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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This work was supported by the Virginia G. Piper Charitable Trust. Piper Trust is a private foundation that supports organizations that enrich health, well-being, and opportunity for the people of Maricopa County, Arizona. The conclusions, views, and opinions expressed in this poster are those of the authors and do not necessarily reflect the official policy or position of the Virginia G. Piper Charitable Trust.
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Wang, C., Solís, P., Villa, L. et al. Spatial Modeling and Analysis of Heat-Related Morbidity in Maricopa County, Arizona. J Urban Health 98, 344–361 (2021). https://doi.org/10.1007/s11524-021-00520-7
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DOI: https://doi.org/10.1007/s11524-021-00520-7