Comparison of District-level Smoking Prevalence and Their Income Gaps from Two National Databases: the National Health Screening Database and the Community Health Survey in Korea, 2009-2014

Contributions of the life expectancy gap reduction between urban and rural areas to the increase in overall life expectancy in South Korea from 2000 to 2019

BACKGROUND

This study aimed to quantify the contribution of narrowing the life expectancy gap between urban and rural areas to the overall life expectancy at birth in Korea and examine the age and death cause-specific contribution to changes in the life expectancy gap between urban and rural areas.

METHODS

We used the registration population and death statistics from Statistics Korea from 2000 to 2019. Assuming two hypothetical scenarios, namely, the same age-specific mortality change rate in urban and rural areas and a 20% faster decline than the observed decline rate in rural areas, we compared the increase in life expectancy with the actual increase. Changes in the life expectancy gap between urban and rural areas were decomposed into age- and cause-specific contributions.

RESULTS

Rural disadvantages of life expectancy were evident. However, life expectancies in rural areas increased more rapidly than in urban areas. Life expectancy would have increased 0.3-0.5 less if the decline rate of age-specific mortality in small-to-middle urban and rural areas were the same as that of large urban areas. Life expectancy would have increased 0.7-0.9 years further if the decline rate of age-specific mortality in small-to-middle urban and rural areas had been 20% higher. The age groups 15-39 and 40-64, and chronic diseases, such as neoplasms and diseases of the digestive system, and external causes significantly contributed to narrowing the life expectancy gap between urban and rural areas.

CONCLUSION

Pro-health equity interventions would be a good strategy to reduce the life expectancy gap and increase overall life expectancy, particularly in societies where life expectancies have already increased.

Machine learning reveals sex-specific associations between cardiovascular risk factors and incident atherosclerotic cardiovascular disease

We aimed to investigate sex-specific associations between cardiovascular risk factors and atherosclerotic cardiovascular disease (ASCVD) risk using machine learning. We studied 258,279 individuals (132,505 [51.3%] men and 125,774 [48.7%] women) without documented ASCVD who underwent national health screening. A random forest model was developed using 16 variables to predict the 10-year ASCVD in each sex. The association between cardiovascular risk factors and 10-year ASCVD probabilities was examined using partial dependency plots. During the 10-year follow-up, 12,319 (4.8%) individuals developed ASCVD, with a higher incidence in men than in women (5.3% vs. 4.2%, P < 0.001). The performance of the random forest model was similar to that of the pooled cohort equations (area under the receiver operating characteristic curve, men: 0.733 vs. 0.727; women: 0.769 vs. 0.762). Age and body mass index were the two most important predictors in the random forest model for both sexes. In partial dependency plots, advanced age and increased waist circumference were more strongly associated with higher probabilities of ASCVD in women. In contrast, ASCVD probabilities increased more steeply with higher total cholesterol and low-density lipoprotein (LDL) cholesterol levels in men. These sex-specific associations were verified in the conventional Cox analyses. In conclusion, there were significant sex differences in the association between cardiovascular risk factors and ASCVD events. While higher total cholesterol or LDL cholesterol levels were more strongly associated with the risk of ASCVD in men, older age and increased waist circumference were more strongly associated with the risk of ASCVD in women.

Income differences in screening, incidence, postoperative complications, and mortality of thyroid cancer in South Korea: a national population-based time trend study

Background

The incidence of thyroid cancer (TC) has increased rapidly over the past few decades in Korea. This study investigated whether the TC epidemic has been driven by overdiagnosis.

Methods

We calculated the TC screening rate from mid-2008 through mid-2014, and the incidence, postoperative complication, and mortality rates of TC between 2006 and 2015, using data from the Korea Community Health Survey, the National Health Insurance Database, and the cause-of-death data of Statistics Korea. Trends in age-standardized rates of all indicators were examined, along with income gaps therein. Analyses were conducted for lung cancer and stroke as negative control outcomes.

Results

The incidence rate of TC increased from 46.6 per 100,000 to 115.0 per 100,000 between 2006 and 2012, and then decreased to 63.5 per 100,000 in 2015. Despite these remarkable changes in incidence, mortality did not fluctuate during the same period. High income was associated with high rates of screening, incidence, and postoperative complications, while low income showed an association with a high mortality rate. Analyses using negative control outcomes showed that high income was associated with low rates of both incidence and mortality, which contrasted with the patterns of TC. The recent decreases in TC incidence and postoperative complications, which reflect societal concerns about the overdiagnosis of TC, were more pronounced in high-income individuals than in low-income individuals.

Conclusions

The time trends in income gaps in screening, incidence, postoperative complications, and mortality of TC, as well as negative control outcomes, provided corroborating evidence of TC overdiagnosis in Korea.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-020-07597-4.

Long-term trends in smoking prevalence and its socioeconomic inequalities in Korea, 1992-2016

BACKGROUND

The aim of this study was to investigate long-term trends in smoking prevalence and its socioeconomic inequalities in Korea.

METHODS

Data were collected from 10 rounds of the Social Survey of Statistics Korea between 1992 and 2016. A total of 524,866 men and women aged 19 or over were analyzed. Age-adjusted smoking prevalence was calculated according to three major socioeconomic position indicators: education, occupational class, and income. The prevalence difference, prevalence ratio, slope index of inequality (SII), and relative index of inequality (RII) were calculated to examine the magnitude of inequality in smoking.

RESULTS

Smoking prevalence among men decreased from 71.7% in 1992 to 39.7% in 2016, while smoking prevalence among women decreased from 6.5% in 1992 to 3.3% in 2016. Socioeconomic inequalities in smoking prevalence according to the three socioeconomic position indicators were found in both men and women throughout the study period. In general, absolute and relative socioeconomic inequalities in smoking, measured by prevalence difference and prevalence ratio for education and occupational class, widened during the study period among Korean men and women. In men, the SII for income increased from 7.6% in 1999 to 10.8% in 2016 and the RII for income also increased from 1.11 in 1999 to 1.31 in 2016. In women, the SII for income increased from 0.1% in 1999 to 2.4% in 2016 and the RII for income increased from 1.39 in 1999 to 2.25 in 2016.

CONCLUSION

Pro-rich socioeconomic inequalities in smoking prevalence were found in men and women. Socioeconomic inequalities in smoking have increased in parallel with the implementation of tobacco control policies. Tobacco control policies should be developed to decrease socioeconomic inequalities in cigarette use in Korea.