Health Policy Manag.  2020 Jun;30(2):199-210. 10.4332/KJHPA.2020.30.2.199.

Analysis of Factors Affecting the Smoking Rates Gap between Regions and Evaluation of Relative Efficiency of Smoking Cessation Projects

• Kim H
• Lee DH
• Jeong JY
• Gu YJ
• Jeong HS

• KMID: 2503577
• DOI: http://doi.org/10.4332/KJHPA.2020.30.2.199

Abstract

Background
Based on the importance of ceasing smoking programs to control the regional disparity of smoking behavior in Korea, this study aims to reveal the variation of smoke rate and determinants of it for 229 provinces. An evaluation of the relative efficiency of the cease smoking program under the consideration of regional characteristics was followed.
Methods
The main sources of data are the Korean Statistical Information Service and a national survey on the expenditure of public health centers. Multivariate regression is performed to figure the determinants of regional variation of smoking rate. Based on the result of the regression model, clustering analysis was conducted to group 229 regions by their characteristics. Three clusters were generated. Using data envelopment analysis (DEA), relative efficiency scores are calculated. Results from the pooled model which put 229 provinces in one model to score relative efficiency were compared with the cluster-separated model of each cluster.
Results
First, the maximum variation of the smoking rate was 16.9%p. Second, sex ration, the proportion of the elder, and high risk drinking alcohol behavior have a significant role in the regional variation of smoking. Third, the population and proportion of the elder are the main variables for clustering. Fourth, dissimilarity on the results of relative efficiency was found between the pooled model and cluster-separated model, especially for cluster 2.
Conclusion
This study figured regional variation of smoking rate and its determinants on the regional level. Unconformity of the DEA results between different models implies the issues on regional features when the regional evaluation performed especially on the programs of public health centers.

Keyword

Regional smoke rate; Cease smoking program; Efficiency evaluation; Clustering analysis; Data envelopment analysis