Has the relation between income inequality and life expectancy disappeared? Evidence from Italy and top industrialised countries

OBJECTIVE: To investigate the relation between income inequality and life expectancy in Italy and across wealthy nations. DESIGN AND SETTING: Measure correlation between income inequality and life expectancy at birth within Italy and across the top 21 wealthy countries. Pearson correlation coefficients were calculated to study these relations. Multivariate linear regression was used to measure the association between income inequality and life expectancy at birth adjusting for per capita income, education, and/or per capita gross domestic product. DATA SOURCES: Data on the Gini coefficient (income inequality), life expectancy at birth, per capita income, and educational attainment for Italy came from the surveys on Italian household on income and wealth 1995-2000 and the National Institute of Statistics information system. Data for industrialised nations were taken from the United Nations Development Program's human development indicators database 2003. RESULTS: In Italy, income inequality (beta = -0.433; p<0.001) and educational attainment (beta = 0.306; p<0.001) were independently associated with life expectancy, but per capita income was not (beta = 0.121; p>0.05). In cross national analyses, income inequality had a strong negative correlation with life expectancy at birth (r = -0.864; p<0.001). CONCLUSIONS: In Italy, a country where health care and education are universally available, and with a strong social safety net, income inequality had an independent and more powerful effect on life expectancy at birth than did per capita income and educational attainment. Italy had a moderately high degree of income inequality and an average life expectancy compared with other wealthy countries. The cross national analyses showed that the relation between income inequality and population health has not disappeared.     

Socioeconomic inequality in voting participation and self-rated health

OBJECTIVES: This study tested the hypothesis that disparities in political participation across socioeconomic status affect health. Specifically, the association of voting inequality at the state level with individual self-rated health was examined. METHODS: A multilevel study of 279,066 respondents to the Current Population Survey (CPS) was conducted. State-level inequality in voting turnout by socioeconomic status (family income and educational attainment) was derived from November CPS data for 1990, 1992, 1994, and 1996. RESULTS: Individuals living in the states with the highest voting inequality had an odds ratio of fair/poor self-rated health of 1.43 (95% confidence interval [CI] = 1.22, 1.68) compared with individuals living in the states with the lowest voting inequality. This odds ratio decreased to 1.34 (95% CI = 1.14, 1.56) when state income inequality was added and to 1.27 (95% CI = 1.10, 1.45) when state median income was included. The deleterious effect of low individual household income on self-rated health was most pronounced among states with the greatest voting and income inequality. CONCLUSIONS: Socioeconomic inequality in political participation (as measured by voter turnout) is associated with poor self-rated health, independently of both income inequality and state median household income.     

"Social capital," GNP per capita, relative income, and health: an ecological study of 23 countries.

The effects of social capital, income inequality, and absolute per capita income were investigated in an ecological analysis of 23 rich and poor countries. Trust was chosen as an indicator of social capital, and GNP (gross national product) per capita and Gini index measured absolute and relative income, respectively. These independent variables were analyzed in a linear regression model with the dependent variables adult mortality rate (25-64 years), life expectancy, and infant mortality rate (IMR). Separate analyses were performed for poor and rich countries as well as all countries combined. Social capital (trust) showed no significant association with the three health outcomes. A particularly strong relationship was found between Gini index and IMR for rich countries, and GNP per capita and life expectancy for all countries. In the group of poor countries, GNP per capita and Gini index in the same model were associated with IMR. The results contradict the suggested impact of social capital on health, and instead support the notion that economic factors such as absolute income and relative income distribution are of importance.     

Different income information as an indicator for health inequality among Japanese adults

BACKGROUND: There are several alternative indicators of income information, which is a fundamental measure of individual socioeconomic position. In this study, we compared the degrees of associations of four types of income information with health variables among Japanese adults. METHODS: Using a nationally representative sample of 29,446 men and 32,917 women aged 20 years and over, the associations between four income indicators and health variables were examined using the odds ratio in logistic regression analysis and the concentration index by sex and age group (20-59 years and 60+ years). Income indicators consisted of total household income, equivalent household income, total household expenditure, and equivalent household expenditure. Current smoking and self-rated health statuses were used as health variables. RESULTS: A low income was associated with a high prevalence of smoking and fair/poor self-rated health, with some differences among sex and age groups and income indicators, but less difference among methods of statistical analyses. Total and equivalent incomes were similarly and more markedly associated with smoking and self-rated health statuses, whereas equivalent expenditure showed the smallest degree of health difference. For the population aged 60+ years, the degree of health differences in smoking was similar between income and expenditure. CONCLUSIONS: Although the degree of income-related health differences is dependent on health outcome and both sex and age group, this study suggests that either crude or equivalent household income is a useful indicator for health inequality among Japanese adults.     

Cross-national comparisons of time trends in overweight inequality by socioeconomic status among women using repeated cross-sectional surveys from 37 developing countries, 1989-2007

Chronic diseases are now among the leading causes of morbidity and mortality in lower income countries. Although traditionally related to higher individual socioeconomic status (SES) in these contexts, the associations between SES and chronic disease may be actively changing. Furthermore, country-level contextual factors, such as economic development and income inequality, may influence the distribution of chronic disease by SES as well as how this distribution has changed over time. Using overweight status as a health indicator, the authors studied repeated cross-sectional data from women aged 18-49 years in 37 developing countries to assess within-country trends in overweight inequalities by SES between 1989 and 2007 (n=405,550). Meta-regression was used to examine the associations between gross domestic product and disproportionate increases in overweight prevalence by SES, with additional testing for modification by country-level income inequality. In 27 of 37 countries, higher SES (vs. lower) was associated with higher gains in overweight prevalence; in the remaining 10 countries, lower SES (vs. higher) was associated with higher gains in overweight prevalence. Gross domestic product was positively related to faster increase in overweight prevalence among the lower wealth groups. Among countries with a higher gross domestic product, lower income inequality was associated with faster overweight growth among the poor.     

Wider income gaps,wider waistbands? An ecological study of obesity and income inequality

OBJECTIVES: To see if obesity, deaths from diabetes, and daily calorie intake are associated with income inequality among developed countries. DESIGN: Ecological study of 21 developed countries.Countries: Countries were eligible for inclusion if they were among the top 50 countries with the highest gross national income per capita by purchasing power parity in 2002, had a population over 3 million, and had available data on income inequality and outcome measures. MAIN OUTCOME MEASURES: Percentage of obese (body mass index >30) adult men and women, diabetes mortality rates, and calorie consumption per capita per day. RESULTS: Adjusting for gross national per capita income, income inequality was positively correlated with the percentage of obese men (r = 0.48, p = 0.03), the percentage of obese women (r = 0.62, p = 0.003), diabetes mortality rates per 1 million people (r = 0.46, p = 0.04), and average calories per capita per day (r = 0.50, p = 0.02). Correlations were stronger if analyses were weighted for population size. The effect of income inequality on female obesity was independent of average calorie intake. CONCLUSIONS: Obesity, diabetes mortality, and calorie consumption were associated with income inequality in developed countries. Increased nutritional problems may be a consequence of the psychosocial impact of living in a more hierarchical society.     

Tests of stationarity and cointegration of health care expenditure and gross domestic product

This study examines the long-run relationship among the per capita private, public, and total health care expenditure and per capita gross domestic product and population growth of Turkey. We find some evidence of multivariate cointegrating relationships among the health care expenditure and gross domestic product, and population growth. We further find a bivariate cointegrating relationship between private health care expenditure and per capita gross domestic product. Accordingly, a 10% increase in gross domestic product would translate into a 21.9% increase in total health care expenditure while controlling population growth. The income elasticity of health expenditure is found to be greater than 1, implying that health care is a luxury good in Turkey. Finally we note that there exists one-way causality running from per capita gross domestic product to various definitions of health care expenses.     

Income inequality and self-rated health in US metropolitan areas: A multi-level analysis

Income inequality has been found to affect health in a number of international and cross-national studies. Using data from a telephone survey of adults in the United States, this study analyzed the effect of metropolitan level income inequality on self-rated health. It combined individual data from the 2000 Behavioral Risk Factor Surveillance System with metropolitan level income data from the 2000 Census. After controlling for smoking, age, education, Black race, Hispanic ethnicity, sex, household income, and metropolitan area per capita income, this study found that for each 1 point rise in the GINI index (on a hundred point scale) the risk of reporting Fair or Poor self-rated health increased by 4.0% (95% confidence interval 1.6–6.5%). Given that self-rated health is a good predictor of morbidity and mortality, this suggests that metropolitan area income inequality is affecting the health of US adults.     

Metropolitan area income inequality and self-rated health--a multi-level study

We examined the association of income inequality measured at the metropolitan area (MA) and county levels with individual self-rated health. Individual-level data were drawn from 259,762 respondents to the March Current Population Survey in 1996 and 1998. Income inequality and average income were calculated from 1990 census data, the former using Gini coefficients. Multi-level logistic regression models were used. Controlling for sex, age, race, and individual-level household income, respondents living in high, medium-high, and medium-low income inequality MAs had odds ratios of fair/poor self-rated health of 1.20 (95% confidence interval 1.04-1.38), 1.07 (0.95-1.21), and 1.02 (0.91-1.15), respectively, compared to people living in the MAs with the lowest income inequality. However, we found only a small association of MA-level income inequality with fair/poor health when controlling further for average MA household income: odds ratios were 1.10 (0.95-1.28), 1.01 (0.89-1.14), and 1.00 (0.89-1.12), respectively. Likewise, we found only a small association of county-level income inequality with self-rated health although only 40.7% of the sample had an identified county on CPS data. Regarding the association of state-level income inequality with fair/poor health, we found the association to be considerably stronger among non-metropolitan (i.e. rural) compared to metropolitan residents.     

Income inequality,illiteracy rate,and life expectancy in Brazil

OBJECTIVES: The link between income disparities and health has been studied mostly in developed nations. This study assesses the relationship between income disparities and life expectancy in Brazil and measures the impact of illiteracy rates on the association. METHODS: The units of analysis (n = 27) are all the Brazilian states and the federal capital. Simple and multiple linear regressions were performed to measure the association between income disparity, measured by the Gini coefficient, gross domestic product (GDP) per capita, and illiteracy rate. Data came from publicly available sources at the Brazilian Ministry of Health and the Brazilian Institute of Geography and Statistics. RESULTS: Income disparities and illiteracy rates were negatively associated with life expectancy in Brazil. GDP per capita was positively associated with life expectancy. The inclusion of illiteracy rates in the regression model removed the effect of income disparities. CONCLUSIONS: Illiteracy rate is strongly associated with life expectancy in Brazil. This finding is in accord with reports from the United States and has implications for health policy and planning for both developed and developing countries.     

Inequities in access to and use of drinking water services in Latin America and the Caribbean.

OBJECTIVE: To identify and evaluate inequities in access to drinking water services as reflected in household per capita expenditure on water, and to determine what proportion of household expenditures is spent on water in 11 countries of Latin America and the Caribbean. METHODS: Using data from multi-purpose household surveys (such as the Living Standards Measurement Survey Study) conducted in 11 countries from 1995 to 1999, the availability of drinking water as well as total and per capita household expenditures on drinking water were analyzed in light of socioeconomic parameters, such as urban vs. rural setting, household income, type and regularity of water supply service, time spent obtaining water in homes not served by running water, and type of water-purifying treatment, if any. RESULTS: Access to drinking water as well as total and per capita household expenditures on drinking water show an association with household income, economic conditions of the household, and location. The access of the rural population to drinking water services is much more restricted than that of the urban population for groups having similar income. The proportion of families having a household water supply system is comparable in the higher-income rural population and the lower-income urban population. Families without a household water supply system spend a considerable amount of time getting water. For poorer families, this implies additional costs. Low-income families that lack a household water supply spend as much money on water as do families with better income. Access to household water disinfection methods is very limited among poor families due to its relatively high cost, which results in poorer drinking water quality in the lower-income population. CONCLUSIONS: Multi-purpose household surveys conducted from the consumer's point of view are important tools for research on equity and health, especially when studying unequal access to, use of, and expenditures on drinking water. It is recommended that countries improve their portion of the surveys that deals with water and sanitation in order to facilitate national health assessments and the establishment of more equitable subsidy programs.     

Socioeconomic circumstances and health among the brazilian elderly: a study using data from a National Household Survey

The influence of socioeconomic circumstances on senior citizens' health is still controversial. We used data from the 1998 Brazilian National Household Survey (PNAD 1998) to examine this influence. A representative sample of the Brazilian population aged > or = 65 years (n = 19,068) were included in the study. The characteristics of those in the lower quintile of per capita household income were compared with those with higher income (< 0.67 vs > or = 0.67 the Brazilian minimum wage). The lower income group presented worse health conditions (self-rated health, inability to perform routine activities due to a health problem, bedridden conditions, and a report of any disease), and worse physical functioning (level of difficulty in performing selected physical activities), and less frequent use of medical and dental services. These results do not confirm observations, in some developed countries, of a lack of association between socioeconomic status and health among the elderly. On the contrary, according to our results, in Brazil even small differences in income are sufficiently sensitive to identify older adults with worse health conditions and limited access to health services.     

Primary care, income inequality, and self-rated health in the United States: a mixed-level analysis.

Using the 1996 Community Tracking Study household survey, the authors examined whether income inequality and primary care, measured at the state level, predict individual morbidity as measured by self-rated health status, while adjusting for potentially confounding individual variables. Their results indicate that distributions of income and primary care within states are significantly associated with individuals' self-rated health; that there is a gradient effect of income inequality on self-rated health; and that individuals living in states with a higher ratio of primary care physician to population are more likely to report good health than those living in states with a lower such ratio. From a policy perspective, improvement in individuals' health is likely to require a multi-pronged approach that addresses individual socioeconomic determinants of health, social and economic policies that affect income distribution, and a strengthening of the primary care aspects of health services.     

Population health and income inequality: new evidence from Israeli time-series analysis

BACKGROUND AND OBJECTIVES: The relationship between population health and inequality in income distribution has attracted much attention during the last two decades. The purpose of this paper is to examine that relationship using Israeli time-series data, and considering three types of income: economic, pre-tax, and disposable. METHODS: Israeli time series (1979-2000) on life expectancy of men and women at birth and at ages 5 and 65, as well as infant mortality, were related to Gini coefficients measuring inequality in economic, pre-tax (after transfers) and disposable (after taxes) incomes, controlling for gross domestic product (GDP) per capita. This design allows for the estimation of the effects on population health of changes in income inequalities over time as well as of contemporaneous reduction in inequality due to transfers and taxes. RESULTS: None of the three income inequality measures by itself had an effect over time on population health. However, larger contemporaneous reductions in inequality, mainly through the transfers system, were associated with better population health, in particular with lower infant mortality. CONCLUSIONS: A significant part of the temporal improvement in the health of the Israeli population has been due to the increasing effort to reduce inequality in economic income by increasing transfer payments. The results are generally inconsistent with the argument of adverse psychosocial effects of inequality on health, and are consistent with inequality being related to other harmful public goods affecting health and with Rodgers' argument.     

Gender differences in the relationship between housing, socioeconomic status, and self-reported health status

This study investigates gender differences in housing, socioeconomic status, and self-reported health status. The analysis focuses on the social and economic dimensions of housing, such as demand, control, material aspects (affordability, type of dwelling) and meaningful aspects (pride in dwelling, home as a refuge) of everyday life in the domestic environment. A random sample, cross-sectional telephone survey was administered in the city of Vancouver, Canada in June 1999 (n = 650). Survey items included measures of material and meaningful dimensions of housing, housing satisfaction, and standard measures of socioeconomic status and social support. The main outcome measure was self-reported health (excellent/very good/good vs. fair/poor). A three-stage analysis provides an overall picture of the sample characteristics for male and female respondents, detects significant relations between individual and housing characteristics and self-rated health status, and investigates male-female differences in the factors associated with fair/poor self-rated health. In multivariate analyses, a small number of socioeconomic dimensions of housing were associated with self-rated health status for women. For men, only one attribute of housing was associated with self-rated health: crowding was positively related to poor health, contradicting expectations and the findings for women. The self-reported strain of housework was unrelated to self-rated health for men, but strongly related to poor health for women. For men and women, satisfaction with social activities increased the likelihood of reporting better health. Future research should focus on the health effects of gendered differences in domestic and paid work, and on home and family roles and the interaction among gender, household crowding, and health.     

Sex- and age- specific relations between economic development,economic inequality and homicide rates in people aged 0-24 years: a cross-sectional analysis

OBJECTIVE: To test whether relations between economic development, economic inequality, and child and youth homicide rates are sex- and age-specific, and whether a country's wealth modifies the impact of economic inequality on homicide rates. METHODS: Outcome variables were homicide rates around 1994 in males and females in the age ranges 0-4, 5-9, 10-14, 15-19 and 20-24 years from 61 countries. Predictor variables were per capita gross domestic product (GDP), GINI coefficient, percentage change in per capita gross national product (GNP) and female economic activity as a percentage of male economic activity. Relations were analysed by ordinary least squares regression. FINDINGS: All predictors explained significant variances in homicide rates in those aged 15-24. Associations were stronger for males than females and weak for children aged 0-9. Models that included female economic inequality and percentage change in GNP increased the effect in children aged 0-9 and the explained variance in females aged 20-24. For children aged 0-4, country clustering by income increased the explained variance for both sexes. For males aged 15-24, the association with economic inequality was strong in countries with low incomes and weak in those with high incomes. CONCLUSION: Relations between economic factors and child and youth homicide rates varied with age and sex. Interventions to target economic factors would have the strongest impact on rates of homicide in young adults and late adolescent males. In societies with high economic inequality, redistributing wealth without increasing per capita GDP would reduce homicide rates less than redistributions linked with overall economic development.     

Education and income: which is more important for mental health?

STUDY OBJECTIVE: To assess which indicators of socioeconomic status are associated with an increased prevalence of common mental disorders. DESIGN: Cross sectional household survey. SETTING: Santiago, Chile. PARTICIPANTS: Random sample of adults aged 16-65 residing in private households. Main results: Less education (odds ratio 2.44, 95% confidence intervals 1.50 to 3.97), a recent income decrease (odds ratio 2.14, 1.70 to 2.70), and poor housing (odds ratio 1.53, 1.05 to 2.23), were the only socioeconomic status variables that remained significantly associated with an increased prevalence of common mental disorders after adjustments. The prevalence of common mental disorders was also higher among people with manual unskilled occupations, overcrowded housing, and lower per capita income but these associations disappeared after adjustment for other explanatory and confounding variables. CONCLUSIONS: There is a strong, inverse, and independent association between education and common mental disorders. However, income was not associated with the prevalence of common mental disorders, after adjusting for other socioeconomic variables. Similar results have been found in other Latin American studies but British studies tend to find the opposite, that income but not education is associated with common mental disorders. Understanding the impact of socioeconomic factors on mental health requires research in poor as well as rich countries.     

The Association Between Women's Self-Rated Health and Satisfaction with Environmental Services in an Underserved Community in Lebanon

This research evaluated the association between women's self-rated health and a number of socioeconomic and environmental health indicators relating to drinking water services in an underserved Lebanese community. A population-based, cross-sectional survey using interviews was adopted to obtain information from female homemakers of 2,223 households in the town of Bebnine, Lebanon. The questionnaire included indicators on self-rated health, satisfaction with water quality, source of drinking water, occurrence of diarrhea, and socioeconomic variables, such as education, occupation, and perceived economic status. Self-rated health was categorized as poor, fair, and good. Odds ratios for poor and fair compared to good self-rated health values were calculated using multinomial logistic regression. A total of 712 women (32%) reported poor self-rated health. Women who perceived their household income to be worse than others in town were four times as likely to report poor health. Compared to women who were satisfied with drinking water quality, dissatisfied women were 42% more likely to report poor health. Women living in households reporting recent episodes of diarrheal illness had poorer health ratings than those without. The findings suggest a positive relationship between individual perceptions of water quality and self-rated health. Community concerns over their surrounding environment serve as a primary guide for infrastructural development and government policy.     

Do social comparisons explain the association between income inequality and health?: Relative deprivation and perceived health among male and female Japanese individuals

Relative deprivation has been hypothesized as one of the pathways accounting for the link between income inequality and health. We tested this hypothesis in a large national sample of men and women in Japan. Our survey included a probability sample of 22,871 men and 24,243 women aged 25-64, from whom information was gathered on demographic variables, household income, occupation or employment status, and self-rated health. Our measure of relative deprivation was the Yitzhaki Index, which calculates the deprivation suffered by each individual as a function of the aggregate income shortfall for each person relative to everyone else with higher incomes in that person's reference group. We modeled several alternative reference groups, including others with the same occupation, others of the same age group, and others living in the same geographic area (prefecture), as well as combinations of these. Generalized estimating equations demonstrated that higher relative deprivation was associated with worse self-rated health. Even after controlling for absolute income as well as other sociodemographic factors, the odds ratio and its 95% confidence intervals (CI) for poor health ranged from 1.09 (95% CI: 1.02-1.16) to 1.18 (95% CI: 1.11-1.26) for men and from 1.10 (95% CI: 1.04-1.16) to 1.16 (95% CI: 1.09-1.23) for women per 1 million increase in the Yitzhaki Index. As such, relative income deprivation is associated with poor self-rated health independently of absolute income, and relative deprivation may be a mechanism underlying the link between income inequality and population health.     

Variations in infant mortality rates among municipalities in the state of Ceará, Northeast Brazil: an ecological analysis.

BACKGROUND: Infant mortality rates vary substantially among municipalities in the State of Ceará, from 14 to 193 per 1000 live births. Identification of the determinants of these differences can be of particular importance to infant health policy and programmes in Brazil where local governments play a pivotal role in providing primary health care. METHODS: Ecological study across 140 municipalities in the State of Ceará, Brazil. RESULTS: To determine the interrelationships between potential predictors of infant mortality, we classified 11 variables into proximate determinants (adequate weight gain and exclusively breastfeeding), health services variables (prenatal care up-to-date, participation in growth monitoring, immunization up-to-date, and decentralization of health services), and socioeconomic factors (female literacy rate, household income, adequate water supply, adequate sanitation, and per capita gross municipality product), and included the variables in each group simultaneously in linear regression models. In these analyses, only one of the proximate determinants (exclusively breastfeeding (inversely), R2 = 9.3) and one of the health services variables (prenatal care up-to-date (inversely), R2 = 22.8) remained significantly associated with infant mortality. In contrast, female literacy rate (inversely), household income (directly) and per capita GMP (inversely) were independently associated with the infant mortality rate (for the model including the three variables R2 = 25.2). Finally, we considered simultaneously the variables from each group, and selected a model that explained 41% of the variation in infant mortality rates between municipalities. The paradoxical direct association between household income and infant mortality was present only in models including female illiteracy rate, and suggests that among these municipalities, increases in income unaccompanied by improvements in female education may not substantially reduce infant mortality. The lack of independent associations between inadequate sanitation and infant mortality rates may be due to the uniformly poor level of this indicator across municipalities and provides no evidence against its critical role in child survival. CONCLUSIONS: These results suggest that promotion of exclusive breastfeeding and increased prenatal care utilization, as well as investments in female education would have substantial positive effects in further reducing infant mortality rates in the State of Ceará.