ArticleInternational journal of health geographics2023
Socioeconomic and environmental determinants of asthma prevalence: a cross-sectional study at the U.S. County level using geographically weighted random forests.
Article in International journal of health geographics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Prevalence and Risk Factors of Food Allergy and Its Association With Asthma Coexistence and Severity in Bangladeshi Schoolchildren: A GIS-Based Cross-Sectional Study.Food science & nutrition · 2026Article
- Emerging role of SIRT1 in asthma and COPD from molecular mechanisms to translational therapy.iScience · 2026Review
- Factors Influencing Asthma in Children at Early Childhood Development Centres in a Densely Populated Urban Informal Township in Gauteng Province, South Africa.Children (Basel, Switzerland) · 2026Article
- Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.BMC medicine · 2026Article
- Comparative Evaluation of Explainable Machine Learning Versus Linear Regression for Predicting County-Level Lung Cancer Mortality Rate in the United States.JCO clinical cancer informatics · 2025Article
- Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review.Current environmental health reports · 2025Review
- Environmental justice index and prevalence of asthma and COPD in US neighborhoods- a population-based study.Lancet regional health. Americas · 2025Article
- Annual household income and chronic pulmonary conditions in long-term survivors of blood or marrow transplantation: a BMTSS report.BMC pulmonary medicine · 2025Article
- Health implications of safe drinking water act violations: a county-level analysis.Frontiers in public health · 2025Article
- Green space quantity and exposure in relation to the risk of immune-mediated diseases: a scoping review.BMC public health · 2024Article
- Harnessing EHR data for health research.Nature medicine · 2024Review
- The Role of Biodiversity in the Development of Asthma and Allergic Sensitization: A State-of-the-Science Review.Environmental health perspectives · 2024Review
- Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran.Scientific reports · 2024Article
- Analysis of the Predictors of Mortality from Ischemic Heart Diseases in the Southern Region of Brazil: A Geographic Machine-Learning-Based Study.Global heart · 2024Article
- Alzheimer's Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis.American journal of Alzheimer's disease and other dementiasArticle
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4 authors.
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Abstract
backgroundSome studies have established associations between the prevalence of new-onset asthma and asthma exacerbation and socioeconomic and environmental determinants. However, research remains limited concerning the shape of these associations, the importance of the risk factors, and how these factors vary geographically.
objectiveWe aimed (1) to examine ecological associations between asthma prevalence and multiple socio-physical determinants in the United States; and (2) to assess geographic variations in their relative importance.
methodsOur study design is cross sectional based on county-level data for 2020 across the United States. We obtained self-reported asthma prevalence data of adults aged 18 years or older for each county. We applied conventional and geographically weighted random forest (GWRF) to investigate the associations between asthma prevalence and socioeconomic (e.g., poverty) and environmental determinants (e.g., air pollution and green space). To enhance the interpretability of the GWRF, we (1) assessed the shape of the associations through partial dependence plots, (2) ranked the determinants according to their global importance scores, and (3) mapped the local variable importance spatially.
resultsOf the 3059 counties, the average asthma prevalence was 9.9 (standard deviation ± 0.99). The GWRF outperformed the conventional random forest. We found an indication, for example, that temperature was inversely associated with asthma prevalence, while poverty showed positive associations. The partial dependence plots showed that these associations had a non-linear shape. Ranking the socio-physical environmental factors concerning their global importance showed that smoking prevalence and depression prevalence were most relevant, while green space and limited language were of minor relevance. The local variable importance measures showed striking geographical differences.
conclusionOur findings strengthen the evidence that socio-physical environments play a role in explaining asthma prevalence, but their relevance seems to vary geographically. The results are vital for implementing future asthma prevention programs that should be tailor-made for specific areas.
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