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.     

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.     

The association between state income inequality and worse health is not confounded by race

BACKGROUND: The relationship between income inequality and health across US states has been challenged recently on grounds that this relationship may be confounded by the effect of racial composition, measured as the proportion of the state's population who are black. METHODS: Using multilevel statistical models, we examined the association between state income inequality and poor self-rated health. The analysis was based on the pooled 1995 and 1997 Current Population Surveys, comprising 201 221 adults nested within 50 US states. RESULTS: Controlling for the individual effects of age, sex, race, marital status, education, income, health insurance coverage, and employment status, we found a significant effect of state income inequality on poor self-rated health. For every 0.05-increase in the Gini coefficient, the odds ratio (OR) of reporting poor health increased by 1.39 (95% CI: 1.26, 1.51). Additionally controlling for the proportion of the state population who are black did not explain away the effect of income inequality (OR = 1.30; 95% CI: 1.15, 1.45). While being black at the individual level was associated with poorer self-rated health, no significant relationship was found between poor self-rated health and the proportion of black residents in a state. CONCLUSION: Our finding demonstrates that neither race, at the individual level, nor racial composition, as measured at the state level, explain away the previously reported association between income inequality and poorer health status in the US.     

Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States

The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.     

Aggregation and the measurement of income inequality: effects on morbidity

This is a cross-sectional study using records from the National Health Interview Survey linked to Census geography. The sample is restricted to white males ages 25-64 in the United States from three years (1989-1991) of the National Health Interview Survey. Perceived health is used to measure morbidity. Individual covariates include income-to-needs ratio, education and occupation. Contextual level measures of income inequality, median household income and percent in poverty are constructed at the US census county and tract level. The association between inequality and morbidity is examined using logistic regression models. Income inequality is found to exert an independent adverse effect on self-rated health at the county level, controlling for individual socioeconomic status and median income or percent poverty in the county. This corresponding effect at the tract level is reduced. Median income or percent poverty and individual socioeconomic status are the dominant correlates of perceived health status at the tract level. These results suggest that the level of geographic aggregation influences the pathways through which income inequality is actualized into an individuals' morbidity risk. At higher levels of aggregation there are independent effects of income inequality, while at lower levels of aggregation, income inequality is mediated by the neighborhood consequences of income inequality and individual processes.     

An investigation of the longitudinal relationship between neighbourhood income inequality and individual self-rated health in England

There are mixed findings on whether neighbourhood income inequality leads to better self-rated health (SRH) or not. This study considers two hypotheses: individuals living in more unequal neighbourhoods have better SRH and the level of neighbourhood income inequality and its impact on SRH is moderated by household and neighbourhood level income related variables. Data from Waves 8–10 of the UK Household Longitudinal Study for respondents living in England at wave 8 were used. Neighbourhood income inequality was measured using Gini coefficients of household income from the Pay As You Earn and benefits systems for Lower Super Output Areas. Longitudinal ordinal multilevel models predicted self-rated health in 2016–18, 2017–19 and 2019-20 by income inequality and its interaction with household income, neighbourhood median income and neighbourhood deprivation, conditional on individual educational attainment, age, sex, ethnic group, years lived in current residence, region of residence and study wave. There were 24,889 respondents analysed over three waves. SRH was worse for those living in more income equal neighbourhoods. There was no indication that neighbourhood inequality was moderated by household income, neighbourhood median income or neighbourhood deprivation. These findings are in line with the balance of existing evidence and support policy interventions that aim to create mixed communities for the purpose of improving population health.     

Societal characteristics and health in the former communist countries of Central and Eastern Europe and the former Soviet Union: a multilevel analysis

OBJECTIVES: To examine whether, in former communist countries that have undergone profound social and economic transformation, health status is associated with income inequality and other societal characteristics, and whether this represents something more than the association of health status with individual socioeconomic circumstances. DESIGN: Multilevel analysis of cross-sectional data. SETTING: 13 Countries from Central and Eastern Europe and the former Soviet Union. PARTICIPANTS: Population samples aged 18+ years (a total of 15 331 respondents). MEAN OUTCOME MEASURES: Poor self-rated health. RESULTS: There were marked differences among participating countries in rates of poor health (a greater than twofold difference between the countries with the highest and lowest rates of poor health), gross domestic product per capita adjusted for purchasing power parity (a greater than threefold difference), the Gini coefficient of income inequality (twofold difference), corruption index (twofold difference) and homicide rates (20-fold difference). Ecologically, the age- and sex-standardised prevalence of poor self-rated health correlated strongly with life expectancy at age 15 (r = -0.73). In multilevel analyses, societal (country-level) measures of income inequality were not associated with poor health. Corruption and gross domestic product per capita were associated with poor health after controlling for individuals' socioeconomic circumstances (education, household income, marital status and ownership of household items); the odds ratios were 1.15 (95% confidence interval 1.03 to 1.29) per 1 unit (on a 10-point scale) increase in the corruption index and 0.79 (95% confidence interval 0.68 to 0.93) per $5000 increase in gross domestic product per capita. The effects of gross domestic product and corruption were virtually identical in people whose household income was below and above the median. CONCLUSION: Societal measures of prosperity and corruption, but not income inequalities, were associated with health independently of individual-level socioeconomic characteristics. The finding that these effects were similar in persons with lower and higher income suggests that these factors do not operate exclusively through poverty.     

Income inequality,household income,and health status in Canada: a prospective cohort study

OBJECTIVES: This study sought to determine whether income inequality, household income, and their interaction are associated with health status. METHODS: Income inequality and area income measures were linked to data on household income and individual characteristics from the 1994 Canadian National Population Health Survey and to data on self-reported health status from the 1994, 1996, and 1998 survey waves. RESULTS: Income inequality was not associated with health status. Low household income was consistently associated with poor health. The combination of low household income and residence in a metropolitan area with less income inequality was associated with poorer health status than was residence in an area with more income inequality. CONCLUSIONS: Household income, but not income inequality, appears to explain some of the differences in health status among Canadians.     

Are manual workers at higher risk of death than non-manual employees when living in Swedish municipalities with higher income inequality?

OBJECTIVES: To test the hypothesis that manual workers are at higher risk of death than are non-manual employees when living in municipalities with higher income inequality. DESIGN: Hierarchical regression was used for the analysis were individuals were nested within municipalities according to the 1990 Swedish census. The outcome was all-cause mortality 1992-1998. The income measure at the individual level was disposable family income weighted against composition of family; the income inequality measure used at the municipality level was the Gini coefficient. PARTICIPANTS: The study population consisted of 1 578 186 people aged 40-64 years in the 1990 Swedish census, who were being reported as unskilled or skilled manual workers, lower-, intermediate-, or high-level non-manual employees. RESULTS: There was no significant association between income inequality at the municipality level and risk of death, but an expected gradient with unskilled manual workers having the highest risk and high-level non-manual employees having the lowest. However, in the interaction models the relative risk (RR) of death for high-level non-manual employees was decreasing with increasing income inequality (RR = 0.77; 95% CI, 0.63-0.93), whereas the corresponding risk for unskilled manual workers increased with increasing income inequality (RR = 1.24; 95% CI, 1.06-1.46). The RRs for skilled manual, low- and medium- level non-manual employees were not significant. Controlling for income at the individual level did not substantially alter these findings, neither did potential confounders at the municipality level. CONCLUSIONS: The findings suggest that there could be a differential impact from income inequality on risk of death, dependent on individuals' social position.     

Inequality in the face of death? Public expenditure on health care for different socioeconomic groups in the last year of life

OBJECTIVE: To investigate the association between public expenditure on health care in the last year of life and individual socioeconomic status in Sweden. METHODS: Population-based study of public expenditure using linked registers for all 16,617 deaths among Stockholm County Council residents in 2002 (population 1.8 million). Age-standardized, total and per capita spend were calculated by income categories, age and specialty. Multivariate analysis examined the association between socioeconomic status and public expenditure. RESULTS: County council expenditure on health care in the last year of life rose with increasing income of the deceased person. Median per capita expenditure increased from 55,417 Swedish Kronor (SEK) (US$ 7542) in the lowest income group to SEK 94,678 (US$ 12,887) in the highest. Total age-standardized spend increased by 60% across the same interval (80,227 [95% confidence interval (CI) 79,946-80,497] to SEK 127,344 [95% CI 126,969-127,719]). Expenditure decreased with increasing age over 65 years in all income groups. Higher income was independently associated with greater total public health spend in multivariate analysis, adjusting for age, sex, health-care utilization and major diagnostic groups. CONCLUSIONS: There is inequality in public expenditure on health care at the end of life across socioeconomic groups in Stockholm. This phenomenon merits attention within Sweden, and beyond, in countries with less comprehensive welfare systems.     

State-level income inequality and individual mortality risk: a prospective, multilevel study

OBJECTIVES: Previous studies have linked state-level income inequality to mortality rates. However, it has been questioned whether the relationship is independent of individual-level income. The present study tests whether state-level income inequality is related to individual mortality risk, after adjustment for individual-level characteristics. METHODS: In this prospective, multilevel study design, the vital status of National Health Interview Survey (NHIS) respondents was ascertained by linkage to the National Death Index, with additional linkage of state-level data to individuals in the NHIS. The analysis included data for 546,888 persons, with 19,379 deaths over the 8-year follow-up period. The Gini coefficient was used as the measure of income inequality. RESULTS: Individuals living in high-income-inequality states were at increased risk of mortality (relative risk = 1.12; 95% confidence interval = 1.04, 1.19) compared with individuals living in low-income-inequality states. In stratified analyses, significant effects of state income inequality on mortality risk were found, primarily for near-poor Whites. CONCLUSIONS: State-level income inequality appears to exert a contextual effect on mortality risk, after income is adjusted for, providing further evidence that the distribution of income is important for health.     

Income inequality and health: multilevel analysis of Chilean communities

STUDY OBJECTIVE: The evidence supporting the effect of income inequality on health has been largely observed in societies far more egalitarian than the US. This study examines the cross sectional multilevel associations between income inequality and self rated poor health in Chile; a society more unequal than the US. DESIGN: A multilevel statistical framework of 98 344 people nested within 61 978 households nested within 285 communities nested within 13 regions. SETTING: The 2000 National Socioeconomic Characterization Survey (CASEN) data from Chile. PARTICIPANTS: Adults aged 18 and above. The outcome was a dichotomised self rated health (0 if very good, good or average; 1 if poor, or very poor). Individual level exposures included age, sex, ethnicity, marital status, education, employment status, type of health insurance, and household level exposures include income and residential setting (urban/rural). Community level exposures included the Gini coefficient and median income. Main results: Controlling for individual/household predictors, a significant gradient was observed between income and poor self rated health, with very poor most likely to report poor health (OR: 2.94) followed by poor (OR: 2.77), low (OR: 2.06), middle (OR: 1.73), high (OR: 1.38) as compared with the very high income earners. Controlling for household and community effects of income, a significant effect of community income inequality was observed (OR:1.22). CONCLUSIONS: Household income does not explain any of the between community differences; neither does it account for the effect of community income inequality on self rated health, with more unequal communities associated with a greater probability of reporting poor health.     

Bicycle helmet-wearing variation and associated factors in Ontario teenagers and adults

BACKGROUND: The incidence of bicycle helmet use and the factors associated with helmet use in Ontario are presented in this study. The Ontario Health Survey (1996), a population-based survey of Ontario residents, was used as the data source. METHODS: As the factors associated with helmet use were found to differ between adults and teens, a separate analysis was performed for each age grouping. A logistic regression model (with Bootstrap confidence intervals--95%) was used and adjusted odds ratios (OR) are reported. RESULTS: Of the 7,693 respondents, 41.1% reported wearing their helmets on a regular basis when riding a bicycle. Helmet use was greatest among 12-14 year olds (71.7%) and lowest among those 15-18 years old (33.3%). In teenagers, drinking alcohol (OR: 2.8) and smoking (OR: 4.4) were strongly associated with helmet non-use. In the adult group, female gender (OR: 1.26), higher income (OR: 1.43), higher education (OR: 1.68), nonsmoking status (OR: 2.0) and abstinence from alcohol (1.27) were associated with helmet use. Living in a rural area was also associated with helmet use in the multi-variable analysis. CONCLUSION: This study indicates that bicycle helmet non-use is a multifaceted problem and thus any strategy for increasing helmet-wearing rates requires multi-dimensional interventions. The results of this study are discussed within the context of other studies and related to their public health implications.     

Income and Mental Health: Unraveling Community and Individual Level Relationships

BACKGROUND: The association between individual socioeconomic status (SES) and mental disorder is well-documented, but studies to date have provided limited and sometimes conflicting evidence on the relationship between aspects of socioeconomic environment, including the role of income inequality, and mental disorder. AIMS OF THE STUDY: This paper explores the relationships between mental disorder and individual SES and socioeconomic environment, with particular attention to both the level and dispersion of community income and to their interactions with individual income. METHODS: Cross sectional study using nationally representative, individual level data from the Healthcare for Communities survey merged with supplemental information. Dependent variable is individual mental health status, measured by the 5 item Mental Health Inventory (MHI-5; average 80.6) and an indicator of probable anxiety or mood disorder based on clinical screening instruments (positive for 14.3 percent of respondents in the sample). RESULTS: MHI-5 decreases (indicating worse mental health), and the probability of an anxiety or depressive disorder increases continuously from the highest to the lowest quintiles of family income. Compared to those in the highest income quintile, MHI-5 is more than 10 points lower and the probability of disorder is much greater among individuals in the lowest income quintile. Within-quintile own income level is also strongly associated with mental health among lower income individuals. We find no evidence that higher levels of income inequality are associated with poor mental health outcomes, measured either by the probability of disorder or MHI-5. Regarding income level, MHI-5 is 3.4 to 3.5 points higher among low income individuals in medium or high income states compared to those in low income states. DISCUSSION: The qualitative conclusions are stable across various specifications reported (two different measures of mental health, two geographic levels, and among all individuals and low income individuals alone), and in specifications with alternative parameterizations of the community variables (continuously measured, included as quintiles instead of tertiles, and using other indicators of inequality). Individual income is highly correlated with mental health status; level of state income has some association; community or state income inequality has no detectable relationship with mental health. This analysis provides no support for the hypothesis that income inequality is a stronger determinant of health than individual or family income, a hypothesis that in recent years has received much attention in the popular press and policy debates. Limitations of our analysis include the cross-sectional nature of the analysis, the sample sizes used in derivation of the site variables (though sensitivity analyses showed robust results) and the age of the state data. CONCLUSIONS: The association between individual income and mental health is strong. No support for the income inequality hypothesis is found.IMPLICATIONS FOR HEALTH POLICY FORMULATION: Our findings point to a need for better understanding of the relationship between individual income and mental health outcomes. Our research does not support the notion that policies aimed at diminishing income inequality are an important lever in improving mental health outcomes for individuals. IMPLICATIONS FOR FURTHER RESEARCH: This research does not address whether and how different sources of income-at the individual or community level-may affect mental health, and whether the associations observed cross-sectionally also bear out longitudinally. In addition, more research into the relationship between other community characteristics, such as service availability, and mental health outcomes is needed.     

No association of income inequality with adult mortality within New Zealand: a multi-level study of 1.4 million 25-64 year olds

STUDY OBJECTIVE: To determine the association of regional income inequality within New Zealand with mortality among 25-64 year olds. DESIGN: Individual census and mortality records were linked over the 1991-94 period. Income inequality (Gini coefficients) and average household income variables were calculated for 35 regions. "Individual level" variables were sex, age, ethnicity, household income, rurality, and small area socioeconomic deprivation. Logistic regression was used for the analyses. Sensitivity analyses for the level of regional aggregation were conducted. PARTICIPANTS: 1.4 million New Zealand census respondents aged 25-64 years followed up for mortality for three years. Main results: Controlling for age, ethnicity, rurality, household income, and regional mean income, there was no association of income inequality with all cause mortality for either men (OR=1.007 for a 0.01 increase in the Gini, 95% confidence intervals 0.989 to 1.024) or women (OR=1.004, 0. 983 to 1.026). By cause of death (cancer, cardiovascular disease, unintentional injury, and suicide) there was some suggestion of a positive association for female unintentional injury (OR=1.068, 0.952 to 1.198) and suicide (OR=1.087, 0.957 to 1.234) but the 95% confidence intervals all included 1.0. Failure to control for ethnicity at the individual level resulted in some association of increasing regional income inequality with increasing mortality risk. Using fewer (n=14) or more (n=73) regional divisions did not substantially change the findings. CONCLUSION: There is no convincing evidence of an association of income inequality within New Zealand with adult mortality. Previous ecological analyses within New Zealand suggesting an association of income inequality with mortality were confounded by ethnicity at the individual level. However, this study does not refute the possibility that income inequality at the national level affects health.     

The proportion of influenza vaccination in Ontario, Canada in 2007/2008 compared with other provinces

In 2000, Ontario, Canada introduced a universal influenza immunization program (UIIP) to provide free vaccines to its residents, whose ages are six months or older. The current study sought to measure the effect of the UIIP on influenza vaccination uptake in Ontario compared with other provinces combined. Data from the 2007/2008 Canadian Community Health Survey (cycle 4.1) were used in the analyses. Logistic regression analyses were conducted to estimate the odds ratios for influenza vaccination 2007/2008 associated with province of residence (Ontario versus other provinces combined) and other factors including chronic disease status, age, gender, household income, smoking status, having a medical doctor, and self-perceived health status. Living in Ontario was positively associated with having an influenza vaccine during the 2007/2008 season [odds ratio (OR) 1.50, 95% confidence interval (CI) 1.45-1.55]. Increased age (OR 6.13, 95% CI 5.77-6.51), a positive chronic disease status (OR 1.70, 95% CI 1.63-1.77) and having a regular medical doctor (OR 1.95, 95% CI 1.85-2.07) also demonstrated a positive relationship with influenza vaccination in 2007/2008. A stratified analysis by province of residence suggested that having a chronic disease, old age and high income had less impact on the likelihood of receiving a vaccine in Ontario than other provinces. The results of this study may help to inform the development of strategies to increase vaccination coverage in Canada.     

Income inequality and ischaemic heart disease in Danish men and women

BACKGROUND: It has been hypothesized that areas with an unequal income distribution are less likely to invest in health and more likely to have a social environment that influences the development of ischaemic heart disease (IHD) METHODS: We used pooled data from two cohort studies conducted in Copenhagen to analyse the association between area income inequality and first admission to hospital or death from IHD in women and men while controlling for individual income and other IHD risk factors. A total of 11 685 women and 10 036 men, with initial health examinations between 1964 and 1992, were followed for a median of 13.8 years. Information on median income share at parish and municipality levels was obtained from population registers. RESULTS: During follow-up 1700 men and 1204 women experienced an IHD event. At parish level income share was inversely associated with an increased risk of IHD in men (hazard ratio [HR](most versus least equal quartile) = 0.85 (95% CI: 0.73-0.98). Among women there was no relation between parish income inequality and IHD. Subject's household income was inversely related to IHD, and when this variable was controlled for, the association between income inequality at parish level and IHD in men attenuated slightly. When behavioural and biological risk factors were entered into the Cox model this relation attenuated further. However, some of these risk factors might mediate rather than confound the effect of income inequality. The association between income inequality at municipality level and IHD was insignificant for men, while in women the relation had a curved shape with those living in the least equal areas having the lowest risk. CONCLUSIONS: This study provides no clear evidence for an association between income inequality measured at parish or municipality level and IHD in Danish adults. The associations were weak and varied between different strata and geographical levels.     

Utilitarian bicycling: a multilevel analysis of climate and personal influences

BACKGROUND: Increasing utilitarian bicycling in urban areas is a means to reduce air and noise pollution, increase physical activity, and reduce the risk of chronic diseases. We investigated the impact of individual- and city-level characteristics on bicycling in Canadian cities to inform transportation and public health policies. METHODS: The study population included 59,899 respondents to the 2003 Canadian Community Health Survey (CCHS) living in cities with populations greater than 50,000. In 2005, data on individual characteristics were drawn from the CCHS, and city-level climate data from Environment Canada records. Separate multilevel logistic regression models were developed for the general (nonstudent) and student populations. RESULTS: The proportion of the urban population reporting bicycling in a typical week was 7.9%, with students cycling more than nonstudents (17.2% vs 6.0%). In the general population, older age, female gender, lower education, and higher income were associated with lower likelihood of cycling. More days of precipitation per year and more days of freezing temperatures per year were both associated with lower levels of utilitarian cycling (odds ratios [ORs] for every 30-day increase in precipitation=0.84, 95% confidence interval [CI]=0.74-0.94, and for every 30-day increase in freezing temperatures OR=0.91, 95% CI=0.86-0.97). There was less variation in the proportion of students who cycled by age and income, and only the number of days with freezing temperatures influenced bicycling. CONCLUSIONS: Bicycling patterns are associated with individual demographic characteristics and the climate where one lives. This evidence might be useful to guide policy initiatives for targeted health promotion and transportation infrastructure.     

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.     

Neighbourhood inequality, neighbourhood affluence and population health

While there is now considerable evidence that the neighbourhood income levels (poverty/affluence) exert an independent effect on health, there is little evidence that neighbourhood income inequality is consequential, net of individual-level socio-economic resources. We show that the usual explanation for the absence of an independent effect of neighbourhood inequality--the assumption of economic homogeneity at the neighbourhood level--cannot account for this result. The authors use hierarchical models that combine individual micro-data from Statistics Canada's 1996/97 National Population Health Survey (NPHS) with neighbourhood and city-level socio-economic characteristics from the 1996 Census of Canada to estimate the effects of neighbourhood affluence and income inequality on self-reported health status. The findings indicate that the negative "ecological" correlation between average neighbourhood health and neighbourhood income inequality is the result not only of compositional differences among individuals but also of contextual neighbourhood effects associated with low and high inequality neighbourhoods.