摘要：Objectives. We examined the effects of market income inequality (income inequality before taxes and transfers) and income redistribution via taxes and transfers on inequality in longevity. Methods. We used life tables to compute Gini coefficients of longevity inequality for all individuals and for individuals who survived to at least 10 years of age. We regressed longevity inequality on market income inequality and income redistribution, and we controlled for potential confounders, in a cross-sectional time-series sample of up to 28 predominantly Western developed countries and up to 37 years (1974–2011). Results. Income inequality before taxes and transfers was positively associated with inequality in the number of years lived; income redistribution (the difference between market income inequality and income inequality after taxes and transfers were accounted for) was negatively associated with longevity inequality. Conclusions. To the extent that our estimated effects derived from observational data are causal, governments can reduce longevity inequality not only via public health policies, but also via their influence on market income inequality and the redistribution of incomes from the relatively rich to the relatively poor. Public policies affect not only health and mortality at the individual level, but also the inequality of longevity—inequality in the number of years lived. For example, higher tobacco 1 and alcohol 2 taxes reduce consumption, as do nonfiscal regulatory measures such as restrictions on smoking in closed spaces. This reduces avoidable mortality from lung cancer and liver cirrhosis. More directly, governments implement health and safety regulations, influence total health spending and its allocation, and regulate the coverage of health insurance across individuals. All factors that reduce premature deaths also reduce longevity inequality. Although these pathways are generally well understood, another mechanism surprisingly has no cross-country evidence: the influence of income inequality and income redistribution on lifetime inequality. Low income has multiple direct and indirect negative consequences for individual health. 3–5 This does not necessarily imply that greater income inequality leads to greater inequality in health outcomes at the population level. However, greater income inequality is typically associated with a higher prevalence of poverty. A higher prevalence of poverty, all other things being equal, increases the number of premature deaths and therefore leads to greater longevity inequality. 6 Poverty is, for example, linked to unhealthy diets and lack of physical activity, thus contributing to the emergence of diabetes and cardiovascular diseases such as coronary heart disease and strokes, as well as increased alcohol and tobacco consumption, which contributes to lung cancer, diseases of the liver, and many other diseases. 5 Poor people enjoy fewer opportunities for recreational activities and report higher levels of stress and mental health problems, which reduce the capacity to cope with life’s adversities. 7 Poverty also diminishes individual investment in education, which has been shown to be an important predictor of subsequent mortality. 8 Greater income inequality, however, need not represent a higher prevalence of poverty, but could instead reflect a higher concentration of incomes at the top of the income distribution at the expense of the share held by individuals in the middle. It is therefore important not to equate the effect of income inequality on longevity inequality with the effect of poverty on longevity inequality. Income inequality affects inequality in longevity through societal effects that go well beyond any potential direct impacts on individuals’ behavior as a function of their low disposable personal income. 9 In some countries, high income inequality tends to result in the spatial segregation of rich and poor. Poor communities and neighborhoods have lower levels of social cohesion, support, and capital; receive lower-quality public services; and experience higher rates of crime, social disorder, and violence, with potentially negative health consequences. 10,11 Economic inequality also affects political decision-making. Poor people are less likely to vote and have little influence on political decisions, whereas the very rich can exercise a strong influence via lobbying and donations. More economically unequal societies will thus be characterized by more unequal access to political decision-making. 12,13 This in turn creates political incentives to skew policies toward benefiting the relatively rich at the expense of the relatively poor, for example, by lower government investment in goods such as publicly funded education or recreational and health care facilities that benefit people independently of their personal income. In ongoing research, we model a specific pathway through which greater income inequality affects longevity inequality via a lower share of public-to-total health expenditures at the country level. The poor are dependent on public health expenditures because they cannot afford substantial investments in private health care, unlike the rich, who can buy better health care privately. Though research has occasionally tested the theory that redistributive policies and longevity inequality are associated at the country level, 14 we were the first to empirically study the relationship between market inequality and redistributive government policies on inequality in longevity, in a pooled analysis of up to 22 Western developed countries plus the Czech Republic, Estonia, Israel, Poland, the Slovak Republic, and Slovenia over up to 37 years (with considerably fewer years for some, particularly the non-Western, countries). We used the Gini coefficient as our preferred measure of inequality, but different inequality measures that capture the entire distribution tend to produce similar results in the analysis of longevity. 15 The Gini coefficient is the most popular measure of inequality in the social sciences. It describes how far the Lorenz curve deviates from the line of perfect equality. The Lorenz curve is a cumulative distribution function. It sorts all individuals according to the dimension in which inequality is measured (age at deaths in our case; Figure 1 ). Accordingly, in our context individuals are sorted from those who died at birth on the left to those who lived to the age of 110 years on the right. The Lorenz curve depicts the proportion of the total time lived by the bottom deciles of the entire cohort. Logically, all individuals together lived 100% of all the years. If, hypothetically, every individual reached exactly the same age, then the lowest 10% of the population would live 10% of all years lived, 20% of the individuals would live 20% of all years lived, and so on. The function of perfect equality is represented by the straight line from the origin to the upper right corner. If only 1 individual survived birth, then one would get total inequality. All individuals except 1 would live 0% of the total time, and the last individual would live 100% of the total time lived. Open in a separate window FIGURE 1— The Gini Coefficient of Longevity Inequality in the United States: 2010 Figure 1 plots an actual Lorenz curve based on actual US longevity data for 2010. The further away the Lorenz curve is from the diagonal, the larger the inequality in the data. The Gini coefficient measures the area between the Lorenz curve and the line of perfect equality (the light gray area) as a proportion of the total area below the line of equality in the quadrant. As Figure 1 shows, longevity is relatively equally distributed. Not surprisingly, in light of natural constraints on the number of years anyone can live, longevity is more equally distributed than incomes. Because infant mortality has a relatively strong effect on longevity inequality, most demographers analyze not the entire range of life tables, but typically left-truncated ones of those who have survived beyond the age of 5, 10, or 15 years. 16,17 We report analyses of Gini coefficients over both the entire life tables (0–110 years) and for those who survived to the age of 10 years (10–110 years) to eliminate the potentially strong influence of child mortality, but our findings also held for other thresholds. Longevity inequality declined in all countries in our sample over the past 2 centuries. This development was paralleled by a large increase in life expectancy. Because of the strong association between these trends, some argue that inequality in longevity should only be analyzed with controls for life expectancy included in the analysis. 15 However, rather than increases in life expectancy causing more equality in longevity, both trends are likely determined by the same factors: the sharp decline in infant mortality and the somewhat less pronounced decline in premature mortality. 14,17 Despite the dramatic decline in longevity inequality over the past 2 centuries, substantial differences in longevity inequality persist across countries. Even for the seemingly similar countries included in our sample, lifetime inequality varied moderately over time and across countries; it varied more over longer periods and larger sets of countries. 16,17 A good example is provided by comparing Sweden, one of the most equal, and the United States, one of the most unequal countries, in 1975 and in 2010. Figures A and B (available as a supplement to the online version of this article at http://www.ajph.org ) plot mortality rates by age for these 2 countries in these 2 years. Both countries experienced significant increases in life expectancy and reductions in longevity inequality. However, the differences between these countries over 35 years were largely stable. The United States lagged behind the development in lifetime inequality in Sweden, reaching Sweden’s level of longevity inequality from 1975 only 35 years later in 2010.
