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

• Published in: Journal of Korean medical science 2018, 33(6), , pp.30-42
• Main Authors: Kim, Ikhan, Bahk, Jinwook, Kim, Yeon Yong, Lee, Jeehye, Kang, Hee Yeon, Lee, Juyeon, Yun, Sung Cheol, Park, Jong Heon, Shin, Soon Ae, Khang, Young Ho
• Format: Article
• Language: English
• Subjects: Original; 의학일반
• ISSN: 1011-8934; 1598-6357
• DOI: 10.3346/jkms.2018.33.e44

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). 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. 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. 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.