ȱ

ȱ¡¢ȱȱȱȱȱȱǯȱȱȱȱȱȱ¢ȱȱŗŜǰȱŘŖŖŜȱ

ȱȱȱŝȬśŝŖŖȱ
ǯǯȱřŘŝşŘȱ

ȱȱȱ
Prepared for Members and Committees of Congressȱȱ¡¢ȱȱȱȱȱ¢ȱAs a result of falling age-specific mortality, life expectancy rose dramatically in the United Statesover the past century. Final data for 2003 (the most recent available) show that life expectancy atbirth for the total population has reached an all-time American high level, 77.5 years, up from49.2 years at the turn of the 20th century. Record-high life expectancies were found for whitefemales (80.5 years) and black females (76.1 years), as well as for white males (75.3 years) andblack males (69.0 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 to a rapid aging of theAmerican 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 theunderlying factors that contributed to mortality reductions and the continuing longevity
differentials by sex and race. In addition, it considers whether life expectancy will continue toincrease in future years. Detailed statistics on life expectancy are provided. A brief comparison
with other countries is also provided.
While this report focuses on a description of the demographic context of life expectancy change
in the United States, these trends have implications for a wide range of social and economic
programs and issues that are likely to be considered by Congress.
This report will be updated upon release of final data for 2004 by the National Center for Health
Statistics (NCHS).

ȱȱȱȱ¡¢ȱȱȱȱȱȱȱ
Introduction............................................................................................................................... 1
Trends in the Level of Longevity Over the Past Century.......................................................... 2
A Quick Global Comparison..................................................................................................... 5
What Will Be the Future Course of American Longevity? ....................................................... 6
Differentials in Life Expectancy ............................................................................................... 8
Sex Differentials ................................................................................................................. 8
Race Differentials ............................................................................................................. 12
Conclusion .............................................................................................................................. 19ȱ
Figure 1. Life Expectancy at Birth, by Sex: 1900 to 2003. ............................................................. 9
Figure 2. Trends in Life Expectancy at Birth, By Race and Sex, 1900 to 2003............................ 13
Figure 3. Differences in Life Expectancy at Birth Between Whites and Blacks, by Sex,
1900-2003................................................................................................................................... 14ȱ
Table 1. U.S. Life Expectancy at Birth, by Sex, in Selected Years.................................................. 2
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 2006.......................................................................................................................................... 5
Table 4. Projected Life Expectancies, SSA, in Selected Years........................................................ 7
Table 5. Racial Disparity in Potential Life Years Lost .................................................................. 15
Table B-1. Life Expectancy at Birth, by Race and Sex: 1900-2003.............................................. 23
Table B-2. Life Expectancy at Various Ages in 2003, by Sex and Race ....................................... 26¡ȱ
Appendix A. Glossary of Terms .................................................................................................... 21
Appendix B. Detailed Life Expectancy Tables.............................................................................. 23ȱ
Author Contact Information .......................................................................................................... 27ȱȱȱȱ¡¢ȱȱȱȱȱȱȱThis report considers population longevity in the United States, as measured by life expectancy.1
Life expectancy is the expected number of years to be lived, on average, by a particular cohort,2 ifcurrent mortality trends continue for the rest of that cohort’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 final data, life expectancy at birth in 2003
was 77.5 years.4 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 at age 60, forinstance, 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 was 22.2 years in the UnitedStates.5 A person who reached age 60 in 2003 was expected to live an additional 22.2 years, on
average, and would die at age 82.2. While this report concentrates on trends and differentials inlife expectancy at birth, Appendix B Table B-2 provides estimates of life expectancy at selected
additional ages in 2003 (the most recent final data available).
Measures of life expectancy are published in official life tables, which are based on age-specificdeath rates. In the United States, data on mortality are collected and compiled through the vitalstatistics system by the Centers for Disease Control and Prevention (CDC)/National Center for
Health Statistics (NCHS). The most recently released final data on deaths and mortality are forcalendar year 2003;6 preliminary estimates are often released by NCHS but are generally notreferred to in this report.
The concept of life expectancy, which considers the average experience for a population, isdistinct from the concept of life span, which considers the upper limit of human life that could bereached by an individual. According to the U.S. Census Bureau, International Data Base,7 thehighest attained life expectancy to date for a national population was that of Andorra in 2006,
when life expectancy was 83.5 years for the total population (86.6 years for females; 80.6 years
for males). The oldest authenticated female life span thus far recorded was for J. Calment ofFrance, who died at age 122 years, 164 days, and, for a man, C. Mortensen (a Danish immigrantto the U.S.), who died at age 115 years, 252 days.8 There is a lively debate among researchers

1

Research assistance provided by (name redacted), Librarian, Knowledge Services Group of the Congressional ResearchService.
2
Persons born in particular year, see Appendix A, Glossary.
3Life expectancy is a hypothetical measure that applies today’s age-specific death rates to predict the future survival ofa cohort. It would technically be more accurate to follow the cohort through time and apply the actual age-specificdeath rates that the cohort experiences as it moves through its life course, but calculation of actual life expectancy
would then require more then 100 years (until the death of the last survivor in the cohort).
4
National Center for Health Statistics (NCHS), “Deaths: Final Data for 2003,” National Vital Statistics Report (NVSR),
vol. 54, no. 13, Apr. 19, 2006. (Hereafter cited as: NCHS, Deaths: Final Data for 2003).
5
National Center for Health Statistics, “United States Life Tables, 2003,” National Vital Statistics Report (NVSR), vol.
54, no. 14, Apr. 19, 2006.
6
NCHS, Deaths: Final Data for 2003.
7
At http://www.census.gov/ipc/www/idbnew.html, accessed Aug. 11, 2006.
8
Max Planck Institute for Demographic Research, International Database on Longevity, at
http://www.supercentenarians.org/, accessed Aug. 11, 2006.

ȱȱȱŗȱȱ¡¢ȱȱȱȱȱȱ

regarding whether the biological limits of life spans have been reached or whether future
increases are probable. Life spans are not considered further in this report.
This report documents the improvements in life expectancy that have occurred, analyzing boththe 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 toincrease in future years. While this report focuses on describing the demographic context of
longevity change in the United States, these trends have implications for a wide range of socialand economic issues that are likely to be considered by Congress. For instance, one consequenceof lengthening life expectancies is that the older population’s needs for care—assistance withdaily 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 same time, there is the recognition that government programs, such as Social Security andMedicare, will face financial pressures to meet the increasing needs. What program changes are
required to ensure the continued viability of such programs as the number of beneficiaries
increases? What will be the federal government’s role in an environment of competing demands
for limited resources?

ȱȱȱȱȱ¢ȱȱȱȱ¢ȱAs seen in Table 1 and Appendix B Table B-1, life expectancy at birth increased dramaticallyover the past century in the United States—from 49.2 years (the average for 1900-1902) to 77.5
years in 2003, the most recent year for which official data have been released by the Centers for
Disease Control (CDC)/National Center for Health Statistics (NCHS).
Table 1. U.S. Life Expectancy at Birth, by Sex, in Selected Years(in years)

Years

Total

Males

Females

1900-1902

49.2

47.9

50.7

1909-1911

51.5

49.9

53.2

1919-1921

56.4

55.5

57.4

1929-1931

59.2

57.7

60.9

1939-1941

63.6

61.6

65.9

1949-1951

68.1

65.5

71.0

1959-1961

69.9

66.8

73.2

1969-1971

70.8

67.0

74.6

1979-1981

73.9

70.1

77.6

ȱȱȱŘȱȱ¡¢ȱȱȱȱȱ

ȱ

Years

Total

Males

Females

1989-1991

75.4

71.8

78.8

2002

77.3

74.5

79.9

2003

77.5

74.8

80.1

For data through 2002, the Congressional Research Service (CRS) compilation from National Centerfor Health Statistics (NCHS), United States Life Tables, 2002, National Vital Statistics Reports, vol. 53, no. 6, Nov.
10, 2004. For 2003, NCHS, Deaths: Final Data for 2003, National Vital Statistics Reports, vol. 54, no. 13, Apr. 19,
2006.
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 (DRA). States were only admitted as
qualification standards were met. Only 10 states and the District of Columbia were in the original DRA of 1900.
Statistics prior to 1939-1941 are based on data from the DRA states (which increased in number over time).
Alaska and Hawaii are first included in 1959-1961 figures. Also note that data for years 1999-2001 are notreported in this data source.
Source:Gains in longevity were fastest in the first half of the 20th century. These advances were largely
attributed to “an enormous scientific breakthrough—the germ theory of disease” which led to theeradication and control of numerous infectious and parasitic diseases, especially among infants
and children.9 The new theory led to an entirely new approach to preventative medicine,
practiced both by departments of public health and by individuals. Interventions included boilingbottles and milk, washing hands, protecting food from flies, isolating sick children, ventilatingrooms, and improving water supply and sewage disposal.10 Beginning in the 1940s, the control of
infectious diseases was also aided by the increasing distribution and usage of antibiotics,
including penicillin and sulfa drugs.
Since mid-century, advances in life expectancy have largely been attributable to improvements inthe prevention and control of the chronic diseases of adulthood. In particular, death rates fromtwo of the three major causes of death in 1950—diseases of the heart (i.e., coronary heart disease,
hypertensive heart disease, and rheumatic heart disease) and cerebrovascular diseases (stroke)—have fallen by approximately 60% and 70%, respectively, on an age-adjusted basis11 since 1950
(see Table 2), improvements that the CDC has characterized as “one of the most important publichealth achievements of the 20th century.”12

9

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).
10
Preston and Haines rule out formal health care (doctors, hospitals, drugs, and therapies) as the primary catalyst for
longevity improvements during this period, as most of the decline had occurred before any effective therapies wereavailable. Also, the mortality experience of physicians and their families was not significantly different from that of thegeneral population. Evidence from other industrialized countries also supports this conclusion about early-century
mortality declines. See (1) T. McKeown , et al., 1975, “An Interpretation of the Decline of Mortality in England andWales During the 20th Century,” Popl Studies, vol. 29:391:422; (2) S.H. Preston, and E. Van de Walle, “Urban French
Mortality Decline,” Popl Studies, vol. 32(2), pp. 275-97, 1978.
11
CRS calculations from NCHS, Health, United States, 2005, With Chartbook on Trends in the Health of Americans,
2005, Table 29. Uses 2000 standard population.
12
CDC, “Achievements in Public Health, 1900-1999, Decline in Deaths from Heart Disease and Stroke, U.S., 19001999,” MMWR Weekly, Aug. 6, 1999, vol. 48(30), pp. 649-656.

ȱȱȱřȱȱ¡¢ȱȱȱȱȱȱ

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

Cause

All causes

Diseases of heart
Malignant neoplasms
Cerebrovascular diseases
Chronic lower respiratory diseases
Influenza and pneumonia
Chronic liver disease and cirrhosis
Diabetes mellitus
Unintentional injuries (incl. motor accidents)

1950

1980

2002

1,446.0

1,039.1

832.7

586.8
193.9
180.7
—
48.1
11.3
23.1
78.0

412.1
207.9
96.2
28.3
31.4
15.1
18.1
46.4

232.3
190.0
53.5
43.3
22.0
9.3
25.3
37.3

Source: CRS compilation from National Center for Health Statistics (NCHS), Health, United States, 2005 with
Chartbook on Trends in the Health of Americans, Table 29.

The CDC13 attributes the declines in diseases of the heart and cerebrovascular diseases 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 cardiovasculardiseases;—an increase in emergency medical services for heart attack and stroke; 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 andcontrolled;—a decrease in mean blood cholesterol levels; and—changes in the American diet (reductions in the consumption of saturated fat andcholesterol).

13

Ibid.

ȱȱȱŚȱȱ¡¢ȱȱȱȱȱȱ

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 discuss them in detail or to disentangle them fromthe factors already described:•

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

•

Social policies. Some social policies, such as Medicare and Medicaid, areoriented to health improvements. Both programs were designed to increase
access to health care for vulnerable populations, the elderly and the poor, with theultimate goal of improving health for these groups. Other social policies, such asSocial Security, affect income, and may affect health and well-being through thatchannel. Finally, some social policies may affect health by changing the accessthat people have to already-established resources. An example is the combinationof civil rights legislation and improved health programs for the poor during themid-1960s, especially through Medicaid.14ȱȱ ȱȱ
Life 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 more developed countries15 (seeTable 3). Life expectancy surpasses that of the United States in a large number of countries,
including but not limited to Japan, Andorra, Canada, Hong Kong, Macau S.A.R, Singapore,
Sweden, 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 andterritories for both sexes.

Table 3. Life Expectancy at Birth (in Years) in Selected Countries: A Global
Comparison in 2006
World
Less Developed Countries
More Developed Countries

AndorraBoth Sexes

Males

Females

64.8

63.2

66.5

63.4
76.8
83.5

62.0
73.2
80.6

64.9
80.5
86.6

14

D.M. Cutler and E. Meara, Changes in the Age Distribution of Mortality Over the 20th Century, NBER, Working
Paper No. W8556, October 2001.
15
This characterization by the Census Bureau divides 227 countries and territories into two groupings: “Moredeveloped” 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). See, also, the Central Intelligence Agency (CIA), The
World Factbook, at https://www.cia.gov/cia/publications/factbook/ rankorder/2102rank. html.

ȱȱȱśȱȱ¡¢ȱȱȱȱȱȱBoth Sexes

Males

FemalesMacau S.A.R.
SingaporeJapan
Switzerland
Australia
CanadaGreece

82.2
81.7
81.2
80.5
80.5
80.2
79.2

79.4
79.1
78.0
77.7
77.6
76.9
76.7

85.2
84.5
84.7
83.5
83.5
83.7
81.9

United States

77.8

75.0

80.8

CyprusDenmark

77.8
77.8

75.4
75.5

80.3
80.2

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 Aug. 10, 2006.

ȱȱȱȱȱȱȱȱ¢ǵȱThe Social Security Trustees report to Congress on the actuarial status of the Trust 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 averageannual mortality decline for the total U.S. population aged 65 and older between 1900 and 2000.16
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 a roughly equal
likelihood of doing better or worse. This rate of improvement is more optimistic—about twice aslarge—as experienced during the last 18 years of the 20th century. Goss further suggested that“matching the accomplishments of the past century will not be easy. AIDS, SARS,17 andantibiotic resistant microbes, along with increasing obesity18 and declining levels of exercise,remind us that mortality improvements will not be automatic. Gains from replacement organs andgenetic engineering will be expensive, and may be difficult to provide for the population as awhole.”19 SSA’s projections of period life expectancy are shown in Table 4.

16

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 Congress, first session, June 3, 2003,
S.Hrg. 108-192 (Washington: GPO, 2003).
17
SARS (Severe Acute Respiratory Syndrome), a viral respiratory illness caused by a coronavirus. SARS was firstreported in Asia in Feb. 2003. Over the next few months, the illness 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.
18
See, for instance, S.J. Olshanky and colleagues, “A Potential Decline in Life Expectancy in the United States in the
21st Century,” New England Journal of Medicine, 352:11, pp. 1138-1145. The researchers argue that, over the next few
decades, life expectancy for the average American could decline by as much as five years unless aggressive efforts are
made to slow rising rates of obesity.
19
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 Congress, first session, June 3, 2003,
S.Hrg. 108-192 (Washington: GPO, 2003).

ȱȱȱŜȱȱ¡¢ȱȱȱȱȱȱ

A benefit of the statistical methods that have emerged to extrapolate historical mortality trends tothe future is that they have worked well and are relatively simple and efficient.20 In addition to
being utilized by SSA, similar approaches are also used in Canada and in the United Kingdom(UK). Canada’s approach assumes that economic productivity is the overall driving factor forsustained longevity improvements, and projects a relationship between future mortality decline
and future real growth in employment earnings.21 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 ofimprovement after the first 10 years.22. Projected Life Expectancies, SSA, in Selected Years

Table 4(in years)

At Birth

At Age 65

Year

Male

FemaleMale

Female

2005

74.8

79.6

16.2

19.0

2025

77.0

81.2

17.5

20.0

2050

79.4

83.2

18.9

21.4

2075

81.3

84.9

20.2

22.7

Source: CRS compilation from the 2005 Annual Report of the Board of Trustees of Federal Old-Age andSurvivors 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 or she has already attained age 65. For example, a 65-year-old woman in the 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.
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 Institutefor Demographic Research, argues that the Social Security projections are too pessimistic.23 He
notes that SSA’s forecast is that female life expectancy in the United States will gradually risefrom 79.5 years today to 83.4 years in 2050.24 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

20

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. (Hereafter cited as Friedland, Life Expectancy in the Future, 1998). Seealso, (1) S.C. Goss and colleagues, “Historical and Projected Mortality for Mexico, Canada, and the United States,” and(2) M. Sze and colleagues, “Effect of Aging Population with Declining Mortality on Social Security of NAFTACountries,” both in North American Actuarial Journal, vol. 2, no. 4, October 1998.
21
B. Dussalt, cited in Friedland, Life Expectancy in the Future, 1998.
22
C. Daykin, cited in R.B. Friedland, Life Expectancy in the Future, 1998.
23
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 Congress, first session, June 3, 2003, S.Hrg. 108-192 (Washington: GPO, 2003).
24
Note that cited figures differ slightly from those in Table 4. Vaupel was referring to the 2003 Social Security
Trustees Report, Table 4 presents the most recent data from the 2005 Trustees Report. This section is also presented in
CRS Report RL32701, The Changing Demographic Profile of the United States, by (name redacted).

ȱȱȱŝȱȱȱ¡¢ȱȱȱȱȱsuggests that it is unrealistic for SSA to assume that the United States will be unable to match thelevel of life expectancy in half-a-century that is already attained in other countries today.
A number of articles suggested that current models may be too pessimistic in their assumptions
about mortality and survival probabilities (i.e., Americans may live longer than currently
projected).25 Two of these studies showed that there has been a tendency for international life
expectancy to rise linearly by more than two years per decade over the past 40 years26 or the last
160 years,27 a more rapid pace than suggested by current models. Also, useful analyses of thecontributions of smoking behavior to mortality trends28 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 for premature death.29

ȱȱȱ¡¢ȱ¡ȱȱ
Life expectancy worldwide is generally higher for females than for their male counterparts.30 The
United States is no exception; female life expectancy exceeded that of males in all years of thepast 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 the same time. From 1900 to 1975,
the difference in life expectancy increased from 2.0 years to 7.8 years, with females continuing tohave the longevity advantage.31 In the absence of war, such large differences between the sexes in
25
R. Lee, Report for the Roundtable Discussion of the Mortality Assumption for the Social Security Trustees, note
dated Sept. 11, 2002, http://www.ceda.berkeley.edu/papers/rlee/ TrusteesPresentation02.pdf, accessed Aug. 11, 2006.
(Hereafter cited as Lee, 2002).
26
K. White, “Longevity Advances in High Income Countries, 1955-96,” Population and Development Review, vol. 28,
no. 1, March 2002, pp. 59-76.
27
J. Oeppen, and J. Vaupel, “Broken Limits to Life Expectancy,” Science, vol. 296, May 10, 2002, pp. 1029-1030.
28
Also, see the section in this report on “Sex Differentials”. Sources: (1) S.H. Preston and H. Wang, 2005, “SexMortality Differentials in the United States: The Role of Cohort Smoking Patterns,” University of Pennsylvania,
Working Paper 2005-01, at http://rider.wharton.upenn.edu/~prc/PRC/WP/Preston-Wang%20BWP%201%20-9-105.pdf, accessed Aug. 11, 2006. (Hereafter cited as Preston and Wang, 2005); (2) F. Pampel, “Cigarette Use and the
Narrowing Sex Differential in Mortality,” Population and Development Review, vol. 28, no. 1, March 2002, pp. 77104. (Hereafter cited as Pampel, 2002); (3) R. Lee, 2002; and (4) J. Bongaarts, “A Decomposition of Life Expectancy
Levels and Trends”, paper presented at the annual meeting of the Population Association of American, Los Angeles,CA, 2006.
29
Examples of technological advances and promising areas of research are provided in the testimony 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.
30
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).
31
Exact years not shown in Figure 1.

ȱȱȱŞȱȱ¡¢ȱȱȱȱȱȱ

life expectancy—which were also being recorded in other developed countries—are a relatively
recent phenomenon in demographic history.32 For the United States, NCHS attributed theincreasing gap during these years to increases in male mortality due to ischemic heart disease andlung cancer, which were largely the result of men’s early and widespread adoption of cigarettesmoking. In the mid- to late 1970s, the average gap in life expectancy approximated the average
gap seen in developed countries today—roughly seven years.33 The gap has been recorded as
great as 13 years, as seen in parts of the former Soviet Union in recent years as a result of
unusually high levels of current adult male mortality.34
Figure 1. Life Expectancy at Birth, by Sex: 1900 to 2003.

90

80.1

80

74.8

70

IN YEARS60

48.3

Females

50
40

Males
46.3

30

Female Advantage
Influenza
Epidemicof 1918

20

7.8

10
0
1900

5.3

1.0
1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

For 1900-2002, CRS analysis based on data contained in NCHS, United States Life Tables, 2002,
vol. 53, no. 6, Nov. 10, 2004. For 2003, CRS analysis based on NCHS, Deaths: Final
Data for 2003, National Vital Statistics Report, vol. 54, no. 13, Apr. 19, 2006.
Notes: Later year estimates are more reliable than those of the early 20th century.
Source:National Vital Statistics Report,

Since 1979, the “female advantage” in life expectancy between the sexes in the United States has
narrowed from 7.8 to 5.3 years, reflecting proportionately greater increases in lung cancer
mortality for women than for men and proportionately larger decreases in heart disease mortality
32

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.
33
K. Kinsella and Y.J. Gist, Gender and Aging, International Brief: Mortality and Health, Census Bureau, IB/98-02,
October 1998.
34
Ibid.

ȱȱȱşȱȱȱ¡¢ȱȱȱȱȱamong men.35 The average girl born in 2003 in the United States could expect to live 80.1 years
compared to 74.8 years for a boy born in the same year.
A now dated, but still informative, study evaluated the contributions of various causes of death tothe size of sex differentials in life expectancy in developed countries for the early 1980s.36
Diseases of the circulatory system were found to account for nearly 40% of the mean sex
differential in life expectancy; neoplasms (cancer) for 18%, accidents, suicide, and violence for
19%, and diseases of the respiratory system for nearly 10%.37
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 the underlying disease and mortality
profiles for men and women. At birth, boys have a clear advantage. In the United States, 104.9
boys were born for every 100.0 girls in 2003.38 But, male mortality exceeds that of females inevery age group and for most major causes of death, beginning in infancy and continuing throughthe oldest-old 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.”39ȱȱIt has long been argued that hormones play a role in longevity. As described by Desjardins,40 thefemale hormone estrogen helps to eliminate “bad” cholesterol (LDL) and thus may offer some
protection against heart disease.41 In contrast, some say, testosterone, found in greater amounts inmales, may make men more likely to engage in violence and risk-taking behavior, especially if
reinforced by cultural influences.42 Women may also gain an additional biological advantage
because of their two X chromosomes. If a gene mutation occurs on one X, a woman’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.

35

E. Arias, United States life tables, 2002, NVSR, vol. 53, no. 6, Nov. 10, 2004, based on: (1) R.N. Anderson, “Sometrends and comparisons of United States life table data: 1900-1991,” 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.
36
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.
37
Note that these results are not surprising, as cardiovascular disease and neoplasms were the two leading causes ofdeath in the total population.
38
National Center for Health Statistics (NCHS), “Births, Final Data for 2003,” NVSR, vol. 54, no. 2, Sept. 8, 2005.
39
B. Desjardins, “Ask the Experts,” Scientific American, December 2004, vol. 291, issue 6, p. 118.
40
Ibid.
41
See W.R. Hazzard, “Biological Basis of the Sex Differential in Longevity,” Journal of the American Geriatrics
Society, vol. 34, 1986, p. 455, who argued that the sex differential in sex hormone levels gives rise to the sex
differential in lipoprotein metabolism which in time (given our lifestyle) contributes to the sex differential inatherosclerosis and this in turn to sex differentials in longevity.
42
I. Waldron, “Sex Differences in Human Mortality: the Role of Genetic Factors,” Social Sciences and Medicine, vol.
17, no. 6, pp. 321-333.

ȱȱȱ

ŗŖȱ

ȱ

ȱ¡¢ȱȱȱȱȱ

Stindl,43 however, argues that these classic biological explanations do not withstand criticalanalysis.44 He offered an alternative hypothesis that has not yet been subject to long-termscientific scrutiny. He asserts that a strong positive correlation has been reported between sexual
size dimorphism (SSD)45 and male-based 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 that offemale cells, resulting in the exhaustion of the regeneration potential and the early onset of ageassociated diseases predominantly in males. The underlying mechanism is the gradual erosion ofchromosome 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 stressand indices of poor health, including risk factors for cardiovascular disease and poorer immune
function.46

ȱȱȱȱ
Many researchers believe that behavioral and social factors also contribute significantly to the sex
differentials observed between men and women. Women’s social status and life conditions (suchas the hardships associated with childbirth) may have nullified American women’s biologicaladvantage at the beginning of the 20th century but are no longer major factors in genderdifferentials in life expectancy in the United States, though these explanations are still relevant ina number of other countries. Higher male mortality rates have been attributed to greater male
exposure to specific risk factors, such as alcohol consumption and occupational hazards. Life
expectancy in Russia, for instance, fell by 6.3 years for Russian men during the period 1990 to
1995—a level of decline that was unprecedented both in Russia and in other industrializedcountries. In investigating the cause of the sudden drop, a team of researchers from the London
School of Economics and the Russian Academy of Sciences observed that excessive alcohol
consumption contributed both directly and indirectly to the marked increases in deaths from fatal
events (e.g. accidents, injuries, suicides, poisonings) and in deaths from cardiovascular disease.47
The most cited behavioral contributor to higher male mortality rates in the United States—and thesubject of considerable research interest—has been the greater male exposure to cigarettesmoking. Smoking patterns are an obvious place to look for an explanation of sex mortality
differences because the health risks are high and long-lasting; large fractions of the population
have engaged in the habit; and smoking patterns differ between the sexes.48 More specifically,43
R. Stindl, “Tying it All Together: Telomeres, Sexual Size Dimorphism and the Gender Gap in Life Expectancy,”
Medical Hypotheses, 2004:62, pp. 151-154.
44
Stindl shows that estrogen levels in postmenopausal women are virtually identical to estrogen levels in males and canhardly explain the discrepancy. He notes that testosterone got its bad reputation from one outdated study on a nonrepresentative sample of men. And, since it’s unlikely that mutations in genes on the X chromosome are involved in all
age-related diseases and that mutated versions of these genes occur in all men, the model might be of academic value
only.
45
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 thefact that the two sexes have different shapes, sizes, etc. from each other.
46
E.S. Epel and colleagues, “Accelerated Telomere Shortening in Response to Life Stress,” PNAS, vol. 101, no. 49,
Dec. 7, 2004.
47
D. Leon, M. McKee, L. Chenet, Adult Mortality in Russia, at http://www.lshtm.ac.uk/ ecohost/projects/mortalityrussia.htm#alcconsump, accessed Aug. 11, 2006.
48
I. Waldron, 1986, “The Contribution of Smoking to Sex Differences in Mortality,” Public Health Reports 101:163(continued...)ȱȱȱ

ŗŗȱ

ȱ

ȱ¡¢ȱȱȱȱȱ

women’s uptake of smoking lagged behind that of men.49 In the 1970s, when the sex differential
in mortality was increasing, cigarette smoking was implicated.50 Now, as the sex differential isnarrowing, a new body of research is evaluating the role of cigarette smoking in explaining thetrend. Pampel,51 for instance, documented that the rate of decline in female mortality in the
United States has slowed since 1980 or so, while that of males has returned to its earlier trend of
relatively rapid improvement—thus resulting in a narrowing life expectancy differential bygender. He concludes that smoking behavior lies behind the changing pace of mortality decline
not only in the United States, but also in 20 other industrial nations. Extending Pampel’s analysis,
Lee showed that the rate of decline for deaths not associated with smoking was actually faster for
women (than men) while death rates associated with smoking actually increased for women while
decreasing for men.52 Preston and Wang53 demonstrate that changes in sex mortality differences in
the United States have been structured on a cohort rather than a period basis, and that the cohort
imprint is closely related to histories of cigarette smoking. Allowance for the smoking histories ofcohorts significantly affects the assessment of mortality trends: national mortality levels would
have declined more rapidly in the absence of smoking, and they are likely to decline more rapidly
in the future as smoking recedes.

ȱśŚȱ
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 B-1). At that time, the expected longevity of awhite newborn girl exceeded that 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).

(...continued)
173.
49
Pampel, 2002.
50
See, for instance, (1) S.H. Preston, 1970. “Older Male Mortality and Cigarette Smoking: A Demographic Analysis”,
Institute for International Studies, Univ. Of California, Berkeley and (2) R.D. Rutherford, 1975. “The Changing Sex
Differential in Mortality,” Westport, Conn.: Greenwood Press.
51
Pampel, 2002.
52
Lee, 2002.
53
Preston and Wang, 2005.
54
This section considers only the differentials between blacks and whites, as these are the main categories available in
the NCHS life table publications that this analysis is based on.

ȱȱȱŗŘȱȱ¡¢ȱȱȱȱȱȱ

Figure 2. Trends in Life Expectancy at Birth, By Race and Sex, 1900 to 2003

90
80
70

IN YEARS605040White Females

30

White Males
Black Females

20Black Males
10
0
1900

1910

1920

1930

1940

1950

1960

1970

1980

1990

2000

For 1900 to 2002, CRS compilation from National Center for Health Statistics (NCHS), National Vital, vol. 53, no. 6, Nov. 10, 2004. For 2003, NCHS, National Vital Statistics Reports, vol. 54, no. 14,
Apr. 19, 2005.
Notes: Later year estimates are more reliable than those of the early 20th century.
Source:Statistics Reports

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 whitecounterparts was dramatic and mostly consistent throughout the century. From the height of thedifferential in 1904—when white women survived, on average, 17.9 years longer than black
women—the gap fell to 4.4 years in 2003.
A significant reduction in the life expectancy gap between American white and black men was
also observed over the 20th century. From its height of 17.8 years in 1904, the differential had
fallen to 6.3 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 ofroughly 6.0 to 8.5 years. While the male gap has been falling over the past decade, this trend
obscures the fact that the differential had already been at or near this level for most of the mid1950s to mid-1960s. The gap in 1961 was narrower than that observed today—at that time, thegap between white and black men was 5.8 years (as compared to 6.3 now). Factors that contributeto the differential are discussed in later sections of this report.

ȱȱȱŗřȱȱ¡¢ȱȱȱȱȱȱ

Figure 3. Differences in 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

For 1900-2002, CRS computation based on, NCHS, United States Life Tables, vol. 53, no. 6, Nov 10,
2004. For 2003, NCHS, Deaths: Final Data for 2003, vol. 54, no. 13, Apr. 19, 2006.
Notes: Later year estimates are more reliable than those of the early 20th century.
Source:In summary, mortality rates in the United States have declined dramatically over the past century.
Black persons, however, still live, on average, 5.3 fewer years than their white counterparts. In
2003, the most recent year for which we have official data, the highest life expectancy wasobserved for white females, who will live, on average, 80.5 years. The values for black females
and white males are quite similar to each other—76.1 years and 75.3 years, with black females
having the slight advantage. Of the four race-sex groups considered, black males have the shortest
average longevity—69.0 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, andespecially for black men in the United States? This has been a subject of research by medical andsocial scientists for at least a century, and the issue stands at the heart of the current public healthagenda in the United States.55 One of the two primary goals of Healthy People 2010 is toeliminate health disparities.

55

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

ȱȱȱŗŚȱȱ¡¢ȱȱȱȱȱȱMortality from most, but not all, 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,56 for instance, recently calculated potential
years of life lost related to specific causes of deaths for blacks 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)% ofCause of death

Cardiovascular disease
Ischemic heart disease
Cerebrovascular stroke
Hypertension
Congestive heart failure
Other arteriosclerotic
Other CVD disease
CancerLung disease
Diabetes mellitus
Liver disease
Alcohol-related diseases
Renal disease
Rheumatologic diseases% ofDisparity

34.0
5.5
2.8
15.0
0.1
5.6
5.0
3.4
(5.8)
8.5
2.6
0.8
4.0
1.4

Cause of death

Infection
Tuberculosis
Pneumonia
Viral hepatitis
SepsisHIV
Other infections
All trauma
Motor vehicle accident
Suicide
Homicide
Other accidents
All other causes
Total

Disparity

21.1
0.6
5.2
0.1
3.4
11.2
0.6
10.7
2.5
(2.5)
8.5
2.2
19.8
100.0

CRS adaptation from M.D. Wong and colleagues, “Contribution of Major Diseases to Disparities inMortality,” 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 inparentheses show causes-of-death for which blacks fare better than whites; and these estimates are for persons
dying before the age of 75 years though the authors state that all results were similar when potential life-years
lost before the age of 85 years were examined. Note that trends and racial differentials at the oldest ages (85and older) differ as black mortality rates are lower than those of whites for both men and women in official
mortality data from NCHS. See Appendix B Table B-2.
Source:As seen in Table 5, when considering the major categories of disease, deaths from cardiovasculardisease contributed most to the racial disparity in mortality from any cause (34.0%), followed by
infection (21.1%), and trauma (10.7%).
When looking at specific diseases, the leading sources of the disparity were largely preventablecauses of premature death—hypertension (which contributed 15.0% to the disparity), followed by
HIV disease (11.2%), diabetes (8.5%), and homicide (8.5%). Note that blacks had a lower
mortality risk from respiratory diseases (lung disease), suicide, and certain types of cancer
56

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.

ȱȱȱ

ŗśȱ

ȱ

ȱ¡¢ȱȱȱȱȱ(breast, colon, uterus or ovary, bladder or kidney, and leukemia or lymphoma; figures are in theoriginal source but are not shown in table). These results are consistent with findings from otherstudies,57 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 tothe credibility of public-health interventions aimed at reducing the exposure to these risk
factors.”58 The results may also offer hope for the elimination of racial disparities in health.59
Beyond describing gross health disparities, scientific inquiry has shifted to explaining theunderlying factors that account for these differences in health outcomes. Understanding theseunderlying causes requires disentangling the complex web of factors connecting the nexus among
race, socioeconomic status, behavioral factors, and health.60 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 be significantly
reduced.61,62
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 health insurance, the strain of physically demanding work,and exposure to a broad range of 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 late life, thesefactors may affect the age of onset of both morbidity and disability, the severity of symptoms, andultimately the age at, and cause of death.63
In addition, Martin and Soldo64 note that there are differences between racial groups in norms
regarding not only lifestyle and self-care behaviors, but also in access to health care providers andtreatment compliance. Moreover, the experience of racial discrimination may have adverse
psychological and physiological effects, in addition to limiting the quantity and quality of healthcare received. Some of these factors that contribute to the racial gap in life expectancy will be
discussed briefly in the following paragraphs.

57

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.
58
P. Bach (Memorial Sloan-Kettering Cancer Center), cited in D. Lawrence, “Which Diseases Contribute to LifeExpectancy Differences Between Races?,” The Lancet, vol. 360, Health Module, Nov. 16, 2002, p. 1571.
59
Ibid, p. 1571.
60
J.P. Smith and R.S. Kington, “Race, Socioeconomic Status, and Health in Late Life,” in National Research Council,
Racial and Ethnic Differences in the Health of Older Americans, 1997.
61
Ibid.
62
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.
63
L.G. Martin and B.J. Soldo, “Introduction,” in R.A. Hummers, M.R. Benjamins, R.G. Rogers, eds., Racial andEthnic Differences in the Health of Older Americans, National Research Council (Washington: The National
Academies Press, 1997) (hereafter: NRC, 1997).
64
Ibid.

ȱȱȱ

ŗŜȱ

ȱ

ȱ¡¢ȱȱȱȱȱȱȱȱȱIn general, as income increases, mortality decreases, because high income provides access tohigh-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).65 Poverty
rates among African Americans are persistently higher than those of non-Hispanic whites. In
2003, 24.4% of blacks were poor, compared to 8.2% of non-Hispanic whites.66
Recent research also highlights the enduring effects of education. Increased education appears tolower the risks for some chronic diseases—most notably, coronary heart disease (which is theleading cause of death in the United States)—while retarding the pace of disease progression forother conditions.67 In 2003, the proportion of both blacks and non-Hispanic whites who had ahigh school diploma (of persons in the population aged 25 and over) reached record highs but atdifferent 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.68
Marriage is also a socioeconomic determinant that is related to health outcomes. Married people
consistently exhibit lower levels of mortality than those who are not married. Marriage acts toselect healthy individuals, but it also enhances social integration and encourages healthful
behaviors.69 Race differences in marital and cohabitational stability are substantial, and may be
increasing over time. About 91 percent of white women born in the 1950s are estimated to marryat some time in their 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 to remarry thanwhite divorcees.70 The degree of attachment to marriage among black Americans is similar to thatof white Americans as measured by attitudes toward marriage. One explanation offered by someresearchers for the lower proportion of time spent in marriage among black Americans is the ideaof a “marriage squeeze,” in which the “marriageable pool” of black men is low due to high rates
of joblessness, incarceration, and mortality. Employed men are more likely than unemployed men
to marry.71

65

C. DeNavas-Walt, B.D. Proctor, and R.J. Mills, Income, Poverty, and Health Insurance Coverage in the UnitedStates, 2003, U.S. Census Bureau, Current Population Reports, P60-226, 2004. Note that the distribution of householdincome is influenced by many factors, such as the number of earners and household size. If a comparison is madeinstead on per capita income, the median money income for whites is $24,442 compared to $15,583 for blacks.
66
CRS Report 95-1024, Trends in Poverty in the United States, by (name redacted).
67
L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.
68
N. Stoops, Educational Attainment in the United States, 2003, Population Characteristics, U.S. Census Bureau,
Current Population Reports, P20-550.
69
R.G. Rogers, “Living and Dying in the U.S.A.: Sociodemographic Determinants of Death Among Blacks andWhites,” Demography, vol. 29, no. 2, 1992, pp. 287-303.
70
M.D. Bramlett, and W.D. Mosher, “Cohabitation, Marriage, Divorce, and Remarriage in the United States,” NCHS,
Vital Health Stat 23(22), 2002.
71
Ibid.

ȱȱȱŗŝȱȱ¡¢ȱȱȱȱȱȱȱȱȱ
Prolific research over the past two decades has confirmed the link between certain diseases andhealth outcomes and various health-damaging (such as smoking, alcohol abuse) and healthpromoting (exercise, low-fat diet) behaviors. And, some researchers have explored the extent towhich health-damaging and health-promoting behaviors explain black-white differences in healthstatus. Berkman and Mullen,72 for instance, found that, despite greater apparent concern on thepart of blacks than whites about their health, blacks do not consistently adopt more beneficial
behaviors than whites. Older blacks engage in less physical activity and are more likely to beobese (especially women), but they are less likely to consume alcohol than whites. Racialdifferences 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
and diabetes, both of which have been reported to be twice as common among blacks than amongwhites.73

ȱȱ ȱȱThe United States is the only developed country in the world that does not have national healthcoverage,74 and significant numbers of Americans, and especially African Americans, do not havesufficient health care coverage. More specifically, 21.0% of blacks under age 65 and 12.9% of
whites of the same age lacked private health insurance in 2003.75
Beyond health insurance, Chandra and Skinner76 argue that there is differential access to healthservices in the United States, especially because of geographic variation in treatment and outcome
patterns. Minorities tend to seek care from different hospitals and from different physicians thannon-Hispanic whites, in large part a reflection of the general spatial distribution of the UnitedStates population with concentrations of minorities in certain hospital referral regions.

ȱȱ
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, suchas aplastic anemia. As recently noted by the National Research Council, however, “Probably no
aspect of the debate about the causes of racial differences in health is potentially more sensitive
than the discussion about the extent to which genetic factors are in any way responsible. There72

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 Health Behaviors: 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 ResearchCouncil, Panel on Race, Ethnicity, and Health in Later Life, Committee on Population, Division of Behavioral andSocial Sciences and Education (Washington: The National Academies Press, 2004), pp. 310-352 (hereafter: NRC,
2004).
73
L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.
74
B. Cohen, “Introduction,” in NRC, 2004, p. 16.
75
CRS Report 96-891, Health Insurance Coverage: Characteristics of the Insured and Uninsured Populations in 2007,
by (name redacted) and (name redacted).
76
A. Chandra and J.S. Skinner, “Geography and Racial Health Disparities,” in NRC, 2004, pp. 604-642.

ȱȱȱ

ŗŞȱ

ȱ

ȱ¡¢ȱȱȱȱȱare numerous historical examples of scientific mischief in the support of racism.”77 Those in favor
of using race assert that there is a useful degree of association between genetic differences andracial classifications, so that the use of race as a research variable is warranted. Opponents,
however, argue that bundling the population into four or five categories based on skin color orother traits is not a useful way to summarize genetic variation when we know that there are atleast 15 million genetic polymorphisms in humans, of which an unknown number underlie
variation in (normal and) disease traits.78
Research in this area is still in its infancy and tends to reflect two ways that genes may be
relevant to the study of health differentials.79 First, there are a small number of conditions withsingle-gene disorders in populations that have descended from a relatively small number ofpeople and that remain endogamous80 (an example is Tay-Sachs Disease among Ashkenazi Jews).
Second, genes may be relevant to the study of health differentials through environmental factors,
which may vary by racial or ethnic group, and which might interact with genotype to produce
different outcomes for different groups.

ȱOne 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 control of 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 prevalentcauses of death—cardiovascular diseases and cerebrovascular diseases.
A consequence of the improved survival, coupled with declining fertility rates, is that the UnitedStates 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.81 Hastenedby the retirement of the “Baby Boom” generation (the cohort born between 1946 and 1964), theinexorable demographic momentum will have important implications for a large number of
essential economic and social domains, including work, retirement, and pensions, wealth andincome security, and the health and well-being of the aging population.
Whether the life expectancy improvements will continue is the subject of intense debate. The
Social Security Administration (SSA) assumes that the rate of future mortality improvements will
be nearly the same as for the last century—a little more than 0.7% annually—while asserting thatit may be difficult to match the accomplishments of the past century, especially in light ofincreasing obesity, declining levels of exercise, and the introduction of new scourges, such as
AIDS, SARS, antibiotic resistant microbes.82 Some demographers, on the other hand, feel that77

B. Cohen, “Introduction,” in NRC, 2004, p. 9.
E.G. Burchard and colleagues, “The Importance of Race and Ethnic Background in Biomedical Research andClinical Practice,” New England Journal of Medicine, vol. 348, no. 12, pp. 1170-1175, 2003.
79
See R.S. Cooper, “Genetic Factors in Ethnic Differences in Health,” in NRC, 2004, pp. 269-309.
80
Marriage within a specific group as required by custom or law.
81
CRS Report RL32701, The Changing Demographic Profile of the United States, by (name redacted).
82
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 Congress, first session, June 3, 2003,
S.Hrg. 108-192 (Washington: GPO, 2003).
78ȱȱȱ

ŗşȱ

ȱ

ȱ¡¢ȱȱȱȱȱsuch projections are pessimistic, and argue, based on historical trends and evidence from otherdeveloped countries, that American survival will be longer than that projected by SSA.83 The
outcome of the debate has important implications for determining the number of future
beneficiaries and ultimately the financial soundness of the Social Security and the Medicare
programs.
This report also highlights the continuing differentials in life expectancy by race and sex in the
United States, with black males continuing to be the most disadvantaged group on this measure.
Life expectancy at birth in 2003 for black males measured 69.0 years, falling short of thecomparable figure for white males by 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 require disentangling thecomplex 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 employerprovided health insurance, the strain of physically demanding work, exposure to toxins, risky
behaviors (such as smoking, high saturated diet), adherence to preventative health measures (suchas maintaining a healthy weight, exercise), and access to and quality of health care. In addition,
the experience of racial discrimination may have adverse psychological and physiological effects,
in addition to limiting the quantity and quality of health care received.84
Recent research, however, that shows that the leading specific diseases that are the main sourcesof the racial disparity in life expectancy are largely preventable causes 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.85

83

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 Congress, first session, June 3, 2003, S.Hrg. 108-192 (Washington: GPO, 2003).
84
L.G. Martin and B.J. Soldo, “Introduction,” in NRC, 1997.
85
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.

ȱȱȱŘŖȱȱ¡¢ȱȱȱȱȱȱ¡ȱǯ
Ageadjustment.
Age-specificrate.
Aging (ofpopulation).
At-risk
population.

¢ȱȱȱ

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.
A rate that relates a given demographic event at a specific age (or age group) to thecorresponding at-risk population in the same age (or age group). For example, the age-specificdeath rate in a particular population for persons aged 40-44 = [(Deaths to persons aged 4044)/(Total population aged 40-44)] * 1000.
A process in which the proportion of adults and elderly increase in a population, while theproportion of children and adolescents decrease. This process results in a rise in the median ageof the population.
The persons to whom an event can potentially occur. In the form 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.
Cohort.

Cohort life
expectancy.
Crude rate.

Death.

Death rate.

Death

Registration
Area.
Expectation of
life.
Life
expectancy.

Life span.

Life table.

Life tablefunctions.

Longevity.

Members of a population born in a given period (e.g., year 1900, time period 1946-1964, 2002).
A group of people who experience the same demographic event during a particular period oftime 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 the basis of a terminating signal event (e.g.,death).
A method to calculate life expectancy using death rates not from a single year, but from theseries of years in which the individual will actually reach each succeeding age if he or she survives.
A rate that relates a demographic event to the total population and makes no distinction
concerning different exposure levels to the event.
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 death certificate.
The number of deaths per 1,000 persons in the population in a given year. Also referred to as thecrude death rate. See also age-specific rate.
In the United States, the states and local governments complying with federal standards for theregistration of deaths. It was established in 1900 and by 1933 encompassed all states.
A statistical measure of the average amount of time (usually measured in years) remaining for a
person or group of persons before death, usually estimated using a life table.
An estimate of the average number of additional years a person could expect to live if the agespecific death rates for a given year prevailed for the rest of that person’s life. Also refers to theaverage number of years of life remaining to a group of persons who reached a given age, ascalculated from a life table. Most commonly refers to life expectancy at birth; can also be
calculated for other ages. See also Cohort life expectancy and Period life expectancy.
The maximum age that human beings could attain under optimum conditions. The extreme upper
limits of human life.
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 and age data from a single point
in time; a generational life table is based on the mortality of an actual birth cohort followed overtime (to its extinction).
The fundamental elements of a life table include number surviving to a given age, the number ofdeaths to those surviving to a given birthday before they reach a subsequent birthday, theprobability 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 a given birthday (including birth).
Length of life; life span. “Average longevity” usually refers to life expectancy.

ȱȱȱŘŗȱȱ¡¢ȱȱȱȱȱȱMean age atdeath.
Morbidity.
Mortality.
Period life
expectancy.

Period life
table.
Person-years
lived.

The arithmetic mean age at death of the reported deaths in a given year. In the life table, themean age at death of life table deaths is equal to life expectancy at birth in the same life table.
The frequency of disease, illness, injuries, and disabilities in a population.
A general term for the incidence of deaths in a population.
A method to calculate life expectancy for a given year using the actual or expected death rates at
each age for that year. It is a useful summary statistic for illustrating the overall level of the death
rates experienced in a single year. It is closely related to the age-sex-adjusted death rate. The
period life expectancy for a particular year may be viewed as the expected remaining life at aselected age only if it is assumed that will be no change in death rates after that year.
A life table based on mortality data collected at a given point in time (frequently one year) for agiven population.
The total number of years (and fractions thereof) lived by a given population or population
segment during a given period of time. It is approximated 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.
Population
projection.

Potential life

The “inhabitants” of a given area at a given time.
The numerical outcome of a particular set of implicit and explicit assumptions regarding future
values of the components of population change for a given area in combination with an algorithm.
Strictly speaking, it is a conditional statement about the size of a future population (often alongwith its composition and distribution).
See years of potential life lost.

years lost.
Projection.
Race.

Sex.
Survival.
Survival rate.

Years ofpotential life
lost.

See Population projection.

In theory, classification of the members of a population in terms of biological ancestry. In
demographic practice, classification of the members of a population in terms of sociallyconstructed definitions of membership in categories in which skin color or other characteristics,
including national ethnic affiliations, may be the basis of assignment by census or survey
enumerators or by self-enumeration. In the United States decennial census, persons are selfidentified by race.
Classification of the population into the categories of male and female.
Primarily a condition where an individual or group remains alive after a specified interval.
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 be based on life tables or two censuses.
Measure of the relative impact of various diseases and lethal forces on society, computed byestimating the years that people would have lived if they had not died prematurely from injury or
disease. Sometimes referred to as potential life years lost.

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; (3) A. Haupt and T.T. Kane. Population
Source:Reference Bureau’s Population Handbook, 4th International Edition, Wash., DC, Population Reference Bureau, 1998;

Health, United States, 2004, With Chartbook on Trends in the Health ofAmericans, Hyattsville, MD, 2004, Appendix 2; (5) Social Security Administration, 2006 Annual Report of theTrustees of the Federal Old-Age and Survivors Insurance and Disability Trust Funds, May 1, 2006, at
http://www.ssa.gov/ OACT/TR/TR06/tr06.pdf, table V, A3.
(4) National Center for Health Statistics,ȱȱȱŘŘȱȱ¡¢ȱȱȱȱȱȱ¡ȱǯ ȱȱ¡¢ȱȱ
Table B-1. Life Expectancy at Birth, by Race and Sex: 1900-2003(in years)

All Races

White

Blacka

Yr.

Sex

Both

M

F

Both

M

F

Both

M

F

United Statesb
2003

77.5

74.8

80.1

78.0

75.3

80.5

72.7

69.0

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

ȱȱȱŘřȱȱ¡¢ȱȱȱȱȱȱ

All Races
Yr.
Sex

Both

White

M

F

Both

Blacka

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

1963d

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

1940

62.9

60.8

65.2

64.2

62.1

66.6

53.1

51.5

54.9

ȱȱȱŘŚȱȱ¡¢ȱȱȱȱȱȱ

All Races

White

Blacka

Yr.

Sex

Both

M

F

Both

M

F

Both

M

F

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

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

ȱȱȱŘśȱȱ¡¢ȱȱȱȱȱȱ

All Races

White

Blacka

Yr.

Both

Sex

M

F

Both

M

F

Both

M

F

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

For historical data: CRS compilation from National Center for Health Statistics (NCHS), National Vital, United States Life Tables, 2002, Nov. 10, 2004, Table 12. For most recent year: NCHS, National
Vital Statistics Report, Deaths: Final Data for 2003, Apr. 19, 2006.
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.

Source:Statistics Report

Table B-2. Life Expectancy at Various Ages in 2003, by Sex and Race(final data, in years)

Age

White Population
All
M
F

Black Population
All
M
F

Difference(White-Black)
All
M
F

0

78.0

75.3

80.5

72.7

69.0

76.1

5.3

6.3

4.4

1

77.4

74.8

79.9

72.7

69.1

76.0

4.7

5.7

3.9

5

73.5

70.9

76.0

68.9

65.3

72.2

4.6

5.6

3.8

10

68.5

66.0

71.0

63.9

60.3

67.2

4.6

5.7

3.8

15

63.6

61.0

66.1

59.0

55.4

62.3

4.6

5.6

3.8

20

58.8

56.3

61.2

54.2

50.7

57.4

4.6

5.6

3.8

25

54.1

51.6

56.3

49.6

46.3

52.6

4.5

5.3

3.7

30

49.3

46.9

51.5

45.0

41.8

47.8

4.3

5.1

3.7

35

44.5

42.2

46.6

40.4

37.3

43.1

4.1

4.9

3.5

ȱȱȱŘŜȱȱ¡¢ȱȱȱȱȱ

ȱ

Age
40
45
50
55
60
65
70
75
80
85
90
95
100

White Population
All
M
F
39.8
35.2
30.8
26.5
22.3
18.5
14.9
11.7
9.0
6.7
4.9
3.5
2.5

37.6
33.1
28.8
24.6
20.6
16.9
13.5
10.5
8.0
5.9
4.3
3.1
2.2

41.9
37.2
32.6
28.1
23.8
19.8
16.0
12.6
9.6
7.1
5.1
3.6
2.5

Black Population
All
M
F

Difference(White-Black)
All
M
F

36.0
31.6
27.6
23.8
20.2
17.0
14.0
11.4
9.2
7.4
5.7
4.4
3.4

3.7
3.6
3.2
2.7
2.1
1.5
0.9
0.3
-0.2
-0.7
-0.8
-0.9
-0.9

32.9
28.7
24.8
21.2
17.9
14.9
12.1
9.8
7.9
6.4
5.0
3.8
3.0

38.6
34.1
29.9
25.9
22.1
18.5
15.3
12.4
9.8
7.8
6.0
4.5
3.4

4.5
4.4
4.0
3.4
2.7
2.0
1.4
0.7
0.1
-0.5
-0.7
-0.7
-0.8

3.3
3.1
2.7
2.2
1.7
1.3
0.7
0.2
-0.2
-0.7
-0.9
-0.9
-0.9

CRS compilation from National Center for Health Statistics, National Vital Statistics Report, “Deaths:
Final Data for 2003,” vol. 54, no. 13, Apr. 19, 2006.
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.

Source:ȱȱ ȱ(name redacted)
Specialist in Domestic Social Policy[redacted]@crs.loc.gov, 7-....

ȱȱȱŘŝȱ

EveryCRSReport.com
The Congressional Research Service (CRS) is a federal legislative branch agency, housed inside the
Library of Congress, charged with providing the United States Congress non-partisan advice on
issues that may come before Congress.
EveryCRSReport.com republishes CRS reports that are available to all Congressional staff. The
reports are not classified, and Members of Congress routinely make individual reports available tothe public.
Prior to our republication, we redacted names, phone numbers and email addresses of analysts
who produced the reports. We also added this page to the report. We have not intentionally madeany other changes to any report published on EveryCRSReport.com.
CRS reports, as a work of the United States government, are not subject to copyright protection in
the United States. Any CRS report may be reproduced and distributed in its entirety without
permission from CRS. However, as a CRS report may include copyrighted images or material from athird party, you may need to obtain permission of the copyright holder if you wish to copy orotherwise use copyrighted material.
Information in a CRS report should not be relied upon for purposes other than public
understanding of information that has been provided by CRS to members of Congress inconnection with CRS' institutional role.
EveryCRSReport.com is not a government website and is not affiliated with CRS. We do not claim
copyright on any CRS report we have republished.