Socioeconomic Inequalities In Self-rated Health Research Articles

An evolution of socioeconomic inequalities in self-rated health in Korea: Evidence from Korea National Health and Nutrition Examination Survey (KNHANES) 1998–2018

Reducing socioeconomic inequalities in health has become an important health policy agenda. This study aimed to measure socioeconomic inequalities in health in Korea over the past two decades and identify the contributing factors to the observed inequalities. Data from the Korea National Health and Nutrition Examination Survey (KNHANES) from 1998 to 2016/2018 were utilized. The concentration index (CI) was calculated to measure health inequalities, and decomposition analysis was applied to identify and quantify the contributing factors to the observed inequalities in health. The results indicated that health inequalities exist, suggesting that poor health was consistently more concentrated among Korean adults with lower income (1998: −0.154; 2016/2018: −0.152). Gender-stratified analyses also showed that poor health was more concentrated in lower income women and men, with the degree of inequalities slightly more pronounced among women. The decomposition approach revealed that income and educational attainment were the largest contributors to the observed health inequalities as higher income and education associated with better self-rated health. These findings suggest the importance of considering socioeconomic determinants, such as income and education, in efforts to tackling health inequalities, particularly considering that self-rated health is a predictor of future mortality and morbidity. Furthermore, it is essential to implement more egalitarian social, labour market, and health policies in order to eliminate the existing socioeconomic inequalities in health in Korea.

Trends in socioeconomic inequalities in self-rated health and mental distress during four decades in a Norwegian population: a HUNT Study

Trends in socioeconomic inequalities in self-rated health and mental distress during four decades in a Norwegian population: a HUNT Study

Sociodemographic decomposition of inequality in self-rated health: A cross-sectional study in Hubei, China

Objectives: Health inequality is associated with profound social, health and economic costs. Despite extensive studies about inequality in health outcomes, our understanding of inequality in self-rated health is quite limited. This study aimed to determine the inequality in self-rated health and its associated factors in Hubei populations, China. Methods: A cross-sectional questionnaire survey was conducted on the community residents purposively selected from six municipalities in Hubei province, China. Participants were asked to rate their health on a five-point Likert scale, ranging from 1 to 5. A total of 1336 valid questionnaires were collected. Inequality in self-rated health was assessed using concentration index and further decomposed to measure sociodemographic inequality in the health of residents. Results: Two thirds (66%) of respondents rated their health as “excellent/very good/good”, while 34% rated it as fair or poor. The income-related concentration index was 0.0321 (95% CI, 0.0229 to 0.0413), indicating a concentration of poor self-rated health in the low-income groups. The CI of SRH in urban areas was 0.0239, which was lower than that in rural areas (0.0379). Age (17.5%) made the biggest contribution to the inequality in SRH, which was followed by employment (15.7%), income (8.5%), education (4.5%) and physical exercise (3.0%). Conclusions: There exist socioeconomic inequalities in self-rated health in Hubei, China. Policy priorities should be given to rural area, the older people and those with low economic participation.

Socioeconomic inequalities in self-rated health in Japan, 32 European countries and the United States: an international comparative study.

Japan is known as a country with low self-rated health despite high life expectancy. We compared socioeconomic inequalities in self-rated health in Japan with those in 32 European countries and the US using nationally representative samples. We analysed individual data from the Comprehensive Survey of Living Conditions (Japan), the European Union Statistics on Income and Living Conditions, and the Behavioral Risk Factor Surveillance System (US) in 2016. We used ordered logistic regression models with four ordinal categories of self-rated health as an outcome, and educational level or occupational class as independent variables, controlling for age. In Japan, about half the population perceived their health as 'fair', which was much higher than in Europe (≈20-40%). The odds ratios of lower self-rated health among less educated men compared with more educated were 1.72 (95% confidence interval (CI) 1.61-1.85) in Japan, and ranged from 1.67 to 4.74 in Europe (pooled; 2.10 (95% CI 2.01-2.20)), and 6.65 (95% CI 6.22-7.12) in the US. The odds ratios of lower self-rated health among less educated women were 1.79 (95% CI 1.65-1.95) in Japan, and ranged from 1.89 to 5.30 in Europe (pooled; 2.43 (95% CI 2.33-2.54)), and 8.82 (95% CI 8.29-9.38) in the US. Socioeconomic inequalities were large when self-rated health was low for European countries, but Japan and the US did not follow the pattern. Japan has similar socioeconomic gradient patterns to European countries for self-rated health, and our findings revealed smaller socioeconomic inequalities in self-rated health in Japan compared with those in western countries.

Mediation Effect of Metal Mixtures in the Association Between Socioeconomic Status and Self-rated Health Among US Adults: A Weighted Quantile Sum Mediation Approach

This study aimed to examine the association between socioeconomic status (SES) and self-rated health (SRH) among US adults and the extent to which blood and urinary metal mixtures explain this association. We used 14 years of repeated cross-sectional data that consists of seven consecutive NHANES cycles from 2003 to 2016 (n = 9497). SRH was measured using a 5-point Likert scale, and SES was measured by family income to poverty ratio (FMPIR), levels of education, and employment status. Blood concentration of lead, mercury, and cadmium, and urinary concentrations of ten heavy metals (arsenic, barium, cadmium, cesium, cobalt, lead, mercury, molybdenum, thallium, tungsten) were used as metal mixtures. The total effect of SES on SRH was examined by linear regression model. The direct effect of SES on blood and urinary metal mixtures was examined by the weighted quantile sum (WQS) regression with repeated holdout validation method, and the average causal mediation effects of blood and urinary metal mixtures were examined by model-based causal mediation technique. Results showed that SES indicators [education β: 0.17; 95% Confidence Interval (CI): 0.15, 0.18; employment β: 0.16; 95% CI: 0.12, 0.21; and FMPIR β: 0.09; 95% CI: 0.08, 0.11] were significantly positively, and the WQS indices of blood and urine metal mixtures (blood β: −0.04; 95% CI: − 0.05, − 0.03, urine β: − 0.07; 95% CI: − 0.13, − 0.004) were significantly inversely associated with SRH in the US adults. The novel finding was the mechanism between SES and SRH that exposure to heavy metals may explain socioeconomic inequalities in SRH in the US general population. Longitudinal studies are needed to corroborate this study results.

Trends and socioeconomic inequalities in self-rated health in Japan, 1986\u20132016

IntroductionDespite having very high life expectancy, Japan has relatively poor self-rated health, compared to other high-income countries. We studied trends and socioeconomic inequalities in self-rated health in Japan using nationally representative data.MethodsThe Comprehensive Survey of Living Conditions was analyzed, every 3 years (n ≈ 0.6–0.8 million/year) from 1986 to 2016. Whereas previous studies dichotomized self-rated health as an outcome, we used four categories: very good, good, fair, and bad/very bad. Proportional odds ordinal logistic regression models are used, with ordinal scale self-rated health as an outcome, and age category, survey year and occupational class or educational level as independent variables.ResultsIn 2016, the age-adjusted percentages for self-rated health categorized as very good, good, fair, and bad/very bad, were 24.0, 17.1, 48.7, and 10.2% among working-age men, and 21.6, 17.5, 49.4, and 11.5% among working-age women, respectively. With 1986 as the reference year, the odds ratios (ORs) of less good self-rated health were lowest in 1995 (0.69; 95% Confidence Interval [95% CI]: 0.66–0.71 of working-age men), and highest in 2010 (1.23 [95% CI: 1.19–1.27]). The ORs of male, lower non-manual workers (compared to upper non-manual) increased from 1.12 (95% CI: 1.07–1.17) in 2010 to 1.20 (95% CI: 1.15–1.26) in 2016. Between 2010 and 2016, the ORs of working-age men with middle and low levels of education (compared to a high level of education) increased from 1.22 (95% CI: 1.18–1.27) to 1.34 (95% CI: 1.29–1.38), and from 1.47 (95% CI: 1.39–1.56) to 1.75 (95% CI: 1.63–1.88), respectively. The ORs of working-age women with middle and low levels of education also increased from 1.22 (95% CI: 1.17–1.28) to 1.32 (95% CI: 1.26–1.37), and from 1.74 (95% CI: 1.61–1.88) to 2.03 (95% CI: 1.87–2.21) during the same period.ConclusionJapan has the unique feature that approximately 50% of the survey respondents rated their self-rated health as fair, but with important variations over time and between socioeconomic groups. In-depth studies of the role of socioeconomic conditions may shed light on the reasons for the high prevalence of poor self-rated health in Japan.

Linear trend or graded association: an international study of objective and subjective socioeconomic inequalities in self-rated health

Despite the well-documented socioeconomic inequalities in health, it is less known about how objective and subjective socioeconomic statuses (SES) are related to self-rated health (SRH) in an international context. Using data from the 2007 International Social Survey Program (ISSP) that included 33 countries across six continents (N = 40,049), we found that for objective SES, either education or income, or both were related to SRH as general linear trends (i.e., higher SES was associated with better SRH as a general trend) rather than graded associations (i.e., adjacent levels of SES were associated with SRH in a dose–response relationship). After controlling for subjective SES, the magnitude of the associations between objective SES and SRH reduced, whereas the associations between subjective SES and SRH remained strong in nearly all countries. Findings suggested that more rigorous analyses are needed to clearly describe the SES-health associations, and future international research should expand to include subjective measures of SES.

Socioeconomic disparities in self-rated health in two East Asian countries: Comparative study between Japan and Korea.

Although Japan and South Korea share a number of commonalities, social security systems are very different. We opt to compare socioeconomic disparities in self-rated health between these two countries. The analytic sample included those aged 20 years and older from the nationally representative surveys in Japan (Comprehensive Survey of Living Conditions) and South Korea (Korean Community Health Survey). As socioeconomic status, we used income (quintiles of equivalized annual household income) and education (five categories). We measured socioeconomic inequalities using two indices; the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII), in each age group for each country. In Japan, we found relatively little evidence of socioeconomic inequalities in self-rated health over the life course, on either the absolute or relative scale. In Korea, the absolute inequality assessed by SII of self-rated poor health was higher in middle and old age groups compared to other age groups, while relative inequality measured by RII was significantly higher in younger ages. In Japan with more generous welfare system to the older generations, health inequality was relatively lower compared to Korea. The gaps in health status for Korean people suggest where social policy might direct their efforts in the future - (a) reducing inequalities in working-age people by addressing the gap between standard workers & non-standard workers; and (b) improving the financial conditions of older people by shoring up the social security system.

Trends in socioeconomic inequalities in self-rated health in Germany: a time-trend analysis of repeated cross-sectional health surveys between 2003 and 2012

ObjectivesThis study assessed the extent of educational and income inequalities in self-rated health (SRH) in the German adult population between 2003 and 2012 and how these inequalities changed over time.DesignRepeated...

Socioeconomic inequalities in self-rated health: role of work-to-family conflict in married Korean working women

ABSTRACTLittle evidence exists on the role of work-to-family conflict (WFC) in explaining socioeconomic inequality in self-rated health (SRH). We examined the association between socioeconomic status (SES) and SRH and tested the mediating effect of WFC in the association between SES and SRH among married Korean working women. A cross-sectional study was conducted using data from the 2014 Korean Longitudinal Survey of Women and Family. Participants were 3,226 women. Three SES indicators were used: income as measured by income-to-needs ratio; education categorized into college vs. noncollege education levels; and occupation classified by white vs. pink/blue-collar occupations. Lower levels of all the SES indicators were significantly associated with poor SRH and higher levels of WFC. The higher levels of WFC were also significantly associated with poor SRH. In the relation between SES and SRH, WFC showed a partial mediating effect for income (z = −4.13, p < .001) and full mediating effects for education (z = −3.79, p < .001) and occupation (z = −4.59, p < .001). WFC played a mediating role in explaining socioeconomic health inequality among married Korean working women. Workplace strategies focused on alleviating the WFC levels of socioeconomically disadvantaged married women may be crucial for improving their health status.

The contribution of work and lifestyle factors to socioeconomic inequalities in self-rated health ‒ a systematic review.

Objective This study aimed to systematically review the literature on the contribution of work and lifestyle factors to socioeconomic inequalities in self-rated health among workers. Methods A search for cross-sectional and longitudinal studies assessing the contribution of work and/or lifestyle factors to socioeconomic inequalities in self-rated health among workers was performed in PubMed, PsycINFO and Web of Science in March 2017. Two independent reviewers performed eligibility and risk of bias assessment. The median change in odds ratio between models without and with adjustment for work or lifestyle factors across studies was calculated to quantify the contribution of work and lifestyle factors to health inequalities. A best-evidence synthesis was performed. Results Of those reviewed, 3 high-quality longitudinal and 17 cross-sectional studies consistently reported work factors to explain part (about one-third) of the socioeconomic health inequalities among workers (grade: strong evidence). Most studies separately investigated physical and psychosocial work factors. In contrast with the 12 cross-sectional studies, 2 longitudinal studies reported no separate contribution of physical workload and physical work environment to health inequalities. Regarding psychosocial work factors, lack of job resources (eg, less autonomy) seemed to contribute to health inequalities, whereas job demands (eg, job overload) might not. Furthermore, 2 longitudinal and 4 cross-sectional studies showed that lifestyle factors explain part (about one-fifth) of the health inequalities (grade: strong evidence). Conclusions The large contribution of work factors to socioeconomic health inequalities emphasizes the need for future longitudinal studies to assess which specific work factors contribute to health inequalities.

Trends in socioeconomic inequalities in self-rated health, smoking, and physical activity of Japanese adults from 2000 to 2010

Health disparities in Japan are attracting increasing attention. Temporal trends in health disparities should be continuously monitored using multiple indices of socioeconomic status (SES) and health-related outcomes. We explored changes in socioeconomic differences in the health of Japanese adults during 2000–2010. The data was taken from the Japanese General Social Surveys, the cross-sectional surveys for nationally representative samples of Japanese adults. We used 14,193 samples (individuals of 20–64 years of age) in our analysis. We estimated age-adjusted prevalence ratios of the lowest SES group in comparison with the highest SES group using Poisson regression models with robust error variance. Relative index of inequality (RII) and slope index of inequality (SII) were also calculated. We examined the changes in the association between health-related outcomes (self-rated health (SRH), smoking, and physical activity) and SES indices (income, education, occupation, and subjective social class identification). The results showed temporally expanding trends for the associations of current smoking with SES, especially among women, in both relative and absolute measures. In contrast, no expanding trends were seen for SRH and physical activity. Although the smoking rates declined through the first decade of the 21st century, the socioeconomic disparities in smoking prevalence among Japanese adults expanded, especially among women. Researchers and policymakers should continuously monitor the trends that may cause future disparities in smoking-related morbidity and mortality.

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

BackgroundIn 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.MethodsData 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.ResultsThere 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.ConclusionsUsing 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.

Socioeconomic Inequalities in Self-Rated Health Among Middle-Aged and Older Adults

Despite increased attention to health disparities in the United States, few studies have examined the impact of socioeconomic inequalities on self-rated health over time. Using data from the Health and Retirement Study, this article investigates socioeconomic inequalities in self-rated health among middle-aged and older adults. The findings indicated that higher level of income, assets, and education, and having private health insurance predicted better self-rated health. In particular, increases in income or assets predicted slower decline in self-rated health. Interestingly, economic status had greater impact on females' decline in self-rated health. Blacks were less likely to suffer rapid decline in self-rated health than were whites. The findings led to the conclusion that health disparities should be understood as the interplay of socioeconomic status, gender, and race/ethnicity.

Socioeconomic Variation in the Magnitude of the Association between Self-Rated Health and Mortality

To assess socioeconomic variation in the association between self-rated health (SRH) and mortality and to determine whether socioeconomic inequalities in SRH and socioeconomic inequalities in mortality differ in magnitude. We used data from a cohort of Spanish people 60 years of age and older with an 8-year follow-up of mortality. The association between SRH at baseline and mortality was estimated by the age-adjusted relative risk of mortality in people with low, medium, and high education. The measures of health inequalities were the prevalence ratio of poor SRH and the age-adjusted relative risk of mortality according to educational level. The validity of SRH to reflect life-threatening and non-life-threatening health conditions was summarized with the likelihood ratio for poor SRH in each educational category. The relative risk of mortality according to SRH in subjects with high and low education was 3.24 and 1.62 in men and 2.25 and 1.50 in women, respectively. Inequalities in poor self-rated health were larger than inequalities in mortality: -1.63 versus 1.07 in men and 1.45 versus 1.30 in women. The highest likelihood ratio for SRH was seen in persons with high education in the case of life-threatening conditions, and for those with low education, in the case of non-life-threatening conditions. Socioeconomic variation in the validity of SRH to reflect life-threatening and non-life-threatening conditions could explain the greater ability of SRH to predict mortality in persons with high education and why inequalities in poor SRH are larger than inequalities in mortality.

Health inequalities in Israel: Explanatory factors of socio-economic inequalities in self-rated health and limiting longstanding illness

We examined an integrated multi-level model of psychosocial, community and behavioral factors as explanatory pathways to socio-economic inequalities in health in Israel. Using a random national sample of 1328 individuals aged 30–70 and measurements of socio-economic position (education, number of cars), health outcomes—self-rated health, limiting longstanding illness (LLI), we evaluated the contribution of psychosocial factors (stressors and psychosocial resources), community factors (individual and aggregate-level social participation and social capital) and health behaviors, to the explanation of health inequalities. Community factors contributed more than psychosocial factors or health behaviors. The integrative model provided an explanation of social inequalities in both health outcomes and a full explanation for the education-LLI association.

An assessment of socio-economic inequalities in health among elderly in Greece, Italy and Spain

This study explores socio-economic inequalities in health among Mediterranean people aged 50 or higher. The data used in the analysis come from the Survey of Health, Ageing and Retirement in Europe, wave 1, release 2; the sample includes 2,671 Greek, 2,502 Italian and 2,343 Spanish persons. Seven health indicators are examined using age-sex standardized prevalence rates and logistic regression models. Concentration indices are also computed for self-rated health (SRH). Socio-economic position of individuals declines with age. Persons of lower socio-economic position experience worse health in all instances. Independently of education and gender, Greek persons display the lowest prevalence rates for SRH and physical and depressive symptoms, Spanish exhibit the highest rates for chronic conditions, and Italians perform better regarding functional limitations. Within-country analysis shows that the magnitude of socio-economic inequalities in SRH is greatest in Greece, followed by Spain and lastly by Italy. The analysis reconfirms the advantage of high over low socio-economic position for all countries and health indicators and proves education as an important correlate compared to wealth and income among the elderly.

Physical and psychosocial working conditions as explanations for occupational class inequalities in self-rated health

Socio-economic health inequalities are well documented, but efforts to explain health inequalities are less. However, previous studies suggest that working conditions provide potential explanations for inequalities in health. Cross-sectional questionnaire survey data, collected from municipal employees of the City of Helsinki, aged 40-60 years (n = 8960, response rate 67%) in 2000-02, were examined using binomial regression analysis. Socio-economic position was measured by six occupational social classes ranging from top managers to manual workers, and the outcome was self-rated health (SRH). Key physical and psychosocial working conditions and work arrangements were included as explanatory factors for inequalities in health. Occupational class inequalities in SRH were clear among women [prevalence ratio (PR) 1.89, 95% confidence interval (CI) 1.54-2.32] and men (PR 1.78, 95% CI 1.40-2.25). Heavy physical workload explained a half of the health inequalities among women and almost one-third among men. Physical and chemical exposures at work explained one-fifth of the health inequalities among women and a half among men. Job control explained 24% of the men's and 40% of women's inequalities, whereas job demands widened the inequalities by 13-14%. The effects of shift work and working hours were negligible. In the fully adjusted model, 60% of the women's and 32% of the men's inequalities in SRH were explained. Physical working conditions explained a large part and job control, a somewhat smaller part of socio-economic inequalities in SRH. Improving physical working conditions and increasing job control provide potential routes to reduced inequalities in health among employees.

Socioeconomic Position and Self-Rated Health: The Contribution of Childhood Socioeconomic Circumstances, Adult Socioeconomic Status, and Material Resources

We examined socioeconomic inequalities in self-rated health by analyzing indicators of childhood socioeconomic circumstances, adult socioeconomic position, and current material resources. We collected data on middle-aged adults employed by the City of Helsinki (n=8970; 67% response rate). Associations between 7 socioeconomic indicators and health self-ratings of less than "good" were examined with sequential logistic regression models. After adjustment for age, each socioeconomic indicator was inversely associated with self-rated health. Childhood economic difficulties, but not parental education, were associated with health independently of all other socioeconomic indicators. The associations of respondents' own education and occupational class with health remained when adjusted for other socioeconomic indicators. Home ownership and economic difficulties, but not household income, were the material indicators associated with health after full adjustment. Own education and occupational class showed consistent associations with health, but the association with income disappeared after adjustment for other socioeconomic indicators. The effect of parental education on health was mediated by the respondent's own education. Both childhood and adulthood economic difficulties showed clear associations with health and with conventional socioeconomic indicators.