Evidence map›Paper›PMID 37722035›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Emergency department visits respond nonlinearly to wildfire smoke.

Sam Heft-Neal, Carlos F Gould, Marissa L Childs, Mathew V Kiang, Kari C Nadeau, Mark Duggan, Eran Bendavid, Marshall Burke

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
9.6field-weighted citation impact, top 1% of its field
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

34 citing papers in PubMed, 61 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Associations between wildland fire smoke PMEnvironmental health : a global access science source · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Behavioral responses to wildfire smoke: Insights from smartphone location data.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Valuing wildfire smoke-related mortality benefits from climate mitigation.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  14. Review
  15. Prenatal Exposure to Wildfire and Autism in Children.Environmental science & technology · 2026
    Article
  16. Article
  17. Wildfire-Specific PMGeoHealth · 2026
    Article
  18. Article
  19. Article
  20. Article
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

8 authors at 3 institutions in 1 country.

Sam Heft-NealCenter on Food Security and the Environment, Stanford University, Stanford, CA 94305.ORCID 0000-0002-9129-2365
Carlos F GouldDoerr School of Sustainability, Stanford University, Stanford, CA 94305.ORCID 0000-0002-7736-3905
Marissa L ChildsCenter for the Environment, Harvard University, Cambridge, MA 02138.ORCID 0000-0002-8597-2161
Mathew V KiangDepartment of Epidemiology and Population Health, Stanford University, Stanford, CA 94305.ORCID 0000-0001-9198-150X
Kari C NadeauDepartment of Environmental Health, Harvard University, Cambridge, MA 02138.ORCID 0000-0002-2146-2955
Mark DugganDepartment of Economics, Stanford University, Stanford, CA 94305.ORCID 0000-0001-5251-0131
Eran BendavidDepartment of Health Policy, Stanford University, Stanford, CA 94305.ORCID 0000-0002-8364-4711
Marshall BurkeCenter on Food Security and the Environment, Stanford University, Stanford, CA 94305.ORCID 0000-0003-4288-5858
Stanford University · USHarvard University · USNational Bureau of Economic Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution negatively affects a range of health outcomes. Wildfire smoke is an increasingly important contributor to air pollution, yet wildfire smoke events are highly salient and could induce behavioral responses that alter health impacts. We combine geolocated data covering all emergency department (ED) visits to nonfederal hospitals in California from 2006 to 2017 with spatially resolved estimates of daily wildfire smoke PM[Formula: see text] concentrations and quantify how smoke events affect ED visits. Total ED visits respond nonlinearly to smoke concentrations. Relative to a day with no smoke, total visits increase by 1 to 1.5% in the week following low or moderate smoke days but decline by 6 to 9% following extreme smoke days. Reductions persist for at least a month. Declines at extreme levels are driven by diagnoses not thought to be acutely impacted by pollution, including accidental injuries and several nonurgent symptoms, and declines come disproportionately from less-insured populations. In contrast, health outcomes with the strongest physiological link to short-term air pollution increase dramatically in the week following an extreme smoke day: We estimate that ED visits for asthma, COPD, and cough all increase by 30 to 110%. Data from internet searches, vehicle traffic sensors, and park visits indicate behavioral changes on high smoke days consistent with declines in healthcare utilization. Because low and moderate smoke days vastly outweigh high smoke days, we estimate that smoke was responsible for an average of 3,010 (95% CI: 1,760-4,380) additional ED visits per year 2006 to 2017. Given the increasing intensity of wildfire smoke events, behavioral mediation is likely to play a growing role in determining total smoke impacts.

Indexed as

Air PollutionAsthmaWildfiresCoughEmergency Service, HospitalHumansbehaviorhealthpollutionwildfire

Identifiers

PMID37722035
PMCPMC10523589
OpenAlexW4386824180

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.