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Air Conditioning in Nursing Homes and Mortality During Extreme Heat

2025· article· en· W4417334213 on OpenAlexaffabout
Gabrielle M. Katz, Kevin A. Brown, Vasily Giannakeas, Nathan M. Stall

Bibliographic record

VenueJAMA Internal Medicine · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity Health NetworkWomen's College HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsNursing homesExtreme heatExtreme ColdMEDLINEExtreme weather

Abstract

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Importance: Extreme heat poses a serious health risk to older adults because they are generally more susceptible to heat-related mortality. Many nursing homes in the US and elsewhere lack air conditioning (AC). Ecological studies have evaluated the protective role of AC against mortality on extreme heat days in prisons and large urban settings; however, the nursing home setting remains understudied. Objective: To assess mortality rates during extreme heat days in nursing homes with AC compared to those without AC. Design, Setting, and Participants: This was a case-crossover study conducted in Ontario, Canada, to determine the odds of mortality associated with extreme days separated for nursing homes with and without AC using conditional logistic regression. Nursing home residents who died during the warm months (June to September) from 2010 to 2023 were included. Data were analyzed from June 2024 to April 2025. Exposures: An extreme heat day was defined as any day in the ≥90th percentile of the heat index (ambient temperature and relative humidity) for any given nursing home location during the study period. Main Outcomes and Measures: All-cause mortality during extreme heat days, by AC status of nursing homes. Results: Of the 73 578 deaths of nursing home residents from 2010 to 2023, 40 255 residents (mean [SD] age, 86.8 [8.8] years; 65.6% women) died at 276 homes with AC and 33 323 residents (mean [SD] age, 87.2 [8.7] years; 64.8% women) at 339 homes without AC. Before the AC mandate was announced in July 2020, nursing homes without AC (55.1%) were predominantly investor owned (ie, for profit; standardized mean difference [SMD], 0.47), were built to older design standards (SMD, 0.57), and had more residents per room (SMD, 0.58) compared with nursing homes with AC. Overall, 4889 deaths (13.8%) in nursing homes without AC occurred on extreme heat days compared with 4611 deaths (12.1%) in those with AC. Extreme heat was associated with significantly increased odds of mortality in nursing homes without AC (odds ratio [OR], 1.11; 95% CI, 1.06-1.16) but not in those with AC (OR, 1.03; 95% CI, 0.98-1.07). Compared to nursing homes with AC, those without AC were associated with significantly higher relative odds of mortality on extreme heat days (relative OR, 1.08; 95% CI, 1.01-1.15). Lagged analyses suggest that the associated effects of extreme heat persisted for 3 days beyond the initial exposure. Conclusion and Relevance: In this case-crossover study, mortality was lower during extreme heat days in nursing homes with AC compared to those without AC. These findings suggest that AC provision in nursing homes and other congregate care settings may be important for preventing mortality among older adults during extreme heat days.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.356
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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