Life Expectancy in the United States






Prepared for Members and Committees of Congress



As a result of falling age-specific mortality, life expectancy rose dramatically in the United States
over the past century. Final data for 2003 (the most recent available) show that life expectancy at
birth for the total population has reached an all-time American high level, 77.5 years, up from th
49.2 years at the turn of the 20 century. Record-high life expectancies were found for white
females (80.5 years) and black females (76.1 years), as well as for white males (75.3 years) and
black 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 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 and the continuing longevity
differentials by sex and race. In addition, it considers whether life expectancy will continue to
increase 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).






Introduc tion ............................................................................................................................... 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
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
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
Appendix A. Glossary of Terms....................................................................................................21
Appendix B. Detailed Life Expectancy Tables..............................................................................23
Author Contact Information..........................................................................................................27





This report considers population longevity in the United States, as measured by life expectancy.1 2
Life expectancy is the expected number of years to be lived, on average, by a particular cohort, if 3
current mortality trends continue for the rest of that cohort’s life. 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 4
was 77.5 years. 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, 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 was 22.2 years in the United 5
States. 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 in
life 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-specific
death rates. In the United States, data on mortality are collected and compiled through the vital
statistics 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 for 6
calendar year 2003; preliminary estimates are often released by NCHS but are generally not
referred to in this report.
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 7
reached by an individual. According to the U.S. Census Bureau, International Data Base, the
highest 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 of
France, who died at age 122 years, 164 days, and, for a man, C. Mortensen (a Danish immigrant 8
to the U.S.), who died at age 115 years, 252 days. There is a lively debate among researchers

1 Research assistance provided by Angela Napili, Librarian, Knowledge Services Group of the Congressional Research
Service.
2 Persons born in particular year, see Appendix A, Glossary.
3 Life expectancy is a hypothetical measure that applies todays age-specific death rates to predict the future survival of
a cohort. It would technically be more accurate to follow the cohort 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 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.





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 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 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 social
and economic issues that are likely to be considered by Congress. For instance, one consequence
of 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 same time, there is the recognition that government programs, such as Social Security and
Medicare, 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?
As seen in Table 1 and Appendix B Table B-1, life expectancy at birth increased dramatically
over 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





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
Source: For data through 2002, the Congressional Research Service (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: 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 not
reported in this data 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 the
eradication and control of numerous infectious and parasitic diseases, especially among infants 9
and children. The new theory led to an entirely new approach to preventative medicine,
practiced both by departments of public health and by individuals. Interventions included boiling
bottles and milk, washing hands, protecting food from flies, isolating sick children, ventilating 10
rooms, and improving water supply and sewage disposal. 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 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, and rheumatic heart disease) and cerebrovascular diseases (stroke)—11
have fallen by approximately 60% and 70%, respectively, on an age-adjusted basis since 1950
(see Table 2), improvements that the CDC has characterized as “one of the most important public th12
health achievements of the 20 century.”

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 were
available. Also, the mortality experience of physicians and their families was not significantly different from that of the
general 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 and th
Wales During the 20 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., 1900-
1999,” MMWR Weekly, Aug. 6, 1999, vol. 48(30), pp. 649-656.





Table 2. Age-adjusted Death Rates for Various Causes of Death
(per 100,000 population)
Cause 1950 1980 2002
All causes 1,446.0 1,039.1 832.7
Diseases of heart 586.8 412.1 232.3
Malignant neoplasms 193.9 207.9 190.0
Cerebrovascular diseases 180.7 96.2 53.5
Chronic lower respiratory diseases 28.3 43.3
Influenza and pneumonia 48.1 31.4 22.0
Chronic liver disease and cirrhosis 11.3 15.1 9.3
Diabetes mellitus 23.1 18.1 25.3
Unintentional injuries (incl. motor accidents) 78.0 46.4 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 and
hypercholesterolemi a;
—greater numbers of specialists and health-care providers focusing on cardiovascular
diseases;
—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 and
controlled;
—a decrease in mean blood cholesterol levels; and
—changes in the American diet (reductions in the consumption of saturated fat and
cholesterol).

13 Ibid.





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 from
the factors already described:
• 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 to have financial resources or health insurance to
ensure access to medical care.
• Social policies. Some social policies, such as Medicare and Medicaid, 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 health for these groups. Other social policies, such as
Social Security, affect income, and may affect health and well-being through that
channel. 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 14
mid-1960s, especially through Medicaid.
Life expectancy in the United States, for both men and women, is significantly higher than the 15
global average but is only slightly higher than the average for more developed countries (see
Table 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 th
selected counties in Table 3. The United States was ranked 48 among 227 countries and
territories for both sexes.
Table 3. Life Expectancy at Birth (in Years) in Selected Countries: A Global
Comparison in 2006
Both Sexes Males Females
World 64.8 63.2 66.5
Less Developed Countries 63.4 62.0 64.9
More Developed Countries 76.8 73.2 80.5
Andorra 83.5 80.6 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: 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 beless 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.





Both Sexes Males Females
Macau S.A.R. 82.2 79.4 85.2
Singapore 81.7 79.1 84.5
Japan 81.2 78.0 84.7
Switzerland 80.5 77.7 83.5
Australia 80.5 77.6 83.5
Canada 80.2 76.9 83.7
Greece 79.2 76.7 81.9
United States 77.8 75.0 80.8
Cyprus 77.8 75.4 80.3
Denmark 77.8 75.5 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.
The 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 average 16
annual mortality decline for the total U.S. population aged 65 and older between 1900 and 2000.
He asserted that assuming future mortality improvement at nearly the same rate as for the last
century—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 as th
large—as experienced during the last 18 years of the 20 century. Goss further suggested that 17
“matching the accomplishments of the past century will not be easy. AIDS, SARS, and 18
antibiotic resistant microbes, along with 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 as a 19
whole.” 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 first
reported 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).





A benefit of the statistical methods that have emerged to extrapolate historical mortality trends to 20
the future is that they have worked well and are relatively simple and efficient. 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 for
sustained longevity improvements, and projects a relationship between future mortality decline 21
and future real growth in employment earnings. The UK extrapolates trends from 15 years of
past 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 22
improvement after the first 10 years.
Table 4. Projected Life Expectancies, SSA, in Selected Years
(in years)
At Birth At Age 65
Year Male Female Male 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 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 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 Institute 23
for Demographic Research, argues that the Social Security projections are too pessimistic. He
notes that SSA’s forecast is that female life expectancy in the United States will gradually rise 24
from 79.5 years today to 83.4 years in 2050. 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). See
also, (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 NAFTA
Countries,” 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, th
108 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 Laura B. Shrestha.





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 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 25
projected). Two of these studies showed that there has been a tendency for international life 26
expectancy to rise linearly by more than two years per decade over the past 40 years or the last 27

160 years, a more rapid pace than suggested by current models. Also, useful analyses of the 28


contributions of smoking behavior to mortality trends 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 29
the diseases and conditions that are responsible for premature death.
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 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 the same time. From 1900 to 1975,
the difference in life expectancy increased from 2.0 years to 7.8 years, with females continuing to 31
have the longevity advantage. 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, “Sex
Mortality 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%20-9-1-
05.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. 77-
104. (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.





life expectancy—which were also being recorded in other developed countries—are a relatively 32
recent phenomenon in demographic history. 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, which were largely the result of men’s early and widespread adoption of cigarette
smoking. In the mid- to late 1970s, the average gap in life expectancy approximated the average 33
gap seen in developed countries today—roughly seven years. 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 34
unusually high levels of current adult male mortality.
Figure 1. Life Expectancy at Birth, by Sex: 1900 to 2003.
90
80.1
80
7074.8
6048.3
SFemales
50ARMales
E
40IN YFemale Advantage46.3
Influenza
30Epidemic
of 1918
20
107.85.3
1.0
0
1 900 19 10 192 0 1 93 0 1 940 19 50 196 0 1 97 0 19 80 19 90 2 00 0
Source: For 1900-2002, CRS analysis based on data contained in 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: 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.
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.





among 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 to 36
the size of sex differentials in life expectancy in developed countries for the early 1980s.
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 37

19%, and diseases of the respiratory system for nearly 10%.


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 38
boys were born for every 100.0 girls in 2003. But, male mortality exceeds that of females in
every age group and for most major causes of death, beginning in infancy and continuing through
the oldest-old age groups. One researcher has suggested that the male advantage at birth is
moderated by higher male mortality to “ensure that the number of men and women will be about 39
the same at reproductive age.”
It has long been argued that hormones play a role in longevity. As described by Desjardins,40 the
female hormone estrogen helps to eliminate “bad” cholesterol (LDL) and thus may offer some 41
protection against heart disease. 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 42
reinforced by cultural influences. 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, “Some
trends 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 of
death 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 in
atherosclerosis 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.





Stindl,43 however, argues that these classic biological explanations do not withstand critical 44
analysis. 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 45
size dimorphism (SSD) 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 of
female cells, resulting in the exhaustion of the regeneration potential and the early onset of age-
associated diseases predominantly in males. The underlying mechanism is 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 46
function.
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 (such
as the hardships associated with childbirth) may have nullified American women’s biological th
advantage at the beginning of the 20 century but are no longer major factors in gender
differentials in life expectancy in the United States, though these explanations are still relevant in
a 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 industrialized
countries. 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 47
events (e.g. accidents, injuries, suicides, poisonings) and in deaths from cardiovascular disease.
The most cited behavioral contributor to higher male mortality rates in the United States—and the
subject of considerable research interest—has been the greater male exposure to cigarette
smoking. 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 48
have engaged in the habit; and smoking patterns differ between the sexes. 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 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
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 the
fact 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/mortality-
russia.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...)





women’s uptake of smoking lagged behind that of men.49 In the 1970s, when the sex differential 50
in mortality was increasing, cigarette smoking was implicated. Now, as the sex differential is
narrowing, a new body of research is evaluating the role of cigarette smoking in explaining the 51
trend. Pampel, 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 by
gender. 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 5253
decreasing for men. Preston and Wang 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 of
cohorts 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.

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 a
white 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.





Figure 2. Trends in Life Expectancy at Birth, By Race and Sex, 1900 to 2003
90
80
70
60
50ARS
40N YEWhite Females
I
30White Males
Black Females
20
Black Males
10
0
19 00 1910 19 20 1930 1 940 1950 1 960 197 0 198 0 1990 200 0
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. 54, no. 14,
Apr. 19, 2005.
Notes: Later year estimates are more reliable than those of the early 20th century.
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 consistent throughout the century. From the height of the
differential 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 th
also observed over the 20 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 of
roughly 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 mid-
1950s to mid-1960s. The gap in 1961 was narrower than that observed today—at that time, the
gap between white and black men was 5.8 years (as compared to 6.3 now). Factors that contribute
to the differential are discussed in later sections of this report.





Figure 3. Differences in Life Expectancy at Birth Between Whites and Blacks, by Sex,
1900-2003
18
16Females
14
Males
12
S
10AR
E
8IN Y
6
4
2
0
1 90 0 1 91 0 1 92 0 1 930 1 940 19 50 19 60 19 70 19 80 19 90 200 0
Source: 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.
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 was
observed 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, and
especially for black men in the United States? This has been a subject of research by medical and
social scientists for at least a century, and the issue stands at the heart of the current public health 55
agenda in the United States. One of the two primary goals of Healthy People 2010 is to
eliminate health disparities.

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





Mortality 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 56
differences between the races. Wong and colleagues, 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)
% of % of
Cause of death Disparity Cause of death Disparity
Cardiovascular disease 34.0 Infection 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 failure 0.1 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 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 (85
and 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.
As seen in Table 5, when considering the major categories of disease, deaths from cardiovascular
disease 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 preventable
causes 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.





(breast, colon, uterus or ovary, bladder or kidney, and leukemia or lymphoma; figures are in the
original source but are not shown in table). These results are consistent with findings from other 57
studies, 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 the exposure to these risk 5859
factors.” The results may also offer hope for the elimination of racial disparities in health.
Beyond describing gross health disparities, scientific inquiry has shifted to explaining the
underlying factors that account for these differences in health outcomes. Understanding these
underlying causes requires disentangling the complex web of factors connecting the nexus among 60
race, socioeconomic status, behavioral factors, and health. Some have argued that, if pertinent
differences between whites and blacks in their underlying social, demographic, familial, and
economic circumstances were eliminated, racial differences in mortality would be significantly 61,62
reduced.
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, these
factors may affect the age of onset of both morbidity and disability, the severity of symptoms, and 63
ultimately the age at, and cause of death.
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 and
treatment compliance. Moreover, the experience of racial discrimination may have adverse
psychological and physiological effects, in addition to limiting the quantity and quality of health
care 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 Life-
Expectancy 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 and
Ethnic Differences in the Health of Older Americans, National Research Council (Washington: The National
Academies Press, 1997) (hereafter: NRC, 1997).
64 Ibid.





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, 65
which was 62% of the median for non-Hispanic White households (about $48,000). Poverty
rates among African Americans are persistently higher than those of non-Hispanic whites. In 66

2003, 24.4% of blacks were poor, compared to 8.2% of non-Hispanic whites.


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 67
other conditions. In 2003, the proportion 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 68
aged 25 and older had attained a four-year college degree compared to 17% of blacks.
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 to
select healthy individuals, but it also enhances social integration and encourages healthful 69
behaviors. 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 marry
at 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 than 70
white divorcees. The degree of attachment to marriage among black Americans is similar to that
of white Americans as measured by attitudes toward marriage. One explanation offered by some
researchers for the lower proportion of time 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
of joblessness, incarceration, and mortality. Employed men are more likely than unemployed men 71
to marry.

65 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, P60-226, 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 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 Thomas Gabe.
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 and
Whites,” 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.





Prolific research over the past two decades has confirmed the link between certain diseases and
health outcomes and various health-damaging (such as smoking, alcohol abuse) and health-
promoting (exercise, low-fat diet) behaviors. And, some researchers have explored the extent to
which health-damaging and health-promoting behaviors explain black-white differences in health 72
status. Berkman and Mullen, for instance, found that, despite greater apparent concern on the
part 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 be
obese (especially women), but they are less 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
and diabetes, both of which have been reported to be twice as common among blacks than among 73
whites.
The United States is the only developed country in the world that does not have national health 74
coverage, and significant numbers of Americans, and especially African Americans, do not have
sufficient health care coverage. More specifically, 21.0% of blacks under age 65 and 12.9% of 75
whites of the same age lacked private health insurance in 2003.
Beyond health insurance, Chandra and Skinner76 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 from different hospitals and from different physicians than
non-Hispanic whites, in large part a reflection of the general spatial distribution of the United
States population with concentrations of minorities in certain hospital referral regions.
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 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. There

72 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 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).
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 Chris L. Peterson and April Grady.
76 A. Chandra and J.S. Skinner,Geography and Racial Health Disparities,” in NRC, 2004, pp. 604-642.





are 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 and
racial 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 or
other traits is not a useful way to summarize genetic variation when we know that there are at
least 15 million genetic polymorphisms in humans, of which an unknown number underlie 78
variation in (normal and) disease traits.
Research in this area is still in its infancy and tends to reflect two ways that genes may be 79
relevant to the study of health differentials. First, there are a small number of conditions with
single-gene disorders in populations that have descended from a relatively small number of 80
people and that remain endogamous (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.
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 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 prevalent
causes of death—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 81
that is replacing the earlier “young” age-sex structure with that of an older population. Hastened
by the retirement of the “Baby Boom” 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 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 that
it may be difficult to match the accomplishments of the past century, especially in light of
increasing obesity, declining levels of exercise, and the introduction of new scourges, such as 82
AIDS, SARS, antibiotic resistant microbes. Some demographers, on the other hand, feel that

77 B. Cohen, “Introduction,” in NRC, 2004, p. 9.
78 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.
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 Laura B. Shrestha.
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).





such projections are pessimistic, and argue, based on historical trends and evidence from other 83
developed countries, that American survival will be longer than that projected by SSA. 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 the
comparable 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 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 health insurance, the strain of physically demanding work, exposure to toxins, risky
behaviors (such as smoking, high saturated diet), adherence to preventative health measures (such
as 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, 84
in addition to limiting the quantity and quality of health care received.
Recent research, however, that shows that the leading specific diseases that are the main sources
of 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), 85
followed by HIV disease (11.2%), diabetes (8.5%), and homicide (8.5%) in a recent analysis.

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, th
108 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.






Age-Procedure used to compare risks of two or more populations at one point in time or one
adjustment. 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 A rate that relates a given demographic event at a specific age (or age group) to the
rate. 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 A process in which the proportion of adults and elderly increase in a population, while the
population). proportion of children and adolescents decrease. This process results in a rise in the median age
of the population.
At-risk The persons to whom an event can potentially occur. In the form of the population at the middle
population. 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 a particular 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 the basis of a terminating signal event (e.g.,
death).
Cohort life A method to calculate life expectancy using death rates not from a single year, but from the
expectancy. series of years in which the individual will actually reach each succeeding age if he or she survives.
Crude rate. A rate that relates a demographic event to the total population and makes 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 death certificate.
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 In the United States, the states and local governments complying with federal standards for the
Registration registration of deaths. It was established in 1900 and by 1933 encompassed all states.
Area.
Expectation of A statistical measure of the average amount of time (usually measured in years) remaining for a
life. person or group of persons before death, usually estimated using a life table.
Life An estimate of the average number of additional years a person could expect to live if the age-
expectancy. 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. See also Cohort life expectancy and Period life expectancy.
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 and age data from a single point
in time; a generational life table is based on the mortality of an actual birth cohort followed over
time (to its extinction).
Life table The fundamental elements of a life table include number surviving to a given age, the number of
functions. 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 a given birthday (including birth).
Longevity. Length of life; life span. “Average longevity” usually refers to life expectancy.





Mean age at The arithmetic mean age at death of the reported deaths in a given year. In the life table, the
death. mean age at death of life table deaths is equal to life expectancy at birth in the same life table.
Morbidity. The frequency of disease, illness, injuries, and disabilities in a population.
Mortality. A general term for the incidence of deaths in a population.
Period life A method to calculate life expectancy for a given year using the actual or expected death rates at
expectancy. 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 a
selected age only if it is assumed that will be no change in death rates after that year.
Period life A life table based on mortality data collected at a given point in time (frequently one year) for a
table. given population.
Person-years The total number of years (and fractions thereof) lived by a given population or population
lived. 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. The “inhabitants” of a given area at a given time.
Population The numerical outcome of a particular set of implicit and explicit assumptions regarding future
projection. 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 along
with its composition and distribution).
Potential life See years of potential life lost.
years lost.
Projection. See Population projection.
Race. 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 socially
constructed 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 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 be based on life tables or two censuses.
Years of Measure of the relative impact of various diseases and lethal forces on society, computed by
potential life estimating the years that people would have lived if they had not died prematurely from injury or
lost. disease. Sometimes referred to as potential life years lost.
Source: CRS compilation based on: (1) J.S. Siegel and D.A. Swanson, eds. The Methods and Materials of nd
Demography, 2 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 th
Reference Bureau’s Population Handbook, 4 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; (5) Social Security Administration, 2006 Annual Report of the
Trustees 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.






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





All Races White Blacka
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
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





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





All Races White Blacka
Yr.
Sex Both 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
Source: For historical data: CRS compilation from National Center for Health Statistics (NCHS), National Vital
Statistics Report, 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 United
States.
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 the
District of Columbia were in the original death registration area of 1900; the number of states included
increased with time.
Table B-2. Life Expectancy at Various Ages in 2003, by Sex and Race
(final data, in years)
Difference
White Population Black Population (White-Black)
Age All M F All M F 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





Difference
White Population Black Population (White-Black)
Age All M F All M F All M F
40 39.8 37.6 41.9 36.0 32.9 38.6 3.7 4.5 3.3
45 35.2 33.1 37.2 31.6 28.7 34.1 3.6 4.4 3.1
50 30.8 28.8 32.6 27.6 24.8 29.9 3.2 4.0 2.7
55 26.5 24.6 28.1 23.8 21.2 25.9 2.7 3.4 2.2
60 22.3 20.6 23.8 20.2 17.9 22.1 2.1 2.7 1.7
65 18.5 16.9 19.8 17.0 14.9 18.5 1.5 2.0 1.3
70 14.9 13.5 16.0 14.0 12.1 15.3 0.9 1.4 0.7
75 11.7 10.5 12.6 11.4 9.8 12.4 0.3 0.7 0.2
80 9.0 8.0 9.6 9.2 7.9 9.8 -0.2 0.1 -0.2
85 6.7 5.9 7.1 7.4 6.4 7.8 -0.7 -0.5 -0.7
90 4.9 4.3 5.1 5.7 5.0 6.0 -0.8 -0.7 -0.9
95 3.5 3.1 3.6 4.4 3.8 4.5 -0.9 -0.7 -0.9
100 2.5 2.2 2.5 3.4 3.0 3.4 -0.9 -0.8 -0.9
Source: 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 and
Budget 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.
Laura B. Shrestha
Specialist in Domestic Social Policy
lshrestha@crs.loc.gov, 7-7046