• Journal of Preventive Medicine and Public Health
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• v.53 no.4
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• pp.266-274
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• 2020

Objectives: Describe out-of-pocket payment (OOP) and the proportion of Peruvian households with catastrophic health expenditure (CHE) and evaluate changes in socioeconomic inequalities in CHE between 2008 and 2017. Methods: We used data from the 2008 and 2017 National Household Surveys on Living and Poverty Conditions (ENAHO in Spanish), which are based on probabilistic stratified, multistage and independent sampling of areas. OOP was converted into constant dollars of 2017. A household with CHE was assumed when the proportion between OOP and payment capacity was ≥0.40. OOP was described by median and interquartile range while CHE was described by weighted proportions and 95% confidence intervals (CIs). To estimate the socioeconomic inequality in CHE we computed the Erreygers concentration index. Results: The median OOP reduced from 205.8 US dollars to 158.7 US dollars between 2008 and 2017. The proportion of CHE decreased from 4.9% (95% CI, 4.5 to 5.2) in 2008 to 3.7% (95% CI, 3.4 to 4.0) in 2017. Comparison of socioeconomic inequality of CHE showed no differences between 2008 and 2017, except for rural households in which CHE was less concentrated in richer households (p<0.05) and in households located on the rest of the coast, showing an increase in the concentration of CHE in richer households (p<0.05). Conclusions: Although OOP and CHE reduced between 2008 and 2017, there is still socioeconomic inequality in the burden of CHE across different subpopulations. To reverse this situation, access to health resources and health services should be promoted and guaranteed to all populations.

• Journal of Preventive Medicine and Public Health
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• v.40 no.5
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• pp.381-387
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• 2007

Objectives: This study was conducted in order to determine how the association between socioeconomic position(SEP) and health status changes with age among Seoul residents aged 25 and over. Methods: We utilized the 2001 and 2005 Seoul Citizens Health Indicators Surveys. We used self-rated 'poor' health status as an outcome variable, and family income as an indicator of SEP. In order to characterize the differential effects of socioeconomic position on health by age, we conducted separate multivariate analyses by 10-year age groups, controlling for sociodemographic covariates. In order to assess the relative health inequality across socioeconomic groups, we estimated the Relative Index of Inequality (RII). Results: The risk of 'poor health' is significantly high in low family income groups, and this increased risk is seen at all ages. However, the magnitude of relative socioeconomic inequality in health, as measured by the odds ratio and RII, is not identical across age groups. The difference in health across income groups is small in early adulthood (ages 25-34), but increases with age until relatively late in life (ages 35-64). It then decreases among the elderly population (ages more than 65). When the RII reported in 2005 is compared to that reported in 2001, RII can be seen to have increased across all ages, with the exception of individuals aged 25-34. Conclusions: The magnitude of health inequality is the greatest during mid- to late adulthood (ages 45-64). In addition, health inequalities have worsened between 2001 and 2005 across all age groups after economic crisis.

• International Area Studies Review
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• v.20 no.2
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• pp.175-194
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• 2016

In this study, we aimed to identify the impact of socioeconomic characteristics on the health status of Chinese, which suggests that there might be the phenomena of health inequality in China. We used the year 2000, 2004 and 2009 pooled cross-sectional data of China Health and Nutrition Survey (CHNS), and utilized the Ordinary Least Square model (OLS) and Ordered Logit Estimation Method for this purpose. Empirical results showed that socioeconomic status and year dummy variables have a meaningful impact on Chinese health status. Therefore, we conclude that the phenomenon of health inequality has existed in China since 2000.

• Journal of Preventive Medicine and Public Health
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• v.38 no.3
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• pp.359-365
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• 2005

Objectives : An abrupt economic decline may widen the socioeconomic differences in health between the advantaged and disadvantaged in a society. The aim of this study was to examine whether the South Korean economic crisis of 1997-98 affected the socioeconomic inequality from all-causes and from cause-specific mortality between 1995 and 2001. Methods : Population denominators were obtained from the registration population data, with the number of death (numerators) calculated from raw death certificate data. The indicator used to assess the geographic socioeconomic position was the per capita regional tax revenue. Administrative districts (Si-Gun-Gu) were ranked according to this socioeconomic measure, and divided into equal population size quintiles on the basis of this ranking. The sex- and 5-year age-specific numbers of the population and deaths were used to compute the sex- and age-adjusted mortality rates (via direct standardization method), standardized mortality ratios (via indirect standardization methods) and relative indices of inequality (RII) (via Poisson regression). Results : Geographic inequalities from all-causes of mortality, as measured by RII, did not increase as a result of the economic crisis (from 1998-2001). This was true for both sexes and all age groups. However, the cause-specific analyses showed that socioeconomic inequalities in mortalities from external causes were affected by South Korean economic crisis. For males, the RIIs for mortalities from transport accidents and intentional self-harm increased between 1995 and 2001. For females, the RII for mortality from intentional self-harm increased during the same period. Conclusions : The South Korean economic crisis widened the geographic inequality in mortalities from major external causes. This increased inequality requires social discourse and counter policies with respect to the rising health inequalities in the South Korean society.

• Health Policy and Management
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• v.25 no.4
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• pp.277-284
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• 2015

Background: This study investigates the relationship of socioeconomic status with adverse birth outcomes (low birth weight, preterm birth) and the relationship of socioeconomic status with infant mortality, using the birth cohort in Korea, 1995-2010. Methods: 8,648,035 births from National Statistics Offics, 1995-2010 were studied with respect to social variation in adverse birth outcomes and infant mortality in Korea. The effect of social inequality was examined against adverse birth outcomes and infant mortality using multivariate logistic regression after controlling for other covariates. Results: Social inequality were observed in adverse birth outcomes: low birth weight (LBW, 1,500-2,499 g), very LBW (1,000-1,499 g), and extremely LBW (500-999 g) as well as moderately preterm birth (PTB, 33-36 weeks), very PTB (28-32 weeks), extremely PTB (22-27 weeks), and infant mortality. The effect of social inequality was higher among moderately LBW (1,500-2,499 g) and PTB (33-36 weeks) than very or extremely LBW and PTB. Conclusion: The social inequality in adverse birth outcomes (low birth weight and preterm) and infant mortality existed and increased in Korea from 1995 to 2010. The effect of maternal education on adverse birth outcomes as well as infant mortality was apparent in the study results. Especially, social inequailiy in infant mortality was greater among the sub-normal births (low birth weight [1,500-2,499 g] or preterm birth [33-36 weeks]), which suggests, social interventions should aim at more among the subnormal births. This study suggest that tackling inequality in births as well as infant mortality should be focused on the social inequality itself.

• Journal of Preventive Medicine and Public Health
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• v.51 no.6
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• pp.289-297
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• 2018

Objectives: Obesity is a considerable and growing public health concern worldwide. The present study aimed to quantify socioeconomic inequalities in adult obesity in western Iran. Methods: A total of 10 086 participants, aged 35-65 years, from the Ravansar Non-communicable Disease Cohort Study (2014-2016) were included in the study to examine socioeconomic inequalities in obesity. We defined obesity as a body mass index ${\geq}30kg/m^2$. The concentration index and concentration curve were used to illustrate and measure wealth-related inequality in obesity. Additionally, we decomposed the concentration index to identify factors that explained wealth-related inequality in obesity. Results: Overall, the prevalence of obesity in the total sample was 26.7%. The concentration index of obesity was 0.04; indicating that obesity was more concentrated among the rich (p<0.001). Decomposition analysis indicated that wealth, place of residence, and marital status were the main contributors to the observed inequality in obesity. Conclusions: Socioeconomic-related inequalities in obesity among adults warrant more attention. Policies should be designed to reduce both the prevalence of obesity and inequalities in obesity by focusing on those with higher socioeconomic status, urban residents, and married individuals.

• Journal of Preventive Medicine and Public Health
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• v.41 no.3
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• pp.186-194
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• 2008

Objectives : This study describes trends in the socioeconomic disparities in breast cancer screening among US women aged 40 or over, from 2000 to 2005. We assessed 1) the disparities in each socioeconomic dimension; 2) the changes in screening mammography rates over time according to income, education, and race; and 3) the sizes and trends of the disparities over time. Methods : Using data from the Behavioral Risk Factor Surveillance System (BRFSS) from 2000 to 2005, we calculated the age-adjusted screening rate according to relative household income, education level, health insurance, and race. Odds ratios and the relative inequality index (RII) were also calculated, controlling for age. Results : Women in their 40s and those with lower relative incomes were less likely to undergo screening mammography. The disparity based on relative income was greater than that based on education or race (the RII among low-income women across the survey years was 3.00 to 3.48). The overall participation rate and absolute differences among socioeconomic groups changed little or decreased slightly across the survey years. However, the degree of each socioeconomic disparity and the relative inequality among socioeconomic positions remained quite consistent. Conclusions : These findings suggest that the trend of the disparity in breast cancer screening varied by socioeconomic dimension. Continued differences in breast cancer screening rates related to income level should be considered in future efforts to decrease the disparities in breast cancer among socioeconomic groups. More focused interventions, as well as the monitoring of trends in cancer screening participation by income and education, are needed in different social settings.

• Journal of Preventive Medicine and Public Health
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• v.40 no.6
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• pp.475-486
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• 2007

Objectives : Socioeconomic position (SEP) refers to the socioeconomic factors that influence which position an individual or group of people will hold within the structure of a society. In this study, we provide a comprehensive review of various indicators of SEP, including education level, occupation-based SEP, income and wealth, area SEP, life-course SEP, and SEP indicators for women, elderly and youth. Methods and results : This report provides a brief theoretical background and discusses the measurement, interpretation issues, advantages and limitations associated with the use of each SEP indicator. We also describe some problems that arise when selecting SEP indicators and highlight the indicators that appear to be appropriate for health inequality research. Some practical information for use in health inequality research in South Korea is also presented. Conclusions : Investigation into the associations between various SEP indicators and health outcomes can provide a more complete understanding of mechanisms between SEP and health. The relationship between specific SEP indicators and specific health outcomes can vary by country due to the differences in the historical, socioeconomic, and cultural contexts of the SEP indicators.

• 대한예방의학회:학술대회논문집
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• 2005.10a
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• pp.342-342
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• 2005

• 한국노년학
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• v.36 no.3
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• pp.611-632
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• 2016

Solutions for elderly health issues need to be found that take into account not only a medical perspective, but also interactions with social conditions such as socioeconomic status. With this in mind, this study aims to understand how socioeconomic status leads to health inequalities for the elderly. Specifically, this study investigates the mediating effects of socioeconomic status(income and education levels), health activities as an intermediary of the three dimensions of physical health(medical health, functional health, subjective health), accessibility of medical facilities, social participation, and social network. To test the research model, a secondary data analysis was conducted on the 2014 National Survey of Senior Citizens. The participants of the study were 10,451 elderly men and women aged 65 and above. To test the mediated model, hierarchical multiple regression analysis was conducted following the procedures suggested by Baron and Kenny(1986). In addition, a Sobel test was conducted to test the mediated model's significance. According to the analysis, the effects of income and educational levels on the health of the elderly were not the same. Additionally, different results were found depending on health dimensions. However, the overall direction of the results showed that the socioeconomic status of the elderly creates health disparities, and health behaviors, accessibility of medical facilities, social participation, and social network had significant mediation effects between socioeconomic status and physical health. Study findings especially worth noting are as follows: education was shown to have a stronger effect on health than income; effects of social integration factors such as social participation were highlighted; and significant mediating effects on the accessibility of medical facilities remained even after taking residential area into account. Results of this study shed light on health inequality mechanisms due to socioeconomic conditions and the need to find alternatives to alleviate these problems.