Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

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

Nature Mental Health volume 2, pages 379–387 (2024)Cite this article

Subjects

Abstract

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.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

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.

Similar content being viewed by others

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 (https://doi.org/10.3334/ORNLDAAC/2129). The active-fire-point data are publicly available in the FIRMS database (https://firms.modaps.eosdis.nasa.gov/active_fire/). The zip code level wildfire smoke PM2.5 data used for this study can be found on Figshare (https://doi.org/10.6084/m9.figshare.25016510). 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 https://cran.r-project.org/web/packages/survival/index.html. 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 (https://github.com/qingyang-remote-sensing/NMH_anxiety_paper/), or on reasonable request from the corresponding author and Q.Z. (qingyang.zhu@emory.edu). The SAS code is available on reasonable request from H.H.C. (howard.chang@emory.edu) and R.R.D. (rohan.dsouza@emory.edu).

References

  1. Ellis, T. M. et al. Global increase in wildfire risk due to climate-driven declines in fuel moisture. Glob. Change Biol. 28, 1544–1559 (2022).

    Article  Google Scholar 

  2. Jones, M. W. et al. Global and regional trends and drivers of fire under climate change. Rev. Geophys. 60, e2020RG000726 (2022).

    Article  Google Scholar 

  3. Amrutha, K. et al. Demarcation of forest fire risk zones in Silent Valley National Park and the effectiveness of forest management regime. J. Geovis. Spat. Anal. 6, 8 (2022).

    Article  Google Scholar 

  4. Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6, 7537 (2015).

    Article  PubMed  Google Scholar 

  5. Richardson, D. et al. Global increase in wildfire potential from compound fire weather and drought. NPJ Clim. Atmos. Sci. 5, 23 (2022).

    Article  Google Scholar 

  6. Gannon, C. S. & Steinberg, N. C. A global assessment of wildfire potential under climate change utilizing Keetch–Byram drought index and land cover classifications. Environ. Res. Commun. 3, 035002 (2021).

    Article  Google Scholar 

  7. Zhang, L. et al. Large wildfires in the western United States exacerbated by tropospheric drying linked to a multi-decadal trend in the expansion of the Hadley Circulation. Geophys. Res. Lett. 47, e2020GL087911 (2020).

    Article  Google Scholar 

  8. Burke, M. et al. The changing risk and burden of wildfire in the United States. Proc. Natl Acad. Sci. USA 118, e2011048118 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Elser, H. et al. Wildfire smoke exposure and emergency department visits for headache: A case-crossover analysis in California, 2006–2020. Headache 63, 94–103 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Reid, C. E. et al. Critical review of health impacts of wildfire smoke exposure. Environ. Health Perspect. 124, 1334–1343 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Wu, J., Snell, G. & Samji, H. Climate anxiety in young people: a call to action. Lancet Planet. Health 4, e435–e436 (2020).

    Article  PubMed  Google Scholar 

  12. GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry 9, 137–150 (2022).

  13. Vos, T. et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1204–1222 (2020).

    Article  Google Scholar 

  14. Yang, X. et al. Global, regional and national burden of anxiety disorders from 1990 to 2019: results from the Global Burden of Disease Study 2019. Epidemiol. Psychiatr. Sci. 30, e36 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Clayton, S. Climate anxiety: psychological responses to climate change. J. Anxiety Disord. 74, 102263 (2020).

    Article  PubMed  Google Scholar 

  16. To, P., Eboreime, E. & Agyapong, V. I. O. The impact of wildfires on mental health: a scoping review. Behav. Sci. 11, 126 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Pun, V. C., Manjourides, J. & Suh, H. Association of ambient air pollution with depressive and anxiety symptoms in older adults: results from the NSHAP study. Environ. Health Perspect. 125, 342–348 (2017).

    Article  PubMed  Google Scholar 

  18. Power, M. C. et al. The relation between past exposure to fine particulate air pollution and prevalent anxiety: observational cohort study. Br. Med. J. 350, h1111 (2015).

    Article  Google Scholar 

  19. Shi, W. et al. Depression and anxiety associated with exposure to fine particulate matter constituents: a cross-sectional study in North China. Environ. Sci. Technol. 54, 16006–16016 (2020).

    Article  PubMed  Google Scholar 

  20. Zhao, W. et al. PM2.5 exposure associated with prenatal anxiety and depression in pregnant women. Ecotoxicol. Environ. Saf. 248, 114284 (2022).

    Article  PubMed  Google Scholar 

  21. Hao, G. et al. Associations of PM2.5 and road traffic noise with mental health: evidence from UK Biobank. Environ. Res. 207, 112221 (2022).

    Article  PubMed  Google Scholar 

  22. Eisenman, D. P. & Galway, L. P. The mental health and well-being effects of wildfire smoke: a scoping review. BMC Public Health 22, 2274 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Mirabelli, M. C. et al. Wildfire smoke and symptoms affecting mental health among adults in the US state of Oregon. Prev. Med. 164, 107333 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Humphreys, A. et al. What can we do when the smoke rolls in? An exploratory qualitative analysis of the impacts of rural wildfire smoke on mental health and wellbeing, and opportunities for adaptation. BMC Public Health 22, 41 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Agyapong, V. I. O. et al. Prevalence rates and predictors of generalized anxiety disorder symptoms in residents of Fort McMurray six months after a wildfire. Front. Psychiatry 9, 345 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Li, S. H. & Graham, B. M. Why are women so vulnerable to anxiety, trauma-related and stress-related disorders? The potential role of sex hormones. Lancet Psychiatry 4, 73–82 (2017).

    Article  PubMed  Google Scholar 

  27. Lachlan, K. A. et al. The 2018 California wildfires: examining sex differences in response to crisis communication and underlying processes. Atl. J. Commun. 31, 85–96 (2023).

    Article  Google Scholar 

  28. Hong, J. et al. Significant association between increased risk of emergency department visits for psychiatric disorders and air pollutants in South Korea. J. Expo. Sci. Environ. Epidemiol. 33, 490–499 (2023).

    Article  PubMed  Google Scholar 

  29. Szyszkowicz, M. et al. Air pollution and emergency department visits for mental disorders among youth. Int. J. Environ. Res. Public Health 17, 4190 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ferreira, A. P. S. et al. Experimental rodent models exposed to fine particulate matter (PM2.5) highlighting the injuries in the central nervous system: a systematic review. Atmos. Pollut. Res. 13, 101407 (2022).

    Article  Google Scholar 

  31. Chu, C. et al. Ambient PM2.5 caused depressive-like responses through Nrf2/NLRP3 signaling pathway modulating inflammation. J. Hazard. Mater. 369, 180–190 (2019).

    Article  PubMed  Google Scholar 

  32. Hong, J. S. et al. Mental health effects of the Gangwon wildfires. BMC Public Health 22, 1183 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Andréen, L. et al. Sex steroid induced negative mood may be explained by the paradoxical effect mediated by GABAA modulators. Psychoneuroendocrinology 34, 1121–1132 (2009).

    Article  PubMed  Google Scholar 

  34. Kondo, M. C. et al. Meta-analysis of heterogeneity in the effects of wildfire smoke exposure on respiratory health in North America. Intl J. Environ. Res. Public Health 16, 960 (2019).

    Article  Google Scholar 

  35. Masri, S. et al. Disproportionate impacts of wildfires among elderly and low-income communities in California from 2000–2020. Intl J Environ. Res. Public Health 18, 3921 (2021).

    Article  Google Scholar 

  36. Wibbenmeyer, M. & Robertson, M. The distributional incidence of wildfire hazard in the western United States. Environ. Res. Lett. 17, 064031 (2022).

    Article  Google Scholar 

  37. Vasiliadis, H. M. et al. The excess healthcare costs associated with depression and anxiety in elderly living in the community. Am. J. Geriatr. Psychiatry 21, 536–548 (2013).

    Article  PubMed  Google Scholar 

  38. Zhang, D. et al. A machine learning model to estimate ambient PM2.5 concentrations in industrialized highveld region of South Africa. Remote Sens. Environ. 266, 112713 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zhu, Q. et al. Satellite-based long-term spatiotemporal patterns of surface ozone concentrations in China: 2005–2019. Environ. Health Perspect. 130, 027004 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Filonchyk, M., Peterson, M. P. & Sun, D. Deterioration of air quality associated with the 2020 US wildfires. Sci. Total Environ. 826, 154103 (2022).

    Article  PubMed  Google Scholar 

  41. Levin, N. & Heimowitz, A. Mapping spatial and temporal patterns of Mediterranean wildfires from MODIS. Remote Sens. Environ. 126, 12–26 (2012).

    Article  Google Scholar 

  42. Klotzbach, P. J. et al. Trends in global tropical cyclone activity: 1990–2021. Geophys. Res. Lett. 49, e2021GL095774 (2022).

    Article  Google Scholar 

  43. Sibolla, B. H., Van Zyl, T. & Coetzee, S. Determining real-time patterns of lightning strikes from sensor observations. J. Geovis. Spat. Anal. 5, 4 (2021).

    Article  Google Scholar 

  44. Zhang, D. et al. Wildland fires worsened population exposure to PM2.5 pollution in the contiguous united states. Environ. Sci. Tech. 57, 19990–19998 (2023).

    Article  Google Scholar 

  45. NASA Earthdata MODIS Collection 6 Hotspot/Active Fire Detections MCD14ML. NASA FIRMS https://firms.modaps.eosdis.nasa.gov/download/ (2019).

  46. Thornton, M. M. et al. Daymet: daily surface weather data on a 1-km grid for North America, version 4 R1, ORNL Distributed Active Archive Center, https://doi.org/10.3334/ORNLDAAC/2129 (2022).

  47. Lawrence, M. G. The relationship between relative humidity and the dewpoint temperature in moist air: a simple conversion and applications. Bull. Am. Meteorol. Soc. 86, 225–234 (2005).

    Article  Google Scholar 

Download references

Acknowledgments

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.

Author information

Authors and Affiliations

  1. Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Qingyang Zhu, Wenhao Wang, Haisu Zhang, Binyu Yang, Kyle Steenland, Noah Scovronick, Stefanie Ebelt & Yang Liu

  2. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Danlu Zhang, Rohan Richard D’Souza & Howard H. Chang

Authors
  1. Qingyang Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danlu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenhao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rohan Richard D’Souza
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haisu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Binyu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kyle Steenland
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Noah Scovronick
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Stefanie Ebelt
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Howard H. Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Yang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

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.

Corresponding author

Correspondence to Yang Liu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

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

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5 and Table 1.

Reporting Summary

Supplementary Data 1

Source data for Supplementary Fig. 1.

Supplementary Data 2

Source data for Supplementary Fig. 2.

Supplementary Data 3

Source data for Supplementary Fig. 3.

Supplementary Data 4

Source data for Supplementary Fig. 4.

Supplementary Data 5

Source data for Supplementary Fig. 5.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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). https://doi.org/10.1038/s44220-024-00210-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s44220-024-00210-8

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing