ArticleInternational journal of health geographics2025
Self-reported mental distress in the United States: a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups.
Article in International journal of health geographics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe COVID-19 had an outstanding impact on well-being and mental health, which might have elicited geographical variations over time. This study examines the eventual impact of COVID-19 on self-reported mental distress in the mainland USA.
aimsThere were two main aims. First, to evaluate the pre-pandemic (2019; [Formula: see text]) and post-pandemic (2021; [Formula: see text]) mental distress spatial distribution. Second, to contrast spatial data across three age groups, young (18-44 years), middle-aged (45-65 years), and old (older than 65 years).
methodWe considered a the Bayesian modified Besag-York-Molliè (BYM2) model, which is a Bayesian hierarchical model. Mental distress was the response variable function of age group, year and spatially structured and unstructured effects.
resultsThe main findings indicate a positive spatial dependence between states of general mental distress before and after the COVID-19 and across age groups with substantial unstructured component. Moreover, younger individuals reported higher levels of mental distress and suffered the major worsening due to the pandemic.
conclusionsCOVID-19 had a detrimental impact on mental health across the population, with consistent evidence of positive spatial dependence across states. Notably, young adults emerged as particularly vulnerable, exhibiting concerning levels of mental distress problems and being more sensitive to the effects of the pandemic. Henceforth, young adults might require specific tailored public health policies in eventual major pandemic events.
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