The Laryngoscope
October 13, 2026 · via Europe PMC
Wildfire Air Pollution Exposure and Head and Neck Cancer Incidence.
Jung YS, Yu SE, Nadeau KC, +5 more, Lee SE.
AI summary — for doctors, generated from the abstract only
Higher exposure to wildfire-specific fine particulate matter was associated with higher head and neck cancer incidence, with the strongest signal for laryngeal cancer and for long-term exposure.
What was studied
Retrospective ecological cohort using SEER data (2016-2022) and county-level wildfire-specific PM2.5 (wPM2.5) exposure, modelled with a distributed lag non-linear model over 10 years and adjusted for health behaviours, demographics, population size and year.
Key findings
- Cumulative relative risk of head and neck cancer was 1.06 (95% CI 1.04-1.09) per additional smoke exceedance day and 1.41 (1.24-1.60) for any annual exposure.
- Laryngeal cancer showed the largest effect (cRR 1.13, 1.07-1.19), followed by oropharyngeal (1.09, 1.06-1.13) and oral cavity cancer (1.03, 1.00-1.06) over a 10-year lag.
- Associations were significant for p16-positive, p16-negative and p16-unknown tumours.
Clinical relevance
Wildfire smoke may be an emerging environmental contributor to head and neck cancer risk, relevant to public health planning and counselling in smoke-prone regions.
Who should care
Limitations
This is a county-level ecological analysis, so individual exposure and confounding by smoking, alcohol or other factors cannot be fully excluded; association does not prove causation. Latency of cancer development may exceed the study period.
Wildfire smoke exposure was associated with higher head and neck cancer incidence, but individual-level studies are needed to confirm a causal link.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Objectives
To determine the association between wildfire-specific particulate matter 2.5 (wPM2.5) exposure and the overall and site-specific incidences of head and neck and aerodigestive cancer (HNC).
Study design
Epidemiological retrospective cohort analysis.
Methods
HNC incidence data were derived from the Surveillance, Epidemiology, and End Results Program (2016-2022). The relationship between county-level wPM2.5 exposure metrics and HNC incidence rates were examined using a distributed lag non-linear model, adjusting for health behaviors (tobacco/alcohol use, diet, exercise, and sexual activity), demographics (age, sex, race/ethnicity), population size, and year, with county as a random effect. Lag effects were analyzed over 10 years. HNC subsites included nasal/sinus/ear, nasopharynx, oral cavity, oropharynx (stratified by p16 status), hypopharynx, and larynx.
Results
Higher wildfire-specific PM2.5 exposure was associated with increased cumulative HNC incidence over 0-10-year lags, with a cumulative relative risk (cRR) of 1.06 (95% CI: 1.04-1.09) per additional smoke exceedance day, 1.41 (1.24-1.60) for any annual exposure, and 1.23 (1.13-1.33) per percentage-point increase in days above 5 μg/m3. Among subsites, oral cavity cancer showed consistent increases (cRR 1.03, 95% CI: 1.00-1.06), oropharyngeal cancer risk increased to 1.09 (1.06-1.13), and laryngeal cancer exhibited the largest effect, with a cRR of 1.13 (1.07-1.19) per additional exceedance day over a 10-year lag period. When stratified by p16 status, significant associations were noted for p16-positive, p16-negative, and p16-unknown tumors.
Conclusions
Higher frequency, intensity, or persistence of wildfire-smoke exposure is associated with increased HNC risk, with the strongest associations driven by long-term exposures.
Level of evidence: 3
DOI
10.1002/lary.70874
PMID
42870377
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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