Regional Health Disparities of Self-Rated Health Using Cluster Analysis in South Korea
10.4332/KJHPA.2023.33.2.118
- Author:
Min-Hee HEO
1
;
Sei-Jong BAEK
;
Young-Jin KIM
;
Jin-Won NOH
Author Information
1. Department of Health Administration, Yonsei University Graduate School, Wonju, Korea
- Publication Type:ORIGINAL ARTICLE
- From:Health Policy and Management
2023;33(2):118-128
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:Personal socio-economic abilities are crucial as it affects health inequalities. These multidimensional inequalities across the regions have been structured and fixed. This study aimed to analyze health vulnerabilities by regional cluster and identify regional health disparities of self-rated health, using nationally representative cross-sectional data.
Methods:This study used personal and regional data. Data from the Community Health Survey 2021 were analyzed. K-means cluster analysis was applied to 250 si-gun-gu using administrative regional data. The clusters were based on three areas: physical environment, health-related behaviors and biological factors, and the psychosocial environment through the conceptual framework for action on the social determinants of health. And binary logistic regression analyses were conducted to examine the differences in self-rated health status by the regional clusters, controlling human biology, environment, lifestyle, and healthcare organization factors.
Results:The most vulnerable group was group 3, the moderate vulnerable group was group 1, and the least vulnerable group was group 2. The group 2 was more likely to have high self-rated health status than the moderate vulnerable group (odds ratio [OR], 1.023; p<0.001). And the group 3 showed low self-rated health status than the moderate vulnerable group (OR, 0.775; p<0.001). However, the moderate vulnerable group had significantly higher self-rated health status than the most vulnerable group (group 2:OR, 1.023; p<0.001; group 3: OR, 0.775; p<0.001).
Conclusion:These results demonstrate that community members’ health status is influenced by regional determinants of health and individual levels. And these contribute to understanding the importance of specific and differentiated interventions like locally tailored support programs considering both individual and regional health determinants.
