Bahk J, et al. J Korean Med Sci. 2017 Nov;32(11):1764-1770. https://doi.org/10.3346/jkms.2017.32.11.1764

This study aimed to estimate and compare life expectancy at birth among people with and without officially registered disabilities in Korea between 2004 and 2017. We used the National Health Information Database in Korea to obtain aggregate data on the numbers of population and deaths according to calendar year (2004 to 2017), sex, age groups, and officially registered disability status. A total of 697,503,634 subjects and 3,536,778 deaths, including 33,221,916 disabled subjects (829,464 associated deaths), were used to construct life tables. Between 2004 and 2017, life expectancy for people with disabilities increased by 9.1 years in men and 8.3 years in women, while life expectancy for the non-disabled increased by 5.5 years in men and 4.6 years in women. The average life expectancy difference between non-disabled and disabled people was 18.2 years during the study period, decreasing from 20.4 years in 2004 to 16.4 years in 2017. In 2017, the life expectancy of people with the most severe grade of disabilities was 49.7 years, while the life expectancy of people with the least severe grade of disabilities was 77.7 years. The government should implement more effective policies to protect the health of people with officially registered disabilities.

Medical Aid beneficiaries in Korea are more likely to have poor health status and to receive insufficient healthcare services, but their life expectancy has not been compared with that of National Health Insurance beneficiaries. We used the National Health Information Database in Korea to obtain aggregate data on the numbers of population and deaths according to calendar year (2004 to 2017), sex, age group, and insurance eligibility (Medical Aid or National Health Insurance). Between 2004 and 2017, a summed total of 697,503,634 subjects (combining numbers of subjects for 14 years) and 3,536,778 deaths, including 22,417,216 Medical Aid beneficiaries and 499,604 associated deaths, were used to construct annual abridged life tables. In 2017, the life expectancy of Medical Aid beneficiaries was 70.9 years, while that of National Health Insurance beneficiaries was 83.7 years. Between 2004 and 2017, life expectancy for Medical Aid beneficiaries increased by 8.7 years in men and 6.1 years in women, while life expectancy for National Health Insurance beneficiaries increased by 5.2 years in men and 4.5 years in women. The life expectancy difference between National Health Insurance beneficiaries and Medical Aid beneficiaries was especially great among men across all study periods. The life expectancy difference was 15.8 years for men and 8.9 years for women in 2017. The life expectancy of Medical Aid beneficiaries was shorter than that of National Health Insurance beneficiaries. The government should implement policies to deliver more adequate health care to Medical Aid beneficiaries.

OBJECTIVES: This study aimed to describe trends in health behaviours between 2011 and 2020 and compare the changes in these behaviours between the 2020 COVID-19 pandemic and previous periods according to socio-demographic variables.METHODS: This study used data from the 2011 to 2020 Korea National Health and Nutrition Examination Survey. Current cigarette smoking, high-risk drinking, and inadequate physical activity levels were used as health behaviour indicators. The age-standardized prevalence, differences in prevalence between the periods, and the annual percentage change (APC) were calculated.RESULTS: Current cigarette smoking showed a decreasing trend (APC, -2.6), high-risk drinking remained unchanged, and inadequate physical activity levels increased (APC, 3.5) during 2011-2020. There were significant differences in high-risk drinking (3.1%p; 95% confidence interval [CI], 0.3 to 5.9) and inadequate physical activity levels (4.3%p; 95% CI, 0.4 to 8.1) between 2019 and 2020 in men. Among men, increased high-risk drinking was found in those aged 40-49 years, non-single households, urban residents, and the middle and highest income groups between 2019 and 2020. The low educational group and manual workers among men aged 30-59 years also showed an increased proportion of high-risk drinking. Inadequate physical activity levels also increased among men between 2019 and 2020 in those aged 30-39 years, non-single households, urban residents, and the upper-middle-income group.CONCLUSIONS: In the first year of the COVID-19 pandemic, Korean men’s high-risk drinking and inadequate physical activity levels increased. In addition to social efforts to reduce the spread of infectious diseases, active measures to positively change health behaviour are needed.

Background: The aim of this study was to measure differences in quality-adjusted life expectancy (QALE) by income in Korea at the national and district levels. Methods: Mortality rates and EuroQol-5D (EQ-5D) scores were obtained from the National Health Information Database of the National Health Insurance Service and the Korea Community Health Survey, respectively. QALE and differences in QALE among income quintiles were calculated using combined 2008–2014 data for 245 districts in Korea. Correlation analyses were conducted to investigate the associations of neighborhood characteristics with QALE and income gaps therein. Results: QALE showed a graded pattern of inequality according to income, and increased over time for all levels of income and in both sexes, except for low-income quintiles among women, resulting in a widened inequality in QALE among women. In all 245 districts, pro-rich inequalities in QALE were found in both men and women. Districts with higher QALE and smaller income gaps in QALE were concentrated in metropolitan areas, while districts with lower QALE and larger income gaps in QALE were found in rural areas. QALE and differences in QALE by income showed relatively close correlations with socioeconomic characteristics, but relatively weak correlations with health behaviors, except for smoking and indicators related to medical resources. Conclusions: This study provides evidence of income-based inequalities in health measured by QALE in all subnational areas in Korea. Furthermore, QALE and differences in QALE by income were closely associated with neighborhood-level socioeconomic characteristics.

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. 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. 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. 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.