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

Chuyuan Wang, Patricia Solís, Lily Villa, Nayan Khare, Elizabeth A. Wentz, Aaron Gettel

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)344-361
Number of pages18
JournalJournal of Urban Health
Issue number3
StatePublished - Jun 2021


  • Census
  • Heat-related morbidity
  • Maricopa County
  • Multiscale geographically weighted regression
  • Remote sensing
  • Spatial heterogeneity

ASJC Scopus subject areas

  • Health(social science)
  • Urban Studies
  • Public Health, Environmental and Occupational Health


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