5; also see Hank and Wagner, 2013). Childless elders in this study are
defined as those who never had any children and those who have outlived their children (3 percent of the childless
people aged 50 and older).
Family and intergenerational relations play an important role for support in old age. Older parents in need typically
receive the most help from their children. In the absence of children, vital support for older persons has been taken
over by public providers in many countries in Europe. In countries with low social service provision such as Italy,
Spain, and Poland, older people are thus likely to experience a lack of help (Deindl and Brandt, 2011), especially
when childless and dependent on care. Childless elders also often receive care by extended family, friends, and
neighbors (Deindl and Brandt, 2014).
Compared with those who have children, childless older people in need of care (with at least one limitation in
instrumental activities of daily living) are more likely to receive any support (Figure 3-6). With regard to the type
of support (formal, informal, or
both), childless older people are
more likely than their counterparts
to receive formal and combined
support. Older parents, however,
on average receive more help
hours from their children and
their broader social network such
as family, friends, and neighbors
(Deindl and Brandt, 2014).
The provision of formal care is
of great importance not only for
childless older people but also
for older parents whose children
live far away. It will likely become
even more important in the future
when the number of available fam-
ily helpers is expected to further
decline, due to fewer siblings and
children and greater living dis-
tances between family members.
In developed welfare states, social
networks and services work hand
in hand, and likely leading to a
higher quantity and better quality
of support for older people without
children who are especially depen-
dent on formal care arrangements.
Figure 3-6.
Type of Support Received by People Aged 50 and
Over in Selected European Countries by Child Status:
2006–2007
Notes: This figure includes only older people with limitations in Activities of Daily Living
(ADL) and Instrumental Activities of Daily Living (IADL).
Aggregate data are based on the following countries: Austria, Belgium, Czech Republic,
Denmark, France, Germany, Greece, Italy, Netherlands, Spain, Sweden, and Switzerland.
Source: Survey of Health, Ageing, and Retirement in Europe, release 2.5.0, May 2011.
Both
Formal
Informal
None
Childless
Have children
(In percent)
56.7
64.7
22.5
6.2
6.2
23.0
10.1
10.8
22 An Aging World: 2015 U.S. Census Bureau
on dependency ratios later in this
chapter), potentially enabling
demographic dividends in the
next few decades for many African
countries.2 However, demographers
and economists warn that Sub-
Saharan Africa’s continued rapid
increase of children may translate
into a large number of unemployed
youth, hindering economic devel-
opment with an adverse impact
on food security and sustainability
of natural resources (Sippel et al.,
2011; African Development Bank
Group, 2012; Drummond, Thakoor,
and Yu, 2014).3
SOME COUNTRIES TO
EXPERIENCE SIMULTANEOUS
POPULATION AGING AND
POPULATION DECLINE
European demographers have
warned for decades about the
possibility of declining total
population size accompanying
population aging in some European
countries, due to their persistent
“lowest-low fertility” levels (Kohler,
Billari, and Ortega, 2002). In
some European countries, such as
Belarus, Bulgaria, Romania, Serbia,
and Ukraine, population decline
started 2 decades ago.
Interestingly, a list of countries
projected to experience a popula-
tion decline of at least 1 million
2 Demographic dividend refers to
accelerated economic growth as a result of
fertility and mortality declines and subse-
quent lower dependency ratios. For more
information on the demographic dividend,
see Bloom, Canning, and Sevilla, 2003.
3 For more discussion on possible
overestimates of the pace of Sub-Saharan
Africa’s future fertility decline, and thus
underestimates of the growth of children,
see Eastwood and Lipton (2011) and
UNICEF (2014).
Figure 3-7.
Countries With Expected Decline of at Least 1 Million
in Total Population From 2015 to 2050
(Numbers in millions)
Note: Percentage decline is shown in parentheses.
Source: U.S. Census Bureau, 2013; International Data Base.
–57.8
(–4.2%)
–19.7 (–15.5%)
–12.5 (–8.8%)
–10.4 (–23.7%)
–9.3 (–11.5%)
–6.2 (–16.2%)
–5.7 (–11.7%)
–3.6 (–16.6%)
–2.6 (–11.0%)
–2.2 (–32.3%)
–1.9 (–2.8%)
–1.9 (–17.0%)
–1.4 (–14.2%)
–1.3 (–18.2%)
–1.3 (–36.2%)
–1.3 (–13.0%) Belarus
Moldova
Serbia
Hungary
Cuba
Thailand
Bulgaria
Taiwan
Romania
South
Korea
Poland
Germany
Ukraine
Russia
Japan
China
compiled by Kinsella and He (2009,
Figure 3-3) in 2008 differs some-
what from the same list compiled
in 2015 (Figure 3-7). Four countries
included in the earlier list are no
longer projected to face a sub-
stantial population decline—South
Africa, Italy, Spain, and the Czech
Republic. Decreases in mortality
due to HIV/AIDS has changed the
prospects for South Africa and
removed it from the list. Italy and
Spain have dropped off the list pri-
marily due to increases in fertility
and major immigration flows. Italy’s
total population is still projected to
decline but only by 0.4 million
by 2050.
U.S. Census Bureau An Aging World: 2015 23
New countries joining the list
include China, South Korea,
Thailand, Cuba, Hungary, Serbia,
and Moldova. The addition of the
three Asian countries is being
driven by rapid decreases in their
fertility rates. It is important to
bear in mind that the projected
decline in total population in these
Asian countries will be accompa-
nied by the rapid expansion of their
older population. The demographic
phenomenon of simultaneous
population aging and population
decline, originally projected to
occur only in European countries, is
now spreading to Asia.
COMPOSITION OF
DEPENDENCY RATIO
WILL CONTINUE TO
SHIFT TOWARD OLDER
DEPENDENCY
The total dependency ratio is the
sum of the older dependency ratio
and the youth dependency ratio.
The older dependency ratio in this
report is defined as the number of
people aged 65 and over per 100
people of working ages 20 to 64,
and the youth dependency ratio is
the number of people aged 0 to 19
per 100 people aged 20 to 64. The
working ages of 20 to 64 are used
here with the acknowledgment that
world regions and countries differ
vastly in youngest working age and
retirement age.
Dependency ratios provide a gross
estimate of the pressure on the
productive population, and offer an
indication of a society’s caregiving
burden by estimating the potential
supply of caregivers and the poten-
tial demand for care (number of
care recipients). However, not all
individuals who fall in a certain age
category are actually “dependents”
or “providers”—some older (or
younger) people work or have the
financial resources to be indepen-
dent and some in the “working
ages” do not work.
The total dependency ratio for the
world in 2015 is 73, indicating that
every 100 people aged 20 to 64
are supporting 73 youth and older
people combined (Figure 3-8). The
world’s total dependency ratio is
not expected to rise very much in
the next few decades, reaching 78
in 2050. However, the composi-
tion of the total dependency ratio
will change considerably—in 2015,
there are 15 older people and 59
youth per 100 working age people,
and by 2050 the older dependency
ratio is projected to double to 30
and the youth dependency ratio to
decline to 48 per 100 working age
people. Youth will still account for
the majority of all dependents, but
the older share is rising.
Countries vary drastically in their
total dependency ratio composi-
tion, largely due to differences in
their stages of fertility and mortal-
ity decline. Indonesia, for example
(Figure 3-9), experienced a nearly
50 percent reduction in the total
dependency ratio from 1980 (121)
to 2015 (70), due in large mea-
sure to a sharp fertility decline
and corresponding decrease in
the youth dependency ratio. The
youth dependency ratio dropped
from 114 in 1980 to 59 in 2015,
while the older dependency ratio
increased slightly from a mere 7 to
11 over the same period, provid-
ing an ideal opportunity to reap the
demographic dividend. However,
looking forward, while Indonesia’s
total dependency ratio is projected
to increase just slightly to 74 in
2050, the contributing factors will
be shifted due to both ongoing
fertility decline and increasing life
expectancy. By 2050, the youth
dependency ratio will decrease
further to 41 and the older depen-
dency ratio will rise sharply to 33.
Zambia, on the other hand, pres-
ents a sharp contrast in the level
and trend of its total dependency
ratio. Zambia’s total dependency
ratio was at a much higher level
in 1980 (165) and is projected to
decline at a slower rate than the
trajectory for Indonesia (Figure
3-9). By 2050, the total dependency
ratio in Zambia is projected to
remain over 100 (at 116), indicat-
ing that the dependent population
of youth and older people will
continue to exceed the size of the
working age population. The com-
position of the total dependency
ratio in Zambia changes very little
from 1980 to 2050. Fertility decline
lowers the youth dependency ratio
from 159 in 1980 to 140 in 2015
and to 109 in 2050, while the older
dependency ratio remains almost
constant at an extremely low level
of about 6 to 7. Even by the middle
of the twenty-first century, popula-
tion aging will not have material-
ized in Zambia.
24 An Aging World: 2015 U.S. Census Bureau
Figure 3-8.
Dependency Ratios for the World: 2015 to 2050
Note: The older dependency ratio is the number of people aged 65 and over per 100 people aged 20 to 64. The youth dependency ratio
is the number of people aged 0 to 19 per 100 people aged 20 to 64.
Source: U.S. Census Bureau, 2013; International Data Base.
0
20
40
60
80
100
20502045204020352030202520202015
Youth dependency ratio
Older dependency ratio
Figure 3-9.
Dependency Ratios for Indonesia and Zambia: 1980, 2015, and 2050
Note: The older dependency ratio is the number of people aged 65 and over per 100 people aged 20 to 64. The youth dependency ratio
is the number of people aged 0 to 19 per 100 people aged 20 to 64.
Source: U.S. Census Bureau, 2013; International Data Base.
Indonesia Zambia
0
20
40
60
80
100
120
140
160
180
205020151980
0
20
40
60
80
100
120
140
160
180
205020151980
Youth dependency ratio
Older dependency ratio
U.S. Census Bureau An Aging World: 2015 25
MEDIAN AGES FOR
COUNTRIES RANGE FROM
15 TO NEAR 50
Another way to measure popula-
tion aging is to consider a coun-
try’s median age, the age that
divides a population into numeri-
cally equal shares of younger and
older people. African countries
are among the youngest, with
relatively low median ages. For
example, Niger, Uganda, and Mali
have current median ages of about
15 to 16 (Figure 3-10)—more than
half of the population in these
countries are children under age
18. Furthermore, African coun-
tries with sustained high fertility
are expected to have very young
median ages even by 2050 (e.g.,
Zambia, 20).
At the other end of the spectrum
are Japan and Germany with a
current median age of 47. It is
projected that Japan’s median age
will reach 53 by 2030 and 56 by
2050—half of the population in
Japan will be at or near the ages for
the older population. Obviously the
allocation of resources in countries
with drastically different median
ages will diverge significantly.
As expected, older regions have a
higher median age and vice versa
(Table 3-2). However, an interesting
observation is the variation in the
median age by sex differentials,
reflecting the differences in mortal-
ity and life expectancy by sex in
different regions. While women in
Figure 3-10.
Countries With Lowest or Highest Median Age in 2015: 2015, 2030, and 2050
Note: Median age for the years 2015, 2030, and 2050 is shown for the five countries with the lowest and highest median age as of 2015.
Source: U.S. Census Bureau, 2013; International Data Base.
0
10
20
30
40
50
60
JapanGermanyItalySloveniaGreeceMozambiqueZambiaMaliUgandaNiger
205020302015
Years
Table 3-2.
Median Age by Sex and Region: 2015, 2030, and 2050
(In years)
Region Both sexes Male Female
2015 2030 2050 2015 2030 2050 2015 2030 2050
Africa ............................. 19.7 22.0 26.0 19.4 21.7 25.6 19.9 22.3 26.4
Asia .............................. 30.6 35.7 40.5 29.9 34.9 39.6 31.3 36.6 41.5
Europe ............................ 41.6 45.3 47.1 39.7 43.4 44.8 43.4 47.2 49.6
Latin America and the Caribbean ....... 29.1 34.4 40.6 28.2 33.3 39.2 30.0 35.5 42.1
Northern America ................... 38.1 40.0 41.1 36.8 38.8 39.8 39.5 41.3 42.4
Oceania ........................... 34.0 36.8 40.0 33.5 36.1 39.1 34.6 37.5 41.0
Source: U.S. Census Bureau, 2013; International Data Base.
26 An Aging World: 2015 U.S. Census Bureau
all regions have older median ages
than men, the female-male gap
is currently and projected to be
largest in the oldest region, Europe
(3.7 in 2015 and 4.8 in 2050). The
higher proportion of women among
the older population combined
with a larger number of older
people result in a European society
with many more older and old-
est women than men. In contrast,
in the youngest region of Africa,
males and females are almost
equally young, with a differential of
less than 1 year in median age for
2015, 2030, and 2050.
SEX RATIOS AT OLDER AGES
RANGE FROM LESS THAN 50
TO OVER 100
Sex ratio is defined as the number
of males for every 100 females. It
is a common measure of a popu-
lation’s gender composition with
implications for social support
needs. In general, younger males
outnumber younger females, but
thanks to the female advantage in
life expectancy at birth and at older
ages, older women outnumber
older men, as illustrated in Figure
3-11 for the United States.4
At older ages, the sex ratio
decreases with increasing age
(Figure 3-12). Globally, the total
number of males slightly exceeds
4 See Chapter 4 for more information on
sex differentials in life expectancy.
Figure 3-11.
Difference Between Female and Male Populations by Age in the United States: 2010
Source: U.S. Census Bureau, 2011; 2010 Census.
Age
2.0 2.01.5 1.51.0 1.00.5 0.50.0
0 to 4
5 to 9
10 to 14
15 to 19
20 to 24
25 to 29
30 to 34
35 to 39
40 to 44
45 to 49
50 to 54
55 to 59
60 to 64
65 to 69
70 to 74
75 to 79
80 to 84
85 and over
Millions
More femaleMore male
U.S. Census Bureau An Aging World: 2015 27
Figure 3-12.
Sex Ratio for World Total Population and Older Age Groups: 2015
Note: Sex ratio is number of men per 100 women.
Source: U.S. Census Bureau, 2013; International Data Base.
100+95+90+85+80+75+70+65+Total
101.4
39.6
80.3
74.9
30.1
68.4
60.5
50.6
22.5
the number of females in 2015,
with a sex ratio of 101.4. However,
by age 65 and older, the sex ratio
is only 80.3. The sex ratio contin-
ues to decline steadily for older
age groups. For example, there are
only half as many men as women
in the world in the age group 85
and over. The sex ratio drops to a
low of 22.5 for people aged 100
and over, indicating that for every
male centenarian, there are over 4
female counterparts.
Sex ratios vary greatly by region
and country (see Appendix B, Table
B-4). While the vast majority of
countries have a sex ratio below
100 for their older population,
Russia and some other Eastern
European countries have unusu-
ally low sex ratios (e.g., in 2015,
Belarus, 46.4; Latvia, 48.5; Ukraine,
48.9; and Estonia, 49.8). These
exceptionally low sex ratios for
the older population started in the
late 1980s when the World War II
combat cohort reached the older
age ranks, a reflection of the devas-
tating male casualties in the war for
these former Soviet Union countries
(Vassin, 1996; Heleniak, 2014).
Russia’s sex ratio for the older
population in 1990 was a very
low 35.8. It climbed up to the 40s
by the mid-1990s and remained
steady throughout the 2000s and
2010s, and is at 44.6 in 2015. It
is projected that Russia’s sex ratio
will not rise above 50 until the
28 An Aging World: 2015 U.S. Census Bureau
Figure 3-13.
Sex Ratios for Population Aged 65 and Over for Bangladesh and Russia:
1990 to 2050
Note: Sex ratio is number of men per 100 women.
Source: U.S. Census Bureau, 2013; International Data Base.
Russia
Bangladesh
0
20
40
60
80
100
120
2050204520402035203020252020201520102005200019951990
mid-2020s and will remain at that
level through 2050 (Figure 3-13).
With the passage of the World War
II cohort, the main contributors to
the low sex ratio in Russia in recent
years have been high male midlife
mortality from various diseases
such as cardiovascular disease as
well as violence, accidents, and
alcohol-related causes (Oksuzyan et
al., 2014).
An opposite and also unusual pat-
tern for sex ratios is found in parts
of Asia and Sub-Saharan Africa—the
sex ratios for the older popula-
tion are as high as 90 or even
above 100 (e.g., in 2015, India,
90.1; Malaysia, 90.3; China, 91.9;
Bangladesh, 96.7; Mali, 100.0;
Niger, 103.6; Bhutan, 109.9; and
Sudan, 119.4). These remarkably
high sex ratios are projected to
decline only slightly through 2050.
For example, Bangladesh’s sex
ratio for the population aged 65
and over in 1990 was 111.9. It
stayed over 100 until 1999, and
is projected to remain over 90
until 2029 (Figure 3-13). By 2050,
Bangladesh’s sex ratio for the older
population likely will be about 87.
The excess male sex imbalance
in older ages, found primarily in
parts of Asia, is often referred to
as “missing women.” This phenom-
enon is believed to be the result of
long standing female disadvantage
in health and nutrition, leading
to higher female infant and child
mortality in addition to mater-
nal mortality (Sen, 1990; 2001).
Looking forward, the distorted sex
ratio at older ages could persist
due to the introduction of prenatal
diagnosis technology around 1980.
The available technology com-
bined with traditional patriarchal
cultural norms of son preference
led to unusually high sex ratios at
birth in several countries, includ-
ing China, India, and South Korea.
While concerns have been raised
about “an irreversible demographic
masculinization” (Guilmoto, 2012),
South Korea may lead a new trend
for reversing the distorted sex ratio
at birth—the sex ratio at birth in
South Korea has been declining
from the mid-1990s. Son prefer-
ence in the country has decreased,
impacted by normative changes
in desired family size triggered by
social and economic development
(Chung and Das Gupta, 2007).
U.S. Census Bureau An Aging World: 2015 29
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CHAPTER 4.
Life Expectancy, Health, and Mortality
There is little doubt that popula-
tion aging will accelerate over the
coming decades, as outlined in
Chapter 2. The changed age struc-
tures in most parts of the world
have contributed to a growing
number of older people who may
have various health conditions or
concerns about functioning in older
age. Understanding the differences
in health status and well-being of
older populations is essential not
only to those who comprise this
age group, but also for the social
and economic systems. Variations
within regions or between coun-
tries help to identify the impact
of different policies and to plan
for future health care services and
social support systems.
Current questions about whether or
not limits to human life span exist
and whether healthy life expec-
tancy will keep pace with increas-
ing average life expectancy are just
two of the scientific issues being
robustly debated about our aging
world (Oeppen and Vaupel, 2002;
Olshansky et al., 2007, Sanderson
and Scherbov, 2010; Lee, 2011).
A number of other related topics,
including frailty, mild cognitive
impairment, predisease thresholds,
and premature death, are also
generating considerable discussion.
The scientific outcomes of these
debates have practical implications:
the health levels among the grow-
ing number of older adults have
real and potentially significant cost
considerations for health and pen-
sion systems.
Despite considerable interest in the
negative impact of aging on popu-
lation health and public coffers,
the contributions to society would
likely outweigh burdens if adults
reach older age healthier. However,
the current evidence about whether
older adult cohorts are physically
and cognitively healthier than
preceding generations is mixed
(Langa et al., 2008; Crimmins
and Beltran-Sanchez, 2011; Lin et
al., 2012; Matthews et al., 2013;
Lowsky et al., 2014). Better health
for those reaching older age could
be realized through addressing
the social determinants of health,
minimizing health risks, and recon-
figuring health and social support
systems to maximize well-being
in an aging population; and these
efforts could simultaneously sus-
tain the growth in life expectancy
seen since the mid-1800s and lead
to more rational use of resources
(Brandt, Deindl, and Hank, 2012;
Rizzuto et al., 2012; Bloom et
al., 2015; Kruk, Nigenda, and
Knaul, 2015).
DEATHS FROM
NONCOMMUNICABLE
DISEASES RISING
The world average age of death
has increased by 35 years since
1970, with declines in death rates
in all age groups, including those
aged 60 and older (Institute for
Health Metrics and Evaluation,
2013; Mathers et al., 2015). From
1970 to 2010, the average age of
death increased by 30 years in East
Asia and 32 years in tropical Latin
America, and in contrast, by less
than 10 years in western, south-
ern, and central Sub-Saharan Africa
(Institute for Health Metrics and
Evaluation, 2013; Figure 4-1).1
The leading causes of death
are shifting, in part because of
1 These geographic areas are defined by
the World Health Organization.
increasing longevity. Between 1990
and 2013, the number of deaths
from noncommunicable diseases
(NCDs) has increased by 42 per-
cent; and the largest increases in
the proportion of global deaths
took place among the population
aged 80 and over (Lozano et al.,
2012; GBD 2013 Mortality and
Causes of Death Collaborators,
2015). An estimated 42.8 percent
of deaths worldwide occur in the
population aged 70 and over, with
22.9 percent in the population aged
80 and over (Wang et al., 2012).
Cardiovascular disease, lung
disease, cancer, and stroke are the
leading killers for the population
aged 60 and over; however, with a
few notable exceptions such as dia-
betes and chronic kidney disease,
age-standardized rates for many of
the leading NCDs have generally
declined. The drivers of mortality
also vary considerably by region
and level of economic develop-
ment. The communicable disease
burden is highest in the World
Health Organization’s (WHO) Africa
region, but also more broadly
in low and lower-middle income
countries (Table 4-1). These same
regions are also facing a significant
burden from NCDs and injuries.
Deaths and disability from NCDs
are rapidly rising in less devel-
oped countries and yielding worse
outcomes than in more developed
countries; some diseases that are
preventable or treatable in more
developed countries are lead-
ing to deaths in less developed
countries (Daniels, Donilon, and
Bollyky, 2014). Age-standardized
mortality rates due to communi-
cable diseases in 2012 show a
clear gradient by country income
grouping. While these differences
32 An Aging World: 2015 U.S. Census Bureau
Table 4-1.
Age-Standardized Mortality Rates by Cause of Death, WHO
Region, and Income Group: 2012
(Per 100,000 population)
Characteristic Communicable
diseases
Non-
communicable
diseases Injuries
Global .................... 178 539 73
WHO Region
Africa ..................... 683 652 116
Americas .................. 63 437 62
South-East Asia ............. 232 656 99
Europe .................... 45 496 49
Eastern Mediterranean ....... 214 654 91
Western Pacific ............. 56 499 50
Income Group
Low income ................ 502 625 104
Lower-middle income ........ 272 673 99
Upper-middle income ........ 75 558 59
High income ................ 34 397 44
Note: Region refers to World Health Organization regional grouping. Income groupings refer to World
Bank analytical income of economies for fiscal year 2014.
Source: World Health Organization, 2014.
Figure 4-1.
Mean Age of Death in Global Burden of Disease Regions: 1970 and 2010
Source: Wang et al., 2012. Adapted from Figure 8.
010 20 30 40 50 60 70 80
0
10
20
30
40
50
60
70
80
Mean age at death in 1970 (years)
Western
Europe
Australasia
High-income
Asia Pacific
Southern Latin America
Central Asia
East Asia
South Asia
Oceania
Eastern sub-Saharan Africa
Western sub-Saharan Africa
Central
sub-Saharan Africa
Southern sub-Saharan Africa
Southeast Asia Tropical Latin America
Central Latin America
Andean Latin America
North Africa and Middle East
Caribbean
Central Europe
Mean age at death in 2010 (years)
High-income North America
Eastern Europe
contribute to considerable changes
in the mean age at death between
1970 and 2010 across different
WHO regions, all regions have had
increases in mean age at death,
particularly East Asia and tropical
Latin America (Figure 4-1).
LIFE EXPECTANCY AT BIRTH
EXCEEDS 80 YEARS IN 24
COUNTRIES WHILE IT IS
LESS THAN 60 YEARS IN 28
COUNTRIES
In July 2015, a woman in the United
States celebrated her 116th birth-
day, becoming the world’s oldest
person according to the Guinness
World Records, following the death
of a 117-year-old woman from
Japan earlier in the year (Associated
U.S. Census Bureau An Aging World: 2015 33
Press, 2015). Increasing longevity
around the globe is indeed remark-
able, but looking across countries
reveals uneven progress in popula-
tion health as demonstrated by the
cross-country differences in aver-
age life expectancy. Life expec-
tancy at different ages for men
and women points to considerable
heterogeneity and plasticity of
aging processes, but also extreme
variation and persistent inequality.
The very same factors correlated
with the dramatic drops in mortal-
ity in Western Europe and North
America at the beginning of the
1900s, namely water, sanitation,
and diet still contribute to mortality
rates across many other regions—
although with considerable and
ongoing progress.
Global life expectancy at birth
reached 68.6 years in 2015
(Table 4-2). A female born today
is expected to live 70.7 years on
average and a male 66.6 years.
The global life expectancy at birth
is projected to increase almost 8
years, reaching 76.2 years in 2050.
Northern America currently has
the highest life expectancy at 79.9
years and is projected to continue
to lead the world with an average
regional life expectancy of 84.1
years in 2050. The current life
expectancy for Africa is only 59.2
years. However, Africa is expected
to undergo major improvements in
health and AIDS-related mortality
in the next few decades and its life
expectancy in 2050 is projected
to be 71.0 years, narrowing the
gap between Northern America
and Africa.
As of 2015, 24 countries have a
life expectancy at birth of 80 years
or longer. Japan, Singapore, and
Macau lead this group with life
expectancy at birth exceeding 84
years (Table 4-3). Women born in
these countries today are expected
on average to live to about age
88, compared with about age 82
for men. In the next 35 years,
most of these 24 countries will
see an extension of 2 to 3 years in
their life expectancy at birth, with
the top two countries, Japan and
Table 4-2.
Life Expectancy at Birth by Sex for World Regions:
2015 and 2050
Region Both sexes Male Female
2015 2050 2015 2050 2015 2050
World .......................... 68.6 76.2 66.6 73.7 70.7 78.8
Africa ........................ 59.2 71.0 57.6 68.7 60.7 73.4
Asia ......................... 71.0 78.5 69.1 76.0 73.0 81.1
Europe ....................... 77.3 82.1 73.7 78.8 81.1 85.5
Latin America and the Caribbean .. 74.5 80.3 71.6 77.3 77.6 83.5
Northern America .............. 79.9 84.1 77.4 81.9 82.2 86.2
Oceania ...................... 76.7 80.7 74.4 78.2 79.2 83.4
Source: U.S. Census Bureau, 2013; International Data Base.
Singapore, projected to have life
expectancy exceeding 90 years
(both sexes).
At the other end of the spectrum,
28 countries have a life expec-
tancy at birth below 60 years in
2015. Among the 28 countries,
27 are in Africa and one is in Asia
(Afghanistan). By 2050, all 28
countries, except Botswana and
Namibia, are projected to have their
life expectancy at birth increase by
more than 10 years, with Lesotho
(an impressive increase of 19.4
years) and Mozambique (17.9 years
increase) leading the way.
Women currently live longer than
men on average, except in four
countries: Botswana, Lesotho,
Mali, and Swaziland. However, the
female advantage generally is nar-
rower (about 2 to 3 years currently)
among countries with the lowest
life expectancies at birth as com-
pared to countries with the highest
life expectancies at birth (gaps of
about 5 to 6 years). Global mortal-
ity rates show a uniformly smaller
percentage decline for men than
women at all age groups, with the
possible exception of men in the 80
years and older age group (Wang
et al., 2012; GBD 2013 Mortality
and Causes of Death Collaborators,
2015). This means that the female
mortality advantage persists and is
generally expanding at the global
level. Over time, the gender gap is
expected to increase in countries
with the lowest life expectancies at
birth (Table 4-3).
34 An Aging World: 2015 U.S. Census Bureau
Table 4-3.
Countries With Highest and Lowest Life Expectancy at Birth by Sex in 2015 and Projected
for 2050
(In percent)
Country
Life expectancy at birth
2015 2050
Both sexes Male Female Both sexes Male Female
Japan ...................... 84.7 81.4 88.3 91.6 88.4 95.0
Singapore .................. 84.7 82.1 87.5 91.6 88.7 94.6
Macau ..................... 84.5 81.6 87.6 85.1 82.2 88.1
Hong Kong .................. 82.9 80.2 85.8 84.4 81.6 87.4
Switzerland ................. 82.5 80.2 84.9 84.2 81.6 87.0
Australia .................... 82.2 79.7 84.7 84.1 81.4 86.9
Italy ....................... 82.1 79.5 84.9 84.1 81.3 87.0
Sweden .................... 82.0 80.1 84.0 84.0 81.5 86.6
Canada .................... 81.8 79.2 84.5 83.9 81.1 86.8
France ..................... 81.8 78.7 85.0 83.9 80.9 87.0
Norway. . . . . . . . . . . . . . . . . . . . . 81.7 79.7 83.8 83.9 81.4 86.5
Spain ...................... 81.6 78.6 84.8 83.8 80.9 86.9
Israel ...................... 81.4 79.1 83.7 83.8 81.1 86.5
Netherlands ................. 81.2 79.1 83.5 83.7 81.1 86.4
New Zealand ................ 81.1 79.0 83.2 83.6 81.1 86.3
Ireland ..................... 80.7 78.4 83.1 83.4 80.8 86.2
Germany ................... 80.6 78.3 83.0 83.4 80.7 86.2
Jordan ..................... 80.5 79.1 82.1 83.4 81.1 85.8
United Kingdom .............. 80.5 78.4 82.8 83.4 80.8 86.1
Greece ..................... 80.4 77.8 83.2 83.3 80.6 86.3
Austria ..................... 80.3 77.4 83.4 83.3 80.3 86.4
Belgium .................... 80.1 76.9 83.4 83.2 80.1 86.3
South Korea ................. 80.0 77.0 83.3 84.2 81.5 87.1
Taiwan ..................... 80.0 76.9 83.3 83.1 80.1 86.3
Rwanda .................... 59.7 58.1 61.3 72.0 69.6 74.4
Congo (Brazzaville) ........... 58.8 57.6 60.0 71.1 69.0 73.2
Liberia ..................... 58.6 56.9 60.3 70.7 68.3 73.2
Cote d’Ivoire ................ 58.3 57.2 59.5 69.7 68.0 71.4
Cameroon .................. 57.9 56.6 59.3 72.0 69.7 74.4
Sierra Leone ................ 57.8 55.2 60.4 70.2 67.1 73.3
Zimbabwe .................. 57.1 56.5 57.6 67.2 66.9 67.5
Congo (Kinshasa) ............ 56.9 55.4 58.5 70.2 67.8 72.7
Angola ..................... 55.6 54.5 56.8 69.2 67.1 71.5
Mali ....................... 55.3 53.5 57.3 68.4 65.7 71.1
Burkina Faso ................ 55.1 53.1 57.2 67.8 65.1 70.5
Niger ...................... 55.1 53.9 56.4 68.2 66.1 70.5
Uganda .................... 54.9 53.5 56.4 67.8 65.6 70.0
Botswana ................... 54.2 56.0 52.3 61.6 64.8 58.4
Malawi ..................... 53.5 52.7 54.4 65.3 64.0 66.5
Nigeria ..................... 53.0 52.0 54.1 68.1 66.0 70.3
Lesotho .................... 52.9 52.8 53.0 72.3 71.5 73.2
Mozambique ................ 52.9 52.2 53.7 70.8 69.0 72.7
Zambia ..................... 52.2 50.5 53.8 64.5 62.5 66.7
Gabon ..................... 52.0 51.6 52.5 62.1 61.6 62.6
Somalia .................... 52.0 49.9 54.1 65.5 62.6 68.5
Central African Republic ....... 51.8 50.5 53.2 65.5 63.5 67.7
Namibia .................... 51.6 52.1 51.2 57.8 60.1 55.5
Swaziland .................. 51.1 51.6 50.5 61.4 63.0 59.8
Afghanistan ................. 50.9 49.5 52.3 64.5 62.2 66.9
Guinea-Bissau ............... 50.2 48.2 52.3 63.5 61.0 66.2
Chad ...................... 49.8 48.6 51.0 63.4 61.7 65.1
South Africa ................. 49.7 50.7 48.7 63.2 64.1 62.3
Note: Life expectancy at birth for 2015 and 2050 is shown for countries with the highest and lowest life expectancy at birth as of 2015.
Source: U.S. Census Bureau, 2013; International Data Base.
U.S. Census Bureau An Aging World: 2015 35
Figure 4-2.
Countries With Highest and Lowest Life Expectancy at Age 65 by Sex:
2015 and 2050
Note: Life expectancy estimates are derived from population estimates and projections produced for over 220 countries by the
U.S. Census Bureau. For methodology, see <www.census.gov/population/international/data/idb/estandproj.pdf>.
Source: U.S. Census Bureau, 2013; unpublished lifetables.
Female
2015
2050
(In years)
20.6 20.2 20.0 19.0 19.0
22.522.4
25.2
24.9
24.5
AustraliaSwitzerlandJapanMacauSingapore
11.0 11.4 12.9 11.7 11.712.8
13.1
12.8
11.7
12.1
SomaliaBurkina
Faso
MaliGuinea-
Bissau
Afghanistan
25.0 25.5
20.7 20.2 20.1
24.3
24.4
25.3
30.3
30.6
SwitzerlandSouth
Korea
MacauSingaporeJapan
13.0 13.5 15.6 13.7 13.8 15.7
16.0
16.2
13.5
15.0
ChadMaliGuinea-
Bissau
SomaliaAfghanistan
Male
LIVING LONGER FROM AGE
65 AND AGE 80
Extension of life expectancy has
also occurred at older ages. In the
United States, for example, life
expectancy at age 65 has increased
from 11.9 years in 1900–1902 to
19.1 years in 2009. Life expec-
tancy at age 80 over the same time
period also almost doubled from
5.3 years to 9.1 years (Arias, 2014).
The female advantage in life expec-
tancy is also demonstrated at older
ages. In 2015, older men at age
65 in Singapore, Macau, and Japan
would live on average for about
another 20 years, but older women
in these countries live on average
about another 25 years (Figure
4-2). By 2050, the life expectancy
for Japanese and Singaporean older
men is projected to be about 25
years and for older women about
30 years.
Countries with the lowest life
expectancy at older ages are also
projected to see improvement.
Afghanistan, for example, has the
lowest current life expectancy for
age 65, 11.0 years for men and
12.1 for women. By 2050, these
rates are projected to improve to
13.0 years and 15.0 years for men
and women, respectively.
The largest gains in life expectancy
at age 60 have come from the
reduction in cardiovascular disease
and diabetes mortality (Figure 4-3).
In high-income countries, reduc-
tion in cardiovascular disease and
diabetes mortality contributed a
gain of 3.0 years in life expectancy
for men and 4.3 years for women,
and for men reductions in tobacco-
caused mortality contributed to
another 2.0 years of gain in life
expectancy. On the other hand, an
36 An Aging World: 2015 U.S. Census Bureau
–1
0
1
2
3
4
5
6
High-income
countries
Middle-income
countries of Europe
Latin America and
the Caribbean
Men Women
Men Women
Men Women
Figure 4-3.
Drivers of Increase or Decrease in Life Expectancy at Age 60 by Sex, Region,
and Income: 1980 to 2011
Tobacco-
attributable
deaths
Communicable
diseases
Cancers
Cardiovascular
disease and
diabetes
Chronic
respiratory
diseases
Other
noncommun-
icable diseases
Injuries
Note: Tobacco-attributable deaths for specific disease causes are subtracted from the disease cause categories and shown as a
single cause group. Thus, for example, the category labeled "Cancers" excludes tobacco-caused cancers.
Source: Mathers et al., 2015. Adapted from Figure 2.
Years
increase in tobacco-related deaths
among women has limited their
gains in life expectancy at age 60
in high-income countries. Similar
patterns in cause-specific mortal-
ity reductions were found in the
middle-income countries in Latin
America and the Caribbean.
The burden of simultaneous com-
municable and noncommunicable
diseases, higher tobacco use, and
lower effective health care cover-
age has contributed to slower
improvements in older age mortal-
ity in middle-income countries than
in high-income countries (Mathers
et al., 2015). However, aging
populations and shifting infectious
disease epidemiology mean that
older adults are likely to account
for a larger share of communicable
disease morbidity and mortality in
low- and middle-income countries
(Salomon et al., 2012). Meanwhile,
dementia and obesity are underly-
ing factors for the small losses
in life expectancy and may limit
progress in older age mortality in
the coming decades.
YES, PEOPLE ARE LIVING
LONGER, BUT HOW MANY
YEARS WILL BE LIVED IN
GOOD HEALTH?
Life expectancy is a good summary
measure of population mortality
levels. Increasing life expectancy
at birth and at older ages suggests
healthier populations overall in
most countries. However, because
of population aging and the accom-
panying morbidity, a summary
measure that also incorporates
functioning, disease, and ill health
may better describe population
health across the life span. Healthy
life expectancy (HALE) is one such
measure.
HALE takes into account both
mortality and morbidity and is
described by the WHO as “the
average number of years that a
person can expect to live in “full
health” by taking into account
“years lived in less than full health
due to disease and/or injury”
(World Health Organization, 2012).
Among European countries in
2012, French women had the
longest life expectancy at age 65,
23.4 years (European Commission,
2014; Figure 4-4). French men
were also among the highest in life
U.S. Census Bureau An Aging World: 2015 37
Figure 4-4.
Life Expectancy (LE) and Healthy Life Years (HALE) at Age 65 by Sex for
Selected European Countries: 2012
HALE LE with activity limitations
LE for men
Years
LE for women
HALE LE with activity limitations
Note: HALE is the average number of years that a person can expect to live in full health by taking into account years lived in less
than full health due to disease and/or injury.
Source: European Commission, 2014; Eurostat.
25 20 15 10 5 0
Bulgaria
Romania
Hungary
Latvia
Slovakia
Croatia
Czech Republic
Lithuania
Poland
Denmark
Estonia
United Kingdom
Greece
Malta
Netherlands
Norway
Ireland
Slovenia
Sweden
Germany
Belgium
Austria
Portugal
Luxembourg
Iceland
Finland
Italy
Switzerland
Spain
France
5 10 15 20 25
38 An Aging World: 2015 U.S. Census Bureau
expectancy at age 65, 19.1 years.
However, Norway was at the top in
2012 for both men and women for
healthy life expectancy. Norwegian
women at age 65 were expected
to live another 16 years without
activity limitations, and their male
counterparts 15.3 years. At the
other end of the spectrum, some
Eastern European countries had a
very short HALE. In Slovakia, for
example, women aged 65 were
expected to live just 3.1 years
without activity limitations and
men 3.5 years.
Healthy life expectancy can also
help to assess the extent to which
prevailing health conditions diverge
or converge with mortality pat-
terns. The proportion of life lived
in good health, the ratio of HALE
to life expectancy, is a measure of
the compression or expansion of
morbidity, or the extent to which
the extra years of life lived are in
a state of good or poor health and
well-being. For example, among
European countries, Slovakia had
the lowest proportion of remain-
ing years of life expectancy at age
65 in good health—16 percent for
women and 23 percent for men.
Sweden, on the other hand, had
the highest proportion at age 65
of remaining years with no activity
limitation—73 percent for women
and 77 percent for men.
BIG IMPACTS, OPPOSITE
DIRECTIONS? SMOKING AND
OBESITY
Risk factors, such as tobacco use,
physical inactivity, obesity, mid-
life hypertension, and household
air pollution from solid fuels are
directly or indirectly responsible for
a large share of the global burden
of disease (Lim et al., 2012). A
leading contributor to mortality
and morbidity, tobacco use has
dropped dramatically in countries
like the United States over the past
3 decades. Yet an estimated 18
percent of the general U.S. adult
population still smoke (Colditz,
2015) and the long latency of
health consequences from smok-
ing means that it is still playing
out in current mortality rates in
the United States and worldwide
(Crimmins, Preston, and Cohen,
2011; Preston et al., 2014; Ng
et al., 2014; Carter et al., 2015).
Therefore, while smoking-related
mortality is declining for American
men and women, the history of
heavy smoking in the United States
is still contributing to current and
future life expectancy estimates
and projections and to the poor
international ranking of U.S. life
expectancy at age 50 (Preston, Glei,
and Wilmoth, 2011). Meanwhile,
the time lapse for smoking decline
in other high-income countries
(for example in Western Europe)
means that the mortality impact
will continue to play out for many
years with uncertainty about the
exact trajectory; more fine-grained
data about smoking intensity and
duration are required for more
precise projections (Michaud et al.,
2011; Ng et al., 2014; Bilano et al.,
2015). The majority of smokers
worldwide live in low- and middle-
income countries (Ezzati and Riboli,
2013), where, for example, smok-
ers exceed 70 percent of men aged
60 and over in Laos and 20 percent
of women aged 60 and over in the
Philippines (Byles et al., 2014).
Both a history of obesity and cur-
rent obesity are important risk
factors in mortality (Abdullah et al.,
2011; Flegal et al., 2013; Kramer,
Zinman, and Retnakaran, 2013). In
older ages, being underweight is
also associated with increased mor-
tality (Population Reference Bureau,
2007). The prevalence of obesity
has increased in the United States
since the 1970s and accounts for
as much as 30 percent of the lower
U.S. life expectancy compared
to other high-income countries
(Alley, Lloyd, and Shardell, 2011;
Crimmins, Preston, and Cohen,
2011). While weight increase in
the United States has been larger
and at earlier ages than other
high-income countries, the obesity
epidemic is neither restricted to
the United States nor to younger
people (Ng et al., 2014). The preva-
lence of adult obesity ranges from
over 60 percent in some Pacific
Island nations to less than 2 per-
cent in Bangladesh (Stevens et al.,
2012; Ezzati and Riboli, 2013; Ng
et al., 2015). At ages 50 and older,
the United States has the highest
level of obesity when compared to
other high-income countries. Only
older English men and Spanish
women approach the levels of obe-
sity found among older U.S. men
and women (Crimmins, Garcia, and
Kim, 2011).
Clustering of risk factors increases
as age advances and increases the
risk of disease and poor health
(Negin et al., 2011a; Teo et al.,
U.S. Census Bureau An Aging World: 2015 39
2013). For example, the combina-
tion of dietary risk factors and
physical inactivity was responsible
for 10 percent of global disability-
adjusted life years (DALYs) in 2010
(Lim et al., 2012).2 A multicountry
study of NCD risk factors that
2 One DALY can be thought of as 1 lost
year of “healthy” life. The sum of these DALYs
across the population, or the burden of dis-
ease, can be thought of as a measurement of
the gap between current health status and an
ideal health situation where the entire popula-
tion lives to an advanced age, free of disease
and disability.
included over 38,000 respondents
aged 50 and older found a high
proportion of individuals with mul-
tiple risk factors (Wu et al., 2015).
China, Ghana, and India had com-
paratively lower rates of multiple
risk factors than Mexico, Russia,
and South Africa (Figure 4-5).
Another cross-Asian study found
that over 70 percent of adults aged
25 to 64 had three or more risk
factors for chronic NCDs (Ahmed et
al., 2009). The nature and patterns
of individual risk factors and risk
factor clusters are rapidly changing
by age, sex, education, and wealth
at the individual level, as well as
within and between high-, middle-,
and low-income countries (Dans
et al., 2011; Hosseinpoor et al.,
2012; Lim et al., 2012). Ongoing
surveillance and interventions will
be required to prevent NCDs and
to model the current and future
impacts of risk factors on health
(Ng et al., 2006; Bonita, 2009).
Figure 4-5.
Percentage Distribution of Cumulative Risk Factors Among People Aged 50 and
Over for Six Countries: 2007–2010
None 1 risk factor 2 risk factors
Percent
3 risk factors 4 risk factors 5 risk factors 6 risk factors
Note: Risk factors include current daily tobacco use, frequent heavy drinking, hypertension, insufficient vegetable and fruit intake,
low level of physical activity, and obesity.
Source: Wu et al., 2015. Adapted from Figure 2.
0 10 20 30 40 50 60 70 80 90 100
South Africa
Russia
Mexico
India
Ghana
China
40 An Aging World: 2015 U.S. Census Bureau
15.0 or more
14.3 to 14.9
13.1 to 14.2
Fewer than 13.1
United States Healthy Life Expectancy at Age 65 by Sex and State: 2007–2009
Source: Centers for Disease Control and Prevention, 2013. Adapted from Figure 1.
Men Women
DC
DC
(In years)
Figure 4-6.
State average
Male: 12.9
Female: 14.8
Years
With U.S. life expectancy at birth
and at age 65 falling behind many
other high- and middle-income
countries, the American wealth-
health paradox (wealthiest larger
country, but not the healthiest in
the world) and increasing regional
variability in the United States
confounds current understand-
ing about population health and
well-being (Murray et al., 2006;
Woolf and Aron, 2013). Smoking,
obesity, and high blood pressure
contributed to the relative increase
in female mortality as compared
to male mortality from the 1980s
to 2000s (Ezzati et al., 2008;
Danaei et al., 2010). Generally,
men and women living in the
(poorer) southern states of the
United States had lower healthy life
expectancy than elsewhere in the
country (Figure 4-6), and regional
inequalities in mortality appear
to be growing (Wilmoth, Boe, and
Barbieri, 2011; Olshansky et al.,
2012). Yet, the results are not all in
a negative direction for the United
States: it has higher survival after
age 75 than many high-income
countries, lower current smoking
rates, and better management of
hypertension. In fact, a measure
that captures functioning and pres-
ence of health conditions together
resulted in no differences in
health when comparing the United
States and England (Banks et al.,
2006; Cieza et al., 2015). A better
understanding of the key dynam-
ics contributing to the U.S. health
disadvantage relative to other high-
income countries, and a standard-
ized metric for measurement, may
well inform trajectories of aging
and health in many other contexts.
U.S. Census Bureau An Aging World: 2015 41
Box 4-1.
Early Life Conditions and Older Adult Health
By Mary C. McEniry, University of Wisconsin-Madison
Adult health, disease, and mortality in later life are influenced by early life factors (Barker, 1998; Crimmins
and Finch, 2006; Smith et al., 1998). Research also supports the influence of the social determinants of
health and socioeconomic conditions on health outcomes later in life (Marmot and Wilkinson, 2005; Almond
and Currie, 2010). These findings demonstrate the importance of a life-course approach to understanding
older adult health. This life-course approach has expanded our understanding of modern shifts in life expec-
tancy in diverse settings.
The intriguing links between early life adversities and later life health can be examined through the rapid
mortality declines during the 1930s to the 1960s in less developed countries (Palloni, Pinto-Aguirre, and
Pelaez, 2002). During this period, less developed countries experienced significant reductions in infant and
child mortality triggered by the medical and public health revolution (Preston, 1976). However, adults born
during these 4 decades were still exposed to poor socioeconomic conditions, poor nutrition, and infectious
diseases as infants and children. Exposure to these conditions in early life can increase the risk of poor health
at older ages and, in particular, increase the risk of adult diabetes, obesity, and heart disease (Barker, 1998;
Elo and Preston, 1992; Lillycrop et al., 2014; Tarry-Adkins and Ozanne, 2014).
Cohorts increasingly characterized by their exposure to and survivorship of poor early life conditions may be
at higher risk of poor health at older ages, especially for diseases known to originate in early life. The pro-
jected large increases in adult health conditions, such as diabetes, obesity, and heart disease, may well have
their origins in the past (Murray and López, 1996; Hossain, Kawar, and El Nahas, 2007). These circumstances
may also have important implications for older adult health for at least the next 20 to 30 years (Palloni,
Pinto-Aguirre, and Pelaez, 2002).
The timing of rapid mortality decline was different across countries for the birth cohorts of the 1930s to
1960s. The present-day middle-income countries, such as Costa Rica, experienced rapid mortality reductions
in the 1930s and 1940s, whereas several of today’s low-income countries did not experience significant mor-
tality changes until the 1950s and 1960s. If early life events indeed have large impacts on adult health, and if
differences in timing and pace of mortality decline created cohorts with markedly different health patterns in
later life, then differences in health patterns for adults aged 60 and over should appear.
A newly compiled data set contains harmonized cross-sectional and longitudinal data from major surveys of
older adults or households in 20 countries and areas in Asia, Africa, and Latin America, as well as England,
the Netherlands, and the United States (McEniry, 2013). The countries contributing data are diverse in their
patterns of mortality decline and early life nutrition and infectious disease environments during the 1930s
to the 1960s. The data set includes both very poor and wealthier countries and areas in the 1930s, including
those that saw their economic status rise over time (e.g., Barbados, Puerto Rico, and Taiwan) and their aver-
age caloric intake increase (China, Costa Rica, Mexico, and others) (Table 4-4).
These data reveal health patterns in older adults born during periods of rapid demographic changes, par-
ticularly for adult diabetes in the cohort born in the 1930s and 1940s. Figure 4-7 compares country-specific
prevalence of self-reported diabetes for these older adults surveyed in the 2000s with country-level per-
capita daily caloric intake in the 1930s and 1940s during their childhood. A high prevalence of adult diabetes
is found for those born in very poor caloric intake countries that experienced significant and rapid mortality
decline in the 1940s (countries labeled C and D in Figure 4-7). The prevalence is higher than for those born in
Continued on next page.
42 An Aging World: 2015 U.S. Census Bureau
countries that experienced a more gradual mortality decline (countries labeled A and B), or countries that did
not experience significant mortality decline (countries labeled E). Being born into a country that experienced
rapidly increasing life expectancy during the 1940s (labeled C and D) increased the odds of adult diabetes by
61 percent to 72 percent and of adult obesity by 46 percent to 53 percent (McEniry, 2014). Even though the
numbers in the graph for diabetes are self-reported and are probably underestimated, especially for low- and
middle-income countries, the prevalence of diabetes in C and D countries is higher now than what appeared
historically in more developed countries (labeled A) (Wilkerson and Krall, 1947; Gordon, 1964; García-Palmieri
et al., 1970; Hadden and Harris, 1987; Harris et al., 1998). With more accurate information about the preva-
lence of diabetes, the steepness of the line would most likely increase, suggesting a larger contrast between
middle- and high-income countries. The rapid demographic changes between the 1930s and the 1960s may
help explain these health patterns and predict what is to come for adults in low-income countries born in the
1950s and 1960s.
Two avenues of research hold promise in further examining early life conditions and older adult health. The
epigenetic basis for disease may lead to developing future therapeutic approaches to prevent or address dis-
ease. Epigenetic patterns may also provide clearer evidence about lifetime health risks resulting from expo-
sures that occur in utero and in childhood (Horvath, 2013; Lillycrop et al., 2014). On the other hand, emerg-
ing interest in using genomic data with social science survey data may provide a better understanding of how
genes and early life environment combine to influence adult health. Recent evidence shows that poor early
life conditions can impact gene expression at older ages (Levine et al., 2015). Both research avenues have the
potential to lead to informed health policy that benefits those exposed to poor early life conditions.
Table 4-4.
GDP per Capita and Caloric Intake in Selected Countries
and Areas: 1930s and 2000s
Country GDP per capita
1930s
Income group
2000s
Caloric intake
1930s 2000s
Barbados ............ 1,815 High N 3,025
England ............. 5,441 High 3,005 3,370
Netherlands .......... 5,603 High 2,958 3,215
Puerto Rico .......... 815 High 2,219 N
Taiwan .............. 1,150 High 2,153 N
United States ......... 6,231 High 3,249 3,732
Argentina ............ 4,080 Upper middle 3,275 3,272
Brazil ............... 1,048 Upper middle 2,552 2,885
Chile ............... 2,859 Upper middle 2,481 2,806
Costa Rica ........... 1,626 Upper middle 2,014 2,804
Cuba ............... 1,505 Upper middle 2,918 3,051
Mexico .............. 1,618 Upper middle 1,909 3,172
South Africa .......... 2,247 Upper middle 2,300 2,886
Uruguay ............. 4,301 Upper middle 2,902 2,831
Bangladesh .......... 659 Low 2,021 2,125
China ............... 568 Lower middle 2,201 2,908
Ghana .............. 878 Low 2,311 2,596
India ................ 726 Lower middle 2,021 2,314
Indonesia ............ 1,141 Lower middle 2,040 2,498
N Not available.
Note: GDP per capita is expressed in 1990 international dollars. Income group reflects World Bank
categories. Puerto Rico was classified as high income due to its relationship with the United States. Caloric
intake is daily caloric intake per capita.
Source: McEniry, 2014. Adapted from Table 1.1 and Table 2.1.
Continued on next page.
U.S. Census Bureau An Aging World: 2015 43
Figure 4-7.
Caloric Intake in Early Life and Diabetes in Later LIfe
Notes:
A = more developed countries, experiencing earlier and gradual mortality decline (beginning or prior to mid 20th century)
B = less developed countries, experiencing earlier and more gradual mortality decline (early to mid 20th century)
C = less developed countries, experiencing later and more rapid mortality decline (around 1930s)
D = less developed countries, experiencing later and more rapid mortality decline (around 1940s)
E = less developed countries, experiencing very late rapid mortality decline (after 1950s)
CLHLS = Chinese Longitudinal Healthy Longevity Survey
CHNS = China Health and Nutrition Study
HRS = Health and Retirement Study
MHAS = Mexican Health and Aging Study
SAGE = Study on Global Ageing and Adult Health
WLS = Wisconsin Longitudinal Study
For a complete listing of surveys used in the figure, see McEniry, 2014.
Source: McEniry, 2014. Adapted from Figure 4.2.
Age-standardized diabetes prevalence (percent)
C. Puerto Rico
C. Costa Rica
D. Mexico
D. Mexico-SAGE
D. Mexico-MHAS
C. Taiwan
C. Chile
C. South Africa
E. China-SAGE
E. China-CLHLS
E. India
E. China-CHNS
E. Indonesia
B. Cuba
B. Uruguay
A. Netherlands A. UK
A. US-WLS
A. US-HRS
B. Argentina
D. Russia
E. Bangladesh
D. Brazil
Calories
1800 2000 2200 2400 2600 2800 3000 3200 3400
0
5
10
15
20
25
30
44 An Aging World: 2015 U.S. Census Bureau
CHANGE IS POSSIBLE!
The good news is that large-scale
chronic disease prevention is possi-
ble, resulting in gains in both popu-
lation health and wealth (Bloom et
al., 2011; Capewell and O’Flaherty,
2011; Ezzati and Riboli, 2012;
Franco et al., 2013). Modification or
elimination of health risk factors,
even for men and women aged
75 and older, can add years to life
(Rizzuto et al., 2012). The benefits
of risk factor modification are most
clear for control of hypertension
and high cholesterol in older adults
(Prince et al., 2014). High-income
countries are doing better at treat-
ment for these chronic diseases
than middle-income countries
(Crimmins, Garcia, and Kim, 2011;
Lloyd-Sherlock et al., 2014).
While significant health gains can
be realized from changes in risks
at older ages, changes earlier in life
will compound the benefits (Sabia et
al., 2012; Danaei et al., 2013; Wong
et al., 2015). Current projections for
reduction of the major risk factors,
including smoking and obesity,
show the potential benefit of the
resulting decrease in deaths (see
Figure 4-8) from four main NCDs
(cardiovascular diseases, chronic
respiratory diseases, cancers, and
diabetes) and is likely an underesti-
mate of the full impact (Kontis et al.,
2014; Carter et al., 2015).
Figure 4-8.
Projected 2025 Deaths by Age, Income Level, and
Projection Assumptions
Note: Number of deaths due to cardiovascular diseases, chronic diseases, cancers,
and diabetes.
Source: Kontis et al., 2014. Adapted from Figure 4B.
0 10 20 30 40
Achieving more
ambitious tobacco use target
Achieving targets for risk factors
Business-as-usual trend
At 2010 death rate
Number of deaths in 2010
0 10 20 30 40
Achieving more
ambitious tobacco use target
Achieving targets for risk factors
Business-as-usual trend
At 2010 death rate
Number of deaths in 2010
Low- and middle-income countries
High-income countries
Aged 30 to 69 Aged 70+
Millions
Millions
U.S. Census Bureau An Aging World: 2015 45
Table 4-5.
Disability-Adjusted Life Years (DALYs) Attributable to Chronic Noncommunicable
Diseases for World Population Aged 60 and Over: 1990 and 2010
(Nmbers in millions)
Chronic noncommunicable disease 1990 2010 Change 1990–
2010 PercentNumber Percent of total Number Percent of total
Cerebrovascular disease .............. 54.5 12.5 66.4 11.6 21.8
Chronic obstructive pulmonary disease. . . 44.7 10.3 43.3 7.5 –3.1
Dementia .......................... 4.7 1.1 10.0 1.7 112.8
Diabetes mellitus .................... 12.6 2.9 22.6 3.9 79.4
Hearing impairment .................. 5.3 1.2 7.5 1.3 41.5
Ischaemic heart disease .............. 60.7 14.0 77.7 13.5 28.0
Vision impairment ................... 7.0 1.6 10.4 1.8 48.6
Note: One DALY can be thought of as one lost year of “healthy” life. The sum of these DALYs across the population, or the burden of disease, can be thought of
as a measurement of the gap between current health status and an ideal health situation where the entire population lives to an advanced age, free of disease and
disability.
Source: Prince et al., 2014. Adapted from Table 1.
WHAT DOESN’T KILL YOU,
MAKES YOU . . . POSSIBLY
UNWELL
For most countries, age- and sex-
specific mortality is decreasing, with
a progressive shift towards a larger
share of deaths caused by NCDs
and injury (GBD 2013 Mortality
and Causes of Death Collaborators,
2015). This means that more people
are living longer with these chronic
conditions and the resulting decre-
ments in health. The loss of health,
not including death, is more diffi-
cult to quantify. Does the presence
of chronic disease in one of two
otherwise identical populations
make the population without the
disease healthier (Banks et al., 2006;
Martinson, Teitler, and Reichman,
2011)? Other researchers (Fries,
1980; Gruenberg, 1977; Manton,
1982) recommend using a metric of
decrements in functioning to define
population health and aging. Still
other researchers recommend that
a combination of both number of
chronic diseases and decrements
in functioning be used (Cieza et al.,
2015; Beltrán-Sánchez, Razak, and
Subramanian, 2014).
The global burden of NCDs, such
as heart and lung diseases, diabe-
tes, depression, and dementia, in
people aged 60 and older grew by
33 percent between 1990 and 2010
(Prince et al., 2014). People in this
broad older age group account for
23.1 percent of the total disease
burden (World Health Organization,
2008). The per-capita disease bur-
den, DALYs/1000 population, for
older adults is higher in low- and
middle-income countries than in
high-income countries (Prince et
al., 2014).
The largest increases from 1990 to
2010 are seen in the burdens from
dementia (113 percent) and diabe-
tes (79 percent; Table 4-5). The five
most burdensome conditions for
adults aged 60 years and older in
2010 are ischaemic heart disease
(77.7 million DALYs), stroke (66.4
million DALYs), chronic obstructive
pulmonary disease (43.3 million
DALYs), and diabetes (22.6 million
DALYs; Table 4-5).
46 An Aging World: 2015 U.S. Census Bureau
Box 4-2.
The Rising Tide of Aging With HIV
By Joel Negin and Robert Cumming, University of Sydney
The HIV pandemic has had a profound impact across the world. In 2013, an estimated 35 million people
were living with HIV and the global response to the epidemic has been unprecedented in terms of funding,
attention, and action (Joint United Nations Programme on HIV/AIDS, 2014). Despite considerable progress,
important gaps remain in the global HIV response. Older adults have long been neglected despite important
evidence of the growing impact among those aged 50 and older in both developing and developed countries
(Mills, Barnighausen, and Negin, 2012).
As of 2013, more than one-third of those living with HIV in North America and Western Europe were aged
50 and older (Mahy et al., 2014; Joint United Nations Programme on HIV/AIDS, 2014). In Latin America, 15.4
percent of those living with HIV were in this age group and in Sub-Saharan Africa—the region most affected
by HIV—almost 12 percent were aged 50 and over (Joint United Nations Programme on HIV/AIDS, 2014). The
numbers are increasing, with a dramatic rise in those aged 50 and older living with HIV in all regions of the
world (Figure 4-9). In Sub-Saharan Africa, there are already more than 2.5 million adults aged 50 and over
living with HIV.
This rapid increase in the HIV burden among older adults can be attributed to a number of factors.
Principally, the 13 million people accessing anti-retroviral treatment are living longer with life expectancies
returning to near normal in most countries (Joint United Nations Programme on HIV/AIDS, 2014; Mills et al.,
2011). Therefore, many individuals are now aging with HIV into their 50s and beyond. In addition, older
adults remain sexually active and condom use among those aged 50 and over remains low, thus putting
these individuals at risk of HIV transmission (Drew and Sherrard, 2008; Freeman and Anglewicz, 2012). In
general, older adults have lower levels of HIV-related knowledge than younger adults (Figure 4-10). Lack of
knowledge works to impede preventative actions and, as a result, contributes to emerging evidence of new
HIV infection among older adults (Wallrauch, Barnighausen, and Newell, 2010).
Lower levels of HIV-related knowledge and HIV testing among older adults not only have implications for HIV
transmission, but for HIV treatment as well. Those aged 50 and older have smaller CD4+ T-cell gains while on
treatment (Vinikoor et al., 2014). They also have poorer therapy outcomes than younger adults (Bakanda et
al., 2011; Negin et al., 2011b).
The emergence of multimorbidity is a further challenge for HIV care as a result of living longer with HIV. Aging
with HIV means older individuals often have the additional burden of multiple chronic health conditions. Older
people living with HIV have high rates of kidney disease, cognitive impairment, and metabolic abnormalities
(Calvo and Martinez, 2014; Cysique and Brew, 2014; Nadkarni, Konstantinidis, and Wyatt, 2014). There is
ongoing debate whether claims of accelerated aging as a result of HIV and its treatment have been overstated
(Justice and Falutz, 2014). However, there is evidence from South Africa that those living with HIV have mark-
ers of accelerated aging—reduced telomere length and CD2NKA expression—when compared to HIV-negative
individuals (Pathai et al., 2013). Prevention, testing, and treatment services targeted at older adults and
designed appropriately will help ensure an inclusive response to the continuing HIV epidemic.
Continued on next page.
U.S. Census Bureau An Aging World: 2015 47
Figure 4-10.
Percentage With Comprehensive Knowledge About HIV and AIDS by Age
and Country: Selected Years
Sources: ICF International, 2014; Demographic and Health Surveys, various countries and years.
Uganda 2011Sierra Leone 2013Rwanda 2010Lesotho 2009Ethiopia 2011
31.0 31.3
23.3
29.2
15–49 50–59
26.5
24.5
51.6
43.0 42.7
39.7
Figure 4-9.
Number of People Aged 50 and Over Living With HIV for Selected Regions:
1995 to 2013
Note: Regional grouping per UNAIDS, 2014.
Source: Joint United Nations Programme on HIV/AIDS (UNAIDS), 2014.
0
500
1000
1500
2000
2500
3000
2013201020072004200119981995
Sub-Saharan Africa
Western and Central Europe and Northern America
Asia and the Pacific
Latin America
Thousands
48 An Aging World: 2015 U.S. Census Bureau
Table 4-7.
Disability Prevalence Rate by Age Group for Malawi: 2008
(In percent)
Age group Total Male Female
5 and over .......... 4.3 4.3 4.4
5 to 14 ............. 2.8 2.9 2.6
15 to 64 ............ 4.2 4.2 4.2
65 and over ......... 17.6 17.1 18.0
Source: Malawi National Statistical Office, 2010.
Table 4-6.
Odds Ratios for Effect of Age, Sex, and Educational Attainment on Multimorbidity for
World Regions: 2002–2004
Region
Age Sex Educational attainment
Under 55
55 and
over Male Female
Less than
primary Primary Secondary Higher
All regions ............................. 1.00 ***4.10 ***0.59 1.00 ***1.33 1.00 0.97 0.97
Africa ............................... 1.00 ***3.13 ***0.56 1.00 ***1.64 1.00 0.99 0.90
Central and South America .............. 1.00 ***2.99 ***0.43 1.00 ***1.31 1.00 0.91 0.81
Eastern Europe and Central Asia ......... 1.00 ***6.02 ***0.59 1.00 1.17 1.00 ***0.60 ***0.49
South Asia ........................... 1.00 ***4.08 ***0.68 1.00 ***1.36 1.00 ***0.53 ***0.46
South East Asia ....................... 1.00 ***3.09 ***0.80 1.00 ***1.81 1.00 **0.82 0.90
Western Europe ....................... 1.00 ***5.95 ***0.53 1.00 ***1.61 1.00 ***0.40 ***0.18
Notes: * p-value<0.05; ** <0.01; *** <0.001. Regional grouping per Afshar et al., 2015.
Source: Afshar et al., 2015. Adapted from Table 4.
PRESENCE OF MULTIPLE
CONCURRENT CONDITIONS
INCREASES WITH AGE
NCDs often occur together and
when two or more such chronic
health conditions occur, it is termed
“multimorbidity” (Boyd et al., 2008;
Fortin et al., 2010; Diederichs,
Berger, and Bartels, 2011). The
complex care required to manage
multimorbidity often adversely
impacts health and quality of life
and increases health service use
(Schoenberg et al., 2007; Lehnert
et al., 2011; Barnett et al., 2012).
Evidence from both high- and low-
income countries indicates that
older age is a risk for multimorbid-
ity, from over 30 percent in India
and 58 percent in Bangladesh, to 60
percent in Spain and Germany, and
76 percent among Scottish adults
aged 75 and older (Khanam et al.,
2011; Kirchberger et al., 2012; Pati
et al., 2014; McLean et al., 2014;
Garin et al., 2014).
A review of 26 studies from WHO’s
Eastern-Mediterranean countries
reported that a higher prevalence
of multimorbidity is associated with
low income, low level of educa-
tion, and unemployment (Boutayeb,
Boutayeb, and Boutayeb, 2013). One
study of 28 countries (Afshar et al.,
2015), using highest level of educa-
tion as a proxy for socioeconomic
status, reveals a positive association
between age and multimorbidity
and a negative association between
education and multimorbidity
across different regions (Table 4-6).
Compared with the reference group
(odds ratio of 1.00), an odds ratio
greater than “1” indicates that the
comparison group was more likely
to have multimorbidity; and an odds
ratio smaller than “1” indicates the
opposite. The results here point
to a higher multimorbidity burden
in those who are older or the least
educated in both higher- and lower-
income countries. In a study of six
countries, multimorbidity showed
clear age, sex, and wealth patterns,
with resulting higher levels of dis-
ability, depression, and poor quality
of life (Arokiasamy et al., 2015).
For the growing population of
older adults with HIV (Negin and
Cumming, 2010), now considered a
chronic condition given the success
of antiretroviral therapy (Negin et
al., 2012; Deeks, Lewin, and Havlir,
2013), multimorbidity is an even
bigger problem. In one study, 91
percent of older adults with HIV had
one comorbidity condition and 77
percent had multiple comorbidity
conditions (Karpiak, Shippy, and
Cantor, 2006). The most common
comorbidities in that study were
depression (52 percent), arthritis
(31 percent), hepatitis (31 percent),
neuropathy (30 percent), and hyper-
tension (27 percent). A challenge
for aging with HIV is the additional
layer of treatment-related complex-
ity and associated adverse effects
(High et al., 2012).
TREND OF AGE-RELATED
DISABILITY VARIES BY
COUNTRY
Whether the additional years of life
lived will be in good or poor health
remains contested, but research
suggests that the aging process
is modifiable (Christensen et al.,
2009). Data show that disability
rates rise with age (He and Larsen,
2014; Table 4-7). An examina-
tion of limitation in activities of
U.S. Census Bureau An Aging World: 2015 49
daily living (ADLs) in 12 European
countries, Israel, and the United
States shows a steady rise with
age in all countries. The increase
is considerable between the ages
of 50 and 70 in Greece, Italy, and
Spain, whereas increases are more
evident in adults aged 70 and older
in the Netherlands, Sweden, and
Switzerland (Chatterji et al., 2015).
Levels of ADL limitations have been
falling steadily across consecutive
study cohorts in England compared
to the United States (Figure 4-11).
In the United States, the mean
proportions of ADL have steadily
increased across all ages older than
50, while in England, the propor-
tions decreased except for those at
the oldest ages (Figure 4-11).
FRAILTY IS A PREDISABLED
STAT E
Frailty and disability are interre-
lated yet have distinct conditions.
The classifications and definitions
of frailty are numerous, with no
consensus at this point (Abellan
van Kan et al., 2008). However, two
definitions are often operational-
ized as a physical phenotype (Fried
et al., 2001) and a multidomain
phenotype (Rockwood, 2005). One
description of frailty is a multi-
dimensional syndrome of loss of
reserves (energy, physical ability,
cognition, or health) that gives rise
to vulnerability (Rockwood et al.,
2005). In this case, frailty could be
a predisabled state. An individual
could be frail but without any
disabilities; or frail people could
have comorbidity and disability.
A study comparing community-
dwelling adults aged 50 and older
found clear socioeconomic gradi-
ents in higher- and lower-income
countries—individuals with lower
education and wealth levels were
more likely to be frail. The study
also reported higher levels of frailty
in older age and higher rates in
women than men (Harttgen et
al., 2013).
Figure 4-11.
Activity of Daily Living Limitations by Age for
the United States and England: 1998 to 2008
1998
2002
2004
2006
2008
2002
2004
2006
2008
Mean ADL
Mean ADL
Age
Age
Note: U.S. data are from the Health and Retirement Study; English data are from the
English Longitudinal Study of Ageing.
Source: Chatterji et al., 2015. Adapted from Figure 1.
England
United States
0.3
0.4
0.5
0.6
0.7
0.8
0.9
80787674727068666462605856545250
0.3
0.4
0.5
0.6
0.7
0.8
0.9
80787674727068666462605856545250
50 An Aging World: 2015 U.S. Census Bureau
THE U-SHAPE OF
SUBJECTIVE WELL-BEING
BY AGE IS NOT OBSERVED
EVERYWHERE
Quality of life is important at all
ages, but in later life it becomes
of paramount importance for the
remaining years to be lived. As life
expectancy increases and treat-
ments for life-threatening disease
become more effective, the issue of
maintaining well-being at advanced
ages is growing in importance
(National Research Council, 2013).
Yet research into subjective well-
being and health at older ages is
at an early stage (Steptoe, Deaton,
and Stone, 2014). Within subjective
well-being, at least three different
approaches have been used to cap-
ture different aspects of well-being.
One approach is life evaluation that
generally refers to one’s overall
life satisfaction or general happi-
ness with one’s life. Eudemonic
well-being, a second approach,
focuses on judgments about the
meaning and purpose of one’s life.
Finally, hedonic well-being refers to
everyday feelings or moods, such
as experienced happiness, sadness,
anger, and stress.
Looking at aspects of life evalu-
ation and hedonic well-being, a
U-shaped pattern is more evident
in high-income, English-speaking
countries (Figure 4-12), compared
to other regions where life satisfac-
tion either declines at older ages,
or remains rather stable across the
lifespan (Sub-Saharan Africa). Lack
of happiness (as an experienced
moment-to-moment emotion) is
rather uncommon in high-income
English-speaking and Latin America
and Caribbean countries, but quite
common in transition countries
(countries of the former Soviet
Union and Eastern Europe), includ-
ing nearly 70 percent of those aged
65 and older who were not happy
on the previous day (Steptoe,
Deaton, and Stone, 2014).
Although in high-income countries
subjective well-being has a typi-
cal U-shaped pattern with age, it
progressively decreases in older
adults in the former Soviet Union,
Eastern Europe, and Latin America.
This pattern is corroborated by
evidence from Finland, Poland, and
Spain, where poor health status is
significantly associated with nega-
tive emotional status and reduced
life satisfaction (Miret et al., 2014).
The dynamics between good health
and subjective well-being are
associated with longer survival,
which increases support for these
to be goals of economic and social
policies (Stiglitz, Sen, and Fitoussi,
2010). To achieve the proposed
post-2015 development agenda
goal of promoting well-being at
all ages will require a focus on
the health of the older population
(Suzman et al., 2014).
U.S. Census Bureau An Aging World: 2015 51
Figure 4-12.
Well-Being and Happiness by Age and Sex in Four Regions: 2006–2010
Note: Cantril ladder ranges from 0 (worst possible life) to 10 (best possible life).
Source: Steptoe, Deaton, and Stone, 2014. Adapted from Figure 1 and Figure 5.
Male
Female
Mean score
Life evaluation
High-income English-speaking countries
Age
4
5
6
7
8
65–7555–6445–5435–4425–3415–24
Proportion
Unhappiness
High-income English-speaking countries
Age
0.0
0.2
0.4
0.6
65–7555–6445–5435–4425–3415–24
Proportion
Age
0.0
0.2
0.4
0.6
65–7555–6445–5435–4425–3415–24
Proportion
Age
0.0
0.2
0.4
0.6
65–7555–6445–5435–4425–3415–24
Proportion
Age
0.0
0.2
0.4
0.6
65–7555–6445–5435–4425–3415–24
Mean score
Mean score
Mean score
Countries of the former Soviet Union and Eastern Europe Countries of the former Soviet Union and Eastern Europe
Age
4
5
6
7
8
65–7555–6445–5435–4425–3415–24
Sub-Saharan Africa Sub-Saharan Africa
Age
4
5
6
7
8
65–7555–6445–5435–4425–3415–24
Latin America and the Caribbean Latin America and the Caribbean
Age
4
5
6
7
8
65–7555–6445–5435–4425–3415–24
52 An Aging World: 2015 U.S. Census Bureau
Box 4-3.
Epigenetics of Aging
By Kirstin N. Sterner, University of Oregon
Most health outcomes associated with aging result from a complex interplay of an individual’s genome and
life experiences. Life experiences and environmental factors influence the expression of complex genetic
traits, making it difficult to identify specific genetic markers that can be used to slow aging or unambigu-
ously diagnose, treat, or prevent aging-related diseases. The epigenome helps mediate these gene-environ-
ment interactions and, therefore, has the potential to provide insights into aging and disease processes.
Life experiences, such as stress, nutrition, and environmental exposure, can affect the genome through “epi-
genetic modifications,” which are biochemical alterations of the genome and chromatin that make specific
regions of the genome more or less accessible to the cell’s transcriptional machinery without changing the
underlying DNA sequence itself. The results of these biochemical modifications are changes in gene expres-
sion (when genes are turned on/off and the quantity of gene product made). Unlike the genome, the epig-
enome can be dynamic and flexible, and varies across tissue/cell types and the lifespan.
One of the most commonly studied forms of epigenetic modification is DNA methylation. In DNA methyla-
tion, a methyl group is added to a cytosine in the genome sequence by DNA methyltransferases. A modified
cytosine is typically followed by a guanine, forming a “CpG” site. DNA methylation typically reduces gene
expression. During the normal aging process, there is an overall reduction in DNA methylation across the
genome, although increases have been observed in more localized regions (D’Aquila et al., 2013). This raises
the question of whether DNA methylation status can be used as a biomarker of aging and aging-related
diseases.
A number of recent studies have identified epigenetic markers associated with common aging-related dis-
eases, including Alzheimer’s, cardiovascular disease, and cancers, although the significance of these findings
is unclear (Kanherkar, Bhatiq-Dey, and Csoka, 2014; Jung and Pfeifer, 2015). In addition, some epigenetically
modified CpG sites predict age in specific tissues and across tissue and cell types (Hannum et al., 2013;
Horvath, 2013). These sites behave in a clocklike manner, with a higher rate of methylation early in life that
slows after adulthood and can be used to estimate an individual’s methylation age (Horvath et al., 2014). In
most cases, methylation age and true chronological age are highly correlated. When methylation age and
chronological age differ, it may suggest acceleration or deceleration of aging (see note).
There is a growing interest in identifying lifestyle, environmental, and genetic factors that are associated with
age acceleration to better understand aging-related diseases. While use of epigenetic data and the epigen-
etic clock is relatively new to aging-research, a number of recent studies hint at its potential. For instance,
methylation age acceleration is associated with decreased lung function, grip strength, and cognition and
increased all-cause mortality (Marioni et al., 2015a; Marioni et al., 2015b). Horvath (2013) used the epigen-
etic clock to identify evidence of age acceleration in liver tissue, adipose tissue, muscle, and blood. A study
of German patients found a strong correlation between body mass index (BMI) and liver disease, and between
BMI and age acceleration (Horvath et al., 2014; Figure 4-13). Age acceleration was defined as the residual
resulting from the regression of methylation age on chronological age. Further research is needed to deter-
mine: 1) the molecular mechanisms that underlie age acceleration; 2) how divergent patterns of methylation
influence health outcomes associated with aging; and, 3) how the epigenome changes throughout an indi-
vidual’s lifetime. Continued on next page.
U.S. Census Bureau An Aging World: 2015 53
Figure 4-13.
Age Acceleration in Liver Tissue and BMI
Note: Age acceleration is when someone’s epigenetic age, as measured overall or in particular body parts like the liver, is deemed
to be older than chronological age. BMI is body mass index. The dashed line indicates the regression line and data point
corresponds to a human subject. Age acceleration in liver tissue is significantly correlated with BMI (r=0.42, P=6.8X10-4).
Source: Horvath et al., 2014. Adapted from Figure 1E.
Years
Male Female
BMI
10 20 30 40 50 60 70 80
–15
–10
–5
0
5
10
54 An Aging World: 2015 U.S. Census Bureau
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CHAPTER 5.
Health Care Systems and Population Aging
Increasing longevity will force
adjustments to health care systems
and finance, retirement policies
and pensions, and likely labor and
capital markets (Lutz, Sanderson,
and Scherbov, 2008; Bloom,
Canning, and Fink, 2010; Lee and
Mason, 2011; National Research
Council, 2012). Population aging is
frequently placed in the framework
of whether health services, welfare
provision, and economic growth
are sustainable, dismissing the
substantial social, economic, and
cultural contributions from older
adults (Lloyd-Sherlock et al., 2012).
Aging is a concern for costs to
health care systems, as much as
health care costs are a concern for
older people, especially in settings
where there is limited institutional,
human, and financial resource
capacity to meet the basic needs
of older people and where social
safety nets do not exist. High-
income countries may differ from
low- and middle-income countries
in readiness or resources available
to provide health care for an aging
population.
The growing number and share of
older people in all societies are also
posing an increasing burden to old
age care. Institutional long-term
care and informal care combined
are some of the options to meet
this challenge.
INCREASING FOCUS ON
UNIVERSAL HEALTH CARE
AND AGING
As part of the post-Millennium
Development Goals set by the
United Nations (UN), universal
health coverage has become a
focus for the post-2015 Sustainable
Development Goals (United
Nations, 2012). Multiple interna-
tional organizations and many
governments argue that health and
other systems should be refor-
mulated to eliminate or minimize
inequalities and maximize healthy
life expectancy, capabilities, and
well-being in older ages (Sen, 1999;
Krueger et al., 2009; Stiglitz, Sen,
and Fitoussi, 2009; Marmot, 2013;
Chatterji et al., 2015). The goal is
for people at all ages to receive the
health services they need without
undue financial hardship.
The World Health Organization
(WHO) defines the goal for uni-
versal health coverage (UHC) as
ensuring that all people obtain the
health services they need without
risk of financial ruin or impoverish-
ment, and presents the concept of
UHC in three dimensions: (1) the
health services that are needed,
(2) the number of people that need
them, and (3) the costs to whoever
must pay (WHO, 2010; 2013). UHC
is understood and implemented in
many ways, with differences largely
based on potential recipients,
range and quality of services to be
provided, and financing of those
services (Stuckler et al., 2010;
Global Health Workforce Alliance
and World Health Organization,
2013; Global Health Watch, 2014).
In some countries, UHC is viewed
as a health insurance model that
would provide a means-tested,
basic package of limited services
with a multitude of service buyers
and providers, while in other coun-
tries it is a single provider, public
tax-financed system based on the
principles of equality of access for
all who need care.
Today close to half of the countries
worldwide are engaged in health
reforms as a result of the resur-
gence in interest in UHC, and a
little more than a half of the world
population is covered for about half
of the possible services they need
(Boerma et al., 2014; Marzouk,
2014). Two years after the UN
General Assembly Resolution on
global health and foreign policy
calling for UHC among all of its
Member States (United Nations,
2012), a coalition of more than
500 organizations from more than
100 countries marked December
12, 2014, as the first-ever
Universal Health Coverage Day
(Universalhealthcoverageday.org,
2014; WHO and World Bank, 2015).
66 An Aging World: 2015 U.S. Census Bureau
Table 5-1.
Country Distribution of Share of Population Without Legal Health Coverage by Region
Region
Total
number of
countries
studied
0% without coverage 1–49% without
coverage
50–74% without
coverage
75–100% without
coverage
Number of
countries
Percent of
region
Number of
countries
Percent of
region
Number of
countries
Percent of
region
Number of
countries
Percent of
region
Africa ......................... 47 4 8.5 8 17.0 6 12.8 29 61.7
Asia .......................... 43 14 32.6 16 37.2 6 14.0 7 16.3
Europe ........................ 40 19 47.5 20 50.0 0 0.0 1 2.5
Latin America and the Caribbean ... 31 6 19.4 9 29.0 5 16.1 11 35.5
Northern America ............... 2 1 50.0 1 50.0 0 0.0 0 0.0
Oceania ....................... 4 4 100.0 0 0.0 0 0.0 0 0.0
Notes: Legal health coverage is defined as percentage of population affiliated to or registered in a public or private health system or scheme.
Number of countries includes only countries with available data for legal health coverage; data as of latest available year.
Source: Scheil-Adlung, 2015. (Percentage distribution calculated based on the Statistical Annex.)
However, significant differences
remain between more developed
countries and less developed coun-
tries in coverage level (Table 5-1),
and the urban/rural divide in
health coverage and access is
consistent across the world
(Scheil-Adlung, 2015). Furthermore,
challenges common to all health
care systems extend beyond cover-
age and include financing and
quality (Massoud, 2014; USAID
Health Finance and Governance
Project, 2015).
There is considerable evidence that
population aging does not contrib-
ute substantially to growing health
care costs (Geue et al., 2014; Bloom
et al., 2015; Yu, Wang, and Wu,
2015). Public health and health care
systems that successfully reorient
toward the health and long-term
care needs of the older popula-
tion may help produce a “triple
dividend—thriving lives, costing
less, contributing more” (Early
Action Task Force, 2014). Given
this, the implications of popula-
tion aging on systems are far from
bleak if governments make the nec-
essary and targeted changes in the
face of population aging (Economist
Intelligence Unit, 2009; Bloom et
al., 2015). Nevertheless, aging will
demand action on health care for
the older population (Boerma
et al., 2014).
HEALTH SYSTEMS IN
RESPONSE TO AGING
The contribution of health care sys-
tems to population health has long
been contested, and while some
believe that health care does not
contribute significantly to health,
evidence is now emerging that sys-
tems which promote the adoption
of healthy lifestyles are improving
or maintaining the health of older
people (Cutler, Landrum, and
Stewart, 2006; McKee et al., 2009).
In both more developed and less
developed countries, chronic
noncommunicable diseases are the
main causes of mortality, mor-
bidity, and disability in old age.
Yet, throughout the world, health
systems are mainly designed to
provide episodic acute care. In
particular, health services geared
to the needs of older people would
need to be strengthened and bet-
ter integrated with other levels of
care to provide the continuum of
chronic care required (Tinetti, Fried,
and Boyd, 2012). The primary
health care system is also the best
channel to provide support to the
informal caregiver who provides
long-term, home-based care to a
dependent older person.
U.S. Census Bureau An Aging World: 2015 67
The demographic transition is shift-
ing population epidemiology from
primarily acute infectious disease
to primarily chronic infectious and
noninfectious disease. This alone
would suggest a need to reorient
health systems to ensure services
meet population needs, where
health and social services are
integrated, with continuity of care
across different services. Aging
populations will have different
health care needs, with more peo-
ple affected by dementia, stroke,
cancer, fractured hips, osteoporo-
sis, Parkinson’s disease, lower back
pain, sleep problems, and urinary
incontinence, for example. As
mentioned in Chapter 4, it is also
likely that the complexity of health
problems will increase as popula-
tions age, with more multimorbid-
ity and risk factor clustering, result-
ing in a plethora of treatments
that potentially interact with each
other (Dubois, McKee, and Nolte,
2006; Boyd and Fortin, 2010). This
complexity makes coordination
of care across health and social
services and integration across
different levels of care particularly
important. Some of this care might
be provided at home, rather than in
a facility—regardless, primary care
providers with geriatric training or
a comprehensive geriatric assess-
ment in all settings provide better
outcomes (Ellis et al., 2011; O’Neill,
2011). Health system reforms
that incorporate people-centered
health services that are sensitive
to the health needs at all ages over
the life course, including geriatric
assessments in older age, would be
an effective approach to integration
of care services (WHO, 2015).
Even before needing formal or
informal care, increased primary or
secondary prevention efforts could
have significant impacts on health
in older age, such as tobacco cessa-
tion, cognitive training, and immu-
nization programs for vaccine-
preventable diseases stemming
from human papillomavirus, influ-
enza- and pneumococcal-related
infections (Esposito et al., 2014).
Additionally, greater attention to
the unique needs of aging minority
populations by the health and social
systems may improve their healthy
life expectancy. All older adults
would benefit from appropriate and
well-coordinated health and social
policies, thereby slowing the rate
of age-related health decline and
the subsequent amount of services
required (Goldman et al., 2013).
Previous research on utilization
of health services at old age in
individual countries has found that
use peaks at about 80 years of
age, falling in those who are older
(McGrail et al., 2000; Kardamanidis
et al., 2007). These findings were
confirmed in the Survey of Health,
Ageing, and Retirement in Europe
(SHARE) which surveyed 20,000
Europeans over age 50 across 11
countries. The survey found that
the use of health services peaks at
ages 75 to 79, levels off at age 80,
and falls among those older than
85 years (Chawla, Betcherman, and
Banerji, 2007). The Study on global
AGEing and adult health (SAGE)
surveyed 35,000 people aged 50
and older across six middle- and
lower-income countries and found
that the 70–79 age group had the
highest likelihood of using both
outpatient and inpatient services
(Peltzer et al., 2014).
68 An Aging World: 2015 U.S. Census Bureau
Box 5-1.
Global Aging and Minority Populations: Healthcare Access, Quality of Care, and Use
of Services
By Karen I. Fredriksen-Goldsen, University of Washington
In addition to the common concerns about aging, older adults from minority and migrant groups face addi-
tional worries about support and access to services as they age. Barriers and discrimination at many levels
may impact access to needed services for themselves or loved ones, formal financial arrangements and secu-
rity, and physical accommodation in older age. The impact of discrimination and ongoing disadvantage over
a lifetime are borne out by recent numbers: lower life expectancies and higher disease burdens.
Despite recent attention, the gaps in life expectancy and other indicators are not closing, for instance, in
indigenous populations in Australia, Canada, and New Zealand, and for those with lower levels of educa-
tion (Olshansky et al., 2012; Mitrou et al., 2014). The variations in health often reflect differences by group
status such as race, ethnicity, immigration, socioeconomic status, sexual and gender identities, and physical
and mental abilities (National Institutes of Health, 2013). This is likely compounded by additional language,
linguistic, and cultural barriers (Warnes et al, 2004; Bramley et al., 2005; Sayegh and Knight, 2013). Among
lesbian, gay, bisexual, and transgender (LGBT) older adults, experiences of discrimination and victimization
are linked to poor health outcomes, yet they often experience barriers to accessing care and remain largely
invisible in services given their stigmatized identities (Fredriksen-Goldsen et al., 2011; Fredriksen-Goldsen
et al., 2013). Among those with intellectual, emotional, and physical disabilities, adjustments in healthcare
information are often needed to better match capacity (Emerson et al., 2011).
Health inequities, resulting from economic, environmental, and social disadvantage, are costly. In the United
States, where the 65-and-older population has nearly complete health care coverage by Medicare, it is
estimated that among Blacks, Hispanics, and Asian Americans, nearly one-third of direct healthcare expen-
ditures are excess costs as a result of health inequities (LaVeist, Gaskin, and Richard, 2009). Furthermore,
when examining differences in health care quality in the United States, those living in poverty, compared to
those with high incomes, received worse care for 47 percent of the quality measures; people aged 65 and
older received worse care for 39 percent of the quality measures compared to adults aged 18 to 44 (Figure
5-1; Agency for Healthcare Research and Quality, 2012). There were also significant differences by race and
ethnicity. Ensuring appropriate access to and use of care and quality care are critical factors in the promotion
of health, especially for racial and ethnic minorities, indigenous and aboriginal people, immigrants, LGBT
people, as well as those with intellectual, emotional, and physical disabilities.
Across population groups, several factors have been linked to inequities in health, including the heightened
risk of exposure to social determinants of poor health (such as poverty, unemployment, isolation, and dis-
crimination) and other structural and organizational barriers, including lack of available services and institu-
tional and societal biases in services as well as policies (Braveman, Egerter, and Williams, 2011). In addition,
older adults from these population groups may be at elevated risk of adverse health behaviors as well as at
risk of reduced health literacy. They may also be reluctant to utilize healthcare services, preventative screen-
ings, and other health promotion activities. Promoting health equity, embedded within a life course perspec-
tive, is critical for older adults across diverse population groups to have the capacity to reach their full health
potential (Fredriksen-Goldsen et al., 2014).
Continued on next page.
U.S. Census Bureau An Aging World: 2015 69
HEALTH SYSTEM’S
RESPONSE TO AGING IN
HIGH-INCOME COUNTRIES
Older population in higher-income
countries are typically further along
the epidemiologic transition; how-
ever, many of the existing health
care systems were created at the
early stages of the antibiotic era
and still need to evolve to provide
well-coordinated and integrated
care for chronic diseases. Health
systems in high-income coun-
tries are at different stages of this
evolution, but most have cost and
continuity of care issues related
to long-term treatment of chronic
conditions. In some cases, the sys-
tems themselves, to some extent,
shape population preferences
(Mair, Quinones, and Pasha, 2015).
Regardless of preferences though,
removal of financial and other
barriers to access, through univer-
sal coverage efforts, would benefit
all people including vulnerable
populations in wealthier countries
(Nolte and McKee, 2012).
Just as national health and social
systems are at different stages in
their service capacity, some coun-
tries have older adult populations
with declining disability, while
other countries have increasing
Figure 5-1.
Proportion of Quality Measures for Which Members of Selected Groups
Experienced Better, Same, or Worse Quality of Care Compared With Reference
Group in the United States: 2011
Better (Population received better quality of care than reference group)
Same (Population and reference groups received about the same quality of care)
Worse (Population received worse quality of care than reference group)
Percent
AIAN American Indian or Alaska Native. NHW Non-Hispanic White.
Note: “ref.” is reference groups.
Source: Agency for Healthcare Research and Quality, 2012.
0
20
40
60
80
100
Poor
(ref. High Income)
Hispanic
(ref. NHW)
AIAN
(ref. White)
Asian
(ref. White)
Black
(ref. White)
70 An Aging World: 2015 U.S. Census Bureau
disability (Wahrendorf, Reinhardt,
and Siegrist, 2013). These systems
will need to invest in patient-
centered prevention, treatment,
and palliation in correct propor-
tions and across an integrated
continuum, incorporate cutting-
edge knowledge of what improves
health as a population ages—not
necessarily expensive new technol-
ogy—and offer health prevention
opportunities across the life course
so that individuals arrive at older
age in a healthier state (Fried and
Paccaud, 2012). Such health care
models would need a multidisci-
plinary team to deal with diverse
health needs, including increasing
illness complexity, disability, and
frailty.
HEALTH SYSTEM’S
RESPONSE TO AGING IN
LOW- AND MIDDLE-INCOME
COUNTRIES
The competition for resources is
strong in all countries—albeit, at
different starting points in terms
of level of existing infrastructure,
human resources, and available
finances and mechanisms for cost-
sharing (Ali et al., 2013). The rate
of aging in lower-income countries
today means that governments
will have less time to prepare than
higher-income countries have had
in the past. Fortunately, interna-
tional attention to achieving uni-
versal health care has the potential
to stimulate national political will,
as well as financial and technical
assistance.
Regarding infrastructure, few low-
and middle-income countries have
vital registration systems with high
coverage of deaths, a cornerstone
of well-functioning health systems;
whereas high-income countries are
more likely to have accurate and
complete vital registration systems
(United Nations Statistics Division,
2014). Another important differ-
ence is in the quality of care, often
quite low in many low-income
countries, with few professionals
trained to provide multidisciplinary
geriatric care. Further complicating
matters is the loss of professionals
trained in lower-income countries
to positions in higher-income coun-
tries (Aluttis, Bishaw, and Frank,
2014).
Increasingly though, populations
are demanding that better health
services be provided without
causing financial hardship: the
top priority of African and Asian
respondents to a recent UN survey
(Kruk, 2013). Beyond provision of
a public good, governments may
gain public trust as a result of
improving health system access
and performance (Rockers, Kruk,
and Laugesen, 2012).
HEALTHCARE COST FOR
AGING POPULATIONS
A debate as robust as the ones
about lifespan limits and the com-
pression of morbidity (see Chapter
4) is raging about the role of aging
populations on increasing health
care costs (Peterson, 1999; Wallace,
1999; Heller, 2006; McKee et al.,
2009; The Economist, 2009; Bloom
et al., 2015). Despite the fact that
increased longevity underscores
one of the most remarkable human
success stories of any era, there
are serious concerns about the
potential economic consequences
of this global trend for rich and
poor countries alike. Yet, evidence
about the contribution of late life
costs to lifetime health care costs is
somewhat mixed (Alemayehu and
Warner, 2004; Martini et al., 2007;
Suhrcke et al., 2008; Ogawa et al.,
2009; Payne et al., 2009; Center for
Studies on Aging—Lebanon, 2010;
Tchoe and Nam, 2010; Medici,
2011; World Bank, 2011).
While health care costs at the
individual level are largely driven
by ill health, hosts of demographic
and nondemographic factors are
driving costs for the entire health
system. Aging is just one of the
demographic contributors; others
include urbanization, migration,
and family/household structures.
Numerous nondemographic factors
contribute to health care costs,
including technological advances
in health care, increasing use of
technology, and higher female
employment levels—resulting in
less informal (unpaid) caregiving
(Rechel et al., 2009). While some-
what limited data are available,
the current evidence suggests that
health costs are highest around the
beginning and end of life in many
countries, and that the final 2 years
before death consume around
one-quarter of one’s lifetime health
cost, regardless if one is young or
old (Economist Intelligence Unit,
2009; Ji-yoon, 2010). Nonetheless,
and noting the limitations of avail-
able research, at the population
level and removing proximity to
death, longer life does not neces-
sarily correlate with higher health
expenditure, (Felder, Zweifel, and
Werblow, 2006; Seshamani and
Gray, 2004; Felder, Werblow, and
Zweifel, 2010).
U.S. Census Bureau An Aging World: 2015 71
Figure 5-2.
Out-of-Pocket Health Care Expenditures as a
Percentage of Household Income by Age Group and
Income Category in the United States: 2009
Source: Federal Interagency Forum on Aging-Related Statistics, 2012.
Poor/near poor Low/middle/high income
21
23
22
4
6 6
5
23
85+75–8465–7465+
Chronic conditions are, on average,
typically more costly to treat than
acute, time-limited infectious dis-
eases. While older adults are more
likely to have chronic diseases,
population aging alone has been
found to contribute only a small
amount to health spending growth
(White, 2007; Martin, Gonzalez,
and Garcia, 2011; Xu, Saksena, and
Holly, 2011; de Meijer et al., 2013).
Current evidence suggests that the
promotion of “healthy” or “active”
aging may reduce lifetime health
care expenditure (Dormont et al.,
2008; Suhrcke et al., 2008;
Fried, 2011).
The contribution from population
aging on overall health spending
remains difficult to clearly delin-
eate. We do know that older adults
are typically high users of care,
this population group is growing
in number, and per capita health
costs continue to grow in many
countries (de la Maisonneuve and
Martins, 2013). A challenge for
governments will be to slow or
stop ever-growing health spending
as a proportion of gross domestic
product (GDP) where population
aging is likely acting as a modest
cost driver (Appleby, 2013; OECD
2015). Encouragingly, the propor-
tion of public-sector health spend-
ing on older adults (as a percentage
of GDP) did not change significantly
in Canada between 2002 (44.6
percent) and 2012 (45.2 percent),
although there was considerable
variability across different regions
in the country (Canadian Institute
for Health Information, 2014).
Furthermore, total aging costs as a
percentage of GDP in the European
Union have been revised down-
wards in recent forward projection
analyses from 3.5 percent to 1.5
percent (European Commission,
2015).
COST IS ONE THING . . .
It is essential to reform the health
care financing system when
dealing with an aging popula-
tion (Economist Intelligence Unit,
2009). It may well be that aging
contributes only a small amount
to overall health care spending
growth in high-income countries.
Given the clear positive relationship
between wealth and health spend-
ing at the country and individual
levels, the association between
aging and health expenditures
may differ by level of country
development or by the wealth
of individuals within countries.
Even in high-income countries like
the United States, the burden of
out-of-pocket expenditures was
considerably higher for poorer than
wealthier older adults (Figure 5-2).
Poor or near poor U.S. households
with older adults had 3 to 5 times
higher out-of-pocket health care
costs as a percentage of household
income than wealthier households.1
Overall though, out-of-pocket
expenditures as a percentage of
household income in the United
States was below the 2009 aver-
age for Organisation for Economic
Co-operation and Development
(OECD) countries, suggesting a
considerable impact in many high-
income countries (Organisation
for Economic Co-operation and
Development, 2011).
1 Out-of-pocket expenses for U.S. older
adults depend on health status.
72 An Aging World: 2015 U.S. Census Bureau
Figure 5-3.
Predicted Quarterly Primary Care Costs by Time to Death and Age in Italy:
2006–2009
Source: Atella and Conti, 2014. Adapted from Figure 1.
0
50
100
150
200
250
300
350
12345678910111213141516
Euro per quarter
Ages 76 to 80
Ages 71 to 75
Ages 66 to 70
Ages 61 to 65
Ages 56 to 60
Time to death (quarters)
In high-income countries, costs
may also differ by type of care. An
example from Italy shows gener-
ally higher costs for primary care in
older adults than younger adults,
somewhat attenuated with proxim-
ity to death (Figure 5-3), but also
notes higher inpatient costs for
younger adults than older adults
(Atella and Conti, 2014). A study
in New Zealand with more com-
prehensive health system spend-
ing data also found wide variation
in costs by age (with costs per
person-year highest at age 0 and
ages 80 and over), but the varia-
tion was substantially less among
people within 6 months of death
(Blakely et al., 2014). With rising
life expectancy, projections of
health spending should separate
end-of-life expenditures and expen-
ditures for those not about to die,
otherwise future health costs will
be overestimated (ibid.).
Meanwhile, in middle- and low-
income countries, demographic
and epidemiological shifts are
creating higher costs for care and
financing systems not yet adapted
to providing the type of chronic
care required at a reasonable cost.
At the individual level, the burden
of noncommunicable diseases is
already large for the adult popu-
lation overall and may start at
earlier ages in many lower-income
countries, providing additional
rationale to start reconfiguring
health systems sooner rather
than later (Engelgau et al., 2011;
Robinson and Hort, 2012). Costs
from ongoing chronic care can be
especially debilitating for house-
holds in low- and middle-income
countries where a much higher per-
centage of health costs are out-of-
pocket, compared to high-income
countries; however, considerable
challenges remain for the uptake of
health insurance in these settings
(Schieber et al., 2006; Acharya et
al., 2012; Kruk, 2013).
In a number of middle- and low-
income countries, a long lag exists
in increasing per capita health
expenditure in line with growth in
national income. Even so, a system
overall that views chronic disease
management as serial acute epi-
sodes necessitating more interac-
tion with care providers is not a
sustainable arrangement (Allotey
U.S. Census Bureau An Aging World: 2015 73
et al., 2011; McKee, Basu, and
Stuckler, 2012). From a systems
perspective, inequalities in health
worker distribution within coun-
tries are often significant. Without
incentives, health professionals will
remain concentrated in urban cen-
ters, while many older people will
continue to live in rural settings
even with current urbanization
trends. Financing of health systems
is an increasing concern for econo-
mies as a whole when considering
the growth in overall population
sizes, the benefits of universal
coverage, and the need to provide
social protection in older age. The
costs and financing of care should
be examined in light of all drivers
of health spending, not just aging.
. . . ABILITY TO PAY IS
ANOTHER
When faced with health care
costs, a large portion of the global
population do not benefit from
cost sharing schemes, such as
health insurance, that would defray
potentially impoverishing health
expenses (Saksena, Hsu, and
Evans, 2014). These individuals
and households may delay or forgo
needed health care. This happens
more often in lower-income coun-
tries where formal health insurance
is rare, but cost and access are also
a concern for poorer and vulnerable
populations in high-income coun-
tries. A high percentage of costs for
drug, dental, and long-term care
facility services are out-of-pocket
for U.S. older adults covered by
Medicare insurance (Figure 5-4).
While not guaranteed, provisions
for health care in older age are
more often available for those liv-
ing in countries with social protec-
tion systems, or with universal care
schemes. Those without insurance
coverage or not living in countries
with social protection schemes
are forced to rely on alternative
financing mechanisms. These cop-
ing mechanisms provide important
information about how house-
holds deal with payments and also
income loss from inability to work
(Leive and Xu, 2008). For example,
almost 26 percent of households
Figure 5-4.
Source of Payment for Health Care Services by Type of Service
for Medicare Enrollees Aged 65 and Over in
the United States: 2008
Note: "Other" refers to private insurance, Department of Veteran's Affairs, and other public programs.
Source: Federal Interagency Forum on Aging-Related Statistics, 2012.
Other
Percent
Out-of-pocket
Medicaid
Medicare
0
20
40
60
80
100
Long
-term
care facility
Dental Prescription
drugs
Out-
patient
hospital
Physician/
medical
Short-
term
institution
Home
health
care
Inpatient
hospital
HospiceAll services
74 An Aging World: 2015 U.S. Census Bureau
HH Household.
Notes: A nonpoor household is considered to be impoverished by health payments when it becomes poor after paying for health care.
Catastrophic expenditures are out-of-pocket payments of at least 40 percent of a household's capacity to pay nonsubsistence spending.
For more information, see Xu et al., 2003.
Source: Bloom et al., 2015. Adapted from Figure 5.
HH with no
member 50+
HH with
member 50+
HH with no
member 50+
HH with
member 50+
HH with no
member 50+
HH with
member 50+
China Ghana India Mexico Russia South Africa
4.5
6.5 7.2
5.9
4.2
1.9
3.7 2.9
7.7
22.2 22.1
17.1
10.4
6.8
8.88.6
13.9
3.8
10.3
21.5
18.6
9.69.2
3.1
7.0
11.6
9.5
8.1
0.9
21.2
2.7
18.9
11.0
3.2
0.70.5
Impoverished by health Borrowed from relativesCatastrophic health expenditure
Figure 5-5.
Financial Impacts of Having a Household Member Aged 50 and Over in Six
Middle-Income Countries: 2007–2010
from 40 low- and middle-income
countries borrowed money or sold
items to pay for health care (Kruk,
Goldmann, and Galea, 2009).
WHO’s SAGE also provides a recent
look at the microeconomic impact
of aging on both households and
individuals (He, Muenchrath, and
Kowal, 2012). A larger financial
burden was seen in households
with members aged 50 and older
in all six countries. Households
with older adult members tended
to have higher rates of impov-
erishment and face higher rates
of catastrophic payment experi-
ence (Figure 5-5). These increased
demands on personal financial
resources resulted in increased
borrowing from relatives and,
consequently, amplified the burden
on the broader family and the
household unit. Increased borrow-
ing from family members and rela-
tives suggests a need for financial
support or improved access to
risk pooling for health care costs.
Formalized solutions which address
this need, such as publicly funded
health care that is free or (highly)
subsidized at the point of use, can
alleviate the burden not only on the
individual but also on the extended
household.
LONG-TERM CARE NEEDS
AND COSTS WILL INCREASE
Long-term care use consists of a
broad continuum of care, use of
which will undoubtedly increase
with population aging (Rechel
et al., 2009). Unlike health care
costs, a strong positive correlation
is seen with long-term care costs
and increasing size of the older
adult population. Long-term care
refers to services for persons who
have chronic, ongoing health and
functional dependency. Age and
disability are two main predictors
of long-term care need and expen-
ditures (Giovannetti and Wolff,
2010; Olivares-Tirado et al., 2011;
de Meijer et al., 2013). While we
know populations are aging, the
evidence about levels of current
and projected disability remains
unclear (Chapter 4). The percentage
of those aged 65 and older receiv-
ing long-term care exceeded 15
percent in seven OECD countries in
2011 (Figure 5-6).
U.S. Census Bureau An Aging World: 2015 75
Figure 5-6.
Percentage Receiving Long-Term Care Among Population Aged 65 and Over in
Selected Countries: Circa 2011
Note: Long-term care includes services provided at home or in institutions (nursing and residential care facilities which provide
accommodation and long-term care as a package).
Source: Organisation for Economic Co-operation and Development, 2013.
0.8
3.2
3.4
3.7
4.1
5.9
6.4
6.4
6.4
6.7
7.2
11.2
11.2
11.7
12.3
12.8
13.0
13.1
14.5
16.3
16.7
17.4
17.6
19.1
20.3
22.1
Israel
Switzerland
Netherlands
New Zealand
Norway
Denmark
Sweden
Australia
Czech Republic
Luxembourg
Japan
Finland
Germany
Hungary
France
Spain
Slovenia
South Korea
Estonia
United States
Iceland
Italy
Ireland
Canada
Slovakia
Poland
76 An Aging World: 2015 U.S. Census Bureau
Figure 5-7.
Annual Growth Rate in Public Expenditure on
Long-Term Care (LTC) in Institutions and at Home in
Selected Countries: 2005–2011
Source: Organisation for Economic Co-operation and Development, 2013.
Home LTC Institution LTC
Estonia
Spain
Switzerland
Japan
France
Finland
New Zealand
Norway
Belgium
Poland
Austria
Sweden
Germany
Canada
Denmark
Hungary
Czech Republic
Netherlands
Slovenia
1.3
4.3
3.5
8.2
1.8
1.7
1.7
1.9
2.2
2.5
3.1
3.1
3.7
4.5 11.6
8.14.8
6.4
6.4
6.5
6.9
7.3
7.6
8.0 4.0
8.7
16.6
4.0
4.7
2.6
–4.0
4.9
3.9
6.0
3.2
3.1
1.0
–1.6
A wide range of funding sources
are used for long-term care, with
four common models: (1) a special
long-term care insurance scheme,
as in Germany, Japan, and South
Korea; (2) general taxation, as
in Austria; (3) a combination of
insurance, general taxation, and
private contributions, as in Greece;
and (4) special programs, as in the
Netherlands (Chawla, Betcherman,
and Banerji, 2007). Private cofund-
ing also plays a role in almost all
European countries. However, the
annual growth in public long-term
care spending increased in most
OECD countries between 2005
and 2011 (Figure 5-7); over the
same period, the growth in spend-
ing on institutional long-term care
decreased in Finland and Hungary.
Long-term care programs also
differ in terms of whether they
cover people needing such care
at all ages or are limited to older
people, whether there is means
testing, the degree of cost-sharing,
the scope and depth of coverage,
and whether they support care by
family members or by trained and
supervised staff (Tamiya et al.,
2011). Regardless, there is sub-
stantial scope for better organiza-
tion and coordination of services
(Kendrick and Conway, 2006).
Outside of wealthy countries,
long-term care remains a neglected
policy issue. The common view
in lower-income countries relates
to the primacy of family provision
U.S. Census Bureau An Aging World: 2015 77
Figure 5-8.
Cumulative Growth in Elder Care Homes in Selected Chinese Cities: 1952 to 2009
Note: Elder care home is defined as a provider of institutional long-term care services licenced by the city government.
Source: Feng et al., 2011. Adapted from Figure 2.
0
50
100
150
200
250
300
350
20092006200320001997199419911988198519821979197619731970196719641961195819551952
Number of elder care homes
Beijing
Tianjin
Nanjing
of long-term care. This assumes
continued material and nonmate-
rial family support in the face of
widely documented demographic
and economic shifts. In many
lower-income countries, although
also in high-income countries,
longstanding assumptions about
families taking care of older people,
including health care expenses, are
breaking down—as young people
move to cities, more women enter
the labor force, couples have
fewer children, and intergenera-
tional spacing becomes greater.
As a result of these realities, social
attitudes towards formal care in
these settings may already be shift-
ing. In China, for example, where
the Constitution stipulates that
“children who have come of age
have the duty to support and assist
their parents,” institutional elder
care was virtually unknown until
recent years (Feng et al., 2011).
However, some major cities have
seen dramatic growth in elder care
homes operated by the city govern-
ment (Figure 5-8).
78 An Aging World: 2015 U.S. Census Bureau
Box 5-2.
Social Networks and Health Care Utilization
In recent years, a wide range of technological innovations, such as robot nurses and telemedicine, has been
developed in the United States, Europe, and Asia, to help care for older people (Economist Intelligence Unit,
2009). While technology will undoubtedly play an increasing role in future health care systems, social interac-
tions and relationships remain one of the drivers of health, behaviours, and health care utilization worldwide.
Social interactions and networks influence a wide range of behaviours and decisions in life, including some
impacting health that are quite remarkable—from recovery after a heart attack and susceptibility to the
common cold, to the dynamic spread of negative (smoking and obesity) and positive (happiness) factors for
health (Berkman, Leo-Summer, and Horwitz, 1992; Cohen et al., 1997; Christakis and Fowler, 2007; Christakis
and Fowler, 2008; Fowler and Christakis, 2008). Social integration also plays a considerable role in preserv-
ing memory as we age (Ertel, Glymour, and Berkman, 2008; Wang, He, and Dong, 2015).
Equally astonishing are recent findings about the role of social connectedness in disease pathways: experi-
mentally induced inflammation in otherwise healthy women and men contributed to greater increases in
depressed mood and feelings of social disconnection among women—suggesting a better understanding of
sex differences in depression prevalence and a possible avenue for interventions (Moieni et al., 2015). One
such health promoting intervention had a positive impact on social support and healthy lifestyle in a small
sample of adults aged 60 to 73 in Tehran (Foroushani et al., 2014), and multiple interventions to reduce
loneliness in older adults show promise (Cohen-Mansfield and Perach, 2015).
Social isolation, on the other hand, has been shown to be detrimental to health in older adults, including
higher all-cause mortality risk (Holt-Lunstad, Smith, and Layton, 2010; Shankar et al., 2011; Steptoe et al.,
2013). In another cohort of older community-dwelling adults, lack of social activity was associated with dis-
ability (James et al., 2011). Similarly, some social relationships have the potential for a health damaging effect
in older adults (Seeman, 2000).
Social relationships are critical for well-being in older adults and are also central to health maintenance over
the life course. Reaching older age in better health, partly as a result of strong positive social relationships,
would decrease health service needs and demands, yet the direct evidence behind the peer effect of social
networks on health care utilization in older age is sparse (Wang, He, and Dong, 2015). Researchers in the
United States showed how social relationships influenced the prevalence of having visited a dentist (Watt et
al., 2014) and a significant association with health service demand (Wang, He, and Dong, 2015). A study in
Canada found that social networks influence health care utilization through two main channels—sharing of
information and social norms (Deri, 2005). How this extends to older people in lower income countries and
the impact of social media remains to be determined.
One challenge for all countries will be to identify an etiologic period clearly enough to know when to inter-
vene. The follow-on challenge is how to construct an intervention in something as inherently complicated as
social networks over a lifetime.
U.S. Census Bureau An Aging World: 2015 79
Figure 5-9.
Percentage of Population Aged 50 and Over Who
Report Being Informal Caregivers in Selected
European Countries: 2010
Source: Organisation for Economic Co-operation and Development, 2013.
Belgium
Italy
United
Kingdom
Czech
Republic
Estonia
Netherlands
Hungary
Austria
France
Germany
Portugal
Switzerland
Slovenia
Spain
Poland
Sweden
Denmark 11.8
12.3
12.8
14.2
14.6
14.8
15.6
15.7
16.0
16.1
16.2
16.9
17.5
17.7
18.2
19.7
20.6
However, a number of factors
hamper the development of long-
term care programs including it
being a low policy priority, a lack
of disability data, and poor under-
standing of the extent and changes
in informal support systems. The
extent of neglect on this topic was
clearly illustrated in a recent study
about the heavily skewed balance
of published research on the topic
favoring high-income countries
(Lloyd-Sherlock, 2014).
QUANTIFYING INFORMAL
CARE AND CARE AT HOME
Unpaid caregiving by family mem-
bers and friends remains the main
source of long-term care for older
people worldwide (Fernández et
al., 2009). Yet it has a cost. At the
individual level, caregiving exacts
a considerable toll on the caregiver.
For example, in rural India, older
caregivers spent an average of 39
hours per week providing informal
care with consequences for their
own health and well-being (Brinda
et al., 2014). In 11 European coun-
tries, over 15 percent of the popu-
lations aged 50 and over reported
being informal caregivers in 2010
(Figure 5-9).
80 An Aging World: 2015 U.S. Census Bureau
Figure 5-10.
Percentage of Canadians Providing Care to Older
Population or Receiving Care by Age Group: 2014
Source: Canadian Medical Association, 2014.
34
5
18
12
16
5
75 and over65 to 7455 to 64
Providing care to older adult Receiving care
At the population level, efforts to
quantify the costs have helped to
increase recognition of the impor-
tance of informal unpaid care. In
some cases, this has translated
into payment schemes for informal
care, but more often has provided
insights into the types of sup-
port that can be given to informal
caregivers to keep older people at
home. The value of informal care to
the economy has been increasing,
reaching $522 billion annually in
a recent estimate from the United
States (Chari et al., 2014). One
particular condition, dementia, has
received attention because of its
increasing prevalence and the high
cost of care provision; and was
estimated to be around $200 billion
in 2010 in the United States alone,
with much of this cost borne by
informal caregivers (Schwarzkopf
et al., 2012; Hurd et al., 2013).
A number of high-income countries
have moved to reduce expensive,
formal institutional care while
increasing support for self-care
and other services that enable
older people to remain in their own
homes or a home-like environment
(Coyte, Goodwin, and Laporte,
2008; Häkkinen et al., 2008).
Informal care may substitute for
formal long-term care in some cir-
cumstances in Europe, particularly
when low levels of unskilled care
are needed (Bonsang, 2009).
Older adults are not solely recipi-
ents of pensions or health and
long-term care. This population
also provides a large proportion
of care for other people, includ-
ing older adults and spouses. In
Canada, for instance, 34 percent
of those aged 55 to 64 were care
providers and 5 percent were
care recipients (Figure 5-10). This
shifted to 12 percent care providers
and 16 percent care recipients in
the group aged 75 and older, but
nonetheless demonstrates giving
and receiving even into older age.
Informal care is more often pro-
vided by older women, many of
whom have higher levels of dis-
ability and chronic conditions than
men. Up to 71 percent of informal
caregivers in Hungary are women,
while this drops closer to parity
U.S. Census Bureau An Aging World: 2015 81
Figure 5-11.
Percentage of Women Among Informal Caregivers
Aged 50 and Over in Selected European Countries:
2010
Source: Organisation for Economic Co-operation and Development, 2013.
Hungary
Estonia
Italy
Poland
Portugal
Spain
Sweden
Czech
Republic
Switzerland
France
Austria
Germany
Slovenia
Belgium
Netherlands
United
Kingdom
Denmark 53.6
56.6
58.2
59.8
60.6
60.8
61.0
62.4
63.0
63.5
63.8
63.9
64.2
64.6
65.6
65.6
71.0
in Denmark, where 54 percent of
informal caregivers are women
(Figure 5-11).
Improvements in the caregivers’
health status may mean that more
older adults are able to provide
such care to a spouse or parent,
effectively enlarging the pool of
potential caregivers. Additionally, a
significant number of older people
in many countries engage in vol-
unteer work or help to look after
their grandchildren, providing an
important input into society that
would otherwise have to be pur-
chased in the marketplace (Chari et
al., 2014).
OTHER CARE OPTIONS:
RESPITE, REHABILITATIVE,
PALLIATIVE, AND
END-OF-LIFE CARE
A proportion of the older adult
population is faced with heavier
burdens from poor health and ill-
ness in older age that overwhelms
informal care or does not fit easily
within the bulk of formal care
structures. Additionally, otherwise
healthy older adults who need reha-
bilitative care after a health shock
may face a trajectory of declining
functioning and dependence if they
fail to receive the care. These indi-
viduals, and often their families,
need viable alternate types of care
such as rehabilitative, palliative,
respite, or end-of-life care options.
Further yet, a secular trend in
higher-income countries has seen a
steady increase in the proportion of
deaths at home (Gomes, Calanzani,
and Higginson, 2012). In these
cases in particular, health promo-
tion and universal care systems
require enough breadth to incor-
porate the idea of a good death
(Kelly et al., 2009; Rumbold, 2011;
Prince, Prina, and Guerchet, 2013;
Davies et al., 2014).
82 An Aging World: 2015 U.S. Census Bureau
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CHAPTER 6.
Work and Retirement
For many individuals, the transi-
tion from work to retirement marks
one of the most significant changes
that they will experience in their
lifetime. Increasingly, this transition
occurs in stages and may involve
multiple entries into and out of the
labor force. While labor force par-
ticipation declines as people age,
rates vary by sex and by level of
economic development. Evidence
suggests that the gap is narrow-
ing between men and women and
across countries.
Workers formulate expectations
about their lives after retirement
but may find that circumstances
beyond their control, such as
official retirement ages and eco-
nomic cycles, affect their retire-
ment decisions. The recent Great
Recession of 2007–2009 led some
workers to delay retirement or to
come out of retirement and rejoin
the labor force while others retired
earlier than planned (Burtless and
Bosworth, 2013). In addition to
the economic, psychological, and
physical implications for indi-
viduals transitioning from work to
retirement, there may be aggregate
effects on the overall economy
and society. As traditional family
support erodes, new institutions
emerge to address the needs of
the older population. In addition,
how workers prepare for a longer
retirement period due to increased
life expectancy has implications for
economic growth.
LABOR FORCE
PARTICIPATION RATES
VARY SHARPLY BY AGE
AND SEX
The labor force is commonly
defined to include those who
are either employed or seeking
employment. Typically, those who
perform unpaid work within a
household are not considered to
be part of the labor force, even
though such work clearly has value
and would be expensive to replace
(Schultz, 1990). Those who want to
work but have given up searching
for a job (“discouraged workers”)
are also considered to be out of the
labor force.
The size of the labor force reflects
not only economic conditions but
also demographic factors, such as
the total population size and the
age distribution of the population.
For cross-country and cross-group
comparisons, a more useful indica-
tor is the labor force participation
rate, which is the proportion of any
particular population that is in the
labor force.
For the countries shown in Table
6-1, labor force participation rates
in 2012 for men aged 45 to 49
were quite high—exceeding 90 per-
cent in most countries. In general,
the rates decline slightly for the
next older group aged 50 to 54.
Rates continue to decline for each
successively older age group. By
ages 60 to 64, labor force par-
ticipation rates were less than half
the level for those aged 45 to 49
in countries such as South Africa,
Tunisia, Italy, Russia, and Ukraine.
For men aged 65 and older, only
two countries had participation
rates exceeding 50 percent—
Zambia and Guatemala. In Germany
and Italy, rates were less than 10
percent for older males.
For all countries in Table 6-1 labor
force participation rates for women
aged 45 to 49 were lower than
those of their male counterparts,
although the gap was quite small
in Russia and Ukraine. Less than
one third of women aged 45 to 49
in Morocco and Tunisia were in the
labor force. Similar to the trend
for men, labor force participation
rates for women decline at older
age groups. For women aged 65
and older, participation rates were
below 20 percent in all countries
except Zambia (52.2 percent) and
South Korea (23.0 percent).
92 An Aging World: 2015 U.S. Census Bureau
Table 6-1.
Labor Force Participation Rates by Age and Sex in Selected Countries: 2012
(In percent)
Country
Men Women
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Africa
Morocco ................ 95.3 89.1 79.8 51.1 28.7 31.6 31.2 27.9 19.2 8.5
South Africa ............. 82.6 75.6 66.1 31.8 N 62.1 54.3 42.9 18.7 N
Tunisia ................. 94.1 88.2 70.1 34.4 15.4 23.5 16.6 11.5 4.8 1.9
Zambia ................. 96.9 96.8 88.9 89.6 71.2 84.1 84.3 77.8 74.3 52.2
Asia
Japan .................. 96.1 95.0 92.2 75.4 28.7 75.7 73.4 64.6 45.8 13.4
Malaysia ............... 96.9 92.5 76.8 57.4 N 55.3 48.3 34.6 21.2 N
Singapore .............. 95.6 93.8 88.5 74.6 32.4 73.4 65.6 56.2 41.7 13.7
South Korea ............. 93.0 91.4 84.7 72.3 41.6 67.7 62.5 54.8 43.9 23.0
Europe
Germany ............... 93.9 91.6 85.7 58.9 7.1 85.3 81.9 73.3 41.1 3.3
Italy ................... 91.6 89.5 74.1 32.7 6.2 66.7 61.3 48.4 15.9 1.4
Russia ................. 92.6 88.7 77.8 38.5 14.1 90.6 84.3 52.9 24.9 8.9
Ukraine ................ 85.2 78.2 66.7 32.2 20.5 83.2 73.5 34.7 25.9 16.7
Latin America/Caribbean
Argentina ............... 94.6 91.4 86.8 75.7 22.2 67.7 63.4 53.8 33.7 7.5
Brazil .................. 91.6 86.1 78.2 62.0 30.0 67.4 58.8 45.5 30.0 11.7
Costa Rica .............. 94.0 92.0 85.8 67.5 26.5 55.0 50.3 39.8 27.3 6.8
Guatemala .............. 96.2 96.5 92.9 90.0 66.4 56.0 51.8 44.7 36.3 15.0
Mexico ................. 94.9 91.8 85.4 71.5 42.8 55.4 50.2 41.5 32.8 15.5
Northern America
Canada ................ 89.9 87.8 78.9 58.0 17.1 84.4 80.9 69.4 45.7 8.8
United States ............ 88.1 84.1 78.0 60.5 23.6 75.6 73.7 67.3 50.4 14.4
Oceania
Australia ................ 89.2 86.7 80.0 62.6 16.8 78.5 76.3 65.7 44.5 7.8
New Zealand ............ 91.5 90.9 88.2 77.6 25.5 82.3 82.8 77.4 64.1 15.0
N Not available.
Note: For historical time series of labor force participation in these and other countries, see Appendix Table B-8.
Source: International Labour Organization, 2014; ILOSTAT Database.
OLDER POPULATION
IN HIGHER INCOME
COUNTRIES LESS LIKELY TO
BE IN LABOR FORCE
Sharp differences in labor force
participation at ages 65 and above
exist among regions of the world
(Figure 6-1). In 2010, older African
men and women both had the
highest rates of labor force par-
ticipation—more than 50 percent
for men and over 30 percent for
women. At the other end of the
scale, in Europe, less than 10
percent of older men and less than
5 percent of older women were in
the labor force. Clearly, the vast
majority of the older population
in Europe spends their time on
pursuits other than work. Europe’s
relatively low labor force par-
ticipation rates are likely due to its
substantial economic resources,
policies that encourage early
retirement, and patterns of public
spending that provide security for
the older population (World Bank
Group, 2014).
In addition to substantial varia-
tion in labor force participation
across world regions, there are
sometimes large differences among
countries within the same region.
In Africa, for instance, labor force
participation of the older popula-
tion in 2011 was below 15 percent
in Algeria, South Africa, Egypt, and
U.S. Census Bureau An Aging World: 2015 93
Figure 6-1.
Labor Force Participation Rates for Population Aged 65 and Over
by Sex and World Region: 2010 Estimate and 2020 Projection
Source: International Labour Organization, 2011; LABORSTA.
Percent
Male
010 20 30 40 50 60
2020
2010
2020
2010
2020
2010
2020
2010
2020
2010
2020
2010
2020
2010
Oceania
Northern
America
Latin
America
and the
Caribbean
Europe
Asia
Africa
World
(191 countries)
Female
94 An Aging World: 2015 U.S. Census Bureau
Figure 6-2.
Labor Force Participation Rates for Population Aged 65 and Over for Selected
African Countries: 2011
Source: The World Bank, 2013; World DataBank.
0 10 20 30 40 50 60 70 80 90 100
Algeria
South Africa
Egypt
Tunisia
Libya
Mali
Somalia
Morocco
Sudan
Botswana
Niger
Angola
Liberia
Senegal
Nigeria
Ethiopia
Kenya
Rwanda
Cote d'Ivoire
Uganda
Tanzania
Zimbabwe
Central African
Republic
Mozambique
Malawi
Percent
Tunisia, and more than 70 percent
in Malawi, Mozambique, the Central
African Republic, and Zimbabwe
(Figure 6-2).
In general, countries with higher
incomes per capita and more
developed social security systems
tend to have lower labor force
participation among the older
population. In contrast, in lower
income countries, the notion of
retirement may not make sense—
the older population may need
to continue to work, perhaps at a
reduced level, until physically or
mentally unable to do so.
The causal relationships between
labor force participation and eco-
nomic development are often com-
plex. While developmental factors
may lead to rises in female labor
force participation, those employ-
ment patterns in turn contribute
to economic development. As
noted earlier, a key reason for the
U.S. Census Bureau An Aging World: 2015 95
difference by sex concerns tradi-
tional norms about the division of
labor between males and females.
GENDER GAP IN LABOR
FORCE PARTICIPATION
RATE IS NARROWING
Globally, the gender gap in labor
force participation narrowed in the
1990s (decreasing by 1.8 percent-
age points) and then held constant
in the 2000s (International Labour
Organization, 2012). Female labor
force participation tends to be
greater in more developed societ-
ies, among women less accepting
of traditional norms regarding the
division of labor between males
and females, and among those
with certain demographic charac-
teristics, such as fewer children
(Contreras and Plaza, 2010).
Female labor force participation
at older ages may also reflect a
gradual change in the perceived
value of wage earnings as
subsequent cohorts realize the
benefits of working longer
(Fernandez, 2013).
Table 6-2 shows the difference
in labor force participation rates
between men and women aged
65 and over for 34 countries in
the 1990s and in 2012. West
European countries had some of
the smallest gaps between men
and women (less than 5 percent-
age points) in the 1990s, while
Table 6-2.
Gender Gap in Labor Force Participation Rates for
Population Aged 65 and Over by Country: 1990s and 2012
(Percentage point difference)
Country 1990s 2012
France ....................... 0.3 1.5
Belgium ...................... 1.2 2.9
Austria ....................... 2.4 3.8
Germany ..................... 2.8 3.8
Russia ....................... 3.9 5.2
United Kingdom ................ 3.9 5.8
Italy ......................... 4.2 4.7
Mozambique .................. 4.2 6.4
Czech Republic ................ 4.5 3.5
Australia ...................... 6.5 9.0
New Zealand .................. 6.5 10.5
Denmark ..................... 6.7 6.1
Poland ....................... 6.8 4.7
Sweden ...................... 7.0 7.8
United States .................. 7.2 9.2
Greece ....................... 7.3 3.0
Canada ...................... 8.8 8.3
Israel ........................ 11.8 14.4
Uruguay ...................... 12.7 14.0
Zimbabwe .................... 13.4 9.6
Singapore .................... 14.4 18.7
Argentina ..................... 18.7 14.7
South Korea ................... 18.8 18.6
Turkey ....................... 20.3 13.7
Japan ........................ 20.6 15.3
Chile ........................ 20.9 22.9
Peru ......................... 21.9 20.8
Philippines .................... 24.7 21.8
Jamaica ...................... 28.0 38.2
Egypt ........................ 29.8 19.1
Tunisia ....................... 30.5 13.5
Mexico ....................... 37.9 27.3
Guatemala .................... 42.6 51.4
Pakistan ...................... 45.3 31.0
Note: Gender gap is male labor force participation rate minus female labor force participation rate.
Sources: International Labour Office, 2007, 2014; LABORSTA, ILOSTAT Database.
Guatemala and Pakistan had the
largest gaps at 42.6 percentage
points and 45.3 percentage points,
respectively. By 2012, the gender
gap had increased for 18 of the
countries and decreased for 16
countries compared to an earlier
year in the 1990s. The gap wid-
ened in Guatemala, rising to 51.4
percentage points, and narrowed in
Pakistan, dropping to 31.0 percent-
age points.
LABOR FORCE
PARTICIPATION AMONG
THE OLDER POPULATION
CONTINUES TO RISE
IN MANY DEVELOPED
COUNTRIES
The size of the workforce relative
to the number of pensioners can
have major implications for eco-
nomic growth and the sustainabil-
ity of old age security programs.
From the 1950s to the mid-1980s,
an increasing share of older men
exited the labor force in most
developed countries. Beginning
in the 1990s, this trend reversed
(Kinsella and He, 2009). Labor force
participation rates for older men
have continued to increase through
the 2000s in many developed
countries. Older women in these
countries also experienced a rise in
economic activity over the past 2
decades.
A variety of factors have contrib-
uted to this increase, including
uncertainty about the sufficiency
and viability of public pension
systems, increased reliance on
defined contribution pension
schemes, higher eligibility ages for
retirement benefits, and changing
social norms favoring a later exit
from the labor force (Friedberg
and Webb, 2005; van Dalen et al.,
2010; Hurd and Rohwedder, 2011;
Skugor, Muffels, and Wilthagen,
2012; Hasselhorn and Apt, 2015).
All of these changes are driven to
some extent by the fact that people
96 An Aging World: 2015 U.S. Census Bureau
Percent
2012
Percent
1990s
Sources: International Labour Office, 2007, 2014; LABORSTA, ILOSTAT Database.
Figure 6-3.
Labor Force Participation Rates for Men Aged 65 and Over in More Developed
Countries: 1990s and 2012
United States
Japan
New Zealand
Greece
Poland
Russia
Australia
Sweden
United Kingdom
Canada
France
Italy
Belgium
Germany Austria
Czech Republic
Denmark
06 12 18 24 30 36
0
6
12
18
24
30
36
are living longer. For example,
unless retirement ages rise along
with increased life expectancy,
societies will bear the extra cost of
a longer period of retirement (The
Economist, 2011). This is especially
the case in countries where old age
security systems are based on pay-
as-you-go (PAYGO) financing, which
requires payroll deductions from
current workers to provide benefits
to current retirees.
Although the factors mentioned
above tend to encourage later
retirement ages, there are also
countervailing factors contribut-
ing to an individual’s retirement
decision, which can be complex
and hard to predict. Employment
participation is affected by individ-
ual level factors (such as personal
and family health and personal
financial resources), work place
factors (such as physical demands
of job and changing required skill
set), and macro level factors (such
as the economic growth rate,
retirement and pension policy, and
changes in information and com-
munication technologies).
The change in labor force par-
ticipation rates at ages 65 and
above between the 1990s and
2012 is illustrated on Figure 6-3
(males) and Figure 6-4 (females) for
selected more developed countries.
Countries that fall on the diagonal
experienced no change in labor
force participation rates. For both
men and women, most countries
are below the diagonal, reflecting
an increase in labor force participa-
tion. Among countries experiencing
a decline in participation rates for
older men were Greece, Japan, and
Poland. Countries with the largest
increases in participation rates for
both older men and older women
included Australia, New Zealand,
Sweden, and the United States.
U.S. Census Bureau An Aging World: 2015 97
In countries with high employment
in the primary sector (agriculture
and mining), participation rates
often remain high at older ages.
When the scale of agriculture is
small with a large share engaged
in subsistence farming, family
members often continue to work
into their 60s and beyond out of
economic necessity. As econo-
mies develop and the service and
industry sectors expand and
pension eligibility increases, the
labor force participation rate of the
older population typically declines
from previous levels (Reddy, 2014;
Samorodov, 1999).
Among less developed countries
shown in Figures 6-5 and 6-6, more
experienced declines in labor force
participation rates than experi-
enced increases from the 1990s
to 2012. Substantial differences
exist in participation rates between
more developed countries and less
developed countries. For example,
older males had labor force partici-
pation rates that exceeded 50 per-
cent in 2012 in six less developed
countries (Guatemala, Jamaica,
Mozambique, Peru, Philippines,
and Zimbabwe) displayed in Figure
6-5 but did not reach this rate in
any more developed countries
shown in Figure 6-3. Labor force
participation rates for older women
exceeded 50 percent in two less
developed countries (Mozambique
and Zimbabwe) shown in Figure 6-6
but did not come close to this rate
in any of the more developed coun-
tries included in Figure 6-4.
Demographic forecasts of labor
force participation rates among
older adults are typically based
upon recent trends, such as those
implied by Figures 6-3 to 6-6.
Forecasts by the International
Labour Organization (2011) imply
an increase in labor force par-
ticipation for the older population
Sources: International Labour Office, 2007, 2014; LABORSTA, ILOSTAT Database.
Figure 6-4.
Labor Force Participation Rates for Women Aged 65 and Over in More Developed
Countries: 1990s and 2012
United States
Japan
New Zealand
Greece
Poland
Russia
Australia Sweden
United Kingdom
Canada
France
Italy
Belgium Germany
Austria
Czech Republic
Denmark
06 12 18 24 30 36
0
6
12
18
24
30
36
Percent
2012
Percent
1990s
98 An Aging World: 2015 U.S. Census Bureau
Notes: The earlier year for Singapore is 2000. The later year for Pakistan and Zimbabwe is 2011 and for China, Jamaica, and
the Philippines is 2010.
Sources: International Labour Office, 2007, 2014; LABORSTA, ILOSTAT Database.
Figure 6-5.
Labor Force Participation Rates for Men Aged 65 and Over in Less Developed
Countries: 1990s and 2012
Zimbabwe
Mozambique
Philippines
Tunisia
Egypt
Pakistan
Turkey
Israel Singapore
South Korea
Uruguay
Jamaica
Guatemala
Mexico
Argentina Chile
Peru
China
010 20 30 40 50 60 70 80 90
0
10
20
30
40
50
60
70
80
90
Percent
2012
Percent
1990s
(both men and women) between
2010 and 2020 in more developed
regions such as Oceania, Northern
America, and Europe (see Figure
6-1).1 In contrast, labor force
participation rates in Africa, which
are currently the world’s highest,
are expected to continue a gradual
1 The International Labour Organization
(2011) generates projections of the economi-
cally active population using a three-step
procedure, including application of extrapola-
tion methods, changes in the business cycle,
and judgement adjustments to achieve con-
sistency across gender and age groups. The
adjustments are based on the share of the
population aged 0–14 and aged 55 and over,
the share of the female population in total
population, share of immigrant workers in the
country, forthcoming changes in retirement
and preretirement schemes, other relevant
policy or legal changes, and HIV prevalence.
decline through 2020 for both
men and women. In Asia and Latin
America and the Caribbean, the
direction of projections is mixed.
In Asia, rates for older men are
projected to decline while rates for
older women are expected to hold
steady. In Latin America and the
Caribbean, older men are projected
to see a slight decline while older
women will see an increase.
Increases in labor force participa-
tion rates in more developed coun-
tries are not confined to the older
population. Among 12 European
countries and the United States,
participation rates increased for
those aged 55 to 64 from 2001
to 2011 for all countries except
Portugal (Table 6-3). For the group
aged 65 to 69, rates increased
over the same period in all coun-
tries except Greece, Poland, and
Portugal. Increasing labor force par-
ticipation rates among the group
aged 55 to 64 may suggest future
increases in participation rates for
the older population.
SHARE OF THE OLDER,
EMPLOYED POPULATION
WORKING PART-TIME
VARIES ACROSS COUNTRIES
The labor force includes those who
are working (or seeking to work)
full-time or part-time. Among older
U.S. Census Bureau An Aging World: 2015 99
Notes: The earlier year for Singapore is 2000. The later year for Pakistan and Zimbabwe is 2011 and for China, Jamaica, and
the Philippines is 2010.
Sources: International Labour Office, 2007, 2014; LABORSTA, ILOSTAT Database.
Figure 6-6.
Labor Force Participation Rates for Women Aged 65 and Over in Less Developed
Countries: 1990s and 2012
Zimbabwe
Mozambique
Philippines
Tunisia
Egypt
Pakistan
Turkey
Israel Singapore
South Korea
Uruguay
Jamaica
Guatemala
Mexico
Argentina
Chile
Peru
China
0 10 20 30 40 50 60 70 80 90
0
10
20
30
40
50
60
70
80
90
Percent
2012
Percent
1990s
workers, part-time work may be
attractive for a variety of reasons.
Part-time work can provide older
workers a stream of income and
allow them to maintain social con-
nections with colleagues without
the daily demands of full-time
work. Part-time arrangements may
be especially attractive for older
workers who are already receiving
a pension or have other financial
resources, which allow them to
sequentially step away from the
workforce (Hannon, 2014). In
general, part-time work is more
common among older women than
older men.
Table 6-3.
Labor Force Participation Rates for Older Workers in
Selected Countries: 2001 and 2011
(In percent)
Country Aged 55 to 64 Aged 65 to 69
2001 2011 2001 2011
Belgium ............... 25.2 38.7 2.4 3.5
Czech Republic ......... 37.1 47.6 7.6 9.3
Denmark .............. 56.5 59.5 12.2 13.5
Finland ................ 45.9 57.0 5.3 11.8
France ................ 30.7 41.4 2.1 5.3
Germany .............. 37.9 59.9 5.4 10.1
Greece ................ 38.0 39.4 10.3 8.6
Ireland ................ 46.9 50.8 14.8 16.8
Netherlands ............ 37.3 56.1 5.6 11.4
Poland ................ 29.0 36.9 10.8 9.4
Portugal ............... 50.2 47.9 27.8 21.9
Spain ................. 39.2 44.5 3.9 4.5
United States1 .......... 61.9 64.3 26.1 32.1
1 Data for the United States is for 2002 and not 2001.
Sources: Kritzer, 2013; Bureau of Labor Statistics, 2013.
100 An Aging World: 2015 U.S. Census Bureau
Figure 6-7.
Employment Status of Employed Men Aged 65 and Over by Country: 2013
0 10 20 30 40 50 60 70 80 90 100
South Africa
Greece
Latvia
Russia
Spain
United States
Israel
Estonia
Italy
Mexico
Hungary
South Korea
Chile
Turkey
Slovakia
Ireland
Canada
Czech Republic
New Zealand
Japan
Poland
Norway
Australia
Slovenia
Denmark
France
United Kingdom
Finland
Portugal
Austria
Sweden
Belgium
Germany
Luxembourg
Netherlands
Note: Part-time employment is less than 30 usual hours for main job.
Source: Organisation for Economic Co-operation and Development, 2014; OECD Stat.
Percent
Part-timeFull-time
Figures 6-7 and 6-8 show the
employment status of older,
employed men and women,
respectively, in a selection of 35
countries. Across these countries,
women account for 33 percent
of older workers employed full-
time and 49 percent of older
workers employed part-time in
2013 (Organisation for Economic
Co-operation and Development,
2014). Among the older, employed
population of men, the propor-
tion engaged in part-time work
as of 2013 ranged from under
20 percent in Greece, Latvia,
Russia, and South Africa to over
60 percent in Belgium, Germany,
Luxembourg, the Netherlands,
and Sweden (Figure 6-7). Overall,
employed women aged 65 and
over showed higher proportions
engaged in part-time work than
older, employed men (Figure 6-8).
Among the same set of countries,
the proportion of older female
workers employed part-time was
less than 20 percent in Greece only
and exceeded 60 percent in 11
countries.
The frequency of part-time employ-
ment among the older population
U.S. Census Bureau An Aging World: 2015 101
Figure 6-8.
Employment Status of Employed Women Aged 65 and Over by Country: 2013
0 10 20 30 40 50 60 70 80 90 100
Greece
Latvia
Russia
South Africa
United States
Spain
South Korea
Italy
Estonia
Turkey
Mexico
Chile
Hungary
Slovenia
Japan
Czech Republic
Poland
Israel
Canada
Norway
France
Luxembourg
Denmark
Slovakia
New Zealand
Australia
Portugal
Finland
Belgium
Ireland
Sweden
Austria
United Kingdom
Germany
Netherlands
Note: Part-time employment is less than 30 usual hours for main job.
Source: Organisation for Economic Co-operation and Development, 2014; OECD Stat.
Percent
Part-timeFull-time
is also related to the willingness of
employers to allow part-time work.
In a survey of 16 countries, the pro-
portion of employees saying that
their employer provided the option
of part-time work to phase into
retirement ranged from a high of
30 to 31 percent in Germany, India,
and Sweden to a low of 16 to 17
percent in Japan and Spain (Aegon,
2014). On the other hand, some
older workers may prefer to work
full-time but can only find part-time
employment.
While Greece showed very low
reliance on part-time work among
the older employed population,
the labor force participation rate of
older Greeks is among the lowest in
the world. The large proportion of
older employees working full-time
may indicate that when Greek retir-
ees exit the labor force they do so
without any sequential step-down
to part-time work. Access to gener-
ous pensions at retirement may
allow more Greek workers to enter
total retirement once reaching age
55 for public sector workers and
age 60 for private sector workers
(Mylonas and de la Maisonneuve,
1999; Organisation for Economic
102 An Aging World: 2015 U.S. Census Bureau
Figure 6-9.
Unemployment Rate for Men and Women Aged 65 and Over by Country:
2005 and 2013
Source: Organisation for Economic Co-operation and Development, 2014; OECD Stat.
3.4
3.5
3.4
3.6
1.3
0.9
7.4
10.8
1.7
0.4
1.0
4.7
7.1
4.3
0.5
3.6
1.3
2.5
1.7
1.4
4.0
11.8
0.7
1.0
0.6
3.4
4.7
2.8
5.8
1.0
1.7
1.4
0.8
1.0
1.7
Men
Women
2005 2013
United
States
United
Kingdom
Sweden
Spain
South
Korea
Slovakia
Russia
Mexico
Japan
Hungary
Greece
Germany
Czech
Republic
Colombia
Chile
Australia
(In percent)
1.2
1.7
1.7
2.1
5.6
4.5
5.8
1.0
1.2 2.0
1.2
2.2
3.0
1.2
2.3
2.6
4.7
3.0
1.6
6.4
1.5
6.2
1.3
2.7
3.3
0.7
5.5
5.1
3.1
0.8
0.7
Co-operation and Development,
2007). The reluctance of Greek
employers to offer part-time work
could also be a partial explanation
for the rarity of part-time employ-
ment (van Dalen et al., 2010).
UNEMPLOYMENT PATTERNS
VARY ACROSS SEXES AND
OVER TIME
Assessing levels and trends in
unemployment rates of older
people is challenging for multiple
reasons, including lack of data
availability, the nature of the busi-
ness cycle, and definition differ-
ences across countries. Economic
upheavals may sometimes affect
unemployment patterns across
countries. A case study of the
recent Global Recession of 2007–
2009 and its impact on unem-
ployment patterns and retirement
patterns appears in Box 6-1. During
economic downturns, older work-
ers may choose to retire rather
than remain unemployed for an
extended period even though their
preference is to remain in the labor
force. At the same time, some older
workers may delay their retirement
to recover financially from the
recession.
One comparison of 16 countries
shows that unemployment lev-
els and patterns vary by coun-
try and timing relative to the
Great Recession of 2007–2009
(Figure 6-9). For instance, the
U.S. Census Bureau An Aging World: 2015 103
Figure 6-10.
Unemployment Rate for Men and Women Aged 55 to 64 and Over by Country:
2005 and 2013
Source: Organisation for Economic Co-operation and Development, 2014; OECD Stat.
3.5
3.4
2.5
3.3
3.3
3.3
7.5
11.6
10.6
5.4
5.7
1.1
4.7
12.0
13.0
4.3
0.5
5.0
2.7
3.1
1.6
13.8
13.1
3.3
1.0
6.3
6.3
4.5
5.8
3.0 4.3
2.9
3.7
1.7
Men
Women
2005 2013
United
States
United
Kingdom
Sweden
Spain
South
Korea
Slovakia
Mexico
Japan
Hungary
Greece
Germany
Czech
Republic
Colombia
Chile
Australia
(In percent)
5.6
4.3
5.8
8.6
1.2 2.0
16.4
15.9
4.4
2.8
5.0
7.5
2.9
1.2 2.8
3.0
6.4
5.8
6.1
19.7
20.3
4.2
3.2
5.5
3.8
5.4
5.4
5.2
1.4 3.6
0.7
unemployment rate for older men
was higher than for older women
in both 2005 and 2013 in Chile,
Colombia, Japan, Mexico, South
Korea, and the United Kingdom,
but the opposite was the case for
Czech Republic, Germany, Hungary,
and Sweden. Older men were more
likely to face an increase in the
unemployment rate from 2005 to
2013 than older women (unem-
ployment rates rose in 11 of the 16
countries for men but declined for
women in 9 of the 16 countries).
The labor force aged 55 to 64 is
approaching retirement and their
unemployment status can affect the
financial security of future retirees;
therefore, it is worthwhile to exam-
ine this cohort as well. Estimates
of the unemployment rate also are
likely to be more robust for this age
group. Among the same 16 coun-
tries, men aged 55 to 64 tended to
have higher unemployment rates
than women aged 55 to 64 (Figure
6-10). Unemployment rates were
substantially higher for both men
and women aged 55 to 64 in 2013
compared to 2005 for Greece and
Spain. On the other hand, unem-
ployment rates dropped notably
in 2013 compared to 2005 for
both men and women in this same
cohort in Germany.
104 An Aging World: 2015 U.S. Census Bureau
Box 6-1.
Impact of the Great Recession on the Older Population
World markets experienced a general economic decline during the 2007 to 2009 period. While only a portion of
the world’s countries saw negative growth rates for gross domestic product (GDP) during this time, many other
countries faced slowdowns in their economic growth. In the United States, for example, a recession officially
began in December 2007 and ended in June 2009. Nearly all member countries of the European Union also went
into recession around the same time. China and India, on the other hand, did not enter recession but did experi-
ence slowing economic growth (Bernanke, 2009). In addition, countries whose economies were less integrated
with the world economy through trade or financial markets, such as many countries in Africa, were less directly
affected. The International Monetary Fund estimated that real world GDP per capita (in purchasing power parity
terms) declined in 2009 and stated that the world economy was experiencing a “Great Recession” more severe
than at any time since the end of World War II (International Monetary Fund, 2009).
The recession originated in the United States after a sharp decline in housing prices triggered defaults on sub-
prime mortgages, the financial fallout from which spread to other parts of the world (International Monetary Fund,
2009). The recession was characterized by rising unemployment as well as falling prices of housing, commodi-
ties, and other investments. To what extent did the recession affect the older population and have any effects
lingered?
The unemployment rates over the 2000 to 2013 period for four countries—Portugal, South Korea, United
Kingdom, and United States—help illustrate the diverse impact of the Great Recession (Figure 6-11).
Unemployment in the United States at ages 65 and over more than doubled between 2006 and 2010—from 2.9
to 6.7 percent, an increase of nearly 4 percentage points—before starting a slow decline and reaching 5.3 percent
in 2013. The older labor force in South Korea and Portugal also saw a rise in unemployment levels following 2006
but at levels below those of the United States. However, while the unemployment rate peaked in 2010 for South
Korea, the peak did not occur until 2012 in Portugal. In the United Kingdom, unemployment rates fluctuated
around 2 percent over the entire 2000 to 2013 period for the older population. While unemployment rose for the
older population, they were lower than the rates of younger adults (aged 25 to 54) in each of the four countries.
South Korea did not experience sharp fluctuations in unemployment for the population aged 25 to 54 through-
out the period. Unemployment rates among younger adults largely flattened in the United Kingdom after 2009
and continued to rise in Portugal after 2008, reaching 15.5 percent in 2013. The lack of notable improvement
in unemployment rates in Portugal and the United Kingdom likely reflect the subsequent public debt crisis and
implementation of austerity measures in Europe, in contrast to a decline in U.S. unemployment after 2010.
The retirement plans and wealth of the older population in the countries most impacted by the Great
Recession were also affected by the declines in asset prices—in particular housing and financial investments.
In Denmark, Ireland, the Netherlands, and Spain, for example, real housing prices declined by 25 percent or more
(International Monetary Fund, 2015). In the United States, housing prices also declined although older Americans
tended to have greater equity accumulated prior to the housing collapse than did younger home owners (West et
al., 2014). One study focused on American preretirees aged 53 to 58 in 2006 found that their net housing wealth
declined by 23 percent in real terms between 2006 and 2010, although their total wealth declined only 2.8 per-
cent from 2006 to 2010 (Gustman, Steinmeier, and Tabatabai, 2012).
While the Great Recession had a major impact on unemployment rates even among the older population, the
trend of rising labor force participation rates among people aged 60 and older in more developed countries was
not halted. A study of 20 Organisation for Economic Co-operation and Development (OECD) member countries
found that the average rate of increase in labor force participation for those in the groups aged 60 to 64, 65 to
Continued on next page.
U.S. Census Bureau An Aging World: 2015 105
69, and 70 to 74 accelerated in more than half of the 20 countries since the onset of the Great Recession (Burtless
and Bosworth, 2013). The trend of a labor force participation rate increase for workers aged 60 and over slowed
significantly in only three of the 20 countries—Greece, Portugal, and Ireland—countries that experienced particu-
larly severe recessions (ibid). Overall, the Great Recession motivated some older workers to postpone retirement
and drew others back into the labor force.
Lastly, given the many modifications to world social security systems observed between 2008 and 2013
(Organisation for Economic Co-operation and Development, 2013), one may ask whether the Great Recession pro-
vided a catalyst for such changes. The answer is not entirely straightforward. Many social security systems were
quite generous and financially unsustainable before the Great Recession and likely in need of reform even if the
recession had not occurred (Capretta, 2007). However, the Great Recession may have contributed to the substan-
tial reform packages introduced in OECD countries and helped to revise thinking about who should be covered
and what is affordable (Organisation for Economic Co-operation and Development, 2013).
Note: For example, the labor force participation rate of 65- to 69-year-olds increased at an average rate of 0.1
percentage point per year between 1989 and 2007 but at an average rate of 0.8 percentage point a year between
2007 and 2012 for the 20 sample countries.
Figure 6-11.
Unemployment Rates for Population Aged 25 to 54 and Aged 65 and Over for
Portugal, South Korea, United Kingdom, and United States: 2000 to 2013
Source: Organisation for Economic Co-operation and Development, 2014; OECD Stat.
0
2
4
6
8
10
12
14
16
20132012201120102009200820072006200520042003200220012000
Percent
Portugal 25 to 54
Portugal 65+
United States 65+
United Kingdom 25 to 54
United Kingdom 65+
United States 25 to 54
South Korea 25 to 54
South Korea 65+
106 An Aging World: 2015 U.S. Census Bureau
Figure 6-12.
Work Plans After Retirement by Workers and Retirees for Selected Countries: 2013
Notes: The question for workers was "Looking ahead, how do you envision your transition to retirement?" The question for retirees was
"Looking back, how did your transition to retirement take place?"
Source: Aegon, 2013.
FranceSpainHungaryGermanySwedenPolandNether-
lands
United
Kingdom
ChinaJapanUnited
States
CanadaAll
respondents
Current retirees selecting "I immediately stopped working altogether and entered full retirement."
Current workers selecting "I will immediately stop working altogether and enter full retirement."
(In percent)
34
57
22
59
25
59
49
74
43
58
45
39
24
44
31
51
36
51 48
68
67
38
28
23
54
64
EXPECTATIONS AND
REALITIES—MANY
WORKERS UNCERTAIN
ABOUT THEIR LIFESTYLE
AFTER RETIREMENT AND
MANY RETIRE EARLIER
THAN EXPECTED
In the transition from work to
retirement, some workers prefer
a gradual “step down” to retire-
ment, while others wish to move
from full-time employment imme-
diately into full-time retirement.
Increasingly, the gradual transi-
tion model is being preferred by
workers in developed countries
(Hasselhorn and Apt, 2015). One
survey of 12 countries found
potential differences between
expectations of workers and reali-
ties experienced by retirees in 2013
(Figure 6-12). A minority of workers
(34 percent) in these 12 countries
said they planned to stop working
altogether and enter full retirement.
Such expectations contrast with the
realities of current retirees, among
whom 57 percent stopped working
entirely after retirement.
These discordant findings likely
reflect unforeseen circumstances
that individual retirees often
encounter, such as health problems
that preclude further work even
on a part time basis or favorable
financial circumstances that allow
them to avoid it (Aegon, 2013).
The discordancy may also reflect
the cohort difference between cur-
rent workers and current retirees.
Thus, if current workers expect an
increasingly tenuous future for pub-
lic social security systems or simply
want to continue working to later
ages, their plans to continue work-
ing part-time may differ from that
of current retirees (Organisation
for Economic Co-operation and
Development, 2013).
U.S. Census Bureau An Aging World: 2015 107
Workers’ preferences for when to
retire and which transition model
to follow are influenced by their
expected financial security in retire-
ment. Workers around the world
express varying opinions about
how comfortable they expect their
lifestyle will be upon retirement.
Among the 12 countries included in
the Aegon (2013) survey, workers
in Canada and China seemed to be
more optimistic (low proportions
who lack confidence about having
a comfortable lifestyle in retire-
ment), whereas about two-thirds or
more in France, Hungary, Poland,
and Spain were not confident about
achieving a comfortable lifestyle in
retirement (Figure 6-13).
Such differing opinions likely
reflect circumstances specific to
each country as well as subjective
interpretations about what exactly
would constitute a comfortable
lifestyle in retirement. Confidence
about a comfortable retirement
may also be related to the gen-
eration that each cohort was born
into, including the circumstances
Figure 6-13.
Workers Who Are Not Confident About Having A Comfortable Lifestyle in
Retirement by Country: 2013
Notes: The question was "Overall, how confident are you that you will be able to fully retire with a lifestyle you consider comfortable?"
Not confident includes those responding “not at all confident” or “not very confident.”
Source: Aegon, 2013.
PolandHungarySpainFranceJapanUnited
Kingdom
SwedenNether-
lands
GermanyUnited
States
CanadaChinaAll
respondents
(In percent)
33
57
20
52
41
74
45
85
66
50
49
40
65
108 An Aging World: 2015 U.S. Census Bureau
Figure 6-14.
Workers' Expectations Regarding
Standard of Living in Retirement in
the United States by Generation: 2014
Notes: The question was "Do you expect your standard of living to increase, decrease,
or stay the same when you retire?"
Millennials—born 1979–1996, Generation X—born 1965–1978, and Baby Boomer—born
1946–1964.
Source: Transamerica Center for Retirement Studies, 2014.
Increase
Stay the same
Decrease
Not sure
0
10
20
30
40
50
60
70
80
90
100
Baby BoomerGeneration XMillennials
Percent
encountered at primary working
ages as well as those encountered
(or envisioned) at retirement. In the
United States, the Baby Boom gen-
eration (born between mid-1946 to
1964), which is already in retire-
ment or closest to it, seemed more
pessimistic about their standard of
living after retirement, while the
younger generation of Millennials
seemed more optimistic (Figure
6-14). Such differences might sim-
ply reflect intergenerational differ-
ences of hope and experience—the
challenges foreseen during retire-
ment may seem easiest to resolve
by those furthest from it.
STATUTORY RETIREMENT
AGES VARY WIDELY ACROSS
WORLD REGIONS, YET TEND
TO LUMP AT CERTAIN AGES
When workers are asked to evalu-
ate their prospects upon retire-
ment, one of the first concerns an
individual may have is the age at
which s/he will qualify for a public
pension. The statutory retirement
age for social security programs
varies widely across the world
(Figure 6-15), reflecting any num-
ber of local factors, such as life
expectancy and available budgets.
Among many other considerations,
it is often claimed that increases
in the official retirement age will
result in more youth unemploy-
ment, although empirical studies
in OECD countries have questioned
whether such a connection truly
exists (Böheim, 2014).
The youngest statutory retirement
ages (ages at which retirees are
eligible to receive a social pen-
sion) are in Africa, where less than
20 percent of countries specify
an eligibility age exceeding 60. In
contrast, the share of European
countries with pensionable ages
above 60 exceeds 90 percent for
males and 75 percent for females.
Despite such variation, Figure 6-14
illustrates that statutory pension-
able ages around the world tend
to continue to concentrate on the
exact ages 55, 60, and 65.
U.S. Census Bureau An Aging World: 2015 109
Figure 6-15.
Percentage Distribution of Statutory Pensionable Age by Region and Sex:
2012/2014
Over 65
Percent
Africa
(N=46)
Asia
(N=38)
Europe
(N=44)
Latin America
and the
Caribbean
(N=33)
Northern
America
(N=3)
Oceania
(N=11)
65 Between 60 and 65 60 Between 55 and 60 55 Under 55
N=Number of countries in each region.
Sources: Social Security Administration, 2013a, 2013b, 2014a, 2014b; Social Security Programs Throughout the World.
0 10 20 30 40 50 60 70 80 90 100
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
Male
Of course, the statutory pension-
able age is subject to change. As
noted earlier, official retirement
ages have tended to rise in many
parts of the world (World Bank
Group, 2014).
Upward pressure on statutory
retirement ages often occurs
under PAYGO systems, which rely
on payroll deductions from cur-
rent workers to fund pensions of
current retirees. Such systems are
readily sustainable when a smaller
proportion of the population is at
older ages, but as the population
ages and the older dependency
ratio (retirees per worker) rises
(Chapter 2), changes are needed.
To remain financially sustainable,
such systems require one or more
of the following: increases in the
payroll tax for workers, cuts to
pensioner benefits, or a rise in the
official retirement age. For many
governments experiencing such
challenges, the latter option has
often been preferred (Organisation
for Economic Co-operation and
Development, 2013). A number of
European countries and the United
States are gradually increasing their
statutory pensionable age to 67.
For France, Germany, Spain, the
United Kingdom, and the United
States, pension eligibility will reach
age 67 by 2022, 2029, 2027, 2028,
and 2027, respectively (Social
Security Administration, 2014a;
2014b).
110 An Aging World: 2015 U.S. Census Bureau
Box 6-2.
A Second Demographic Dividend?—Age Structure, Savings, and Economic Growth
As fertility falls, a “demographic dividend” of more rapid economic growth might be achieved due to a higher
proportion of the population at working ages (Chapter 3) and increased labor force participation of women.
Conversely, the proportions of children and older adults—who tend to consume economic resources rather
than produce them—will be lower. Yet the window of opportunity for reaping this potential benefit from
changing age structure is temporary, and there is no guarantee that it will be reaped. Moreover, as fertility
remains low for a long time, this initial dividend will dissipate as the large cohort of workers reaches older
ages (Chapters 2 and 3).
However, a second demographic dividend might also occur as a population ages and the age structure once
again changes. Given longer expected lives and diminished traditional family support due to fewer children,
workers may attempt to save more and accumulate additional assets in preparation for their retirement
(Bloom, Canning, and Graham, 2003; Bloom et al., 2007). That extra savings and an increase in capital per
worker due to a shrinking labor force may lead to rapid economic growth in contrast to the pessimistic view
of the labor force shrinking, per capita income declining, and consumption and welfare falling (Mason and
Lee, 2006; Bloom and Canning, 2008).
The opportunity to achieve the second demographic dividend will exist for many countries, but the realiza-
tion of that dividend will depend on how consumption of the older population is supported—through savings
or borrowing, governmental transfers, or family transfers (Bloom and Canning, 2008). Economic policies that
encourage workers to save and accumulate assets such as housing, businesses, and funded pensions will be
important. A developed financial system and access to global markets are key to providing opportunities for
workers to achieve financial independence in old age and reduce reliance on families and the government. If
governments choose to increase PAYGO public pensions in response to population aging, then this will coun-
ter saving incentives and substantially increase the burden on younger generations (ibid.).
Japan, one of the most rapidly aging countries in the world due to a dramatic decline in fertility in the 1950s
and mortality improvements that have placed Japan ahead of nearly all other countries in terms of life expec-
tancy, is the first Asian country to begin reaping the second demographic dividend. The second dividend
contributions to growth in Japan were high in the 1980s (adding nearly 1.5 percentage points to economic
growth), while in more recent years the benefits are more modest—adding about 0.5 percentage point to
growth (Ogawa et al., 2010). The traditional family support system is disappearing due to fewer children and
increased public pension benefits. One statistic illustrates the change—in 1950 nearly two-thirds of Japanese
married women said they intended to rely on their children for old age support but in 2000 only 11 percent
expected to depend on their children (Ogawa, Kondo, and Matsukura, 2005). While Japan has increased
spending in support of the aging population, the government has set a ceiling of 45 percent of national
income for the tax burden for financial social security programs (ibid). The government hopes that increas-
ing financial literacy rates among adults in Japan will further increase life cycle saving among workers and
continue the second demographic dividend (Ogawa et al., 2010).
U.S. Census Bureau An Aging World: 2015 111
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U.S. Census Bureau An Aging World: 2015 115
CHAPTER 7.
Pensions and Old Age Poverty
The economic well-being of older
populations differs quite markedly
throughout the world, as do the
sources of income and support
that they receive. In most coun-
tries, a key source of income for
the older population comes from
public pension systems that rely on
pooled payroll taxes from current
workers and employers, a pay-as-
you-go (PAYGO) type of financing.
A smaller number of countries have
systems requiring contributions
to personal retirement accounts,
Provident Funds, or other pension
vehicles earmarked for each indi-
vidual. Assets can also be accumu-
lated through voluntary saving and
investment, sometimes encouraged
by government programs that pro-
vide favorable tax treatment.
In addition to these income
sources, the financial well-being of
the older population often depends
on other sources, such as families,
who may provide both monetary
and nonmonetary forms of support.
Various frameworks have been
developed to organize these ele-
ments of old age financial security,
such as the World Bank’s “5-pillar”
approach (Holzmann and Hinz,
2005). A portion of the older peo-
ple may not have sufficient means
to support themselves financially
and, as a result, live in poverty.
NUMBER OF COUNTRIES
OFFERING A PUBLIC
PENSION CONTINUES TO
RISE
As of 1940, only 33 countries
in the world had public pension
programs to support the welfare of
the older population. Since then,
the number of countries with such
programs has steadily increased.
The largest increase occurred dur-
ing the 1960s when the number of
countries increased from 58 to 97.
Another burst occurred during the
1990s. At present, 177 countries
have mandated pension systems of
one kind or another for their older
populations (Figure 7-1).1
The purpose of these public sys-
tems is typically two-fold: to help
smooth out a stream of income,
which would otherwise decline
drastically following the transition
from work to retirement, and to
reduce the incidence of poverty
(MacKellar, 2009). A diversity of
programs has been developed to
meet these common goals.
EARNINGS-RELATED
PENSION PROGRAMS ARE
STILL THE MOST COMMON
By far the most common public
old age pension program involves
a periodic payment related to the
level of earnings one had while
working. Among the 177 countries
that mandate a public pension,
more than 80 percent have an earn-
ings-related program (Table 7-1).
Among the six regions, those with
the highest percentage of countries
having this type of pension are
Latin America and the Caribbean
(97 percent), Europe (89 percent),
and Africa (85 percent).
These mandated defined-benefit
pensions are based on a formula
that typically considers factors
such as the level of earnings, years
of service, and age at retirement,
although earnings are usually
1 According to the U.S. Department of
State, there are 195 independent countries
in the world and about 60 dependencies and
areas of special sovereignty. Some dependen-
cies have pension systems separate from
their associated independent country.
Figure 7-1.
Number of Countries With Public Old Age/Disability/
Survivors Programs: 1940 to 2012/2014
Sources: 1940–2004 from Kinsella and He, 2009; 2012/14 from Social Security Administration,
2013a, 2013b, 2014b, 2014c; Social Security Programs Throughout the World.
58
97
123
135
167
177
33
44
2012/20142004198919791969195819491940
116 An Aging World: 2015 U.S. Census Bureau
Table 7-1.
Number and Percentage of Public Pension Systems by Type of Scheme and World Region
Region
Countries
with any pub-
lic pension
system
Earnings
related Flat rate Means-
tested
Provident
fund
Occupational
retirement
scheme
Individual
retirement
scheme
Num-
ber
Per-
cent
Num-
ber
Per-
cent
Num-
ber
Per-
cent
Num-
ber
Per-
cent
Num-
ber
Per-
cent
Num-
ber
Per-
cent
Num-
ber
Per-
cent
All regions .................... 177 100 144 81 46 26 62 35 16 9 9 5 26 15
Africa ........................ 47 100 40 85 5 11 3 6 4 9 1 2 1 2
Asia ......................... 46 100 28 61 15 33 11 24 12 26 2 4 5 11
Europe ....................... 45 100 40 89 19 42 27 60 0 0 4 9 10 22
Latin America and the Caribbean .. 33 100 32 97 4 12 18 55 0 0 0 0 10 30
Northern America .............. 3 100 2 67 2 67 3 100 0 0 1 33 0 0
Oceania ...................... 3 100 2 67 1 33 0 0 0 0 1 33 0 0
Note: Countries may have more than one type of scheme. Data as of latest available year.
Sources: Social Security Administration, 2013a, 2013b, 2014b, 2014c; Social Security Programs Throughout the World.
capped in the computation of bene-
fits. The range of pensions paid out
tends to be flatter than the range of
income among workers.
Less common types of public old
age pension programs include flat-
rate pensions (a uniform amount
or based on years of service or
residence), means-tested pensions
(paid only to eligible retirees with
income or wealth below a desig-
nated level), provident funds (ben-
efits paid as a lump sum based on
contributions and accrued interest),
and individual retirement schemes
(benefits paid as an annuity or
lump sum based on contributions
and investment results). Some
countries require that employers in
certain industries, such as railroad
or mining, contribute to special
occupational retirement schemes
for their employees.
Countries often have more than
one type of program. By region, flat
rate and means-tested pension pro-
grams are most common in Europe
and Northern America, whereas
provident funds are most common
in Asia.
Regardless of the type of man-
datory, old age income security
program, funding comes from a
combination of worker, employer,
and government contributions.
Figure 7-2.
Contribution Rates for Old Age Social Security
Programs by Country and Contributor: 2012 and 2013
Note: Old age social security programs includes old age, disability, and survivor's benefits.
Sources: Social Security Administration, 2013a, 2013b, 2014b, 2014c; Social Security
Programs Throughout the World.
0 5 10 15 20 25 30 35 40
Hungary
Italy
Egypt
India
China
Sudan
Finland
Uruguay
Argentina
Turkey
Germany
Saudi Arabia
Nigeria
United States
Costa Rica
South Korea
Ireland
Indonesia
Honduras
Israel
Insured person
Percent
Employer
Workers typically pay a percentage
of covered salary and employers
contribute a percentage of covered
payroll. The government often con-
tributes by covering administrative
costs for the program and, in some
cases, by providing general rev-
enue. However, the governments
of Bangladesh, Georgia, Botswana,
and South Africa, for example,
pay the total cost of old age pen-
sion programs in their countries
U.S. Census Bureau An Aging World: 2015 117
with no contributions from work-
ers or employers (Social Security
Administration, 2013a; 2013b;
2014c).
The required contribution amount
varies widely throughout the world,
from less than 2 percent in Israel to
over 35 percent in Hungary (Figure
7-2).2 In between the extremes,
contribution rates in other coun-
tries appear to be fairly evenly
distributed. There are also differ-
ences in the share of the contribu-
tion between the employee and
employer. In many countries, the
contribution amount is the same
2 Contribution rates are not directly com-
parable across countries because the earnings
subject to the rate can vary and a ceiling may
exist on the earnings subject to the contribu-
tion rate.
for each, although the share for
employees is notably higher in
some countries such as Uruguay,
in contrast to countries such as
Finland, Hungary, Italy, and China
where the share for employers is
higher.
PUBLIC PENSION COVERAGE
GREATER IN HIGH-INCOME
COUNTRIES
Although many countries have
mandated public pension sys-
tems, their coverage of the over-
all workforce differs markedly.
The Organisation for Economic
Co-operation and Development
(2013b) has calculated coverage
based on whether an individual
contributed to or accrued pension
rights in any major public pension
scheme. Based on that definition,
high-income countries tend to
have greater coverage. Coverage
exceeds 90 percent of the labor
force in Japan, United Kingdom,
United States, Australia, and Italy
(Figure 7-3). In contrast, in the
world’s two population billionaires,
public pensions cover only 1 out of
3 in China and 1 out of 10 in India.
Such sharp international differences
in coverage rates are often linked
to the proportion of people who
work in the “informal economy.”
Those who work outside of the
formal sector are far more chal-
lenging to cover administratively
using the wage-based criteria of
traditional social security systems
and, because of their lower income
levels, they may have little or no
resources available to contribute
to the system (MacKellar, 2009).
In China, public pension schemes
are limited to employees in urban
enterprises (and urban institutions
managed as enterprises); the urban
self-employed are covered only in
some provinces. The rural popula-
tion is largely uncovered. In India,
the main pension scheme excludes
an even larger swath of the popula-
tion—the self-employed (urban as
well as rural), agricultural work-
ers, and members of cooperatives
with fewer than 50 workers (Social
Security Administration, 2013b).
To address this major coverage
gap, India launched a new defined
contribution pension scheme (Atal
Pension Yojana) in 2015 that offers
participants flexibility in contribu-
tion levels, a guaranteed minimum
rate of return, and for those who
join in 2015, the government will
provide matching funds for the
next 5 years (India Ministry of
Finance, 2015).
Figure 7-3.
Proportion of Labor Force Covered by Public Pension
Systems in Each Country: 2005–2012
Note: Data refer to various years from 2005 to 2012 provided by each country.
Source: Organisation for Economic Co-operation and Development, 2013a.
0 10 20 30 40 50 60 70 80 90 100
India
Indonesia
Vietnam
Thailand
Sri Lanka
Philippines
China
Malaysia
Hong Kong
Korea
Singapore
Germany
France
Canada
Italy
Australia
United States
United Kingdom
Japan
Percent
118 An Aging World: 2015 U.S. Census Bureau
In addition to coverage, another
important characteristic of public
pension programs is the extent
to which the pension “replaces”
wages earned during the working
years. One formula for calculating
the replacement rate divides the
total value of net expected pension
entitlements by total net earnings
(adjusted for differences in income
taxes and social security contribu-
tions paid by workers and retirees;
see Organisation for Economic
Co-operation and Development,
2013a). As is the case for cover-
age, replacement rates tend to vary
quite widely. Among the countries
shown in Figure 7-4, replace-
ment rates exceed 100 percent in
Argentina, the Netherlands, and
Saudi Arabia (that is, the median
Box 7-1.
Defined Benefit and Defined Contribution Pensions in Selected African Countries
Unlike the shift from defined benefit to defined contribution systems in some parts of the world, in some
African countries such as Ghana, Tanzania, and Zambia, the trend has been away from defined contribution
toward defined benefit or toward a combination of both (Stewart and Yermo, 2009). The nascent pension sys-
tems set up in former British colonies in Africa following independence were primarily defined benefit plans
limited to civil servants and defined contribution provident funds for workers in the formal sector (Kpessa,
2010). Coverage was limited, and family and community were the primary sources of support in old age.
However, with changing expectations and concerns about administrative management of large lump sum
payouts, the steady stream of pension income under a more traditional defined benefit plan has become a
more attractive option. This is especially so given the high fertility in Africa under which PAYGO financing is
most viable.
Ghana provides an illustration of such reforms. In years past, the primary mandatory pension system was
called the Social Security and National Insurance Trust (SSNIT), which covered most civil servants and some
workers in the private sector. The SSNIT relied on a partially funded PAYGO system with features of both
defined benefit and defined contribution. A special feature allowed workers to collect 25 percent of their
earned pension in a lump sum at the time of retirement (Steward and Yermo, 2009). As in many other African
societies, however, coverage under the system is very low, only about 10 percent of the labor force. Although
coverage remains very low today, a series of reforms implemented in 2010 helped to address inadequacies in
the system for those who are covered. Workers are fully vested in a defined benefits program at age 60 with
15 years of service. Contribution rates are 5.5 percent of wages for employees and 13 percent for employers
(Social Security Administration, 2013a). The lump sum payment of 25 percent of the pension at retirement
was eliminated. The pension is 37.5 percent of the highest earnings over a 3-year period, with an additional
1.125 percent of earnings for each year worked beyond 15 years. In addition to early retirement provisions,
those with insufficient years of service receive a lump sum. A smaller mandatory occupational pension
scheme based on defined contributions and offering a lump sum payout covers another portion of workers
(Stewart and Yermo, 2009). The Informal Sector Fund, established in 2008, consists of defined contribution
schemes that are voluntary, based on individual contributions, and have no fixed contribution rate. These
schemes target informal sector workers and as of 2013, there were 2 million participants (Van Dam, 2014).
In contrast, Nigeria appears to have moved in the opposite direction, setting up a Chilean style system
of mandatory individual retirement accounts in 2004 known as the Contributory Pension Scheme (Social
Security Administration, 2013a). However, the new system has suffered problems similar to those experi-
enced in other countries with the Chilean model, such as higher administrative costs compared to PAYGO
systems and relatively low payouts (Ojonugwa, Isaiah, and Longinus, 2013). Given the potential drawbacks
of both defined benefit and defined contribution systems, as well as the critical need for good governance
and administration of both systems, some have suggested that Nigerian authorities consider a “social pen-
sion” for the older population based on general tax revenues, much of which would be financed from profits
in the oil industry (Casey and Dostal, 2008).
U.S. Census Bureau An Aging World: 2015 119
Figure 7-4.
Public Pension Net Replacement Rate for Median
Earners by Country: 2013
Notes: The net replacement rate is defined as the individual net public pension
entitlement divided by net pre-retirement earnings, taking account of personal income
taxes and social security contributions paid by workers and pensioners. For countries
with different net replacement rates for men and women, the bar reflects the rate for
men and the rate for women is shown in parentheses.
Source: Organization for Economic Co-operation and Development, 2013a.
112.4 (103.9)
63.1 (57.4)
64.4
89.7 (70.8)
72.3
57.8
94.4
68.7 (64.0)
14.4 (13.2)
82.0
42.5
45.3
103.8
51.7
72.4 (64.9)
109.9 (96.2)
12.9
55.3
94.9
49.9
South Africa
Indonesia
Japan
Mexico
United States
New Zealand
Sweden
Germany
Brazil
Canada
India
France
Russia
Italy
China
Hungary
Turkey
Netherlands
Saudi Arabia
Argentina
(In percent)
earner can expect to receive more
back during retirement than what
they earned while working), com-
pared to less than 15 percent in
Indonesia and South Africa. In 7 of
the 20 countries shown, the net
replacement rate for women and
men is different, and in all cases
the net replacement rate is lower
for women.
Singapore is unusual in that it has a
single-tier pension system con-
sisting of a defined-contribution
plan administered by the Central
Provident Fund. While Singapore
has achieved nearly universal
coverage of the citizen and per-
manent resident labor force, the
benefit level is low compared to
other countries of similar wealth
(Organisation for Economic
Co-operation and Development,
2012).3 As of 2011, the aver-
age balance per member was
about equal to per capita income,
which was viewed as inadequate
given the high life expectancy in
Singapore (Asher and Bali, 2012).
The Singapore government has
undertaken multiple initiatives to
encourage employment of older
residents in recent years with
some success. The labor force
3 Nonresidents (not citizens or permanent
residents) accounted for 25 percent of the
population in Singapore in 2009 and 35 per-
cent of the labor force (Asher and Bali, 2012).
participation rate for residents
aged 55 to 64 rose from 49.5
percent in 2004 to 68.4 percent in
2014, and for residents aged 65
to 69 increased from 18.9 percent
in 2004 to 41.2 percent in 2014
(Singapore Ministry of Manpower,
2014). In addition, the government
appointed a Central Provident Fund
Advisory Panel in 2014 to recom-
mend further reforms to provide
greater flexibility and improve
retirement adequacy in the face of
increases in the cost of living and
rising life expectancy.
OPINIONS DIFFER ON
HOW TO IMPROVE
SUSTAINABILITY OF PUBLIC
PENSION SYSTEMS
Upon first being established,
earnings-related pension sys-
tems typically generate a surplus
because the size of the workforce
contributing is generally much
larger than the pool of retirees who
have qualified to receive benefits.
Surplus payroll tax revenues can
either be banked for future retirees
or used to fund other government
spending. When surplus payroll
tax revenue is not set aside for
future retirees, as often is the case,
the system becomes financed on
a PAYGO basis. As the population
ages, a PAYGO system may run
a deficit unless adjustments are
made, and such adjustments may
provide a drag on the economy
(Holzmann, 2012; Organisation
for Economic Co-operation and
Development, 2014b). For exam-
ple, based on current pension
benefits, the long-term contribu-
tion rate required will be over
30 percent of payroll in Pakistan
and over 40 percent in China and
Vietnam (Organisation for Economic
Co-operation and Development,
2013b).
120 An Aging World: 2015 U.S. Census Bureau
Figure 7-5 provides estimates and
projections of the total cost of pub-
lic benefits provided to the popu-
lation aged 60 and over—includ-
ing both pension and health care
programs—in 2010 and projected
to 2040. Among the 16 countries
shown, 5 had pension and health
costs equal to 15 percent or more
of GDP in 2010, whereas 14 coun-
tries are expected to reach that
share in 2040. The average cost of
such programs is expected to rise
from 10 percent of GDP to more
than 15 percent by 2040. Among
the countries in Figure 7-5, the
sharpest increases are projected
in South Korea and China, where
the share of GDP devoted to public
benefits to the 60 and over popu-
lation will more than triple over
the interval, due largely to the
historic rapidity of fertility decline.
However, China’s expenditures on
the older population will remain
well below the GDP share projected
for the United States and other
wealthier countries.
With a shrinking share of work-
ers in the population, options to
ensure financial solvency of PAYGO
systems (including PAYGO-funded
health care systems, such as
Medicare in the United States) are
to:
• Raise the minimum age for
benefit eligibility.
• Raise the payroll tax for work-
ers and/or employers.
• Reduce benefits for recipients.
• Increase tax-funded subsidies
or government borrowing to
subsidize the system.
Opinions about which of these
options is best for solving the
inherent challenges of a PAYGO sys-
tem may differ among workers and
retirees. Public opinion may also
play a role in each country’s choices
regarding the reform of public sys-
tems. A recent cross-national sur-
vey of workers recorded opinions
about possible policy options for
reforming public pension systems
(Aegon, 2013) with results shown
in Figure 7-6. Only a small share
Figure 7-5.
Total Public Benefits to Population Aged 60 and Over
as a Percentage of GDP: 2010 and 2040 Projection
Note: Total public benefits include both pensions and healthcare.
Source: Jackson, Howe, and Peter, 2013.
0 5 10 15 20 25 30
India
Mexico
China
South Korea
Chile
Russia
Australia
Canada
Brazil
Netherlands
Switzerland
United States
Poland
United Kingdom
Spain
Japan
Sweden
Germany
France
Italy
Percent
2010 2040
U.S. Census Bureau An Aging World: 2015 121
of workers felt that the govern-
ment should do nothing and that
the public pension system would
remain affordable (shares ranged
from 1 percent in China to 14
percent in the Netherlands). When
asked about options to increase
the sustainability of government
pensions, 4 percent of workers
in China said they did not know
what the government should do,
while one-third of respondents
in France did not know. When
asked to choose between reducing
pension benefits, raising pension
taxes, or a combination of reduced
pension benefits and increased
taxes, the largest share selected
the balanced approach of both in
Canada, France, Germany, Japan,
the Netherlands, Poland, the United
Kingdom, and the United States.
In both Spain and China, workers
favored raising pension taxes alone
over reducing pension benefits or
a combination of the two policies.
As to the acceptability of reduced
benefits, there were also notable
differences over specific options
for reducing them. For instance,
about more than half of respon-
dents in Germany and in Poland
(Aegon, 2013) believed that people
already work long enough and
that the retirement age should not
be changed. In contrast, only 17
percent shared that belief in Japan
(ibid.).
Figure 7-6.
Favored Options to Increase Sustainability of Government Pensions by
Country: 2013
Government should:
Don’t know
Percent
Source: Aegon, 2013.
Reduce
pension
benefits
Raise
pension
taxes
Balance a reduction
in pension benefits
and an increase in
pension taxes
Do nothing,
system will
remain
affordable
0 10 20 30 40 50 60 70 80 90 100
United
States
United
Kingdom
Spain
Poland
Netherlands
Japan
Germany
France
China
Canada
122 An Aging World: 2015 U.S. Census Bureau
THE CHILEAN MODEL
UNDERGOES FURTHER
REFORM AND SOME
COUNTRIES ABANDON IT
COMPLETELY
The Chilean government in 1981
made a bold decision to abandon
its defined benefit public pension
system and introduce a defined
contribution system administered
by the private sector. Following the
early success of Chile’s reforms,
other countries, many in Latin
America and the Caribbean and
Eastern Europe, followed the
Chilean model and established
individual retirement accounts to
replace or supplement defined ben-
efit public systems. At present, of
the 26 countries currently mandat-
ing such accounts, 10 are in Latin
America and the Caribbean and 10
are in Europe (Table 7-1).
Most of the Latin American and
Caribbean countries with mandated
individual accounts systems set
them up during the 1990s (Table
7-2). Under this system, workers
have some choice, albeit limited,
regarding the management of their
retirement account. The number of
investment companies from which
individuals may choose ranges from
2 to 15 per country, while the num-
ber of investment options offered
by each company ranges from 1 to
5 (Kritzer, Kay, and Sinha, 2011).
Typically, investment managers are
expected to invest in broad catego-
ries or indexes of funds.
Between 2004 and 2009, the
proportion of the labor force con-
tributing to individual retirement
accounts in Latin America increased
in 9 of the 10 countries, although
a large share of the labor force
remained uncovered (Figure 7-7).4
In 2009, for instance, only Chile
and Costa Rica had more than 50
percent of the labor force con-
tributing to individual retirement
accounts while less than 20 percent
were doing so in Bolivia, Colombia,
El Salvador, and Peru.
4 Argentina was the tenth country, and it
abolished individual accounts in 2009.
Table 7-2.
Characteristics of Latin American Individual Account Pensions: 2009
Country Year system
began
Number of
pension fund
management
companies
Allowable
investment
fund types per
company
Minimum
rate-of-return
requirement
Contribution rates (percent)
Employee Employer
Bolivia ......................... 1997 2 1 No 10.000 None
Chile .......................... 1981 6 5 Ye s 10.000 Voluntary
Colombia ....................... 1993 8 3 Ye s 3.850 11.625
Costa Rica ...................... 1995 5 1 No 1.000 3.250
Dominican Republic ............... 2003 5 1 Ye s 2.870 7.100
El Salvador ..................... 1998 2 1 Ye s 6.250 4.050
Mexico ......................... 1997 15 5 No 1.125 5.150
Peru ........................... 1993 4 3 Ye s 10.000 None
Uruguay ........................ 1996 4 1 Ye s 15.000 None
Note: Uruguay employee contribution rate applied only to gross monthly earnings above 19,805 pesos.
Source: Kritzer, Kay, and Sinha, 2011.
U.S. Census Bureau An Aging World: 2015 123
The maturing Chilean model has
faced a number of challenges
in Chile and many of the other
countries that implemented this
model over the past 30 years (Gill,
Packard, and Yermo, 2005; Gill et
al., 2005; Kritzer, Kay, and Sinha,
2011). It was the lack of financial
sustainability inherent in the public
PAYGO pension system, low cover-
age, and the potential higher rate
of return to be earned in the private
sector on retirement contributions
that led Chile and other countries
to switch to privately-managed
individual accounts. However,
coverage remained limited and the
pension fund management compa-
nies were criticized for high fees
and weak competition.
In response to these issues,
countries have taken different
approaches, ranging from imple-
menting further reforms to weak-
ening the individual accounts to
completely abandoning the Chilean
model. Both Argentina (2009)
and Hungary (2011) closed the
individual accounts systems in
their countries and transferred all
workers back to the PAYGO defined
benefit pillar. A number of coun-
tries in Eastern Europe, including
Estonia, Latvia, Lithuania, Poland,
and Slovakia, reduced contribu-
tions to the individual accounts, in
some cases on a temporary basis.
For these countries fiscal deficits,
aggravated by the global financial
crisis and the Maastricht limits,
were a major factor in their deci-
sion. Chile, Colombia, Mexico,
Peru, and Uruguay have moved
forward with a second round of
reforms to strengthen their indi-
vidual accounts systems (Bucheli,
Forteza, and Rossi, 2008; Kritzer,
Kay, and Sinha, 2011). Chile led the
way with a round of reforms imple-
mented in 2008 (see Box 7-2).
Figure 7-7.
Percentage of Labor Force Contributing to Individual Account Pensions by
Country: 2004 and 2009
Source: Kritzer, Kay, and Sinha, 2011.
2009
2004
Percent
0
10
20
30
40
50
60
BoliviaPeruColombiaDominican
Republic
El
Salvador
ArgentinaUruguayMexicoCosta RicaChile
124 An Aging World: 2015 U.S. Census Bureau
THE BIGGER FINANCIAL
PICTURE INCLUDES OTHER
SOURCES OF INCOME
Clearly, every category of pen-
sion schemes has its own benefits
and limitations (MacKellar, 2009;
Holzmann, 2012; Cannon and
Tonks, 2013). Defined benefit plans
become less viable as populations
age. Defined contribution plans
tend to have limited coverage and
uncertain payouts for a large por-
tion of the older population. Given
such limitations, many countries
appear to be experimenting with
multiple approaches to minimize
risk (Organisation for Economic
Co-operation and Development,
2013a and 2014b).
Of course, incomes among the
older population are not limited
to public pensions. In addition to
mandatory government savings
programs, individuals may save
on their own. In some countries,
voluntary saving is encouraged
through favorable tax treatment,
such as 401K-type plans in the
United States. There are also mul-
tiple ways that individuals may
generate an income stream in their
older years, including investments
in rent-producing property and
reverse home mortgages. Some
continue to work beyond age 65
(see Chapter 6).
A more complete picture of
income sources among the older
population is shown for sev-
eral Organisation for Economic
Co-operation and Development
(OECD) countries on Figure 7-8. In
2011, public transfers represented
over three-quarters of income for
the older population in Austria,
Czech Republic, Finland, Greece,
Ireland, Luxembourg, Portugal,
Slovenia, and Spain. In the United
States, only 38 percent of income
among the older population came
from public transfers. The propor-
tion of income from work earnings
varies among this grouping, from
10 percent in Finland to 34 percent
in the United States. While private
pensions and investment earnings
constituted 28 percent of income in
the United States, they represented
Box 7-2.
Chile’s Second Round of Pension Reform
Chile’s government appointed a council to review the pension system and recommend new reforms. The
series of reforms enacted in 2008 were intended to increase participation rates, lower administrative costs,
and improve the adequacy of pension benefits for all (Shelton, 2012). In order to address the issue of cover-
age, participation of self-employed workers was transitioned from voluntary to mandatory.
Several of the reforms focused on reducing the multiple, high administrative fees that participants faced.
Prior to the 2008 reforms, the five pension fund management companies (Administradoras de Fondos de
Pension) charged an average of 1.71 percent of earnings and several of the companies also charged fixed
monthly fees (Kritzer, 2008). Reforms eliminated the monthly fixed administrative fees. The pension fund
management companies now must bid and compete to manage the contributions of new labor force entrants
with the selection going to the company submitting the lowest fees. The company must then maintain that
fee for 24 months and offer the same low fee to all its account holders. Another change allowed insurance
companies to set up fund management companies to compete with the existing companies. Reforms also
gradually increased the share of foreign investments allowed to 80 percent of assets, up from 45 percent.
The council concluded that Chile’s individual account system was working well for middle- and upper-wage
earners who were regular contributors, but those who did not make regular contributions or made minimal
contributions did not fare well (James, Edwards, and Iglesias, 2010). Thus, another pillar was added, Pension
Basica Solidariato, to provide a basic pension to those who had not contributed to individual accounts or who
would receive an inadequate pension based on their individual account balances.
Reforms also sought to address gender inequities. Women had been particularly disadvantaged because
of their shorter work history, lower earnings, and greater participation in the informal sector, which is not
covered by the pension system. Women’s pensions were 30 to 40 percent less than men’s (Kritzer, 2008).
The 2008 reforms introduced a pension bonus for each child that a woman had and the bonus will be added
to her regular retirement pension when she reaches age 65. In addition, all widowers are now eligible for a
survivor pension.
U.S. Census Bureau An Aging World: 2015 125
Figure 7-8.
Income Distribution for Population Aged 65 and Over by Source and
Country: 2011
Wage earnings Self-employed earnings Public transfers Private transfers and capital earnings
Percent
Note: U.S. estimates are for 2012 and wage earnings includes self-employed earnings.
Sources: Organisation for Economic Co-operation and Development, 2014a; Social Security Administration, 2014a.
0 10 20 30 40 50 60 70 80 90 100
United States
Spain
Slovenia
Slovak
Republic
Portugal
Poland
Luxembourg
Italy
Ireland
Iceland
Greece
Finland
Estonia
Czech
Republic
Austria
less than 5 percent in the Czech
Republic, Estonia, Greece, Poland,
Slovakia, Slovenia, and Spain.
One important question is whether
the receipt of income from one
source may affect the effort to
save or earn income from another
source, a hypothesis known as
“crowding out” (Alessie, 2005). One
approach to assess crowding out
is to compare expected income
streams from mandatory pension
plans with the amount of private
savings on a country-by-country
basis. Using data calculated by the
OECD and collected in longitudi-
nal surveys, Hurd, Michaud, and
Rohwedder (2012) estimated the
mean public pension replacement
rate and relative financial wealth
for 12 countries. They found that
for every extra dollar in expected
pension income, the amount of
savings at retirement is reduced by
22 cents in the 12 countries (ibid.).
Another approach is to examine
the effect of pension reforms
(involving a change in the expected
value of the public pension) on
household saving rates (before
and after the implementation of
the pension reform). Attanasio and
Brugiavini (2003) focused on the
1992 pension reforms implemented
in Italy that reduced the present
discounted value of the public
pension fund and found evidence
of a displacement effect on private
saving. Attanasio and Rohwedder
(2003) found substitution between
the United Kingdom public pension
scheme and financial wealth at the
time of reforms from 1975 to 1981.
126 An Aging World: 2015 U.S. Census Bureau
Figure 7-9.
Average Income Tax Rate for Ages 18–65 and Over Age 65 by Country: 2011
Source: Organisation for Economic Co-operation and Development, 2014a.
Tax rate
0
5
10
15
20
25
30
35
IcelandGreeceAustriaItalyPortugalSloveniaLuxem-
bourg
IrelandPolandFinlandEstoniaCzech
Republic
SpainSlovakia
18–65 Over 65
Governments often offer prefer-
ential tax treatment for specific
sources of income received by the
older population, such as pensions;
however, tax rates vary substan-
tially across the world. Among the
group of OECD countries shown
in Figure 7-9, for instance, the
average income tax rate paid by
those aged 65 and over ranged
from below 5 percent in the Czech
Republic and Slovakia to above 20
percent in Iceland. In all the coun-
tries shown in Figure 7-9, the older
population has a lower average tax
rate than those at primary working
ages. The lower average income
tax rate for the older population
may reflect the lower income level
of this age group in addition to
favorable tax treatment.
FAMILIES PLAY A MAJOR
SUPPORT ROLE IN MANY
SOCIETIES
For generations, families have been
key providers of both monetary and
nonmonetary support for the older
population. In fact, a key strategy
in traditional societies for ensuring
one’s security at older ages was to
raise several children to adulthood
(Schultz, 1990). However, as popu-
lations become more urbanized and
fertility rates decline, the forms of
family support for the older popula-
tion are changing.
The value of family contributions to
the welfare of older people can be
challenging to estimate, since this
can take the form of in-kind goods
and services, such as housing and
daily assistance. The interpreta-
tion of intergenerational transfers
can be rather complicated. For
instance, in some societies, they
may actually constitute a reverse
transfer back to parents who had
turned over their assets to one or
more children with the expecta-
tion that they would receive care in
return. Despite these interpretive
challenges, one thing is clear—the
family provides important protec-
tion from poverty for the older
population. In India, for instance,
over three-quarters of the older
population live in three-generation
households (Desai et al., 2010), an
arrangement ideally suited to the
sharing of assets and provision of
care for dependents. In the United
States, family members often serve
as long-distance caregivers for a
parent or relative living in another
location (Clark, 2014). They
may help manage prescriptions,
U.S. Census Bureau An Aging World: 2015 127
Figure 7-10.
Poverty Rate for Total Population
and Population Aged 65 and Over
for OECD Countries: 2010
1 Country data for 2011.
2 Country data for 2009.
Note: Poverty is defined as income less than 50 percent of median equivalized
household disposable income. Incomes are measured on a household basis and
equivalized to adjust for differences in household size.
Source: Organisation for Economic Co-operation and Development, 2013a.
Total population
65 and over
Percent
0 5 10 15 20 25 30 35 40 45 50
Israel
Mexico
Turkey2
Chile1
United States
Japan2
Spain
South Korea1
Australia
Greece
Italy
Canada
Estonia
Portugal
Poland
New Zealand2
United Kingdom
Belgium
Switzerland2
Slovenia
Sweden
Ireland2
Germany
Austria
France
Slovakia
Norway
Netherlands
Finland
Luxembourg
Hungary2
Iceland
Denmark
Czech Republic
coordinate health care, ensure that
bills are paid, arrange for home
services, or assist with legal affairs.
Besides the family, societies also
sometimes provide nonmonetary
sources of support, such as hous-
ing subsidies, coupons for basic
foodstuffs, and coordinate volun-
teers providing free services.
PENSIONS CAN
DRASTICALLY LOWER
POVERTY RATES FOR THE
OLDER POPULATION
As noted earlier, one of the key
goals of mandated public pension
programs is to alleviate poverty
among the older population. Given
that older people are less likely to
work, they are potentially more vul-
nerable than those at working age.
Comparing poverty rates across
countries is challenging given
the variation in poverty measures
and definitions. Poverty is defined
by the World Bank as “the pro-
nounced deprivation in well-being”
(Haughton and Khandker, 2009).
Typically, poverty is defined in
terms of resources needed to cover
basic necessities such as food,
shelter, and clothing. However, the
standard of well-being could also
include capability to function in
society, which would involve access
to education, political rights, and
psychological support (ibid.).
The OECD calculated poverty rates
for its 34 member countries using
a relative poverty level of receiv-
ing income less than 50 percent
of median equivalized household
disposable income (Figure 7-10).
Under this poverty measure, 5 of
the 34 OECD member countries
(Australia, Israel, Mexico, South
Korea, and Switzerland) had pov-
erty rates exceeding 20 percent for
the older population.
128 An Aging World: 2015 U.S. Census Bureau
Figure 7-11.
Poverty Rate for Total Population and Population
Aged 65 and Over for Latin America and the
Caribbean: 2005 to 2007
Note: Poverty line defined as US$2.50 per day purchasing power parity.
Source: Cotlear and Tornarolli, 2011.
0 5 10 15 20 25 30 35 40 45 50
Nicaragua
Colombia
Honduras
Bolivia
Guatemala
El Salvador
Peru
Panama
Paraguay
Venezuela
Dominican
Republic
Brazil
Ecuador
Mexico
Costa Rica
Argentina
Uruguay
Chile
Total population
65 and over
Percent
In a study of 18 countries in
Latin America and the Caribbean,
Cotlear, and Tornarolli (2011)
calculated poverty rates for the
older population using an abso-
lute poverty line defined as daily
income of $2.50 in purchasing
power parity (Figure 7-11). Poverty
rates for the population aged 65
and over exceeded 20 percent for
nearly half the countries (Bolivia,
Colombia, El Salvador, Guatemala,
Honduras, Mexico, Nicaragua, and
Peru). However, in 14 of the coun-
tries, the poverty rate for the older
population was lower than the pov-
erty rate for the total population
suggesting positive support for the
older population through govern-
ment programs.
In Latin America and Caribbean
countries, the average poverty rate
of those receiving a pension for the
18 countries is 5.3 percent, one-
fifth of the average poverty rate of
those not receiving pensions (25.8
percent). Colombia shows the most
dramatic absolute difference in
poverty rates between those receiv-
ing a pension and those without
a pension (2.4 percent vs. 51.4
percent; Table 7-3). Uruguay shows
the least difference (0.5 percent vs.
3.0 percent). In Colombia about 15
percent of the population aged 65
and over were receiving a pension,
while 84 percent were in Uruguay.
The role of pensions in reducing
poverty among the older popula-
tion can be seen in Figure 7-12,
where countries in Latin America
and the Caribbean with higher pro-
portions receiving a pension tend
to have lower poverty rates overall.
While it may come as no surprise
that poverty rates among older
individuals who receive a pension
income stream are lower than for
those who do not, the magnitude
of the gap in some of these coun-
tries is noteworthy.
U.S. Census Bureau An Aging World: 2015 129
Table 7-3.
Population Aged 65 and Over in Poverty by Pension Status for Selected Countries in Latin
America and the Caribbean: 2005 to 2007
(In percent)
Country
Poverty rate
Percent
receiving a pensionTotal
Receive a
pension No pension
Uruguay ............... 0.9 0.5 3.0 84.0
Chile ................. 2.3 1.0 4.3 60.6
Brazil ................. 3.5 1.5 14.3 84.4
Argentina .............. 3.7 1.1 11.3 74.5
Dominican Republic ...... 15.6 6.9 16.8 12.1
Ecuador ............... 17.2 3.2 20.7 20.0
Paraguay .............. 17.2 0.0 18.8 8.5
Panama ............... 18.2 1.9 29.7 41.4
Costa Rica ............. 18.5 16.0 22.2 59.7
Venezuela ............. 19.4 6.3 40.4 61.6
Peru .................. 20.1 0.4 26.0 23.0
El Salvador ............ 20.7 2.2 24.3 16.3
Mexico ................ 21.9 2.7 27.9 23.8
Bolivia ................ 25.3 22.9 46.0 89.6
Guatemala ............. 29.1 8.2 33.0 15.7
Nicaragua ............. 32.5 10.4 35.4 11.6
Honduras .............. 37.1 7.8 39.6 7.9
Colombia .............. 44.3 2.4 51.4 14.5
Note: Poverty line defined as US$2.50 per day purchasing power parity. Percentage receiving pension is derived algebraically from the first three columns.
Source: Cotlear and Tornarolli, 2011.
Percent receiving a pension
Percent in poverty
Note: Poverty line defined as US$2.50 per day purchasing power parity.
Source: Cotlear and Tornarolli, 2011.
Figure 7-12.
Poverty Rate Among Those Aged 60 and Over by Percentage Receiving Pension
in Latin America and the Caribbean: 2005 to 2007
Mexico
Nicaragua
Panama
Costa Rica
Venezuela
Ecuador
Bolivia
Argentina
Paraguay
Uruguay
Peru
Honduras
Chile
Dominican Republic Colombia
Guatemala
Brazil
El Salvador
5 10 15 20 25 30 35 40 45
0
10
20
30
40
50
60
70
80
90
130 An Aging World: 2015 U.S. Census Bureau
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U.S. Census Bureau An Aging World: 2015 133
CHAPTER 8.
Summary
This report has provided an update
on the world’s older population as
well as the demographic, health,
and economic aspects of our aging
world. Among all demographic
trends underway in the world today,
it is population aging—and how
societies, families, and individuals
prepare for and manage it—that
may be the most consequential. As
Suzman said (quoted in Holmes,
2015), “Ageing is reshaping our
world.”
In addition to updating the most
recent trends, this latest report in
the Census Bureau’s series of An
Aging World featured a variety of
special topics, with some contrib-
uted by researchers outside the
Census Bureau. Below is a summary
of select essential points illustrated
in this report:
POPULATION GROWTH
• In 2015, 8.5 percent of the
world’s population is aged 65
and over. This older population
of 617 million is projected to
increase by an average of 27
million a year over the next 35
years, reaching 1.6 billion in
2050. The older population is
expected to represent 16.7 per-
cent of the world total popula-
tion by then.
• While Europe is still the oldest
region today and is projected to
remain so by 2050, aging in Asia
and Latin America will acceler-
ate and rapidly catch up. Asia is
just as notable for leading the
world in the size of the older
population as speed of aging. At
the other end of the spectrum
is Africa, exceptionally young in
2015 in terms of proportion of
older population, even though
some African countries already
have a large number of older
people.
• The oldest segment (aged 80
and over) of the older popula-
tion has been growing faster
than the younger segments,
thanks to increasing life expec-
tancy at older ages. Some coun-
tries will experience a quadru-
pling of their oldest population
from 2015 to 2050.
• Declining fertility levels have
been the main propeller for
population aging and rates
of decline vary by region and
country. Currently the total fertil-
ity rate is near or below the 2.1
replacement level in all regions
except Africa.
• Some countries have experi-
enced simultaneous popula-
tion aging and population
decline. The traditionally oldest
European countries such as
Italy and Spain are no longer
experiencing population decline
thanks to increases in fertility
and major immigration flows.
New countries joining the list
with projected population
declines between now and 2050
include some Asian countries
driven by rapid fertility decline
such as China, South Korea, and
Thailand.
• Although the world’s total
dependency ratio in 2050 is
projected to remain similar to
the 2015 ratio, the composi-
tion will change considerably,
with the share due to the older
population (rather than children)
projected to almost double, from
20 percent to 38 percent in the
next 3 decades.
HEALTH AND HEALTH CARE
• The leading causes of death
have been shifting in part due
to increasing longevity, with the
share due to noncommunicable
diseases (NCDs) on the rise.
NCDs often occur together and
this multimorbidity increases
with age. African and other low-
and lower-middle income coun-
tries continue to face a consider-
able burden from communicable
diseases as well.
• People continue to live lon-
ger. Global life expectancy at
birth reached 68.6 years and is
projected to rise to 76.2 years
in 2050. Regions and countries
vary drastically, with current life
expectancy exceeding 80 years
in 24 countries but less than 60
years in 28 countries. Among
those reaching older ages,
remaining life expectancy also
varies notably. In several coun-
tries, males and females at age
65 can expect to live at least 20
years and 25 years, respectively,
compared to poorer countries
where they may live less than 12
years and 14 years, respectively.
• A portion of one’s expected
years of life may not be healthy
ones. Healthy life expectancy
(HALE) measures the number
of expected years living in full
health and without activity
limitations. In 2012, HALE for
women at age 65 in European
countries ranged from 3 years
for Slovakians to 16 years for
Norwegians.
• A cluster of risk factors are
directly or indirectly responsible
for the global burden of disease.
For instance, tobacco use has
dropped in some high-income
134 An Aging World: 2015 U.S. Census Bureau
countries, and the majority of
smokers worldwide now live in
low- and middle-income coun-
tries. Increasing obesity, in addi-
tion to being underweight, has
been associated with increased
mortality at older ages.
• The older population has dif-
ferent health care needs than
younger adults due to increasing
chronic diseases and disability
at older ages. Provisions for
health care at older ages are
more often available in countries
with social protection systems
or with universal care schemes.
Universal health coverage has
become a focus for the post-
2015 Sustainable Development
Goals being set by the United
Nations.
• The increasing size and share
of the older population in any
society drives its long-term care
costs. A wide range of funding
sources is used for long-term
care, and the care provided
differs in coverage, degree of
cost-sharing, the scope and
depth of coverage, and provid-
ers’ qualifications.
• Older adults are not solely sup-
ported by pensions or long-term
health insurance. Unpaid care-
giving by family members and
friends remains the main source
of long-term care for older
people worldwide. Informal care
may substitute for formal long-
term care in some circumstances
in Europe, particularly when
low levels of unskilled care are
needed.
WORK, RETIREMENT, AND
PENSIONS
• Labor force participation among
the older population contin-
ues to rise in many developed
countries, yet such participation
remains far higher in low-income
countries.
• Many workers are uncertain
about their lifestyle after
retirement and many retire
earlier than they had expected.
Statutory retirement ages vary
widely across world regions, yet
tend to lump at certain ages,
such as 60 and 65. In several
OECD countries, the formal
retirement age has risen (or is
set to increase) to well above 65.
• The Great Recession (2007–
2009) had a major impact
on unemployment rates and
financial assets among many
older people in more developed
countries. However, the trend
of rising labor force participa-
tion rates among the population
aged 60 and older in these coun-
tries was not halted. The Great
Recession had a much smaller
impact on the majority of less
developed countries whose
economies were less linked
to more developed countries,
where the recession originated.
• Among mandatory pension pro-
grams, earnings-related public
PAYGO systems are still the most
common. Several countries that
had mandated privatized indi-
vidual retirement accounts have
either abandoned that approach
entirely (e.g., Argentina) or
supplemented it with public sys-
tems (e.g., Chile and Ghana).
• Pension coverage of the older
population varies widely
throughout the world. More than
90 percent of the older popula-
tion receives a pension in more
developed countries such as
Japan, United States, Australia,
and Italy. In contrast, in the
world’s two population billion-
aires, public pensions cover less
than a third of the older popu-
lation in China and a tenth of
those in India.
• The proportion of income
that older people received
from public pension systems
in Organisation for Economic
Co-operation and Development
countries range from under 40
percent to over 75 percent. The
remainder of income comes
from a mix of other public trans-
fers, private savings and invest-
ments, and family support.
• Public pensions can drastically
lower poverty rates for the older
population. In Latin America
and Caribbean countries, for
instance, the average poverty
rate of those receiving a pension
is 5.3 percent, one-fifth of the
average poverty rate of those
not receiving pensions (25.8
percent).
• In addition to reducing poverty,
public pensions also may reduce
incentives for private savings, a
phenomenon known as “crowd-
ing out.” Debates about the size
and scope of this phenomenon
continue.
Although some of the aforemen-
tioned issues, as well as future
dynamics of population aging, are
well understood today, the story
of our aging world may evolve in
unexpected ways. The broad institu-
tional response of governments and
policymakers to the challenges of
aging is difficult to anticipate. So too
are the evolving family institutions
and social networks that provide the
foundation of support for each older
person. As these stories continue
to unfold, societies throughout the
world will choose common and
diverse ways to respond to these
challenges.
Chapter 8 Reference
Holmes, David. 2015. “Profile:
Richard Suzman: Helping
the World to Grow Old More
Gracefully.” The Lancet
385/9967: 499.
U.S. Census Bureau An Aging World: 2015 135
APPENDIX A.
Country Composition of World Regions
AFRICA
Eastern Africa
Burundi
Comoros
Djibouti
Eritrea
Ethiopia
Kenya
Madagascar
Malawi
Mauritius
Mozambique
Rwanda
Seychelles
Somalia
Tanzania
Uganda
Zambia
Zimbabwe
Middle Africa
Angola
Cameroon
Central African Republic
Chad
Congo (Brazzaville)
Congo (Kinshasa)
Equatorial Guinea
Gabon
Sao Tome and Principe
Northern Africa
Algeria
Egypt
Libya
Morocco
South Sudan
Sudan
Tunisia
Western Sahara
Southern Africa
Botswana
Lesotho
Namibia
South Africa
Swaziland
Western Africa
Benin
Burkina Faso
Cabo Verde
Cote d’Ivoire
Gambia, The
Ghana
Guinea
Guinea Bissau
Liberia
Mali
Mauritania
Niger
Nigeria
Saint Helena
Senegal
Sierra Leone
Togo
ASIA
Eastern Asia
China
Hong Kong
Japan
Korea, North
Korea, South
Macau
Mongolia
Taiwan
South-Central Asia
Afghanistan
Bangladesh
Bhutan
India
Iran
Kazakhstan
Kyrgyzstan
Maldives
Nepal
Pakistan
Sri Lanka
Tajikistan
Turkmenistan
Uzbekistan
South-Eastern Asia
Brunei
Burma
Cambodia
Indonesia
Laos
Malaysia
Philippines
Singapore
Thailand
Timor-Leste
Vietnam
Western Asia
Armenia
Azerbaijan
Bahrain
Cyprus
Gaza Strip
Georgia
Iraq
Israel
Jordan
Kuwait
Lebanon
Oman
Qatar
Saudi Arabia
Syria
Turkey
United Arab Emirates
West Bank
Yemen
EUROPE
Eastern Europe
Belarus
Bulgaria
Czech Republic
Hungary
Moldova
Poland
Romania
Russia
Slovakia
Ukraine
136 An Aging World: 2015 U.S. Census Bureau
Northern Europe
Denmark
Estonia
Faroe Island
Finland
Guernsey
Iceland
Ireland
Isle of Man
Jersey
Latvia
Lithuania
Norway
Sweden
United Kingdom
Southern Europe
Albania
Andorra
Bosnia and Herzegovina
Croatia
Gibraltar
Greece
Italy
Kosovo
Macedonia
Malta
Montenegro
Portugal
San Marino
Serbia
Slovenia
Spain
Western Europe
Austria
Belgium
France
Germany
Liechtenstein
Luxembourg
Monaco
Netherlands
Switzerland
LATIN AMERICA AND THE
CARIBBEAN
Anguilla
Antigua and Barbuda
Argentina
Aruba
Bahamas, The
Barbados
Belize
Bolivia
Brazil
Cayman Islands
Chile
Colombia
Costa Rica
Cuba
Curacao
Dominica
Dominican Republic
Ecuador
El Salvador
Grenada
Guatemala
Guyana
Haiti
Honduras
Jamaica
Mexico
Montserrat
Nicaragua
Panama
Paraguay
Peru
Puerto Rico
Saint Barthelemy
Saint Kitts and Nevis
Saint Lucia
Saint Martin
Saint Vincent and the
Grenadines
Sint Maarten
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela
Virgin Islands, British
Virgin Islands, U.S.
NORTHERN AMERICA
Bermuda
Canada
Greenland
Saint Pierre and Miquelon
United States
OCEANIA
American Samoa
Australia
Cook Islands
Fiji
French Polynesia
Guam
Kiribati
Marshall Islands
Micronesia, Federated
States of
Nauru
New Caledonia
New Zealand
Northern Mariana Islands
Palau
Papua New Guinea
Samoa
Solomon Islands
Tonga
Tuvalu
Vanuatu
Wallis and Futuna
U.S. Census Bureau An Aging World: 2015 137
Table B-1.
Total Population, Percentage Older, and Percentage Oldest Old: 1950, 1980, 2015, and
2050—Con.
(Numbers in thousands)
Country
1950 1980
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Africa
Egypt .................... 21,834 3.0 0.2 6.7 43,674 3.9 0.4 10.3
Kenya .................... 6,077 3.9 0.3 7.7 16,282 3.0 0.3 10.0
Malawi ................... 2,881 3.1 0.2 6.5 6,215 2.8 0.3 10.7
Morocco .................. 8,953 2.9 0.2 6.9 19,567 4.2 0.6 14.3
South Africa ............... 13,683 3.6 0.3 8.3 29,074 3.1 0.4 12.9
Tunisia ................... 3,530 5.7 0.9 15.8 6,458 3.8 0.3 7.9
Uganda .................. 5,158 3.0 0.3 10.0 12,661 2.6 0.2 7.7
Zimbabwe ................ 2,747 3.2 0.2 6.3 7,285 2.9 0.3 10.3
Asia
Bangladesh ............... 43,852 5.1 0.6 11.8 88,855 2.9 0.3 10.3
China .................... 554,760 4.5 0.3 6.7 998,877 4.7 0.4 8.5
India ..................... 371,857 3.1 0.4 12.9 688,575 3.6 0.3 8.3
Indonesia ................. 79,538 4.0 0.3 7.5 151,108 3.4 0.3 8.8
Israel .................... 1,258 3.9 0.3 7.7 3,764 8.6 1.2 14.0
Japan .................... 83,625 4.9 0.4 8.2 116,807 9.0 1.4 15.6
Malaysia ................. 6,110 5.1 0.6 11.8 13,763 3.7 0.5 13.5
Pakistan .................. 36,944 5.3 0.5 9.4 79,222 3.4 0.4 11.8
Philippines ................ 19,996 3.6 0.4 11.1 48,088 3.2 0.3 9.4
Singapore ................ 1,022 2.4 0.4 16.7 2,415 4.7 0.5 10.6
South Korea ............... 18,859 3.0 0.2 6.7 38,124 3.8 0.4 10.5
Sri Lanka ................. 7,339 3.6 0.1 2.8 14,941 4.4 0.5 11.4
Thailand .................. 20,607 3.2 0.4 12.5 46,809 3.8 0.5 13.2
Turkey ................... 21,484 3.2 0.3 9.4 46,316 4.6 0.7 15.2
Europe
Austria ................... 6,935 10.4 1.2 11.5 7,549 15.4 2.7 17.5
Belgium .................. 8,628 11.0 1.4 12.7 9,828 14.4 2.6 18.1
Bulgaria .................. 7,251 6.7 0.7 10.4 8,862 11.9 1.6 13.4
Czech Republic ............ 8,925 8.3 1.0 12.0 10,284 13.4 1.9 14.2
Denmark ................. 4,271 9.1 1.2 13.2 5,123 14.4 2.9 20.1
France ................... 41,829 11.4 1.7 14.9 53,880 14.0 3.1 22.1
Germany ................. 68,376 9.7 1.0 10.3 78,289 15.6 2.8 17.9
Greece ................... 7,566 6.8 1.0 14.7 9,643 13.1 2.3 17.6
Hungary .................. 9,338 7.3 0.8 11.0 10,707 13.4 2.1 15.7
Italy ..................... 47,104 8.3 1.1 13.3 56,434 13.1 2.2 16.8
Norway. . . . . . . . . . . . . . . . . . . 3,265 9.7 1.7 17.5 4,086 14.8 3.0 20.3
Poland ................... 24,824 5.2 0.7 13.5 35,574 10.1 1.5 14.9
Russia ................... 102,702 6.2 0.9 14.5 138,655 10.2 1.4 13.7
Sweden .................. 7,014 10.3 1.5 14.6 8,310 16.3 3.2 19.6
United Kingdom ............ 50,616 10.7 1.5 14.0 56,314 14.9 2.7 18.1
Ukraine .................. 37,298 7.6 1.2 15.8 50,044 11.9 1.7 14.3
APPENDIX B.
Detailed Tables
138 An Aging World: 2015 U.S. Census Bureau
Table B-1.
Total Population, Percentage Older, and Percentage Oldest Old: 1950, 1980, 2015 and
2050—Con.
(Numbers in thousands)
Country
2015 2050
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Africa
Egypt .................... 88,487 5.2 0.7 13.2 137,873 13.1 2.8 21.4
Kenya .................... 45,925 2.9 0.4 14.3 70,755 9.2 1.5 16.6
Malawi ................... 17,715 2.7 0.3 10.8 37,407 4.2 0.6 14.0
Morocco .................. 33,323 6.4 1.4 21.0 42,026 18.6 4.9 26.4
South Africa ............... 48,286 6.5 1.0 16.1 49,401 11.4 3.3 28.6
Tunisia ................... 11,037 8.0 1.6 20.3 12,180 24.3 6.8 27.9
Uganda .................. 37,102 2.0 0.3 15.7 93,476 3.4 0.5 15.6
Zimbabwe ................ 14,230 3.5 0.7 19.6 25,198 6.9 1.2 16.9
Asia
Bangladesh ............... 168,958 5.1 0.7 14.0 250,155 14.6 2.9 20.2
China .................... 1,361,513 10.1 1.8 18.2 1,303,723 26.8 8.7 32.7
India ..................... 1,251,696 6.0 0.8 13.2 1,656,554 14.7 3.2 21.7
Indonesia ................. 255,994 6.6 1.1 16.1 300,183 19.0 4.8 24.9
Israel .................... 7,935 10.9 3.0 27.3 10,828 18.1 5.7 31.4
Japan .................... 126,920 26.6 8.0 29.9 107,210 40.1 18.3 45.7
Malaysia ................. 30,514 5.6 0.9 15.4 42,929 16.0 4.3 26.8
Pakistan .................. 199,086 4.3 0.6 14.4 290,848 11.3 2.2 19.5
Philippines ................ 109,616 4.6 0.7 15.4 171,964 11.7 2.7 22.9
Singapore ................ 5,674 8.9 2.0 22.9 8,610 23.9 9.1 38.0
South Korea ............... 49,115 13.0 2.8 21.2 43,369 35.9 14.0 39.1
Sri Lanka ................. 22,053 9.0 1.8 19.4 25,167 21.2 6.5 30.6
Thailand .................. 67,976 9.9 1.9 18.9 66,064 27.4 8.7 31.9
Turkey ................... 82,523 6.9 1.1 16.4 100,955 19.3 4.8 24.9
Table B-1.
Total Population, Percentage Older, and Percentage Oldest Old: 1950, 1980, 2015, and
2050—Con.
(Numbers in thousands)
Country
1950 1980
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Latin America/Caribbean
Argentina ................. 17,150 4.2 0.5 11.9 28,094 8.1 1.1 13.6
Brazil .................... 53,975 3.0 0.3 10.0 121,615 4.1 0.5 12.2
Chile .................... 6,082 4.3 0.5 11.6 11,174 5.5 0.9 16.4
Colombia ................. 12,568 3.1 0.3 9.7 28,356 3.8 0.5 13.2
Costa Rica ................ 966 4.8 0.5 10.4 2,347 4.7 0.8 17.0
Guatemala ................ 3,146 2.5 0.2 8.0 7,013 2.9 0.4 13.8
Jamaica .................. 1,403 3.9 0.2 5.1 2,133 6.7 1.5 22.4
Mexico ................... 27,741 3.5 0.6 17.1 69,325 3.7 0.6 16.2
Peru ..................... 7,632 3.5 0.3 8.6 17,325 3.6 0.4 11.1
Uruguay .................. 2,239 8.2 1.4 17.1 2,914 10.5 1.7 16.2
Northern America/Oceania
Australia .................. 8,219 8.1 1.1 13.6 14,638 9.6 1.7 17.7
Canada .................. 13,737 7.7 1.1 14.3 24,516 9.4 1.8 19.1
New Zealand .............. 1,908 9.0 1.1 12.2 3,113 10.0 1.7 17.0
United States .............. 157,813 8.3 1.1 13.3 230,917 11.2 2.4 21.4
U.S. Census Bureau An Aging World: 2015 139
Table B-1.
Total Population, Percentage Older, and Percentage Oldest Old: 1950, 1980, 2015 and
2050—Con.
(Numbers in thousands)
Country
2015 2050
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Total
population
Percent 65
and over
of total
population
Percent 80
and over
of total
population
Percent 80
and over of
65 and over
Europe
Austria ................... 8,224 19.5 5.3 27.1 7,521 30.1 12.8 42.4
Belgium .................. 10,454 19.3 5.8 30.1 9,883 27.7 11.1 40.2
Bulgaria .................. 6,867 19.8 4.7 23.7 4,651 33.8 10.7 31.6
Czech Republic ............ 10,645 18.0 4.1 22.6 10,210 29.0 9.0 30.9
Denmark ................. 5,582 18.7 4.3 23.1 5,575 24.6 9.7 39.3
France ................... 66,554 18.7 5.9 31.4 69,484 25.8 10.3 40.1
Germany ................. 80,854 21.5 5.8 27.2 71,542 30.1 13.3 44.3
Greece ................... 10,776 20.5 6.2 30.4 10,036 32.1 11.6 36.1
Hungary .................. 9,898 18.2 4.5 24.6 8,490 29.9 9.5 31.9
Italy ..................... 61,855 21.2 6.4 30.4 61,416 31.0 11.9 38.5
Norway. . . . . . . . . . . . . . . . . . . 5,208 16.3 4.2 26.0 6,364 23.0 8.3 36.2
Poland ................... 38,302 15.5 4.0 25.8 32,085 31.7 9.9 31.1
Russia ................... 142,424 13.6 3.2 23.7 129,908 25.7 7.7 30.1
Sweden .................. 9,802 20.0 5.1 25.3 12,011 22.3 8.3 37.1
Ukraine .................. 44,009 16.2 3.5 21.4 33,574 29.3 9.1 31.1
United Kingdom ............ 64,088 17.7 4.8 27.2 71,154 23.6 9.1 38.7
Latin America/Caribbean
Argentina ................. 43,432 11.6 3.0 26.1 53,511 18.9 5.6 29.3
Brazil .................... 204,260 7.8 1.4 17.8 232,304 21.1 5.8 27.4
Chile .................... 17,508 10.2 2.1 20.6 19,688 23.2 8.0 34.7
Colombia ................. 46,737 6.9 1.2 17.6 56,228 19.1 5.9 30.8
Costa Rica ................ 4,814 7.3 1.3 18.4 6,066 20.7 6.2 30.1
Guatemala ................ 14,919 4.3 0.6 14.6 22,995 10.3 2.1 20.4
Jamaica .................. 2,950 7.9 2.0 25.0 3,555 14.5 3.9 26.6
Mexico ................... 121,737 6.8 1.3 19.7 150,568 18.0 5.1 28.2
Peru ..................... 30,445 7.0 1.2 16.7 36,944 17.1 4.5 26.7
Uruguay .................. 3,342 14.0 3.9 28.0 3,495 21.6 7.0 32.3
Northern America/Oceania
Australia .................. 22,751 15.5 4.1 26.3 29,013 22.5 8.1 36.1
Canada .................. 35,100 17.7 5.0 28.2 41,136 26.3 10.6 40.5
New Zealand .............. 4,438 14.6 3.7 25.5 5,199 23.0 8.9 38.5
United States .............. 321,369 14.9 3.8 25.3 398,328 22.1 8.2 37.1
Sources: United Nations Department of Economic and Social Affairs, 2007, World Population Prospects. The 2006 Edition; and U.S. Census Bureau, 2013,
2014a, 2014b; International Data Base, U.S. population estimates, and U.S. population projections.
140 An Aging World: 2015 U.S. Census Bureau
Table B-2.
Percentage Change in Population for Older Age Groups by Country: 2010 to 2030 and
2030 to 2050
Country Percent change 2010–2030 Percent change 2030–2050
55–64 65–79 80 and over 65 and over 55–64 65–79 80 and over 65 and over
Africa ................... 86.2 98.2 136.2 103.2 89.7 106.3 157.8 114.2
Algeria ........................ 125.3 151.9 133.2 148.3 46.1 102.9 197.1 120.1
Angola ........................ 83.1 93.5 158.3 100.0 105.3 110.7 144.1 115.0
Benin ......................... 125.7 109.2 188.5 117.8 102.3 144.8 176.3 149.4
Botswana ...................... 47.2 75.8 96.3 80.3 81.0 70.7 90.9 75.5
Burkina Faso ................... 133.4 86.0 120.1 89.4 101.6 148.5 190.2 153.4
Burundi ....................... 94.5 140.7 130.3 139.4 123.6 118.8 194.4 127.7
Cameroon ..................... 82.4 89.8 139.6 95.6 116.0 119.1 145.0 122.7
Cape Verde .................... 193.0 110.8 46.4 96.9 87.7 83.5 233.3 107.5
Central African Republic .......... 92.4 46.6 50.9 47.2 89.5 97.3 139.9 103.1
Chad ......................... 50.3 63.7 101.7 67.8 112.4 82.0 116.4 86.4
Comoros ...................... 112.1 75.2 148.8 84.1 67.7 143.4 137.5 142.5
Congo (Brazzaville) .............. 150.2 116.8 88.6 112.8 51.2 129.0 226.8 141.2
Congo (Kinshasa) ............... 98.5 92.2 137.5 96.9 125.0 135.4 171.6 139.8
Cote d’Ivoire ................... 81.1 75.0 230.6 89.0 89.5 142.7 139.8 142.3
Djibouti ........................ 102.3 113.9 197.3 122.8 122.8 138.0 192.4 145.7
Egypt ......................... 60.9 137.4 272.3 152.4 73.5 91.1 164.4 103.1
Equatorial Guinea ............... 112.8 66.7 113.8 72.3 85.3 113.2 169.6 121.4
Eritrea ........................ 116.2 59.8 155.2 71.8 82.1 162.4 135.3 157.4
Ethiopia ....................... 89.1 107.2 175.7 114.4 115.6 119.3 170.9 126.3
Gabon ........................ 41.4 53.1 69.8 55.7 66.9 38.3 116.7 51.5
Gambia, The ................... 107.5 110.7 183.8 119.1 113.8 133.7 158.1 137.4
Ghana ........................ 103.9 101.6 120.1 104.4 70.5 104.0 167.5 114.2
Guinea ........................ 78.6 90.2 164.4 98.8 90.4 96.9 154.2 105.6
Guinea-Bissau .................. 59.0 74.1 148.0 81.2 77.1 93.7 111.9 96.1
Kenya ......................... 112.2 128.2 152.5 131.6 110.4 154.5 185.6 159.2
Lesotho ....................... –2.4 13.3 35.2 17.4 94.0 57.6 34.8 52.6
Liberia ........................ 73.1 97.5 205.4 107.0 84.1 118.1 154.2 122.8
Libya ......................... 230.8 148.1 119.9 143.1 33.6 187.0 284.3 202.5
Madagascar .................... 113.3 129.2 116.2 127.3 105.9 115.3 202.7 127.5
Malawi ........................ 62.4 73.5 141.1 80.3 124.7 109.1 117.9 110.3
Mali .......................... 78.7 78.3 85.9 79.2 114.3 105.7 132.3 109.1
Mauritania ..................... 93.8 104.5 160.7 111.1 92.0 110.7 165.2 118.6
Mauritius ...................... 34.1 154.2 131.6 149.6 11.9 20.7 140.6 43.3
Morocco ....................... 100.9 119.3 101.2 115.8 33.3 70.5 180.4 90.1
Mozambique ................... 54.7 48.4 86.2 53.4 118.0 89.5 99.5 91.1
Namibia ....................... 20.7 49.1 140.8 61.9 78.8 44.5 62.9 48.3
Niger ......................... 101.7 97.0 111.5 98.9 108.0 112.3 138.4 115.9
Nigeria ........................ 79.1 77.0 135.4 82.9 88.1 110.4 132.8 113.3
Rwanda ....................... 110.9 152.8 112.1 147.3 108.0 144.3 211.5 152.0
Saint Helena ................... 49.9 78.6 118.7 87.4 –36.9 14.9 93.8 35.1
Sao Tome and Principe ........... 126.9 70.5 15.6 61.2 94.0 155.8 238.2 165.8
Senegal ....................... 113.1 112.5 117.6 113.1 108.0 122.7 197.7 132.5
Seychelles ..................... 147.4 130.8 67.9 117.6 9.7 65.2 222.4 90.6
Sierra Leone ................... 91.5 49.3 160.1 60.4 74.7 129.7 141.0 131.5
Somalia ....................... 154.2 117.8 53.0 110.5 64.2 93.9 293.8 110.2
South Africa .................... 1.7 54.6 131.0 66.1 58.8 12.6 71.7 24.9
South Sudan ................... 206.9 168.6 75.5 155.0 104.0 157.8 296.2 171.6
Sudan ........................ 137.2 98.1 30.7 85.7 81.4 118.8 235.6 133.9
Swaziland ..................... 26.1 55.9 131.8 66.3 111.7 51.0 79.8 56.5
Tanzania ...................... 105.0 91.6 161.8 100.3 108.5 147.9 144.1 147.3
Togo .......................... 101.3 116.6 188.0 125.0 110.2 124.6 178.0 132.6
Tunisia ........................ 105.8 116.8 109.7 115.5 8.3 56.0 173.1 77.2
Uganda ....................... 144.1 90.2 72.8 87.7 149.7 136.8 189.6 143.8
Western Sahara ................. 120.5 139.2 156.5 141.5 92.8 108.5 187.7 119.6
Zambia ........................ 106.8 68.1 88.8 70.7 109.6 136.9 123.6 135.0
Zimbabwe ..................... 44.4 55.0 98.0 62.8 180.3 153.4 81.2 137.4
Asia .................... 71.7 97.5 126.5 102.4 19.0 47.9 144.2 66.0
Afghanistan .................... 84.4 93.6 134.5 97.1 110.4 100.0 163.0 106.4
Armenia ....................... 19.9 84.3 44.4 76.3 30.3 1.0 140.9 23.9
Azerbaijan ..................... 100.6 141.7 46.1 123.0 44.0 32.6 267.5 62.6
Bahrain ....................... 148.7 231.8 149.1 216.1 35.4 93.3 276.6 120.8
U.S. Census Bureau An Aging World: 2015 141
Table B-2.
Percentage Change in Population for Older Age Groups by Country: 2010 to 2030 and
2030 to 2050—Con.
Country Percent change 2010–2030 Percent change 2030–2050
55–64 65–79 80 and over 65 and over 55–64 65–79 80 and over 65 and over
Asia—Con.
Bangladesh .................... 113.6 130.3 177.8 136.5 61.5 105.3 184.2 117.5
Bhutan ........................ 81.4 62.3 170.1 77.6 92.6 131.8 134.4 132.4
Brunei ........................ 96.9 274.6 247.1 270.4 53.6 73.7 260.7 100.3
Burma ........................ 98.7 117.7 110.0 116.6 36.7 75.2 205.7 92.9
Cambodia ..................... 116.0 137.2 125.5 135.6 89.1 90.7 223.9 108.2
China ......................... 62.1 105.9 116.1 107.7 –6.2 19.6 168.1 46.1
Cyprus ........................ 52.1 97.1 151.8 107.4 26.7 39.4 105.3 54.4
Gaza Strip ..................... 164.0 175.9 128.1 167.5 139.4 143.8 259.2 161.2
Georgia ....................... 6.1 38.4 26.9 35.4 26.8 –3.2 61.6 13.1
Hong Kong ..................... 21.7 131.2 81.3 117.4 –15.5 –11.2 110.3 17.0
India .......................... 83.8 98.0 162.4 105.9 34.1 75.2 162.3 88.8
Indonesia ...................... 95.3 99.0 158.7 107.1 12.6 65.6 169.4 83.2
Iran .......................... 125.5 127.5 81.7 118.4 70.6 122.6 203.4 136.0
Iraq .......................... 165.6 154.0 113.8 146.7 72.5 167.2 248.7 180.0
Israel ......................... 41.8 75.4 76.2 75.6 25.3 44.6 70.6 51.9
Japan ......................... –6.8 4.1 110.5 33.6 –29.1 6.6 15.3 10.4
Jordan ........................ 157.2 86.9 174.1 101.2 45.4 119.3 170.7 130.8
Kazakhstan .................... 49.9 109.7 79.9 104.5 44.5 33.5 160.2 53.1
Korea, North ................... 93.4 45.0 180.6 60.3 –4.9 34.1 130.7 53.2
Korea, South ................... 55.7 102.8 182.5 117.0 –20.6 5.6 124.5 33.2
Kuwait ........................ 96.5 198.9 352.6 215.2 49.4 82.5 244.4 107.2
Kyrgyzstan ..................... 57.2 122.8 20.3 101.0 64.8 44.7 226.7 67.9
Laos .......................... 107.7 101.8 106.2 102.3 90.9 104.9 197.6 116.8
Lebanon. . . . . . . . . . . . . . . . . . . . . . . 61.5 66.1 133.0 76.8 18.6 47.7 119.1 62.7
Macau ........................ 85.7 232.6 115.6 199.8 5.3 17.7 200.0 54.5
Malaysia ...................... 91.3 165.8 202.1 171.2 27.8 62.3 201.3 85.2
Maldives ...................... 128.3 103.8 116.9 105.9 107.4 120.2 223.7 138.0
Mongolia ...................... 156.3 158.8 113.8 151.9 50.9 93.0 286.1 118.2
Nepal ......................... 90.1 91.9 169.8 100.7 98.2 111.8 168.3 120.4
Oman ......................... 100.3 94.8 204.2 110.6 139.9 218.3 135.5 201.1
Pakistan ....................... 105.2 97.0 115.0 99.4 97.2 100.5 190.0 113.3
Philippines ..................... 91.7 127.5 175.0 134.4 60.6 90.0 175.7 104.5
Qatar ......................... 125.0 276.4 269.6 275.7 35.4 94.5 279.5 111.9
Saudi Arabia ................... 150.2 161.1 172.6 162.7 87.8 140.6 259.1 157.8
Singapore ..................... 62.2 188.9 226.0 197.5 65.7 54.9 178.8 86.3
Sri Lanka ...................... 42.6 109.7 151.3 117.6 9.8 35.4 112.2 52.3
Syria ......................... 137.3 130.0 125.4 129.3 83.7 129.4 231.8 146.6
Taiwan ........................ 37.0 121.0 93.8 114.4 –9.1 9.6 121.8 34.2
Tajikistan ...................... 157.6 141.2 50.9 128.3 87.3 106.8 362.1 131.1
Thailand ....................... 63.5 111.3 143.1 116.7 –9.1 24.0 146.1 47.3
Timor-Leste .................... 85.9 118.5 253.9 131.2 80.3 70.5 185.8 87.0
Turkey ........................ 79.3 115.3 151.7 120.7 23.7 65.9 171.4 83.7
Turkmenistan ................... 101.9 180.1 79.0 163.3 68.9 65.1 281.7 89.5
United Arab Emirates ............ 99.2 164.2 230.3 171.2 34.1 100.3 225.9 116.4
Uzbekistan ..................... 110.2 165.1 51.6 139.7 76.0 72.6 254.0 98.3
Vietnam ....................... 118.0 159.8 65.2 139.3 39.2 66.9 242.2 93.1
West Bank ..................... 184.1 148.0 118.1 142.5 85.1 126.5 241.5 145.6
Yemen ........................ 96.5 136.5 96.3 130.2 168.1 158.8 183.8 162.2
Europe .................. 10.7 37.6 48.9 40.5 –7.5 2.7 50.9 16.1
Albania ........................ 23.7 71.3 126.9 80.7 54.1 2.9 94.0 22.3
Andorra ....................... 70.8 122.7 66.2 105.4 –53.3 7.1 116.2 34.1
Austria ........................ 24.6 38.7 48.5 41.4 –18.2 –12.7 56.9 7.5
Belarus ....................... 6.4 45.7 22.5 40.0 6.4 6.2 76.0 21.2
Belgium ....................... 3.8 41.2 38.0 40.3 –9.5 –11.3 45.4 5.1
Bosnia and Herzegovina .......... 26.1 67.3 122.6 75.5 –15.8 –0.6 117.8 21.7
Bulgaria ....................... –14.6 5.5 44.8 14.3 –23.4 2.6 19.9 7.5
Croatia ........................ –6.2 34.5 49.9 38.3 –7.3 –3.7 43.7 9.1
Czech Republic ................. –0.1 33.6 88.1 46.6 –9.5 23.2 25.6 23.9
Denmark ...................... 4.9 31.0 75.1 42.1 –9.2 –6.9 33.7 5.7
Estonia ........................ –11.1 10.8 39.8 17.9 –10.8 –5.7 26.3 3.6
Faroe Islands ................... 8.8 47.6 59.2 50.8 14.2 –12.5 47.4 5.1
142 An Aging World: 2015 U.S. Census Bureau
Table B-2.
Percentage Change in Population for Older Age Groups by Country: 2010 to 2030 and
2030 to 2050—Con.
Country Percent change 2010–2030 Percent change 2030–2050
55–64 65–79 80 and over 65 and over 55–64 65–79 80 and over 65 and over
Europe—Con.
Finland ........................ –21.6 39.7 76.5 49.6 0.7 –14.4 21.3 –3.0
France ........................ 5.8 49.4 50.7 49.8 –9.8 –3.1 37.6 9.9
Germany ...................... 12.0 22.1 51.6 29.5 –17.5 –22.2 49.3 –1.2
Gibraltar ....................... –12.0 13.1 86.6 30.7 31.7 34.2 8.3 25.4
Greece ........................ 24.6 20.3 43.0 26.5 –24.6 13.0 43.3 22.4
Guernsey ...................... 12.2 48.1 55.1 50.2 –6.6 –3.7 45.9 11.7
Hungary ....................... –2.1 20.3 58.4 29.4 –13.5 13.1 29.0 17.7
Iceland ........................ 20.9 83.5 64.5 78.0 9.4 8.1 70.5 24.7
Ireland ........................ 50.3 73.5 97.0 79.2 –0.0 49.3 79.3 57.3
Isle of Man ..................... 19.5 49.2 65.3 53.9 –11.8 –3.4 43.6 11.4
Italy .......................... 32.7 25.7 43.0 30.8 –24.2 7.6 43.8 19.1
Jersey ........................ 8.3 60.1 70.2 62.9 28.7 –19.2 66.8 5.4
Kosovo ........................ 74.3 76.6 93.7 79.4 49.4 59.2 147.2 74.6
Latvia ......................... 4.7 10.8 37.9 16.6 –5.5 –2.2 42.9 9.3
Liechtenstein ................... 21.9 86.2 133.0 97.4 –7.7 –3.9 64.9 15.5
Lithuania ...................... 18.9 30.7 41.4 33.6 –2.3 2.2 47.4 15.2
Luxembourg .................... 28.9 61.1 57.2 60.0 14.6 8.3 72.3 25.6
Macedonia ..................... 18.4 54.9 114.0 64.9 2.7 17.6 85.2 32.3
Malta ......................... –12.1 55.2 126.6 71.3 10.5 3.9 28.9 11.3
Moldova ....................... –17.4 42.9 41.2 42.6 2.6 –9.3 63.6 4.6
Monaco ....................... 4.5 57.2 154.5 90.6 –36.5 –12.9 48.9 15.4
Montenegro .................... 20.8 64.6 23.7 51.9 –11.8 21.3 82.5 36.7
Netherlands .................... 6.2 54.4 88.7 63.2 –7.4 –11.9 47.0 5.6
Norway. . . . . . . . . . . . . . . . . . . . . . . . 22.6 58.7 57.7 58.4 11.1 14.0 51.9 25.4
Poland ........................ –10.0 63.7 62.3 63.3 1.3 11.1 47.8 20.4
Portugal ....................... 24.9 24.7 45.6 30.5 –20.4 15.3 38.1 22.3
Romania ...................... 22.2 19.0 52.9 26.2 –17.8 29.4 62.2 37.9
Russia ........................ 0.0 52.3 34.0 48.2 9.1 5.3 76.3 19.8
San Marino .................... 44.5 55.3 66.6 58.6 –24.2 –0.0 62.9 19.6
Serbia ........................ –11.6 22.0 42.0 26.3 –8.9 –1.4 46.3 10.3
Slovakia ....................... 7.2 65.1 69.3 66.1 –2.0 19.0 61.5 29.5
Slovenia ....................... 0.2 40.7 64.6 46.4 –22.3 –2.4 49.4 11.6
Spain ......................... 60.8 45.8 48.3 46.5 –21.9 31.2 68.7 42.1
Sweden ....................... 8.4 23.6 62.7 34.5 18.1 7.2 23.8 12.8
Switzerland .................... 26.9 46.3 60.8 50.4 2.0 7.5 54.1 21.6
Ukraine ....................... –5.7 22.6 28.2 23.8 –0.7 0.9 51.4 12.6
United Kingdom ................. 15.6 39.5 53.9 43.6 4.0 1.4 45.9 15.0
Latin America and
the Caribbean ........... 70.9 104.8 126.0 108.9 29.4 52.4 128.6 68.4
Anguilla ....................... 142.1 202.5 119.4 183.3 16.8 39.0 236.4 74.2
Antigua and Barbuda ............. 85.6 161.6 95.1 146.5 14.6 34.8 190.3 62.7
Argentina ...................... 27.6 47.7 62.1 51.4 31.9 44.9 57.4 48.3
Aruba ......................... 25.8 119.5 204.4 133.1 23.7 9.0 108.3 29.8
Bahamas, The .................. 86.7 130.4 182.5 138.8 5.8 40.7 159.8 63.6
Barbados ...................... 39.9 131.6 68.6 115.5 –13.9 0.2 133.9 27.0
Belize ......................... 128.7 145.8 111.2 139.5 83.7 98.7 236.4 120.7
Bolivia ........................ 73.7 112.6 106.2 111.3 86.9 96.8 126.8 102.6
Brazil ......................... 67.0 113.1 148.6 119.2 20.9 53.6 137.8 70.1
Cayman Islands ................. 56.4 191.1 236.3 199.7 21.3 14.9 144.6 42.5
Chile ......................... 58.3 111.2 132.2 115.4 16.6 17.9 125.2 41.3
Colombia ...................... 81.7 148.3 163.0 150.7 28.4 35.8 181.3 61.5
Costa Rica ..................... 86.5 157.1 174.2 160.2 34.8 49.6 172.5 73.1
Cuba ......................... 61.2 60.2 97.5 67.7 –28.4 –2.3 102.2 22.6
Curacao ....................... –11.4 78.6 131.2 89.1 29.9 –21.7 59.7 –1.8
Dominica ...................... 64.7 69.2 41.5 62.2 6.5 25.2 137.2 50.0
Dominican Republic .............. 84.7 117.5 153.2 124.1 35.3 49.6 146.0 69.5
Ecuador ....................... 78.1 116.4 126.1 118.5 50.5 64.4 129.3 78.6
El Salvador .................... 66.1 79.0 104.0 83.8 45.6 62.9 119.3 75.0
Grenada ....................... 53.2 91.0 108.6 93.9 32.3 12.6 123.5 32.2
Guatemala ..................... 63.1 113.6 159.5 120.6 130.5 100.0 135.9 106.4
Guyana ....................... 53.6 129.6 96.8 123.8 41.2 37.0 170.6 57.8
U.S. Census Bureau An Aging World: 2015 143
Table B-2.
Percentage Change in Population for Older Age Groups by Country: 2010 to 2030 and
2030 to 2050—Con.
Country Percent change 2010–2030 Percent change 2030–2050
55–64 65–79 80 and over 65 and over 55–64 65–79 80 and over 65 and over
Latin America and
the Caribbean—Con.
Haiti .......................... 71.2 71.1 132.7 78.1 82.6 97.9 149.2 105.5
Honduras ...................... 115.8 131.7 163.8 136.9 85.0 105.2 181.3 118.9
Jamaica ....................... 55.5 37.8 57.2 42.5 80.5 68.8 68.4 68.7
Mexico ........................ 98.1 109.4 138.0 114.7 28.5 64.0 147.5 81.3
Montserrat ..................... 183.7 98.2 2.6 76.8 –6.6 107.8 286.3 131.0
Nicaragua ..................... 118.4 124.5 136.1 126.5 78.2 98.5 185.7 113.9
Panama ....................... 84.9 104.5 148.2 113.1 25.6 57.8 125.6 73.4
Paraguay ...................... 90.3 130.6 127.6 130.0 63.9 65.3 147.6 81.9
Peru .......................... 73.2 95.0 158.4 104.6 39.6 54.8 139.4 70.9
Puerto Rico .................... –1.5 34.7 97.8 49.8 –0.6 0.4 30.8 10.0
Saint Barthelemy ................ 3.0 107.4 267.4 133.5 –26.0 –21.0 67.6 1.7
Saint Kitts and Nevis ............. 95.2 190.2 46.5 150.7 8.9 30.4 210.0 59.2
Saint Lucia ..................... 98.5 140.7 84.0 122.5 –0.0 44.7 161.5 75.7
Saint Martin .................... 23.5 124.3 207.0 139.9 12.7 19.5 82.6 34.7
Saint Vincent and the Grenadines ... 67.3 111.6 60.2 100.0 –1.8 21.1 153.3 45.0
Sint Maarten ................... 67.8 446.1 595.6 462.9 –4.0 –20.9 280.0 20.9
Suriname ...................... 140.3 125.0 93.8 119.6 22.1 77.0 243.1 102.1
Trinidad and Tobago ............. 19.0 118.7 129.3 120.6 3.3 12.7 115.8 31.8
Turks and Caicos Islands. . . . . . . . . . 351.3 265.9 144.7 238.4 22.0 189.1 330.8 212.3
Uruguay ....................... 20.8 29.8 34.1 30.9 20.5 19.3 51.8 28.1
Venezuela ..................... 76.4 148.0 129.0 144.5 42.2 56.6 151.8 73.3
Virgin Islands, British ............. 100.9 243.9 206.8 236.4 38.9 49.9 197.9 76.9
Virgin Islands, U.S ............... 0.7 50.5 220.5 80.1 –33.2 –15.7 35.5 0.2
Northern America ......... 7.7 81.3 68.5 77.7 16.9 2.6 68.7 20.2
Bermuda ...................... –1.4 90.3 114.8 96.2 –4.3 –31.1 66.9 –5.3
Canada ....................... 5.8 84.0 81.7 83.3 12.2 –5.2 57.0 12.9
Greenland ..................... 14.1 123.2 179.9 130.5 4.5 –37.8 168.4 –5.8
Saint Pierre and Miquelon ......... 16.5 42.6 83.2 53.3 –57.9 –11.5 48.2 7.3
United States ................... 5.6 82.7 72.2 79.8 19.6 –1.0 59.0 15.1
Oceania ................. 32.4 77.5 87.1 80.0 20.2 23.9 65.3 35.4
American Samoa ................ 85.5 198.7 163.1 193.5 26.8 31.2 301.1 66.9
Australia ....................... 21.2 70.3 82.0 73.6 14.9 15.6 54.3 27.1
Cook Islands ................... 8.5 21.7 77.0 30.1 –36.7 –22.8 97.3 1.8
Fiji 49.2 125.9 280.0 141.1 33.8 49.7 164.8 67.5
French Polynesia ................ 90.6 141.9 241.6 156.3 20.8 42.3 172.0 67.3
Guam ......................... 41.2 117.9 189.5 130.4 19.6 15.8 123.9 39.6
Kiribati ........................ 81.8 120.4 146.2 123.5 75.7 71.3 229.0 92.1
Marshall Islands ................. 85.7 209.4 183.8 205.4 71.7 113.6 216.6 128.9
Micronesia, Federated States of .... 29.9 112.7 57.8 105.5 18.9 34.6 131.7 44.4
Nauru ......................... 64.0 339.4 213.3 326.5 67.1 98.4 444.7 124.4
New Caledonia ................. 87.2 92.4 206.7 110.8 24.1 66.5 124.5 80.1
New Zealand ................... 27.0 77.2 78.3 77.5 4.9 4.2 68.9 22.2
Northern Mariana Islands ......... 114.1 457.2 394.3 449.3 48.6 59.1 403.2 98.1
Palau ......................... 65.3 181.9 108.0 160.2 –3.1 –4.7 202.1 43.9
Papua New Guinea .............. 104.7 125.7 222.7 136.6 49.6 98.2 182.4 111.0
Samoa ........................ 90.1 95.6 96.0 95.6 52.8 52.1 171.8 72.7
Solomon Islands ................ 155.8 111.0 169.1 120.3 70.7 147.1 180.6 153.6
Tonga ......................... 73.5 31.7 79.7 40.0 4.1 56.6 133.5 73.7
Tuvalu ........................ –6.1 107.7 51.7 98.9 118.2 –5.5 160.0 14.3
Vanuatu ....................... 119.4 158.6 232.8 167.6 72.5 104.2 250.8 126.2
Wallis and Futuna ............... 42.5 99.6 171.8 113.4 31.0 51.1 97.8 62.5
Source: U.S. Census Bureau, 2013; International Data Base.
144 An Aging World: 2015 U.S. Census Bureau
Table B-3.
Median Age: 2015, 2030, and 2050
(In years)
Country 2015 2030 2050
Africa
Algeria .............................. 27.5 31.8 37.0
Angola .............................. 18.0 19.5 22.6
Benin ............................... 17.9 20.8 26.1
Botswana ............................ 23.1 25.6 29.0
Burkina Faso ......................... 17.1 18.6 21.7
Burundi ............................. 17.0 17.9 20.4
Cameroon ........................... 24.5 31.3 38.6
Cape Verde .......................... 18.4 20.4 24.3
Central African Republic ................ 19.5 21.3 24.8
Chad ............................... 17.4 20.9 24.8
Comoros ............................ 19.4 25.1 33.4
Congo (Brazzaville) .................... 19.8 20.7 23.5
Congo (Kinshasa) ..................... 18.1 22.1 28.8
Cote d’Ivoire ......................... 20.5 24.5 30.4
Djibouti .............................. 23.2 28.0 33.3
Egypt ............................... 25.3 28.8 34.1
Equatorial Guinea ..................... 19.5 22.6 28.4
Eritrea .............................. 19.3 23.7 30.1
Ethiopia ............................. 17.7 19.8 24.3
Gabon .............................. 18.6 19.4 21.6
Gambia, The ......................... 20.5 24.9 31.8
Ghana .............................. 20.9 22.8 26.0
Guinea .............................. 18.8 20.3 23.8
Guinea-Bissau ........................ 19.9 22.3 26.7
Kenya ............................... 19.3 25.2 33.9
Lesotho ............................. 23.8 26.5 32.5
Liberia .............................. 18.1 21.6 26.8
Libya ............................... 28.0 34.2 40.2
Madagascar .......................... 19.4 22.6 28.8
Malawi .............................. 17.5 19.4 23.7
Mali ................................ 16.1 18.2 23.7
Mauritania ........................... 20.1 23.2 28.5
Mauritius ............................ 34.4 39.3 44.4
Morocco ............................. 28.5 34.0 39.4
Mozambique ......................... 17.0 18.5 21.6
Namibia ............................. 23.1 28.5 34.1
Niger ............................... 15.2 17.7 23.0
Nigeria .............................. 18.2 20.0 23.1
Rwanda ............................. 18.8 21.7 24.3
Saint Helena ......................... 41.0 46.7 49.6
Sao Tome and Principe ................. 17.9 23.0 31.1
Senegal ............................. 18.5 21.6 26.8
Seychelles ........................... 34.4 41.5 49.2
Sierra Leone ......................... 19.0 20.0 22.2
Somalia ............................. 17.8 19.5 23.2
South Africa .......................... 25.9 29.3 33.4
South Sudan ......................... 17.0 20.7 26.7
Sudan .............................. 19.3 24.6 31.5
Swaziland ........................... 21.2 25.0 29.6
Tanzania ............................ 17.5 19.8 23.5
Togo ................................ 19.6 21.4 25.1
Tunisia .............................. 31.9 38.8 44.0
Uganda ............................. 15.6 17.4 21.9
Western Sahara ....................... 20.9 23.9 28.8
Zambia .............................. 16.7 17.6 19.8
Zimbabwe ........................... 20.5 22.0 25.9
Asia
Afghanistan .......................... 18.4 20.7 25.6
Armenia ............................. 34.2 42.4 51.3
Azerbaijan ........................... 30.5 37.4 42.3
Bahrain ............................. 31.8 34.1 36.9
Bangladesh .......................... 24.7 30.8 37.7
U.S. Census Bureau An Aging World: 2015 145
Table B-3.
Median Age: 2015, 2030, and 2050—Con.
(In years)
Country 2015 2030 2050
Asia—Con.
Bhutan .............................. 26.7 33.6 41.7
Brunei .............................. 29.6 33.9 38.1
Burma .............................. 28.3 33.4 38.0
Cambodia ........................... 24.5 29.3 35.2
China ............................... 37.0 42.9 48.9
Cyprus .............................. 36.1 41.8 48.7
Gaza Strip ........................... 18.4 23.9 32.9
Georgia ............................. 37.9 41.8 45.1
Hong Kong ........................... 43.6 49.5 54.1
India ................................ 27.3 31.8 37.2
Indonesia ............................ 29.6 34.4 40.9
Iran ................................ 28.8 36.9 42.5
Iraq ................................ 21.8 26.5 33.2
Israel ............................... 30.1 32.9 38.2
Japan ............................... 46.5 52.6 56.4
Jordan .............................. 23.0 26.0 30.7
Kazakhstan .......................... 30.0 34.9 38.4
Korea, North ......................... 33.6 37.3 41.8
Korea, South ......................... 40.8 48.3 55.1
Kuwait .............................. 29.0 31.0 33.9
Kyrgyzstan ........................... 26.0 29.3 34.5
Laos ................................ 22.3 27.8 34.2
Lebanon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.9 39.2 46.8
Macau .............................. 38.2 46.2 55.0
Malaysia ............................ 27.9 31.9 36.7
Maldives ............................ 27.4 35.0 42.3
Mongolia ............................ 27.5 33.7 39.2
Nepal ............................... 23.4 30.3 36.6
Oman ............................... 25.1 28.4 33.2
Pakistan ............................. 23.0 29.0 35.9
Philippines ........................... 23.7 27.4 32.5
Qatar ............................... 32.8 34.8 35.2
Saudi Arabia ......................... 26.8 31.9 36.5
Singapore ........................... 34.0 39.2 47.0
Sri Lanka ............................ 32.1 36.5 41.3
Syria ............................... 23.5 29.5 36.9
Taiwan .............................. 39.7 47.5 54.9
Tajikistan ............................ 23.9 28.2 34.4
Thailand ............................. 36.7 42.8 48.5
Timor-Leste .......................... 18.6 21.7 28.6
Turkey .............................. 30.0 35.2 41.4
Turkmenistan ......................... 27.1 33.3 38.1
United Arab Emirates .................. 30.3 30.3 30.8
Uzbekistan ........................... 27.6 35.1 42.3
Vietnam ............................. 29.6 36.6 43.3
West Bank ........................... 22.7 28.6 36.0
Yemen .............................. 18.9 24.2 32.0
Europe
Albania .............................. 32.0 39.4 49.8
Andorra ............................. 43.0 52.2 54.2
Austria .............................. 44.6 47.6 49.6
Belarus ............................. 39.6 44.8 48.3
Belgium ............................. 43.3 45.5 47.2
Bosnia and Herzegovina ................ 41.2 47.2 53.0
Bulgaria ............................. 42.8 48.4 53.0
Croatia .............................. 42.3 46.4 49.7
Czech Republic ....................... 41.3 46.6 47.8
Denmark ............................ 41.8 42.4 45.0
Estonia .............................. 41.5 46.3 51.7
Faroe Islands ......................... 37.7 38.0 40.1
Finland .............................. 43.3 45.3 46.8
France .............................. 41.1 42.8 44.0
146 An Aging World: 2015 U.S. Census Bureau
Table B-3.
Median Age: 2015, 2030, and 2050—Con.
(In years)
Country 2015 2030 2050
Europe—Con.
Germany ............................ 46.5 48.5 49.1
Gibraltar ............................. 34.2 38.6 43.0
Greece .............................. 43.8 48.8 50.3
Guernsey ............................ 43.4 45.8 47.6
Hungary ............................. 41.4 46.7 49.5
Iceland .............................. 36.6 40.4 44.1
Ireland .............................. 36.1 40.1 42.1
Isle of Man ........................... 43.7 45.4 47.0
Italy ................................ 44.8 49.0 49.4
Jersey .............................. 39.0 40.1 44.3
Kosovo .............................. 28.2 34.1 41.1
Latvia ............................... 41.7 46.4 52.3
Liechtenstein ......................... 42.7 44.8 45.9
Lithuania ............................ 41.5 46.6 53.4
Luxembourg .......................... 39.6 39.9 41.4
Macedonia ........................... 37.2 42.5 47.6
Malta ............................... 41.2 46.2 50.3
Moldova ............................. 36.0 42.5 47.5
Monaco ............................. 51.7 63.4 71.7
Montenegro .......................... 39.7 46.9 50.8
Netherlands .......................... 42.3 43.2 44.4
Norway. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.1 41.1 43.6
Poland .............................. 39.9 46.6 51.9
Portugal ............................. 41.5 46.6 49.4
Romania ............................ 40.2 46.6 51.5
Russia .............................. 39.1 44.0 45.7
San Marino .......................... 43.9 46.7 48.6
Serbia .............................. 42.1 46.1 49.6
Slovakia ............................. 39.2 45.7 50.1
Slovenia ............................. 43.8 49.4 52.7
Spain ............................... 42.0 47.2 49.2
Sweden ............................. 41.2 41.5 42.1
Switzerland .......................... 42.1 44.1 45.0
Ukraine ............................. 40.8 45.8 50.4
United Kingdom ....................... 40.4 41.9 43.3
Latin America and the Caribbean
Anguilla ............................. 34.3 38.6 41.6
Antigua and Barbuda ................... 31.4 35.4 40.4
Argentina ............................ 31.4 34.9 39.7
Aruba ............................... 39.0 42.1 44.5
Bahamas, The ........................ 31.5 36.1 41.0
Barbados ............................ 38.0 42.8 46.1
Belize ............................... 22.1 26.7 32.8
Bolivia .............................. 23.7 28.6 35.1
Brazil ............................... 31.1 36.9 43.4
Cayman Islands ....................... 39.7 41.7 43.8
Chile ............................... 33.7 39.2 44.5
Colombia ............................ 29.3 35.1 41.6
Costa Rica ........................... 30.4 36.7 42.4
Cuba ............................... 40.4 44.3 49.2
Curacao ............................. 36.1 39.3 43.3
Dominica ............................ 32.6 40.1 50.1
Dominican Republic .................... 27.4 32.6 38.4
Ecuador ............................. 27.0 32.6 39.7
El Salvador .......................... 26.1 34.1 44.3
Grenada ............................. 30.4 38.1 42.9
Guatemala ........................... 21.4 26.8 34.0
Guyana ............................. 25.4 31.9 40.2
Haiti ................................ 22.5 28.1 34.6
Honduras ............................ 22.3 27.8 34.5
Jamaica ............................. 25.3 30.9 38.2
Mexico .............................. 27.6 32.7 39.3
U.S. Census Bureau An Aging World: 2015 147
Table B-3.
Median Age: 2015, 2030, and 2050—Con.
(In years)
Country 2015 2030 2050
Latin America and the Caribbean—Con.
Montserrat ........................... 31.9 38.3 49.7
Nicaragua ........................... 24.7 32.4 41.6
Panama ............................. 28.6 33.1 39.3
Paraguay ............................ 27.3 34.4 42.0
Peru ................................ 27.3 33.0 39.5
Puerto Rico .......................... 39.1 44.3 51.1
Saint Barthelemy ...................... 43.0 48.4 47.7
Saint Kitts and Nevis ................... 34.0 41.2 48.5
Saint Lucia ........................... 33.5 43.8 55.8
Saint Martin .......................... 32.0 34.9 36.4
Saint Vincent and the Grenadines ......... 32.5 40.3 46.6
Sint Maarten ......................... 40.4 41.3 44.8
Suriname ............................ 29.1 34.6 41.7
Trinidad and Tobago ................... 35.0 44.0 47.7
Turks and Caicos Islands. . . . . . . . . . . . . . . . 32.4 38.1 42.3
Uruguay ............................. 34.5 38.1 43.7
Venezuela ........................... 27.2 32.0 37.0
Virgin Islands, British ................... 35.9 39.7 41.9
Virgin Islands, U.S. .................... 44.9 53.7 59.4
Northern America
Bermuda ............................ 43.1 44.3 45.6
Canada ............................. 41.8 44.3 45.4
Greenland ........................... 33.7 36.9 40.6
Saint Pierre and Miquelon ............... 45.2 54.3 57.8
United States ......................... 37.7 39.6 40.6
Oceania
American Samoa ...................... 28.8 38.0 46.9
Australia ............................. 38.4 40.7 42.7
Cook Islands ......................... 35.2 42.3 46.4
Fiji ................................. 28.2 33.4 39.3
French Polynesia ...................... 31.0 37.8 44.2
Guam ............................... 30.1 34.3 39.9
Kiribati .............................. 23.9 29.5 35.1
Marshall Islands ....................... 22.6 27.7 36.0
Micronesia, Federated States of .......... 24.2 30.5 37.3
Nauru ............................... 25.7 29.3 33.2
New Caledonia ....................... 31.4 36.2 41.8
New Zealand ......................... 37.7 40.1 42.9
Northern Mariana Islands ............... 32.1 40.5 48.8
Palau ............................... 33.2 36.5 41.2
Papua New Guinea .................... 22.6 27.0 32.6
Samoa .............................. 23.5 29.7 36.8
Solomon Islands ...................... 21.9 26.9 33.9
Tonga ............................... 22.3 28.6 43.6
Tuvalu .............................. 25.2 28.8 32.2
Vanuatu ............................. 21.4 26.8 34.3
Wallis and Futuna ..................... 30.9 39.8 48.4
Source: U.S. Census Bureau, 2013; International Data Base.
148 An Aging World: 2015 U.S. Census Bureau
Table B-4.
Sex Ratio for Population 35 Years and Over by Age: 2015, 2030, and 2050
(Men per 100 women)
Country
2015 2030 2050
35–49 50–64 65–79
80 and
over 35–49 50–64 65–79 80+ 35–49 50–64 65–79
80 and
over
Africa
Algeria ....................... 102.3 102.5 89.4 73.8 102.8 100.8 95.5 72.6 104.1 101.9 93.0 72.7
Angola ....................... 101.9 94.4 87.5 75.2 102.6 98.4 86.2 72.5 101.6 99.5 90.7 67.5
Benin ........................ 103.2 81.6 65.7 66.0 102.0 100.1 76.0 53.1 101.9 98.9 91.4 66.3
Botswana ..................... 132.0 90.9 69.5 56.3 135.7 142.8 77.4 51.1 149.3 155.1 128.4 71.5
Burkina Faso .................. 105.0 83.7 60.6 58.9 101.2 99.1 74.6 44.5 98.5 95.3 86.0 59.0
Burundi ...................... 100.0 90.8 76.0 61.3 98.2 97.0 83.8 63.9 97.9 94.3 88.3 67.0
Cameroon .................... 101.5 96.2 88.8 75.9 100.9 98.6 88.1 72.0 98.7 97.0 90.0 67.7
Cape Verde ................... 91.5 80.9 62.7 54.9 95.5 89.6 74.6 48.1 95.4 93.2 83.0 56.3
Central African Republic ......... 99.6 88.7 65.1 59.7 101.3 94.9 80.1 50.5 99.8 97.0 85.6 62.7
Chad ........................ 78.8 80.7 71.9 62.8 89.1 74.2 72.3 57.3 96.1 88.0 68.9 53.2
Comoros ..................... 91.3 82.6 87.6 90.3 89.1 88.9 77.2 68.8 91.1 86.8 79.5 62.5
Congo (Brazzaville) ............. 110.7 103.7 80.9 60.2 93.3 107.7 96.7 67.6 99.9 93.1 89.6 79.1
Congo (Kinshasa) .............. 99.6 92.0 75.1 57.1 99.5 94.7 81.1 57.9 99.4 95.5 83.9 61.1
Cote d’Ivoire .................. 107.6 102.9 93.6 88.8 103.4 102.7 89.4 70.0 103.0 99.9 89.2 65.7
Djibouti ....................... 67.3 81.3 84.1 63.3 71.6 63.4 68.8 60.8 82.2 70.0 56.2 40.5
Egypt ........................ 101.8 96.7 86.7 56.9 105.0 98.5 83.4 54.3 103.1 101.0 92.1 51.7
Equatorial Guinea .............. 99.5 78.8 72.2 73.5 102.1 96.3 72.0 56.0 101.8 99.5 89.2 61.3
Eritrea ....................... 99.1 82.1 74.9 75.9 98.1 94.6 74.4 55.5 99.5 94.9 83.6 62.0
Ethiopia ...................... 99.4 95.8 84.2 66.5 96.6 94.5 82.8 61.6 97.0 92.1 82.2 58.2
Gabon ....................... 98.0 95.7 79.9 52.9 110.3 86.3 77.5 56.4 112.5 103.1 76.9 48.9
Gambia, The .................. 96.4 93.2 89.5 76.4 96.2 93.3 82.0 64.7 98.5 93.3 82.1 57.2
Ghana ....................... 93.2 96.0 87.6 79.5 93.6 90.4 86.8 67.9 94.8 89.9 80.6 62.1
Guinea ....................... 100.3 93.3 81.5 63.9 101.3 96.2 84.3 63.8 100.7 97.6 88.6 64.2
Guinea-Bissau ................. 101.6 70.9 60.5 58.4 98.6 93.8 62.6 42.3 98.5 92.1 79.0 54.2
Kenya ........................ 106.0 87.9 77.6 72.2 101.4 103.2 79.2 59.9 99.8 99.5 92.2 64.8
Lesotho ...................... 105.3 113.0 109.9 81.1 95.8 127.2 113.3 90.7 97.7 116.3 121.1 96.5
Liberia ....................... 100.5 94.4 97.9 87.7 96.4 95.8 82.3 72.5 99.7 91.5 84.9 59.6
Libya ........................ 110.1 101.2 104.1 87.3 111.2 108.2 92.4 77.1 103.6 105.6 102.0 69.8
Madagascar ................... 99.6 96.1 83.3 80.0 99.1 97.7 91.3 70.4 99.0 96.5 90.4 71.9
Malawi ....................... 107.7 87.0 74.5 63.3 103.7 103.0 74.9 55.9 103.2 100.1 89.8 59.3
Mali ......................... 90.5 100.2 101.6 89.8 84.3 93.7 95.3 81.8 89.8 84.9 81.7 70.1
Mauritania .................... 84.1 83.6 75.3 63.4 87.3 80.9 75.8 58.9 91.0 85.4 73.4 54.5
Mauritius ..................... 99.5 92.3 74.0 47.4 100.7 94.7 78.9 49.8 102.6 97.2 84.0 53.6
Morocco ...................... 92.2 97.0 86.7 65.8 94.7 90.6 88.2 59.6 97.0 93.2 83.3 57.5
Mozambique .................. 90.2 92.5 86.7 75.1 89.5 89.8 86.3 70.0 100.3 92.4 78.2 60.6
Namibia ...................... 116.8 84.9 77.3 65.3 121.9 114.1 68.8 52.7 127.3 133.4 108.8 49.9
Niger ........................ 102.8 106.8 104.4 99.0 100.4 106.3 106.4 93.3 97.8 99.2 99.3 84.9
Nigeria ....................... 107.0 97.6 92.1 82.7 104.8 102.7 88.6 74.5 102.6 101.3 92.4 71.0
Rwanda ...................... 102.1 93.6 71.4 60.5 97.8 99.1 85.8 59.5 98.7 94.6 87.7 69.8
Saint Helena .................. 98.4 103.8 122.6 54.6 99.9 95.7 92.5 83.5 103.4 99.1 87.2 60.7
Sao Tome and Principe .......... 94.9 87.2 82.1 78.5 96.9 94.8 79.8 62.9 99.6 95.8 86.9 66.1
Senegal ...................... 79.7 76.9 82.9 76.5 87.4 76.4 69.7 64.5 92.5 86.3 71.0 51.6
Seychelles .................... 112.3 105.2 76.1 33.0 124.7 110.2 88.0 41.2 135.6 127.0 100.9 52.1
Sierra Leone .................. 91.9 87.8 72.7 77.3 91.1 87.3 78.4 53.8 95.2 87.2 77.3 56.7
Somalia ...................... 112.5 101.1 64.0 61.8 102.9 108.6 93.4 48.3 95.2 97.2 89.1 76.5
South Africa ................... 112.7 78.4 68.1 52.8 125.7 106.8 64.6 46.4 119.8 123.2 106.3 46.8
South Sudan .................. 88.2 112.2 127.7 118.9 100.7 85.9 100.5 97.5 102.6 103.9 75.3 67.0
Sudan ....................... 90.1 107.6 119.7 118.2 97.8 85.8 97.2 93.7 98.5 97.7 75.9 66.9
Swaziland .................... 112.1 71.3 64.8 61.4 120.1 109.7 58.3 44.0 120.0 122.6 108.6 46.4
Tanzania ..................... 102.9 84.1 75.8 68.8 99.2 99.7 76.3 60.9 100.5 96.3 88.1 66.2
Togo ......................... 99.6 91.2 79.2 58.3 98.5 95.1 79.0 55.1 98.5 95.0 84.1 54.7
Tunisia ....................... 94.1 101.8 99.3 86.5 89.3 97.3 100.4 79.0 85.5 91.2 91.1 73.0
Uganda ...................... 101.0 95.4 79.4 74.7 100.7 98.2 86.5 65.2 97.6 96.4 87.9 68.1
Western Sahara ................ 95.8 89.4 80.1 68.2 97.5 91.8 81.0 63.8 98.4 94.1 83.0 60.9
Zambia ....................... 104.1 91.7 78.3 64.7 99.7 99.2 76.9 63.1 99.2 95.1 84.9 60.3
Zimbabwe .................... 133.0 65.7 62.0 72.3 108.0 125.0 56.1 43.5 114.4 106.2 101.0 55.4
U.S. Census Bureau An Aging World: 2015 149
Table B-4.
Sex Ratio for Population 35 Years and Over by Age: 2015, 2030, and 2050—Con.
(Men per 100 women)
Country
2015 2030 2050
35–49 50–64 65–79
80 and
over 35–49 50–64 65–79 80+ 35–49 50–64 65–79
80 and
over
Asia
Afghanistan ................... 104.2 98.8 87.7 73.5 102.5 98.7 87.3 67.9 100.6 97.0 86.6 65.0
Armenia ...................... 92.0 84.0 69.6 57.2 102.5 98.5 78.2 53.9 102.5 112.7 101.4 60.8
Azerbaijan .................... 92.7 85.8 66.3 48.0 102.4 87.8 71.8 43.7 113.5 100.7 80.6 47.8
Bahrain ...................... 200.8 180.8 98.5 80.8 175.6 164.3 105.9 72.7 177.3 142.6 113.0 73.2
Bangladesh ................... 93.1 99.7 100.3 76.8 101.2 99.6 90.9 76.6 99.9 101.6 94.9 62.7
Bhutan ....................... 120.2 115.4 111.7 101.5 106.3 118.7 108.4 92.7 103.2 101.4 108.3 86.4
Brunei ....................... 92.9 102.7 100.7 66.5 86.4 81.2 90.0 73.0 88.5 78.5 70.3 56.8
Burma ....................... 99.0 90.7 79.7 62.4 99.3 94.5 79.9 58.5 100.3 95.6 84.1 58.0
Cambodia .................... 95.0 74.8 61.8 51.4 95.8 91.3 69.2 48.7 98.0 91.8 83.3 59.1
China ........................ 104.1 102.5 96.8 72.8 106.4 101.0 91.3 68.7 112.5 106.2 90.7 64.7
Cyprus ....................... 108.9 93.0 82.3 55.5 114.5 103.4 82.9 57.1 115.4 111.6 96.9 58.9
Gaza Strip .................... 105.0 105.5 74.0 58.3 103.8 102.7 96.6 57.7 104.4 101.9 93.0 72.1
Georgia ...................... 94.4 81.9 71.4 50.0 98.8 87.8 70.2 48.4 108.6 98.6 78.1 48.7
Hong Kong .................... 68.6 90.5 100.5 65.9 82.5 67.0 82.4 71.4 94.7 88.3 64.1 49.9
India ......................... 105.1 101.6 92.8 74.2 108.9 101.3 91.2 71.8 112.0 107.3 92.6 68.5
Indonesia ..................... 106.1 88.1 80.2 61.4 105.0 102.1 78.1 55.9 105.8 102.0 90.4 59.8
Iran ......................... 104.1 97.1 87.8 78.1 104.6 101.5 87.8 64.6 104.2 102.3 92.7 65.7
Iraq ......................... 105.5 97.2 88.5 78.5 102.2 103.0 90.5 73.9 102.3 99.8 93.1 74.9
Israel ........................ 104.6 98.2 86.2 63.1 103.8 102.5 90.5 65.7 103.5 101.7 94.3 68.6
Japan ........................ 97.5 100.6 89.2 54.1 99.0 95.6 92.3 61.8 106.1 103.7 88.9 63.8
Jordan ....................... 100.8 96.5 93.2 85.3 94.0 95.6 90.3 71.3 96.7 90.7 84.7 71.4
Kazakhstan ................... 93.8 80.1 59.2 26.7 97.7 85.5 63.4 30.2 95.6 92.3 73.1 37.4
Korea, North .................. 99.7 92.6 60.2 17.0 101.4 95.1 72.5 29.5 100.8 97.0 79.0 43.4
Korea, South .................. 102.2 98.1 79.9 45.5 111.5 98.9 87.9 57.7 106.9 109.1 93.3 64.8
Kuwait ....................... 176.0 144.7 91.5 74.3 162.5 127.7 72.4 54.6 152.7 117.5 68.8 45.9
Kyrgyzstan .................... 94.7 80.0 66.3 48.3 95.9 84.0 65.1 45.0 99.6 89.1 73.1 44.5
Laos ......................... 96.3 95.7 84.7 70.5 98.3 93.0 85.6 64.4 99.0 94.2 85.0 60.0
Lebanon. . . . . . . . . . . . . . . . . . . . . . 90.8 85.2 86.5 71.2 95.8 90.0 79.5 64.3 93.0 94.4 85.8 59.3
Macau ....................... 82.4 100.5 93.9 73.9 79.3 81.4 92.2 70.9 93.9 91.2 65.2 63.8
Malaysia ..................... 103.5 104.3 95.8 64.8 101.0 101.4 92.8 67.6 102.6 98.8 89.6 64.1
Maldives ..................... 131.9 105.4 88.3 90.8 101.8 92.7 77.1 63.0 102.9 99.4 88.0 57.5
Mongolia ..................... 93.5 86.7 73.7 50.3 92.7 85.2 69.6 46.0 95.8 87.7 71.3 45.6
Nepal ........................ 92.2 95.2 86.6 79.2 102.2 97.8 88.1 67.3 99.6 100.4 91.6 66.0
Oman ........................ 147.4 126.8 100.2 93.2 125.9 113.8 87.4 73.5 124.1 106.5 94.0 66.5
Pakistan ...................... 108.7 102.9 89.4 77.0 106.6 105.0 93.0 66.5 104.4 102.5 94.2 68.5
Philippines .................... 101.5 88.7 79.3 58.1 102.9 97.4 78.5 56.4 103.9 100.1 88.7 57.7
Qatar ........................ 578.8 387.7 185.2 79.6 546.3 532.8 197.3 89.8 472.9 416.3 232.0 88.5
Saudi Arabia .................. 136.7 125.5 106.1 96.6 122.4 113.0 102.1 72.9 125.1 108.7 96.6 70.5
Singapore .................... 96.5 101.0 88.2 69.1 94.2 96.0 91.2 70.0 94.3 94.3 87.9 70.8
Sri Lanka ..................... 94.5 87.7 77.2 62.2 98.9 89.8 76.1 55.4 102.4 96.7 81.4 53.8
Syria ........................ 102.7 99.7 87.1 67.9 103.1 99.9 89.7 62.1 103.3 100.3 91.1 65.5
Taiwan ....................... 99.3 96.8 86.5 83.7 98.3 94.9 86.4 62.8 98.7 95.7 85.7 61.0
Tajikistan ..................... 96.4 86.5 78.6 45.4 99.4 90.6 73.5 46.6 100.8 95.1 81.0 46.4
Thailand ...................... 97.5 89.7 81.7 63.5 99.5 92.6 79.4 60.3 101.9 96.7 83.8 56.8
Timor-Leste ................... 97.0 99.5 93.3 75.6 86.6 93.6 88.1 68.8 89.6 85.7 80.1 59.5
Turkey ....................... 101.7 98.9 87.2 74.1 102.4 98.6 88.3 66.5 103.2 100.1 89.2 64.4
Turkmenistan .................. 98.9 89.9 82.0 56.7 98.6 95.0 78.6 56.9 99.5 95.2 83.9 55.2
United Arab Emirates ........... 360.3 335.6 180.4 106.4 337.1 281.3 123.1 91.6 293.2 226.8 107.4 60.9
Uzbekistan .................... 97.8 91.1 79.8 59.1 99.8 92.9 78.9 58.2 103.4 96.8 83.7 56.2
Vietnam ...................... 100.4 87.9 68.7 44.7 104.4 97.1 78.1 46.0 109.5 102.9 89.6 57.1
West Bank .................... 106.2 103.3 77.5 57.1 104.3 103.6 93.8 58.2 104.1 101.7 93.7 69.2
Yemen ....................... 105.7 86.6 88.0 78.1 102.8 100.8 75.9 63.9 100.2 95.9 93.7 54.3
Europe
Albania ....................... 85.4 96.9 96.2 62.3 98.0 83.1 88.2 62.6 111.1 100.6 78.1 55.3
Andorra ...................... 104.3 113.8 109.2 85.5 103.7 101.9 104.5 88.3 104.1 104.3 91.5 76.8
Austria ....................... 99.4 99.5 84.8 51.8 99.1 95.5 89.0 59.9 99.0 96.2 85.4 62.7
Belarus ...................... 95.0 81.9 53.7 29.2 100.4 85.9 60.5 29.8 104.3 95.3 72.7 35.2
Belgium ...................... 101.5 99.1 85.4 50.5 103.1 98.5 88.0 56.6 102.6 100.4 89.1 59.3
Bosnia and Herzegovina ......... 100.2 94.8 73.0 34.1 102.9 96.4 82.3 41.2 105.7 101.9 85.2 52.6
150 An Aging World: 2015 U.S. Census Bureau
Table B-4.
Sex Ratio for Population 35 Years and Over by Age: 2015, 2030, and 2050—Con.
(Men per 100 women)
Country
2015 2030 2050
35–49 50–64 65–79
80 and
over 35–49 50–64 65–79 80+ 35–49 50–64 65–79
80 and
over
Europe—Con.
Bulgaria ...................... 98.3 87.7 73.1 51.0 101.7 92.7 73.7 48.2 102.4 97.0 83.3 48.9
Croatia ....................... 97.2 94.0 78.2 48.9 100.1 92.7 81.4 56.8 102.5 97.2 83.4 55.7
Czech Republic ................ 105.4 96.5 77.8 49.0 107.6 101.1 82.7 55.5 110.6 104.5 90.2 58.8
Denmark ..................... 98.8 99.8 90.5 55.3 96.9 95.7 90.5 63.0 100.3 96.0 85.4 62.1
Estonia ....................... 92.2 79.0 56.0 35.1 90.8 84.2 61.6 35.8 90.5 85.2 69.3 41.7
Faroe Islands .................. 116.8 108.2 104.9 67.1 116.1 113.8 98.2 75.9 106.1 105.5 110.7 70.8
Finland ....................... 103.8 98.0 83.9 47.4 105.0 99.5 85.2 56.6 104.1 101.1 90.2 56.4
France ....................... 101.5 94.4 87.0 54.5 102.7 98.2 85.3 61.9 102.9 100.3 90.7 60.2
Germany ..................... 102.4 100.0 86.8 57.6 98.6 97.8 90.1 64.5 97.4 94.0 86.5 65.8
Gibraltar ...................... 105.6 82.9 112.1 57.9 106.2 102.9 70.3 76.6 103.2 105.1 92.7 52.8
Greece ....................... 99.8 97.0 85.0 63.3 97.7 97.6 87.5 61.7 97.2 95.6 88.4 63.1
Guernsey ..................... 99.1 99.5 93.8 59.2 105.5 97.5 94.3 69.3 97.3 99.7 98.4 66.8
Hungary ...................... 101.3 87.5 66.6 42.9 102.2 95.0 72.3 45.3 104.1 98.5 82.5 50.5
Iceland ....................... 101.7 101.2 94.2 67.3 100.6 99.8 92.9 70.6 99.1 97.8 91.5 66.6
Ireland ....................... 102.6 100.8 94.0 62.6 100.1 102.0 92.9 69.2 101.6 100.4 92.7 67.8
Isle of Man .................... 98.4 102.3 96.5 66.2 100.7 99.0 96.0 76.2 110.9 103.4 91.3 71.8
Italy ......................... 98.1 95.0 84.9 56.4 97.0 95.4 86.6 60.8 99.0 94.9 86.6 62.6
Jersey ....................... 98.7 95.8 81.6 56.8 106.1 96.3 85.3 57.2 107.9 102.8 93.7 60.2
Kosovo ....................... 111.6 103.7 75.1 59.8 111.5 107.6 91.9 54.5 106.6 106.6 96.8 67.8
Latvia ........................ 100.3 83.5 56.1 29.1 98.9 93.0 66.3 31.5 100.9 94.9 78.0 42.7
Liechtenstein .................. 98.6 95.3 93.9 56.4 100.7 94.2 85.1 73.9 109.2 94.2 85.0 64.6
Lithuania ..................... 100.2 86.8 62.8 35.7 101.6 93.8 72.6 39.1 105.2 98.4 81.6 49.4
Luxembourg ................... 99.8 100.4 87.0 46.9 97.9 96.8 88.0 56.0 99.3 96.2 85.4 58.7
Macedonia .................... 103.1 97.1 79.1 59.7 104.2 99.2 85.0 55.4 105.9 102.2 89.6 59.1
Malta ........................ 104.6 99.4 88.6 58.9 105.6 102.9 92.3 67.2 105.5 104.0 96.8 65.3
Moldova ...................... 101.0 85.9 69.9 38.7 108.0 98.2 75.6 43.6 112.6 110.0 94.7 47.5
Monaco ...................... 96.1 100.6 90.6 64.9 143.6 85.5 86.8 62.2 242.4 129.4 74.7 54.7
Montenegro ................... 119.1 100.6 66.8 64.3 113.9 115.8 86.7 53.0 92.2 92.2 108.5 66.1
Netherlands ................... 100.2 99.9 92.5 56.3 101.2 97.6 91.4 66.7 101.7 98.9 88.8 64.5
Norway. . . . . . . . . . . . . . . . . . . . . . . 106.3 103.4 94.1 59.4 108.0 105.7 96.3 71.4 105.6 105.8 99.5 70.4
Poland ....................... 101.7 91.7 71.7 45.0 101.5 96.3 76.6 48.4 103.5 98.0 84.5 51.6
Portugal ...................... 101.0 89.2 75.7 55.5 109.9 97.1 79.1 54.0 110.9 108.3 89.8 56.6
Romania ..................... 102.4 90.2 72.0 55.9 104.2 96.3 75.1 51.3 104.9 99.9 84.8 54.9
Russia ....................... 95.8 79.0 51.3 26.6 97.3 85.0 58.0 28.6 102.2 90.9 69.0 34.7
San Marino ................... 87.3 96.1 90.8 62.5 90.1 87.2 88.7 66.3 103.2 91.8 80.9 62.0
Serbia ....................... 101.5 95.0 74.9 55.9 102.9 96.9 80.4 53.3 104.8 100.7 85.3 56.2
Slovakia ...................... 101.4 92.4 69.6 41.8 102.5 96.0 77.4 45.9 103.5 98.6 84.6 51.6
Slovenia ...................... 102.4 97.5 79.2 43.0 103.0 98.6 82.6 52.2 104.7 100.3 88.2 54.4
Spain ........................ 103.1 96.6 83.6 56.6 105.2 99.7 86.6 58.9 104.7 101.8 91.3 62.4
Sweden ...................... 103.0 101.5 94.8 60.9 101.6 100.5 95.2 71.3 102.0 98.8 93.7 68.5
Switzerland ................... 100.6 101.0 88.2 55.7 100.0 98.8 92.7 65.0 100.8 98.4 90.3 66.9
Ukraine ...................... 92.6 78.0 54.9 30.5 99.7 82.6 59.9 30.2 104.3 94.8 71.4 35.2
United Kingdom ................ 104.9 98.3 89.3 62.0 105.1 102.8 90.5 66.8 105.1 102.8 95.6 66.8
Latin America and the Caribbean
Anguilla ...................... 78.3 84.8 104.1 79.0 75.3 73.5 79.5 85.5 80.7 73.4 67.6 56.0
Antigua and Barbuda ............ 82.5 82.2 78.8 63.3 83.2 79.3 74.0 60.0 87.1 82.7 71.3 53.9
Argentina ..................... 99.2 95.1 79.2 52.2 101.0 95.9 82.1 55.6 103.2 99.4 85.6 57.6
Aruba ........................ 93.7 86.9 68.0 49.5 92.5 88.0 76.4 46.8 94.4 89.3 79.5 50.3
Bahamas, The ................. 100.4 85.4 66.3 45.4 102.6 96.0 74.1 46.4 103.1 99.9 85.9 56.0
Barbados ..................... 99.8 90.8 72.7 47.9 99.0 95.9 80.8 53.0 95.9 95.0 86.3 59.0
Belize ........................ 101.6 97.6 93.4 72.2 106.3 97.2 85.9 66.3 106.9 103.3 90.0 60.6
Bolivia ....................... 92.5 86.7 82.9 64.3 98.4 88.5 77.5 62.3 100.5 95.4 82.7 54.9
Brazil ........................ 97.6 91.0 78.6 55.6 98.8 92.8 80.2 55.8 100.5 95.4 83.5 56.0
Cayman Islands ................ 94.7 92.0 94.0 69.0 94.4 94.1 85.7 69.2 96.7 94.6 87.0 62.4
Chile ........................ 98.9 90.7 78.6 50.1 101.7 95.8 81.4 53.8 102.2 99.6 88.0 57.6
Colombia ..................... 96.9 90.1 74.5 58.6 100.5 93.2 81.1 51.6 103.2 98.5 85.7 56.9
Costa Rica .................... 100.6 95.7 91.9 63.2 102.1 98.2 87.7 64.5 102.6 99.7 91.9 61.7
Cuba ........................ 101.4 94.3 86.5 62.3 102.6 98.0 87.3 60.2 103.1 99.6 90.4 64.4
Curacao ...................... 93.5 77.3 74.3 56.9 105.7 91.6 69.7 53.3 102.5 104.2 92.1 48.9
U.S. Census Bureau An Aging World: 2015 151
Table B-4.
Sex Ratio for Population 35 Years and Over by Age: 2015, 2030, and 2050—Con.
(Men per 100 women)
Country
2015 2030 2050
35–49 50–64 65–79
80 and
over 35–49 50–64 65–79 80+ 35–49 50–64 65–79
80 and
over
Latin America and the
Caribbean—Con.
Dominica ..................... 101.5 112.1 88.1 55.8 105.5 99.6 100.7 60.2 109.7 106.1 93.8 63.6
Dominican Republic ............. 104.9 102.1 90.8 67.5 105.2 102.7 92.9 65.8 103.8 102.8 94.7 66.6
Ecuador ...................... 92.7 95.4 94.3 80.5 97.4 89.7 87.9 73.1 101.2 96.4 83.7 63.0
El Salvador ................... 81.6 78.6 82.6 67.7 91.3 78.2 72.2 61.5 96.8 90.6 76.0 48.1
Grenada ...................... 110.7 106.2 89.2 67.3 100.4 109.4 94.9 67.4 106.4 97.7 94.1 66.0
Guatemala .................... 86.4 90.5 90.1 68.3 93.7 84.1 81.3 67.6 97.5 93.1 78.6 56.1
Guyana ...................... 110.1 87.1 74.0 56.9 109.2 104.5 74.7 48.2 101.4 102.4 92.5 55.2
Haiti ......................... 99.4 94.4 82.6 67.8 99.4 96.7 86.1 64.4 100.2 97.3 87.4 65.4
Honduras ..................... 101.7 90.8 79.1 69.2 104.6 98.1 82.6 60.0 105.9 102.7 90.6 64.4
Jamaica ...................... 97.3 95.1 87.6 63.9 101.3 95.6 85.9 63.5 102.4 100.5 88.5 62.6
Mexico ....................... 91.1 85.4 83.7 74.6 94.7 87.9 79.0 67.0 96.2 93.0 81.9 60.1
Montserrat .................... 89.4 85.7 130.4 392.9 95.4 90.2 86.5 196.3 105.5 102.5 89.8 89.6
Nicaragua .................... 87.1 86.3 84.6 68.1 92.9 84.0 77.3 60.0 100.4 93.2 77.2 53.7
Panama ...................... 101.9 99.2 91.2 65.6 102.8 99.4 91.1 63.6 102.5 100.4 91.7 64.4
Paraguay ..................... 100.1 104.5 94.0 66.6 100.5 100.1 96.1 68.7 101.2 99.9 91.6 67.5
Peru ......................... 91.0 94.0 92.8 77.4 91.0 87.4 86.8 72.6 94.2 89.4 79.5 62.2
Puerto Rico ................... 90.9 84.0 80.1 63.9 96.5 90.0 78.1 62.2 97.5 100.5 86.5 61.3
Saint Barthelemy ............... 119.6 119.2 106.1 72.3 120.2 115.4 107.7 77.7 120.3 117.0 106.1 74.5
Saint Kitts and Nevis ............ 106.1 103.2 92.0 61.9 106.1 106.5 95.3 71.5 103.9 105.1 97.5 71.4
Saint Lucia .................... 93.0 87.3 87.4 72.7 93.1 89.3 84.9 74.2 97.9 91.8 86.7 71.0
Saint Martin ................... 83.6 88.8 86.6 56.9 94.6 83.6 78.6 59.1 91.9 92.7 76.6 53.0
Saint Vincent and the Grenadines .. 109.5 107.3 95.5 62.1 106.3 109.1 101.4 71.3 102.5 103.4 99.1 74.4
Sint Maarten .................. 96.0 91.9 98.0 58.7 98.9 94.0 83.5 72.8 109.9 97.2 88.0 59.6
Suriname ..................... 103.1 97.9 79.0 64.8 104.2 99.9 88.2 58.0 103.1 100.7 91.6 64.2
Trinidad and Tobago ............ 110.3 100.9 83.8 49.3 111.2 107.9 87.6 54.3 109.0 110.1 96.8 57.7
Turks and Caicos Islands. . . . . . . . . 106.2 115.1 83.1 72.6 96.4 104.8 103.0 62.3 100.7 95.2 92.3 74.3
Uruguay ...................... 96.1 90.5 74.3 49.0 100.8 92.8 78.2 49.8 101.9 98.6 83.8 54.0
Venezuela .................... 95.8 91.3 82.8 61.1 97.5 91.9 80.4 57.5 101.3 94.9 82.0 54.1
Virgin Islands, British ............ 87.0 95.2 99.2 75.8 86.6 85.0 87.7 77.9 85.9 84.2 78.5 63.1
Virgin Islands, U.S. ............. 84.3 92.5 87.9 62.0 72.2 88.3 85.1 64.1 70.2 70.1 75.7 60.0
Northern America
Bermuda ..................... 101.3 91.2 80.7 53.3 101.8 98.3 82.1 56.8 102.0 98.1 90.7 57.4
Canada ...................... 102.2 99.2 89.5 59.8 103.7 100.8 89.3 64.5 104.2 102.4 91.6 62.5
Greenland .................... 114.1 121.4 126.8 63.9 104.8 112.1 104.6 89.3 105.2 101.1 89.2 69.1
Saint Pierre and Miquelon ........ 96.1 108.9 85.7 40.8 89.0 93.3 87.9 57.4 98.8 86.6 76.2 62.7
United States .................. 99.0 94.4 86.1 60.7 102.5 96.0 87.0 68.5 104.3 101.0 90.1 68.5
Oceania
American Samoa ............... 112.0 92.2 90.8 55.6 106.4 108.4 77.5 57.3 85.5 99.3 102.7 53.2
Australia ...................... 103.7 99.5 95.0 64.8 105.0 102.5 91.7 70.2 106.3 103.9 95.5 66.3
Cook Islands .................. 96.5 119.2 108.6 56.8 94.0 103.5 117.1 57.8 106.8 100.9 85.4 72.5
Fiji .......................... 105.4 102.5 88.9 59.5 105.1 104.5 91.6 59.0 103.5 102.5 93.9 60.6
French Polynesia ............... 106.3 106.8 99.0 73.5 104.5 104.1 96.4 74.1 107.5 104.1 93.7 71.6
Guam ........................ 104.2 103.7 89.8 61.5 101.8 101.1 93.4 61.4 104.2 102.1 89.5 64.4
Kiribati ....................... 92.0 84.6 68.7 44.4 92.9 83.9 66.9 44.7 89.3 84.4 70.4 45.0
Marshall Islands ................ 106.1 101.4 101.0 71.8 102.7 103.4 90.1 75.0 102.8 100.1 94.0 61.6
Micronesia, Federated States of ... 91.6 96.8 86.8 47.0 91.9 88.4 77.6 47.0 89.1 87.9 72.2 38.2
Nauru ........................ 101.3 70.7 64.6 45.5 104.2 90.6 51.0 30.6 72.2 97.0 77.9 35.4
New Caledonia ................ 101.3 96.5 86.5 56.6 102.4 97.3 82.8 54.2 103.7 100.0 86.0 55.4
New Zealand .................. 102.2 95.6 92.4 69.1 99.7 100.7 88.5 71.4 101.1 99.0 92.1 66.7
Northern Mariana Islands ........ 85.1 112.6 99.5 49.0 74.6 82.6 100.1 68.0 123.8 123.8 45.6 67.7
Palau ........................ 178.9 67.5 38.5 32.2 174.4 87.6 34.2 20.4 174.1 83.5 48.1 20.8
Papua New Guinea ............. 108.1 106.8 105.3 110.8 102.8 103.1 93.9 74.6 103.9 100.1 88.0 67.4
Samoa ....................... 111.5 104.5 82.1 57.7 98.8 108.9 90.7 53.5 101.0 95.2 92.5 66.2
Solomon Islands ............... 103.4 104.1 95.6 76.4 103.7 102.0 96.9 68.6 105.5 103.0 92.5 71.1
Tonga ........................ 101.0 98.7 86.1 73.9 95.5 106.0 95.6 62.2 95.5 100.4 97.3 76.2
Tuvalu ....................... 83.1 71.1 69.7 64.8 120.0 76.3 58.1 51.7 105.3 111.7 77.3 47.5
Vanuatu ...................... 94.3 99.8 104.7 100.7 95.7 91.9 91.9 82.8 94.9 93.4 85.4 68.1
Wallis and Futuna .............. 92.0 93.3 104.8 49.2 116.9 91.3 86.1 73.8 116.3 113.2 95.9 55.9
Source: U.S. Census Bureau, 2013; International Data Base.
152 An Aging World: 2015 U.S. Census Bureau
Table B-5.
Dependency Ratios: 2015, 2030, and 2050
Country Total1Youth2Older3
2015 2030 2050 2015 2030 2050 2015 2030 2050
Africa
Algeria ............................. 71 75 76 62 59 45 9 16 30
Angola ............................. 134 119 99 127 112 90 7 7 9
Benin .............................. 134 107 82 127 100 71 7 7 11
Botswana ........................... 91 80 75 83 70 60 8 10 15
Burkina Faso ........................ 141 125 103 135 119 95 6 6 8
Burundi ............................ 142 135 115 136 128 106 6 7 9
Cameroon .......................... 84 70 72 75 56 45 9 15 27
Cape Verde ......................... 129 112 91 122 104 81 7 8 10
Central African Republic ............... 120 105 88 112 97 78 8 8 10
Chad .............................. 142 106 86 135 99 78 7 7 9
Comoros ........................... 122 79 69 114 70 52 9 9 16
Congo (Brazzaville) ................... 115 111 101 108 103 88 6 9 13
Congo (Kinshasa) .................... 131 96 69 125 90 59 6 6 10
Cote d’Ivoire ........................ 110 83 69 103 75 56 7 7 13
Djibouti ............................. 88 69 65 81 61 50 7 8 16
Egypt .............................. 85 77 76 76 63 53 10 14 23
Equatorial Guinea .................... 122 98 75 113 89 63 9 9 13
Eritrea ............................. 123 88 71 114 80 57 8 8 14
Ethiopia ............................ 137 116 89 130 109 79 7 7 10
Gabon ............................. 131 125 105 122 115 96 9 9 9
Gambia, The ........................ 110 82 67 103 74 53 7 8 15
Ghana ............................. 110 101 91 102 90 76 9 11 15
Guinea ............................. 128 115 94 120 106 84 8 9 11
Guinea-Bissau ....................... 115 98 79 108 90 68 7 8 11
Kenya .............................. 118 73 67 112 65 51 6 8 15
Lesotho ............................ 92 79 67 82 68 51 10 11 16
Liberia ............................. 132 102 79 125 95 68 7 8 11
Libya .............................. 65 58 78 58 46 44 7 12 34
Madagascar ......................... 120 98 74 113 89 61 7 9 13
Malawi ............................. 139 118 89 132 112 81 7 6 8
Mali ............................... 157 132 89 149 125 81 8 7 8
Mauritania .......................... 115 95 78 107 86 64 8 9 14
Mauritius ........................... 58 67 79 44 40 37 14 27 42
Morocco ............................ 71 68 79 60 50 45 11 18 33
Mozambique ........................ 148 127 101 141 121 94 7 6 7
Namibia ............................ 90 65 58 81 55 43 9 10 15
Niger .............................. 168 137 92 161 131 85 7 7 8
Nigeria ............................. 130 115 96 123 108 87 7 7 9
Rwanda ............................ 122 101 96 116 93 84 6 7 12
Saint Helena ........................ 59 68 98 36 32 36 22 36 62
Sao Tome and Principe ................ 134 90 68 127 83 54 7 7 13
Senegal ............................ 127 103 81 121 95 69 7 8 12
Seychelles .......................... 53 53 71 41 32 26 11 21 44
Sierra Leone ........................ 125 115 105 117 107 94 8 8 11
Somalia ............................ 130 119 94 124 111 85 5 7 9
South Africa ......................... 79 75 69 68 58 50 12 16 19
South Sudan ........................ 141 106 77 136 100 67 5 6 10
Sudan ............................. 120 83 67 113 75 53 7 8 14
Swaziland .......................... 105 80 67 97 71 56 8 9 11
Tanzania ........................... 138 116 95 131 109 85 7 7 10
Togo ............................... 117 106 91 110 98 79 7 9 12
Tunisia ............................. 62 70 86 49 46 41 13 23 45
Uganda ............................ 163 138 99 158 133 92 5 5 7
Western Sahara ...................... 108 92 77 100 82 63 8 10 14
Zambia ............................. 146 136 116 140 130 109 6 6 7
Zimbabwe .......................... 110 101 87 103 93 74 7 8 13
See notes at end of table.
U.S. Census Bureau An Aging World: 2015 153
Table B-5.
Dependency Ratios: 2015, 2030, and 2050—Con.
Country Total1Youth2Older3
2015 2030 2050 2015 2030 2050 2015 2030 2050
Asia
Afghanistan ......................... 129 107 80 123 101 72 6 6 8
Armenia ............................ 57 70 84 40 37 32 17 33 52
Azerbaijan .......................... 57 64 70 47 43 37 10 21 33
Bahrain ............................ 42 42 50 38 34 33 4 8 17
Bangladesh ......................... 88 67 71 78 54 46 10 13 25
Bhutan ............................. 74 58 65 63 45 37 11 13 28
Brunei ............................. 57 58 65 51 43 39 7 15 26
Burma ............................. 68 64 71 59 49 45 9 15 27
Cambodia .......................... 81 71 67 73 60 47 7 11 20
China .............................. 50 62 82 35 34 33 15 28 49
Cyprus ............................. 50 59 75 33 32 30 17 27 45
Gaza Strip .......................... 126 85 64 120 77 50 6 8 14
Georgia ............................ 64 77 81 39 40 36 26 37 44
Hong Kong .......................... 48 81 101 25 31 30 23 50 71
India ............................... 76 67 70 66 53 45 10 15 25
Indonesia ........................... 70 65 74 59 47 41 11 18 33
Iran ............................... 57 57 70 49 43 37 8 14 34
Iraq ............................... 100 76 71 93 67 52 7 9 19
Israel .............................. 85 80 77 65 55 45 20 24 32
Japan .............................. 80 91 121 32 30 33 48 62 89
Jordan ............................. 97 88 86 87 74 63 10 13 23
Kazakhstan ......................... 65 73 72 53 52 43 12 21 29
Korea, North ........................ 64 64 72 47 43 38 16 21 34
Korea, South ........................ 50 66 100 30 27 28 20 40 72
Kuwait ............................. 51 48 49 48 41 37 4 7 12
Kyrgyzstan .......................... 77 80 74 68 64 51 9 16 23
Laos ............................... 96 73 65 89 63 48 7 10 17
Lebanon. . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 67 84 48 42 37 16 25 46
Macau ............................. 42 59 86 28 25 24 14 34 63
Malaysia ........................... 75 72 77 65 55 49 10 17 28
Maldives ........................... 53 58 63 47 45 35 7 13 28
Mongolia ........................... 65 64 69 58 51 40 7 14 28
Nepal .............................. 88 65 64 80 54 44 9 11 20
Oman .............................. 75 69 63 70 62 46 6 7 17
Pakistan ............................ 93 68 64 84 58 45 8 11 18
Philippines .......................... 92 80 75 83 67 55 9 13 20
Qatar .............................. 21 24 29 20 22 23 1 2 5
Saudi Arabia ........................ 65 56 61 60 47 41 5 9 20
Singapore .......................... 41 51 68 29 28 28 13 23 40
Sri Lanka ........................... 69 71 80 54 46 42 15 25 38
Syria .............................. 89 69 69 82 58 46 8 11 23
Taiwan ............................. 48 64 93 30 26 26 18 38 68
Tajikistan ........................... 84 73 68 78 62 49 6 10 19
Thailand ............................ 52 62 85 37 33 34 15 29 51
Timor-Leste ......................... 130 107 74 121 97 62 9 10 13
Turkey ............................. 68 63 73 56 45 39 12 18 33
Turkmenistan ........................ 66 66 70 59 52 44 7 15 26
United Arab Emirates ................. 37 40 41 36 38 37 1 2 5
Uzbekistan .......................... 63 60 65 55 45 36 8 15 30
Vietnam ............................ 61 60 72 52 42 36 9 18 35
West Bank .......................... 92 72 65 85 61 44 7 11 21
Yemen ............................. 123 82 65 117 75 52 6 7 13
Europe
Albania ............................. 64 70 72 45 39 31 19 30 41
Andorra ............................ 53 71 126 30 26 37 22 45 89
Austria ............................. 62 79 94 31 32 35 32 46 58
Belarus ............................ 53 69 86 31 34 34 22 35 52
Belgium ............................ 68 81 88 35 36 36 32 45 52
Bosnia and Herzegovina ............... 50 66 92 29 29 31 20 38 62
Bulgaria ............................ 63 72 102 30 30 34 32 42 68
Croatia ............................. 63 76 91 33 33 34 30 43 56
Czech Republic ...................... 60 69 90 31 31 35 29 38 55
See notes at end of table.
154 An Aging World: 2015 U.S. Census Bureau
Table B-5.
Dependency Ratios: 2015, 2030, and 2050—Con.
Country Total1Youth2Older3
2015 2030 2050 2015 2030 2050 2015 2030 2050
Europe—Con.
Denmark ........................... 72 80 83 40 39 38 32 41 45
Estonia ............................. 65 80 104 34 36 38 31 44 66
Faroe Islands ........................ 77 87 80 48 50 44 29 37 36
Finland ............................. 72 87 88 37 39 37 35 49 51
France ............................. 76 88 89 43 44 40 33 44 49
Germany ........................... 65 84 94 29 33 35 35 51 58
Gibraltar ............................ 74 74 77 47 45 38 27 29 39
Greece ............................. 64 72 99 31 29 35 34 43 64
Guernsey ........................... 63 76 86 33 34 35 31 42 51
Hungary ............................ 62 71 92 33 32 35 30 39 57
Iceland ............................. 67 78 83 44 43 39 23 35 44
Ireland ............................. 67 71 84 46 43 41 21 29 43
Isle of Man .......................... 72 84 89 38 39 36 34 45 52
Italy ............................... 66 75 96 31 31 35 35 45 61
Jersey ............................. 63 78 73 37 41 35 26 37 38
Kosovo ............................. 72 62 66 60 46 38 12 17 28
Latvia .............................. 56 70 94 29 31 33 27 39 60
Liechtenstein ........................ 61 78 82 34 36 35 27 42 48
Lithuania ........................... 56 71 94 29 30 32 27 41 62
Luxembourg ......................... 65 74 75 40 40 39 26 33 36
Macedonia .......................... 59 67 82 39 36 35 20 31 48
Malta .............................. 65 80 90 34 35 34 31 45 56
Moldova ............................ 55 72 86 37 39 36 18 33 49
Monaco ............................ 86 130 183 30 22 16 57 108 167
Montenegro ......................... 52 69 102 30 32 36 22 37 65
Netherlands ......................... 68 82 84 38 39 38 30 43 46
Norway. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 75 79 41 40 38 28 35 41
Poland ............................. 54 70 95 30 31 33 24 39 62
Portugal ............................ 67 72 94 36 32 35 32 40 60
Romania ........................... 55 61 93 31 28 33 24 32 61
Russia ............................. 53 70 81 32 36 35 21 34 47
San Marino ......................... 69 78 95 36 34 36 32 44 58
Serbia ............................. 61 71 87 32 31 33 28 40 54
Slovakia ............................ 54 67 92 32 31 34 22 35 58
Slovenia ............................ 57 75 103 28 29 34 29 46 69
Spain .............................. 61 68 97 32 31 36 29 37 62
Sweden ............................ 73 82 79 39 43 39 35 40 40
Switzerland ......................... 62 74 81 33 36 36 29 38 45
Ukraine ............................ 54 67 87 29 30 32 25 37 55
United Kingdom ...................... 69 79 80 39 41 38 30 38 42
Latin America and the Caribbean
Anguilla ............................ 63 72 82 49 46 44 14 26 38
Antigua and Barbuda .................. 68 70 75 55 48 42 13 22 33
Argentina ........................... 79 74 77 58 50 43 21 24 33
Aruba .............................. 59 74 78 39 39 37 20 35 41
Bahamas, The ....................... 63 66 75 51 45 40 12 21 35
Barbados ........................... 55 72 88 38 38 38 17 34 50
Belize .............................. 97 79 70 90 68 52 7 11 18
Bolivia ............................. 92 73 69 83 61 48 10 12 20
Brazil .............................. 65 62 74 52 41 38 13 21 37
Cayman Islands ...................... 56 74 78 38 39 38 18 34 40
Chile .............................. 62 70 78 46 41 37 17 29 41
Colombia ........................... 69 67 71 57 46 38 12 21 33
Costa Rica .......................... 63 66 74 51 44 38 12 22 36
Cuba .............................. 55 65 87 35 32 34 20 33 53
Curacao ............................ 71 86 77 47 46 39 24 40 38
Dominica ........................... 67 72 90 49 44 37 18 28 53
Dominican Republic ................... 79 74 76 66 54 46 13 20 31
Ecuador ............................ 81 69 70 68 51 41 13 18 29
El Salvador ......................... 82 65 70 69 47 36 13 18 33
Grenada ............................ 72 75 75 56 47 38 17 28 37
Guatemala .......................... 105 78 66 96 67 49 9 11 17
See notes at end of table.
U.S. Census Bureau An Aging World: 2015 155
Table B-5.
Dependency Ratios: 2015, 2030, and 2050—Con.
Country Total1Youth2Older3
2015 2030 2050 2015 2030 2050 2015 2030 2050
Latin America and the Caribbean—Con.
Guyana ............................ 82 62 61 72 46 38 10 16 23
Haiti ............................... 95 69 65 87 60 48 8 10 17
Honduras ........................... 97 74 68 89 63 49 8 11 20
Jamaica ............................ 87 69 64 72 53 40 15 16 24
Mexico ............................. 77 71 74 65 53 43 12 18 31
Montserrat .......................... 62 48 75 52 32 31 10 16 44
Nicaragua .......................... 80 62 64 71 48 37 9 13 27
Panama ............................ 78 72 74 64 52 42 14 20 32
Paraguay ........................... 73 65 69 62 47 39 12 18 30
Peru ............................... 76 69 70 64 51 41 12 18 29
Puerto Rico ......................... 73 81 93 43 38 35 30 44 58
Saint Barthelemy ..................... 54 75 83 31 28 29 23 47 54
Saint Kitts and Nevis .................. 58 68 86 45 40 37 13 28 50
Saint Lucia .......................... 66 72 108 48 37 32 18 34 76
Saint Martin ......................... 63 70 76 51 49 48 12 21 29
Saint Vincent and the Grenadines ........ 65 67 83 50 39 36 15 28 47
Sint Maarten ........................ 52 82 79 40 44 38 12 38 42
Suriname ........................... 68 59 70 59 43 38 10 16 32
Trinidad and Tobago .................. 54 70 90 39 37 36 15 33 54
Turks and Caicos Islands. . . . . . . . . . . . . . . 50 51 76 43 38 37 6 13 38
Uruguay ............................ 75 71 75 50 42 37 25 29 38
Venezuela .......................... 76 71 73 66 54 46 11 17 26
Virgin Islands, British .................. 46 58 72 34 35 38 12 24 34
Virgin Islands, U.S. ................... 72 94 131 39 33 35 34 61 96
Northern America
Bermuda ........................... 67 94 89 39 42 39 28 52 50
Canada ............................ 64 83 87 35 38 38 29 46 49
Greenland .......................... 60 77 70 47 47 39 14 30 31
Saint Pierre and Miquelon .............. 66 84 135 35 30 36 31 54 100
United States ........................ 68 82 81 43 45 43 25 37 38
Oceania
American Samoa ..................... 61 66 78 52 44 38 8 21 41
Australia ............................ 65 74 78 40 40 38 26 34 40
Cook Islands ........................ 74 79 92 54 42 41 20 37 51
Fiji ................................ 74 70 73 63 52 43 11 19 30
French Polynesia ..................... 63 64 75 51 42 36 12 22 38
Guam .............................. 76 77 74 60 51 41 16 26 32
Kiribati ............................. 86 68 66 78 57 47 8 11 19
Marshall Islands ...................... 99 75 70 91 63 48 7 12 22
Micronesia, Federated States of ......... 84 69 68 78 57 47 6 11 21
Nauru .............................. 75 72 78 72 61 57 4 10 21
New Caledonia ...................... 68 63 71 53 43 38 15 20 33
New Zealand ........................ 70 80 82 45 44 40 25 36 42
Northern Mariana Islands .............. 60 64 74 52 39 30 8 25 44
Palau .............................. 57 67 79 45 41 40 11 26 39
Papua New Guinea ................... 96 77 71 88 66 52 8 11 18
Samoa ............................. 95 73 69 84 58 46 11 16 23
Solomon Islands ..................... 102 77 71 93 67 50 8 10 20
Tonga .............................. 108 78 76 95 63 42 13 15 34
Tuvalu ............................. 81 86 69 71 69 53 10 17 16
Vanuatu ............................ 104 78 70 97 67 50 8 11 19
Wallis and Futuna .................... 68 65 79 53 40 33 16 25 46
1 Total dependency ratio is the number of people aged 0 to 19 years and 65 years and over per 100 people aged 20 to 64. Youth and older ratios may not sum to
total ratio due to rounding.
2 Youth dependency ratio is the number of people aged 0 to 19 per 100 people aged 20 to 64.
3 Older dependency ratio is the number of people aged 65 and over per 100 people aged 20 to 64.
Source: U.S. Census Bureau, 2013; International Data Base.
156 An Aging World: 2015 U.S. Census Bureau
Table B-6.
Life Expectancy at Birth, Age 65, and Age 80 by Sex for Selected Countries: 2015 and 2050
(In percent)
Country
Life expectancy at birth Life expectancy at 65 Life expectancy at 80
2015 2050 2015 2050 2015 2050
Both
sexes Male Female
Both
sexes Male Female Male Female Male Female Male Female Male Female
Japan ................. 84.7 81.4 88.3 91.6 88.4 95.0 20.0 25.2 25.0 30.6 9.4 12.6 12.6 16.8
Singapore ............. 84.7 82.1 87.5 91.6 88.7 94.6 20.6 24.5 25.5 30.3 11.5 12.9 14.1 16.9
Macau ................ 84.5 81.6 87.6 85.1 82.2 88.1 20.2 24.9 20.7 25.3 10.1 13.4 10.5 13.8
Hong Kong ............. 82.9 80.2 85.8 84.4 81.6 87.4 18.9 23.1 20.1 24.6 8.5 10.9 9.8 12.8
Switzerland ............ 82.5 80.2 84.9 84.2 81.6 87.0 19.0 22.4 20.1 24.3 8.4 10.4 9.7 12.6
Australia ............... 82.2 79.7 84.7 84.1 81.4 86.9 19.0 22.5 20.1 24.3 8.9 11.0 9.9 12.8
Italy .................. 82.1 79.5 84.9 84.1 81.3 87.0 18.6 22.4 20.0 24.3 8.7 10.7 9.8 12.7
Sweden ............... 82.0 80.1 84.0 84.0 81.5 86.6 18.6 21.5 20.0 23.9 7.9 9.8 9.5 12.3
Canada ............... 81.8 79.2 84.5 83.9 81.1 86.8 18.9 22.7 20.1 24.4 9.4 11.6 10.1 13.0
France ................ 81.8 78.7 85.0 83.9 80.9 87.0 18.9 22.9 20.0 24.5 8.6 10.8 9.7 12.7
Norway. . . . . . . . . . . . . . . . 81.7 79.7 83.8 83.9 81.4 86.5 18.5 21.3 19.9 23.8 8.1 9.8 9.6 12.3
Spain ................. 81.6 78.6 84.8 83.8 80.9 86.9 18.2 22.2 19.8 24.2 8.3 10.1 9.6 12.5
Israel ................. 81.4 79.1 83.7 83.8 81.1 86.5 18.4 21.4 19.9 23.9 8.6 10.3 9.8 12.5
Netherlands ............ 81.2 79.1 83.5 83.7 81.1 86.4 17.9 21.4 19.7 23.9 8.0 10.0 9.6 12.3
New Zealand ........... 81.1 79.0 83.2 83.6 81.1 86.3 18.6 21.4 19.9 23.8 8.9 10.4 9.9 12.5
Ireland ................ 80.7 78.4 83.1 83.4 80.8 86.2 17.7 21.0 19.6 23.7 8.1 9.8 9.6 12.3
Germany .............. 80.6 78.3 83.0 83.4 80.7 86.2 17.9 20.9 19.6 23.6 8.3 9.6 9.7 12.2
Jordan ................ 80.5 79.1 82.1 83.4 81.1 85.8 18.0 20.2 19.5 23.2 7.8 9.0 9.3 11.8
United Kingdom ......... 80.5 78.4 82.8 83.4 80.8 86.1 18.0 20.9 19.7 23.6 8.4 10.1 9.7 12.4
Greece ................ 80.4 77.8 83.2 83.3 80.6 86.3 17.6 20.9 19.5 23.7 8.3 10.1 9.6 12.4
Austria ................ 80.3 77.4 83.4 83.3 80.3 86.4 17.5 21.3 19.4 23.8 8.1 10.0 9.5 12.3
Belgium ............... 80.1 76.9 83.4 83.2 80.1 86.3 16.9 21.4 19.2 23.8 7.8 10.3 9.4 12.5
Korea, South ........... 80.0 77.0 83.3 84.2 81.5 87.1 17.1 21.1 20.2 24.4 7.8 9.8 10.1 13.0
Taiwan ................ 80.0 76.9 83.3 83.1 80.1 86.3 17.7 21.4 19.5 23.8 8.4 10.4 9.6 12.5
Rwanda ............... 59.7 58.1 61.3 72.0 69.6 74.4 13.0 14.1 15.2 17.6 5.5 6.1 6.9 8.3
Congo (Brazzaville) ...... 58.8 57.6 60.0 71.1 69.0 73.2 13.2 14.3 15.4 17.7 5.6 6.0 7.0 8.4
Liberia ................ 58.6 56.9 60.3 70.7 68.3 73.2 12.0 13.5 14.5 17.2 5.1 5.7 6.6 8.1
Cote d’Ivoire ........... 58.3 57.2 59.5 69.7 68.0 71.4 12.2 13.8 15.0 17.8 5.3 6.0 6.9 8.6
Cameroon ............. 57.9 56.6 59.3 72.0 69.7 74.4 12.9 14.0 15.3 17.6 5.5 6.0 6.9 8.3
Sierra Leone ........... 57.8 55.2 60.4 70.2 67.1 73.3 12.5 13.9 14.7 17.4 5.3 5.9 6.6 8.1
Zimbabwe ............. 57.1 56.5 57.6 67.2 66.9 67.5 14.4 17.0 17.4 21.0 6.9 8.2 8.6 11.0
Congo (Kinshasa) ....... 56.9 55.4 58.5 70.2 67.8 72.7 11.7 13.1 14.2 16.7 5.0 5.6 6.4 7.8
Angola ................ 55.6 54.5 56.8 69.2 67.1 71.5 12.4 13.4 14.5 16.5 5.2 5.7 6.5 7.6
Mali .................. 55.3 53.5 57.3 68.4 65.7 71.1 11.7 12.8 13.7 16.0 4.8 5.3 6.0 7.2
Burkina Faso ........... 55.1 53.1 57.2 67.8 65.1 70.5 11.7 13.1 13.8 16.5 4.9 5.5 6.1 7.6
Niger ................. 55.1 53.9 56.4 68.2 66.1 70.5 12.3 13.1 14.3 16.1 5.1 5.5 6.3 7.3
Uganda ............... 54.9 53.5 56.4 67.8 65.6 70.0 13.4 14.4 15.1 17.4 5.7 6.2 6.6 8.0
Botswana .............. 54.2 56.0 52.3 61.6 64.8 58.4 15.1 18.3 18.5 21.7 8.2 10.0 10.1 12.7
Malawi ................ 53.5 52.7 54.4 65.3 64.0 66.5 12.0 13.4 14.0 16.5 5.1 5.8 6.5 8.0
Nigeria ................ 53.0 52.0 54.1 68.1 66.0 70.3 12.1 13.1 14.2 16.2 5.2 5.6 6.3 7.5
Lesotho ............... 52.9 52.8 53.0 72.3 71.5 73.2 12.8 14.9 15.9 18.5 5.9 6.9 7.7 9.7
Mozambique ........... 52.9 52.2 53.7 70.8 69.0 72.7 12.0 13.5 14.7 17.2 5.3 6.0 6.8 8.4
Zambia ................ 52.2 50.5 53.8 64.5 62.5 66.7 12.4 13.7 14.0 16.2 5.3 5.8 6.0 7.3
Gabon ................ 52.0 51.6 52.5 62.1 61.6 62.6 12.4 14.7 15.4 19.0 5.7 6.8 7.5 9.7
Somalia ............... 52.0 49.9 54.1 65.5 62.6 68.5 11.7 12.8 13.5 15.6 4.9 5.4 5.9 7.1
Central African Republic .. 51.8 50.5 53.2 65.5 63.5 67.7 12.0 13.2 14.0 16.2 5.2 5.8 6.4 7.7
Namibia ............... 51.6 52.1 51.2 57.8 60.1 55.5 13.0 15.6 15.3 18.6 6.2 7.4 7.9 10.3
Swaziland ............. 51.1 51.6 50.5 61.4 63.0 59.8 12.9 15.4 15.3 18.2 6.0 7.1 7.6 9.8
Afghanistan ............ 50.9 49.5 52.3 64.5 62.2 66.9 11.0 12.1 13.0 15.0 4.6 5.1 5.7 6.8
Guinea-Bissau .......... 50.2 48.2 52.3 63.5 61.0 66.2 11.4 12.9 13.5 16.2 5.0 5.7 6.1 7.7
Chad ................. 49.8 48.6 51.0 63.4 61.7 65.1 11.7 12.8 13.8 15.7 5.0 5.5 6.2 7.3
South Africa ............ 49.7 50.7 48.7 63.2 64.1 62.3 13.0 15.7 16.3 20.0 6.2 7.7 8.2 10.7
Source: U.S. Census Bureau, International Data Base; unpublished lifetables.
U.S. Census Bureau An Aging World: 2015 157
Table B-7.
Deficits in Universal Health Protection: Share of Total
Population Without Health Protection by Country
Region or country Percent of total
population Year of estimate
Africa
Algeria ............................ 14.8 2005
Angola ............................ 100.0 2005
Benin ............................. 91.0 2009
Burkina Faso ....................... 99.0 2010
Burundi ........................... 71.6 2009
Cabo Verde ........................ 35.0 2010
Cameroon ......................... 98.0 2009
Central African Republic .............. 94.0 2010
Comoros .......................... 95.0 2010
Congo (Kinshasa) ................... 90.0 2010
Cote d’Ivoire ....................... 98.8 2008
Djibouti ............................ 70.0 2006
Egypt ............................. 48.9 2008
Eritrea ............................ 95.0 2011
Ethiopia ........................... 95.0 2011
Gabon ............................ 42.4 2011
Gambia ........................... 0.1 2011
Ghana ............................ 26.1 2010
Guinea ............................ 99.8 2010
Guinea Bissau ...................... 98.4 2011
Kenya ............................. 60.6 2009
Lesotho ........................... 82.4 2009
Libya ............................. 0.0 2004
Madagascar ........................ 96.3 2009
Mali .............................. 98.1 2008
Mauritania ......................... 94.0 2009
Mauritius .......................... 0.0 2010
Morocco ........................... 57.7 2007
Mozambique ....................... 96.0 2011
Namibia ........................... 72.0 2007
Niger ............................. 96.9 2003
Nigeria ............................ 97.8 2008
Rwanda ........................... 9.0 2010
Sao Tome and Principe ............... 97.9 2009
Senegal ........................... 79.9 2007
Seychelles ......................... 10.0 2011
Sierra Leone ....................... 100.0 2008
Somalia ........................... 80.0 2006
South Africa ........................ 0.0 2010
Sudan ............................ 70.3 2009
Swaziland ......................... 93.8 2006
Tanzania .......................... 87.0 2010
Togo .............................. 96.0 2010
Tunisia ............................ 20.0 2005
Uganda ........................... 98.0 2008
Zambia ............................ 91.6 2008
Zimbabwe ......................... 99.0 2009
Latin America and the Caribbean
Antigua and Barbuda ................. 48.9 2007
Argentina .......................... 3.2 2008
Aruba ............................. 0.8 2003
Bahamas .......................... 0.0 1995
Barbados .......................... 0.0 1995
Belize ............................. 75.0 2009
Bolivia ............................ 57.3 2009
Brazil ............................. 0.0 2009
Chile ............................. 6.9 2011
Colombia .......................... 12.3 2010
Costa Rica ......................... 0.0 2009
Cuba ............................. 0.0 2011
Dominica .......................... 86.6 2009
158 An Aging World: 2015 U.S. Census Bureau
Table B-7.
Deficits in Universal Health Protection: Share of Total
Population Without Health Protection by Country—Con.
Region or country Percent of total
population Year of estimate
Latin America and the Caribbean—Con.
Dominican Republic .................. 73.5 2007
Ecuador ........................... 77.2 2009
El Salvador ........................ 78.4 2009
Guatemala ......................... 70.0 2005
Guyana ........................... 76.2 2009
Haiti .............................. 96.9 2001
Honduras .......................... 88.0 2006
Jamaica ........................... 79.9 2007
Mexico ............................ 14.4 2010
Nicaragua ......................... 87.8 2005
Panama ........................... 48.2 2008
Paraguay .......................... 76.4 2009
Peru .............................. 35.6 2010
Saint Kitts and Nevis ................. 71.2 2008
Saint Lucia ......................... 64.5 2003
Saint Vincent and the Grenadines ....... 90.6 2008
Uruguay ........................... 2.8 2010
Venezuela ......................... 0.0 2010
Northern America
Canada ........................... 0.0 2011
United States ....................... 16.0 2010
Asia
Armenia ........................... 0.0 2009
Azerbaijan ......................... 97.1 2006
Bahrain ........................... 0.0 2006
Bangladesh ........................ 98.6 2003
Bhutan ............................ 10.0 2009
Brunei ............................ 0.0 2010
Cambodia ......................... 73.9 2009
China ............................. 3.1 2010
Cyprus ............................ 35.0 2008
Georgia ........................... 75.0 2008
Hong Kong ......................... 0.0 2010
India .............................. 87.5 2010
Indonesia .......................... 41.0 2010
Iran .............................. 10.0 2005
Israel ............................. 0.0 2011
Japan ............................. 0.0 2010
Jordan ............................ 25.0 2006
Kazakhstan ........................ 30.0 2001
Korea, South ....................... 0.0 2010
Kuwait ............................ 0.0 2006
Kyrgyzstan ......................... 17.0 2001
Laos .............................. 88.4 2009
Lebanon. . . . . . . . . . . . . . . . . . . . . . . . . . . 51.7 2007
Malaysia .......................... 0.0 2010
Maldives .......................... 70.0 2011
Mongolia .......................... 18.1 2009
Nepal ............................. 99.9 2010
Oman ............................. 3.0 2005
Pakistan ........................... 73.4 2009
Philippines ......................... 18.0 2009
Qatar ............................. 0.0 2006
Saudi Arabia ....................... 74.0 2010
Singapore ......................... 0.0 2010
Sri Lanka .......................... 0.0 2010
Syria ............................. 10.0 2008
Tajikistan .......................... 99.7 2010
Thailand ........................... 2.0 2007
Turkey ............................ 14.0 2011
Turkmenistan ....................... 17.7 2011
U.S. Census Bureau An Aging World: 2015 159
Table B-7.
Deficits in Universal Health Protection: Share of Total
Population Without Health Protection by Country—Con.
Region or country Percent of total
population Year of estimate
Asia—Con.
United Arab Emirates ................ 0.0 2010
Uzbekistan ......................... 0.0 2010
Vietnam ........................... 39.0 2010
Yemen ............................ 58.0 2003
Europe
Albania ............................ 76.4 2008
Austria ............................ 0.7 2010
Belarus ........................... 0.0 2010
Belgium ........................... 1.0 2010
Bosnia and Herzegovina .............. 40.8 2004
Bulgaria ........................... 13.0 2008
Croatia ............................ 3.0 2009
Czech Republic ..................... 0.0 2011
Denmark .......................... 0.0 2011
Estonia ............................ 7.1 2011
Finland ............................ 0.0 2010
France ............................ 0.1 2011
Germany .......................... 0.0 2010
Greece ............................ 0.0 2010
Hungary ........................... 0.0 2010
Iceland ............................ 0.0 2010
Ireland ............................ 0.0 2011
Italy .............................. 0.0 2010
Latvia ............................. 30.0 2005
Liechtenstein ....................... 5.0 2008
Lithuania .......................... 5.0 2009
Luxembourg ........................ 2.4 2010
Macedonia ......................... 5.1 2006
Malta ............................. 0.0 2009
Moldova ........................... 24.3 2004
Montenegro ........................ 5.0 2004
Netherlands ........................ 1.1 2010
Norway. . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.0 2011
Poland ............................ 2.5 2010
Portugal ........................... 0.0 2010
Romania .......................... 5.7 2009
Russia ............................ 12.0 2011
Serbia ............................ 7.9 2009
Slovakia ........................... 5.2 2010
Slovenia ........................... 0.0 2011
Spain ............................. 0.8 2010
Sweden ........................... 0.0 2011
Switzerland ........................ 0.0 2010
Ukraine ........................... 0.0 2011
United Kingdom ..................... 0.0 2010
Oceania
Australia ........................... 0.0 2011
Fiji ............................... 0.0 2010
New Zealand ....................... 0.0 2011
Vanuatu ........................... 0.0 2010
Source: Scheil-Adlung, Xenia (ed.) 2015. Global Evidence on Inequities in Rural Health Protection:
New Data on Rural Deficits in Health Coverage for 174 Countries. International Labour Office Extension of
Social Security (ESS) Document 47, Statistical Annex. Geneva: International Labour Organization.
160 An Aging World: 2015 U.S. Census Bureau
Table B-8.
Labor Force Participation Rates by Age, Sex, and Country: Selected Years, 1980 to 2012
(In percent)
Country
Year
Male Female
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Africa
Egypt .................. 1986 94.2 91.3 88.8 68.3 25.5 6.0 4.3 3.4 2.0 0.7
1995 898.1 N 497.9 76.4 36.5 825.5 N 416.0 6.6 2.1
1999 898.1 N 497.9 63.5 32.1 822.3 N 414.2 5.6 2.3
2012 795.0 N 969.1 N 21.5 728.1 N 915.5 N 2.4
Morocco ................ 1982 96.6 93.3 89.5 68.9 42.1 14.1 14.6 14.6 11.2 5.3
1990 1090.3 N N N 538.1 1017.1 N N N 58.9
1999 1090.0 N N N 543.7 1030.1 N N N 513.0
2005 1087.6 N N N 540.0 1030.4 N N N 512.5
2012 95.3 89.1 79.8 51.1 28.7 31.6 31.2 27.9 19.2 8.5
Mozambique ............ 1997 89.9 89.8 90.0 88.4 1187.2 91.9 89.9 89.0 85.4 1183.0
2012 79.8 81.9 81.6 81.5 75.3 90.5 86.9 81.7 81.1 68.9
South Africa ............. 1980 N N 977.3 N 34.7 N N 924.1 N 5.9
1991 N N 970.5 N 21.3 N N 928.5 N 5.2
2003 80.8 73.7 63.5 40.6 25.6 62.6 50.9 38.4 15.2 9.6
2012 82.6 75.6 66.1 31.8 N 62.1 54.3 42.9 18.7 N
Tunisia ................. 1984 96.2 92.8 82.1 59.2 38.5 12.9 11.6 9.8 4.4 3.5
1994 95.6 90.1 78.3 54.6 31.5 17.6 12.6 9.6 7.3 3.3
1997 95.6 90.4 78.4 54.1 34.0 21.6 14.4 12.2 7.7 3.5
2012 94.1 88.2 70.1 34.4 15.4 23.5 16.6 11.5 4.8 1.9
Zambia ................. 1980 98.4 97.7 97.8 96.5 1165.3 41.5 46.8 49.5 57.0 1123.6
2008 97.2 95.2 90.5 88.5 72.0 85.6 85.3 83.5 79.4 56.3
2012 96.9 96.8 88.9 89.6 71.2 84.1 84.3 77.8 74.3 52.2
Zimbabwe .............. 1982 93.9 92.5 90.4 N 569.1 52.4 50.6 50.7 N 531.5
1992 95.1 92.2 88.8 77.5 52.0 54.0 49.7 47.1 40.0 21.7
1999 95.6 94.2 87.8 84.1 74.1 83.0 84.4 78.8 77.8 60.7
2011 94.1 96.8 94.6 88.9 72.6 89.3 87.0 86.0 84.3 63.0
Asia
Bangladesh ............. 1981 93.6 90.6 90.7 84.7 68.7 4.4 4.7 4.4 4.5 3.6
1986 99.7 99.3 98.0 93.4 70.4 10.3 10.8 9.8 9.0 10.9
2003 99.5 99.2 97.3 87.8 66.1 22.6 19.9 17.1 13.4 8.7
2010 97.4 94.1 88.5 77.2 57.9 50.1 9.4 10.5 6.6 8.3
China .................. 1982 97.5 91.4 83.0 63.7 30.1 70.6 50.9 32.9 16.9 4.7
1990 97.9 93.5 83.9 63.7 33.6 81.1 62.0 45.1 27.4 8.4
2000 94.2 89.3 79.6 60.2 33.7 78.5 66.8 54.5 38.9 17.2
2010 95.1 89.8 80.4 58.3 N 80.1 62.4 53.8 40.6 N
India ................... 1981 898.1 N 493.8 N 565.5 837.0 N 430.3 N 514.3
1991 896.9 N 492.6 1171.4 1242.3 841.5 N 435.5 1120.8 128.2
2001 897.0 N 492.0 1169.7 1245.4 847.3 N 440.9 1126.3 1212.0
2012 98.5 96.0 91.5 73.4 46.3 41.1 37.5 33.3 26.2 11.5
Indonesia ............... 1982 97.2 93.0 87.4 76.8 57.9 56.7 51.1 50.4 39.3 23.2
1992 97.6 93.8 89.6 79.7 56.8 60.5 57.7 52.2 42.7 25.1
1999 98.0 95.7 87.6 N 566.5 62.2 60.0 54.3 N 534.0
2005 98.6 97.0 91.2 N 568.5 61.8 59.9 57.4 N 536.6
2010 97.6 95.0 88.4 78.9 69.0 63.7 61.4 58.3 47.3 39.8
Israel .................. 1983 91.5 89.1 84.2 78.2 32.2 51.1 43.2 36.7 22.0 9.2
1996 787.4 N 75.9 59.0 16.9 765.8 N 44.7 19.9 5.1
2006 784.0 N 76.5 60.2 16.5 70.6 N 58.3 32.6 5.2
2012 87.3 84.4 79.3 71.1 24.8 75.6 74.9 66.4 48.2 10.4
Japan .................. 1980 98.0 97.3 94.0 81.5 46.0 62.3 58.7 50.7 38.8 16.1
1989 97.6 96.0 91.6 71.4 35.8 70.7 64.2 52.2 39.2 15.7
1999 97.5 97.1 94.7 74.1 35.5 71.8 67.9 58.7 39.8 14.9
2006 96.9 95.7 93.2 70.9 29.3 74.0 70.5 60.3 40.2 13.0
2012 96.1 95.0 92.2 75.4 28.7 75.7 73.4 64.6 45.8 13.4
See notes at end of table.
U.S. Census Bureau An Aging World: 2015 161
Table B-8.
Labor Force Participation Rates by Age, Sex, and Country: Selected Years 1980 to 2012—Con.
(In percent)
Country
Year
Male Female
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Asia—Con.
Malaysia ............... 1980 96.1 92.2 78.1 69.5 49.7 42.3 37.7 32.6 26.7 19.0
1991 92.4 87.1 65.0 53.3 31.8 35.8 29.6 20.6 14.6 6.7
2000 98.0 93.4 75.1 61.6 N 49.6 40.6 28.5 23.2 N
2012 96.9 92.5 76.8 57.4 N 55.3 48.3 34.6 21.2 N
Pakistan ................ 1981 93.9 92.0 90.4 N 575.7 2.7 3.1 2.4 N 52.3
1994 97.2 96.5 91.5 78.8 52.7 15.6 13.9 15.3 11.8 7.4
2006 97.6 95.8 90.7 77.5 49.3 26.5 22.5 22.8 19.1 11.5
2011 97.8 96.6 92.2 78.0 41.6 28.6 28.1 26.3 21.0 10.6
Philippines .............. 1989 797.4 N 988.9 N 59.0 758.2 N 950.7 N 29.4
1999 796.8 N 988.1 N 54.5 764.0 N 955.8 N 29.8
2006 793.8 N 980.6 N 50.6 763.3 N 954.1 N 28.7
2010 95.0 91.7 86.1 73.4 62.4 65.5 63.9 59.9 49.6 40.6
Singapore .............. 1980 95.7 89.6 70.7 52.5 28.6 26.5 20.4 14.5 11.3 6.4
1989 96.1 89.2 66.6 48.2 20.7 41.3 30.7 19.4 11.0 5.0
2000 96.3 91.3 74.4 49.6 18.5 57.4 46.7 29.6 15.3 4.1
2006 96.5 93.3 81.9 62.5 22.0 66.2 59.5 44.6 26.2 8.3
2012 95.6 93.8 88.5 74.6 32.4 73.4 65.6 56.2 41.7 13.7
South Korea ............. 1989 93.6 89.7 82.4 65.6 39.0 63.5 60.4 52.7 41.6 18.1
1999 93.0 89.9 81.0 65.5 40.2 62.8 55.4 51.2 46.3 21.4
2006 93.1 89.7 79.9 68.5 42.0 64.4 58.5 49.7 43.8 22.7
2012 93.0 91.4 84.7 72.3 41.6 67.7 62.5 54.8 43.9 23.0
Sri Lanka ............... 1981 92.3 87.4 74.3 56.6 35.7 25.2 19.3 13.2 6.9 3.8
1996 91.9 91.8 73.0 N 538.6 39.0 32.3 27.2 N 57.8
2000 95.6 88.8 76.8 N 540.6 47.1 36.4 31.6 N 510.2
2012 94.4 90.5 81.0 64.9 35.5 45.3 41.8 36.6 22.4 9.3
Thailand ................ 1980 93.7 90.7 84.4 67.8 39.3 73.5 68.6 59.1 43.1 19.0
1994 897.5 N 492.8 N 547.2 876.7 N 463.8 N 523.5
2006 896.7 N 492.0 N 552.2 883.6 N 471.3 N 527.3
2012 96.9 95.0 90.5 73.7 38.8 83.6 77.7 70.9 52.0 19.9
Turkey ................. 1980 91.1 84.9 76.8 67.4 43.9 48.3 46.1 42.4 36.3 20.8
1988 89.2 82.7 71.5 59.2 33.8 36.3 36.4 29.4 20.9 10.9
1996 83.0 71.0 60.3 54.0 33.6 29.7 29.3 30.4 23.4 13.3
2006 82.0 65.4 51.3 39.8 22.0 24.8 21.8 18.5 14.5 6.6
2012 86.1 68.7 53.7 41.9 20.1 33.1 26.2 20.0 16.0 6.4
Europe
Austria ................. 1981 96.3 91.5 77.3 23.3 3.1 57.3 53.5 32.4 9.5 1.8
1991 95.1 89.8 63.1 12.3 1.7 65.1 56.3 23.1 4.9 0.7
1998 93.6 88.4 63.2 13.2 4.4 72.6 63.6 24.8 8.4 1.9
2006 93.1 87.6 69.1 21.9 5.5 82.6 75.0 41.9 10.1 2.2
2012 93.1 90.4 76.4 29.7 7.3 85.8 80.0 53.9 14.3 3.5
Belgium ................ 1981 90.8 85.7 70.7 32.3 3.3 38.2 30.7 17.3 5.7 1.0
1997 90.5 81.6 49.2 18.4 1.9 59.5 44.2 21.8 4.6 0.7
2006 91.4 85.2 58.3 22.6 2.7 72.8 61.1 36.2 10.3 1.0
2012 90.8 86.6 66.8 26.8 4.0 78.8 69.7 51.0 17.2 1.1
Bulgaria ................ 1985 94.6 88.1 80.9 39.2 15.2 91.0 83.6 32.0 16.5 4.3
2006 84.1 79.2 66.1 38.6 4.6 82.8 76.5 53.4 11.7 1.5
2012 83.4 81.2 69.8 44.4 4.5 85.1 80.7 69.5 22.7 1.9
Czech Republic .......... 1980 96.0 92.7 84.2 46.3 19.5 88.1 79.9 40.8 21.5 6.5
1991 95.5 91.5 80.0 28.4 11.6 93.4 85.7 31.1 16.2 4.9
1999 94.9 90.1 77.1 27.5 7.2 90.8 81.5 33.2 12.9 2.7
2006 94.6 90.6 83.1 36.1 6.6 91.8 88.2 51.2 13.1 2.5
2012 95.6 93.8 86.4 41.0 6.8 93.8 90.0 66.5 17.2 3.3
See notes at end of table.
162 An Aging World: 2015 U.S. Census Bureau
Table B-8.
Labor Force Participation Rates by Age, Sex, and Country: Selected Years 1980 to 2012—Con.
(In percent)
Country
Year
Male Female
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Europe—Con.
Denmark ............... 1981 93.5 91.4 87.8 60.0 23.2 76.1 67.4 55.8 31.5 6.3
1993 93.9 90.2 80.6 45.5 10.1 87.7 79.4 63.6 27.1 3.4
2006 92.2 89.2 85.3 46.7 120.7 87.2 83.4 77.0 28.2 18.4
2012 92.2 88.6 86.6 52.4 10.2 87.1 83.8 79.5 38.3 4.1
France ................. 1984 95.0 90.8 70.0 29.9 4.3 61.0 54.1 41.4 18.0 2.1
1996 95.0 92.6 70.4 16.4 2.3 80.9 71.5 51.7 15.2 2.0
2005 94.1 90.3 62.5 15.4 1.6 83.2 77.3 53.4 13.4 0.8
2012 94.0 91.1 77.0 25.1 3.1 85.1 81.9 68.3 21.2 1.7
Germany ............... 1980 96.8 93.3 82.3 44.2 7.4 52.2 47.2 38.7 13.0 3.0
1988 96.4 93.2 79.8 34.5 4.9 60.9 53.7 41.1 11.1 1.8
1996 94.5 90.4 73.9 28.7 4.4 74.7 67.4 50.5 11.3 1.6
2006 94.3 91.2 82.0 42.3 5.0 83.5 78.7 65.6 24.4 2.2
2012 93.9 91.6 85.7 58.9 7.1 85.3 81.9 73.3 41.1 3.3
Greece ................. 1981 95.1 90.0 81.1 61.7 26.2 28.9 25.8 20.0 13.4 5.0
1987 98.0 84.2 74.3 53.5 14.0 43.9 37.2 29.3 22.0 5.1
1997 95.2 89.2 75.0 47.8 10.7 49.9 39.3 30.7 20.3 3.4
2006 95.6 89.4 74.0 45.2 7.4 64.0 51.3 33.5 21.8 2.1
2012 93.8 88.7 73.0 37.4 4.5 72.1 56.4 40.7 18.8 1.5
Hungary ................ 1980 92.9 86.2 72.2 13.2 4.0 77.5 67.4 18.8 8.7 2.9
1996 83.1 70.0 46.1 9.2 24.3 76.1 55.4 15.5 6.0 22.1
2006 82.5 74.4 61.3 19.6 24.3 78.9 71.7 44.1 9.4 21.6
2012 87.6 82.0 68.4 18.6 3.5 84.9 80.0 54.9 11.8 1.3
Italy ................... 1981 93.2 85.7 65.1 29.1 6.9 36.2 30.2 16.9 8.0 1.5
1989 95.6 87.5 67.8 35.2 7.9 44.7 34.1 20.2 9.8 2.2
1996 93.1 79.3 58.9 30.6 6.0 49.0 37.1 21.5 8.2 1.8
2006 94.0 89.0 58.0 28.9 6.1 62.3 54.0 32.8 10.2 1.2
2012 91.6 89.5 74.1 32.7 6.2 66.7 61.3 48.4 15.9 1.4
Norway. . . . . . . . . . . . . . . . . 1980 94.0 90.9 88.7 74.1 234.3 76.0 67.5 58.1 39.8 213.0
1990 93.9 89.2 82.0 64.2 221.2 83.5 74.5 62.0 46.5 212.0
2000 91.7 89.9 84.8 60.6 213.5 86.0 80.8 71.8 48.4 28.5
2006 90.7 87.7 82.9 63.0 217.8 84.1 81.5 71.2 51.2 210.6
2012 90.1 87.2 83.8 67.5 23.1 84.2 83.5 76.3 58.0 14.6
Poland ................. 1988 89.6 82.4 72.0 53.6 32.5 81.2 71.1 50.6 34.3 19.0
1996 85.1 76.8 55.2 33.4 15.3 79.1 63.1 35.0 19.2 8.5
2006 84.7 75.7 51.6 26.8 8.2 77.9 59.8 25.3 12.4 3.3
2012 86.7 81.0 68.5 35.7 7.7 82.5 73.1 46.6 14.2 3.0
Russia ................. 1989 95.8 91.7 79.3 35.4 14.2 93.7 83.8 34.8 20.4 6.4
1992 N 93.9 80.5 38.1 13.3 N 83.6 43.0 21.0 5.7
1999 88.6 85.3 65.2 29.2 6.4 86.8 78.9 33.7 16.0 2.5
2006 89.0 84.8 70.2 39.7 9.4 88.2 80.6 47.0 23.6 4.6
2012 92.6 88.7 77.8 38.5 14.1 90.6 84.3 52.9 24.9 8.9
Sweden ................ 1980 92.0 89.8 84.4 65.9 8.1 82.9 77.8 66.4 41.4 2.6
1990 91.6 89.5 84.1 63.9 10.6 89.8 85.8 76.8 53.1 3.7
2000 90.6 89.9 83.8 56.2 N 87.2 85.7 79.4 48.2 N
2006 90.9 89.8 84.9 66.2 N 87.2 85.4 80.0 58.3 N
2012 94.4 91.9 89.2 72.8 19.1 89.7 87.8 83.2 63.1 11.3
Ukraine ................ 1989 95.6 89.9 78.2 32.0 10.9 93.3 86.0 29.5 15.3 4.5
1999 86.3 76.4 69.7 28.3 29.8 84.3 70.1 33.4 16.7 26.0
2005 84.3 79.1 67.6 32.2 622.7 81.1 72.9 37.6 24.7 617.3
2012 85.2 78.2 66.7 32.2 20.5 83.2 73.5 34.7 25.9 16.7
United Kingdom .......... 1981 97.3 95.7 91.5 74.6 10.7 68.5 63.5 52.0 22.5 3.7
1993 92.8 88.1 75.7 52.2 7.4 77.9 70.0 54.5 24.7 3.5
2000 N 368.9 N N 7.4 N 464.0 N N 58.4
2006 N 372.3 N N 9.7 N 468.6 N N 511.4
2012 91.4 88.1 80.0 58.9 12.4 82.1 80.2 69.0 36.8 6.6
See notes at end of table.
U.S. Census Bureau An Aging World: 2015 163
Table B-8.
Labor Force Participation Rates by Age, Sex, and Country: Selected Years 1980 to 2012—Con.
(In percent)
Country
Year
Male Female
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Latin America/Caribbean
Argentina ............... 1980 92.4 87.6 77.6 51.9 17.9 30.2 25.4 17.6 9.8 3.2
1989 95.0 90.6 79.4 56.1 23.5 31.9 27.8 19.8 11.2 3.7
1995 93.6 90.0 82.8 63.2 27.6 53.2 46.6 35.4 22.6 8.9
2006 95.3 92.6 87.3 76.8 28.3 67.2 62.1 55.6 38.7 10.7
2012 94.6 91.4 86.8 75.7 22.2 67.7 63.4 53.8 33.7 7.5
Brazil .................. 1980 91.5 85.7 77.9 67.0 32.4 28.1 23.5 18.6 12.6 4.8
1990 894.5 N 482.3 N 546.0 849.5 N 434.5 N 511.5
2000 88.2 N 476.8 1149.8 1220.1 54.6 N 439.0 1115.5 124.6
2004 92.1 85.8 77.6 64.9 35.1 65.4 57.3 45.5 30.9 14.1
2012 91.6 86.1 78.2 62.0 30.0 67.4 58.8 45.5 30.0 11.7
Chile .................. 1982 90.1 82.8 72.8 61.5 25.5 26.0 21.9 16.2 10.1 4.5
1992 94.9 92.4 82.1 66.6 31.5 39.7 39.3 28.2 19.2 6.3
1999 95.9 91.3 83.4 69.2 27.4 47.1 42.9 32.4 21.0 6.5
2006 95.3 91.4 86.1 73.2 26.9 51.9 48.4 40.1 25.3 7.7
2012 93.6 93.8 90.1 80.5 35.0 66.2 61.1 56.0 38.3 12.0
Colombia ............... 1985 1086.0 N N N 558.4 1031.4 N N N 516.7
1999 896.0 N 488.2 1155.4 1225.2 869.1 N 443.7 1119.3 125.4
2010 96.6 94.0 87.8 74.5 61.5 69.6 62.3 49.1 35.2 25.0
Costa Rica .............. 1984 92.3 88.7 83.0 69.6 38.9 20.9 15.5 11.6 6.9 3.1
1996 894.4 N 485.4 1151.4 1221.1 844.2 N 422.2 119.1 122.8
2006 95.7 92.5 87.2 71.1 29.1 54.3 42.0 35.0 20.3 6.8
2012 94.0 92.0 85.8 67.5 26.5 55.0 50.3 39.8 27.3 6.8
Guatemala .............. 1981 93.2 91.7 90.3 85.8 66.9 12.2 11.6 10.1 9.0 6.5
1987 98.0 95.2 95.0 88.5 63.3 31.3 26.6 23.7 20.6 13.7
1998–99 97.7 95.1 94.1 87.2 71.4 56.4 46.9 45.1 41.0 28.8
2004 91.4 93.8 92.5 92.2 66.7 53.2 44.6 39.7 30.3 23.7
2012 96.2 96.5 92.9 90.0 66.4 56.0 51.8 44.7 36.3 15.0
Jamaica ................ 1988 794.6 N 990.5 N 52.4 773.7 N 965.4 N 24.9
1998 795.1 N 981.6 N 46.4 775.5 N 953.5 N 18.4
2004 793.7 N 981.8 N 41.4 772.6 N 950.1 N 17.3
2010 790.6 N 980.8 N 54.8 775.9 N 955.7 N 16.6
Mexico ................. 1980 95.3 93.8 91.4 85.6 68.6 29.1 27.5 24.6 24.1 18.6
1988 96.9 91.9 85.5 77.5 58.4 38.2 31.7 24.6 23.2 16.9
1996 95.6 91.9 85.6 74.1 52.0 41.3 35.0 31.2 23.8 14.1
2006 95.4 92.5 88.2 74.0 45.8 50.4 44.0 35.3 28.5 14.7
2012 94.9 91.8 85.4 71.5 42.8 55.4 50.2 41.5 32.8 15.5
Peru ................... 1972 97.1 95.5 92.8 83.9 61.5 19.5 17.9 16.1 13.4 8.5
1981 98.7 97.3 94.9 88.5 63.2 26.9 26.0 23.6 23.4 12.5
1989 94.4 88.3 83.2 75.0 34.6 54.4 42.9 38.8 23.9 12.0
1999 96.8 93.3 85.6 72.5 41.1 68.1 57.2 47.5 38.2 19.2
2006 98.7 94.6 87.0 65.5 28.8 67.0 56.2 39.2 34.9 15.3
2012 97.0 94.9 91.0 83.5 56.9 77.8 73.6 65.2 57.8 36.1
Uruguay ................ 1985 94.3 89.4 80.0 51.8 16.2 46.4 37.5 25.3 13.3 3.6
1995 96.4 94.3 89.3 59.3 19.4 64.6 59.5 41.0 23.9 6.7
2006 97.9 96.4 91.2 68.8 19.7 75.9 69.4 58.7 39.0 8.4
2012 96.3 94.6 89.0 65.4 24.5 78.4 73.3 67.0 43.1 10.4
Northern America
Canada ................ 1981 93.6 90.9 84.4 68.8 17.3 59.6 52.1 41.9 28.3 6.0
1991 93.1 89.5 78.3 54.1 14.4 76.3 66.4 49.9 28.1 5.7
2001 91.1 86.4 72.2 46.5 9.4 79.8 72.7 53.3 27.4 3.4
2006 90.8 87.8 76.1 53.3 12.1 82.6 78.1 62.3 37.1 5.2
2012 89.9 87.8 78.9 58.0 17.1 84.4 80.9 69.4 45.7 8.8
See notes at end of table.
164 An Aging World: 2015 U.S. Census Bureau
Table B-8.
Labor Force Participation Rates by Age, Sex, and Country: Selected Years 1980 to 2012—Con.
(In percent)
Country
Year
Male Female
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
45 to 49
years
50 to 54
years
55 to 59
years
60 to 64
years
65 years
and over
Northern America—Con.
United States ............ 1980 92.0 88.5 80.6 60.4 19.3 61.5 56.3 48.4 34.0 8.2
1991 92.2 88.4 79.0 54.8 15.8 75.4 67.8 55.7 35.1 8.6
2000 90.1 86.8 77.1 54.8 17.5 79.1 74.1 61.2 40.1 9.4
2006 785.7 N 76.3 57.5 19.7 764.7 N 64.7 45.4 10.7
2012 88.1 84.1 78.0 60.5 23.6 75.6 73.7 67.3 50.4 14.4
Oceania
Australia ................ 1981 92.5 89.4 81.3 53.1 12.3 56.5 46.3 32.8 15.5 4.9
1991 789.6 N 73.8 50.0 8.9 762.8 N 36.0 15.2 2.5
1999 89.5 85.1 72.5 46.7 9.6 73.8 65.0 44.6 18.3 3.1
2006 89.2 86.1 75.7 56.4 12.1 78.3 73.4 57.9 33.5 4.3
2012 89.2 86.7 80.0 62.6 16.8 78.5 76.3 65.7 44.5 7.8
New Zealand ............ 1981 95.8 94.1 87.5 45.7 10.9 52.5 43.7 30.9 11.7 1.9
1992 94.2 89.5 80.0 33.5 8.8 79.7 65.7 49.9 15.7 2.9
1999 90.7 88.4 81.2 57.4 10.4 79.9 73.6 60.1 32.5 3.9
2006 92.6 91.6 87.2 73.1 16.8 81.9 80.0 71.7 50.0 8.0
2012 91.5 90.9 88.2 77.6 25.5 82.3 82.8 77.4 64.1 15.0
N Not available.
1 Refers to ages 65 to 66 years.
2 Refers to ages 65 to 74 years.
3 Refers to ages 50 to 64 years.
4 Refers to ages 50 to 59 years.
5 Refers to ages 60 years and over.
6 Refers to ages 65 to 70 years.
7 Refers to ages 45 to 54 years.
8 Refers to ages 40 to 49 years.
9 Refers to ages 55 to 64 years.
10 Refers to ages 45 to 59 years.
11 Refers to ages 60 to 69 years.
12 Refers to ages 70 years and over.
Notes:
For some countries in this table, data are derived from labor force surveys as well as population censuses. Labor force surveys are more focused on economic
activity than are general census enumerations and, therefore, may yield more comprehensive information on various aspects of economic activity. The user should
recognize that temporal differences in labor force participation rates within a country may, in part, reflect different modes of data collection.
Czech Republic: Data prior to 1991 refer to the for mer Czechoslovakia.
Germany: Data prior to 1996 refer to the former West Ger many.
United Kingdom: Data for 2000 and 2006 are averages of reported quarterly rates.
Sources: U.S. Census Bureau, Population Division data files; various issues of the International Labour Office Yearbook of Labour Statistics; and the International
Labour Office electronic data base accessible at <www.ilo.org/ilostat/faces/home/statisticaldata>.
U.S. Census Bureau An Aging World: 2015 165
APPENDIX C.
Sources and Limitations of the Data
This report includes data compiled
by the International Programs area
in the Population Division of the
Census Bureau, from publications
and electronic files of national
statistical offices, various agencies
of the United Nations, and other
international organizations (e.g.,
the Organisation for Economic
Co-operation and Development, the
European Union, the World Health
Organization, and the International
Labour Organization). It also
includes cross-national informa-
tion from sources such as the
Global Burden of Disease Project,
the Survey of Health, Ageing and
Retirement in Europe, the Study on
Global Ageing and Adult Health,
and other university-based research
projects.
The majority of demographic
projections in Chapter 2, Chapter
3, and Appendix B come from
the International Data Base (IDB),
maintained and updated by Census
Bureau’s Population Division. The
Census Bureau has been preparing
estimates and projections of the
populations of foreign countries
since the 1960s. In the 1980s, the
Census Bureau released its first
comprehensive set of estimates and
projections for over 200 countries
and areas of the world. Since then,
the Census Bureau has routinely
updated estimates and projections
for countries as new data have
become available. Estimates and
projections for countries, as well as
for regions and the world, are made
available to the public through the
Census Bureau’s International Data
Base (IDB), located at
<www.census.gov/population
/international/data/idb>.
The Census Bureau’s IDB estimates
and projections have several
distinguishing features. For coun-
tries and areas recognized by the
U.S. Department of State and which
have populations of 5,000 or more,
population size and components
of change are provided for each
calendar year beyond the initial or
base year, through 2050. Within
this time series, sex ratios, popula-
tion, and mortality measures are
developed for single-year ages
through age 100-plus. As a result
of single-year age and calendar-
year accounting, IDB data capture
the timing and demographic impact
of important events such as wars,
famine, and natural disasters, with
a precision exceeding that of other
online resources for international
demographic data.
The estimation and projection pro-
cess involves data collection, data
evaluation, parameter estimation,
making assumptions about future
change, and final projection of the
population for each country. The
Census Bureau begins the process
by collecting demographic data
from censuses, surveys, vital regis-
tration, and administrative records
from a variety of sources. Available
data are evaluated, with particular
attention to internal and temporal
consistency.
Estimation and projection proce-
dures make use of a variety of
demographic techniques and
incorporate assumptions formed
by consulting the social science
and health science literature. In
addition to using demographic
data, Census Bureau demographers
consider information on public
health efforts, sociopolitical circum-
stances, and historical events such
as natural disasters and civil con-
flict in preparing the assumptions
feeding into population projections.
Regional and world populations are
obtained by projecting each coun-
try’s population separately and then
combining the results to derive
aggregated totals. For more details
on methodology, see International
Data Base Population Estimates and
Projections Methodology located
at <www.census.gov/population
/international/data/idb
/estandproj.pdf>.
