哮喘患病率的社会经济和环境决定因素:在美国县级使用地理加权随机森林的横断面研究。

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Health Geographics Pub Date : 2023-08-10 DOI:10.1186/s12942-023-00343-6
Aynaz Lotfata, Mohammad Moosazadeh, Marco Helbich, Benyamin Hoseini
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引用次数: 0

摘要

背景:一些研究已经确定了新发哮喘和哮喘加重的患病率与社会经济和环境决定因素之间的关联。然而,关于这些关联的形式、风险因素的重要性以及这些因素在地理上如何变化的研究仍然有限。目的:我们的目的是(1)研究美国哮喘患病率与多种社会物理决定因素之间的生态关联;(2)评估其相对重要性的地理差异。方法:我们的研究设计是基于2020年美国县级数据的横断面设计。我们获得了每个县18岁及以上成年人自我报告的哮喘患病率数据。我们应用传统和地理加权随机森林(GWRF)来调查哮喘患病率与社会经济(如贫困)和环境决定因素(如空气污染和绿地)之间的关系。为了提高GWRF的可解释性,我们(1)通过部分依赖图评估关联的形状,(2)根据其全局重要性评分对决定因素进行排序,以及(3)对局部变量重要性进行空间映射。结果:3059个县平均哮喘患病率为9.9(标准差±0.99)。GWRF优于传统的随机森林。例如,我们发现了一个迹象,温度与哮喘患病率呈负相关,而贫困与哮喘患病率呈正相关。部分依赖图显示,这些关联具有非线性形状。对社会物理环境因素的全球重要性进行排名表明,吸烟率和抑郁症患病率是最相关的,而绿地和有限的语言是次要的。地方变量重要性度量显示出显著的地理差异。结论:我们的研究结果加强了社会物理环境在解释哮喘患病率方面发挥作用的证据,但它们的相关性似乎在地理上有所不同。这些结果对于实施未来针对特定地区的哮喘预防计划至关重要。
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Socioeconomic and environmental determinants of asthma prevalence: a cross-sectional study at the U.S. County level using geographically weighted random forests.

Background: Some 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.

Objective: We 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.

Methods: Our 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.

Results: Of 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.

Conclusion: Our 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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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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