Epidemiol Health.  2017;39:e2017025. 10.4178/epih.e2017025.

Analysis of the relationship between community characteristics and depression using geographically weighted regression

Affiliations
  • 1Korea Centers for Disease Control and Prevention, Cheongju, Korea.
  • 2Graduate School of Public Health, Seoul National University, Seoul, Korea. hokim@snu.ac.kr
  • 3Asian Institute for Energy, Environment and Sustainability, Seoul, Korea.

Abstract


OBJECTIVES
Achieving national health equity is currently a pressing issue. Large regional variations in the health determinants are observed. Depression, one of the most common mental disorders, has large variations in incidence among different populations, and thus must be regionally analyzed. The present study aimed at analyzing regional disparities in depressive symptoms and identifying the health determinants that require regional interventions.
METHODS
Using health indicators of depression in the Korea Community Health Survey 2011 and 2013, the Moran's I was calculated for each variable to assess spatial autocorrelation, and a validated geographically weighted regression analysis using ArcGIS version 10.1 of different domains: health behavior, morbidity, and the social and physical environments were created, and the final model included a combination of significant variables in these models.
RESULTS
In the health behavior domain, the weekly breakfast intake frequency of 1-2 times was the most significantly correlated with depression in all regions, followed by exposure to secondhand smoke and the level of perceived stress in some regions. In the morbidity domain, the rate of lifetime diagnosis of myocardial infarction was the most significantly correlated with depression. In the social and physical environment domain, the trust environment within the local community was highly correlated with depression, showing that lower the level of trust, higher was the level of depression. A final model was constructed and analyzed using highly influential variables from each domain. The models were divided into two groups according to the significance of correlation of each variable with the experience of depression symptoms.
CONCLUSIONS
The indicators of the regional health status are significantly associated with the incidence of depressive symptoms within a region. The significance of this correlation varied across regions.

Keyword

Depression; Depressive disorder; Spatial regression; Spatial analysis; Health status

MeSH Terms

Breakfast
Depression*
Depressive Disorder
Diagnosis
Health Behavior
Health Equity
Health Surveys
Incidence
Korea
Mental Disorders
Myocardial Infarction
Spatial Analysis
Spatial Regression*
Tobacco Smoke Pollution
Tobacco Smoke Pollution
Full Text Links
  • EPIH
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr