https://doi.org/10.4081/gh.2022.1132
Spatial analysis and modelling of depression relative to social vulnerability index across the United States
Submitted: 13 July 2022
Accepted: 9 August 2022
Published: 1 September 2022
Accepted: 9 August 2022
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
According to the Substance Abuse and Mental Health Services Administration, about 21 million adults in the US experience a major depressive episode. Depression is considered a primary risk factor for suicide. In the US, about 19.5% of adults are reported to be experiencing a depressive disorder, leading to over 45,000 deaths (14.0 deaths per 100,000) due to suicides. To our knowledge, no previous spatial analysis study of depression relative to the social vulnerability index has been performed across the nation. In this study, county-level depression prevalence and indicators were compiled. We analysed the geospatial distribution of depression prevalence based on ordinary least squares, geographically weighted regression, and multiscale geographically weighted regression models. Our findings indicated that the multiscale model could explain over 86% of the local variance of depression prevalence across the US based on per capita income, age 65 and older, belonging to a minority group (predominantly negative impacts), and disability (mainly positive effect). This study can provide valuable insights for public health professionals and policymakers to address depression disparities.
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How to Cite
Rivera, K. M., & Mollalo, A. (2022). Spatial analysis and modelling of depression relative to social vulnerability index across the United States. Geospatial Health, 17(2). https://doi.org/10.4081/gh.2022.1132
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