Demographers have established that the rich live longer, on average, than the poor. In recent years, a substantial body of research has also demonstrated that the gap in average life spans between the rich and the poor is growing significantly. For example, a recent study by the National Academy of Sciences (NAS) finds that among male workers born in 1930, those in the bottom lifetime earnings quintile can expect to live to age 77, on average, while male workers in the top quintile can expect to live to 82. For the later 1960 cohort, this same study estimates that male workers in the bottom quintile show no gains in life expectancy as compared with those born three decades earlier, while men at the top quintile of lifetime earnings can expect to live more than seven years longer, to age 89. Current interest in the growing gap in life expectancy by income has been fueled by several recent, high-profile studies on this issue. In addition to the NAS work ( The Growing Gap in Life Expectancy by Income: Implications for Federal Programs and Policy Responses, 2015 ), in 2016 the Government Accountability Office (GAO; Retirement Security: Shorter Life Expectancy R educes Projected Lifetime Benefits for Lower Earners ), the Brookings Institution ( Later Retirement, Inequality in Old Age, and the Growing Gap in Longevity B etween Rich and Poor ), and Stanford economist Raj Chetty and colleagues ( The Association Between Income and Life Expectancy in the United States, 2001-2014 ) all published new evidence on the growing gap in life expectancy. These studies also discuss the policy implications of these findings. While policymakers and others may view increases in life expectancy as a positive outcome, they may be concerned with widening differentials in longevity. For instance, Congress may be interested in the connection between the growing gap in life expectancy between the rich and the poor and federal expenditures on programs like Social Security. Social Security provides monthly benefits to retired and disabled workers and their dependents, and to dependents of deceased workers. The goals of Social Security, a redistributive program, may be compromised by widening gaps in life spans. The program is designed to be progressive by redistributing income from those with high lifetime earnings to those with low lifetime earnings. When Social Security retirement benefits are measured on a lifetime basis, low earners, who show little to no gains in life expectancy over recent decades, are projected to receive relatively smaller benefits when compared with high earners. A commonly discussed Social Security reform proposal in the United States involves increasing the retirement age, which would affect low earners' lifetime benefits disproportionately. Congress may wish to reevaluate this type of reform proposal in light of the growing gap in life expectancy by income and may be interested in policy proposals that protect the interests of lower-earning, shorter-lived workers, for example. This report provides a brief overview of the concept of life expectancy, how it is measured, and how it has changed over time in the United States. While life expectancy may be studied in a variety of contexts, this report focuses on the link between life expectancy and socioeconomic status (SES), as measured by lifetime income. In particular, this report synthesizes recent research on (1) the life expectancy gap by income and (2) the relationship between this gap and Social Security retirement benefits. Finally, this report discusses the implications of this research for one type of Social Security reform proposal: raising the Social Security retirement age. Life expectancy is a measure of population longevity that refers to the average number of years an individual will live, given survival to a particular age and subject to age-specific mortality rates. Life expectancy has an inverse relationship with mortality rates (also referred to as death rates): as mortality rates decline, life expectancy increases. These measures can be studied in the aggregate (i.e., full population) or separately across demographic subgroups. Differential mortality rates across groups—for example, age, sex, or race—result in differential life expectancy estimates. Life expectancy is commonly presented as life expectancy at birth as well as at age 65. It can, however, be calculated at any age. When calculated at birth, life expectancy represents the average life span. Alternatively, life expectancy may refer to additional years of life when it is calculated for ages after birth (e.g., a life expectancy of 10 years at age 75, which indicates an expected age at death of 85). According to data from the Centers for Disease Control and Prevention (CDC) National Center for Health Statistics (NCHS), in 2014, life expectancy at age 65 in the United States was estimated to be 19.3 years (meaning individuals would be expected to live to age 84.3), whereas life expectancy at birth was 78.8 years. Life expectancy is often broken out by sex and race due to observed differences in sex-specific and race-specific death patterns. For example, in 2014, life expectancy at birth in the United States was estimated to be 76.4 years for men and 81.2 years for women. The comparable figures for life expectancy at birth by race were 75.6 years for blacks and 79.0 years for whites. In 2014, life expectancy at age 65 in the United States was estimated to be 18.0 years for men (so an expected age of death of 83.0 years [65+18.0=83.0]) and 20.5 years for women (so an expected age of death at 85.5 years [65+20.5=85.5]). Life expectancy at age 65 in 2014 was 18.2 years for blacks (so an expected age of death at 83.2 [65+18.2=83.2]) and 19.3 years for whites (so an expected age of death at 84.3 years [65+19.3=84.3]). For more background on the data and methods used to estimate life expectancy, see Box 1 . The recent research discussed throughout this report uses life expectancy estimates calculated at various ages (e.g., at age 50, age 65, or at the various ages of sample participants). For ease of comparison, these study estimates will be referred to as "life expectancy," although in some cases they may represent expected age of death (or total years of life expected to be lived). Figure 1 and Figure 2 provide CDC's recent estimates of period life expectancy in the United States over 1950-2014 (see Box 1 for a discussion of period life expectancy). Figure 1 presents life expectancy trends over this period for men and women at birth as well as expected ages of death based on life expectancy at age 65. Figure 2 graphs the same data broken out for whites and blacks. Two key observations may be drawn from these figures. First, life expectancy has increased over time for all groups. These increases in life expectancy have been driven by decreases in mortality rates. In particular, during the second half of the 20 th century, improvements in the prevention and control of chronic disease (e.g., heart disease and cerebrovascular diseases) have contributed to reduced adult mortality rates. Additionally, advances and innovations in medical technology (such as vaccines and antibiotics) as well as public health measures (for instance, clean water and sanitation initiatives and antismoking campaigns) have also contributed to mortality declines. (See Box 2 for a discussion of recent research, including recent work by Case and Deaton, that complicates this finding.) Second, there are gaps in life expectancy across sex and race that—despite evidence of narrowing over recent periods—have persisted over time. Worldwide, life expectancy is generally higher for women than for men. Researchers have proposed biological as well as behavioral and social factors to explain this differential in life expectancy by sex. In terms of race, in the United States, whites tend to live longer, on average, than blacks—although the longevity gap, as calculated at birth, has decreased over time. To explain this racial differential, researchers point to higher mortality for blacks due to health disparities as well as interactions among factors such as inequalities in socioeconomic status, behavioral factors, access to health care, and environmental surroundings. In addition to documenting differences in life expectancy across sex and race, researchers have also focused on disparities in life expectancy by socioeconomic status. SES serves as a measure of class, or an individual's economic and social position in society relative to others. It is a common indicator of social stratification and inequality. Policymakers may be particularly interested in gaps in life expectancy by SES because, unlike sex and race, SES is a measure of inequality that could potentially be addressed by policy interventions. Although gaps in life expectancy by sex and race have narrowed over time, there is evidence that the gap in life expectancy by SES has been growing over time, particularly across recent decades, as this report will discuss in detail below. SES is commonly measured by income, education, occupation, or some interaction of these concepts. In the field of life expectancy research, there are a variety of ways to operationalize SES. The two most common approaches are to measure SES with education or with income. The positive relationship between education and life expectancy—or the negative relationship between education and mortality—has been well-documented. Additionally, studies have found a growing gap in life expectancy by education over time, although this trend may not be uniform across sex and race. While education is a useful measure of SES because it is often stable by middle age, there are several drawbacks to this measure. First, education is subject to reporting error (e.g., misreported data), particularly in death record files. Second, it is a comparatively gross measure of SES; there are large components of the population that have attained each level of education (e.g., high school and college). Using such broad educational categories could gloss over disparities in life expectancy between population subgroups. Finally, there have been significant shifts in educational attainment in the United States over the last century (e.g., increasing rates of high school completion).