Climate change and health disparities: assessing local, regional, and national health inequities in the United States
Date
2026
DOI
Authors
Version
Embargo Date
2027-05-18
OA Version
Citation
Abstract
Climate change is a critical global public health concern with unevenly distributed health hazards. In the U.S., persistently marginalized populations face the highest burden of hazardous environmental exposures and subsequent health disparities. This dissertation includes a novel method for health impact assessments of environmental health disparities and two quasi-experimental study designs evaluating understudied populations and health outcomes.In my first study, I addressed a gap in publicly available, highly spatially resolved population data, constructing an address-level synthetic population (‘matched allocation’) using publicly available U.S. Census and tax property data. I compared this population with a random assignment of households to addresses. From these comparisons, I found that strong interactions between modifiers and exposures contributed to differences in health impacts. In my second study, I used a quasi-experimental study design with a difference-in-differences estimator to investigate psychiatric emergency services use for 1) hot days with and without alerts, and 2) hot days after compared to before the implementation of a citywide climate resilience plan. I found no appreciable evidence of change in the incidence rate ratios (IRRs) for: services use on hot days with compared to without alerts (IRR: 1.06, 95% CI: 0.93, 1.19) or services use on hot days after compared to before the plan (IRR: 1.03, 95% CI: 0.97, 1.09). Alert systems alone may be insufficient at preventing adverse outcomes in vulnerable populations. In my third study, I used a time-stratified case-crossover study design to examine associations between summertime heat index and mental-health related hospitalizations among adult Medicaid beneficiaries. I derived climate, sex, age, and race/ethnicity group-specific effect estimates and conducted a meta-analysis across climate regions. Models with lags (0-6 days) showed increased risks at the 1st (IRR: 1.24, 95% CI 1.21, 1.28) and 99th (IRR: 1.07, 95% CI 1.04, 1.11) percentiles in the continental group and decreased risk in the 95th percentile (IRR: 0.94, 95% CI 0.91, 0.97) in the tropical/temperate group. Further stratifications revealed greater magnitudes of effects among males, older age groups, and non-White race/ethnicity groups.
These three studies implement a range of methods to identify and examine climate change-related health disparities.
Description
2026
License
Attribution-NonCommercial-NoDerivatives 4.0 International