Evidence map›Paper›PMID 37563691›Full record

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.

Aynaz Lotfata, Mohammad Moosazadeh, Marco Helbich, Benyamin Hoseini

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Aynaz LotfataDepartment of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, USA.ORCID 0000-0002-2967-3626
Mohammad MoosazadehIntegrated Engineering, Department of Environmental Science and Engineering, College of Engineering, KyungHee University, Yongin, 446-701, Republic of Korea.ORCID 0000-0001-5714-9787
Marco HelbichDepartment of Human Geography and Spatial Planning, Faculty of Geosciences, University Utrecht, Utrecht, The Netherlands.ORCID 0000-0003-0392-8915
Benyamin HoseiniPharmaceutical Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran. binyamin.hoseini@gmail.com.ORCID 0000-0002-0355-6181

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AsthmaRandom ForestAdultArtificial IntelligenceCross-Sectional StudiesEnvironmentHumansPrevalenceSocioeconomic FactorsUnited StatesAsthma prevalenceExplainable machine learningGeographically weighted modelingGeospatial artificial intelligenceRisk factors

Identifiers

PMID37563691
PMCPMC10413687

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.