Black-White Disparities in Life Expectancy: How Much Can the Standard SES Variables Explain?

This article quantifies the extent to which socioeconomic and demographic characteristics can account for black-white disparities in life expectancy in the United States. Although many studies have investigated the linkages between race, socioeconomic status, and mortality, this article is the first to measure how much of the life expectancy gap remains after differences in mortality are purged of the compositional differences in socioeconomic characteristics between blacks and whites. The decomposition is facilitated by a reweighting technique that creates counterfactual estimation samples in which the distribution of income, education, employment and occupation, marital status, and other theoretically relevant variables among blacks is made to match the distribution of these variables among whites. For males, 80% of the black-white gap in life expectancy at age 1 can be accounted for by differences in socioeconomic and demographic characteristics. For females, 70% percent of the gap is accounted for. Labor force participation, occupation, and (among women only) marital status have almost no additional power to explain the black-white disparity in life expectancy after precise measures for income and education are controlled for.     

Double jeopardy: Interaction effects of marital and poverty status on the risk of mortality

The purpose of this paper is to examine the hypothesis that marital and poverty status interact in their effects on mortality risks beyond their main effects. This study examines the epidemiological bases for applying an additive rather than a multiplicative specification when testing for interaction between two discrete risk factors. We specifically predict that risks associated with being nonmarried and with being poor .interact to produce mortality risks that are greater than each risk acting independently. The analysis is based on men and women who were ages 25–74 during the 1971–1975 National Health and Nutrition Examination Survey I (NHANES I) and who were traced successfully in the NHANES I Epidemiologic Follow-Up Study in 1982–1984. Overall, being both poor and nonmarried places nonelderly (ages 25–64) men, but not women, at risk of mortality greater than that expected from the main effects. This study shows that for all-cause mortality, marital and poverty status interact for men but less so for women; these findings exist when interaction is assessed with either a multiplicative or an additive standard. This difference is most pronounced for poor, widowed men and (to a lesser degree) poor, divorced men. For violent/accidental deaths among men, the interaction effects are large on the basis of an additive model. Weak main and interaction effects were detected for the elderly (age 65 +).     

Early-life conditions and adult mortality decline in Dutch cohorts born 1812–1921

Mounting evidence suggests that early-life conditions have an enduring effect on an individual’s mortality risks as an adult. The contribution of improvements in early-life conditions to the overall decline in adult mortality, however, remains a debated issue. We provide an estimate of the contribution of improvements in early-life conditions to mortality decline after age 30 in Dutch cohorts born between 1812 and 1921. We used two proxies for early-life conditions: median height and early-childhood mortality. We estimate that improvements in early-life conditions contributed more than five years or about a third to the rise in women’s life expectancy at age 30. Improvements in early-life conditions contributed almost three years or more than a quarter to the rise in men’s life expectancy at age 30. Height appears to be the more important of the two proxies for early-life conditions.     

Gender Differences in Disability-Free Life Expectancy for Selected Risk Factors and Chronic Conditions in Canada

SUMMARY

This article shows how mortality and morbidity patterns differ for women and men 45 years of age and older. The impact on disability-free life expectancy was calculated for selected risk factors and chronic conditions: low income, low education, abnormal body mass index, lack of physical activity, smoking, cancer, diabetes, and arthritis. For each factor, the expected number of years free of disability was calculated for men and women using multi-state life tables. In terms of disability-free life expectancy, the greatest impacts on affected women were for diabetes (14.1 years), arthritis (8.8 years), and physical inactivity (6.0 years), while for affected men, the greatest impacts were for diabetes (10.5 years), smoking (6.9 years), arthritis (6.5 years), and cancer (6.4 years). The implications of these results are discussed from the perspective of developing programs designed to improve population health status.     

Health profiles and profile-specific health expectancies of older women and men: The Netherlands

This study focuses on gender differences in health profiles, and examines which health profiles drive gender differences in remaining life expectancy in women and men aged 65 and over in The Netherlands. Data from the first two cycles of the Longitudinal Aging Study Amsterdam (n = 2,141 and 1,659, respectively) were used to calculate health profiles for individuals of 65-85 years. For both women and men, six profiles were found: I. cancer; II. "other" chronic diseases; III. cognitive impairment; IV. frailty or multimorbidity; V. cardiovascular diseases; and VI. good health. The further characterization of these types showed some gender differences. Remaining life expectancy for women was greater than for men in each health profile. A decomposition into health expectancies showed that both women and men could expect to live about 5 years in good health from age 66. The greatest gender differences in years spent with health problems were found for profile IV and for profile III. Their greater number of years spent in these health states have direct consequences for the type and cost of care women need.     

Gender differences in disability-free life expectancy for selected risk factors and chronic conditions in Canada

This article shows how mortality and morbidity patterns differ for women and men 45 years of age and older. The impact on disability-free life expectancy was calculated for selected risk factors and chronic conditions: low income, low education, abnormal body mass index, lack of physical activity, smoking, cancer, diabetes, and arthritis. For each factor, the expected number of years free of disability was calculated for men and women using multi-state life tables. In terms of disability-free life expectancy, the greatest impacts on affected women were for diabetes (14.1 years), arthritis (8.8 years), and physical inactivity (6.0 years), while for affected men, the greatest impacts were for diabetes (10.5 years), smoking (6.9 years), arthritis (6.5 years), and cancer (6.4 years). The implications of these results are discussed from the perspective of developing programs designed to improve population health status.     

Health Profiles and Profile-Specific Health Expectancies of Older Women and Men: The Netherlands

SUMMARY

This study focuses on gender differences in health profiles, and examines which health profiles drive gender differences in remaining life expectancy in women and men aged 65 and over in The Netherlands. Data from the first two cycles of the Longitudinal Aging Study Amsterdam (n = 2,141 and 1,659, respectively) were used to calculate health profiles for individuals of 65–85 years. For both women and men, six profiles were found: I. cancer; II. “other” chronic diseases; III. cognitive impairment; IV. frailty or multimorbidity; V. cardiovascular diseases; and VI. good health. The further characterization of these types showed some gender differences. Remaining life expectancy for women was greater than for men in each health profile. A decomposition into health expectancies showed that both women and men could expect to live about 5 years in good health from age 66. The greatest gender differences in years spent with health problems were found for profile IV and for profile III. Their greater number of years spent in these health states have direct consequences for the type and cost of care women need.     

Exploring the Myth of Unhappiness in Former Communist Countries: The Roles of the Sex Gap in Life Expectancy and the Marital Status Composition

National average happiness and the difference in happiness between women and men are positively correlated in European countries. This study focuses on this cross-country relationship and tests (1) whether, after controlling for socio-economic factors, the correlation is attributed to their direct relationship, or, alternatively, explained by the sex difference in life expectancy, and (2) whether the correlation is not only exogenously explained but also endogenously generated by the sex difference in life expectancy. Performing regression analyses, this study shows that the correlation between happiness and its sex difference is spurious, and that the sex difference in life expectancy generates this correlation and accounts for about one-third of the correlation. A decline in happiness influences men’s mortality more than women’s, and widens the life expectancy gap between women and men. This in turn raises the widowhood ratio among women, lowers women’s average happiness, and reduces the happiness gap between women and men. The results obtained in this study points to the importance of controlling for the demographic composition of the population when we use aggregate happiness measures as national happiness indicators.     

Aging,Proximity to Death,and Religiosity

Considerable evidence has documented that the elderly are more religious and that religiosity is associated with better health and lower mortality. Yet, little is known about the reverse role of life expectancy or proximity to death, as opposed to age, for religiosity. This paper provides evidence for the distinct role of expected remaining life years for the importance of religion in individuals’ lives. We combine individual survey response data for more than 300,000 individuals from 95 countries over the period 1994–2014 with information from period life tables. Contrary to wide-held beliefs, religiosity decreases with greater expected proximity to death. The findings have important implications regarding the consequences of population aging for religiosity and associated outcomes.     

European Perspectives on Healthy Aging in Women

SUMMARY

Using data from the 1994 European Community Household Panel, we compare active life expectancy differentials at age 65 years between women and men in 12 European countries. We seek to explain the extent to which differences are a reflection of gender differentials in life expectancy at 65 years or reflect differences in active life expectancy earlier in life. Considerable variation in the gender differentials in both total and active life expectancies at age 65 years exist within Europe, with some countries experiencing 20% lower life expectancy at age 65 years for men compared to women. Some evidence was found to suggest that gender differentials in active life expectancy may continue from younger ages through to later life.     

The increase in marital status differences in mortality up to the oldest age in seven European countries, 1990–99

We investigate mortality differentials by marital status among older age groups using a database of mortality rates by marital status at ages 40 and over for seven European countries with 1 billion person-years of exposure. The mortality advantage of married people, both men and women, continues to increase up to at least the age group 85–89, the oldest group we are able to consider. We find the largest absolute differences in mortality levels between marital status groups are at high ages, and that absolute differentials are: (i) greater for men than for women; (ii) similar in magnitude across countries; (iii) increase steadily with age; and (iv) are greatest at older age. We also find that the advantage enjoyed by married people increased over the 1990s in almost all cases. We note that results for groups such as older divorced women need to be interpreted with caution.     

The increase in marital status differences in mortality up to the oldest age in seven European countries, 1990-99

We investigate mortality differentials by marital status among older age groups using a database of mortality rates by marital status at ages 40 and over for seven European countries with 1 billion person-years of exposure. The mortality advantage of married people, both men and women, continues to increase up to at least the age group 85-89, the oldest group we are able to consider. We find the largest absolute differences in mortality levels between marital status groups are at high ages, and that absolute differentials are: (i) greater for men than for women; (ii) similar in magnitude across countries; (iii) increase steadily with age; and (iv) are greatest at older age. We also find that the advantage enjoyed by married people increased over the 1990s in almost all cases. We note that results for groups such as older divorced women need to be interpreted with caution.     

European perspectives on healthy aging in women

Using data from the 1994 European Community Household Panel, we compare active life expectancy differentials at age 65 years between women and men in 12 European countries. We seek to explain the extent to which differences are a reflection of gender differentials in life expectancy at 65 years or reflect differences in active life expectancy earlier in life. Considerable variation in the gender differentials in both total and active life expectancies at age 65 years exist within Europe, with some countries experiencing 20% lower life expectancy at age 65 years for men compared to women. Some evidence was found to suggest that gender differentials in active life expectancy may continue from younger ages through to later life.     

Measuring years of inactivity,years in retirement,time to retirement,and age at retirement within the Markov model

Retirement-related concepts are treated as random variables within Markov process models that capture multiple labor force entries and exits. The expected number of years spent outside of the labor force, expected years in retirement, and expected age at retirement are computed—all of which are of immense policy interest but have been heretofore reported with less precisely measured proxies. Expected age at retirement varies directly with a person’s age; but even younger people can expect to retire at ages substantially older than those commonly associated with retirement, such as age 60, 62, or 65. Between 1970 and 2003, men allocated most of their increase in life expectancy to increased time in retirement, but women allocated most of their increased life expectancy to labor force activity. Although people can exit and reenter the labor force at older ages, most 65-year-old men who are active in the labor force will not reenter after they eventually exit. At age 65, the probability that those who are inactive will reenter the labor force at some future time is .38 for men and .27 for women. Life expectancy at exact ages is decomposed into the sum of the expected time spent active and inactive in the labor force, and also as the sum of the expected time to labor force separation and time in retirement.     

Changing Life Expectancy and Health Expectancy Among Russian Adults: Results from the Past 20 Years

The decade following the collapse of the Soviet Union was characterized by wide fluctuations in Russian mortality rates, but since the early 2000s, life expectancy has improved progressively. Recent upturns in longevity have promoted policy debates over extending the retirement age in the country. However, whether observed gains in life expectancy are accompanied by improving health remains to be addressed. Using data from the 1994–2014 Russian Longitudinal Monitoring Survey of the Higher School of Economics, this study investigates trends over 20 years in healthy life expectancy (HLE) and illness-free life expectancy (IFLE) for men and women at adult ages. Analyses using the Sullivan method show that men and women at adult ages have experienced large increases in health expectancies during the post-Soviet period. Increases in HLE exceeded increases in total life expectancy for both genders. Further, health expectancies have evolved over time through cycles of increases and decreases, just like life expectancy. These results suggest increases in good-quality years among men and women at working ages, offering support for changing the official retirement age. The extent of the change in the retirement age, however, needs to be carefully considered, given that, despite recent improvements, the health expectancy of the Russian population still remains low.     

Using Subjective Expectations to Forecast Longevity: Do Survey Respondents Know Something We Don’t Know?

Old-age mortality is notoriously difficult to predict because it requires not only an understanding of the process of senescence-which is influenced by genetic, environmental, and behavioral factors-but also a prediction of how these factors will evolve. In this paper I argue that individuals are uniquely qualified to predict their own mortality based on their own genetic background, as well as environmental and behavioral risk factors that are often known only to the individual. Given this private information, individuals form expectations about survival probabilities that may provide additional information to demographers and policymakers in their challenge to predict mortality. From expectations data from the 1992 Health and Retirement Study (HRS), I construct subjective, cohort life tables that are shown to predict the unusual direction of revisions to U.S. life expectancy by gender between 1992 and 2004: that is, for these cohorts, the Social Security Actuary (SSA) raised male life expectancy in 2004 and at the same lowered female life expectancy, narrowing the gender gap in longevity by 25% over this period. Further, although the subjective life expectancies for men appear to be roughly in line with the 2004 life tables, the subjective expectations of women suggest that female life expectancies estimated by the SSA might still be on the high side.     

Income and inequality as determinants of mortality: An international cross-section analysis

This paper analyses the effects of income and income distribution on mortality. The likely relation between income and mortality for individuals is discussed, and implications for the determinants of mortality at the community level inferred. Measures of income inequality are likely to be related to mortality on aggregate data because of the non-linearity of income effects. An international cross-section analysis is then undertaken in which different measures of income and income distribution are investigated as determinants of mortality, with life expectancy at birth and age five, and infant mortality taken as measures of the dependent variable. It is found that income distribution is consistently and strongly related to mortality; in a relatively inegalitarian country life expectancy may be between five and ten years lower than in a more egalitarian country.     

Diverging Trends in Female Old‐Age Mortality: The United States and the Netherlands versus France and Japan

In the most advanced countries, child mortality and adult mortality under age 65 years have fallen so low that further improvement in life expectancy relies almost completely on the decline of mortality at older ages. This phenomenon is particularly pronounced among women, who are far ahead of men in survival rates. Thus, to project the future of life expectancy, this study focuses on trends in female life expectancy at ages 65 and older. Four countries are selected for this analysis: the United States, Netherlands, France, and Japan. It is particularly interesting to understand why American and Dutch trends in female old‐age mortality have been diverging from those in France and Japan for two decades. It is shown here that most of the divergence derives from the fact that decline in cardiovascular mortality is more and more offset by increases in other causes of death in the United States and the Netherlands, while the other two countries are more successful in reducing mortality from all causes at increasingly older ages. This latter phenomenon could represent a new stage of the health transition.     

Economic Stress, Quality of Life, and Mortality for the Oldest-Old in China

China??s oldest old population is estimated to quadruple by 2050. Yet, poverty rate for the oldest old has been the highest among all age groups in China. This paper investigates the relationship between economic stress, quality of life, and mortality among the oldest-old in China. Both objective economic hardships and perceived economic strain are examined. We base our investigation on data drawn from the Chinese Longitudinal Healthy Longevity Survey conducted between 2000 and 2005. Our sample includes 10,972 men and women between the ages of 80 and 105 in 2000. The data show that about 16% of these oldest-old lived under economic stress in 2000. The risk factors that make one vulnerable to economic stress include age, being male, being widowed or never married, being a minority member, having no education, having no living children, and not having children as main source of income, and having no pension. Economic stress is negatively associated with indicators of quality of life, such as the quality of medical care and mental well-being. The poor quality of life contributes to the higher mortality rate for the oldest old who are under economic stress. Results also show that perceived economic strain increases the risk of mortality by 42% in rural areas, even after controlling for basic demographic characteristics, life style factors, and major health events.?For the rural oldest-old, having children as a main source of income and having access to pension alleviates the negative impact of economic hardship on mortality hazard by 23 and 66% respectively. However, in urban areas, economic stress has no direct impact on the hazard of mortality.     

Living Arrangements and Quality of Life Among Chinese Canadian Elders

This paper examines the role of living arrangements in thequality of life of community-dwelling Chinese elders (aged 65 andover) currently residing in Vancouver and Victoria, BritishColumbia. Data are based on a random sample of 830 persons[response rate = 71.5%], who were interviewed in their homes inthe language of their choice in 1995–96. Three dimensions ofquality of life – satisfaction, well-being and social support –are examined for married men and women [living with spouse alonevs. living intergenerationally] and widowed women [living alonevs. living intergenerationally]. Few differences are found formarried persons, especially women; for widows, living alonesignificantly reduces quality of life in a number of areas.Regression analyses indicate that living arrangements are not asignificant predictor of life satisfaction or well-being formarried men and women. For widows, living arrangements determinewell-being but not life satisfaction.Overall, age, health status, and social support (havingfriends/confidante) are better predictors of quality of life forelderly Chinese Canadians than are living arrangements. Findingshighlight the importance of: empirically distinguishing maritalstatus and living arrangements in studying the quality of life ofelders; not homogenizing Chinese Canadian seniors with regard toliving arrangements; and focussing on Chinese elderly widows wholive alone as a group at risk of low well-being.