Evidence map›Paper›PMID 40305019›Full record

ArticleJAMA network open2025

Wildfire Smoke Exposure and Cause-Specific Hospitalization in Older Adults.

Sofia L Vega, Marissa L Childs, Sarika Aggarwal, Rachel C Nethery

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Long-term exposure to wildfire smoke and mortality: Heterogeneous effects by exposure metric and across subpopulations.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sofia L VegaDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Marissa L ChildsCenter for the Environment, Harvard University, Boston, Massachusetts.
Sarika AggarwalDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Rachel C NetheryDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

Funding

XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI Sheela Sathyanarayana · 1995 to 2026
$42.5M
GRADUATE TRAINING IN BIOSTATISTICST32ES007142 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Brent Andrew Coull · 1985 to 2026
$11.9M
Causal machine learning methods for studying the effects of environmental exposures on childhood cancer using natural experimentsK01ES032458 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI NETHERY, RACHEL C · 2021 to 2023
$417k
NIEHS NIH HHS K01 ES032458NIEHS NIH HHS P30 ES007033NIEHS NIH HHS T32 ES007142
6 · The paper itself

Abstract

Importance: The escalating intensity of wildfires in the western US is increasing exposure to smoke pollution. Previous studies of wildfire smoke and health have primarily focused on mortality and respiratory and cardiovascular events, with limited research on broader health impacts or on the shape of concentration-response curves. Objective: To characterize the associations between exposure to smoke-specific fine particulate matter (PM2.5) and cause-specific hospitalizations among older adults in the western US. Design, Setting, and Participants: This retrospective cohort study used Medicare inpatient claims data from 2006 to 2016 linked with machine learning-derived smoke-specific PM2.5 to assess associations between smoke PM2.5 and hospitalization rates. Participants included Medicare beneficiaries aged 65 years or older who lived in a western US state (ie, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, or Wyoming). Analyses were conducted from October 2023 to February 2025. Exposures: Daily county-level smoke-specific PM2.5 concentrations were estimated from machine learning models trained on monitor and satellite data. Main Outcomes and Measures: Daily county-level rates of unscheduled hospitalization for each of 13 broad cause categories. To characterize the association between each cause of hospitalization and smoke PM2.5, distributed lag models were fitted with hospitalization rates modeled as a function of same-day smoke PM2.5 exposure and exposures on each day of the preceding week, using splines on exposure to allow for nonlinearity. Results: The study included 10 369 361 individuals (mean [SD] age, 74.7 [7.9] years; 4 862 826 male [46.9%]; 5 506 535 female [53.1%]; 373 252 Black [3.6%]; 420 577 Hispanic [4.1%]; and 8 365 607 White [80.7%]), 57 million person-months of follow-up, and 4.7 million unscheduled hospitalizations. Smoke PM2.5 concentration-response curves for respiratory hospitalizations and cardiovascular hospitalizations were flat at lower concentrations but showed increasing trends at concentrations above 25 μg/m3. On average, daily hospitalizations (per 100 000) increased by 2.40 (95% CI, 0.17 to 4.63) for respiratory concerns when increasing same-day and preceding week smoke PM2.5 concentrations from 0 to 40 μg/m3; hospitalizations for cardiovascular concerns increased by 2.61 (95% CI, -0.09 to 5.30), a difference that was not statistically significant. No associations were observed for other causes of hospitalization. Conclusions and Relevance: In this cohort study, exposure to high levels of smoke pollution was associated with an increase in hospitalizations for respiratory diseases. These findings underscore the need for interventions to mitigate the health impacts of wildfire smoke exposure.

Indexed as

Environmental ExposureHospitalizationParticulate MatterSmokeWildfiresAgedAged, 80 and overAir PollutantsFemaleHumansMaleMedicareRetrospective StudiesUnited StatesAir PollutantsParticulate MatterSmoke

Identifiers

PMID40305019
PMCPMC12044514

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Registered trials

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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.