Urban-Rural Differences in the Prevalence of Depressive Symptoms in Korean Adults
10.4068/cmj.2023.59.2.128
- Author:
Ji-An JEONG
1
;
Sun A KIM
;
Jung Ho YANG
;
Min-Ho SHIN
Author Information
1. Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea
- Publication Type:Original Article
- From:Chonnam Medical Journal
2023;59(2):128-133
- CountryRepublic of Korea
- Language:English
-
Abstract:
This study aimed to investigate the prevalence of depression among Koreans living in urban and rural areas, stratified by socioeconomic status. The study included 216,765 participants from the 2017 Korean Community Health Survey. Depressive symptoms were assessed using the PHQ-9, with a score of 10 or higher indicating depressive symptoms. Residences with the words Eup and Myeon in their addresses were categorized as rural areas, and residences with Dong in their addresses as urban areas. Socioeconomic status was evaluated by household income and education level. A Poisson regression analysis with sampling weights was conducted and adjusted for demographic, lifestyle, socioeconomic status, and comorbidity. The adjusted prevalence rate of depressive symptoms was 3.33% (95% CI, 3.21-3.45) in urban areas and 2.59% (95% CI, 2.43-2.74) in rural areas. The prevalence of depressive symptoms in urban areas was 1.29 times (95% CI, 1.20-1.38) higher than in rural areas. The prevalence rate ratio for depressive symptoms in urban areas compared to rural areas sorted by monthly incomes was 1.39 (95% CI, 1.28-1.51) for less than 2 million won, 1.22 (95% CI, 1.06-1.41) for 2 to 3.99 million won, and 1.09 (95% CI, 0.90-1.32) for more than 4 million won, and the urban-rural difference was more evident in lower household income subjects (p for interaction=0.033). However, urban-rural differences did not differ according to sex, age, or education level. In conclusion, we found urban-rural differences in depressive symptoms in a representative sample of Koreans, and revealed that these differences may vary according to income level. These results suggest that mental health policy must consider the health disparities according to residence and income.
