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.     

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.     

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.     

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.     

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.     

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.     

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.     

Social capital and self-rated health: a contextual analysis.

OBJECTIVES: Social capital consists of features of social organization--such as trust between citizens, norms of reciprocity, and group membership--that facilitate collective action. This article reports a contextual analysis of social capital and individual self-rated health, with adjustment for individual household income, health behaviors, and other covariates. METHODS: Self-rated health ("Is your overall health excellent, very good, good, fair, or poor?") was assessed among 167,259 individuals residing in 39 US states, sampled by the Behavioral Risk Factor Surveillance System. Social capital indicators, aggregated to the state level, were obtained from the General Social Surveys. RESULTS: Individual-level factors (e.g., low income, low education, smoking) were strongly associated with self-rated poor health. However, even after adjustment for these proximal variables, a contextual effect of low social capital on risk of self-rated poor health was found. For example, the odds ratio for fair or poor health associated with living in areas with the lowest levels of social trust was 1.41 (95% confidence interval = 1.33, 1.50) compared with living in high-trust states. CONCLUSIONS: These results extend previous findings on the health advantages stemming from social capital.     

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

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

Social class inequalities in self-rated health and their gender and age group differences in Japan

BACKGROUND: Few studies have examined social inequalities in self-rated health in Japan, and the issue of gender differences related to social inequalities in self-rated health remains inconclusive.METHODS: The data derived from interviews with 2987 randomly selected Japanese adults in four prefectures in Japan who completed the cross-national World Mental Health survey from 2002 through 2005. We calculated odds ratios (ORs) of having poor self-rated physical and mental health by two social class indicators independently with multivariate logistic regression models, adjusted for age, gender, marital status, and area. Stratified analyses by gender and age group were also conducted. RESULTS: The adjusted ORs of the lowest educational attainment category having poor self-rated physical and mental health were 1.42 (95% confidence interval [CI]: 1.15-1.76) and 1.37 (95% CI: 1.10-1.70), respectively. Among females, educational attainment had significant linear associations with self-rated physical and mental health. Adjusted household income was also significantly associated with self-rated physical health among female respondents. No associations were found among males. While educational attainment was associated with self-rated health among the young age group, adjusted household income was associated with self-rated physical health in the middle and old age group. CONCLUSION: These results indicated social inequalities in self-rated health and prominent social inequalities in self-rated health among females in Japan. Social inequalities in self-rated health seemed to exist across age groups. However, the mechanism of social inequalities in self-rated health could be different depending on the age group.     

Income inequality and health in Ontario: a multilevel analysis

OBJECTIVE: To examine the association of income inequality at the public health unit level with individual health status in Ontario. METHODS: Cross-sectional multilevel study carried out among subjects aged 25 years or older residing in 42 public health units in Ontario. Individual-level data drawn from 30,939 respondents in 1996-97 Ontario Health Survey. Median area income and income inequality (Gini coefficient) calculated from 1996 census. Self-rated health status (SRH) and Health Utilities Index (HUI-3) scores were used as main outcomes. RESULTS: Controlling for individual-level factors including income, respondents living in public health units in the highest tercile of income inequality had odds ratios of 1.20 (95% CI 1.04 - 1.38) for fair/poor self-rated health, and 1.11 (95% CI 1.01 - 1.22) for HUI score below the median, compared with people living in public health units in the lowest tercile. Controlling further for median area income had little effect on the association. CONCLUSION: Income inequality was significantly associated with individual self-reported health status at public health unit level in Ontario, independent of individual income.     

Self-rated health among industrial workers in Southern Brazil

OBJECTIVE: To analyze the prevalence of negative self-rated health and its factors associates among industrial workers. METHODS: Cross-sectional study with a probabilistic sample of 482 metal mechanic industrial workers of a city in Southern Brazil. Data was collected by means of self-administered questionnaire and anthropometric measures. The magnitude of the association between self-rated health and the study variables was estimated by odds ratio with 95% confidence intervals (95% CI). Multivariate logistic regression models were obtained using a theoretical hierarchical model. RESULTS: Response rate was 98.6%. Negative self-rated health was seen in 16.6% of the employees and most (84.8%) were males engaged in predominantly production activities (79.4%). The most common complaint was back pain (30.9%). After statistical modeling the following variables remained associated with negative self-rated health: females (OR=3.0 95% CI 1.5;6.2), physical inactivity (OR=1.8 95% CI 1.0;3.4), psychological stress (OR=3.0 95% CI 1.6;5.6), lack of control over life (OR=3.0 95% CI 1.5;6.1), reporting of one (OR=3.2 95% CI 1.4;7.2) or two or more chronic conditions (OR=7.7 95% CI 3.4;17.8), short-term medical leave (OR=2.9 95% CI 1.5;5.5), and incapacitating illness (OR=2.8 95% CI 1.2;6.6). CONCLUSIONS: The prevalence of negative self-rated health was associated with socioeconomic/demographic, lifestyle, psychosocial and health-related dimensions. The variable causing the greatest impact on the outcome was reporting of more than two chronic conditions.     

Adult education and child mortality in India: the influence of caste, household wealth, and urbanization

BACKGROUND: Although socioeconomic position is generally found to be related to health, the associations can be different for different measures of socioeconomic position. We examined the association between adult education and child mortality, and the influence of other socioeconomic markers (caste, household wealth, and urbanization) on this association. METHODS: Data were drawn from the 1998-1999 Indian National Family Health Survey, conducted in 26 states and comprising 66,367 children age 5 years or under. Adult education, for the head of household and spouse, was categorized into 0, 1-8, and 9 or more years of schooling. We used logistic regression to estimate associations between education and child mortality in analysis adjusted for other socioeconomic markers. Effect modification by caste, household wealth, and urbanization was assessed by fitting an interaction term with education. RESULTS: Compared with those who had no education, 9 or more years of education for the head of household and for the spouse were associated with lower child mortality (odds ratio [OR] = 0.54; 95% confidence interval [CI] = 0.48-0.62 and OR = 0.44; 95% CI = 0.36-0.54, respectively) in analyses adjusted for age, sex, and state of residence. Further adjustments for caste and urbanization attenuated these associations slightly; when adjustments were made for household wealth the associations were attenuated more substantially. Nevertheless, in fully adjusted models, 9 or more years of education for the head of household (OR = 0.81; 95% CI = 0.70-0.93) and the spouse (OR = 0.75; 95% CI = 0.60-0.94) remained associated with lower child mortality. There was no effect modification of this association by caste, household wealth, and urbanization. CONCLUSION: Adult education has a protective association with child mortality in India. Caste, household wealth, and urbanization do not modify or completely attenuate this association.     

Body weight dissatisfaction by socioeconomic status among obese, preobese and normal weight women and men: results of the cross-sectional KORA Augsburg S4 population survey

ABSTRACT: BACKGROUND: Body weight dissatisfaction is an important factor in preventing weight gain and promoting weight loss or maintenance. This study focuses on differences in the rates of body weight dissatisfaction among obese, preobese and normal weight women and men by socioeconomic status within a general adult population in Germany. METHODS: Data were analyzed from 4186 adults aged 25 to 74 who participated in a cross-sectional, representative population-based health survey (KORA S4, 1999-2001, Augsburg region/Germany). Body mass was measured anthropometrically and indexed following international standards. Among the 2123 women participating in the survey, 40.3% had a normal weight, 34.9% were preobese, and 24.8% were obese (compared to 25.9%, 51.4% and 22.6% among men, respectively). Body weight dissatisfaction, educational level, household income and occupational status were assessed by computer-aided personal interviewing. An index for socioeconomic status was calculated and categorized into quintiles. Multiple logistic regressions were performed to test for differences in the odds of body weight dissatisfaction across socioeconomic strata in normal weight, preobese and obese groups. Body mass index, age, family status, place of residence and health behaviors were adjusted for. RESULTS: Overall, being dissatisfied with one's body weight was more prevalent in women (48.3%) than in men (33.2%). In the normal weight group, no significant differences in the odds of being dissatisfied were found across socioeconomic groups among women or men. Among preobese men, compared to the lowest socioeconomic stratum, increased odds of being dissatisfied with one's body weight were associated with the highest socioeconomic index group (OR=2.3, 95% CI: 1.4-3.8), middle and high educational level (OR=1.6, 95% CI: 1.1-2.3, and OR=1.9, 95% CI: 1.3-3.7), high income (OR=1.8, 95% CI: 1.2-2.7), and middle and high occupational status (both OR=1.8, 95% CI: 1.2-2.6). Among preobese women, the odds of being dissatisfied were only significantly elevated in those with a middle educational level (OR=1.6, 95% CI: 1.1-2.3). Among obese men, elevated odds were found in the highest socioeconomic index group (OR=3.7, 95% CI: 1.8-7.5) and in those with a high educational level (OR=2.3, 95% CI: 1.3-4.1), high income (OR=2.6, 95% CI: 1.4-4.7), and middle and high occupational status (both OR=2.2, 95% CI: 1.3-3.6). The odds of dissatisfaction among obese women were not associated with socioeconomic status as a whole, but were associated with a high educational level, albeit with a comparatively large confidence interval (OR=3.6, 95% CI: 1.0-12.8). CONCLUSIONS: In Germany, body weight dissatisfaction is more prevalent among obese and preobese men in high socioeconomic status groups, a pattern not found in women. The exception to this is a greater prevalence of dissatisfaction among obese and preobese women with a high educational level (albeit inconsistently). Moreover, there is a social gradient in body weight dissatisfaction, especially in obese men, which may partly explain why obesity is more prevalent in men with low socioeconomic status. It also suggests that they are a target group for obesity care in which body weight satisfaction is an important topic.     

Income inequality and mortality: a multilevel prospective study of 521 248 individuals in 50 US states

BACKGROUND: Some of the most consistent evidence in favour of an association between income inequality and health has been among US states. However, in multilevel studies of mortality, only two out of five studies have reported a positive relationship with income inequality after adjustment for the compositional characteristics of the state's inhabitants. In this study, we attempt to clarify these mixed results by analysing the relationship within age-sex groups and by applying a previously unused analytical method to a database that contains more deaths than any multilevel study to date. METHODS: The US National Longitudinal Mortality Study (NLMS) was used to model the relationship between income inequality in US states and mortality using both a novel and previously used methodologies that fall into the general framework of multilevel regression. We adjust age-sex specific models for nine socioeconomic and demographic variables at the individual level and percentage black and region at the state level. RESULTS: The preponderance of evidence from this study suggests that 1990 state-level income inequality is associated with a 40% differential in state level mortality rates (95% CI = 26-56%) for men 25-64 years and a 14% (95% CI = 3-27%) differential for women 25-64 years after adjustment for compositional factors. No such relationship was found for men or women over 65. CONCLUSIONS: The relationship between income inequality and mortality is only robust to adjustment for compositional factors in men and women under 65. This explains why income inequality is not a major driver of mortality trends in the United States because most deaths occur at ages 65 and over. This analysis does suggest, however, the certain causes of death that occur primarily in the population under 65 may be associated with income inequality. Comparison of analytical techniques also suggests coefficients for income inequality in previous multilevel mortality studies may be biased, but further research is needed to provide a definitive answer.     

The Effects of Religious Attendance and Obesity on Health by Race/Ethnicity

ObjectivesThe objectives of this paper are to examine the effects of religion and obesity on health and determine how the relationship varies by racial/ethnic groups with data from the Panel Study of American Race and Ethnicity (PS-ARE).MethodsUsing ordinal logistic regression, the effects of religion and obesity on self-rated health and how the relationship varies by racial/ethnic groups are investigated. Additionally, to determine whether certain ethnic groups are more impacted by the frequency of religious attendance and obesity, whites, blacks, and Hispanics are analyzed separately with ordinal logistic regression.ResultsWhen obesity was added in focal relationship between religious services attendance and self-rated health strengthened this focal relationship which is a suppression effect between religious services attending and self-rated health adding obesity. For BMI is also significantly associated with decreased odds of reporting better health–normal weight (OR = 2.99; 95% CI = 2.43–3.67) and overweight (OR = 2.19; 95% CI = 1.79–2.68) compared to obese. Subjects who attend religious services 1–2 time a year (OR = 1.30; 95% CI = 1.04–1.62) and 1–3 times a month (OR = 1.28; 95% CI = 1.05–1.57) are associated with increased odds of reporting better health. In whites, attending religious services 1–2 times a year are associated with increased odds of reporting better health (OR = 1.48; 95% CI = 1.09–2.00) and 1–3 times a month are also associated with increased odds of reporting health (OR = 1.34; 95% CI = 1.02–1.78) compared to never attending religious attendance. The frequency of religious services attendance of blacks and Hispanics are not associated with self-rated health. For BMI, being white is more positively associated with increased odds of reporting better health than black and Hispanic subjects. Although white subjects are less likely to attend religious services more frequently than black and Hispanic subjects, the influence on self-rated health in white subjects is more evidenced than other racial/ethnic groups.ConclusionsAlthough it was not proven that the association between participation in religious services and self-rated health is mediated by obesity, the research shows the suppression effect of obesity between participation in religious services and self-rated health.     

Hearing impairment and socioeconomic factors: a population-based survey of an urban locality in southern Brazil.

OBJECTIVE: To provide the first population-based data on deafness and hearing impairment in Brazil. METHODS: In 2003, a cross-sectional household survey was conducted of 2,427 persons 4 years old and over. The study population was composed of 1,040 systematically chosen households in 40 randomly selected census tracts (dwelling clusters) in the city of Canoas, which is in the state of Rio Grande do Sul, in southern Brazil. Hearing function was evaluated in all subjects by both pure-tone audiometry and physical examination, using the World Health Organization Ear and Hearing Disorders Survey Protocol and definitions of hearing levels. The socioeconomic data that were gathered included the amount of schooling of all individuals tested and the income of the head of the household. RESULTS: It was found that 26.1% of the population studied showed some level of hearing impairment, and 6.8% (95% confidence interval (CI) = 5.5%-8.1%) were classified in the disabling hearing impairment group. The prevalence of moderate hearing loss was 5.4% (95% CI = 4.4%-6.4%); for severe hearing loss, 1.2% (95% CI = 0.7%-1.7%); and for profound hearing loss, 0.2% (95% CI = 0.03%-0.33%). The groups at higher risk for hearing loss were men (odds ratio (OR) = 1.54; 95% CI = 1.06-2.23); participants 60 years of age and over (OR = 12.55; 95% CI = 8.38-18.79); those with fewer years of formal schooling (OR = 3.92; 95% CI = 2.14-7.16); and those with lower income (OR = 1.56; 95% CI = 1.06-2.27). CONCLUSIONS: These results support advocacy by health policy planners and care providers for the prevention of deafness and hearing impairment. The findings could help build awareness in the community, in universities, and in government agencies of the health care needs that hearing problems create.     

Neighborhood sociodemographic and environmental contexts and self-rated health among Brazilian adults: a multilevel study

The aim of this study was to investigate the association between sociodemographic and environmental contexts on self-rated health. A population-based cross-sectional study with a random sample of 38 neighborhoods (census tracts) and 1,100 adults was carried out. Data analysis used multilevel logistic regression. Data from the Brazilian Census of 2000, mean income, years of study of the head of household and mean number of residents per tract were R$955 (SD = 586), 8 years (SD = 3), and 746 residents (SD = 358) respectively. Higher prevalences of fair/poor self-rated health were found in neighborhoods with greater populations and lower income/schooling levels. After control for individual variables, the odds for fair/poor self-rated health was twice as high in more populous (OR = 2.04; 95%CI: 1.15-3.61) and lower-income neighborhoods (OR = 2.29; 95%CI: 1.16-4.50) compared to less populous, higher-income ones. Self-rated health depends on individual characteristics and the sociodemographic context of neighborhoods.     

Income inequality and the double burden of under- and overnutrition in India

OBJECTIVES: Developing countries are increasingly characterised by the simultaneous occurrence of under- and overnutrition. This study examined the association between contextual income inequality and the double burden of under- and overnutrition in India. DESIGN: A population-based multilevel study of 77,220 ever married women, aged 15-49 years, from 26 Indian states, derived from the 1998-99 Indian National Family Health Survey data. The World Health Organization recommended categories of body mass index constituted the outcome, and the exposure was contextual measure of state income inequality based on the Gini coefficient of per capita consumption expenditure. Covariates included a range of individual demographic, socioeconomic, behavioural and morbidity measures and state-level economic development. RESULTS: In adjusted models, for each standard deviation increase in income inequality, the odds ratio for being underweight increased by 19% (p = 0.02) and the odds ratio for being obese increased by 21% (p<0.0001). Income inequality had a similar effect on the risk of being overweight as it did on the risk of obesity (p = 0.01), and state income inequality increased the risk of being pre-overweight by 9% (p = 0.01). While average levels of state economic development were strongly associated with degrees of overnutrition, no association was found with the risk of being underweight. CONCLUSIONS: Rapidly developing economies, besides experiencing paradoxical health patterns, are typically characterised by increased levels of income inequality. This study suggests that the twin burden of undernutrition and overnutrition in India is more likely to occur in high-inequality states. Focusing on economic equity via redistribution policies may have a substantial impact in reducing the prevalence of both undernutrition and overnutrition.     

Income inequality and elderly self-rated health in São Paulo,Brazil

PurposeTo test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship.MethodsWe analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of São Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable.ResultsIncome inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01–1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P > .05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise.ConclusionsThe health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity.