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Type of Resource (primo): dissertations
Name: Personal
Name: Personal
Name: Personal
Name: Corporate
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Note: thesis: Thesis (Sc. M.)--Brown University, 2024
Genre (aat): theses
Abstract: Background: The escalating frequency, intensity, and duration of extreme heat events due to climate change pose significant threats to public health and strain healthcare systems. Previous research by Dr. Moretti and colleagues in Rhode Island (RI) found that increased summer temperatures were positively correlated with an increased use of emergency medical services (EMS). However, that study did not account for a potentially uneven geographical distribution of these adverse effects of heat on health that might arise from urban heat islands (UHI), small areas with temperatures elevated by their local built environment. UHIs are also frequently home to socially and economically disadvantaged individuals who live in regions with high values of the Area Deprivation Index (ADI). This research expands upon Dr. Moretti’s research to estimate the relative impacts of hot days in summer, heatwaves, UHIs, and socioeconomic factors on EMS utilization across Rhode Island using data from June-August in the years from 2018 to 2021. Methods: We leverage five existing datasets that describe EMS utilization, daily temperature, UHI indices, ADI scores, and population distribution in RI, to form a new comprehensive database. We utilize day-level and day-subgroup level quasi-Poisson regressions to model the number of daily EMS runs from residential areas with high ADI (7-10). The effects of heat on outcomes may arise from both current and lagged temperatures, which can be modeled either collectively or separately. We employ quasi-Poisson regression models and develop three models with both day and day-subpopulation as the unit of analysis. Temperature is modeled in two ways. One approach uses a cross-basis matrix from a distributed lag nonlinear model (DLNM); the other uses functions of current and lagged temperatures. All models include other covariates to assess the effects of UHI in addition to demographic and other temporal effects. Results: The primary influence on EMS utilization is the current daily mean temperature, showing a nearly positive linear association. Day-level analyses indicated that higher proportions of patients from UHI areas correlate with increased EMS utilization, and the day-subpopulation model suggests a positive UHI effect on EMS utilization when assuming consistent age and UHI distributions across the population and EMS patients. The day-level model reveals that areas with greater proportions of female residents and those under 65 have higher EMS call rates, and the day-subpopulation model suggests a greater EMS utilization for females and individuals younger than 65. Conclusion: Rising ambient temperatures and temporal factors correlate with increased EMS use. Living in UHIs may also increase EMS use but conclusive determinations cannot be made from the data available. Although the results from all three models align qualitatively, the different units of analysis result in distinct interpretations of the findings. Therefore, we cannot draw a firm conclusion. More data are needed on individuals who do not use EMS services to provide a basis for informed policy-making in EMS planning and resource allocation.
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01204599")
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00908554")
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01162455")
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