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Wildfires are associated with increased emergency department visits for anxiety disorders in the western United States


As wildfires increasingly impact the global economy and public health, understanding their effects is crucial. Particularly, the relationship between wildfires and anxiety disorders remains unclear. In this study, we explore this association by analyzing 1,897,865 emergency department visits for anxiety disorders in the western United States. We examined records from 2007 to 2018, using a case-crossover design and conditional logistic regression to assess the impact of wildfire-related exposures on these visits. Here we show that exposure to wildfire smoke PM2.5 is positively linked with emergency department visits for anxiety disorders. This effect is more pronounced in women and girls and in older adults, highlighting their vulnerability. Notably, major smoke events (smoke PM2.5 contributed ≥75% of the total PM2.5) significantly amplify this risk. These findings underscore the psychological impacts of wildfires and their smoke, suggesting a need for targeted disaster risk reduction and climate risk management strategies, especially for vulnerable groups such as older adults and women. Our results call for increased climate awareness and tailored risk communication to mitigate these emerging health challenges.

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Fig. 1: The age- and sex-stratified analysis for 48 hour smoke PM2.5.
Fig. 2: The age- and sex-stratified analysis for smoke events and major smoke events.
Fig. 3: The age- and sex-stratified analysis for active fire points.

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Data availability

As part of the data use agreement with individual states, we are prohibited from sharing the ED visits data to protect identifiable health information. However, similar data used in this analysis can be directly requested from the corresponding health departments or hospital association. The Daymet daily 1 km meteorological data are publicly available in the Oak Ridge National Laboratory data archive ( The active-fire-point data are publicly available in the FIRMS database ( The zip code level wildfire smoke PM2.5 data used for this study can be found on Figshare ( The original 1 km wildfire smoke PM2.5 data are available on reasonable request from the corresponding author. Source data are provided with this paper.

Code availability

The raw ED visits data were processed with SAS (version 9.4). The FIRMS active-fire data, Daymet meteorological data, and wildfire smoke PM2.5 data were collected and processed with R (version 4.0.5). All the statistical analyses and plotting were done with R (version 4.0.5). The package survival (version 3.2-10) was used to perform the conditional logistic regression analysis and is publicly available at This study does not involve any custom algorithms/software that are relevant to the core analyses. The R code is available in the GitHub repository (, or on reasonable request from the corresponding author and Q.Z. ( The SAS code is available on reasonable request from H.H.C. ( and R.R.D. (


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This work was supported by the National Institute of Environmental Health Sciences of the National Institutes of Health (NIH; awards R01ES034175 (Y.L.) and R01ES027892 (H.H.C.), P30ES019776 (C. Marsit)). The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. We are grateful for the support of the health data sources listed in the following sentence and their contributing hospitals. The ED visits data used to produce this publication were acquired from the Arizona Department of Health Services; California Office of Statewide Planning and Development, now California Department of Health Care Access and Information; Nevada Division of Health Care Financing and Policy (DJCFP), released through the Center for Health Information Analysis (CHIA) of the University of Nevada, Las Vegas; Oregon Healthcare Enterprises, Inc., Apprise Health Insights, a subsidiary of the Oregon Association of Hospitals & Health Systems; and Utah Department of Health, Office of Health Care Statistics (OHCS). The contents of this publication, including data analysis, interpretation, conclusions derived, and the views expressed herein, are solely those of the authors and do not represent the conclusions or official views of listed data sources. Authorization to release this information does not imply endorsement of this study or its findings by any of these data sources. The data sources, their employees, officers, and agents make no representation, warranty, or guarantee as to the accuracy, completeness, currency, or suitability of the information provided here.

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Authors and Affiliations



Q.Z., Y.L., and H.H.C. conceptualized the study and designed the analysis. D.Z. and W.W. produced the wildfire data. R.R.D. processed the ED visits data. H.Z. and Q.Z. collected the Daymet meteorological data. Q.Z. performed the main analyses in consultation with K.S., N.S., S.E., H.H.C., and Y.L. The data visualization was completed by Q.Z. and B.Y. Q.Z. wrote the initial paper in collaboration with D.Z., W.W., R.R.D., and H.Z. The paper was reviewed and edited by B.Y., K.S., N.S., S.E., H.H.C., and Y.L. The supporting fundings were acquired by S.E., H.H.C., and Y.L. All collaborators of this study that have fulfilled the criteria for authorship required by Nature Portfolio journals have been included as co-authors of this paper. The roles and responsibilities were agreed among collaborators ahead of the research.

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Correspondence to Yang Liu.

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Nature Mental Health thanks Amy Lykins, Manzhu Yu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zhu, Q., Zhang, D., Wang, W. et al. Wildfires are associated with increased emergency department visits for anxiety disorders in the western United States. Nat. Mental Health 2, 379–387 (2024).

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