ArticleThe Journal of allergy and clinical immunology2026
Predicting asthma prevalence across US communities by integrating social vulnerability and environmental risk with machine learning.
Article in The Journal of allergy and clinical immunology, 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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6 authors.
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Abstract
backgroundAsthma is one of the most common chronic conditions in the United States, disproportionately affecting racial and ethnic minority populations and low-income communities. Although both social and environmental factors are known contributors to asthma prevalence, the extent to which they interact to shape geographic disparities remains insufficiently understood.
objectiveThis study aimed to explore how these factors vary across regions with differing asthma prevalence and thereby identify patterns that may inform targeted public health responses.
methodsWe used the US Centers for Disease Control and Prevention's 2022 Environmental Justice Index, which includes standardized social and environmental measures at the census tract level. K-means clustering identified geographic clusters with varying asthma prevalence based on asthma rates and related health outcomes. A random forest model was trained to predict asthma rates by using social and environmental variables, and feature importance was analyzed.
resultsWe identified 9 clusters, with 3 showing the highest asthma prevalence. High-prevalence areas had greater social vulnerability, including higher poverty rate, minority population rate, limited English proficiency, unemployment, and housing cost burden. They also experienced greater environmental exposures, such as elevated level of fine particulate matter with an aerodynamic diameter of 2.5 μm or less, ozone, diesel pollution, more land near hazardous waste sites, more chemical facilities, and older housing. The random forest model predicted asthma rates with strong predictive performance (R
conclusionsGeographic areas with high asthma prevalence are shaped by overlapping social and environmental vulnerabilities. Socioeconomic disparities emerged as particularly influential. These findings support integrated, data-driven public health strategies to address asthma inequities.
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