Inequalities In Self-reported Health Research Articles

Does exposure to democracy decrease health inequality?

Abstract Exposure to (a liberal) democracy can have an impact on both the political attention and visibility of the needs of marginalized populations, as well as the design of health policies that can influence the distribution of population health. This paper investigates the effect of exposure to democracy, that is, the number of years spent in a democracy as measured by democracy indexes, on various measures of inequality in self-reported health across European countries. We use an instrumental variable strategy to leverage the potential endogeneity of a country’s exposure to democracy, drawing on both bivariate (socioeconomic) and univariate health inequality measures. Our estimates provide evidence that an additional year in a democracy reduces both bivariate (income-related) health inequality and overall (univariate) health inequality. Our preferred specification suggests a two-point rank reduction in inequality with an additional year under a democracy. The effect is mainly driven by a reduction of “health poverty” alongside other effects.

Understanding health inequalities in Wales using the Blinder-Oaxaca decomposition method.

Throughout Wales and the world, health inequality remains a problem that is interconnected with a wider and complex social, economic and environmental dynamic. Subsequently, action to tackle inequality in health needs to take place at a structural level, acknowledging the constraints affecting an individual's (or community's) capability and opportunity to enable change. While the 'social determinants of health' is an established concept, fully understanding the composition of the health gap is dependent on capturing the relative contributions of a myriad of social, economic and environmental factors within a quantitative analysis. The decomposition analysis sought to explain the differences in the prevalence of these outcomes in groups stratified by their ability to save at least £10 a month, whether they were in material deprivation, and the presence of a limiting long-standing illness, disability of infirmity. Responses to over 4,200 questions within the National Survey for Wales (n = 46,189; 2016-17 to 2019-20) were considered for analysis. Variables were included based on (1) their alignment to a World Health Organization (WHO) health equity framework ("Health Equity Status Report initiative") and (2) their ability to allow for stratification of the survey sample into distinct groups where considerable gaps in health outcomes existed. A pooled Blinder-Oaxaca model was used to analyse inequalities in self-reported health (fair/poor health, low mental well-being and low life satisfaction) and were stratified by the variables relating to financial security, material deprivation and disability status. The prevalence of fair/poor health was 75% higher in those who were financially insecure and 95% higher in those who are materially deprived. Decomposition of the outcome revealed that just under half of the health gap was "explained" i.e., 45.5% when stratifying by the respondent's ability to save and 46% when stratifying by material deprivation status. Further analysis of the explained component showed that "Social/Human Capital" and "Income Security/Social Protection" determinants accounted the most for disparities observed; it also showed that "Health Services" determinants accounted the least. These findings were consistent across the majority of scenarios modeled. The analysis not only quantified the significant health gaps that existed in the years leading up to the COVID-19 pandemic but it has also shown what determinants of health were most influential. Understanding the factors most closely associated with disparities in health is key in identifying policy levers to reduce health inequalities and improve the health and well-being across populations.

Female political representation and the gender health gap: a cross-national analysis of 49 European countries.

BackgroundDoes increased female participation in the social and political life of a country improve health? Social participation may improve health because it ensures that the concerns of all people are heard by key decision-makers. More specifically, when women’s social participation increases this may lead to health gains because women are more likely to vote for leaders and lobby for policies that will enhance the health of everyone. This article tries to examine whether female participation is correlated with measures of health inequality.MethodsWe draw on data from the World Health Organization Health Equity Status Report initiative and the Varieties of Democracy project to assess whether health is better and health inequalities are smaller in countries where female political representation is greater.ResultsWe find consistent evidence that greater female political representation is associated with lower geographical inequalities in infant mortality, smaller inequalities in self-reported health (for both women and men) and fewer disability-adjusted life-years lost for women and men. Finally, we find that greater female political representation is not only correlated with better health for men and women but is also correlated with a smaller gap between men and women because men seem to experience better health in such contexts.ConclusionsGreater female political representation is associated with better health for everyone and smaller inequalities.

Employment Status and Inequalities in Self-Reported Health

Background: The aim of this study was to investigate the impact of employment status on self-reported health in Gävleborg County.Methods: The study used data from the 2010 Health in Equal terms survey, a cross-sectional survey carried out in Gävleborg County in Sweden. A total of 4,245 individuals, aged 16–65 years were included in the analysis. Descriptive and logistic regression analyses were used to assess the relationship between employment status and self-reported healthResults: People who were outside the labour market had odds of poor health of 2.64 (Cl 2.28–3.05) compared to their employed counterparts. Controlling for other covariates reduced the risk slightly to 2.10 (1.69-2.60) but remained statistically significant. In addition, other variables were associated with self-reported poor health
 Conclusion: This study found a statistically significant association between being outside the labour market and poor self-reported health. The relation was explained partially by socio-economic and demographic variables. Further studies are needed to further investigate the observed relationships. Longitudinal studies are needed to further investigate the observed relationship. Policy-makers within the Gävleborg County need to pay attention to the health status of those out of work, especially during times of combined economic and labour market fluctuations.
 
 Results of the study suggest the need to pay attention to the health status of those outside the labour market especially during times of economic hardship.

Income-related health inequality among Chinese adults during the COVID-19 pandemic: evidence based on an online survey

BackgroundPartial- or full-lockdowns, among other interventions during the COVID-19 pandemic, may disproportionally affect people (their behaviors and health outcomes) with lower socioeconomic status (SES). This study examines income-related health inequalities and their main contributors in China during the pandemic.MethodsThe 2020 China COVID-19 Survey is an anonymous 74-item survey administered via social media in China. A national sample of 10,545 adults in all 31 provinces, municipalities, and autonomous regions in mainland China provided comprehensive data on sociodemographic characteristics, awareness and attitudes towards COVID-19, lifestyle factors, and health outcomes during the lockdown. Of them, 8448 subjects provided data for this analysis. Concentration Index (CI) and Corrected CI (CCI) were used to measure income-related inequalities in mental health and self-reported health (SRH), respectively. Wagstaff-type decomposition analysis was used to identify contributors to health inequalities.ResultsMost participants reported their health status as “very good” (39.0%) or “excellent” (42.3%). CCI of SRH and mental health were − 0.09 (p < 0.01) and 0.04 (p < 0.01), respectively, indicating pro-poor inequality in ill SRH and pro-rich inequality in ill mental health. Income was the leading contributor to inequalities in SRH and mental health, accounting for 62.7% (p < 0.01) and 39.0% (p < 0.05) of income-related inequalities, respectively. The COVID-19 related variables, including self-reported family-member COVID-19 infection, job loss, experiences of food and medication shortage, engagement in physical activity, and five different-level pandemic regions of residence, explained substantial inequalities in ill SRH and ill mental health, accounting for 29.7% (p < 0.01) and 20.6% (p < 0.01), respectively. Self-reported family member COVID-19 infection, experiencing food and medication shortage, and engagement in physical activity explain 9.4% (p < 0.01), 2.6% (the summed contributions of experiencing food shortage (0.9%) and medication shortage (1.7%), p < 0.01), and 17.6% (p < 0.01) inequality in SRH, respectively (8.9% (p < 0.01), 24.1% (p < 0.01), and 15.1% (p < 0.01) for mental health).ConclusionsPer capita household income last year, experiences of food and medication shortage, self-reported family member COVID-19 infection, and physical activity are important contributors to health inequalities, especially mental health in China during the COVID-19 pandemic. Intervention programs should be implemented to support vulnerable groups.

Gender Equality and Gender Inequalities in Self-Reported Health: A Longitudinal Study of 27 European Countries 2004 to 2016.

Significant gender-based health inequalities have been observed across Europe, with women reporting worse health than men. Still, there has been little examination of how the gender–health gap has changed over time, and how it has been shaped by societal gender equality. We used data from the Statistics on Income and Living Conditions Eurostat database (EU-SILC), involving 2,931,081 participants aged 25–64, for 27 European countries. Logistic regressions were performed to model the association between self-reported bad health and gender, in general and over time. Analyses were stratified by employment, education, and clusters of countries according to levels of Gender Equality Index (GEI). Adjusting for age, year, and country, bad health was 17% more likely among women, but this disadvantage ceased after accounting for education and employment. Gender–health inequalities were larger among countries with higher GEI scores and among low-educated groups. The gender–health gap did not reduce significantly between 2004 and 2016, in general and within subgroups. Although societies are becoming more equal, persistent inequalities in employment and income still lead to sustained health differences between men and women.

Gender equality and inequalities in self-reported health in 27 European countries (2004 to 2016)

Abstract Background Across Europe, women tend to report worse health than men, probably due to women's lower position in society. Although societal gender inequalities have decreased, differences persist regarding employment, income and use of time. This study aims to assess the evolution of gender-based inequalities in 27 European countries between 2004 and 2016, and to analyze the impact of societal gender equality in this evolution. Methods We used data from the Survey on Income and Living Conditions (EU-SILC), from subjects between 25 and 64 years old (N = 2,931,081) from 27 European countries. Logistic regressions were performed with bad self-reported health as dependent variable, first adjusted for age, country and year, and later also for education and employment. Interactions between gender and year were added to the models to assess changes over time. Countries were clustered according to their societal gender equality, based on their Gender Equality Index of 2005 and 2015 (GEI). Analyzes were stratified by education, employment and cluster of GEI. Results Women were 17% (OR = 1.17, 95%CI=1.15-1.19) more likely than men to report bad health. Considering education and employment, women were 3% less likely to report bad health (OR = 0.97, 95%CI=0.96-0.99). Gender-based inequalities were larger among the cluster with higher GEI (OR = 1.37, 95%CI=1.26-1.48) and those with lower education (OR = 1.21, 95%CI=1.18-1.24). Although the gender gap reduced from 26% (OR = 1.26, 95%CI=1.18-1.34) in 2004 to 16% (OR = 1.16, 95%CI=1.08-1.24) in 2016, the decrease was not significant. Differences between years were not significant when analyses were stratified for education, employment or cluster of GEI. Conclusions Gender-based inequalities persisted between 2014 and 2016 and were strongly related to differences in education and employment. The gender gap was larger among countries with greater societal gender equality. Key messages Women’s disadvantage in self-reported health persisted in 2016 and was connected to socioeconomic differences. The gender gap is not smaller in countries with greater societal gender equality.

HEALTH INEQUALITIES: WHO IS THE MOST DISADVANTAGED AMONG THE UKRAINIAN WORKING-AGE POPULATION?

Despite inequalities in health, it is a very well developed topic, andtackling health inequalities is one of the main challenges of modern publichealth policies, these are not much explored in Ukraine.The European Social Survey data pooled together from 2004, 2006,2008, 2010, and 2012 including 6,820 Ukrainian respondents of working-age.Self-reported health was used as a dependent variable and four groups ofsocial determinants of health – as predictors. The multilevel binomial logisticregression analysis was conducted to investigate gender and social differencesin subjective health. Both genders were analyzed together and separately.Almost 60 % of the Ukrainian working-age population reported poor health.Multilevel binomial logistic regression analysis showed that respondents whowere female, married or had been divorced, and had children at home tendedto report poor health; the probability of poor health is increasing with age anddecreasing with the level of SES for both genders.Existence of between and within gender groups’ social inequalities inself-reported health as well as the most disadvantaged female subgroups arerevealed among the Ukrainian working-age population.

Gender inequality in self-reported health and its evolution in Europe between 2004 and 2016

Abstract Background That women generally have worse health than men has long been shown. Yet, the situation in Europe might have changed recently. Gender inequalities have decreased in access to education, employment, and political representation. However, women have increasingly adopted traditionally masculine unhealthy behaviors, such as smoking. Also, the Great Recession may have hurt women harder, due to their greater socioeconomic vulnerability. This study aims to analyze gender inequalities in 30 European countries, and its evolution over the 2004-2016 period. Methods We used data from the Survey on Income and Living Conditions (SILC), from people between 25 and 64 years old (N = 3,109,150). We modeled the probability of bad/very bad self-reported health as function of gender, adjusting for age, country and year, using logistic regressions. We further adjusted for education and employment. Then, we included interactions of gender and year to test changes in inequalities over time. Finally, we stratified the analysis according to countries grouped based on the Gender Development Index (GDI). Results Women were 16.8% more likely to report bad health (OR = 1.17, p &amp;lt; 0.01). Considering education and employment, women were 2.6% less likely to report bad health (OR = 0.97, p &amp;lt; 0.01). Over time, adjusting for age, the gender gap reduced from 81.1% (OR = 1.81, p &amp;lt; 0.01) in 2004 to 16.4% in 2016 (OR = 1.16, p &amp;lt; 0.01), and from 31.5% to 2.5% with socioeconomic adjustment. The reduction was larger in countries with a greater GDI. Conclusions Gender inequality has decreased, but was still present in 2016, in favor of men. This thinning is partly explained by the narrowing of inequalities in education and employment. A greater GDI has favored a larger improvement. Key messages Gender inequalities in self-reported health have narrowed over 2004-2006, following the narrowing of socioeconomic inequalities. A greater GDI has favored a larger improvement in gender inequalities.

Time spent on work-related activities, social activities and time pressure as intermediary determinants of health disparities among elderly women and men in 5 European countries: a structural equation model

BackgroundPsychosocial factors shape the health of older adults through complex inter-relating pathways. Besides socioeconomic factors, time use activities may explain gender inequality in self-reported health. This study investigated the role of work-related and social time use activities as determinants of health in old age. Specifically, we analysed whether the impact of stress in terms of time pressure on health mediated the relationship between work-related time use activities (i.e. housework and paid work) on self-reported health.MethodsWe applied structural equation models and a maximum-likelihood function to estimate the direct and indirect effects of psychosocial factors on health using pooled data from the Multinational Time Use Study on 11,168 men and 14,295 women aged 65+ from Italy, Spain, UK, France and the Netherlands.ResultsThe fit indices for the conceptual model indicated an acceptable fit for both men and women. The results showed that socioeconomic status (SES), demographic factors, stress and work-related time use activities after retirement had a significant direct influence on self-reported health among the elderly, but the magnitude of the effects varied by gender. Social activities had a positive impact on self-reported health but had no significant impact on stress among older men and women. The indirect standardized effects of work-related activities on self-reported health was statistically significant for housework (β = − 0.006; P < 0.001 among men and β = − 0.008; P < 0.001 among women) and paid work (β = 0.012; P < 0.01 among men and β = 0.000; P > 0.05 among women), which implied that the paths from paid work and housework on self-reported health via stress (mediator) was very weak because their indirect effects were close to zero.ConclusionsOur findings suggest that although stress in terms of time pressure has a direct negative effect on health, it does not indirectly influence the positive effects of work-related time use activities on self-reported health among elderly men and women. The results support the time availability hypothesis that the elderly may not have the same time pressure as younger adults after retirement.

Erratum: Depression symptoms as mediators of inequalities in self-reported health: the case of Southern European elderly.

Erratum: Depression symptoms as mediators of inequalities in self-reported health: the case of Southern European elderly.

Welfare states, the Great Recession and health: Trends in educational inequalities in self-reported health in 26 European countries.

BackgroundAlthough socioeconomic inequalities in health have long been observed in Europe, few studies have analysed their recent patterning. In this paper, we examined how educational inequalities in self-reported health have evolved in different European countries and welfare state regimes over the last decade, which was troubled by the Great Recession.MethodsWe used cross-sectional data from the EU-SILC survey for adults from 26 European countries, from 2005 to 2014 (n = 3,030,595). We first calculated education-related absolute (SII) and relative (RII) inequalities in poor self-reported health by country-year, adjusting for age, sex, and EU-SILC survey weights. We then regressed the year- and country-specific RII and SII on a yearly time trend, globally and by welfare regime, adjusting for country fixed effects. We further adjusted the analysis for the economic cycle using GDP growth, unemployment, and income inequality.ResultsOverall, absolute inequalities persisted and relative inequalities slightly widened (betaRII = 0.0313, p<0.05). There were substantial differences by welfare regime: Anglo-Saxon countries experienced the largest increase in absolute inequalities (betaSII = 0.0032, p<0.05), followed by Bismarkian countries (betaSII = 0.0024, p<0.001), while they reduced in Post-Communist countries (betaSII = -0.0022, p<0.001). Post-Communist countries also experienced a widening in relative inequalities (betaRII = 0.1112, p<0.001), which were found to be stable elsewhere. Adjustment for income inequality only explained such trend in Anglo-Saxon countries.ConclusionsEducational inequalities in health have overall persisted across European countries over the last decade. However, there is considerable variation across welfare regimes, possibly related to underpinning social safety nets and to austerity measures implemented during this 10-year period.

What Is the Role of Work-Related Factors in Self-Reported Health Inequalities among Employed Individuals? A Longitudinal Study in Luxembourg

Objectives: We measured health inequalities among employed Luxembourg residents over time and the socio-economic and work-related determinants. Design and Setting: Longitudinal data were obtained from the Socio-economic Liewen zu Letzebuerg/European Union Survey on Income and Living Conditions, which has been conducted each year since 2003 in Luxembourg. Participants: Participants comprised 727 Luxembourg residents (58% men), aged between 21 and 55 years in 2003, who were employed between 2003 and 2012. Primary and Secondary Outcomes Measured: The variable of interest was self-reported health. We used transition indicators on work-related factors to consider changes that individuals may have experienced in their job over this period. Results: People who moved from a part-time to a full-time contract (odds ratio (OR): 5.52, confidence interval (CI): 1.55 - 19.73), and those who moved from the 3rd or 4th quartile of earnings to the 1st or 2nd quartile (OR: 2.48, CI: 1.02 - 6.05) between 2003 and 2012, had a higher risk of being in poor health in 2012. The risk of deterioration in self-reported health in 2012 among people who were healthy in 2003 was associated with the type of contract, economic activity, and occupation. Conclusion: Health inequalities occur among employed people in Luxembourg. Their importance varies according to work-related characteristics and economic activity. Our findings showed that declined health status was associated with contract type, profession, and economic activity. This suggests that measures should be taken to maintain good health for people working in these specific occupations or economic sectors (e.g. preventive action, reduction of risk exposure, change of occupation in the same company, and so on).

Depression symptoms as mediators of inequalities in self-reported health: the case of Southern European elderly.

Inequalities in the distribution of self-reported health (SRH) have been widely reported. Its higher expressivity among women, elderly and least educated groups has been partly attributed to differences in their health perceptions. However, this subjectivity may be masking the burden of mental illness in these groups. Thus, we sought to understand if depression symptoms mediate inequalities in SRH. SHARE waves 4 and 6, pertaining to Spain, Italy and Portugal, were used (n2011 = 8517, n2015 = 11 046). Inequalities in SRH were calculated, comparing the risk amongst education level, gender and age groups, adjusting for chronic diseases, functional limitations and country fixed effects. We then tested depression symptoms as mediators. Depression symptoms were associated with poor SRH (odds ratio (OR)2011 = 1.379, OR2015 = 1.384, P < 0.001). Their inclusion reduced the magnitude of the association between SRH and education, annulled the statistical significance for age, and reversed the gender effect. As expected, chronic diseases and functional limitations remained significant predictors of poor SRH. Depression symptoms, together with chronic diseases and functional limitations, explain the poorer SRH of the least educated, female and older groups in the Southern European population. Therefore, tackling inequalities in SRH must require focusing on mental health issues, which disproportionately affect the most vulnerable groups.

Gender inequality in self-reported health among the elderly in contemporary welfare countries: A cross-country analysis of time use activities, socioeconomic positions and family characteristics.

BackgroundParadoxically, despite their longer life expectancy, women report poorer health than men. Time devoted to differing social roles could be an explanation for the observed gender differences in health among the elderly. The objective of this study was to explain gender differences in self-reported health among the elderly by taking time use activities, socio-economic positions, family characteristics and cross-national differences into account.MethodsData from the Multinational Time Use Study (MTUS) on 13,223 men and 18,192 women from Germany, Italy, Spain, UK and the US were analyzed. Multiple binary logistic regression models were used to examine the association between social factors and health for men and women separately. We further identified the relative contribution of different factors to total gender inequality in health using the Blinder-Oaxaca decomposition method.ResultsWhereas time allocated to paid work, housework and active leisure activities were positively associated with health, time devoted to passive leisure and personal activities were negatively associated with health among both men and women, but the magnitude of the association varied by gender and country. We found significant gender differences in health in Germany, Italy and Spain, but not in the other countries. The decomposition showed that differences in the time allocated to active leisure and level of educational attainment accounted for the largest health gap.ConclusionsOur study represents a first step in understanding cross-national differences in the association between health status and time devoted to role-related activities among elderly men and women. The results, therefore, demonstrate the need of using an integrated framework of social factors in analyzing and explaining the gender and cross-national differences in the health of the elderly population.

Lifestyle and Income-related Inequality in Health in South Africa

BackgroundMany low- and middle-income countries are experiencing an epidemiological transition from communicable to non-communicable diseases. This has negative consequences for their human capital development, and imposes a growing economic burden on their societies. While the prevalence of such diseases varies with socioeconomic status, the inequalities can be exacerbated by adopted lifestyles of individuals. Evidence suggests that lifestyle factors may explain the income-related inequality in self-reported health. Self-reported health is a subjective evaluation of people’s general health status rather than an objective measure of lifestyle-related ill-health.MethodThe objective of this paper is to expand the literature by examining the contribution of smoking and alcohol consumption to health inequalities, incorporating more objective measures of health, that are directly associated with these lifestyle practices. We used the National Income Dynamic Study panel data for South Africa. The corrected concentration index is used to measure inequalities in health outcomes. We use a decomposition technique to identify the contribution of smoking and alcohol use to inequalities in health.ResultsWe find significant smoking-related and income-related inequalities in both self-reported and lifestyle-related ill-health. The results suggest that smoking and alcohol use contribute positively to income-related inequality in health. Smoking participation accounts for up to 7.35% of all measured inequality in health and 3.11% of the inequality in self-reported health. The estimates are generally higher for all measured inequality in health (up to 14.67%) when smoking duration is considered. Alcohol consumption accounts for 27.83% of all measured inequality in health and 3.63% of the inequality in self-reported health.ConclusionThis study provides evidence that inequalities in both self-reported and lifestyle-related ill-health are highly prevalent within smokers and the poor. These inequalities need to be explicitly addressed in future programme planning to reduce health inequalities in South Africa. We suggest that policies that can influence poor individuals to reduce tobacco consumption and harmful alcohol use will improve their health and reduce health inequalities.

The social determinants of inequalities in self-reported health in Europe: findings from the European social survey (2014) special module on the social determinants of health.

Health inequalities persist between and within European countries. Such inequalities are usually explained by health behaviours and according to the conditions in which people work and live. However, little is known about the relative contribution of these factors to health inequalities in European countries. This paper aims to investigate the independent and joint contribution of a comprehensive set of behavioural, occupational and living conditions factors in explaining social inequalities in self-rated health (SRH). Data from 21 countries was obtained from the 2014 European Social Survey and examined for respondents aged 25-75. Adjusted rate differences (ARD) and adjusted rate risks (ARR), generated from binary logistic regression models, were used to measure health inequalities in SRH and the contribution of behavioural, occupational and living conditions factors. Absolute and relative inequalities in SRH were found in all countries and the magnitude of socio-economic inequalities varied considerably between countries. While factors were found to differentially contribute to the explanation of educational inequalities in different European countries, occupational and living conditions factors emerged as the leading causes of inequalities across most of the countries, contributing both independently and jointly with behavioural factors. The observed shared effects of different factors to health inequalities points to the interdependent nature of occupational, behavioural and living conditions factors. Tackling health inequalities should be a concentred effort that goes beyond interventions focused on single factors.

SOCIOECONOMIC INEQUALITIES IN SELF-REPORTED HEALTH AND PHYSICAL FUNCTIONING IN ARGENTINA: FINDINGS FROM THE NATIONAL SURVEY ON QUALITY OF LIFE OF OLDER ADULTS 2012 (ENCaViAM).

This study aimed to evaluate educational and income inequalities in self-reported health (SRH), and physical functioning (limitations in Activities of Daily Living (ADL)/Instrumental Activities of Daily Living (IADL)), among 60-year-old and older adults in Argentina. Using cross-sectional data from the Argentinian National Survey on Quality of Life of Older Adults 2012 (Encuesta Nacional sobre Calidad de Vida de Adultos Mayores, ENCaViAM), gender-specific socioeconomic inequalities in SRH and ADL and IADL limitations were studied in relation to educational level and household per capita income. The Relative Index of Inequality (RII) - an index of the relative size of socioeconomic inequalities in health - was used. Socioeconomic inequalities in the studied health indicators were found - except for limitations in ADL among women - favouring socially advantaged groups. The results remained largely significant after full adjustment, suggesting that educational and income inequalities, mainly in SRH and IADL, were robust and somehow independent of age, marital status, physical activity, the use of several medications, depression and the occurrence of falls. The findings add to the existing knowledge on the relative size of the socioeconomic inequalities in subjective health indicators among Argentinian older adults, which are to the detriment of lower socioeconomic groups. The results could be used to inform planning interventions aimed at decreasing socioeconomic inequalities in health, to the benefit of socially disadvantaged adults.

The educational gradient in self-rated health in Europe

Research suggests that doctor–patient relations have evolved from a doctor-centered, paternalistic approach towards a more patient-centered, egalitarian model of interactions between physicians and their patients. Given the long-running debate on the positive relationship between education and health, the question arises how this development in doctor–patient relations affects social inequalities in health. First, we test to what extent egalitarian (e.g. discussing treatment decisions with patients) doctor–patient relations are underlying the education–self-reported health association. Second, we test whether egalitarian and paternalistic (e.g. withholding some information from patients) doctor–patient relations show differential effects on self-reported health across educational groups. Analyses of the European Social Survey (ESS) 2004/2005 for 24 countries demonstrate that a more egalitarian doctor–patient relationship does not substantially reduce educational inequalities in self-reported health. However, some direct positive effects of egalitarian and direct negative effects of paternalistic doctor–patient relations on health ratings can be found. Finally, results show how the health status of the lower educated can improve with a more egalitarian and less paternalistic doctor–patient relationship.

Socio-economic inequalities in health and health service use among older adults in India: results from the WHO Study on Global AGEing and adult health survey

ObjectiveThe objectives of this study were to measure socio-economic inequalities in self-reported health (SRH) and healthcare visits and to identify factors contributing to health inequalities among older people aged 50-plus years. Study designThis study is based on a population-based, cross-sectional survey. MethodsWe accessed data of 7150 older adults from the World Health Organization's Study on Global AGEing and adult health Indian survey. We used multivariate logistic regression to assess the correlates of poor SRH. We estimated the concentration index to measure socio-economic inequalities in SRH and healthcare visits. Regression-based decomposition analysis was employed to explore the correlates contributing to poor SRH inequality. ResultsAbout 19% (95% CI: 18%, 20%) reported poor health (n = 1368) and these individuals were significantly less wealthy. In total, 5134 (71.8%) participants made at least one health service visit. Increasing age, female gender, low social caste, rural residence, multimorbidity, absence of pension support, and health insurance were significant correlates of poor SRH. The standardized concentration index of poor SRH –0.122 (95% CI: –0.102; –0.141) and healthcare visits 0.364 (95% CI: 0.324, 0.403) indicated pro-poor and pro-rich inequality, respectively. Economic status (62.3%), pension support (11.5%), health insurance coverage (11.5%), social caste (10.7%) and place of residence (4.1%) were important contributors to inequalities in poor health. ConclusionSocio-economic disparities in health and health care are major concerns in India. Achievement of health equity demand strategies beyond health policies, to include pro-poor, social welfare policies among older Indians.