Effect of tobacco outlet density on quit attempts in Korea: a multi-level analysis of the 2015 Korean Community Health Survey

Abstract

OBJECTIVES This study aimed to examine whether the regional density of tobacco outlets in Korea was associated with the likelihood of attempting to quit among smokers METHODS This study was designed as a secondary data analysis of a cross-sectional study. Data from the 2015 Korean Community Health Survey and tobacco outlet registrations in 17 metropolitan cities and provinces with 254 communities in Korea were used for the analysis. In total, 41,013 current smokers (≥19 years of age) were included. Multi-level logistic regression analysis was conducted to investigate regional differences associated with smokers’ attempts to quit and to evaluate the effects of individual and regional characteristics on quit attempts. RESULTS Higher tobacco outlet density was associated with lower odds of attempting to quit. Smokers who resided in districts with the highest tobacco outlet density were 18% less likely to attempt quitting (odds ratio, 0.82; 95% confidence interval, 0.70 to 0.98) than smokers who resided in the regions with the lowest tobacco outlet density (intraclass correlation coefficient, 0.030). CONCLUSIONS This study showed that quit attempts were related to community-level factors, such as tobacco outlet density, as well as other individual factors. These findings support the implementation of national policies restricting the number of tobacco outlets within communities or zones and limiting tobacco marketing in tobacco outlets.

Concerns related to COVID-19 in South Korea : What are associated individual and regional factors?

“…While explaining 4•86% of the concerns in area-level, which is somewhat noticeable where the majority of previous research populated in South Korea indicated little explanation of regional variation to health-related outcomes (around 3%). [27][28][29][30] Other characteristics of individuals that had signi cant associations with the concern, which are in line with existing research, are; women, [31] older, [31][32][33] lower income, [34] lower education, [31] perceived health status, [32] and current depressive symptom. [32,35] The association between ADI and the concern related to COVID-19 differed by age groups of 19-29, 30-39, and 40-49, which are the economically active population.…”