You are here

  • Home
  • Online First
  • Use of geographically weighted regression models to inform retail endgame strategies in South Korea: application to cigarette and ENDS prevalence

Article Text

Article menu
Download PDFPDF
Original research
Use of geographically weighted regression models to inform retail endgame strategies in South Korea: application to cigarette and ENDS prevalence
  1. Heewon Kang1,2,
  2. Eunsil Cheon3,
  3. Jaeyoung Ha3,
  4. Sung-il Cho1,3
  1. 1Institute of Health and Environment, Seoul National University, Seoul, South Korea
  2. 2NHMRC Centre of Research Excellence on Achieving the Tobacco Endgame, School of Public Health, University of Queensland, Herston, Queensland, Australia
  3. 3Department of Public Health Sciences, Seoul National University Graduate School of Public Health, Seoul, South Korea
  1. Correspondence to Professor Sung-il Cho, Institute of Health and Environment, Seoul National University, Seoul 08826, South Korea; persontime{at}hotmail.com

Abstract

Background Reducing tobacco retailer availability is a key tobacco endgame policy. The development and evaluation of retail-based policies require spatial methodologies. We modelled the prevalence of adult cigarette and electronic nicotine delivery system (ENDS) use according to tobacco retailer density, considering geographical variations.

Methods Registration data for tobacco retail businesses, a population-representative survey of South Koreans aged ≥19 years, and population and land area data were used. We merged the datasets according to geographical units. Ordinary least squares (OLS) and geographically weighted regression (GWR) analyses were conducted to model cigarette and ENDS use prevalence, respectively.

Findings Tobacco retailer density was associated with increased cigarette use prevalence in the OLS model (β=2.19, p=0.02). A 1.9-fold difference by region was identified for the coefficient, indicating an association with tobacco retailer density (minimum 1.39, maximum 2.65), in the GWR analysis. No significant association was present between tobacco retailer density and ENDS prevalence in either the OLS (β=0.24, p=0.37) or the GWR model (minimum 0.20, maximum 0.28).

Conclusion Our results suggest the importance of using spatial methods to develop and evaluate retail-based endgame policies. The establishment of tobacco retailer databases by the introduction of licensing is necessary to develop and evaluate the effectiveness of tobacco retailer regulations.

  • End game
  • Surveillance and monitoring
  • Electronic nicotine delivery devices
  • Public policy

Data availability statement

Data are available upon reasonable request. The Korea Community Health Survey data are available from the Korea Disease Control and Prevention Agency (https://chs.kdca.go.kr/chs/rawDta/rawDtaProvdMain.do). All other data relevant to the study are included in the article or uploaded as supplementary information.

http://dx.doi.org/10.1136/tc-2023-058117

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Data availability statement

    Data are available upon reasonable request. The Korea Community Health Survey data are available from the Korea Disease Control and Prevention Agency (https://chs.kdca.go.kr/chs/rawDta/rawDtaProvdMain.do). All other data relevant to the study are included in the article or uploaded as supplementary information.

    View Full Text

    Footnotes

    • Contributors HK designed the study, conducted all analyses and drafted the manuscript. All authors interpreted the findings and reviewed and approved the final version of the manuscript. HK is guarantor for the study and manuscript.

    • Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2021R1C1C2094375).

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.