ArticleBMC public health2021
Heat illness data strengthens vulnerability maps.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Characterizing Heat Health Outcomes and Informing Public Health Interventions with Medical Claims Data in California.Environmental science & technology · 2026Article
- Global Warming and the Elderly: A Socio-Ecological Framework.International journal of environmental research and public health · 2026Review
- A Machine Learning Model Integrating Remote Sensing, Ground Station, and Geospatial Data to Predict Fine-Resolution Daily Air Temperature for Tuscany, Italy.Remote sensing · 2025Article
- Extreme heat and hospital admissions in older adults: A small-area analysis in the Greater Boston metropolitan area.Environmental epidemiology (Philadelphia, Pa.) · 2025Article
- The Imperative for Hazard- and Place-Specific Assessment of Heat Vulnerability.Environmental health perspectives · 2025Article
- A scoping review of the impact of extreme weather events on health outcomes and healthcare utilization in rural and remote areas.BMC health services research · 2024Article
- Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEBMJ open · 2024Article
- Uses of Social Determinants of Health Data to Address Cardiovascular Disease and Health Equity: A Scoping Review.Journal of the American Heart Association · 2023Article
- Analysis of Exertion-Related Injuries and Fatalities in Laborers in the United States.International journal of environmental research and public health · 2023Article
- Association of Area-Level Heat and Social Vulnerability With Recurrent Hospitalizations Among Individuals With Rheumatic Conditions.Arthritis care & research · 2023Article
- Toward informatics-enabled preparedness for natural hazards to minimize health impacts of climate change.Journal of the American Medical Informatics Association : JAMIA · 2022Review
- Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundPrevious extreme heat and human health studies have investigated associations either over time (e.g. case-crossover or time series analysis) or across geographic areas (e.g. spatial models), which may limit the study scope and regional variation. Our study combines a case-crossover design and spatial analysis to identify: 1) the most vulnerable counties to extreme heat; and 2) demographic and socioeconomic variables that are most strongly and consistently related to heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, acute renal disease, and respiratory disease) across 67 counties in the state of Florida, U. S over 2008-2012.
methodsWe first used a case-crossover design to examine the effects of air temperature on daily counts of health outcomes. We employed a time-stratified design with a 28-day comparison window. Referent periods were extracted from ±7, ±14, or ± 21 days to address seasonality. The results are expressed as odds ratios, or the change in the likelihood of each health outcome for a unit change in heat exposure. We then spatially examined the case-crossover extreme heat and health odds ratios and county level demographic and socioeconomic variables with multiple linear regression or spatial lag models.
resultsResults indicated that southwest Florida has the highest risks of cardiovascular disease, dehydration, acute renal disease, and respiratory disease. Results also suggested demographic and socioeconomic variables were significantly associated with the magnitude of heat-related health risk. The counties with larger populations working in farming, fishing, mining, forestry, construction, and extraction tended to have higher risks of dehydration and acute renal disease, whereas counties with larger populations working in installation, maintenance, and repair workers tended to have lower risks of cardiovascular, dehydration, acute renal disease, and respiratory disease. Finally, our results showed that high income counties consistently have lower health risks of dehydration, heat-related illness, acute renal disease, and respiratory disease.
conclusionsOur study identified different relationships with demographic/socioeconomic variables for each heat-sensitive health outcome. Results should be incorporated into vulnerability or risk indices for each health outcome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.