Evidence map›Paper›PMID 40497792›Full record

ArticleEnvironmental health perspectives2025

Advancing extreme heat risk assessments to better capture individually-experienced temperatures: A new approach to describe individual and subgroup vulnerabilities.

Carina J Gronlund, David M Hondula, Evan Mallen, Marie S O'Neill, Mayuri Rajput, E Scott Krayenhoff, Ashley Broadbent, Santiago C Grijalva, Larissa S Larsen, Sharon L Harlan and 1 more

Abstract read
In one paragraph

Article in Environmental health perspectives, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

11 authors.

Carina J GronlundInstitute for Social Research, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0000-0002-0533-745X
David M HondulaSchool of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA.
Evan MallenSchool of City and Regional Planning, Georgia Institute of Technology, Atlanta, Georgia, USA.
Marie S O'NeillSchool of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Mayuri RajputSchool of Architecture, Georgia Institute of Technology, Atlanta, Georgia, USA.
E Scott KrayenhoffSchool of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada.
Ashley BroadbentSchool of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA.
Santiago C GrijalvaSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
Larissa S LarsenTaubman College of Architecture and Urban Planning, University of Michigan, Ann Arbor, Michigan, USA.
Sharon L HarlanDepartment of Public Health and Health Sciences and Department of Sociology and Anthropology, Northeastern University, Boston, MA, USA.
Brian StoneSchool of City and Regional Planning, Georgia Institute of Technology, Atlanta, Georgia, USA.

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
Scientific/Technical CoreP2CHD041028 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sarah A. Burgard · 2017 to 2026
$6.5M
Assessing the Neuropsychological Benefits of Weatherization ProgramsR01ES032157 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Carina Gronlund · 2021 to 2026
$3.0M
Causal Mechanisms for Sustainable Adaptation to Adverse Heat and Precipitation Health EffectsR00ES026198 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GRONLUND, CARINA · 2019 to 2021
$732k
NICHD NIH HHS P2C HD041028NIEHS NIH HHS P30 ES017885NIEHS NIH HHS R00 ES026198NIEHS NIH HHS R01 ES032157
6 · The paper itself

Abstract

backgroundExtreme heat risk assessments often rely on epidemiologic studies that used the nearest available outdoor airport temperatures (OATs) rather than individually-experienced temperatures (IETs) and frequently lack key individual-level determinants of exposure, including occupation, housing, and air conditioning. This hampers efforts to characterize heat burden inequities and guide interventions for vulnerable populations.

objectivesWe developed an approach to estimate individual and subgroup-specific health impacts from modeled IETs before and during extreme heat events for three U.S. cities: Atlanta, Georgia (hot-humid), Detroit, Michigan (temperate), and Phoenix, Arizona (hot-dry).

methodsIET profiles were estimated using modeled parcel-linked population microdata, housing-specific indoor temperatures from building energy models, ambient temperatures from urban-scale climate models, and time activity patterns from surveys. We linked each IET profile to daily OATs, then fit mixed-effects regressions to predict "equivalent" OATs (eOATs), based on IET, housing, and demographics. We assigned risk ratios (RRs) from existing literature on all-cause mortality, all-cause emergency department (ED) visits, and preterm births to each person-day's eOAT and estimated 5-day-extreme-heat absolute risks (ARs) by age-race-income-occupation subgroup.

resultsThe eOATs, RRs, and ARs differed between people due to variability in IETs and baseline health outcome incidence rates. All-cause mortality RRs ranges were 1.00-1.16 (Atlanta), 1.01-7.08 (Detroit), and 1.00-6.38 (Phoenix). All-cause-mortality ARs ranged 0.01-32 (Atlanta), 0.01-1,100 (Detroit), and 0.01-950 (Phoenix) per 100,000 persons. ED visit ARs ranges were 0.2-270 (Atlanta) and 0.04-6,200 (Phoenix) per 100,000 persons. Heat mortality ARs were higher among older adults and, only in Detroit, in young, Black, outdoor workers (median = 6.6 per 100,000) compared to young, non-Black, higher-income, indoor workers (median = 0.3 per 100,000). DISCUSSION: When IETs can be estimated or directly measured, person-specific eOATs can be used to estimate the subgroup-specific heat-health burdens that would be experienced without adaptive behaviors. This approach could be adapted for other contexts to inform climate preparedness and justice policies. https://doi.org/10.1289/EHP15223.

Identifiers

PMID40497792
PMCPMC12927444

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.