Order Code RL32792

CRS Report for Congress
Received through the CRS Web

Life Expectancy in the United States

March 3, 2005

Laura B. Shrestha
Specialist in Demography
Domestic Social Policy Division

Congressional Research Service ˜ The Library of Congress

Life Expectancy in the United States
Summary
As a result of falling age-specific mortality, life expectancy rose dramaticallyin the United States over the past century. Preliminary data for 2003 show that life
expectancy at birth for the total population has reached an all-time American highlevel, 77.6 years, up from 49.2 years at the turn of the 20th century. Record-high life
expectancies were found for white males (75.4 years) and black males (69.2 years),
as well as for white females (80.5 years) and black females (76.1 years). Life
expectancy gaps between males and females and between whites and blacks
persisted.
In combination with decreasing fertility, the life expectancy gains have led toa rapid aging of the American population, as reflected by an increasing proportion of
persons aged 65 and older. This report documents the improvements in longevity
that have occurred, analyzing both the underlying factors that contributed to mortality
reductions as well as the continuing longevity differentials by sex and race. In
addition, it considers whether life expectancy will continue to increase in futureyears. Detailed statistics on life expectancy are provided.
While this report focuses on describing the demographic context of life
expectancy change in the United States, these trends have implications for a wide
range of social and economic program and issues that are likely to be considered by
the 109th Congress.
This report will be updated annually.

Contents
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Trends in the Level of Longevity Over the Past Century . . . . . . . . . . . . . . . . 2
A Quick Global Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
What Will Be the Future Course of American Longevity? . . . . . . . . . . . . . . 7
Differentials in Life Expectancy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Sex Differentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Race Differentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Appendix A. Glossary of Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
Appendix B. Detailed Life Expectancy Tables . . . . . . . . . . . . . . . . . . . . . . . . . . 25

List of Figures
Figure 1. Life Expectancy at Birth, by Sex: 1900 to 2003 . . . . . . . . . . . . . . . . . . 10
Figure 2. Trends in Life Expectancy at Birth, by Race and Sex, 1900 to 2003 . . 13
Figure 3. Differences in Values of Life Expectancy at Birth Between
Whites and Blacks, by Sex, 1900-2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

List of Tables
Table 1. U.S. Life Expectancy at Birth, by Sex, in Selected Years . . . . . . . . . . . 3
Table 2. Age-adjusted Death Rates for Various Causes of Death . . . . . . . . . . . . 4
Table 3. Life Expectancy at Birth (in Years) in Selected Countries:
A Global Comparison in 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Table 4. Projected Life Expectancies, SSA, in Selected Years . . . . . . . . . . . . . . 7
Table 5. Racial Disparity in Potential Life Years Lost . . . . . . . . . . . . . . . . . . . . 15
Table A1. Life Expectancy at Birth, by Race and Sex: 1900-2003 . . . . . . . . . . 25
Table A2. Life Expectancy at Various Ages in 2003, by Sex, and Race . . . . . . 29

Life Expectancy in the United States
Introduction
This report considers population longevity in the United States, as measured bylife expectancy.1 Life expectancy is the expected number of years to be lived, on
average, by a particular cohort,2 if current mortality trends continue for the rest of thatcohort’s life.3 It most commonly refers to life expectancy at birth, the median
number of years that a population born in a particular year could expect to live. For
instance, based on recently-released preliminary data, life expectancy at birth in 2003
was 77.6 years4,5. This tells us that, for those born in calendar year 2003 in the
United States, 50% will die before that age; the other half will live longer.
Life expectancy is also routinely calculated for other ages. Life expectancy atage 60, for instance, refers to the additional number of years that a person who has
already attained age 60 will live beyond age 60. Life expectancy at age 60 in the year
2003 (preliminary data) was 22.3 years in the United States. A person who reachedage 60 in 2003 was expected to live an additional 22.3 years, on average, and would
die at age 82.3. While this report concentrates on trends and differentials in life
expectancy at birth, Appendix B Table A2 provides estimates of life expectancy at
selected additional ages in 2003 (the most recent available).

1

Research assistance provided by Angela O. Napili, Librarian, Office of Information
Resources Management.

2

Persons born in particular year, see Appendix A, Glossary.

3Life expectancy is a hypothetical measure that applies today’s age-specific death rates topredict the future survival of a cohort. It would technically be more accurate to follow thecohort through time and apply the actual age-specific death rates that the cohort experiences
as it moves through its life course, but calculation of actual life expectancy would thenrequire more then 100 years (until the death of the last survivor in the cohort).
4

National Center for Health Statistics, “Deaths: Preliminary Data for 2003,” National Vital
Statistics Report (NVSR), vol. 53, no. 15, Feb. 28, 2005. This preliminary data, which is
subject to change, is based on a large number of deaths comprising approximately 93% of
the demographic file and 91% of the medical file for all deaths in the United States in 2003.
Final data are scheduled to be released in Nov. 2005.

5

The concept of life expectancy, which considers the average experience for a population,is distinct from the concept of life span, which considers the upper limit of human life that
could be reached. To date, the highest attained life expectancy for a national population wasthat of Andorra in 2002, when life expectancy was 83 years for the total population (87years for females; 81 years for males). The oldest authenticated female life span wasrecorded for J. Calment of France who died at age 122 years and, for a man, A. Todde of
Italy who died at age 112 years. Life spans are not considered further in this report.

CRS-2
Measures of life expectancy are published in official life tables, which are basedon age-specific death rates. In the United States, data on mortality are collected andcompiled through the vital statistics system by the Centers for Disease Control andPrevention (CDC)/National Center for Health Statistics (NCHS). The most recently
released preliminary data on deaths and mortality are for calendar year 20036; themost recent final data on life expectancy are for calendar year 2002.7
This report documents the improvements in longevity that have occurred,analyzing both the underlying factors that contributed to mortality reductions as wellas the continuing longevity differentials by sex and race. In addition, it considers
whether life expectancy will continue to increase in future years. While this reportfocuses on describing the demographic context of longevity change in the UnitedStates, these trends have implications for a wide range of social and economic issues
that are likely to be considered by the 109th Congress. For instance, one consequenceof lengthening life expectancies is that the older population’s needs for care —assistance with daily tasks to allow continued community-living for high-functioning
seniors, institutions for those with more severe disabilities or cognitive impairments,
training of a specialized work force in geriatric care — are likely to increase,particularly for the oldest-old. There are also questions with respect to ensuring basic
income support, medical care, and housing for the older population. At the sametime, there is the recognition that government programs, such as Social Security andMedicare, will face financial pressures to meet the increasing needs. What programchanges are required to ensure the continued viability of such programs as thenumber of beneficiaries increases? What will be the federal government’s role in anenvironment of competing demands for limited resources?

Trends in the Level of Longevity Over the Past Century
As seen in Table 1 and Appendix B Table A1, life expectancy at birthincreased dramatically over the past century in the United States — from 49.2 years(average for 1900-1902) to 77.6 years (in 2003, preliminary figure).

6

NCHS, “Deaths: Preliminary Data for 2003”, National Vital Statistics Report (NVSR), vol.
53, no. 15, Feb. 28, 2005.
7

NCHS, “United States Life Tables, 2002,” National Vital Statistics Report (NVSR), vol.
53, no. 6, Nov. 10, 2004.

CRS-3

Table 1. U.S. Life Expectancy at Birth, by Sex, in Selected Years(in years)
Years

Total

Males

Females

1900-1902
1909-1911
1919-1921

49.2
51.5
56.4

47.9
49.9
55.5

50.7
53.2
57.4

1929-1931
1939-1941
1949-1951

59.2
63.6
68.1

57.7
61.6
65.5

60.9
65.9
71.0

1959-1961
1969-1971
1979-1981

69.9
70.8
73.9

66.8
67.0
70.1

73.2
74.6
77.6

1989-1991
2002
2003 (preliminary)

75.4
77.3
77.6

71.8
74.5
74.8

78.8
79.9
80.1

Source: For data through 2002: CRS compilation from National Center for Health Statistics (NCHS),
United States Life Tables, 2002, National Vital Statistics Reports, vol. 53, no. 6, Nov. 10, 2004. For
2003: NCHS, Deaths: Preliminary Data for 2003, National Vital Statistics Reports, vol. 53, no. 15,
Feb. 28, 2005.
Notes: Later year estimates are more reliable than those of the early 20th century. The federal civil
registration system began in 1900 with the setting up of the Death Registration Area. States were only
admitted to these areas as qualification standards were met. Only 10 states and the District ofColumbia were in the original death registration area of 1900. Statistics prior to 1939-1941 are basedon data from these death registration states (which increased in number over time). Alaska and Hawaii
are first included in 1959-1961 figures.

Gains in longevity were fastest in the first half of the 20th century. Theseadvances were largely attributed to “an enormous scientific breakthrough — the germ
theory of disease” which led to the eradication and control of numerous infectious
and parasitic diseases, especially among infants and children.8 The new theory led
to an entirely new approach to preventative medicine, practiced both by departmentsof public health and by individuals. Interventions included boiling bottles and milk,
washing hands, protecting food from flies, isolating sick children, ventilating rooms,
and improving water supply and sewage disposal.9 Beginning in the 1940s, the8

S.H. Preston and M. Haines, Fatal Years: Child Mortality in Late Nineteenth Century
America, National Bureau of Economic Research, Series on Long-Term Factors in
Economic Development (Princeton, NJ: Princeton University Press,1991).
9

Note that Preston and Haines rule out formal health care (doctors and hospitals, drugs, andtherapies) as the primary catalyst for life expectancy improvements during this period as thebulk of the decline had occurred before any effective therapies were available. Also, themortality experience of physicians and their families was not significantly different than thatof the general population. Evidence from other industrialized countries also support thisconclusion about the nature of early-century mortality declines. See, (1) T. McKeown , etal., 1975, “An Interpretation of the Decline of Mortality in England and Wales During the(continued...)CRS-4
control of infectious diseases was also aided by the increasing distribution and usageof antibiotics, including penicillin and sulfa drugs.
Since mid-century, advances in life expectancy have largely been attributable
to improvements in the prevention and control of the chronic diseases of adulthood.
In particular, death rates from two of the three major causes of death in 1950 —diseases of the heart (i.e., coronary heart disease, hypertensive heart disease, andrheumatic heart disease) and cerebrovascular diseases (stroke) — have fallen byapproximately 59% and 69%, respectively, on an age-adjusted basis10 since 1950 (seeTable 2), improvements that the CDC has characterized as “one of the mostimportant public health achievements of the 20th century.”11

Table 2. Age-adjusted Death Rates for Various Causes of Death(per 100,000 population)
Cause

1950

1980

1,446.0

1,039.1

845.3

Diseases of heart

586.8

412.1

240.8

Malignant neoplasms

193.9

207.9

193.5

Cerebrovascular diseases

180.7

96.2

56.2

Chronic lower respiratory diseases

—

28.3

43.5

Influenza and pneumonia

48.1

31.4

22.6

Chronic liver disease and cirrhosis

11.3

15.1

9.4

Diabetes mellitus

23.1

18.1

25.4

Unintentional injuries (incl. motor accidents)

78.0

46.4

36.9

All causes

2002

Source: CRS compilation from National Center for Health Statistics, Health, United States, 2004
with Chartbook on Trends in the Health of Americans, Table 29.

9(...continued)
20th Century,” Population Studies, vol. 29:391:422; (2) S.H. Preston, and E. Van de Walle,“Urban French Mortality Decline,” Population Studies, vol. 32(2), pp. 275-97, 1978.
10

CRS calculations from NCHS, Health, United States, 2004, With Chartbook on Trends
in the Health of Americans, 2004, Table 29. Uses 2000 standard population.
11

CDC, “Achievements in Public Health, 1900-1999, Decline in Deaths from Heart Disease
and Stroke, U.S., 1900-1999,” MMWR Weekly, Aug. 6, 1999, vol. 48(30), pp. 649-656.

CRS-5The CDC12 attributes the declines in diseases of the heart and cerebrovasculardiseases to a combination of!

medical advances, including— discoveries in diagnosing and treating heart disease and stroke;— development of effective medications for treatment of hypertension andhypercholesterolemia;— greater numbers of specialists and health-care providers focusing on
cardiovascular diseases;— an increase in emergency medical services for heart attack andstroke; and— an increase in coronary-care units.

!

changes in individually-controlled behaviors, including— declines in cigarette smoking;— decreases in mean blood pressure levels;— an increase in persons with hypertension who have the condition
treated and controlled;— a decrease in mean blood cholesterol levels; and— changes in the American diet (reductions in the consumption ofsaturated fat and cholesterol).

Beyond medical interventions, public health measures, and individual behaviors,
a number of additional factors are known to be associated with mortality decline.
They are briefly mentioned here, but it is beyond the scope of this report to discussthem in detail or to disentangle them from the factors already described:

12
13

!

Socioeconomic status (SES). Higher SES persons tend to be better
educated, have higher incomes, and practice better individual
behaviors (less smoking, healthier diets, etc.), and are more likely tohave financial resources or health insurance to ensure access to
medical care.

!

Social policies. Some social policies, such as Medicare andMedicaid, are oriented to health improvements. Both programs were
designed to increase access to health care for vulnerable populations,the elderly and the poor, with the ultimate goal of improving healthfor these groups. Other social policies, such as Social Security,
affect income, and may affect health and well-being through thatchannel. Finally, some social policies may affect health by changing
the access that people have to already-established resources. An
example is the combination of civil rights legislation and improved
health programs for the poor during the mid-1960s, especiallythrough Medicaid.13

Ibid.

D.M. Cutler and E. Meara, Changes in the Age Distribution of Mortality Over the 20th
Century, NBER, Working Paper No. W8556, Oct. 2001.

CRS-6

A Quick Global ComparisonLife expectancy in the United States, for both men and women, is significantly
higher than the global average but is only slightly higher than the average for moredeveloped countries14 (see Table 3). Life expectancy surpasses that of the UnitedStates in a large number of countries, including but not limited to Japan, Andorra,
Canada, Macau S.A.R., Hong Kong, Singapore, Sweden, Switzerland, Australia,
Martinique, Greece, Israel, Aruba, Italy, Netherlands, Norway, France, Liechtenstein,
Monaco, Spain, and more. Estimates are provided for a non-comprehensive list of
selected counties in Table 3. The United States was ranked 48th among 227 countries
and territories for both sexes.

Table 3. Life Expectancy at Birth (in Years) in Selected
Countries: A Global Comparison in 2002
Both Sexes

Males

Females

World

64

62

66

Less developed countries

62

61

64

More developed countries

76

73

80

Andorra

83

81

87

Macau S.A.R.

82

79

85

Japan

81

78

84

Singapore

80

77

83

Switzerland

80

77

83

Australia

80

77

83

Canada80

76

83

Iceland

80

77

82

Greece79

76

81

United States

77

74

80

Denmark

77

74

80

Source: CRS compilation based on data from the U.S. Census Bureau’s International Data Base,available at [http://www.census.gov/ipc/www/idbnew.html], accessed Feb. 3, 2005.

14

This characterization by the Census Bureau divides 227 countries and territories into twogroupings: “More developed” includes Japan, Australia, New Zealand, countries of North
America (excluding Latin America and the Caribbean), Europe, the Baltics, and the four
European countries of the NIS (Russia, Ukraine, Belarus, and Moldova). Other countries
are considered to be “less developed.” U.S. Census Bureau, International Population Reports
WP/02, Global Population Profile: 2002 (Washington, DC: GPO, 2004).

CRS-7

What Will Be the Future Course of American Longevity?
The Social Security Trustees report to Congress on the actuarial status of theTrust Funds annually. The long-range projections needed for this assessment depend
critically on assumptions for the future course of longevity. According to Steven
Goss, chief actuary of the Social Security Administration (SSA), their future
mortality assumptions are based on the recorded average annual mortality decline forthe total U.S. population aged 65 and older between 1900 and 2000.15 He asserted
that assuming future mortality improvement at nearly the same rate as for the lastcentury — a little more than 0.7% annually — is a reasonable assumption, with aroughly equal likelihood of doing better or worse. This rate of improvement is more
optimistic — about twice as large — as experienced during the last 18 years of the20th century. Goss further suggested that “matching the accomplishments of the past
century will not be easy. AIDS, SARS,16 and antibiotic resistant microbes, alongwith increasing obesity and declining levels of exercise, remind us that mortality
improvements will not be automatic. Gains from replacement organs and genetic
engineering will be expensive, and may be difficult to provide for the population asa whole.”17 SSA’s projections of life expectancy, are shown in Table 4.

Table 4. Projected Life Expectancies, SSA, in Selected Years(in years)
At Birth

At Age 65

Year

Male

FemaleMale

Female

2005

74.7

79.6

16.1

19.0

2025

76.9

81.3

17.4

20.0

2050

79.2

83.3

18.8

21.4

2075

81.2

85.0

20.1

22.7

Source: CRS compilation from: 2004 Annual Report of the Board of Trustees of Federal Old-Age and Survivors
Insurance and Disability Insurance Trust Funds, Table V, A3.
Notes: Interpretation of life expectancy at age 65, the average number of additional years that a person will live,
assuming that he has already attained age 65. For example, a 65 year old woman in year 2005 will live, on
average, an additional 19.0 years — to age 84.0 years (65.0 + 19.0). Table refers to SSA’s intermediate-range
period life expectancies.

15

Testimony of SSA S.C. Goss, chief actuary, in U.S. Congress, Senate, Special Committee
on Aging, The Future of Human Longevity: How Important Are Markets and Innovation?,hearings, 108th Cong., 1st sess., June 3, 2003, S.Hrg. 108-192 (Washington: GPO, 2003).
16

SARS (Severe Acute Respiratory Syndrome), a viral respiratory illness caused by acoronavirus. SARS was first reported in Asia in Feb. 2003. Over the next few months, theillness spread to more than two dozen countries in North America, South America, Europe,and Asia before the SARS global outbreak of 2003 was contained.
See[http://www.cdc.gov/ncidod/sars/factsheet.htm], accessed Feb. 7, 2005.
17

Testimony of SSA S.C. Goss, chief actuary, in U.S. Congress, Senate, Special Committee
on Aging, The Future of Human Longevity: How Important Are Markets and Innovation?,hearings, 108th Cong., 1st sess., June 3, 2003, S.Hrg. 108-192 (Washington: GPO, 2003).

CRS-8A benefit of the statistical methods that have emerged to extrapolate historicalmortality trends to the future is that they have worked well and are relatively simple
and efficient.18 In addition to being utilized by SSA, similar approaches are also usedin Canada and in the United Kingdom (UK). Canada’s approach assumes that
economic productivity is the overall driving factor for sustained longevity
improvements, and projects a relationship between future mortality decline and future
real growth in employment earnings.19 The UK extrapolates trends from 15 years ofpast data to help define base starting points and establish initial rates of mortality
improvement for projections. An assumption is also made that there will be a
gradual slowing of rates of improvement after the first 10 years.20
Future mortality and survival are, however, difficult to predict and specialists
disagree on not only the level but also the direction of future trends. James Vaupel,
director of the Max Planck Institute for Demographic Research, argues that the Social
Security projections are too pessimistic.21 He notes that SSA’s forecast is that female
life expectancy in the United States will gradually rise from 79.5 years today to 83.4
years in 2050.22 SSA’s projected level of life expectancy in 2050, half-a-century
from today, is less than current life expectancy in Japan and France, and is 13 to 14
years less than likely Japanese and French female life expectancy in 2050. Vaupel
further suggests that it is unrealistic for SSA to assume that the United States will be
unable to match the level of life expectancy in half-a-century that is already attainedin other countries today.
A number of articles were also published in the recent past that suggested thatcurrent models may be too pessimistic in their assumptions about mortality andsurvival probabilities (i.e., Americans may live longer than currently projected).23
Two of these studies showed that there has been a tendency for international life

18

R.B. Friedland, “Life Expectancy in the Future: A Summary of a Discussion Among
Experts,” North American Actuarial Journal, vol. 2, no. 4, Oct. 1998. See also, (1) S.C.
Goss and colleagues, “Historical and Projected Mortality for Mexico, Canada, and theUnited States,” and (2) M. Sze and colleagues, “Effect of Aging Population with Declining
Mortality on Social Security of NAFTA Countries,” both in North American Actuarial
Journal, vol. 2, no. 4, Oct. 1998.
19

B. Dussalt, cited in R.B. Friedland, “Life Expectancy in the Future: A Summary of a
Discussion Among Experts,” North American Actuarial Journal, vol. 2, no. 4, Oct. 1998.
20

C. Daykin, cited in R.B. Friedland, “Life Expectancy in the Future: A Summary of a
Discussion Among Experts,” North American Actuarial Journal, vol. 2, no. 4, Oct. 1998.
21

Testimony of J.W. Vaupel, director, Max Planck Institute for Demographic Research, in
U.S. Congress, Senate, Special Committee on Aging, The Future of Human Longevity: How
Important Are Markets and Innovation?, hearings, 108th Cong., 1st sess., June 3, 2003,
S.Hrg. 108-192 (Washington: GPO, 2003).
22

Note that cited figures differ slightly from those in Table 3. Vaupel was referring to the2003 Social Security Trustees Report, Table 3 presents the most recent data from the 2004
Trustees Report. This section is also presented in CRS Report RL32701, The Changing
Demographic Profile of the United States, by Laura Shrestha.
23

R. Lee, Report for the Roundtable Discussion of the Mortality Assumption for the Social
Security Trustees, note dated Sept. 11, 2002.

CRS-9expectancy to rise linearly by more than two years per decade over the past 40 years24
or the last 160 years,25 a more rapid pace than suggested by current models. Also, auseful analysis of the contribution of smoking behavior to mortality trends26 in the
United States suggests that slow female gains in life expectancy over the past few
decades may be temporary, and that the pace may pick up fairly soon.
Technological advances also have the potential to expand life. The National
Institute on Aging supports extensive analyses of genetic contributions to longevity
in diverse species, as well as on the diseases and conditions that are responsible forpremature death.27

Differentials in Life Expectancy
Sex Differentials. Life expectancy worldwide is generally higher for females
than for their male counterparts.28 The United States is no exception; female life
expectancy exceeded that of males in all years of the past century (see Figure 1).
The average girl born at the turn of the 20th century in the United States could
expect to live 50.7 years, roughly three years more than an American boy born at thesame time. From 1900 to 1975, the difference in life expectancy increased from 2.0
years to 7.8 years.29 Such large differences in life expectancy for the sexes in theabsence of war, which were also being recorded in other developed countries, are a
relatively recent phenomenon in demographic history.30 For the United States,
NCHS attributed the increasing gap during these years to increases in male mortality
due to ischemic heart disease and lung cancer, both of which increased largely as theresult of men’s early and widespread adoption of cigarette smoking. In the mid- tolate 1970s, the average gap in life expectancy approximated the average gap seen in

24

K. White, “Longevity Advances in High Income Countries, 1955-96,” Population andDevelopment Review, vol. 28, no. 1, Mar. 2002, pp. 59-76.
25

J. Oeppen, and J. Vaupel, “Broken Limits to Life Expectancy,” Science, vol. 296, May 10,
2002, pp. 1029-1030.
26

F. Pampel, “Cigarette Use and the Narrowing Sex Differential in Mortality,” Population
and Development Review, vol. 28, no. 1, Mar. 2002, pp. 77-104.
27

Examples of technological advances and promising areas of research are provided in thetestimony of R. Hodes, Director, National Institute on Aging, to a Hearing of the Senate
Special Committee on Aging on The Future of Human Longevity: How Important Are
Markets and Innovation?, June 3, 2003.
28

A handful of exceptions includes a few countries in Africa (with high, and differential,
rates of mortality due to HIV/AIDS) or in South Asia (where women’s mortality rates had
traditionally been higher due to lower social status and difficult life conditions).
29
30

Exact years not shown in Figure 1.

United Nations, Sex Differentials in Life Expectancy and Mortality in Developed
Countries: An Analysis by Age Groups and Causes of Death from Recent and Historical
Data, Popul Bull of the United Nations, No. 25-1988, ST/ESA/SER.N/25.

CRS-10developed countries today — roughly seven years.31 The gap can be as great as 13
years, as seen in parts of the former Soviet Union as a result of unusually high levelsof current adult male mortality.32
Figure 1. Life Expectancy at Birth, by Sex: 1900 to 2003
90

80.1

80

74.8

70
60
IN YEARS

48.3

Females

50
40

Males
46.3

Female Advantage
Influenza
Epidemicof 1918

30
20

7.8
10
0
1900

5.3

1.0
1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

Source: For 1900-2002, CRS analysis based on data contained in National Center for Health Statistics(NCHS), United States Life Tables, 2002, National Vital Statistics Report, vol. 53, no. 6, Nov. 10,
2004. For 2003, CRS analysis based on NCHS, Deaths: Preliminary Data for 2003, National Vital
Statistics Report, vol. 53, no. 15, Feb. 28, 2005.
Notes: Data for year 2003 are preliminary; NCHS is scheduled to release final data in Nov. 2005.
Later year estimates are more reliable than those of the early 20th century. The federal civil
registration system began in 1900 with the setting up of the Death Registration Area. States were only
admitted to the registration areas as qualification standards were met. Only 10 states and the Districtof Columbia were in the original death registration area of 1900. Statistics prior to 1939-1941 arebased on data from these death registration states. Alaska is first included in 1959 and Hawaii in the1960 figures respectively.

Since 1979, the “female advantage” in life expectancy between the sexes in the
United States has narrowed from 7.8 to 5.4 years, reflecting proportionately greater
increases in lung cancer mortality for women than for men and proportionately larger
decreases in heart disease mortality among men.33 The average girl born in 2002 in
the United States could expect to live 79.9 years compared to 74.5 years for a boyborn in the same year.
31

K. Kinsella and Y.J. Gist, Gender and Aging, International Brief: Mortality and Health,Census Bureau, IB/98-02, Oct. 1998.
32
33

Ibid.

E. Arias, United States life tables, 2002, NVSR, vol. 53, no. 6, Nov. 10, 2004, based on:(1) R.N. Anderson, “Some trends and comparisons of United States life table data: 19001991,” vol. 1, no. 3, 1999, and (2) I. Waldron, “Recent Trends in Sex Mortality Ratios for
Adults in Developed Countries,” Social Science and Medicine 36:451-62, 1993.

CRS-11
A now dated, but still informative, study evaluated the contributions of various
causes of death to the size of sex differentials in life expectancy in developed
countries for the early 1980s.34 Diseases of the circulatory system were found toaccount for nearly 40% of the mean sex differential in life expectancy; neoplasms(cancer) for 18%, accidents, suicide, and violence for 19%, and diseases of therespiratory system for nearly 10%.35
In general, why is life expectancy longer for women? The answer, which is still
being investigated, involves the complicated interplay of a host of biological, social,
and behavioral conditions. In addition, it differs according to age and to theunderlying disease and mortality profiles for men and women. At birth, boys havea clear advantage. In the United States, 104.8 boys were born for every 100.0 girls
in 2002.36 But, male mortality exceeds that of females in every age group and formost major causes of death, beginning in infancy and continuing through the oldestold age groups. One researcher has suggested that the male advantage at birth ismoderated by higher male mortality to “ensure that the number of men and women
will be about the same at reproductive age.”37
Biological Factors. It has long been argued that hormones play a role inlongevity. As described by Desjardins,38 the female hormone estrogen helps toeliminate “bad” cholesterol (LDL) and thus may offer some protection against heartdisease.39 In contrast, some say, testosterone, found in greater amounts in males, may
make men more likely to engage in violence and risk-taking behavior, especially if
reinforced by cultural influences.40 Women may also gain an additional biologicaladvantage because of their two X chromosomes. If a gene mutation occurs on one
X, women’s second X chromosome may be able to compensate. In comparison,
genes on men’s sole X chromosome may be expressed, even if they are deleterious
without compensation.

34

United Nations, “Sex Differentials in Life Expectancy and Mortality in Developed
Countries: an Analysis by Age Groups and Causes of Death from Recent and Historical
Data,” UN Population Bulletin, 1988;25:65-107.
35

Note that CVD and neoplasms were the two leading causes of death in the total
population.
36

CRS calculations based on data in NCHS “Births, Final Data for 2002,” NVSR, vol. 52,
no. 10, Dec 17, 2003.
37

B. Desjardins, “Ask the Experts,” Scientific American, Dec. 2004, vol. 291, issue 6, p.
118.
38

Ibid.

39

See W.R. Hazzard, “Biological Basis of the Sex Differential in Longevity,” Journal of theAmerican Geriatrics Society, vol. 34, 1986, p. 455, who argued that the sex differential insex hormone levels gives rise to the sex differential in lipoprotein metabolism which in time
(given our lifestyle) contributes to the sex differential in atherosclerosis and this in turn tosex differentials in longevity.
40

I. Waldron, “Sex Differences in Human Mortality: the Role of Genetic Factors,” Social
Sciences and Medicine, vol. 17, no. 6, pp. 321-333.

CRS-12Stindl,41 however, argues that the classic biological explanation does notwithstand critical analysis.42 He offered an alternative hypothesis that has not yet
been subject to long term scientific scrutiny. He asserts that a strong positive
correlation has been reported between sexual size dimorphism (SSD)43 and malebased mortality, with men being the larger/taller sex globally. A larger body requires
more cell doublings, especially due to the ongoing regeneration of tissues over a
lifetime. Accordingly, the replicative history of male cells might be longer than thatof female cells, resulting in the exhaustion of the regeneration potential and the early
onset of age-associated diseases predominantly in males. The underlying mechanismis the gradual erosion of chromosome ends (telomeres); two recent studies confirm
that men do have shorter telomeres than women at the same ages. Numerous studies
also demonstrate links between chronic stress and indices of poor health, including
risk factors for cardiovascular disease and poorer immune function.44
Behavioral and Social Differences. Many researchers believe thatbehavioral and social factors contribute significantly to the sex differentials noted
between men and women. The most cited contributors to higher male mortality rates
are greater male exposure to specific risk factors, especially tobacco use, alcohol
consumption, and occupational hazards. Women’s social status and life conditions,such as the hardships associated with childbirth, may have nullified American
women’s biological advantage at the beginning of the 20th century but are no longera major factor in differentials in life expectancy in the United States.
Race Differentials.45 Life expectancy at birth for whites significantly
exceeded that for blacks at the turn of the 20th century (see Figure 2 and Appendix
B Table A1). At that time, the expected longevity of a white newborn girl exceededthat of a black newborn girl by about 16.0 years (with longevity measured at 51.1
years vs. 35.0 years, respectively). For newborn boys, the white advantage was 15.7
years (48.2 years vs. 32.5 years).

41

R. Stindl, “Tying it All Together: Telomeres, Sexual Size Dimorphism and the Gender
Gap in Life Expectancy,” Medical Hypotheses, 2004:62, pp. 151-154.
42

Stindl shows that estrogen levels in postmenopausal women are virtually identical toestrogen levels in males and can hardly explain the discrepancy. He notes that testosterone
got its bad reputation from one outdated study on a non-representative sample of men. And,
since it’s unlikely that mutations in genes on the X chromosome are involved in all agerelated diseases and that mutated versions of these genes occur in all men, the model might
be of academic value only.

43

In biology, a dimorphism refers to having two different distinct forms of individuals
within the same species or two different distinct forms of parts within the same organism.
Sexual dimorphism is a common case, which refers to the fact that the two sexes havedifferent shapes, sizes, etc. from each other.

44

E.S. Epel and colleagues, “Accelerated Telomere Shortening in Response to Life Stress,”
PNAS, vol. 101, no. 49, Dec. 7, 2004.
45

This section considers only the differentials between blacks and whites, as these are themain categories available in the NCHS life table publications that this analysis is based on.

CRS-13
Figure 2. Trends in Life Expectancy at Birth,by Race and Sex, 1900 to 2003
90
80
70

IN YEARS

60
50White Females

40

White Males

30

Black Females
20Black Males

10
0
1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

Source: For 1900 to 2002, CRS compilation from National Center for Health Statistics (NCHS),
National Vital Statistics Reports, vol. 53, no. 6, Nov. 10, 2004. For 2003, NCHS, National Vital
Statistics Reports, vol. 53, no. 15, Feb. 28, 2005.
Notes: Later year estimates are more reliable than those of the early 20th century. The federal civil
registration system began in 1900 with the setting up of the Death Registration Area. States were only
admitted to the registration areas as qualification standards were met. Only 10 states and the Districtof Columbia were in the original death registration area of 1900. Statistics prior to 1939-1941 arebased on data from these death registration states. The data points for the early decades are notsmoothed; they refer to the situation in 1900, 1910, etc. in the early decades. Alaska is first included
in 1959 and Hawaii in the 1960 figures respectively.

The gap between whites and blacks in average longevity declined significantly
over the past century (Figure 3). For females, the improving situation for black
women relative to their white counterparts was dramatic and mostly consistentthroughout the century. From the height of the differential in 1904 — when white
women survived, on average, 17.9 years longer than then black women — the gap
fell to 4.4 years in 2003 (preliminary estimate).
A significant reduction in the life expectancy gap between American white andblack men was also observed over the 20th century. From its height of 17.8 years in
1904, the differential had fallen to 6.2 years in 2003. The improvement was most
rapid in the first six decades of the past century. Since the mid-1950s, however,improvements for males have stagnated in the range of roughly 6.0 to 8.5 years.
While the male gap has been falling over the past decade, this trend obscures the factthat the differential had already been at or near this level for most of the mid-1950s
to mid-1960s. The gap in 1961 was narrower than that observed today — at thattime, the gap between white and black men was 5.8 years. Factors that contribute to
the differential are discussed in later sections of this report.

CRS-14
Figure 3. Differences in Values of Life Expectancy at Birth Between
Whites and Blacks, by Sex, 1900-2003
18
16

Females14

Males

IN YEARS

12
10
8
6
4
2
0
1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

Source: For 1900-2002, CRS computation based on, NCHS, United States Life Tables, vol. 53, no.
6, Nov 10, 2004. For 2003, NCHS, Deaths: Preliminary Data for 2003, vol. 53, no. 15, Feb. 28, 2005.
Notes: Later year estimates are more reliable than those of the early 20th century. The federal civil
registration system began in 1900 with the setting up of the Death Registration Area. States were only
admitted to the registration areas as qualification standards were met. Only 10 states and the Districtof Columbia were in the original death registration area of 1900. Statistics prior to 1939-1941 arebased on data from these death registration states. To correct for data irregularities, the data points
are smoothed in the early decades. The life expectancy data points in 1904 refer to the 10-year
average values for 1900-1909; the data points in 1914 refer to the average of 1910-1919, etc. Alaska
is first included in 1959 and Hawaii in the 1960 figures respectively.

In summary, mortality rates in the United States have declined dramatically overthe past century. Black persons, however, still live, on average, 5.4 fewer years thantheir white counterparts. In 2002, the most recent year for which we have official
data, the highest life expectancy was observed for white females, who will live, on
average, 80.3 years. The values for black females and white males are quite similar
to each other — 75.6 years and 75.1 years, with black females having the slightadvantage. Of the four race-sex groups considered, black males have the shortest
average longevity — 68.8 years. Within-sex groupings, whites have the advantage
for both females and males.
What accounts for the higher mortality, and subsequent lower life expectancy
for blacks, and especially for black men in the United States? This has been a subjectof research by medical and social scientists for at least a century, and the issue stands
at the heart of the current public health agenda in the United States.46 One of the two
primary goals of Healthy People 2010 is to eliminate health disparities.

46

U.S. Dept. of Health and Human Services, Tracking Healthy People 2010, 2000.

CRS-15
Mortality from most causes of death are higher for blacks, and a number of
researchers have investigated which specific diseases contribute most to life
expectancy differences between the races. Wong and colleagues,47 for instance,
recently calculated potential years of life lost related to specific causes of deaths forblacks and whites in the United States (Table 5).

Table 5. Racial Disparity in Potential Life Years Lost
(Percent contribution of specific cause of death to overall racial disparity)

Cause of death% ofDisparity

Cardiovascular disease

34.0

Cause of death
Infection% ofDisparity
21.1

Ischemic heart disease

5.5

Tuberculosis

0.6

Cerebrovascular stroke

2.8

Pneumonia

5.2

Hypertension

15.0

Viral hepatitis

0.1

Congestive heart
failure0.1

Sepsis

3.4

Other arteriosclerotic

5.6

HIV

11.2

Other CVD disease

5.0

Other infections

0.6

Cancer

3.4

All trauma

10.7

Lung disease(5.8)

Motor vehicle accident

2.5

Diabetes mellitus

8.5

Suicide(2.5)

Liver disease

2.6

Homicide

8.5

Alcohol-related diseases

0.8

Other accidents

2.2

Renal disease

4.0

All other causes

19.8

Rheumatologic diseases

1.4

Total

100.0

Source: CRS adaptation from M.D. Wong and colleagues, “Contribution of Major Diseases to
Disparities in Mortality,” New England Journal of Medicine, vol. 347, no. 20, Nov. 14, 2002.
Notes: Calculations adjust for differences between races in age, sex, and level of education; numbers
in parentheses show causes-of-death for which blacks fare better than whites; and these estimates arefor persons dying before the age of 75 years though the authors state that all results were similar whenpotential life-years lost before the age of 85 years were examined. Note that trends and racialdifferentials at the oldest ages (85 and older) differ as black mortality rates are lower than those ofwhites for both men and women in official mortality data from NCHS. See Appendix B Table A2.

47

M.D. Wong and colleagues, “Contribution of Major Diseases to Disparities in Mortality,”
New England Journal of Medicine, vol. 347, no. 20, Nov. 14, 2002.

CRS-16
As seen in Table 5, when considering the major categories of disease, deaths
from cardiovascular disease contributed most to the racial disparity in mortality fromany cause (34.0%), followed by infection (21.1%), and trauma (10.7%).
When looking at specific diseases, the leading sources of the disparity werelargely preventable causes of premature death — hypertension (which contributed
15.0% to the disparity), followed by HIV disease (11.2%), diabetes (8.5%), andhomicide (8.5%). Note that blacks had a lower mortality risk from respiratory
diseases (lung disease), suicide, and certain types of cancer (breast, colon, uterus orovary, bladder or kidney, and leukemia or lymphoma; figures in original source but
not shown in table). These results are consistent with findings from other studies,48
and are said to show that “most of the influential diseases are ones in which the rates
vary based on avoidable risks such as smoking, exposure to HIV, and obesity. [And,]
this adds to the credibility of public-health interventions aimed at reducing theexposure to these risk factors.”49 The results may also offer hope for the eliminationof racial disparities in health.50
Beyond describing gross health disparities, scientific inquiry has shifted to
explaining the underlying factors that account for these differences in healthoutcomes. Understanding these underlying causes requires disentangling thecomplex web of factors connecting the nexus among race, socioeconomic status,
behavioral factors, and health.51 Some have argued that, if pertinent differences
between whites and blacks in their underlying social, demographic, familial, andeconomic circumstances were eliminated, racial differences in mortality would besignificantly reduced.52,53
Socioeconomic arguments cite the consequences of lifelong poverty. Relevant
factors include both early-life differences, such as birth weight and childhood
nutrition, and mid-life variables (such as access to employer-provided healthinsurance, the strain of physically demanding work, and exposure to a broad rangeof toxins, both behavioral (e.g., smoking) and environmental (e.g., workplace
exposures). Over the life cycle, these factors combine to increase the demand for
health care, while potentially limiting consumption of necessary health services. In

48

See, for instance, R.G. Rogers, “Living and Dying in the U.S.A.: Sociodemographic
Determinants of Death Among Blacks and Whites,” Demography, vol. 29, no. 2, May 1992,
pp. 287-303.
49

P. Bach (Memorial Sloan-Kettering Cancer Center), cited in D. Lawrence, “Which
Diseases Contribute to Life-Expectancy Differences Between Races?,” The Lancet, vol. 360,
Health Module, Nov. 16, 2002, p. 1571.
50

Ibid, p. 1571.

51

J.P. Smith and R.S. Kington, “Race, Socioeconomic Status, and Health in Late Life,” inNational Research Council, Racial and Ethnic Differences in the Health of Older
Americans, 1997.
52
53

Ibid.

R.G. Rogers, R.A. Hummer, and C.B. Nam, “Living and Dying in the U.S.A.: Behavioral,
Health, and Social Differentials of Adult Mortality,” Academic Press, 2000.

CRS-17late life, these factors may affect the age of onset of both morbidity and disability, theseverity of symptoms, and ultimately the age at, and cause of death.54
In addition, Martin and Soldo55 note that there are differences between racial
groups in norms regarding not only lifestyle and self-care behaviors, but also inaccess to health care providers and treatment compliance. Moreover, the experienceof racial discrimination may have adverse psychological and physiological effects,
in addition to limiting the quantity and quality of health care received. Some of thesefactors that contribute to the racial gap in life expectancy will be discussed briefly inthe following paragraphs.
Economic and Social Factors. In general, as income increases, mortality
decreases, because high income provides access to high-quality health care, diet,housing, and health insurance. Black households had the lowest median income in
the United States in 2003. Their median money income was about $30,000, which
was 62% of the median for non-Hispanic White households (about $48,000).56
Poverty rates among African Americans are persistently higher than those of nonHispanic whites. In 2003, 24.4% of blacks were poor, compared to 8.2% of nonHispanic whites.57
Recent research also highlights the enduring effects of education. Increased
education appears to lower the risks for some chronic diseases — most notably,coronary heart disease (which is the leading cause of death in the United States) —while retarding the pace of disease progression for other conditions.58 In 2003, theproportion of both blacks and non-Hispanic whites who had a high school diploma(of persons in the population aged 25 and over) reached record highs but at different
levels for the two racial groups — 80% and 89%, respectively. The gap in
educational attainment is also apparent among recipients of bachelor’s degrees —30% of non-Hispanic whites aged 25 and older had attained a four-year college
degree compared to 17% of blacks.59

54

L.G. Martin and B.J. Soldo, “Introduction,” in R.A. Hummers, M.R. Benjamins, R.G.
Rogers, eds., Racial and Ethnic Differences in the Health of Older Americans, National
Research Council (Washington: The National Academies Press, 1997) (hereafter: NRC,
1997).
55

Ibid.

56

C. DeNavas-Walt, B.D. Proctor, and R.J. Mills, Income, Poverty, and Health Insurance
Coverage in the United States, 2003, U.S. Census Bureau, Current Population Reports, P60226, 2004. Note that the distribution of household income is influenced by many factors,
such as the number of earners and household size. If a comparison is made instead on percapita income, the median money income for whites is $24,442 compared to $15,583 forblacks.
57

CRS Report 95-1024, Trends in Poverty in the United States, by Tom Gabe.

58

L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.

59

N. Stoops, Educational Attainment in the United States, 2003, Population Characteristics,
U.S. Census Bureau, Current Population Reports, P20-550.

CRS-18
Marriage is also a socioeconomic determinant that is related to health outcomes.
Married people consistently exhibit lower levels of mortality than those who are notmarried. Marriage acts to select healthy individuals, but it also enhances social
integration and encourages healthful behaviors.60 Race differences in marital andcohabitational stability are substantial, and may be increasing over time. About 91
percent of white women born in the 1950s are estimated to marry at some time intheir lives, compared with 75% of black women. Black married couples are more
likely to break up than white married couples, and black divorcees are less likely toremarry than white divorcees.61 The degree of attachment to marriage among black
Americans is similar to that of white Americans as measured by attitudes towardmarriage. One explanation offered by some researchers for the lower proportion oftime spent in marriage among black Americans is the idea of a “marriage squeeze,”in which the “marriageable pool” of black men is low due to high rates ofjoblessness, incarceration, and mortality. Employed men are more likely thanunemployed men to marry.62
Behavioral Risk Factors. Prolific research over the past two decades has
confirmed the link between certain diseases and health outcomes and various healthdamaging (such as smoking, alcohol abuse) and health-promoting (exercise, low-fatdiet) behaviors. And, some researchers have explored the extent to which healthdamaging and health-promoting behaviors explain black-white differences in healthstatus. Berkman and Mullen,63 for instance, found that, despite greater apparent
concern on the part of blacks than whites about their health, blacks do notconsistently adopt more beneficial behaviors than whites. Older blacks engage inless physical activity and are more likely to be obese (especially women), but they areless likely to consume alcohol than whites. Racial differences in smoking patterns
are complex, with older blacks less likely to have smoked but, if they have, less likely
to have quit. Lack of exercise and obesity are associated with hypertension anddiabetes, both of which have been reported to be twice as common among blacks
than among whites.64

60

R.G. Rogers, “Living and Dying in the U.S.A.: Sociodemographic Determinants of Death
Among Blacks and Whites,” Demography, vol. 29, no. 2, 1992, pp. 287-303.
61

M.D. Bramlett, and W.D. Mosher, “Cohabitation, Marriage, Divorce, and Remarriage inthe United States,” NCHS, Vital Health Stat 23(22), 2002.
62

Ibid.

63

L.F. Berkman and J.M. Mullen, “How Health Behaviors and the Social Environment
Contribute to Health Differences between Black and White Older Americans,” in NRC,
1997. See also, M.A. Winkleby, and C. Cubbin, “Racial/Ethnic Disparities in HealthBehaviors: a Challenge to Current Assumptions,” in N.B. Anderson, R.A. Bulatao, and B.
Cohen, eds., Critical Perspectives on Racial and Ethnic Differences in Health in Late Life,
National Research Council, Panel on Race, Ethnicity, and Health in Later Life, Committee
on Population, Division of Behavioral and Social Sciences and Education (Washington: The
National Academies Press, 2004), pp.310-352 (hereafter: NRC, 2004).
64

L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.

CRS-19
Access to Health Care. The United States is the only developed country in
the world that does not have national health coverage,65 and significant numbers ofAmericans, and especially African Americans, do not have sufficient health carecoverage. More specifically, 21.0% of blacks under age 65 and 12.9% of whites ofthe same age lacked private health insurance in 2003.66
Beyond health insurance, Chandra and Skinner67 argue that there is differential
access to health services in the United States, especially because of geographic
variation in treatment and outcome patterns. Minorities tend to seek care fromdifferent hospitals and from different physicians than non-Hispanic whites, in largepart a reflection of the general spatial distribution of the United States population
with concentrations of minorities in certain hospital referral regions.
Genetic Factors. Some research suggests that there are race-related genetic
factors both for predisposing conditions, such as hypertension and diabetes mellitus,
and for life-threatening conditions, such as aplastic anemia. As recently noted by the
National Research Council, however, “Probably no aspect of the debate about thecauses of racial differences in health is potentially more sensitive than the discussion
about the extent to which genetic factors are in any way responsible. There are
numerous historical examples of scientific mischief in the support of racism.”68
Those in favor of using race assert that there is a useful degree of association between
genetic differences and racial classifications, so that the use of race as a researchvariable is warranted. Opponents, however, argue that bundling the population into
four or five categories based on skin color or other traits is not a useful way tosummarize genetic variation when we know that there are at least 15 million genetic
polymorphisms in humans, of which an unknown number underlie variation in(normal and) disease traits.69
Research in this area is still in its infancy and tends to reflect two ways thatgenes may be relevant to the study of health differentials.70 First, there are a small
number of conditions with single-gene disorders in populations that have descended
from a relatively small number of people and that remain endogamous71 (an example
is Tay-Sachs Disease among Ashkenazi Jews). Second, genes may be relevant to thestudy of health differentials through environmental factors, which may vary by racial

65

B. Cohen, “Introduction,” in NRC, 2004, p. 16.

66

CRS Report 96-891, Health Insurance Coverage: Characteristics of the Insured andUninsured Populations in 2003, by Chris Peterson.
67

A. Chandra and J.S. Skinner, “Geography and Racial Health Disparities,” in NRC, 2004,
pp. 604-642.
68

B. Cohen, “Introduction,” in NRC, 2004, p. 9.

69

E.G. Burchard and colleagues, “The Importance of Race and Ethnic Background in
Biomedical Research and Clinical Practice,” New England Journal of Medicine, vol. 348,
no. 12, pp. 1170-1175, 2003.
70

See R.S. Cooper, “Genetic Factors in Ethnic Differences in Health,” in NRC, 2004, pp.
269-309.
71

Marriage within a specific group as required by custom or law.

CRS-20or ethnic group, and which might interact with genotype to produce different
outcomes for different groups.

Conclusion
One of the most important public health achievements of the 20th century in the
United States was the dramatic and widespread increase in life expectancy that
occurred over the past century in the United States — first as a result of the controlof the infectious and parasitic diseases that had plagued mostly infants and children
in the early part of the century, and later because of medical advances that led to large
decreases in adult mortality, especially from two of the most prevalent causes ofdeath — cardiovascular diseases and cerebrovascular diseases.
A consequence of the improved survival, coupled with declining fertility rates,is that the United States is in the midst of a profound demographic change: rapid
population aging, a phenomenon that is replacing the earlier “young” age-sex
structure with that of an older population.72 Hastened by the retirement of the “BabyBoom” generation (the cohort born between 1946 and 1964), the inexorable
demographic momentum will have important implications for a large number of
essential economic and social domains, including work, retirement, and pensions,wealth and income security, and the health and well-being of the aging population.
Whether the life expectancy improvements will continue is the subject ofintense debate. The Social Security Administration (SSA) assumes that the rate of
future mortality improvements will be nearly the same as for the last century — alittle more than 0.7% annually — while asserting that it may be difficult to match theaccomplishments of the past century, especially in light of increasing obesity,
declining levels of exercise, and the introduction of new scourges, such as AIDS,SARS, antibiotic resistant microbes.73 Some demographers, on the other hand, feelthat such projections are pessimistic, and argue, based on historical trends andevidence from other developed countries, that American survival will be longer thanthat projected by SSA.74 The outcome of the debate has important implications fordetermining the number of future beneficiaries and ultimately the financial soundnessof the Social Security and the Medicare programs.
This report also highlights the continuing differentials in life expectancy by raceand sex in the United States, with black males continuing to be the mostdisadvantaged group on this measure. Life expectancy at birth in 2002 for black
males measured 68.8 years, falling short of the comparable figure for white males by
72

CRS Report RL32701, The Changing Demographic Profile of the United States, by Laura
B. Shrestha.
73

Testimony of SSA S.C. Goss, chief actuary, in U.S. Congress, Senate, Special Committee
on Aging, The Future of Human Longevity: How Important Are Markets and Innovation?,hearings, 108th Cong., 1st sess., June 3, 2003, S.Hrg. 108-192 (Washington: GPO, 2003).
74

Testimony of J.W. Vaupel, director, Max Planck Institute for Demographic Research, in
U.S. Congress, Senate, Special Committee on Aging, The Future of Human Longevity: How
Important Are Markets and Innovation?, hearings, 108th Cong., 1st sess., June 3, 2003,
S.Hrg. 108-192 (Washington: GPO, 2003).

CRS-21
6.3 years. The gap between black and white men has remained relatively stagnant
since the mid-1950s.
The sources of the racial disparities in life expectancy are complex and requiredisentangling the complex web of factors connecting the nexus among race,socioeconomic status, behavioral factors, and health. Differences exist on a wide
variety of important variables including lifetime income and wealth, marriage
patterns, birth weight and childhood nutrition, access to employer-provided healthinsurance, the strain of physically demanding work, exposure to toxins, risky
behaviors (such as smoking, high saturated diet), adherence to preventative healthmeasures (such as maintaining a healthy weight, exercise), and access to and qualityof health care. In addition, the experience of racial discrimination may have adverse
psychological and physiological effects, in addition to limiting the quantity andquality of health care received.75
Recent research, however, that shows that the leading specific diseases that are
the main sources of the racial disparity in life expectancy are largely preventablecauses of premature death offers hope that public-health interventions can reduce the
racial disparities. Specifically, the leading causes of the racial disparity were
hypertension (which contributed 15.0% to the disparity), followed by HIV disease(11.2%), diabetes (8.5%), and homicide (8.5%) in a recent analysis.76

75
76

L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.

M.D. Wong and colleagues, “Contribution of Major Diseases to Disparities in Mortality,”
New England Journal of Medicine, vol. 347, no. 20, Nov. 14, 2002.

CRS-22

Appendix A. Glossary of Terms
Age-adjustment. Procedure used to compare risks of two or more populations at
one point in time or one population at two or more points in time. Age-adjusted rates
eliminate differences in observed (crude) rates that result from age differences in
population composition.
Age-specific rate. A rate that relates a given demographic event at a specific age (orage group) to the corresponding at-risk population in the same age (or age group).
For example, the age-specific death rate in a particular population for persons aged
40-44 = [(Deaths to persons aged 40-44)/(Total population aged 40-44)] * 1000.
Aging (of population). A process in which the proportion of adults and elderly
increase in a population, while the proportion of children and adolescents decrease.
This process results in a rise in the median age of the population.
At-risk population. The persons to whom an event can potentially occur. In theform of the population at the middle of a given period, such as a year, it is used as an
approximation of “person-years lived.” See also age-specific rate.
Birth cohort. Members of a population born in a given period (e.g., year 1900, time
period 1946-1964, 2002).
Cohort. A group of people who experience the same demographic event during aparticular period of time such as their year of birth. Cohorts are typically defined on
the basis of an initiating signal event (e.g., birth) but they can also be defined on thebasis of a terminating signal event (e.g., death).
Crude rate. A rate that relates a demographic event to the total population andmakes no distinction concerning different exposure levels to the event.
Death. The permanent disappearance of all evidence of life at any time after a live
birth has taken place. The loss of a member of a population, as recorded by a deathcertificate.
Death rate. The number of deaths per 1,000 persons in the population in a given
year. Also referred to as the crude death rate. See also age-specific rate.
Death Registration Area. In the United States, the states and local governmentscomplying with federal standards for the registration of deaths. It was established in1900 and by 1933 encompassed all states.
Expectation of life. A statistical measure of the average amount of time (usually
measured in years) remaining for a person or group of persons before death, usuallyestimated using a life table.

CRS-23
Life expectancy. An estimate of the average number of additional years a person
could expect to live if the age-specific death rates for a given year prevailed for the
rest of that person’s life. Also refers to the average number of years of life remaining
to a group of persons who reached a given age, as calculated from a life table. Most
commonly refers to life expectancy at birth; can also be calculated for other ages.
Life span. The maximum age that human beings could attain under optimum
conditions. The extreme upper limits of human life.
Life table. A statistical model composed of a combination of age-specific mortality
rates for a given population. A period life table is constructed by using mortality andage data from a single point in time; a generational life table is based on the mortalityof an actual birth cohort followed over time (to its extinction).
Life table functions. The fundamental elements of a life table include number
surviving to a given age, the number of deaths to those surviving to a given birthday
before they reach a subsequent birthday, the probability of dying before reaching a
subsequent birthday for those who survived to a given birthday, the number alive
between two birthdays, and the years of life remaining for those who survive to agiven birthday (including birth).
Longevity. Length of life; life span. “Average longevity” usually refers to life
expectancy.
Mean age at death. The arithmetic mean age at death of the reported deaths in agiven year. In the life table, the mean age at death of life table deaths is equal to life
expectancy at birth in the same life table.
Morbidity.
population.

The frequency of disease, illness, injuries, and disabilities in a

Mortality. A general term for the incidence of deaths in a population.
Period life table. A life table based on mortality data collected at a given point intime (frequently one year) for a given population.
Person-years lived. The total number of years (and fractions thereof) lived by agiven population or population segment during a given period of time. It isapproximated by computing the product of (1) the number of persons in the
population or population segment and (2) the amount of time in years (and fractions
thereof) lived by these persons during the time in question. See also: at-risk
population and life table.
Population. The “inhabitants” of a given area at a given time.
Potential life years lost. See years of potential life lost.

CRS-24
Race. In theory, classification of the members of a population in terms of biologicalancestry. In demographic practice, classification of the members of a population interms of socially constructed definitions of membership in categories in which skincolor or other characteristics, including national ethnic affiliations, may be the basisof assignment by census or survey enumerators or by self-enumeration. In the UnitedStates decennial census, persons are self-identified by race.
Sex. Classification of the population into the categories of male and female.
Survival. Primarily a condition where an individual or group remains alive after a
specified interval.
Survival rate. A rate expressing the probability of survival of a population group,
usually an age group, from one date to another and from one age to another. Can bebased on life tables or two censuses.
Years of potential life lost. Measure of the relative impact of various diseases andlethal forces on society, computed by estimating the years that people would have
lived if they had not died prematurely from injury or disease. Sometimes referred toas potential life years lost.
Appendix Source: CRS compilation based on: (1) J.S. Siegel and D.A. Swanson, eds. The
Methods and Materials of Demography, 2nd ed. Elsevier Academic Press, 2004; (2) S.H.
Preston, P. Heuveline, and M. Guillot, Demography: Measuring and Modeling Population
Processes, Blackwell Publishing, 2001; and (3) A. Haupt and T.T. Kane. Population
Reference Bureau’s Population Handbook, 4th International Edition, Wash., DC, Population
Reference Bureau, 1998; (4) National Center for Health Statistics, Health, United States,
2004,With Chartbook on Trends in the Health of Americans, Hyattsville, MD, 2004,
Appendix 2.

CRS-25

Appendix B. Detailed Life Expectancy Tables
Table A1. Life Expectancy at Birth, by Race and Sex: 1900-2003(in years)
All Races
Yr.
Sex

Both

Blacka

White

M

F

Both

M

F

Both

M

F

United Statesb
2003

77.6

74.8

80.1

78.0

75.4

80.5

72.8

69.2

76.1

2002

77.3

74.5

79.9

77.7

75.1

80.3

72.3

68.8

75.6

2001

77.2

74.4

79.8

77.7

75.0

80.2

72.2

68.6

75.5

2000

77.0

74.3

79.7

77.6

74.9

80.1

71.9

68.3

75.2

1999

76.7

73.9

79.4

77.3

74.6

79.9

71.4

67.8

74.7

1998

76.7

73.8

79.5

77.3

74.5

80.0

71.3

67.6

74.8

1997

76.5

73.6

79.4

77.2

74.3

79.9

71.1

67.2

74.7

1996

76.1

73.1

79.1

76.8

73.9

79.7

70.2

66.1

74.2

1995

75.8

72.5

78.9

76.5

73.4

79.6

69.6

65.2

73.9

1994

75.7

72.4

79.0

76.5

73.3

79.6

69.5

64.9

73.9

1993

75.5

72.2

78.8

76.3

73.1

79.5

69.2

64.6

73.7

1992

75.8

72.3

79.1

76.5

73.2

79.8

69.6

65.0

73.9

1991

75.5

72.0

78.9

76.3

72.9

79.6

69.3

64.6

73.8

1990

75.4

71.8

78.8

76.1

72.7

79.4

69.1

64.5

73.6

1989

75.1

71.7

78.5

75.9

72.5

79.2

68.8

64.3

73.3

1988

74.9

71.4

78.3

75.6

72.2

78.9

68.9

64.4

73.2

1987

74.9

71.4

78.3

75.6

72.1

78.9

69.1

64.7

73.4

1986

74.7

71.2

78.2

75.4

71.9

78.8

69.1

64.8

73.4

1985

74.7

71.1

78.2

75.3

71.8

78.7

69.3

65.0

73.4

1984

74.7

71.1

78.2

75.3

71.8

78.7

69.5

65.3

73.6

1983

74.6

71.0

78.1

75.2

71.6

78.7

69.4

65.2

73.5

1982

74.5

70.8

78.1

75.1

71.5

78.7

69.4

65.1

73.6

1981

74.1

70.4

77.8

74.8

71.1

78.4

68.9

64.5

73.2

1980

73.7

70.0

77.4

74.4

70.7

78.1

68.1

63.8

72.5

1979

73.9

70.0

77.8

74.6

70.8

78.4

68.5

64.0

72.9

1978

73.5

69.6

77.3

74.1

70.4

78.0

68.1

63.7

72.4

1977

73.3

69.5

77.2

74.0

70.2

77.9

67.7

63.4

72.0

1976

72.9

69.1

76.8

73.6

69.9

77.5

67.2

62.9

71.6

1975

72.6

68.8

76.6

73.4

69.5

77.3

66.8

62.4

71.3

CRS-26
All Races

Blacka

White

Yr.
Sex

Both

M

F

Both

M

F

Both

M

F

1974

72.0

68.2

75.9

72.8

69.0

76.7

66.0

61.7

70.3

1973

71.4

67.6

75.3

72.2

68.5

76.1

65.0

60.9

69.3

1972c

71.2

67.4

75.1

72.0

68.3

75.9

64.7

60.4

69.1

1971

71.1

67.4

75.0

72.0

68.3

75.8

64.6

60.5

68.9

1970

70.8

67.1

74.7

71.7

68.0

75.6

64.1

60.0

68.3

1969

70.5

66.8

74.4

71.4

67.7

75.3

64.5

60.6

68.6

1968

70.2

66.6

74.1

71.1

67.5

75.0

64.1

60.4

67.9

1967

70.5

67.0

74.3

71.4

67.8

75.2

64.9

61.4

68.5

1966

70.2

66.7

73.9

71.1

67.5

74.8

64.2

60.9

67.6

1965

70.2

66.8

73.8

71.1

67.6

74.8

64.3

61.2

67.6

1964

70.2

66.8

73.7

71.0

67.7

74.7

64.2

61.3

67.3

d

69.9

66.6

73.4

70.8

67.4

74.4

63.7

61.0

66.6

1962d

70.1

66.9

73.5

70.9

67.7

74.5

64.2

61.6

66.9

1961

70.2

67.1

73.6

71.0

67.8

74.6

64.5

62.0

67.1

1960

69.7

66.6

73.1

70.6

67.4

74.1

63.6

61.1

66.3

1959

69.9

66.8

73.2

70.7

67.5

74.2

63.9

61.3

66.5

1958

69.6

66.6

72.9

70.5

67.4

73.9

63.4

61.0

65.8

1957

69.5

66.4

72.7

70.3

67.2

73.7

63.0

60.7

65.5

1956

69.7

66.7

72.9

70.5

67.5

73.9

63.6

61.3

66.1

1955

69.6

66.7

72.8

70.5

67.4

73.7

63.7

61.4

66.1

1954

69.6

66.7

72.8

70.5

67.5

73.7

63.4

61.1

65.9

1953

68.8

66.0

72.0

69.7

66.8

73.0

62.0

59.7

64.5

1952

68.6

65.8

71.6

69.5

66.6

72.6

61.4

59.1

63.8

1951

68.4

65.6

71.4

69.3

66.5

72.4

61.2

59.2

63.4

1950

68.2

65.6

71.1

69.1

66.5

72.2

60.8

59.1

62.9

1949

68.0

65.2

70.7

68.8

66.2

71.9

60.6

58.9

62.7

1948

67.2

64.6

69.9

68.0

65.5

71.0

60.0

58.1

62.5

1947

66.8

64.4

69.7

67.6

65.2

70.5

59.7

57.9

61.9

1946

66.7

64.4

69.4

67.5

65.1

70.3

59.1

57.5

61.0

1945

65.9

63.6

67.9

66.8

64.4

69.5

57.7

56.1

59.6

1944

65.2

63.6

66.8

66.2

64.5

68.4

56.6

55.8

57.7

1943

63.3

62.4

64.4

64.2

63.2

65.7

55.6

55.4

56.1

1942

66.2

64.7

67.9

67.3

65.9

69.4

56.6

55.4

58.2

1941

64.8

63.1

66.8

66.2

64.4

68.5

53.8

52.5

55.3

1963

CRS-27
All Races

Blacka

White

Yr.
Sex

Both

M

F

Both

M

F

Both

M

F

1940

62.9

60.8

65.2

64.2

62.1

66.6

53.1

51.5

54.9

1939

63.7

62.1

65.4

64.9

63.3

66.6

54.5

53.2

56.0

1938

63.5

91.9

65.3

65.0

63.2

66.8

52.9

51.7

54.3

1937

60.0

58.0

62.4

61.4

59.3

63.8

50.3

48.3

52.5

1936

58.5

56.6

60.6

59.8

58.0

61.9

49.0

47.0

51.4

1935

61.7

59.9

63.9

62.9

61.0

65.0

53.1

51.3

55.2

1934

61.1

59.3

63.3

62.4

60.5

64.6

51.8

50.2

53.7

1933

63.3

61.7

65.1

64.3

62.7

66.3

54.7

53.5

56.0

1932

62.1

61.0

63.5

63.2

62.0

64.5

53.7

52.8

54.6

1931

61.1

59.4

63.1

62.6

60.8

64.7

50.4

49.5

51.5

1930

59.7

58.1

61.6

61.4

59.7

63.5

48.1

47.3

49.2

1929

57.1

55.8

58.7

58.6

57.2

60.3

46.7

45.7

47.8

Death Registration Statese
1928

56.8

55.6

58.3

58.4

57.0

60.0

46.3

45.6

47.0

1927

60.4

59.0

62.1

62.0

60.5

63.9

48.2

47.6

48.9

1926

56.7

55.5

58.0

58.2

57.0

59.6

44.6

43.7

45.6

1925

59.0

57.6

60.6

60.7

59.3

62.4

45.7

44.9

46.7

1924

59.7

58.1

61.5

61.4

59.8

63.4

46.6

45.5

47.8

1923

57.2

56.1

58.5

58.3

57.1

59.6

48.3

47.7

48.9

1922

59.6

58.4

61.0

60.4

59.1

61.9

52.4

51.8

53.0

1921

60.8

60.0

61.8

61.8

60.8

62.9

51.5

51.6

51.3

1920

54.1

53.6

54.6

54.9

54.4

55.6

45.3

45.5

45.2

1919

54.7

53.5

56.0

55.8

54.5

57.4

44.5

44.5

44.4

1918

39.1

36.6

42.2

39.8

37.1

43.2

31.1

29.9

32.5

1917

50.9

48.4

54.0

52.0

49.3

55.3

38.8

37.0

40.8

1916

51.7

49.6

54.3

52.5

50.2

55.2

41.3

39.6

43.1

1915

54.5

52.5

56.8

55.1

53.1

57.5

38.9

37.5

40.5

1914

54.2

52.0

56.8

54.9

52.7

57.5

38.9

37.1

40.8

1913

52.5

50.3

55.0

53.0

50.8

55.7

38.4

36.7

40.3

1912

53.5

51.5

55.9

53.9

51.9

56.2

37.9

35.9

40.0

1911

52.6

50.9

54.4

53.0

51.3

54.9

36.4

34.6

38.2

1910

50.0

49.4

51.8

50.3

48.6

52.0

35.6

33.8

37.5

1909

52.1

50.5

53.8

52.5

50.9

54.2

35.7

34.2

37.3

1908

51.1

49.5

52.8

51.5

49.9

53.3

34.9

33.8

36.0

CRS-28
All Races

Blacka

White

Yr.
Sex

Both

M

F

Both

M

F

Both

M

F

1907

47.6

45.6

49.9

48.1

46.0

50.4

32.5

31.1

34.0

1906

48.7

46.9

50.8

49.3

47.3

51.4

32.9

31.8

33.9

1905

48.7

47.3

50.2

49.1

47.6

50.6

31.3

29.6

33.1

1904

47.6

46.2

49.1

48.0

46.6

49.5

30.8

29.1

32.7

1903

50.5

49.1

52.0

50.9

49.5

52.5

33.1

31.7

34.6

1902

51.5

49.8

53.4

51.9

50.2

53.8

34.6

32.9

36.4

1901

49.1

47.6

50.6

49.4

48.0

51.0

33.7

32.2

35.3

1900

47.3

46.3

48.3

47.6

46.6

48.7

33.0

32.5

33.5

Source: CRS compilation from National Center for Health Statistics (NCHS), National Vital Statistics Report,
United States Life Tables, 2002, Nov. 10, 2004, Table 12 and NCHS, National Vital Statistics Report, Deaths:
Preliminary Data for 2003, Feb. 28, 2005.
Notes: Life expectancy at age 0 (at birth) measures the number of years that a newborn could expect to live, on
average, if mortality trends in the year of birth were to continue for the rest of the newborn’s life; For selected
years, life table values shown are estimates; and beginning 1970, excludes deaths of nonresidents of the UnitedStates.
a. Prior to 1970, data for black population are not available. Data shown for 1900-1969 are for nonwhite
population.
b. Alaska included in 1959 and Hawaii in 1960.
c. Deaths based on a 50% sample.
d. Figures by race in this year exclude data for residents of New Jersey.
e. Data for 1900-1928 are based on deaths in the “Death Registration States”; not the entire United States. The
federal civil registration system began in 1900 with the setting up of the Death Registration Area. States
were only admitted to the registration areas as qualification standards were met. Only 10 states and theDistrict of Columbia were in the original death registration area of 1900; the number of states included
increased with time.
f. Data for 2003 are preliminary.

CRS-29

Table A2. Life Expectancy at Various Ages in 2003,
by Sex, and Race(preliminary data, in years)
White Population

Difference(White-Black)

Black Population

Age

All

M

F

All

M

F

All

M

F

0

78.0

75.4

80.5

72.8

69.2

76.1

5.2

6.2

4.4

1

77.5

74.9

79.9

72.8

69.3

76.1

4.7

5.6

3.8

5

73.5

71.0

76.0

69.0

65.4

72.2

4.5

5.6

3.8

10

68.6

66.0

71.1

64.0

60.5

67.3

4.6

5.5

3.8

15

63.6

61.1

66.1

59.1

55.6

62.3

4.5

5.5

3.8

20

58.8

56.3

61.2

54.3

50.9

57.4

4.5

5.4

3.8

25

54.1

51.7

56.4

49.7

46.4

52.6

4.4

5.3

3.8

30

49.3

47.0

51.5

45.1

41.9

47.9

4.2

5.1

3.6

35

44.5

42.3

46.7

40.5

37.5

43.2

4.0

4.8

3.5

40

39.8

37.6

41.9

36.0

33.1

38.6

3.8

4.5

3.3

45

35.3

33.1

37.2

31.7

28.8

34.2

3.6

4.3

3.0

50

30.8

28.8

32.6

27.7

24.9

30.0

3.1

3.9

2.6

55

26.5

24.6

28.1

23.9

21.3

25.9

2.6

3.3

2.2

60

22.3

20.6

23.8

20.3

18.0

22.1

2.0

2.6

1.7

65

18.5

16.9

19.8

17.0

15.0

18.5

1.5

1.9

1.3

70

14.9

13.5

16.0

14.0

12.2

15.3

0.9

1.3

0.7

75

11.8

10.5

12.6

11.4

9.9

12.3

0.4

0.6

0.3

80

9.0

8.0

9.6

9.2

8.0

9.8

-0.2

0.0

-0.2

85

6.7

6.0

7.1

7.4

6.5

7.7

-0.7

-0.5

-0.6

90

4.9

4.4

5.1

5.7

5.2

5.9

-0.8

-0.8

-0.8

95

3.6

3.2

3.7

4.4

4.2

4.5

-0.8

-1.0

-0.8

100

2.6

2.4

2.7

3.4

3.4

3.4

-0.8

-1.0

-0.7

Source: CRS compilation from National Center for Health Statistics, National Vital Statistics Report, “Deaths:
Preliminary Data for 2003,” Feb. 28, 2005.
Notes: Life expectancy at age 0 (at birth) measures the number of years that a child born in 2003 could expect
to live, on average, if the mortality trends observed in 2003 were to continue for the rest of the newborn’s life.
Life expectancy at age 65 measures the number of additional years of life a person at age 65 will live, on average,
given that he had already attained age 65 in 2003.
Data are based on a continuous file of records from the States. Calculations of life expectancy employ
populations estimated as of July 1. Race categories are consistent with the 1977 Office of Management andBudget guidelines. Seven states California, Hawaii, Idaho, Maine, Montana, New York, and Wisconsin reported
multiple-race data in 2003. The multiple-race data for these States were bridged by NCHS to the single
categories of the 1977 OMB standards for comparability with other States. Data are subject to sampling or
random variation.