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Original research
Joint effects of heat-humidity compound events on drowning mortality in Southern China
  1. Zhiying Jiang1,
  2. Ziqiang Lin1,
  3. Zhixing Li2,3,
  4. Min Yu4,
  5. Guanhao He1,
  6. Jianxiong Hu1,
  7. Ruilin Meng3,
  8. Zhulin Hou5,
  9. Sui Zhu1,
  10. Chunliang Zhou6,
  11. Yize Xiao7,
  12. Biao Huang5,
  13. Xiaojun Xu3,
  14. Donghui Jin6,
  15. Mingfang Qin7,
  16. Yiqing Xu6,
  17. Tao Liu1,
  18. Wenjun Ma1
  1. 1Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China
  2. 2Department of Public Health, Jinan University, Guangzhou, China
  3. 3Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
  4. 4Division of NCD Control, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
  5. 5Jilin Provincial Center for Disease Control and Prevention, Changchun, China
  6. 6Hunan Provincial Center for Disease Control and Prevention, Changsha, China
  7. 7Yunnan Provincial Center for Disease Control and Prevention, Kunming, China
  1. Correspondence to Dr Wenjun Ma, Department of Public Health and Preventive Medicine, Jinan University, Guangzhou, China; mawj{at}gdiph.org.cn

Abstract

Background Several previous studies have examined the association of ambient temperature with drowning. However, no study has investigated the effects of heat-humidity compound events on drowning mortality.

Methods The drowning mortality data and meteorological data during the five hottest months (May to September) were collected from 46 cities in Southern China (2013–2018 in Guangdong, Hunan and Zhejiang provinces). Distributed lag non-linear model was first conducted to examine the association between heat-humidity compound events and drowning mortality at city level. Then, meta-analysis was employed to pool the city-specific exposure-response associations. Finally, we analysed the additive interaction of heat and humidity on drowning mortality.

Results Compared with wet-non-hot days, dry-hot days had greater effects (excess rate (ER)=32.34%, 95% CI: 24.64 to 40.50) on drowning mortality than wet-hot days (ER=14.38%, 95%CI: 6.80 to 22.50). During dry-hot days, males (ER=42.40%, 95% CI: 31.92 to 53.72), adolescents aged 0–14 years (ER=45.00%, 95% CI: 21.98 to 72.35) and urban city (ER=36.91%, 95% CI: 23.87 to 51.32) showed higher drowning mortality risk than their counterparts. For wet-hot days, males, adolescents and urban city had higher ERs than their counterparts. Attributable fraction (AF) of drowning attributed to dry-hot days was 23.83% (95% CI: 21.67 to 26.99) which was significantly higher than that for wet-hot days (11.32%, 95% CI: 9.64 to 13.48%). We also observed that high temperature and low humidity had an additive interaction on drowning mortality.

Conclusion We found that dry-hot days had greater drowning mortality risk and burden than wet-hot days, and high temperature and low humidity might have synergy on drowning mortality.

  • drowning
  • mortality
  • public health
  • cross sectional study

Data availability statement

Data are available upon reasonable request. The data and code that support the findings of this study are available on reasonable request from the corresponding author WM. The data are not publicly available because the datasets are the intellectual and labour property of all institutions involved in this study, which cannot be accessed by the public without the permission of all the involved institutions.

https://doi.org/10.1136/ip-2023-045036

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    Data availability statement

    Data are available upon reasonable request. The data and code that support the findings of this study are available on reasonable request from the corresponding author WM. The data are not publicly available because the datasets are the intellectual and labour property of all institutions involved in this study, which cannot be accessed by the public without the permission of all the involved institutions.

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    Footnotes

    • ZJ, ZL and ZL contributed equally.

    • Contributors ZJ: data analysis, manuscript writing and revision. ZL: data analysis, manuscript writing and revision. ZL: data analysis and draft writing. MY: data collection and project administration. GH: data analysis and manuscript revision. JH: data analysis. RM: data collection and project administration. ZH: data collection and project administration. SZ: data analysis and manuscript revision. CZ: data collection and project administration. YX: project administration. BH: data collection and project administration. XX: data collection and analysis. DJ: data collection. MQ: data collection. YX: data collection. TL: data analysis and manuscript revision. WM: guarantor and accepts full responsibility for the work and the conduct of the study, conceptualisation, data analysis, manuscript writing and revision.

    • Funding This work was supported by the National Key Research and Development Program of China (2018YFA0606200).

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.