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:

Large-scale agricultural burning and cardiorespiratory emergency department visits in the U.S. state of Kansas

Journal of Exposure Science & Environmental Epidemiology volume 33, pages 663–669 (2023)Cite this article

Abstract

Background

Prescribed agricultural burning is a common land management practice, but little is known about the health effects from the resulting smoke exposure.

Objective

To examine the association between smoke from prescribed burning and cardiorespiratory outcomes in the U.S. state of Kansas.

Methods

We analyzed a zip code-level, daily time series of primary cardiorespiratory emergency department (ED) visits for February–May (months when prescribed burning is common in Kansas) in the years 2009–2011 (n = 109,220). Given limited monitoring data, we formulated a measure of smoke exposure using non-traditional datasets, including fire radiative power and locational attributes from remote sensing data sources. We then assigned a population-weighted potential smoke impact factor (PSIF) to each zip code, based on fire intensity, smoke transport, and fire proximity. We used Poisson generalized linear models to estimate the association between PSIF on the same day and in the past 3 days and asthma, respiratory including asthma, and cardiovascular ED visits.

Results

During the study period, prescribed burning took place on approximately 8 million acres in Kansas. Same-day PSIF was associated with a 7% increase in the rate of asthma ED visits when adjusting for month, year, zip code, meteorology, day of week, holidays, and correlation within zip codes (rate ratio [RR]: 1.07; 95% confidence interval [CI]: 1.01, 1.13). Same-day PSIF was not associated with a combined outcome of respiratory ED visits (RR [95% CI]: 0.99 [0.97, 1.02]), or cardiovascular ED visits (RR [95% CI]: 1.01 [0.98, 1.04]). There was no consistent association between PSIF during the past 3 days and any of the outcomes.

Significance

These results suggest an association between smoke exposure and asthma ED visits on the same day. Elucidating these associations will help guide public health programs that address population-level exposure to smoke from prescribed burning.

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: Quintiles of Potential Smoke Impact Factor (PSIF) levels, Kansas, February–May 2010.
Fig. 2: Primary respiratory, cardiovascular, and asthma ED visits by month, Kansas 2009–2011.

Similar content being viewed by others

Data availability

The computing code can be obtained by contacting the corresponding author. The data are not available because they include medical information that cannot be released.

References

  1. Fann N, Alman B, Broome RA, Morgan GG, Johnston FH, Pouliot G, et al. The health impacts and economic value of wildland fire episodes in the U.S.: 2008-2012. Sci Total Environ. 2018;610-611:802–9.

    Article  CAS  PubMed  Google Scholar 

  2. Cascio WE. Wildland fire smoke and human health. Sci Total Environ. 2018;624:586–95.

    Article  CAS  PubMed  Google Scholar 

  3. Centers for Disease Control and Prevention. Protect Yourself from Wildfire Smoke. 2021. https://www.cdc.gov/nceh/features/wildfires/. Accessed March 15, 2021.

  4. Ohlenbusch PD, Hartnet DC Prescribed burning as a management practice. Kansas State University, 2000.

  5. U.S. Environmental Protection Agency. Agriculture and Air Quality: Prescribed Burning. 2021. https://www.epa.gov/agriculture/agriculture-and-air-quality#prescribedburning. Accessed June 28, 2021.

  6. World Health Organization. Air quality and health. 2022. https://www.who.int/teams/environment-climate-change-and-health/air-quality-and-health/health-impacts. Accessed December 8, 2022.

  7. Haikerwal A, Reisen F, Sim MR, Abramson MJ, Meyer CP, Johnston FH, et al. Impact of smoke from prescribed burning: Is it a public health concern? J Air Waste Manag Assoc. 2015;65:592–8.

    Article  CAS  PubMed  Google Scholar 

  8. Tian D, Wang Y, Bergin M, Hu Y, Liu Y, Russell AG. Air quality impacts from prescribed forest fires under different management practices. Environ Sci Technol. 2008;42:2767–72.

    Article  CAS  PubMed  Google Scholar 

  9. Hu Y, Odman MT, Chang ME, Jackson W, Lee S, Edgerton ES, et al. Simulation of air quality impacts from prescribed fires on an urban area. Environ Sci Technol. 2008;42:3676–82.

    Article  CAS  PubMed  Google Scholar 

  10. Whitehill AR, George I, Long R, Baker KR, Landis M. Volatile organic compound emissions from prescribed burning in Tallgrass Prairie ecosystems. Atmos. 2019;10:1–464.

    Google Scholar 

  11. Robinson MS, Chavez J, Velazquez S, Jayanty RK. Chemical speciation of PM2.5 collected during prescribed fires of the Coconino National Forest near Flagstaff, Arizona. J Air Waste Manag Assoc. 2004;54:1112–23.

    Article  CAS  PubMed  Google Scholar 

  12. Jaffe DA, O’Neill SM, Larkin NK, Holder AL, Peterson DL, Halofsky JE, et al. Wildfire and prescribed burning impacts on air quality in the United States. J Air Waste Manag Assoc. 2020;70:583–615.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Huang R, Hu Y, Russell AG, Mulholland JA, Odman MT The impacts of prescribed fire on PM2.5 air quality and human health: application to asthma-related emergency room visits in Georgia, USA. Int J Environ Res Public Health 2019;16:1–14.

  14. Afrin S, Garcia-Menendez F. Potential impacts of prescribed fire smoke on public health and socially vulnerable populations in a Southeastern U.S. state. Sci Total Environ. 2021;794:148712.

    Article  CAS  PubMed  Google Scholar 

  15. Ravi V, Vaughan JK, Wolcott MP, Lamb BK. Impacts of prescribed fires and benefits from their reduction for air quality, health and visibility in the Pacific Northwest of the United States. J Air Waste Manag Assoc 2018; https://doi.org/10.1080/10962247.2018.1526721.

  16. Mohler RL, Goodin DG. Mapping burned areas in the Flint Hills of Kansas and Oklahoma, 2000—2010. Great Plains. Research. 2012;22:15–25.

    Google Scholar 

  17. Anderson KL. Utilization of grasslands in the flint hills of Kansas. J Range Manag. 1953;6:86–93.

    Article  Google Scholar 

  18. Kansas Department of Health and Environment. State of Kansas Flint Hills Smoke Management Plan. 2010. https://www.kdheks.gov/bar/air-monitor/flinthillsinfo/SMP_v10FINAL.pdf. Accessed June 28, 2010.

  19. Liu Z Air quality concerns of prescribed range burning in Kansas. MF3121.: Manhattan, Kansas, 2014.

  20. Liu Z, Liu Y, Maghirang R, Devlin D, Blocksome C. Estimating contributions of prescribed rangeland burning in Kansas to ambient PM2.5 through source apportionment with the Unmix receptor model. Trans ASABE. 2016;59:1267–75.

    Article  Google Scholar 

  21. U.S. Environmental Protection Agency. 2017 National Emissions Inventory (NEI) Data. 2020. https://www.epa.gov/air-emissions-inventories/2017-national-emissions-inventory-nei-data. Accessed June 17, 2020.

  22. National Aeronautics and Space Administration. Fire Information for Resource Management System (FIRMS). 2021. https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms. Accessed April 22, 2021.

  23. Li F, Zhang X, Roy DP, Kondragunta S. Estimation of biomass-burning emissions by fusing the fire radiative power retrievals from polar-orbiting and geostationary satellites across the conterminous United States. Atmos Environ. 2019;211:274–87.

    Article  CAS  Google Scholar 

  24. Mota B, Wooster MJ. A new top-down approach for directly estimating biomass burning emissions and fuel consumption rates and totals from geostationary satellite fire radiative power (FRP). Remote Sens Environ. 2018;206:45–62.

    Article  Google Scholar 

  25. Ichoku C, Ellison L. Global top-down smoke-aerosol emissions estimation using satellite fire radiative power measurements. Atmos Chem Phys. 2014;14:6643–67.

    Article  Google Scholar 

  26. Ichoku C, Giglio L, Wooster MJ, Remer LA. Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sens Environ. 2008;112:2950–62.

    Article  Google Scholar 

  27. Waller LA, Louis TA, Carlin BP. Environmental justice and statistical summaries of differences in exposure distributions. J Expo Anal Environ Epidemiol. 1999;9:56–65.

    Article  CAS  PubMed  Google Scholar 

  28. National Aeronautics and Space Administration. Land Data Assimilation System. 2022. https://ldas.gsfc.nasa.gov/. Accessed July 14, 2022.

  29. Zou B, Wilson JG, Zhan FB, Zeng Y. Air pollution exposure assessment methods utilized in epidemiological studies. J Environ Monit. 2009;11:475–90.

    Article  CAS  PubMed  Google Scholar 

  30. Li L, Losser T, Yorke C, Piltner R. Fast inverse distance weighting-based spatiotemporal interpolation: a web-based application of interpolating daily fine particulate matter PM2:5 in the contiguous U.S. using parallel programming and k-d tree. Int J Environ Res Public Health. 2014;11:9101–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Ye D, Klein M, Chang HH, Sarnat JA, Mulholland JA, Edgerton ES, et al. Estimating acute cardiorespiratory effects of ambient volatile organic compounds. Epidemiology. 2017;28:197–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Flanders WD, Strickland MJ, Klein M. A new method for partial correction of residual confounding in time-series and other observational studies. Am J Epidemiol. 2017;185:941–9.

    Article  PubMed  Google Scholar 

  33. Lipsitch M, Tchetgen Tchetgen E, Cohen T. Negative controls: a tool for detecting confounding and bias in observational studies. Epidemiology. 2010;21:383–8.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Flanders WD, Klein M, Darrow LA, Strickland MJ, Sarnat SE, Sarnat JA, et al. A method for detection of residual confounding in time-series and other observational studies. Epidemiology. 2011;22:59–67.

    Article  PubMed  PubMed Central  Google Scholar 

  35. R Core Team. R: A language and environment for statistical computing. In. Vienna, Austria: R Foundation for Statistical Computing, 2021.

  36. Kansas Department of Health and Environment. Flint Hills Wildland Fire Update. 2021 Summary. 2021. https://www.ksfire.org/new-media-archives/weeklyupdates/2021/Flint_Hills-Wildland_Fire_2021_Summary.pdf. Accessed March 15, 2021.

  37. Towne EG, Craine JM. Ecological consequences of shifting the timing of burning tallgrass prairie. PLoS One. 2014;9:e103423.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Duncan ZM, Tajchman AJ, Ramirez MP, Lemmon J, Hollenbeck WR, Blasi DA, et al. Effects of prescribed fire timing on grazing performance of yearling beef cattle, forage biomass accumulation, and plant community characteristics on native tallgrass prairie in the Kansas Flint Hills. Transl Anim Sci. 2021;5:txab077.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Pate CA, Zahran HS, Qin X, Johnson C, Hummelman E, Malilay J. Asthma Surveillance—United States, 2006-2018. MMWR Surveill Summ. 2021;70:1–32.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, et al. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation. 2022;145:e153–e639.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank Dr. Mitchel Klein for his assistance with the SAS programming for this analysis. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. This publication was supported by the Kansas Environmental Public Health Tracking Program through Cooperative Agreement Number NUE1EH001340-01 funded by the Centers for Disease Control and Prevention. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the Department of Health and Human Services.

Author information

Authors and Affiliations

  1. Asthma and Community Health Branch, Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Audrey F. Pennington, Maria C. Mirabelli, Kanta Devi Sircar & W. Dana Flanders

  2. Climate and Health Program, Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Ambarish Vaidyanathan & Arie Manangan

  3. Kansas Department of Health and Environment, Topeka, KS, USA

    Farah S. Ahmed

  4. Commissioned Officers of the United States Public Health Services, Rockville, MD, USA

    Kanta Devi Sircar & Fuyuen Yip

  5. Emergency Management, Radiation, and Chemical Branch, Division of Environmental Health Science and Practice, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Fuyuen Yip

  6. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    W. Dana Flanders

Authors
  1. Audrey F. Pennington
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ambarish Vaidyanathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Farah S. Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Arie Manangan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Maria C. Mirabelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kanta Devi Sircar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Fuyuen Yip
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. W. Dana Flanders
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

FY, FA, and KS conceived of the work. AP, AV, AM, MM, KS, and WDF contributed to study design. FA obtained the health data. AV and AM developed the exposure estimate. AP and WDF completed the analysis. AP and AV drafted the manuscript. All authors contributed to the interpretation of results and to the revision of the manuscript.

Corresponding author

Correspondence to Audrey F. Pennington.

Ethics declarations

Competing interests

The authors declare they have no competing financial interests. Dr. Flanders discloses that he owns a consulting company, Epidemiologic Research & Methods, LLC that does consulting work for clients. He knows of no conflicts with this work.

Ethical approval

This activity was reviewed by the Centers for Disease Control and Prevention (CDC) and was conducted consistent with applicable federal law and CDC (See e.g., 45 C.F.R. part 46, 21 C.F.R. part 56; 42 U.S.C. §241(d); 5 U.S.C. §552a; 44 U.S.C. §3501 et seq.).

Additional information

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pennington, A.F., Vaidyanathan, A., Ahmed, F.S. et al. Large-scale agricultural burning and cardiorespiratory emergency department visits in the U.S. state of Kansas. J Expo Sci Environ Epidemiol 33, 663–669 (2023). https://doi.org/10.1038/s41370-023-00531-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41370-023-00531-3

Keywords

Search

Advanced search

Quick links