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: 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: 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

Background: Health indicators, such as mortality rates or life expectancy, need to be presented at the local level to improve the health of local residents and to reduce health inequality across geographic areas. The aim of this study was to estimate life expectancy at the district level in Korea through a spatio-temporal analysis. Methods: Spatio-temporal models were applied to the National Health Information Database of the National Health Insurance Service to estimate the mortality rates for 19 age groups in 250 districts from 2004 to 2017 by gender in Korea. Annual district-level life tables by gender were constructed using the estimated mortality rates, and then annual district-level life expectancy by gender was estimated using the life table method and the Kannisto-Thatcher method. The annual district-level life expectancies based on the spatio-temporal models were compared to the life expectancies calculated under the assumption that the mortality rates in these 250 districts are independent from one another. Results: In 2017, district-level life expectancy at birth ranged from 75.5 years (95% credible interval [CI], 74.0–77.0 years) to 84.2 years (95% CI, 83.4–85.0 years) for men and from 83.9 years (95% CI, 83.2–84.6 years) to 88.2 years (95% CI, 87.3–89.1 years) for women.Between 2004 and 2017, district-level life expectancy at birth increased by 4.57 years (95% CI, 4.49–4.65 years) for men and by 4.06 years (95% CI, 3.99–4.12 years) for women. To obtain stable annual life expectancy estimates at the district level, it is recommended to use the life expectancy based on spatio-temporal models instead of calculating life expectancy using observed mortality. Conclusion In this study, we estimated the annual district-level life expectancy from 2004 to 2017 in Korea by gender using a spatio-temporal model. Local governments could use annual district-level life expectancy estimates as a performance indicator of health policies to improve the health of local residents. The approach to district-level analysis with spatiotemporal modeling employed in this study could be used in future analyses to produce district-level health-related indicators in Korea.

Background: To determine the priorities and resource allocation of community cancerrelated health policies, it is necessary to measure cancer-related health indicators and the burden of cancer by region. This study calculated the cancer-free life expectancy at the eup/ myeon/dong level (small administrative units in South Korea) for the first time, and analyzed its association with regional health insurance premiums. Methods: We used aggregate data from the 2008–2017 National Health Information Database provided by the National Health Insurance Service. Cancer-free life expectancy was calculated by applying Sullivan's method to mortality and cancer prevalence by age group and sex for the 10-year period in 3,396 eups/myeons/dongs. Correlation analyses were performed to analyze the relationship between cancer-free life expectancy and regional health insurance premiums. Results: Cancer-free life expectancy in eups/myeons/dongs of metropolitan areas tended to be higher than in non-metropolitan areas. However, some eups/myeons/dongs of non-metropolitan areas showed quite a high cancer-free life expectancy, especially for females. The median values of differences between cancer-free life expectancy and life expectancy at the eup/myeon/ dong level (total: 1.6 years, male: 1.8 years, female: 1.4 years) indicated that a person's healthy life can be shortened by a number of years due to cancer. The association of cancer-free life expectancy by eup/myeon/dong with the regional health insurance premium was statistically significant (β = 1.0, P < 0.001) and more prominent for males (β = 1.3, P < 0.001) than for females (β = 0.5, P < 0.001). The relationship between the regional health insurance premium and the burden of cancer (life expectancy minus cancer-free life expectancy) was also statistically significant (β = 0.2 for the total population, β = 0.2 for males, and β = 0.1 for females, all P values < 0.001). Conclusion This study showed a significant regional gap with regard to cancer-free life expectancy and the burden of cancer at the eup/myeon/dong level. This work makes a meaningful contribution by presenting new and firsthand summary measures of cancerrelated health across small areas in Korea. The results will also help the authorities to evaluate the effectiveness of local cancer management projects in small administrative areas and determine regional priorities for implementing cancer control policies.

This study explores whether the National Health Information Database (NHID) can be used to monitor health status of entire population in Korea. We calculated the crude mortality rate and life expectancy (LE) at birth across the national, provincial, and municipal levels using the NHID eligibility database from 2004 to 2015, and compared the results with the corresponding values obtained from the Korean Statistical Information Service (KOSIS) of Statistics Korea. The study results showed that the ratio of crude mortality rate between the two data was 0.99. The absolute difference between the LE of the two data was not more than 0.5 years, and did not exceed 0.3 years in gender specific results. The concordance correlation coefficients (CCC) between the crude mortality rates from NHID and the rates from KOSIS ranged 0.997–0.999 among the municipalities. For LE, the CCC between the NHID and KOSIS across the municipalities were 0.990 in 2004–2009 and 0.985 in 2010–2015 among men, and 0.952 in 2004–2009 and 0.914 in 2010–2015 among women, respectively. Overall, the NHID was a good source for monitoring mortality and LE across national, provincial, and municipal levels with the population representativeness of entire Korean population. The results of this study indicate that NHID may well contribute to the national health promotion policy as a part of the health and health equity monitoring system.
Female ; Health Equity ; Health Promotion ; Humans ; Information Services ; Korea* ; Life Expectancy* ; Male ; Mortality* ; National Health Programs* ; Parturition

BACKGROUND: We compared age-standardized overweight prevalence and their income gaps at the level of district in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: We analyzed 39,093,653 subjects in the NHSD and 926,580 individuals in the CHS between 2009 and 2014. For the comparison of body mass index (BMI) distributions, data from 26,100 subjects in the Korea National Health and Nutrition Examination Survey (KNHANES) were also analyzed. We calculated the age-standardized overweight prevalence and its interquintile income gap at the district level. We examined the magnitudes of the between-period correlation for age-standardized overweight prevalence. The differences in overweight prevalence and its income gap between the NHSD and the CHS were also investigated. RESULTS: The age-adjusted mean BMI from the CHS was lower than those from the NHSD and the KNHANES. The magnitudes of the between-period correlation for overweight prevalence were greater in the NHSD compared to the CHS. We found that the district-level overweight prevalence in the NHSD were higher in all districts of Korea than in the CHS. The correlation coefficients for income gaps in overweight prevalence between the two databases were relatively low. In addition, when using the NHSD, the district-level income inequalities in overweight were clearer especially among women than the inequalities using the CHS. CONCLUSION: The relatively large sample size for each district and measured anthropometric data in the NHSD are more likely to contribute to valid and reliable measurement of overweight inequality at the district level in Korea.
Body Mass Index ; Female ; Health Surveys ; Humans ; Korea ; Mass Screening ; Nutrition Surveys ; Overweight ; Prevalence ; Republic of Korea ; Sample Size ; Socioeconomic Factors

BACKGROUND: We compared age-standardized prevalence of cigarette smoking and their income gaps at the district-level in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS). METHODS: Between 2009 and 2014, 39,049,485 subjects participating in the NHSD and 989,292 participants in the CHS were analyzed. The age-standardized prevalence of smoking and their interquintile income differences were calculated for 245 districts of Korea. We examined between-period correlations for the age-standardized smoking prevalence at the district-level and investigated the district-level differences in smoking prevalence and income gaps between the two databases. RESULTS: The between-period correlation coefficients of smoking prevalence for both genders were 0.92–0.97 in NHSD and 0.58–0.69 in CHS, respectively. When using NHSD, we found significant income gaps in all districts for men and 244 districts for women. However, when CHS was analyzed, only 167 and 173 districts for men and women, respectively, showed significant income gaps. While correlation coefficients of district-level smoking prevalence from two databases were 0.87 for men and 0.85 for women, a relatively weak correlation between income gaps from the two databases was found. CONCLUSION: Based on two databases, income gaps in smoking prevalence were evident for nearly all districts of Korea. Because of the large sample size for each district, NHSD may provide stable district-level smoking prevalence and its income gap and thus should be considered as a valuable data source for monitoring district-level smoking prevalence and its socioeconomic inequality.
Female ; Health Surveys ; Humans ; Information Storage and Retrieval ; Korea ; Male ; Mass Screening ; Prevalence ; Sample Size ; Smoke ; Smoking ; Socioeconomic Factors

BACKGROUND: This study addressed town-level mortality rates using the National Health Information Database (NHID) of the National Health Insurance Service in Korea in comparison with those derived from the National Administrative Data (NAD) of the Ministry of Interior and Safety. METHODS: We employed the NHID and NAD between 2014 and 2017. We compared the numbers of population and deaths at the national level between these two data sets. We also compared the distribution of the town-level numbers of population and deaths of the two data sets. Correlation analyses were performed to investigate the relation between the NHID and NAD in the town-level numbers of population and deaths, crude mortality rate, and standardized mortality ratio (SMR). RESULTS: The numbers of population and deaths in the NHID were almost identical to those in the NAD, regardless of gender. The distribution of the town-level numbers of population and deaths was also similar between the two data sets during the entire study period. Throughout the study period, the Pearson correlation coefficients between the two databases for the town-level numbers of population and deaths and the crude mortality rate were 0.996 or over. The correlation coefficients for the SMR ranged from 0.937 to 0.972. CONCLUSION: Town-level mortality showed significant correlation and concordance between the NHID and NAD. This result highlights the possibility of producing future analyses of town-level health-related indicators in Korea, including the mortality rate, using the NHID.
Dataset ; Korea ; Mortality ; NAD ; National Health Programs ; Republic of Korea ; Statistics as Topic