IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i16p10108-d889184.html
   My bibliography  Save this article

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions

Author

Listed:
  • Jagadeesh Puvvula

    (Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA)

  • Azar M. Abadi

    (Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA)

  • Kathryn C. Conlon

    (Department of Public Health Sciences, University of California Davis, One Shields Ave, Davis, CA 95616, USA)

  • Jared J. Rennie

    (National Centers for Environmental Information, Asheville, NC 28801, USA)

  • Hunter Jones

    (Medical Sciences Interdepartmental Area, Office of Graduate Studies, University of Nebraska Medical Center, Omaha, NE 68198, USA)

  • Jesse E. Bell

    (Department of Environmental, Agricultural and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA
    School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
    Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE 68583, USA)

Abstract

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011–2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Suggested Citation

  • Jagadeesh Puvvula & Azar M. Abadi & Kathryn C. Conlon & Jared J. Rennie & Hunter Jones & Jesse E. Bell, 2022. "Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions," IJERPH, MDPI, vol. 19(16), pages 1-13, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10108-:d:889184
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/16/10108/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/16/10108/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hajat, S. & Sheridan, S.C. & Allen, M.J. & Pascal, M. & Laaidi, K. & Yagouti, A. & Bickis, U. & Tobias, A. & Bourque, D. & Armstrong, B.G. & Kosatsky, T., 2010. "Heat-health warning systems: A comparison of the predictive capacity of different approaches to identifying dangerously hot days," American Journal of Public Health, American Public Health Association, vol. 100(6), pages 1137-1144.
    2. Sabrina K. Beckmann & Michael Hiete, 2020. "Predictors Associated with Health-Related Heat Risk Perception of Urban Citizens in Germany," IJERPH, MDPI, vol. 17(3), pages 1-11, January.
    3. Guirguis, Kristen & Basu, Rupa & Al‐Delaimy, Wael K & Benmarhnia, Tarik & Clemesha, Rachel ES & Corcos, Isabel & Guzman‐Morales, Janin & Hailey, Brittany & Small, Ivory & Tardy, Alexander & Vashishtha, 2018. "Heat, Disparities, and Health Outcomes in San Diego County's Diverse Climate Zones," University of California at San Diego, Economics Working Paper Series qt7hd4618z, Department of Economics, UC San Diego.
    4. Tiffany Smith & Benjamin Zaitchik & Julia Gohlke, 2013. "Heat waves in the United States: definitions, patterns and trends," Climatic Change, Springer, vol. 118(3), pages 811-825, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ghasem Toloo & Gerard FitzGerald & Peter Aitken & Kenneth Verrall & Shilu Tong, 2013. "Evaluating the effectiveness of heat warning systems: systematic review of epidemiological evidence," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 58(5), pages 667-681, October.
    2. Fadly Syah Arsad & Rozita Hod & Norfazilah Ahmad & Mazni Baharom & Fredolin Tangang, 2022. "The Malay-Version Knowledge, Risk Perception, Attitude and Practice Questionnaire on Heatwaves: Development and Construct Validation," IJERPH, MDPI, vol. 19(4), pages 1-11, February.
    3. Frank A. La Sorte & Alison Johnston & Toby R. Ault, 2021. "Global trends in the frequency and duration of temperature extremes," Climatic Change, Springer, vol. 166(1), pages 1-14, May.
    4. Erika Austhof & Heidi E. Brown, 2022. "Global Warming’s Six MTurks: A Secondary Analysis of a US-Based Online Crowdsourcing Market," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    5. Alisa L. Hass & Kelsey N. Ellis & Lisa Reyes Mason & Jon M. Hathaway & David A. Howe, 2016. "Heat and Humidity in the City: Neighborhood Heat Index Variability in a Mid-Sized City in the Southeastern United States," IJERPH, MDPI, vol. 13(1), pages 1-19, January.
    6. Yun Jian & Connor Y. H. Wu & Julia M. Gohlke, 2017. "Effect Modification by Environmental Quality on the Association between Heatwaves and Mortality in Alabama, United States," IJERPH, MDPI, vol. 14(10), pages 1-11, September.
    7. Hung Chak Ho & Ka Ming Wai & Minhao He & Ta-Chien Chan & Chengbin Deng & Man Sing Wong, 2020. "Mortality risk of a future heat event across a subtropical city: implications for community planning and health policy," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 623-637, August.
    8. Sinha, Paramita & Coville, Robert C. & Hirabayashi, Satoshi & Lim, Brian & Endreny, Theodore A. & Nowak, David J., 2021. "Modeling lives saved from extreme heat by urban tree cover✰," Ecological Modelling, Elsevier, vol. 449(C).
    9. Steffen Merte, 2017. "Estimating heat wave-related mortality in Europe using singular spectrum analysis," Climatic Change, Springer, vol. 142(3), pages 321-330, June.
    10. Osvaldo Fonseca-Rodríguez & Erling Häggström Lundevaller & Scott C. Sheridan & Barbara Schumann, 2019. "Association between Weather Types based on the Spatial Synoptic Classification and All-Cause Mortality in Sweden, 1991–2014," IJERPH, MDPI, vol. 16(10), pages 1-12, May.
    11. Lin Zhou & Zheng Xin & Li Bai & Fangjun Wan & Yongming Wang & Shaowei Sang & Shouqin Liu & Ji Zhang & Qiyong Liu, 2014. "Perceptions of Heat Risk to Health: A Qualitative Study of Professional Bus Drivers and Their Managers in Jinan, China," IJERPH, MDPI, vol. 11(2), pages 1-16, January.
    12. Michael Sanderson & Katherine Arbuthnott & Sari Kovats & Shakoor Hajat & Pete Falloon, 2017. "The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-34, July.
    13. Emily J. Tetzlaff & Farah Mourad & Nicholas Goulet & Melissa Gorman & Rachel Siblock & Sean A. Kidd & Mariya Bezgrebelna & Glen P. Kenny, 2024. "“ Death Is a Possibility for Those without Shelter ”: A Thematic Analysis of News Coverage on Homelessness and the 2021 Heat Dome in Canada," IJERPH, MDPI, vol. 21(4), pages 1-15, March.
    14. Mengmeng Li & Shaohua Gu & Peng Bi & Jun Yang & Qiyong Liu, 2015. "Heat Waves and Morbidity: Current Knowledge and Further Direction-A Comprehensive Literature Review," IJERPH, MDPI, vol. 12(5), pages 1-28, May.
    15. Jiaxing Xin & Jun Yang & Yipeng Jiang & Zhipeng Shi & Cui Jin & Xiangming Xiao & Jianhong (Cecilia) Xia & Ruxin Yang, 2023. "Variations of Urban Thermal Risk with Local Climate Zones," IJERPH, MDPI, vol. 20(4), pages 1-14, February.
    16. Kun Hing Yong & Yen Nee Teo & Mohsen Azadbakht & Hai Phung & Cordia Chu, 2023. "The Scorching Truth: Investigating the Impact of Heatwaves on Selangor’s Elderly Hospitalisations," IJERPH, MDPI, vol. 20(10), pages 1-13, May.
    17. Gulcan Cil & Trudy Ann Cameron, 2017. "Potential Climate Change Health Risks from Increases in Heat Waves: Abnormal Birth Outcomes and Adverse Maternal Health Conditions," Risk Analysis, John Wiley & Sons, vol. 37(11), pages 2066-2079, November.
    18. Francesca Cecinati & Tom Matthews & Sukumar Natarajan & Nick McCullen & David Coley, 2019. "Mining Social Media to Identify Heat Waves," IJERPH, MDPI, vol. 16(5), pages 1-19, March.
    19. Yanxu Liu & Shuangshuang Li & Yanglin Wang & Tian Zhang & Jian Peng & Tianyi Li, 2015. "Identification of multiple climatic extremes in metropolis: a comparison of Guangzhou and Shenzhen, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(2), pages 939-953, November.
    20. Larsson, Karl, 2023. "Parametric heat wave insurance," Journal of Commodity Markets, Elsevier, vol. 31(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10108-:d:889184. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.