Background: The objective of this study was to elucidate the relationships musculoskeletal pains with combined vulnerability in terms of age, gender, and employment status Methods: The fifth European Working Conditions Survey (EWCS) in 2010 (43,816 participants aged 15 years and over) analyzed for European employees and the third Korean Working Conditions Survey (KWCS) in 2011 (50,032 participants aged 15 years and older) analyzed for Korean employees. In this study, three well known vulnerable factors to musculoskeletal pains (older age, female gender, and precarious employment status) were combined and defined as combined vulnerability. Associations of musculoskeletal pains with combined vulnerability were assessed with prevalence ratios (PRs) and 95% confidence intervals (CIs) estimated by Poisson regression models with robust estimates of variance. Results: The prevalences of musculoskeletal pains were lower but the absolute and relative differences between combined vulnerabilities were higher among Korean employees compared with the European employees. Furthermore, the increased risk of having musculoskeletal pains according to combined vulnerability was modestly explained by socioeconomic factors and exposure to ergonomic risk factors, especially in Republic of Korea. Conclusions The results of this study showed that the labor market may be more unfavorable for female and elderly workers in Republic of Korea. Any prevention strategies to ward off musculoskeletal pains, therefore, should be found and implemented to mitigate or buffer against the most vulnerable work population, older, female, and precarious employment status, in Republic of Korea.

PURPOSE: Seoul and Busan are the two largest cities in Korea. However, life expectancy (LE) in Busan is shorter than in Seoul and among the total Korean population. This study was conducted to decompose age- and cause-specific contributions to the LE difference between Seoul and Busan. MATERIALS AND METHODS: We obtained population and mortality data for Seoul and Busan between 2015 and 2017 from Statistics Korea. We applied Arriaga's decomposition method to life table data to estimate age- and cause-specific contributions to the LE difference between Seoul and Busan. RESULTS: During 2015–2017, LE in Busan was shorter than in Seoul by 2.22 years. Roughly two-thirds of the LE gap between Seoul and Busan was due to excess mortality among elderly people in Busan. The ≥85 age group alone contributed to approximately 20% of the LE gap, while no meaningful contribution was made by the 1–24 age groups. Cardiovascular disease accounted for over 40% of the total LE gap between Seoul and Busan, and this factor was more prominent in women. The top 15 leading specific causes of deaths explained nearly the entire LE difference between Seoul and Busan. CONCLUSION: The difference in LE between Seoul and Busan was due to higher mortality rate in Busan than in Seoul, especially in the elderly population and from cardiovascular diseases. Information on age- and cause-specific contributions to the LE difference between Seoul and Busan may guide health policy-makers to plan strategies for reducing the gap in LE.
Aged ; Busan ; Cardiovascular Diseases ; Cause of Death ; Female ; Humans ; Korea ; Life Expectancy ; Life Tables ; Methods ; Mortality ; Republic of Korea ; Seoul

Background: The objective of this study was to elucidate the relationships musculoskeletal pains with combined vulnerability in terms of age, gender, and employment status Methods: The fifth European Working Conditions Survey (EWCS) in 2010 (43,816 participants aged 15 years and over) analyzed for European employees and the third Korean Working Conditions Survey (KWCS) in 2011 (50,032 participants aged 15 years and older) analyzed for Korean employees. In this study, three well known vulnerable factors to musculoskeletal pains (older age, female gender, and precarious employment status) were combined and defined as combined vulnerability. Associations of musculoskeletal pains with combined vulnerability were assessed with prevalence ratios (PRs) and 95% confidence intervals (CIs) estimated by Poisson regression models with robust estimates of variance. Results: The prevalences of musculoskeletal pains were lower but the absolute and relative differences between combined vulnerabilities were higher among Korean employees compared with the European employees. Furthermore, the increased risk of having musculoskeletal pains according to combined vulnerability was modestly explained by socioeconomic factors and exposure to ergonomic risk factors, especially in Republic of Korea. Conclusions The results of this study showed that the labor market may be more unfavorable for female and elderly workers in Republic of Korea. Any prevention strategies to ward off musculoskeletal pains, therefore, should be found and implemented to mitigate or buffer against the most vulnerable work population, older, female, and precarious employment status, in Republic of Korea.

The purpose of this study was to examine the degree to which the magnitude of income inequality in life expectancy according to different categorization across beneficiary types under the National Health Insurance Service (NHIS) in Korea. We used population and death data in 2017 from the National Health Information Database of the NHIS. Income quintile groups were classified in four ways according to beneficiary type (employee insured, self-employed insured, and Medical Aid beneficiaries). Standard life table procedures were used to calculate life expectancy. The life expectancy gap between the lowest and highest income quintiles was the largest when the entire population was divided into quintiles without distinguishing among types of beneficiaries. In conclusion, we suggest that income quintile indicators in NHIS data, measured without distinguishing among types of beneficiaries, may best represent the magnitude of health inequalities in Korean society. This indicator could be used for future research on health inequalities, as well as for monitoring health inequalities in Korea.

Objectives: We calculated life expectancy and inequalities therein by income for the period of 2016-2018 across the 253 electoral constituencies of the 20th National Assembly election in Korea. Methods: We obtained population and death data between 2016 and 2018 from the National Health Information Database and constructed abridged life tables using standard life table procedures according to gender and income quintiles for the electoral constituencies of the 20th National Assembly election held in 2016. Results: Life expectancy across the 253 constituencies ranged from 80.51 years to 87.05 years, corresponding to a gap of 6.54 years. The life expectancy difference by income across the 253 constituencies ranged from 2.94 years to 10.67 years. In each province, the difference in life expectancy by income across electoral constituencies was generally greater than the inter-constituency differences. Constituencies in capital and metropolitan areas showed a higher life expectancy and a lower life expectancy difference by income than constituencies in rural areas. Conclusions Pro-rich inequalities in life expectancy by income existed in every electoral constituency in Korea. Both intra-constituency and inter-constituency socioeconomic inequalities in health should be highlighted in future policy-making in the National Assembly.

OBJECTIVES: This study aimed to examine the association between preschool education experiences and adulthood self-rated health using representative data from a national population-based survey. METHODS: Data from the Korean Labor and Income Panel Study in 2006 and 2012 were used. A total of 2391 men and women 21-41 years of age were analyzed. Log-binomial regression analyses were conducted to examine the associations between preschool education experience and self-rated health in adulthood. Parental socioeconomic position (SEP) indicators were considered as confounders of the association between preschool education experience and adulthood subjective health, while current SEP indicators were analyzed as mediators. Age-adjusted prevalence ratios (PRs) and the associated 95% confidence intervals (CIs) were estimated. RESULTS: Compared with men without any experience of preschool education, those with both kindergarten and other preschool education experiences showed a lower prevalence of self-rated poor health (PR, 0.65; 95% CI, 0.47 to 0.89). In women, however, such an association was not evident. The relationship of preschool education experiences with self-rated poor health in adulthood among men was confounded by parental SEP indicators and was also mediated by current SEP indicators. After adjustment for parental and current SEP indicators, the magnitude of the associations between preschool education experiences and adulthood subjective health was attenuated in men. CONCLUSIONS: Preschool education experience was associated with adulthood self-rated health in men. However, this association was explained by parental and current SEP indicators. Further investigations employing a larger sample size and objective health outcomes are warranted in the future.
Child, Preschool ; Diagnostic Self Evaluation ; Early Intervention (Education) ; Education* ; Female ; Humans ; Longitudinal Studies ; Male ; Parents ; Prevalence ; Republic of Korea ; Sample Size ; Socioeconomic Factors

OBJECTIVES: The aim of this study was to measure income differences in smoking prevalence at the district level and to investigate correlations among area deprivation, smoking prevalence, and income differences in smoking prevalence, stratified by urbanity. METHODS: Data were pooled from the Community Health Survey data of South Korea between 2008 and 2014. The age-standardized prevalence of smoking and its interquintile income differences were calculated. We conducted correlation analyses to investigate the association of the deprivation index with smoking prevalence and interquintile differences in smoking prevalence. RESULTS: Across 245 districts, the median prevalence of smoking in men was 45.9% (95% confidence interval [CI], 43.4 to 48.5%), with an interquartile range (IQR) of 4.6% points. In women, the median prevalence was 3.0% (95% CI, 2.4 to 3.6%) and IQR was 1.6% points. The median interquintile difference in smoking prevalence was 7.4% points (95% CI, 1.6 to 13.2% points) in men and 2.7% points (95% CI, 0.5 to 4.9% points) in women. The correlation coefficients for the association between the deprivation index and smoking prevalence was 0.58, 0.15, -0.22 in metropolitan, urban, and rural areas, respectively, among men, and 0.54, -0.33, -0.43 among women. No meaningful correlation was found between area deprivation and interquintile difference in smoking prevalence. The correlation between smoking prevalence and interquintile difference in smoking prevalence was more evident in women than in men. CONCLUSIONS: This study provides evidence of geographical variations in smoking prevalence and interquintile difference in smoking prevalence. Neither smoking prevalence nor the deprivation index was closely correlated with interquintile income difference in smoking prevalence. Measuring inequalities in smoking prevalence is crucial to developing policies aimed at reducing inequalities in smoking.
Female ; Geography ; Health Surveys ; Humans ; Korea* ; Male ; Prevalence* ; Smoke* ; Smoking* ; Socioeconomic Factors

OBJECTIVES: This study examined trends in inequality in cigarette smoking prevalence by income according to recent anti-smoking policies in Korea. METHODS: The data used in this study were drawn from three nationally representative surveys, the Korea National Health and Nutrition Examination Survey, the Korea Community Health Survey, and the Social Survey of Statistics Korea. We calculated the age-standardized smoking prevalence, the slope index of inequality, and the relative index of inequality by income level as a socioeconomic position indicator. RESULTS: Smoking prevalence among men decreased during the study period, but the downward trend became especially pronounced in 2015, when the tobacco price was substantially increased. Inequalities in cigarette smoking by income were evident in both genders over the study period in all three national surveys examined. Absolute inequality tended to decrease between 2014 and 2015 among men. Absolute and relative inequality by income decreased between 2008 and 2016 in women aged 30-59, except between 2014 and 2015. CONCLUSIONS: The recent anti-smoking policies in Korea resulted in a downward trend in smoking prevalence among men, but not in relative inequality, throughout the study period. Absolute inequality decreased over the study period among men aged 30-59. A more aggressive tax policy is warranted to further reduce socioeconomic inequalities in smoking in young adults in Korea.
Female ; Health Surveys ; Humans ; Korea* ; Male ; Nutrition Surveys ; Prevalence* ; Smoke ; Smoking* ; Socioeconomic Factors* ; Taxes ; Tobacco ; Tobacco Products* ; Young Adult

OBJECTIVES: To examine the income gaps associated with self-rated poor health at the district level in Korea and to identify the geographical correlations between self-rated poor health, life expectancy, and the associated income gaps. METHODS: We analyzed data for 1,578,189 participants from the Community Health Survey of Korea collected between 2008 and 2014. The age-standardized prevalence of self-rated poor health and the associated income gaps were calculated. Previously released data on life expectancy and the associated income gaps were also used. We performed correlation and regression analyses for self-rated poor health, life expectancy, and associated income gaps. RESULTS: Across 245 districts, the median prevalence of self-rated poor health was 15.7% (95% confidence interval [CI], 14.6 to 16.8%), with interquartile range (IQR) of 3.1 percentage points (%p). The median interquintile gaps in the prevalence of self-rated poor health was 11.1%p (95% CI, 8.1 to 14.5%p), with IQR of 3.6%p. Pro-rich inequalities in self-rated health were observed across all 245 districts of Korea. The correlation coefficients for the association between self-rated poor health and the associated income gaps, self-rated poor health and life expectancy, and income gaps associated with self-rated poor health and life expectancy were 0.59, 0.78 and 0.55 respectively. CONCLUSIONS: Income gaps associated with self-rated poor health were evident across all districts in Korea. The magnitude of income gaps associated with self-rated poor health was larger in the districts with greater prevalence of self-rated poor health. A strong correlation between self-rated poor health and life expectancy was also observed.
Geography ; Health Surveys ; Korea* ; Life Expectancy* ; Prevalence ; Socioeconomic Factors

OBJECTIVES: To examine the income gaps associated with self-rated poor health at the district level in Korea and to identify the geographical correlations between self-rated poor health, life expectancy, and the associated income gaps.METHODS: We analyzed data for 1,578,189 participants from the Community Health Survey of Korea collected between 2008 and 2014. The age-standardized prevalence of self-rated poor health and the associated income gaps were calculated. Previously released data on life expectancy and the associated income gaps were also used. We performed correlation and regression analyses for self-rated poor health, life expectancy, and associated income gaps.RESULTS: Across 245 districts, the median prevalence of self-rated poor health was 15.7% (95% confidence interval [CI], 14.6 to 16.8%), with interquartile range (IQR) of 3.1 percentage points (%p). The median interquintile gaps in the prevalence of self-rated poor health was 11.1%p (95% CI, 8.1 to 14.5%p), with IQR of 3.6%p. Pro-rich inequalities in self-rated health were observed across all 245 districts of Korea. The correlation coefficients for the association between self-rated poor health and the associated income gaps, self-rated poor health and life expectancy, and income gaps associated with self-rated poor health and life expectancy were 0.59, 0.78 and 0.55 respectively.CONCLUSIONS: Income gaps associated with self-rated poor health were evident across all districts in Korea. The magnitude of income gaps associated with self-rated poor health was larger in the districts with greater prevalence of self-rated poor health. A strong correlation between self-rated poor health and life expectancy was also observed.
Geography ; Health Surveys ; Korea ; Life Expectancy ; Prevalence ; Socioeconomic Factors