Spatial Modeling and Analysis of Heat-Related Morbidity in Maricopa County, Arizona

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.

Automated summary

This study examined the effects of various demographic, socioeconomic, housing, and environmental factors on heat-related morbidity in Maricopa County, Arizona, using OLS regression and MGWR. The results showed that spatial heterogeneity plays a key role in influencing the relationship between these factors, with certain variables having stronger local effects. These findings can help local stakeholders and urban planners address the negative impacts of extreme heat on human health.