Bruce P. Kennedy

Social capital, income inequality, and mortality.

OBJECTIVES Recent studies have demonstrated that income inequality is related to mortality rates. It was hypothesized, in this study, that income inequality is related to reduction in social cohesion and that disinvestment in social capital is in turn associated with increased mortality. METHODS In this cross-sectional ecologic study based on data from 39 states, social capital was measured by weighted responses to two items from the General Social Survey: per capita density of membership in voluntary groups in each state and level of social trust, as gauged by the proportion of residents in each state who believed that people could be trusted. Age-standardized total and cause-specific mortality rates in 1990 were obtained for each state. RESULTS Income inequality was strongly correlated with both per capita group membership (r = -.46) and lack of social trust (r = .76). In turn, both social trust and group membership were associated with total mortality, as well as rates of death from coronary heart disease, malignant neoplasms, and infant mortality. CONCLUSIONS These data support the notion that income inequality leads to increased mortality via disinvestment in social capital.

Income distribution and mortality : cross sectional ecological study of the Robin Hood index in the United States

Abstract Objective: To determine the effect of income inequality as measured by the Robin Hood index and the Gini coefficient on all cause and cause specific mortality in the United States. Design: Cross sectional ecological study. Setting: Households in the United States. Main outcome measures: Disease specific mortality, income, household size, poverty, and smoking rates for each state. Results: The Robin Hood index was positively correlated with total mortality adjusted for age (r=0.54; P<0.05). This association remained after adjustment for poverty (P<0.007), where each percentage increase in the index was associated with an increase in the total mortality of 21.68 deaths per 100000. Effects of the index were also found for infant mortality (P=0.013); coronary heart disease (P=0.004); malignant neoplasms (P=0.023); and homicide (P<0.001). Strong associations were also found between the index and causes of death amenable to medical intervention. The Gini coefficient showed very little correlation with any of the causes of death. Conclusion: Variations between states in the inequality of income were associated with increased mortality from several causes. The size of the gap between the wealthy and less well off—as distinct from the absolute standard of living enjoyed by the poor—seems to matter in its own right. The findings suggest that policies that deal with the growing inequities in income distribution may have an important impact on the health of the population. Key messages The size of the gap between the wealthy and less well off—as distinct from the absolute standard of living enjoyed by the poor—seems to be related to mortality Policies that deal with the growing inequities in income distribution may have a considerable impact on the health of the population

Social capital: a guide to its measurement

The primary aims of this paper are to review the concept of social capital and related constructs and to provide a brief guide to their operationalization and measurement. We focus on four existing constructs: collective efficacy, psychological sense of community, neighborhood cohesion and community competence. Each of these constructs taps into slightly different, yet overlapping, aspects of social capital. The existence of several instruments to measure each of these constructs calls for further study into their use as measures of social capital. Despite differences in the approach to measurement, there is general agreement that community characteristics, such as social capital, should be distinguished from individual characteristics and measured at the community level.

Health and social cohesion: why care about income inequality?

Abstract Throughout the world, wealth and income are becoming more concentrated. Growing evidence suggests that the distribution of income–in addition to the absolute standard of living enjoyed by the poor–is a key determinant of population health. A large gap between rich people and poor people leads to higher mortality through the breakdown of social cohesion. The recent surge in income inequality in many countries has been accompanied by a marked increase in the residential concentration of poverty and affluence. Residential segregation diminishes the opportunities for social cohesion. Income inequality has spillover effects on society at large, including increased rates of crime and violence, impeded productivity and economic growth, and the impaired functioning of representative democracy. The extent of inequality in society is often a consequence of explicit policies and public choice. Reducing income inequality offers the prospect of greater social cohesiveness and better population health.

Income distribution, socioeconomic status, and self rated health in the United States: multilevel analysis

Abstract Objective: To determine the effect of inequalities in income within a state on self rated health status while controlling for individual characteristics such as socioeconomic status. Design: Cross sectional multilevel study. Data were collected on income distribution in each of the 50 states in the United States. The Gini coefficient was used to measure statewide inequalities in income. Random probability samples of individuals in each state were collected by the 1993 and 1994 behavioural risk factor surveillance system, a random digit telephone survey. The survey collects information on an individuals income, education, self rated health and other health risk factors. Setting: All 50 states. Subjects: Civilian, non-institutionalised (that is, non-incarcerated and non-hospitalised) US residents aged 18 years or older. Main outcome measure: Self rated health status. Results: When personal characteristics and household income were controlled for, individuals living in states with the greatest inequalities in income were 30% more likely to report their health as fair or poor than individuals living in states with the smallest inequalities in income. Conclusions: Inequality in the distribution of income was associated with an adverse impact on health independent of the effect of household income.

The relationship of income inequality to mortality: Does the choice of indicator matter?

Ecologic studies in the U.S. and elsewhere in the world have demonstrated that income inequality is strongly related to mortality and life expectancy: the greater the dispersion of income within a given society, the lower the life expectancy. However, these empirical studies have been criticized on the grounds that the choice of indicator may have influenced positive findings. Using a cross-sectional, ecologic design, we tested the relationships of six different income inequality indicators to total mortality rates in the 50 U.S. states. The following summary measures of income distribution were examined: the Gini coefficient; the decile ratio; the proportions of total income earned by the bottom 50%, 60%, and 70% of households; the Robin Hood Index; the Atkinson Index; and Theils entropy measure. All were highly correlated with each other (Pearson r > or = 0.94), and all were strongly associated with mortality (Pearson r ranging from 0.50 to 0.66), even after adjustment for median income and poverty. Thus, the choice of income distribution measure does not appear to alter the conclusion that income inequality is linked to higher mortality. Furthermore, adjustment for taxes and transfers, as well as household size (using equivalence scales), made no difference to the income inequality/mortality association. From a policy perspective, the alternative income distribution measures perform differently under varying types of income transfers, so that theoretical considerations should guide the selection of an indicator to assess the impact of social and economic policies that address income inequality.

State income inequality, household income, and maternal mental and physical health: cross sectional national survey.

Abstract Objective: To examine the association of state income inequality and individual household income with the mental and physical health of women with young children. Design: Cross sectional study. Individual level data (outcomes, income, and other sociodemographic covariates) from a 1991 follow up survey of a birth cohort established in 1988. State level income inequality calculated from the income distribution of each state from 1990 US census. Setting: United States, 1991. Participants: Nationally representative stratified random sample of 8060 women who gave birth in 1988 and were successfully contacted (89%) in 1991. Main outcome measures: Depressive symptoms (Center for Epidemiologic Studies depression score >15) and self rated health Results: 19% of women reported depressive symptoms, and 7.5% reported fair or poor health. Compared with women in the highest fifth of distribution of household income, women in the lowest fifth were more likely to report depressive symptoms (33% v 9%, P<0.001) and fair or poor health (15% v 2%, P<0.001). Compared with low income women in states with low income inequality, low income women in states with high income inequality had a higher risk of depressive symptoms (odds ratio 1.6, 95% confidence interval 1.0 to 2.6) and fair or poor health (1.8, 0.9 to 3.5). Conclusions: High income inequality confers an increased risk of poor mental and physical health, particularly among the poorest women. Both income inequality and household income are important for health in this population.

Mortality, the Social Environment, Crime and Violence

Starting out from the relationship between income equality and indicators of social cohesion and social trust, this paper explores the social processes which might account for the relationship between greater income equality and lower population mortality rates. We note that: homicide shows an even closer relationship to income inequality than does mortality from all other causes combined; there are several reports that homicide rates are particularly closely related to all cause mortality; and that there is a growing body of research on crime in relation to social disorganisation. We use US state level data to examine the relationships between various categories of income inequality, median state income, social trust and mortality. The data suggest that violent crime, but not property crime, is closely related to income inequality, social trust and mortality rates, excluding homicide. The second half of the paper is devoted to literature on the antecedents of violence. Feeling shamed, humiliated and disrespected seem to be central to the picture and are plausibly related to the way in which wider income differences are likely to mean more people are denied access to traditional sources of status and respect. We suggest that these aspects of low social status may be central to the psychosocial processes linking inequality, violence, social cohesion and mortality.

The role of social capital in the Russian mortality crisis

Abstract Emerging evidence suggests that the degree of social cohesion is an important determinant of population health status. Citizens living in societies with a high degree of social cohesion — characterized by strong social networks and high levels of interpersonal trust — seem to be healthier than those living in socially disorganized societies. Epidemiologists have become interested in notions of civil society and social capital to explain variations in health across societies. The purpose of the present paper was to examine the role of social capital in the Russian mortality crisis. Social capital has been defined as those features of social organization — such as the density of civic associations, levels of interpersonal trust, and norms of reciprocity — that act as resources for individuals, and facilitate collective action. A civil society is one that is rich in stocks of social capital. Various scholars have argued that one of the distinguishing characteristics of the Soviet regime was the paucity of civil society. Using household survey data from the Ail-Russian Center for Public Opinion research (VTsIOM), we carried out a cross-sectional, ecologie analysis of the association between indicators of social capital and mortality rates across 40 regions of Russia. We found associations between indicators of social capital (mistrust in government, crime, quality of work relations, civic engagement in politics) and life expectancy, as well as mortality rates. In the absence of civil society, it is believed that far more people in post-Soviet Russia rely on informal sources of support (friends, family) to deal with their day to day problems. Those lacking such sources of support may have been especially vulnerable to the economic hardships following the transformation to a market economy.

Women's status and the health of women and men: a view from the States

We examined the status of women in the 50 American states in relation to womens and mens levels of health. The status of women in each state was assessed by four composite indices measuring womens political participation, economic autonomy, employment and earnings, and reproductive rights. The study design was cross-sectional and ecologic. Our main outcome measures were total female and male mortality rates, female cause-specific death rates and mean days of activity limitations reported by women during the previous month. Measures of womens status were strikingly correlated with each of these health outcomes at the state level. Higher political participation by women was correlated with lower female mortality rates (r = -0.51), as well as lower activity limitations (-0.47). A smaller wage gap between women and men was associated with lower female mortality rates (-0.30) and lower activity limitations (-0.31) (all correlations, P < 0.05). Indices of womens status were also strongly correlated with male mortality rates, suggesting that womens status may reflect more general underlying structural processes associated with material deprivation and income inequality. However, the indices of womens status persisted in predicting female mortality and morbidity rates after adjusting for income inequality, poverty rates and median household income. Associations were observed for specific causes of death, including stroke, cervical cancer and homicide. We conclude that women experience higher mortality and morbidity in states where they have lower levels of political participation and economic autonomy. Living in such states has detrimental consequences for the health of men as well. Gender inequality and truncated opportunities for women may be one of the pathways by which the maldistribution of income adversely affects the health of women.