ArticleFrontiers in public health2026
A multiscale geospatial analysis integrating explainable machine learning to characterize spatial disparities in melanoma mortality associated with environmental justice and healthcare access in the contiguous United States.
Article in Frontiers in public health, 2026. 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
Background: Melanoma mortality exhibits profound geographical disparities associated with complex sociodemographic, environmental, and healthcare factors. Traditional spatial models may not fully capture the multi-scale heterogeneity underlying these geographic disparities. This study aimed to characterize the spatial heterogeneity and operational scales of factors associated with county-level melanoma mortality across the United States. Methods: We conducted a county-level ecological study across the contiguous US (2018-2024). To address mortality data suppression by the Centers for Disease Control and Prevention (CDC) (deaths < 10), a representativeness analysis was performed. Predefined core covariates (median age, UV exposure, dermatologist density) were integrated with 45 Environmental Justice Index (EJI) indicators. Feature selection was performed using an XGBoost-SHAP pipeline followed by stepwise AICc optimization. Multiscale Geographically Weighted Regression (MGWR) was employed to evaluate spatial non-stationarity and operational scales, comparing its performance against ordinary least squares (OLS) and standard geographically weighted regression (GWR) models. Results: The analytical sample comprised 1,156 counties, representing 88.6% of the total US population. MGWR demonstrated superior explanatory power ( Conclusions: Melanoma mortality exhibits multiscale spatial patterns. The limited association observed for environmental UV exposure suggests that demographic structure and healthcare-related factors may play important roles in explaining county-level mortality disparities. These findings support spatially targeted public health strategies, including improved dermatological care access in aging and disaster-prone regions.
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