Gender, ethnicity, health behaviour & self-rated health in Singapore

10.1186/1471-2458-7-184BMC Public Health718

Socioeconomic inequality in domains of health: results from the World Health Surveys

<p>Abstract</p> <p>Background</p> <p>In all countries people of lower socioeconomic status evaluate their health more poorly. Yet in reporting overall health, individuals consider multiple domains that comprise their perceived health state. Considered alone, overall measures of self-reported health mask differences in the domains of health. The aim of this study is to compare and assess socioeconomic inequalities in each of the individual health domains and in a separate measure of overall health.</p> <p>Methods</p> <p>Data on 247,037 adults aged 18 or older were analyzed from 57 countries, drawn from all national income groups, participating in the World Health Survey 2002-2004. The analysis was repeated for lower- and higher-income countries. Prevalence estimates of poor self-rated health (SRH) were calculated for each domain and for overall health according to wealth quintiles and education levels. Relative socioeconomic inequalities in SRH were measured for each of the eight health domains and for overall health, according to wealth quintiles and education levels, using the relative index of inequality (RII). A RII value greater than one indicated greater prevalence of self-reported poor health among populations of lower socioeconomic status, called pro-rich inequality.</p> <p>Results</p> <p>There was a descending gradient in the prevalence of poor health, moving from the poorest wealth quintile to the richest, and moving from the lowest to the highest educated groups. Inequalities which favor groups who are advantaged either with respect to wealth or education, were consistently statistically significant in each of the individual domains of health, and in health overall. However the size of these inequalities differed between health domains. The prevalence of reporting poor health was higher in the lower-income country group. Relative socioeconomic inequalities in the health domains and overall health were higher in the higher-income country group than the lower-income country group.</p> <p>Conclusions</p> <p>Using a common measurement approach, inequalities in health, favoring the rich and the educated, were evident in overall health as well as in every health domain. Existent differences in averages and inequalities in health domains suggest that monitoring should not be limited only to overall health. This study carries important messages for policy-making in regard to tackling inequalities in specific domains of health. Targeting interventions towards individual domains of health such as mobility, self-care and vision, ought to be considered besides improving overall health.</p

Functional and self-rated health mediate the association between diabetes and depression

Depression is common among persons with diabetes and associated with adverse health outcomes. To date, little is known about the causal mechanisms that lead to depression in diabetes. The aim of the present study was to examine to which extent functional and self-rated health mediate the association between physical health and depressive symptoms in diabetes. Data of n = 3222 individuals with type 2 diabetes were analyzed cross-sectionally and longitudinally at three measurement occasions using path analysis. Indicators of physical health were glycemic control, number of comorbid somatic diseases, BMI, and insulin dependence. Furthermore, functional health, self-rated health and depressive symptoms were assessed. The effects of physical health on depressive symptoms were largely mediated by functional health and self-rated health. There was only a weak indirect effect of physical health on depressive symptoms. In contrast, self-rated health was a strong direct predictor of depressive symptoms. Self-rated health in turn depended strongly on patients’ functional health. The way individuals perceive their health appears to have a stronger effect on their depressive symptoms than objective physical indicators of diabetes. Therefore practitioners should be trained to pay more attention to their patients’ subjective health perceptions

A simple measure with complex determinants: investigation of the correlates of self-rated health in older men and women from three continents

Self-rated health is commonly employed in research studies that seek to assess the health status of older individuals. Perceptions of health are, however, influenced by individual and societal level factors that may differ within and between countries. This study investigates levels of self-rated health (SRH) and correlates of SRH among older adults in Australia, United States of America (USA), Japan and South Korea. We conclude that when examining correlates of SRH, the similarities are greater than the differences between countries. There are however differences in levels of SRH which are not fully accounted for by the health correlates. Broad generalizations about styles of responding are not helpful for understanding these differences, which appear to be country- and possibly cohort-specific. When using SRH to characterize the health status of older people, it is important to consider earlier life experiences of cohorts as well as national and individual factors in later life. Further research is required to understand the complex societal influences on perceptions of health.The Australian data on which this research is based were drawn from several Australian longitudinal studies including: the Australian Longitudinal Study of Ageing (ALSA), the Australian Longitudinal Study of Women’s Health (ALSWH) and the Personality And Total Health Through Life Study (PATH). These studies were pooled and harmonized for the Dynamic Analyses to Optimize Ageing (DYNOPTA) project. DYNOPTA was funded by a National Health and Medical Research Council (NHMRC) grant (# 410215)

Gender differences in marital status moderation of genetic and environmental influences on subjective health

From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health

Predictors of mortality: an international comparison of socio-demographic and health characteristics from six longitudinal studies on aging: the CLESA project

PURPOSE: Multiple factors contribute to mortality in the elderly, but the extent to which traditional factors contribute independently to mortality in different countries is not known. Our objective is to determine the differential impact of socio-demographic variables, selected diseases, health habits and disability on all-cause mortality, among older people living in five European countries and Israel. METHODS: From six longitudinal studies on aging (TamELSA-Tampere (Finland), CALAS-Israel, ILSA-Italy, LASA-Netherlands, AL-Leganes (Spain), SATSA-Sweden), a harmonized common database was created in the context of the CLESA Project (Cross-national determinants of quality of life and health services for the elderly). A common five-year follow-up was used. RESULTS: The highest mortality rate was found in Tampere among females (98.7%) and in Israel among males (108.3%), whereas the lowest was observed in Leganes for males (72.3%) and in The Netherlands for females (44.6%). In multivariate models, some predictors were homogeneously, significantly distributed across the six countries, including older age (HR = 1.57) and male sex (HR = 1.60) among the socio-demographic variables; smoking status (HR = 1.15) and alcohol consumption (HR = 0.81) among the health habits variables; presence of heart disease (HR = 1.34), diabetes (HR = 1.46), cancer (HR = 1.93), respiratory disease (HR = 1.19), and disability (HR = 2.92) among the health status variables. Marital status, education, and drug use did not have homogeneous effects in the six countries. DISCUSSION: This large international study shows that multiple factors contribute to increased risk of all cause mortality among older people and that most risk factors are similar across countries. Disability, age greater than 80 years, cancer and male sex were identified as the strongest common risk factors of mortalit