A national pilot program for chronic diseases and health inequalities in South Korea.

BACKGROUND: To achieve the health equity, it is important to reduce socioeconomic inequalities when managing chronic diseases. In South Korea, a pilot program for chronic diseases was implemented at the national level. This study aimed to examine its effect on socioeconomic inequalities in chronic disease management at the individual and regional levels. METHODS: Korean National Health Insurance data from September 2016 to October 2017 were used. Study subjects in the national pilot program for chronic diseases included 31,765 participants and 5,741,922 non-participants. The dependent variable was continuity of prescription medication. Socioeconomic position indicators were health insurance contribution level and the area deprivation index. Covariates were gender, age, and the Charlson Comorbidity Index (CCI). A multilevel logistic regression model was used to address the effects at both the individual and regional levels. This is a cross-sectional study. RESULTS: Unlike the group of non-participants, the participants showed no inequality in prescription medication continuity according to individual-level socioeconomic position. However, continuity of prescription medication was higher among those in less deprived areas compared to those in more deprived areas in both the participation and non-participation groups. CONCLUSIONS: This study found that the pilot program for chronic diseases at the least did not contribute to the worsening of health inequalities at the individual level in South Korea. However, there was a trend showing health inequalities based on the socioeconomic level of the area. These findings suggest that additional policy measures are needed to attain equality in the management of chronic diseases regardless of the regional socioeconomic position.

Did the socioeconomic inequalities in avoidable and unavoidable mortality worsen during the first year of the COVID-19 pandemic in Korea?

OBJECTIVES: This study examined changes in socioeconomic inequalities in mortality in Korea before and after the outbreak of coronavirus disease 2019 (COVID-19). METHODS: From 2017 to 2020, age-standardized mortality rates were calculated for all-cause deaths, avoidable deaths (preventable deaths, treatable deaths), and unavoidable deaths using National Health Insurance claims data and Statistics Korea's cause of death data. In addition, the slope index of inequality (SII) and the relative index of inequality (RII) by six income levels (Medical Aid beneficiary group and quintile of health insurance premiums) were computed to analyze the magnitude and change of mortality inequalities. RESULTS: All-cause and avoidable mortality rates decreased steadily between 2017 and 2020, whereas unavoidable mortality remained relatively stable. In the case of mortality inequalities, the disparity in all-cause mortality between income classes was exacerbated in 2020 compared to 2019, with the SII increasing from 185.44 to 189.22 and the RII increasing from 3.99 to 4.29. In particular, the preventable and unavoidable mortality rates showed an apparent increase in inequality, as both the SII (preventable: 91.31 to 92.01, unavoidable: 69.99 to 75.38) and RII (preventable: 3.42 to 3.66, unavoidable: 5.02 to 5.89) increased. CONCLUSIONS: In the first year of the COVID-19 pandemic, mortality inequality continued to increase, although there was no sign of exacerbation. It is necessary to continuously evaluate mortality inequalities, particularly for preventable and unavoidable deaths.

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis.

OBJECTIVES: We aimed to identify area-based socioeconomic inequalities in diabetes management and to examine whether the distribution of healthcare resources could explain area-based inequalities in diabetes management. DESIGN: Cross-sectional multilevel analysis from national survey data. SETTING AND PARTICIPANTS: Data were derived from the 2018 Korean Community Health Survey. Study subjects included 23 760 participants aged 30 years or older with diabetes diagnosed by a doctor. MAIN OUTCOME MEASURES: The dependent variables were self-reported good glycaemic control, haemoglobin A1c (HbA1c) testing, recognition of the term HbA1c, and diabetic complications testing. Area Deprivation Index was used as an area-based measure of socioeconomic position. Factors related to regional healthcare resources-the coefficient of variation (CV) value of clinics and the number of physicians per 1000-were considered as potential mediating variables in explaining the association between diabetes management and area deprivation. A multilevel logistic regression analysis was used. RESULTS: Compared with the least deprived quintile, the likelihoods of not taking HbA1c tests, not recognising the term HbA1c, and not taking diabetic complication tests in the most deprived quintile were approximately 1.5 times (95% CI 1.25 to 1.80), 2.6 times (95% CI 1.97 to 3.45) and two times (95% CI 1.67 to 2.48) higher, respectively. In the most deprived quintile, CV value of clinics was the highest and the number of doctors was the lowest. Regional healthcare resource factors explained inequalities in managing diabetes by 14%-18%, especially in the most deprived quintile. CONCLUSIONS: The results in this study suggest that socioeconomic inequalities in diabetes management may be explained by regional healthcare resource disparities. Policy interventions for a more even distribution of healthcare resources would likely reduce the magnitude of regional socioeconomic inequalities in diabetes management.

Employment Status and Self-Reported Unmet Healthcare Needs among South Korean Employees.

We aimed to examine the association between employment status and self-reported unmet healthcare needs and to identify factors influencing self-reported unmet healthcare needs by employment status. Nationally representative data from the 2012 Korea National Health and Nutrition Examination Survey were used. Participants were classified by employment status as either permanent or precarious workers. Explanatory variables included sociodemographic, labor-related, and health-related factors. Multivariate logistic regression ascertained the association between employment status and self-reported unmet healthcare needs and explanatory factors associated with self-reporting of unmet healthcare needs. Precarious workers had a higher prevalence of self-reported unmet healthcare needs than permanent workers, with a statistically significant odds ratio (OR) (1.74; 95% confidence interval (CI), 1.19⁻2.54). Male precarious workers working >40 h per week were more likely to self-report unmet needs than male precarious workers working <40 h (OR, 3.90; 95% CI, 1.40⁻10.87). Female precarious workers with a lower household income were about twice as likely to self-report unmet needs. Working hours and household income were significantly influential factors determining self-reporting of unmet healthcare needs, especially among precarious workers. Policy interventions to improve access to healthcare for precarious workers are needed.