ArticleJournal of urban health : bulletin of the New York Academy of Medicine2021
Spatial Modeling and Analysis of Heat-Related Morbidity in Maricopa County, Arizona.
Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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.
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Who cites it
5 citing papers in PubMed.
- Epidemiologically validated spatial modelling reveals fine-scale heat health risks.Environmental science and ecotechnology · 2026Article
- Heat-related mortality in Mexico: A multi-scale spatial analysis of extreme heat effects and municipality-level vulnerability.Environment international · 2025Article
- A multi-method spatial analysis of dysentery incidence determinants across Chinese provinces.Frontiers in public health · 2025Article
- Racial Disparities in Climate Change-Related Health Effects in the United States.Current environmental health reports · 2022Review
- Toward Urban Planetary Health Solutions to Climate Change and Other Modern Crises.Journal of urban health : bulletin of the New York Academy of Medicine · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of the present study was to examine the effects of a confluence of demographic, socioeconomic, housing, and environmental factors that systematically contribute to heat-related morbidity in Maricopa County, Arizona, from theoretical, empirical, and spatial perspectives. The present study utilized ordinary least squares (OLS) regression and multiscale geographically weighted regression (MGWR) to analyze health data, U.S. census data, and remotely sensed data. The results suggested that the MGWR model showed a significant improvement in goodness of fit over the OLS regression model, which implies that spatial heterogeneity is an essential factor that influences the relationship between these factors. Populations of people aged 65+, Hispanic people, disabled people, people who do not own vehicles, and housing occupancy rate have much stronger local effects than other variables. These findings can be used to inform and educate local residents, communities, stakeholders, city managers, and urban planners in their ongoing and extensive efforts to mitigate the negative impacts of extreme heat on human health in Maricopa County.
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Registered trials
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