For other versions of this document, see http://wikileaks.org/wiki/CRS-RL32792 ------------------------------------------------------------------------------ ¡¢ ¢ 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 49.2 years at the turn of the 20th 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). ¢¡ 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 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 Life expectancy is the expected number of years to be lived, on average, by a particular cohort,2 if current mortality trends continue for the rest of 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, 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 States.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 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 calendar year 2003;6 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 reached by an individual. According to the U.S. Census Bureau, International Data Base,7 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 to the U.S.), who died at age 115 years, 252 days.8 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 today's 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). srae detceleS ni ,xeS yb ,ht riB ta ycnatcepxE efiL .S.U .1 elba Y T )sraey ni( sraeY latoT selaM selameF 2091-0091 2.94 9.74 7.05 1191-9091 5.15 9.94 2.35 1291-9191 4.65 5.55 4.75 1391-9291 2.95 7.75 9.06 1491-9391 6.36 6.16 9.56 1591-9491 1.86 5.56 0.17 1691-9591 9.96 8.66 2.37 1791-9691 8.07 0.76 6.47 1891-9791 9.37 1.07 6.77 ¢¡ sraeY latoT selaM selameF 1991-9891 4.57 8.17 8.87 2002 3.77 5.47 9.97 3002 5.77 8.47 1.08 retneC lanoitaN morf noitalipmoc )SRC( ecivreS hcraeseR lanoissergnoC eht ,2002 hguorht atad roF :ecruoS .voN ,6 .on ,35 .lov ,stropeR scitsitatS latiV lanoitaN ,2002 ,selbaT efiL setatS detinU ,)SHCN( scitsitatS htlaeH rof ,91 .rpA ,31 .on ,45 .lov ,stropeR scitsitatS latiV lanoitaN ,3002 rof ataD laniF :shtaeD ,SHCN ,3002 roF .4002 ,01 .6002 noitartsiger livic laredef ehT .yrutnec ht02 ylrae eht fo esoht naht elbailer erom era setamitse raey retaL :setoN sa dettimda ylno erew setatS .)ARD( aerA noitartsigeR htaeD eht fo pu gnittes eht htiw 0091 ni nageb metsys .0091 fo ARD lanigiro eht ni erew aibmuloC fo tcirtsiD eht dna setats 01 ylnO .tem erew sdradnats noitacifilauq .)emit revo rebmun ni desaercni hcihw( setats ARD eht morf atad no desab era 1491-9391 ot roirp scitsitatS ton era 1002-9991 sraey rof atad taht eton oslA .serugif 1691-9591 ni dedulcni tsrif era iiawaH dna aksalA .ecruos atad siht ni detroper 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 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 boiling bottles and milk, washing hands, protecting food from flies, isolating sick children, ventilating rooms, 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 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)-- 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 public health 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 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 Wales 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., 1900- 1999," MMWR Weekly, Aug. 6, 1999, vol. 48(30), pp. 649-656. ¢¡ -egA .2 elbaT htaeD fo sesuaC suoiraV rof setaR htaeD detsujda )noitalupop 000,001 rep( esuaC 0591 0891 2002 sesuac llA 0.644,1 1.930,1 7.238 traeh fo sesaesiD 8.685 1.214 3.232 smsalpoen tnangilaM 9.391 9.702 0.091 sesaesid ralucsavorbereC 7.081 2.69 5.35 sesaesid yrotaripser rewol cinorhC -- 3.82 3.34 ainomuenp dna azneulfnI 1.84 4.13 0.22 sisohrric dna esaesid revil cinorhC 3.11 1.51 3.9 sutillem setebaiD 1.32 1.81 3.52 )stnedicca rotom .lcni( seirujni lanoitnetninU 0.87 4.64 3.73 htiw 5002 ,setatS detinU ,htlaeH ,)SHCN( scitsitatS htlaeH rof retneC lanoitaN morf noitalipmoc SRC :ecruoS .92 elbaT ,snaciremA fo htlaeH eht ni sdnerT no koobtrahC 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 hypercholesterolemia; --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 mid-1960s, especially through Medicaid.14 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 (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 selected counties in Table 3. The United States was ranked 48th among 227 countries and territories for both sexes. labolG A :seirtnuoC detceleS ni )sraeY ni( htriB ta ycnatcepxE efiL .3 elbaT 6002 ni nosirapmoC sexeS htoB selaM selameF dlroW 8.46 2.36 5.66 seirtnuoC depoleveD sseL 4.36 0.26 9.46 seirtnuoC depoleveD eroM 8.67 2.37 5.08 arrodnA 5.38 6.08 6.68 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 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. ¢¡ sexeS htoB selaM selameF .R.A.S uacaM 2.28 4.97 2.58 eropagniS 7.18 1.97 5.48 napaJ 2.18 0.87 7.48 dnalreztiwS 5.08 7.77 5.38 ailartsuA 5.08 6.77 5.38 adanaC 2.08 9.67 7.38 eceerG 2.97 7.67 9.18 setatS detinU 8.77 0.57 8.08 surpyC 8.77 4.57 3.08 kramneD 8.77 5.57 2.08 ta elbaliava ,esaB ataD lanoitanretnI s'uaeruB susneC .S.U eht morf atad no desab noitalipmoc SRC :ecruoS .6002 ,01 .guA dessecca ,lmth.wenbdi/www/cpi/vog.susnec.www//:ptth ¢ 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 annual 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 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 large--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 and antibiotic resistant microbes, along with increasing obesity18 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 whole."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 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 the 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 for sustained 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 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 improvement after the first 10 years.22 4 elbaT sraeY detceleS ni ,ASS ,seicnatcepxE efiL detcejorP . )sraey ni( htriB tA 56 egA tA raeY elaM elameF elaM elameF 5002 8.47 6.97 2.61 0.91 5202 0.77 2.18 5.71 0.02 0502 4.97 2.38 9.81 4.12 5702 3.18 9.48 2.02 7.22 dna egA-dlO laredeF fo seetsurT fo draoB eht fo tropeR launnA 5002 eht morf noitalipmoc SRC :ecruoS .3A ,V elbaT ,sdnuF tsurT ecnarusnI ytilibasiD dna ecnarusnI srovivruS ,evil lliw nosrep a taht sraey lanoitidda fo rebmun egareva eht ,56 ega ta ycnatcepxe efil fo noitaterpretnI :setoN ,evil lliw 5002 raey eht ni namow dlo-raey-56 a ,elpmaxe roF .56 ega deniatta ydaerla sah ehs ro eh taht gnimussa egnar-etaidemretni s'ASS ot srefer elbaT .)0.91 + 0.56( sraey 0.48 ega ot--sraey 0.91 lanoitidda na ,egareva no .seicnatcepxe efil doirep Future mortality and survival are, however, difficult to predict and specialists disagree on not only the level but also the direction of future trends. James Vaupel, director of the Max Planck Institute for Demographic Research, argues that the Social Security projections are too pessimistic.23 He notes that SSA's forecast is that female life expectancy in the United States will gradually rise from 79.5 years today to 83.4 years in 2050.24 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). 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, 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 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 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 the contributions 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 ¡¢ ¡ 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 have 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, "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 recent phenomenon in demographic history.32 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 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 .3002 ot 0091 :xeS yb ,ht riB ta ycnatcepxE efiL .1 erugiF 90 80.1 80 70 74.8 60 48.3 Females IN YEARS 50 Males 40 46.3 Female Advantage Influenza 30 Epidemic of 1918 20 7.8 5.3 10 1.0 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 ,2002 ,selbaT efiL setatS detinU ,SHCN ni deniatnoc atad no desab sisylana SRC ,2002-0091 roF :ecruoS laniF :shtaeD ,SHCN no desab sisylana SRC ,3002 roF .4002 ,01 .voN ,6 .on ,35 .lov ,tropeR scitsitatS latiV lanoitaN .6002 ,91 .rpA ,31 .on ,45 .lov ,tropeR scitsitatS latiV lanoitaN ,3002 rof ataD .yrutnec ht02 ylrae eht fo esoht naht elbailer erom era setamitse raey retaL :setoN 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 the 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 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 the same at reproductive age."39 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 protection against heart disease.41 In contrast, some say, testosterone, found in greater amounts in males, may make men more likely to engage in violence and risk-taking behavior, especially if reinforced by cultural influences.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, "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 analysis.44 He offered an alternative hypothesis that has not yet been subject to long-term scientific scrutiny. He asserts that a strong positive correlation has been reported between sexual size dimorphism (SSD)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 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 function.46 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 advantage at the beginning of the 20th 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 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 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 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 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 in mortality was increasing, cigarette smoking was implicated.50 Now, as the sex differential is narrowing, a new body of research is evaluating the role of cigarette smoking in explaining the trend. 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 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 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 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. ¢¡ 3002 ot 0091 ,xeS dna ecaR yB ,ht riB ta ycnatcepxE efiL ni sdner .2 erugiF T 90 80 70 60 IN YEARS 50 40 White Females 30 White Males Black Females 20 Black Males 10 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 ,)SHCN( scitsitatS htlaeH rof retneC lanoitaN morf noitalipmoc SRC ,2002 ot 0091 roF :ecruoS latiV lanoitaN ,41 .on ,45 .lov ,stropeR scitsitatS latiV lanoitaN ,SHCN ,3002 roF .4002 ,01 .voN ,6 .on ,35 .lov ,stropeR scitsitatS .5002 ,91 .rpA .yrutnec ht02 ylrae eht fo esoht naht elbailer erom era setamitse raey retaL :setoN 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 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 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. ¢¡ ,xeS yb ,skcalB dna setihW neewteB ht riB ta ycnatcepxE efiL ni secnereffiD .3 erugiF 3002-0091 18 16 Females 14 Males 12 IN YEARS 10 8 6 4 2 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 ,01 voN ,6 .on ,35 .lov ,selbaT efiL setatS detinU ,SHCN ,no desab noitatupmoc SRC ,2002-0091 roF :ecruoS .6002 ,91 .rpA ,31 .on ,45 .lov ,3002 rof ataD laniF :shtaeD ,SHCN ,3002 roF .4002 .yrutnec ht02 ylrae eht fo esoht naht elbailer erom era setamitse raey retaL :setoN 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 agenda in the United States.55 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. Medicine, vol. 347, no. 20, Nov. 14, 2002. M.D. Wong and colleagues, "Contribution of Major Diseases to Disparities in Mortality," New England Journal of 56 mortality risk from respiratory diseases (lung disease), suicide, and certain types of cancer HIV disease (11.2%), diabetes (8.5%), and homicide (8.5%). Note that blacks had a lower causes of premature death--hypertension (which contributed 15.0% to the disparity), followed by When looking at specific diseases, the leading sources of the disparity were largely preventable infection (21.1%), and trauma (10.7%). disease contributed most to the racial disparity in mortality from any cause (34.0%), followed by As seen in Table 5, when considering the major categories of disease, deaths from cardiovascular .2-B elbaT B xidneppA eeS .SHCN morf atad ytilatrom laiciffo ni nemow dna nem htob rof setihw fo esoht naht rewol era setar ytilatrom kcalb sa reffid )redlo dna 58( sega tsedlo eht ta slaitnereffid laicar dna sdnert taht etoN .denimaxe erew sraey 58 fo ega eht erofeb tsol sraey-efil laitnetop nehw ralimis erew stluser lla taht etats srohtua eht hguoht sraey 57 fo ega eht erofeb gniyd snosrep rof era setamitse eseht dna ;setihw naht retteb eraf skcalb hcihw rof htaed-fo-sesuac wohs sesehtnerap ni srebmun ;noitacude fo level dna ,xes ,ega ni secar neewteb secnereffid rof tsujda snoitaluclaC :setoN .2002 ,41 .voN ,02 .on ,743 .lov ,enicideM fo lanruoJ dnalgnE weN ",ytilatroM ni seitirapsiD ot sesaesiD rojaM fo noitubirtnoC" ,seugaelloc dna gnoW .D.M morf noitatpada SRC :ecruoS 0.001 latoT 4.1 sesaesid cigolotamuehR 8.91 sesuac rehto llA 0.4 esaesid laneR 2.2 stnedicca rehtO 8.0 sesaesid detaler-lohoclA 5.8 edicimoH 6.2 esaesid reviL )5.2( ediciuS 5.8 sutillem setebaiD 5.2 tnedicca elcihev rotoM )8.5( esaesid gnuL 7.01 amuart llA 4.3 recnaC 6.0 snoitcefni rehtO 0.5 esaesid DVC rehtO 2.11 VIH 6.5 citorelcsoiretra rehtO 4.3 sispeS 1.0 eruliaf traeh evitsegnoC 1.0 sititapeh lariV 0.51 noisnetrepyH 2.5 ainomuenP 8.2 ekorts ralucsavorbereC 6.0 sisolucrebuT 5.5 esaesid traeh cimehcsI 1.12 noitcefnI 0.43 esaesid ralucsavoidraC ytirapsiD htaed fo esuaC ytirapsiD htaed fo esuaC fo % fo % )yti rapsid la ica r l larevo ot hta ed fo esua c cificeps fo noitubirtnoc tnecreP( tsoL srae efiL laitnetoP ni ytirapsiD laicaR .5 elba Y T (Table 5). years of life lost related to specific causes of deaths for blacks and whites in the United States differences between the races. Wong and colleagues,56 for instance, recently calculated potential researchers have investigated which specific diseases contribute most to life expectancy Mortality from most, but not all, causes of death are higher for blacks, and a number of ¢¡ ¢¡ (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 studies,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 to the 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 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 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, and economic 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, these factors may affect the age of onset of both morbidity and disability, the severity of symptoms, and ultimately 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 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, 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 to lower the risks for some chronic diseases--most notably, coronary heart disease (which is the leading cause of death in the United States)--while retarding the pace of disease progression for other conditions.67 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 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 to select 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 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 white divorcees.70 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 to marry.71 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 status. Berkman and Mullen,72 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 whites.73 The United States is the only developed country in the world that does not have national health coverage,74 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 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 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 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 with single-gene disorders in populations that have descended from a relatively small number of people 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. 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 that is replacing the earlier "young" age-sex structure with that of an older population.81 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 AIDS, SARS, antibiotic resistant microbes.82 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 developed 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 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, 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 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), 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. .ycnatcepxe efil ot srefer yllausu "ytivegnol egarevA" .naps efil ;efil fo htgneL .ytivegnoL .)htrib gnidulcni( yadhtrib nevig a ot evivrus ohw esoht rof gniniamer efil fo sraey eht dna ,syadhtrib owt neewteb evila rebmun eht ,yadhtrib nevig a ot devivrus ohw esoht rof yadhtrib tneuqesbus a gnihcaer erofeb gniyd fo ytilibaborp eht ,yadhtrib tneuqesbus a hcaer yeht erofeb yadhtrib nevig a ot gnivivrus esoht ot shtaed .snoitcnuf fo rebmun eht ,ega nevig a ot gnivivrus rebmun edulcni elbat efil a fo stnemele latnemadnuf ehT elbat efiL .)noitcnitxe sti ot( emit revo dewollof trohoc htrib lautca na fo ytilatrom eht no desab si elbat efil lanoitareneg a ;emit ni tniop elgnis a morf atad ega dna ytilatrom gnisu yb detcurtsnoc si elbat efil doirep A .noitalupop nevig a rof setar ytilatrom cificeps-ega fo noitanibmoc a fo desopmoc ledom lacitsitats A .elbat efiL .efil namuh fo stimil reppu emertxe ehT .snoitidnoc mumitpo rednu niatta dluoc sgnieb namuh taht ega mumixam ehT .naps efiL .ycnatcepxe efil doireP dna ycnatcepxe efil trohoC osla eeS .sega rehto rof detaluclac eb osla nac ;htrib ta ycnatcepxe efil ot srefer ylnommoc tsoM .elbat efil a morf detaluclac sa ,ega nevig a dehcaer ohw snosrep fo puorg a ot gniniamer efil fo sraey fo rebmun egareva eht ot srefer oslA .efil s'nosrep taht fo tser eht rof deliaverp raey nevig a rof setar htaed cificeps .ycnatcepxe -ega eht fi evil ot tcepxe dluoc nosrep a sraey lanoitidda fo rebmun egareva eht fo etamitse nA efiL .elbat efil a gnisu detamitse yllausu ,htaed erofeb snosrep fo puorg ro nosrep .efil a rof gniniamer )sraey ni derusaem yllausu( emit fo tnuoma egareva eht fo erusaem lacitsitats A fo noitatcepxE .aerA .setats lla dessapmocne 3391 yb dna 0091 ni dehsilbatse saw tI .shtaed fo noitartsiger noitartsigeR eht rof sdradnats laredef htiw gniylpmoc stnemnrevog lacol dna setats eht ,setatS detinU eht nI htaeD .etar cificeps-ega osla eeS .etar htaed edurc eht sa ot derrefer oslA .raey nevig a ni noitalupop eht ni snosrep 000,1 rep shtaed fo rebmun ehT .etar htaeD .etacifitrec htaed a yb dedrocer sa ,noitalupop a fo rebmem a fo ssol ehT .ecalp nekat sah htrib evil a retfa emit yna ta efil fo ecnedive lla fo ecnaraeppasid tnenamrep ehT .htaeD .tneve eht ot slevel erusopxe tnereffid gninrecnoc noitcnitsid on sekam dna noitalupop latot eht ot tneve cihpargomed a setaler taht etar A .etar edurC .sevivrus ehs ro eh fi ega gnideeccus hcae hcaer yllautca lliw laudividni eht hcihw ni sraey fo seires .ycnatcepxe eht morf tub ,raey elgnis a morf ton setar htaed gnisu ycnatcepxe efil etaluclac ot dohtem A efil trohoC .)htaed ,.g.e( tneve langis gnitanimret a fo sisab eht no denifed eb osla nac yeht tub )htrib ,.g.e( tneve langis gnitaitini na fo sisab eht no denifed yllacipyt era strohoC .htrib fo raey rieht sa hcus emit fo doirep ralucitrap a gnirud tneve cihpargomed emas eht ecneirepxe ohw elpoep fo puorg A .trohoC .)2002 ,4691-6491 doirep emit ,0091 raey ,.g.e( doirep nevig a ni nrob noitalupop a fo srebmeM .trohoc htriB .etar cificeps-ega osla eeS ".devil sraey-nosrep" fo noitamixorppa na sa desu si ti ,raey a sa hcus ,doirep nevig a fo .noitalupop elddim eht ta noitalupop eht fo mrof eht nI .rucco yllaitnetop nac tneve na mohw ot snosrep ehT ksir-tA .noitalupop eht fo ega naidem eht ni esir a ni stluser ssecorp sihT .esaerced stnecseloda dna nerdlihc fo noitroporp .)noitalupop eht elihw ,noitalupop a ni esaercni ylredle dna stluda fo noitroporp eht hcihw ni ssecorp A fo( gnigA .0001 * ])44-04 dega noitalupop latoT(/)44 -04 dega snosrep ot shtaeD([ = 44-04 dega snosrep rof noitalupop ralucitrap a ni etar htaed cificeps-ega eht ,elpmaxe roF .)puorg ega ro( ega emas eht ni noitalupop ksir-ta gnidnopserroc .etar eht ot )puorg ega ro( ega cificeps a ta tneve cihpargomed nevig a setaler taht etar A cificeps-egA .noitisopmoc noitalupop ni secnereffid ega morf tluser taht setar )edurc( devresbo ni secnereffid etanimile setar detsujda-egA .emit ni stniop erom ro owt ta noitalupop .tnemtsujda eno ro emit ni tniop eno ta snoitalupop erom ro owt fo sksir erapmoc ot desu erudecorP -egA ¢ ¡ ¢¡ .3A ,V elbat ,fdp.60rt/60RT/RT/TCAO /vog.ass.www//:ptth ta ,6002 ,1 yaM ,sdnuF tsurT ytilibasiD dna ecnarusnI srovivruS dna egA-dlO laredeF eht fo seetsurT eht fo tropeR launnA 6002 ,noitartsinimdA ytiruceS laicoS )5( ;2 xidneppA ,4002 ,DM ,ellivsttayH ,snaciremA fo htlaeH eht ni sdnerT no koobtrahC htiW ,4002 ,setatS detinU ,htlaeH ,scitsitatS htlaeH rof retneC lanoitaN )4( ;8991 ,uaeruB ecnerefeR noitalupoP ,CD ,.hsaW ,noitidE lanoitanretnI ht 4 ,koobdnaH noitalupoP s'uaeruB ecnerefeR noitalupoP .enaK .T.T dna tpuaH .A )3( ;1002 ,gnihsilbuP llewkcalB ,sessecorP noitalupoP gniledoM dna gnirusaeM :yhpargomeD ,tolliuG .M dna ,enilevueH .P ,notserP .H.S )2( ;4002 ,sserP cimedacA reiveslE .de dn2 ,yhpargomeD fo slairetaM dna sdohteM ehT .sde ,nosnawS .A.D dna legeiS .S.J )1( :no desab noitalipmoc SRC :ecruoS .tsol sraey efil laitnetop sa ot derrefer semitemoS .esaesid .tsol ro yrujni morf ylerutamerp deid ton dah yeht fi devil evah dluow elpoep taht sraey eht gnitamitse efil laitnetop yb detupmoc ,yteicos no secrof lahtel dna sesaesid suoirav fo tcapmi evitaler eht fo erusaeM fo sraeY .sesusnec owt ro selbat efil no desab eb naC .rehtona ot ega eno morf dna rehtona ot etad eno morf ,puorg ega na yllausu ,puorg noitalupop a fo lavivrus fo ytilibaborp eht gnisserpxe etar A .etar lavivruS .lavretni deificeps a retfa evila sniamer puorg ro laudividni na erehw noitidnoc a yliramirP .lavivruS .elamef dna elam fo seirogetac eht otni noitalupop eht fo noitacifissalC .xeS .ecar yb deifitnedi -fles era snosrep ,susnec lainneced setatS detinU eht nI .noitaremune-fles yb ro srotaremune yevrus ro susnec yb tnemngissa fo sisab eht eb yam ,snoitailiffa cinhte lanoitan gnidulcni ,scitsiretcarahc rehto ro roloc niks hcihw ni seirogetac ni pihsrebmem fo snoitinifed detcurtsnoc yllaicos fo smret ni noitalupop a fo srebmem eht fo noitacifissalc ,ecitcarp cihpargomed nI .yrtsecna lacigoloib fo smret ni noitalupop a fo srebmem eht fo noitacifissalc ,yroeht nI .ecaR .noitcejorp noitalupoP eeS .noitcejorP .tsol sraey .tsol efil laitnetop fo sraey eeS efil laitnetoP .)noitubirtsid dna noitisopmoc sti htiw gnola netfo( noitalupop erutuf a fo ezis eht tuoba tnemetats lanoitidnoc a si ti ,gnikaeps yltcirtS .mhtirogla na htiw noitanibmoc ni aera nevig a rof egnahc noitalupop fo stnenopmoc eht fo seulav .noitcejorp erutuf gnidrager snoitpmussa ticilpxe dna ticilpmi fo tes ralucitrap a fo emoctuo laciremun ehT noitalupoP .emit nevig a ta aera nevig a fo "stnatibahni" ehT .noitalupoP .elbat efil dna noitalupop ksir-ta :osla eeS .noitseuq ni emit eht gnirud snosrep eseht yb devil )foereht snoitcarf dna( sraey ni emit fo tnuoma eht )2( dna tnemges noitalupop ro noitalupop eht ni snosrep fo rebmun eht )1( fo tcudorp eht gnitupmoc yb detamixorppa si tI .emit fo doirep nevig a gnirud tnemges .devil noitalupop ro noitalupop nevig a yb devil )foereht snoitcarf dna( sraey fo rebmun latot ehT sraey-nosreP .noitalupop nevig .elbat a rof )raey eno yltneuqerf( emit ni tniop nevig a ta detcelloc atad ytilatrom no desab elbat efil A efil doireP .raey taht retfa setar htaed ni egnahc on eb lliw taht demussa si ti fi ylno ega detceles a ta efil gniniamer detcepxe eht sa deweiv eb yam raey ralucitrap a rof ycnatcepxe efil doirep ehT .etar htaed detsujda-xes-ega eht ot detaler ylesolc si tI .raey elgnis a ni decneirepxe setar htaed eht fo level llarevo eht gnitartsulli rof citsitats yrammus lufesu a si tI .raey taht rof ega hcae .ycnatcepxe ta setar htaed detcepxe ro lautca eht gnisu raey nevig a rof ycnatcepxe efil etaluclac ot dohtem A efil doireP .noitalupop a ni shtaed fo ecnedicni eht rof mret lareneg A .ytilatroM .noitalupop a ni seitilibasid dna ,seirujni ,ssenlli ,esaesid fo ycneuqerf ehT .ytidibroM .elbat efil emas eht ni htrib ta ycnatcepxe efil ot lauqe si shtaed elbat efil fo htaed ta ega naem .htaed eht ,elbat efil eht nI .raey nevig a ni shtaed detroper eht fo htaed ta ega naem citemhtira ehT ta ega naeM ¢¡ 3.17 4.26 8.66 3.77 5.96 4.37 6.67 8.86 6.27 5791 6.17 9.26 2.76 5.77 9.96 6.37 8.67 1.96 9.27 6791 0.27 4.36 7.76 9.77 2.07 0.47 2.77 5.96 3.37 7791 4.27 7.36 1.86 0.87 4.07 1.47 3.77 6.96 5.37 8791 9.27 0.46 5.86 4.87 8.07 6.47 8.77 0.07 9.37 9791 5.27 8.36 1.86 1.87 7.07 4.47 4.77 0.07 7.37 0891 2.37 5.46 9.86 4.87 1.17 8.47 8.77 4.07 1.47 1891 6.37 1.56 4.96 7.87 5.17 1.57 1.87 8.07 5.47 2891 5.37 2.56 4.96 7.87 6.17 2.57 1.87 0.17 6.47 3891 6.37 3.56 5.96 7.87 8.17 3.57 2.87 1.17 7.47 4891 4.37 0.56 3.96 7.87 8.17 3.57 2.87 1.17 7.47 5891 4.37 8.46 1.96 8.87 9.17 4.57 2.87 2.17 7.47 6891 4.37 7.46 1.96 9.87 1.27 6.57 3.87 4.17 9.47 7891 2.37 4.46 9.86 9.87 2.27 6.57 3.87 4.17 9.47 8891 3.37 3.46 8.86 2.97 5.27 9.57 5.87 7.17 1.57 9891 6.37 5.46 1.96 4.97 7.27 1.67 8.87 8.17 4.57 0991 8.37 6.46 3.96 6.97 9.27 3.67 9.87 0.27 5.57 1991 9.37 0.56 6.96 8.97 2.37 5.67 1.97 3.27 8.57 2991 7.37 6.46 2.96 5.97 1.37 3.67 8.87 2.27 5.57 3991 9.37 9.46 5.96 6.97 3.37 5.67 0.97 4.27 7.57 4991 9.37 2.56 6.96 6.97 4.37 5.67 9.87 5.27 8.57 5991 2.47 1.66 2.07 7.97 9.37 8.67 1.97 1.37 1.67 6991 7.47 2.76 1.17 9.97 3.47 2.77 4.97 6.37 5.67 7991 8.47 6.76 3.17 0.08 5.47 3.77 5.97 8.37 7.67 8991 7.47 8.76 4.17 9.97 6.47 3.77 4.97 9.37 7.67 9991 2.57 3.86 9.17 1.08 9.47 6.77 7.97 3.47 0.77 0002 5.57 6.86 2.27 2.08 0.57 7.77 8.97 4.47 2.77 1002 6.57 8.86 3.27 3.08 1.57 7.77 9.97 5.47 3.77 2002 1.67 0.96 7.27 5.08 3.57 0.87 1.08 8.47 5.77 3002 bsetatS detinU F M htoB F M htoB F M htoB xeS .rY a kcalB etihW secaR llA )sraey ni( 3002-0091 :xeS dna ecaR yb ,ht riB ta ycnatcepxE efiL .1-B elbaT ¡¢ ¡ ¢¡ 9.45 5.15 1.35 6.66 1.26 2.46 2.56 8.06 9.26 0491 3.55 5.25 8.35 5.86 4.46 2.66 8.66 1.36 8.46 1491 2.85 4.55 6.65 4.96 9.56 3.76 9.76 7.46 2.66 2491 1.65 4.55 6.55 7.56 2.36 2.46 4.46 4.26 3.36 3491 7.75 8.55 6.65 4.86 5.46 2.66 8.66 6.36 2.56 4491 6.95 1.65 7.75 5.96 4.46 8.66 9.76 6.36 9.56 5491 0.16 5.75 1.95 3.07 1.56 5.76 4.96 4.46 7.66 6491 9.16 9.75 7.95 5.07 2.56 6.76 7.96 4.46 8.66 7491 5.26 1.85 0.06 0.17 5.56 0.86 9.96 6.46 2.76 8491 7.26 9.85 6.06 9.17 2.66 8.86 7.07 2.56 0.86 9491 9.26 1.95 8.06 2.27 5.66 1.96 1.17 6.56 2.86 0591 4.36 2.95 2.16 4.27 5.66 3.96 4.17 6.56 4.86 1591 8.36 1.95 4.16 6.27 6.66 5.96 6.17 8.56 6.86 2591 5.46 7.95 0.26 0.37 8.66 7.96 0.27 0.66 8.86 3591 9.56 1.16 4.36 7.37 5.76 5.07 8.27 7.66 6.96 4591 1.66 4.16 7.36 7.37 4.76 5.07 8.27 7.66 6.96 5591 1.66 3.16 6.36 9.37 5.76 5.07 9.27 7.66 7.96 6591 5.56 7.06 0.36 7.37 2.76 3.07 7.27 4.66 5.96 7591 8.56 0.16 4.36 9.37 4.76 5.07 9.27 6.66 6.96 8591 5.66 3.16 9.36 2.47 5.76 7.07 2.37 8.66 9.96 9591 3.66 1.16 6.36 1.47 4.76 6.07 1.37 6.66 7.96 0691 1.76 0.26 5.46 6.47 8.76 0.17 6.37 1.76 2.07 1691 9.66 6.16 2.46 5.47 7.76 9.07 5.37 9.66 1.07 d2691 6.66 0.16 7.36 4.47 4.76 8.07 4.37 6.66 9.96 d3691 3.76 3.16 2.46 7.47 7.76 0.17 7.37 8.66 2.07 4691 6.76 2.16 3.46 8.47 6.76 1.17 8.37 8.66 2.07 5691 6.76 9.06 2.46 8.47 5.76 1.17 9.37 7.66 2.07 6691 5.86 4.16 9.46 2.57 8.76 4.17 3.47 0.76 5.07 7691 9.76 4.06 1.46 0.57 5.76 1.17 1.47 6.66 2.07 8691 6.86 6.06 5.46 3.57 7.76 4.17 4.47 8.66 5.07 9691 3.86 0.06 1.46 6.57 0.86 7.17 7.47 1.76 8.07 0791 9.86 5.06 6.46 8.57 3.86 0.27 0.57 4.76 1.17 1791 1.96 4.06 7.46 9.57 3.86 0.27 1.57 4.76 2.17 c2791 3.96 9.06 0.56 1.67 5.86 2.27 3.57 6.76 4.17 3791 3.07 7.16 0.66 7.67 0.96 8.27 9.57 2.86 0.27 4791 F M htoB F M htoB F M htoB xeS .rY a kcalB etihW secaR llA ¢¡ 9.33 8.13 9.23 4.15 3.74 3.94 8.05 9.64 7.84 6091 0.43 1.13 5.23 4.05 0.64 1.84 9.94 6.54 6.74 7091 0.63 8.33 9.43 3.35 9.94 5.15 8.25 5.94 1.15 8091 3.73 2.43 7.53 2.45 9.05 5.25 8.35 5.05 1.25 9091 5.73 8.33 6.53 0.25 6.84 3.05 8.15 4.94 0.05 0191 2.83 6.43 4.63 9.45 3.15 0.35 4.45 9.05 6.25 1191 0.04 9.53 9.73 2.65 9.15 9.35 9.55 5.15 5.35 2191 3.04 7.63 4.83 7.55 8.05 0.35 0.55 3.05 5.25 3191 8.04 1.73 9.83 5.75 7.25 9.45 8.65 0.25 2.45 4191 5.04 5.73 9.83 5.75 1.35 1.55 8.65 5.25 5.45 5191 1.34 6.93 3.14 2.55 2.05 5.25 3.45 6.94 7.15 6191 8.04 0.73 8.83 3.55 3.94 0.25 0.45 4.84 9.05 7191 5.23 9.92 1.13 2.34 1.73 8.93 2.24 6.63 1.93 8191 4.44 5.44 5.44 4.75 5.45 8.55 0.65 5.35 7.45 9191 2.54 5.54 3.54 6.55 4.45 9.45 6.45 6.35 1.45 0291 3.15 6.15 5.15 9.26 8.06 8.16 8.16 0.06 8.06 1291 0.35 8.15 4.25 9.16 1.95 4.06 0.16 4.85 6.95 2291 9.84 7.74 3.84 6.95 1.75 3.85 5.85 1.65 2.75 3291 8.74 5.54 6.64 4.36 8.95 4.16 5.16 1.85 7.95 4291 7.64 9.44 7.54 4.26 3.95 7.06 6.06 6.75 0.95 5291 6.54 7.34 6.44 6.95 0.75 2.85 0.85 5.55 7.65 6291 9.84 6.74 2.84 9.36 5.06 0.26 1.26 0.95 4.06 7291 0.74 6.54 3.64 0.06 0.75 4.85 3.85 6.55 8.65 8291 esetatS noitartsigeR htaeD 8.74 7.54 7.64 3.06 2.75 6.85 7.85 8.55 1.75 9291 2.94 3.74 1.84 5.36 7.95 4.16 6.16 1.85 7.95 0391 5.15 5.94 4.05 7.46 8.06 6.26 1.36 4.95 1.16 1391 6.45 8.25 7.35 5.46 0.26 2.36 5.36 0.16 1.26 2391 0.65 5.35 7.45 3.66 7.26 3.46 1.56 7.16 3.36 3391 7.35 2.05 8.15 6.46 5.06 4.26 3.36 3.95 1.16 4391 2.55 3.15 1.35 0.56 0.16 9.26 9.36 9.95 7.16 5391 4.15 0.74 0.94 9.16 0.85 8.95 6.06 6.65 5.85 6391 5.25 3.84 3.05 8.36 3.95 4.16 4.26 0.85 0.06 7391 3.45 7.15 9.25 8.66 2.36 0.56 3.56 9.19 5.36 8391 0.65 2.35 5.45 6.66 3.36 9.46 4.56 1.26 7.36 9391 F M htoB F M htoB F M htoB xeS .rY a kcalB etihW secaR llA ¢¡ 5.3 9.4 1.4 1.34 3.73 4.04 6.64 2.24 5.44 53 7.3 1.5 3.4 8.74 8.14 0.54 5.15 9.64 3.94 03 7.3 3.5 5.4 6.25 3.64 6.94 3.65 6.15 1.45 52 8.3 6.5 6.4 4.75 7.05 2.45 2.16 3.65 8.85 02 8.3 6.5 6.4 3.26 4.55 0.95 1.66 0.16 6.36 51 8.3 7.5 6.4 2.76 3.06 9.36 0.17 0.66 5.86 01 8.3 6.5 6.4 2.27 3.56 9.86 0.67 9.07 5.37 5 9.3 7.5 7.4 0.67 1.96 7.27 9.97 8.47 4.77 1 4.4 3.6 3.5 1.67 0.96 7.27 5.08 3.57 0.87 0 F M llA F M llA F M llA egA )kcalB-etihW( noitalupoP kcalB noitalupoP etihW ecnereffiD )s r a e y n i , a t a d l a n i f ( ecaR dna xeS yb ,3002 ni segA suoiraV ta ycnatcepxE efiL .2-B elbaT .emit htiw desaercni dedulcni setats fo rebmun eht ;0091 fo aera noitartsiger htaed lanigiro eht ni erew aibmuloC fo tcirtsiD eht dna setats 01 ylnO .tem erew sdradnats noitacifilauq sa saera noitartsiger eht ot dettimda ylno erew setatS .aerA noitartsigeR htaeD eht fo pu gnittes eht htiw 0091 ni nageb metsys noitartsiger livic laredef ehT .setatS detinU eritne eht ton ;"setatS noitartsigeR htaeD" eht ni shtaed no desab era 8291-0091 rof ataD .e .yesreJ weN fo stnediser rof atad edulcxe raey siht ni ecar yb serugiF .d .elpmas %05 a no desab shtaeD .c .0691 ni iiawaH dna 9591 ni dedulcni aksalA .b .noitalupop etihwnon rof era 9691-0091 rof nwohs ataD .elbaliava ton era noitalupop kcalb rof atad ,0791 ot roirP .a .setatS detinU eht fo stnedisernon fo shtaed sedulcxe ,0791 gninnigeb dna ;setamitse era nwohs seulav elbat efil ,sraey detceles roF ;efil s'nrobwen eht fo tser eht rof eunitnoc ot erew htrib fo raey eht ni sdnert ytilatrom fi ,egareva no ,evil ot tcepxe dluoc nrobwen a taht sraey fo rebmun eht serusaem )htrib ta( 0 ega ta ycnatcepxe efiL :setoN .6002 ,91 .rpA ,3002 rof ataD laniF :shtaeD ,tropeR scitsitatS latiV lanoitaN ,SHCN :raey tnecer tsom roF .21 elbaT ,4002 ,01 .voN ,2002 ,selbaT efiL setatS detinU ,tropeR scitsitatS latiV lanoitaN ,)SHCN( scitsitatS htlaeH rof retneC lanoitaN morf noitalipmoc SRC :atad lacirotsih roF :ecruoS 5.33 5.23 0.33 7.84 6.64 6.74 3.84 3.64 3.74 0091 3.53 2.23 7.33 0.15 0.84 4.94 6.05 6.74 1.94 1091 4.63 9.23 6.43 8.35 2.05 9.15 4.35 8.94 5.15 2091 6.43 7.13 1.33 5.25 5.94 9.05 0.25 1.94 5.05 3091 7.23 1.92 8.03 5.94 6.64 0.84 1.94 2.64 6.74 4091 1.33 6.92 3.13 6.05 6.74 1.94 2.05 3.74 7.84 5091 F M htoB F M htoB F M htoB xeS .rY a kcalB etihW secaR llA ¢¡ lshrestha@crs.loc.gov, 7-7046 Specialist in Domestic Social Policy Laura B. Shrestha .noitairav modnar ro gnilpmas ot tcejbus era ataD .setatS rehto htiw ytilibarapmoc rof sdradnats BMO 7791 eht fo seirogetac elgnis eht ot SHCN yb degdirb erew setatS eseht rof atad ecar-elpitlum ehT .3002 ni atad ecar-elpitlum detroper nisnocsiW dna ,kroY weN ,anatnoM ,eniaM ,ohadI ,iiawaH ,ainrofilaC setats neveS .senilediug tegduB dna tnemeganaM fo eciffO 7791 eht htiw tnetsisnoc era seirogetac ecaR .1 yluJ fo sa detamitse snoitalupop yolpme ycnatcepxe efil fo snoitaluclaC .setatS eht morf sdrocer fo elif suounitnoc a no desab era ataD .3002 ni 56 ega deniatta ydaerla dah eh taht nevig ,egareva no ,evil lliw 56 ega ta nosrep a efil fo sraey lanoitidda fo rebmun eht serusaem 56 ega ta ycnatcepxe efiL .efil s'nrobwen eht fo tser eht rof eunitnoc ot erew 3002 ni devresbo sdnert ytilatrom eht fi ,egareva no ,evil ot tcepxe dluoc 3002 ni nrob dlihc a taht sraey fo rebmun eht serusaem )htrib ta( 0 ega ta ycnatcepxe efiL :setoN .6002 ,91 .rpA ,31 .on ,45 .lov ",3002 rof ataD laniF :shtaeD" ,tropeR scitsitatS latiV lanoitaN ,scitsitatS htlaeH rof retneC lanoitaN morf noitalipmoc SRC :ecruoS 9.0- 8.0- 9.0- 4.3 0.3 4.3 5.2 2.2 5.2 001 9.0- 7.0- 9.0- 5.4 8.3 4.4 6.3 1.3 5.3 59 9.0- 7.0- 8.0- 0.6 0.5 7.5 1.5 3.4 9.4 09 7.0- 5.0- 7.0- 8.7 4.6 4.7 1.7 9.5 7.6 58 2.0- 1.0 2.0- 8.9 9.7 2.9 6.9 0.8 0.9 08 2.0 7.0 3.0 4.21 8.9 4.11 6.21 5.01 7.11 57 7.0 4.1 9.0 3.51 1.21 0.41 0.61 5.31 9.41 07 3.1 0.2 5.1 5.81 9.41 0.71 8.91 9.61 5.81 56 7.1 7.2 1.2 1.22 9.71 2.02 8.32 6.02 3.22 06 2.2 4.3 7.2 9.52 2.12 8.32 1.82 6.42 5.62 55 7.2 0.4 2.3 9.92 8.42 6.72 6.23 8.82 8.03 05 1.3 4.4 6.3 1.43 7.82 6.13 2.73 1.33 2.53 54 3.3 5.4 7.3 6.83 9.23 0.63 9.14 6.73 8.93 04 F M llA F M llA F M llA egA )kcalB-etihW( noitalupoP kcalB noitalupoP etihW ecnereffiD ¢¡ ------------------------------------------------------------------------------ For other versions of this document, see http://wikileaks.org/wiki/CRS-RL32792