Relation between income inequality and mortality: empirical demonstration

Objective To assess the extent to which observed associations between income inequality and mortality at population level are statistical artifacts. Design Indirect "what if" simulation using observed risks of mortality at individual level as a function of income to construct hypothetical state-level mortality specific for age and sex as if the statistical artifact argument were 100% correct. Method Data from the 1990 census for the 50 US states plus Washington, DC, were used for population distributions by age, sex, state, and income range; data disaggregated by age, sex, and state from the Centers for Disease Control and Prevention were used for mortality; and regressions from the national longitudinal mortality study were used for the individual-level relation between income and risk of mortality. Results Hypothetical mortality, although correlated with inequality (as implied by the logic of the statistical artifact argument), showed a weaker association with the level of income inequality in each state than the observed mortality. Conclusions The observed associations in the United States at the state level between income inequality and mortality cannot be entirely or substantially explained as statistical artifacts of an underlying individual-level relation between income and mortality. There remains an important association between income inequality and mortality at state level above anything that could be accounted for by any statistical artifact. This result reinforces the need to consider a broad range of factors, including the social milieu, as fundamental determinants of health.     

Relations of income inequality and family income to chronic medical conditions and mental health disorders: national survey

ObjectivesTo analyse the relation between geographical inequalities in income and the prevalence of common chronic medical conditions and mental health disorders, and to compare it with the relation between family income and these health problems.Design Nationally representative household telephone survey conducted in 1997-8.Setting 60 metropolitan areas or economic areas of the United States.Participants 9585 adults who participated in the community tracking study.Results A strong continuous association was seen between health and education or family income. No relation was found between income inequality and the prevalence of chronic medical problems or depressive disorders and anxiety disorders, either across the whole population or among poorer people. Only self reported overall health, the measure used in previous studies, was significantly correlated with inequality at the population level, but this correlation disappeared after adjustment for individual characteristics.Conclusions This study provides no evidence for the hypothesis that income inequality is a major risk factor for common disorders of physical or mental health.

What is already known on this topic

Several studies have found a relation between income inequality and self reported health or mortality

What this study adds

There is a strong social gradient in health, as measured by the prevalence of chronic medical conditions and specific mental health disorders, by income or educationNo such association is seen between income inequality and health     

Income inequality and depression: a systematic review and meta‐analysis of the association and a scoping review of mechanisms

Most countries have witnessed a dramatic increase of income inequality in the past three decades. This paper addresses the question of whether income inequality is associated with the population prevalence of depression and, if so, the potential mechanisms and pathways which may explain this association. Our systematic review included 26 studies, mostly from high‐income countries. Nearly two‐thirds of all studies and five out of six longitudinal studies reported a statistically significant positive relationship between income inequality and risk of depression; only one study reported a statistically significant negative relationship. Twelve studies were included in a meta‐analysis with dichotomized inequality groupings. The pooled risk ratio was 1.19 (95% CI: 1.07‐1.31), demonstrating greater risk of depression in populations with higher income inequality relative to populations with lower inequality. Multiple studies reported subgroup effects, including greater impacts of income inequality among women and low‐income populations. We propose an ecological framework, with mechanisms operating at the national level (the neo‐material hypothesis), neighbourhood level (the social capital and the social comparison hypotheses) and individual level (psychological stress and social defeat hypotheses) to explain this association. We conclude that policy makers should actively promote actions to reduce income inequality, such as progressive taxation policies and a basic universal income. Mental health professionals should champion such policies, as well as promote the delivery of interventions which target the pathways and proximal determinants, such as building life skills in adolescents and provision of psychological therapies and packages of care with demonstrated effectiveness for settings of poverty and high income inequality.     

The global impact of income inequality on health by age: an observational study

Objectives To explore whether the apparent impact of income inequality on health, which has been shown for wealthier nations, is replicated worldwide, and whether the impact varies by age.Design Observational study. Setting 126 countries of the world for which complete data on income inequality and mortality by age and sex were available around the year 2002 (including 94.4% of world human population).Data sources Data on mortality were from the World Health Organization and income data were taken from the annual reports of the United Nations Development Programme.Main outcome measures Mortality in 5-year age bands for each sex by income inequality and income level.Results At ages 15-29 and 25-39 variations in income inequality seem more closely correlated with mortality worldwide than do variations in material wealth. This relation is especially strong among the poorest countries in Africa. Mortality is higher for a given level of overall income in more unequal nations.Conclusions Income inequality seems to have an influence worldwide, especially for younger adults. Social inequality seems to have a universal negative impact on health.     

Inequality in income and mortality in the United States: analysis of mortality and potential pathways.

OBJECTIVE--To examine the relation between health outcomes and the equality with which income is distributed in the United States. DESIGN--The degree of income inequality, defined as the percentage of total household income received by the less well off 50% of households, and changes in income inequality were calculated for the 50 states in 1980 and 1990. These measures were then examined in relation to all cause mortality adjusted for age for each state, age specific deaths, changes in mortalities, and other health outcomes and potential pathways for 1980, 1990, and 1989-91. MAIN OUTCOME MEASURE--Age adjusted mortality from all causes. RESULTS--There was a significant correlation (r = -0.62 [corrected], P < 0.001) between the percentage of total household income received by the less well off 50% in each state and all cause mortality, unaffected by adjustment for state median incomes. Income inequality was also significantly associated with age specific mortalities and rates of low birth weight, homicide, violent crime, work disability, expenditures on medical care and police protection, smoking, and sedentary activity. Rates of unemployment, imprisonment, recipients of income assistance and food stamps, lack of medical insurance, and educational outcomes were also worse as income inequality increased. Income inequality was also associated with mortality trends, and there was a suggestion of an impact of inequality trends on mortality trends. CONCLUSION--Variations between states in the inequality of the distribution of income are significantly associated with variations between states in a large number of health outcomes and social indicators and with mortality trends. These differences parallel relative investments in human and social capital. Economic policies that influence income and wealth inequality may have an important impact on the health of countries.     

Poverty or income inequality as predictor of mortality: longitudinal cohort study.

OBJECTIVE: To determine the effect of inequality in income between communities independent of household income on individual all cause mortality in the United States. DESIGN: Longitudinal cohort study. SUBJECTS: A nationally representative sample of 14,407 people aged 25-74 years in the United States from the first national health and nutrition examination survey. SETTING: Subjects were followed from initial interview in 1971-5 until 1987. Complete follow up information was available for 92.2% of the sample. MAIN OUTCOME MEASURES: Relation between both household income and income inequality in community of residence and individual all cause mortality at follow up was examined with Cox proportional hazards survival analysis. RESULTS: Community income inequality showed a significant association with subsequent community mortality, and with individual mortality after adjustment for age, sex, and mean income in the community of residence. After adjustment for individual household income, however, the association with mortality was lost. CONCLUSIONS: In this nationally representative American sample, family income, but not community income inequality, independently predicts mortality. Previously reported ecological associations between income inequality and mortality may reflect confounding between individual family income and mortality.     

Two pathways, but how much do they diverge?

This document presents an argument on how low income differences are associated to the well being of the population. The health of the population was said to be related to either narrow differences in individual income or the greater effect of social disparity. The reality of the health benefits or the central policy implications could not be modified by the pathway. An experiment conducted on monkeys revealed that low status is a risk factor for poor health in a plausible psychosocial pathway. The income of the individual can be considered as one of the marker for social status and inequality in the society can be caused by material risk factors. Inequality effect of the small proportion of the population may be too great when explained using a curvature. Also, the income and health status in the developed countries is closely related and would still fall on the better part of the international curve. A less democratic society may develop an aggressive and less supportive social environment could cause deprivation and low social status. An increase in health inequalities was driven by a more socially antagonistic, delinquent and risky forms of behavior accompanied by deprivation throughout the society. The reduction of health inequalities associated between the pathways of income inequality and population health must not differ with the aim of improving health standards in the society. As a result, redistribution of health services could probably increase the health of those who are in need.     

Health and social cohesion: why care about income inequality?

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

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 100,000. 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.     

Social capital externalities and mortality in Sweden

We conceptualize social capital as an aggregate factor affecting health production and analyze the effect of community social capital (CSC) externalities on individual mortality risk in Sweden. The study was based on a random sample from the adult Swedish population of approximately 95,000 individuals who were followed up for 4-21 years. Two municipality-level variable--registered election participation rate and registered crime rate--were used to be a proxy for CSC. The impact of CSC on mortality was estimated with an extended Cox model, controlling for the initial health status and a number of individual characteristics. The results indicate that both proxies of CSC were associated with individual risk from all-cause mortality for males older than 65+ (p=0.013 and p=0.008) but not for females. A higher election participation rate negatively and significantly associated with the mortality risk from cancer for males (p=0.007), and may also have exerted protective associations for cardiovascular mortality (p=0.134) and deaths due to "suicide" (p=0.186) or "other external causes" (p=0.055). Similar associations were observed for the crime rate variable. The findings were robust to alternative specifications examined in the sensitivity analysis.     

The Link between Inequality and Population Health in Low and Middle Income Countries: Policy Myth or Social Reality?

An influential policy idea states that reducing inequality is beneficial for improving health in the low and middle income countries (LMICs). Our study provides an empirical test of this idea: we utilized data collected by the Demographic and Health Surveys between 2000 and 2011 in as much as 52 LMICs, and we examined the relationship between household wealth inequality and two health outcomes: anemia status (of the children and their mothers) and the women'' experience of child mortality. Based on multi-level analyses, we found that higher levels of household wealth inequality related to worse health, but this effect was strongly reduced when we took into account the level of individuals'' wealth. However, even after accounting for the differences between individuals in terms of household wealth and other characteristics, in those LMICs with higher household wealth inequality more women experienced child mortality and more children were tested with anemia. This effect was partially mediated by the country''s level and coverage of the health services and infrastructure. Furthermore, we found higher inequality to be related to a larger health gap between the poor and the rich in only one of the three examined samples. We conclude that an effective way to improve the health in the LMICs is to increase the wealth among the poor, which in turn also would lead to lower overall inequality and potential investments in public health infrastructure and services.     

An information theory based framework for the measurement of population health

This paper proposes a new framework for the measurement of population health and the ranking of the health of different geographies. Since population health is a latent variable, studies which measure and rank the health of different geographies must aggregate observable health attributes into one summary measure. We show that the methods used in nearly all the literature to date implicitly assume that all attributes are infinitely substitutable. Our method, based on the measurement of multidimensional welfare and inequality, minimizes the entropic distance between the summary measure of population health and the distribution of the underlying attributes. This summary function coincides with the constant elasticity of substitution and Cobb–Douglas production functions and naturally allows different assumptions regarding attribute substitutability or complementarity. To compare methodologies, we examine a well-known ranking of the population health of U.S. states, America's Health Rankings. We find that states’ rankings are somewhat sensitive to changes in the weight given to each attribute, but very sensitive to changes in aggregation methodology. Our results have broad implications for well-known health rankings such as the 2000 World Health Report, as well as other measurements of population and individual health levels and the measurement and decomposition of health inequality.     

On the incompatibility of gompertz or weibull survival dynamics with exponentially distributed individual lifespans

It is well documented, in the biological literature, that many species throughout the animal kingdom exhibit Gompertzian or Weibull-like population level total survival distributions. Many researchers have long assumed, believed, or otherwise postulated that an individual organism, in such a population, survived according to an exponential survival distribution. Using well-known results from reliability theory, it is shown that if every individual in the population has an exponentially distributed lifespan, then a Gompertzian or Weibull-like group/population level dynamics (or any other dynamics with a strictly increasing mortality rate for some interval) is not possible. This implies that, for species with a population level Gompertzian or Weibull (with the mortality rate strictly increasing) survival curve, some or all of the individual organisms must have non-exponentially distributed lifespans.     

Differential adult survival at close seabird colonies: The importance of spatial foraging segregation and bycatch risk during the breeding season

Marine megafauna, including seabirds, are critically affected by fisheries bycatch. However, bycatch risk may differ on temporal and spatial scales due to the uneven distribution and effort of fleets operating different fishing gear, and to focal species distribution and foraging behavior. Scopoli's shearwater Calonectris diomedea is a long‐lived seabird that experiences high bycatch rates in longline fisheries and strong population‐level impacts due to this type of anthropogenic mortality. Analyzing a long‐term dataset on individual monitoring, we compared adult survival (by means of multi‐event capture–recapture models) among three close predator‐free Mediterranean colonies of the species. Unexpectedly for a long‐lived organism, adult survival varied among colonies. We explored potential causes of this differential survival by (1) measuring egg volume as a proxy of food availability and parental condition; (2) building a specific longline bycatch risk map for the species; and (3) assessing the distribution patterns of breeding birds from the three study colonies via GPS tracking. Egg volume was very similar between colonies over time, suggesting that environmental variability related to habitat foraging suitability was not the main cause of differential survival. On the other hand, differences in foraging movements among individuals from the three colonies expose them to differential mortality risk, which likely influenced the observed differences in adult survival. The overlap of information obtained by the generation of specific bycatch risk maps, the quantification of population demographic parameters, and the foraging spatial analysis should inform managers about differential sensitivity to the anthropogenic impact at mesoscale level and guide decisions depending on the spatial configuration of local populations. The approach would apply and should be considered in any species where foraging distribution is colony‐specific and mortality risk varies spatially.     

Inequalities in income and long-term disability in Spain: analysis of recent hypotheses using cross sectional study based on individual data.

OBJECTIVE: To compare the relation between inequalities in long-term disability and income in the 17 regions of Spain. DESIGN: Data were taken from the survey on impairments, disabilities, and handicaps that was carried out in Spain in 1986. For each region the inequality in long-term disability associated with income was calculated as the odds ratio associated with reducing monthly household income by 10,000 pesetas (about Ponds 50) (estimate of effect of inequality of income) and the odds ratio for the inequality in long-term disability between those at the bottom and those at the top of the income hierarchy (relative index of inequality). MAIN OUTCOME MEASURE: Prevalence of long-term disability. RESULTS: Five of the eight regions where lowering income had a greater effect on long-term disability were among those with the lowest income per head, while six of the remaining nine regions where the effect was smaller were among those with the highest income per head. Three regions with the highest estimate of relative index of inequality had the highest estimate of effect, and another three regions with the lowest estimate of relative index of inequality had the lowest estimate of effect. In contrast, the relative position of the remaining 11 regions varied from one measure to another. CONCLUSIONS: These results support the theory that additional increments in material wellbeing have a negligible effect on health in countries with high socioeconomic development. However, inequality in income distribution did not determine inequality in health between those at the bottom and those at the top of the income hierarchy in many Spanish regions.     

Quantifying neighbourhood socioeconomic effects in clustering of behaviour-related risk factors: a multilevel analysis

Background

The extent to which neighbourhood characteristics explain accumulation of health behaviours is poorly understood. We examined whether neighbourhood disadvantage was associated with co-occurrence of behaviour-related risk factors, and how much of the neighbourhood differences in the co-occurrence can be explained by individual and neighbourhood level covariates.

Methods

The study population consisted of 60 694 Finnish Public Sector Study participants in 2004 and 2008. Neighbourhood disadvantage was determined using small-area level information on household income, education attainment, and unemployment rate, and linked with individual data using Global Positioning System-coordinates. Associations between neighbourhood disadvantage and co-occurrence of three behaviour-related risk factors (smoking, heavy alcohol use, and physical inactivity), and the extent to which individual and neighbourhood level covariates explain neighbourhood differences in co-occurrence of risk factors were determined with multilevel cumulative logistic regression.

Results

After adjusting for age, sex, marital status, and population density we found a dose-response relationship between neighbourhood disadvantage and co-occurrence of risk factors within each level of individual socioeconomic status. The cumulative odds ratios for the sum of health risks comparing the most to the least disadvantaged neighbourhoods ranged between 1.13 (95% confidence interval (CI): 1.03–1.24) and 1.75 (95% CI, 1.54–1.98). Individual socioeconomic characteristics explained 35%, and neighbourhood disadvantage and population density 17% of the neighbourhood differences in the co-occurrence of risk factors.

Conclusions

Co-occurrence of poor health behaviours associated with neighbourhood disadvantage over and above individual''s own socioeconomic status. Neighbourhood differences cannot be captured using individual socioeconomic factors alone, but neighbourhood level characteristics should also be considered.     

Economic inequality predicts biodiversity loss

Human activity is causing high rates of biodiversity loss. Yet, surprisingly little is known about the extent to which socioeconomic factors exacerbate or ameliorate our impacts on biological diversity. One such factor, economic inequality, has been shown to affect public health, and has been linked to environmental problems in general. We tested how strongly economic inequality is related to biodiversity loss in particular. We found that among countries, and among US states, the number of species that are threatened or declining increases substantially with the Gini ratio of income inequality. At both levels of analysis, the connection between income inequality and biodiversity loss persists after controlling for biophysical conditions, human population size, and per capita GDP or income. Future research should explore potential mechanisms behind this equality-biodiversity relationship. Our results suggest that economic reforms would go hand in hand with, if not serving as a prerequisite for, effective conservation.     

Social-economic inequality in mortality among older mem amd women. Research on the role of health, life style, parental socio-economic status and psychosocial conditions

This article describes to what degree socio-economic differences exist among community living older men and women, and to what degree these differences are to be explained by health, behaviour, childhood and psychosocial conditions. The data are available from 1427 men and 1503 women (aged 55-85), participating in the Longitudinal Aging Study Amsterdam (LASA) in 1992/1993. As indicators of socio-economic status (ses) we used the highest level of education and net monthly income. Age-adjusted mortality risks for men and women with low income and for men with a low level of education are about 1.5 times as high as for to the persons with high income and educational level. Among men, but not among women, the difference in mortality risk between low and high status persons remains after adjustment for age, health status, and several risk factors. Differences in lifestyle, parental ses and psychosocial characteristics explain little to nothing of the age-adjusted ses-differentiation in mortality. It is concluded that ses-inequalities in mortality are present among Dutch men and, to a lesser extent among women, until high age, and are partly explained by the relatively large health problems of the lower status group.     

Health and income inequalities in Europe: What is the role of circumstances?

Equality of opportunity theories distinguish between inequalities due to individual effort and those due to external circumstances. Recent research has shown that half of the variability in income of World population was determined by country of birth and income distribution. Since health and income are generally strictly related, the aim of this paper is to estimate how much variability in income and health is determined by external circumstances. We use data from the Survey of Health, Ageing and Retirement (SHARE) and the English Longitudinal Survey on Ageing (ELSA), two comparable multidisciplinary surveys that provide micro-level data on health and financial resources among the elderly for a large number of European countries. Our baseline estimation shows that about 20% of the variability in income is explained by current country-specific circumstances, while health outcomes range from 12% using BMI to 19% using self-rated health. By including early-life circumstances, the explained variability increases almost 20 percentage points for income and for self-rated health but less for other health outcomes. Finally, by controlling for endogeneity issues linked with effort, our estimates indicate that circumstances better explain variability in health outcomes. Results are robust to some tests, and the implications of these findings are discussed.     

Inequality in Japan (1892–1941): Physical stature, income, and health

This paper investigates the relationship between physical stature, per capita income, health, and regional inequality in Japan at the prefecture-level for the period 1892-1941. The analysis shows that inequality in income and access to health services explains differences in average height of the population across the 47 Japanese prefectures during this period and that variation in income contributed to changes in height during the 1930s. Annual regional time series of height indicate that Japan experienced a regional convergence in biological welfare before 1914, and that a divergence occurred during the interwar period; personal inequality followed a similar pattern.