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  • 标题:Spatial analysis and modelling of depression relative to social vulnerability index across the United States
  • 本地全文:下载
  • 作者:Kiara M. Rivera ; Abolfazl Mollalo
  • 期刊名称:Geospatial Health
  • 印刷版ISSN:1970-7096
  • 出版年度:2022
  • 卷号:17
  • 期号:2
  • DOI:10.4081/gh.2022.1132
  • 语种:English
  • 出版社:PAGEPress Publications
  • 摘要: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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