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Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study

Journal of Exposure Science & Environmental Epidemiology volume 31, pages 187–196 (2021)Cite this article

Abstract

To assess YLL and mortality burden attributable to non-optimum ambient temperature, we collected mortality and environmental data from June 1, 2012 to December 30, 2017 in Shenzhen. We applied distributed lag nonlinear models with 21 days of lag to examine temperature–YLL and temperature–mortality associations, and calculated the attributable fractions of YLL and deaths for non-optimum temperature, including four subranges, mild cold, mild heat, extreme cold, and extreme heat. Cold and heat were distinguished by the optimum temperature, and each was separated into extreme and mild by cutoffs at 2.5th (12.2 °C) and 97.5th (30.4 °C) temperature percentile further. The optimum temperature was defined as the temperature that had minimum effect on YLL or mortality risk. The optimum temperature for non-accidental YLL was 24.5 °C, and for mortality it was 25.4 °C. Except for the population older than 65 years, the optimum temperature was generally lower in the YLL model than the mortality model. Of the total 61,576 non-accidental deaths and 1,350,835.7 YLL within the study period, 17.28% (95% empirical CI 9.42–25.14%) of YLL and 17.27% (12.70–21.34%) of mortality were attributable to non-optimum temperature. More YLL was caused by cold (10.14%, 3.94–16.36%) than by heat (7.14%, 0.47–13.88%). Mild cold (12.2–24.5 °C) was responsible for far more YLL (8.78%, 3.00–14.61%) than extreme cold (3.5–12.2 °C). As for cardiovascular deaths, only the fractions attributable to overall and cold temperature were significant, with mild cold contributing the largest fraction to YLL (16.31%, 6.85–25.82%) and mortality (16.08%, 9.77–21.22%). Most of the temperature-related YLL and mortality was attributable to mild but non-optimum weather, especially mild cold, while the YLL model implied a more prominent heat effect on premature death. Our findings can supply additional evidence from multiperspectives for health planners to define priorities and make targeted policies for mitigating the burden of adverse temperatures.

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Fig. 1: Scatterplots for daily mortality, YLL, and meteorological factors in Shenzhen, China, June 2012 to December 2017.
Fig. 2: The cumulative effects of temperature on YLL due to deaths from non-accidental causes with temperature distribution in Shenzhen.
Fig. 3: The cumulative effects of temperature on mortality due to non-accidental causes with temperature distribution.
Fig. 4: The delayed cold and hot effects of temperature on years of life lost and mortality risk by lag.

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References

  1. Ye XF, Wolff R, Yu WW, Vaneckova P, Pan XC, Tong SL. Ambient temperature and morbidity: a review of epidemiological evidence. Environ Health Perspect. 2012;120:19–28.

    Article  Google Scholar 

  2. Bunker A, Wildenhain J, Vandenbergh A, Henschke N, Rocklov J, Hajat S, et al. Effects of air temperature on climate-sensitive mortality and morbidity outcomes in the elderly: a systematic review and meta-analysis of epidemiological evidence. Ebiomedicine. 2016;6:258–68.

    Article  Google Scholar 

  3. Kovats RS, Hajat S. Heat stress and public health: a critical review. Annu Rev Publ Health. 2008;29:41.

    Article  Google Scholar 

  4. Yang ZM, Wang Q, Liu PF. Extreme temperature and mortality: evidence from China. Int J Biometeorol. 2019;63:29–50.

    Article  Google Scholar 

  5. Hajat S, Kosatky T. Heat-related mortality: a review and exploration of heterogeneity. J Epidemiol Commun H. 2010;64:753–60.

    Article  Google Scholar 

  6. Song XP, Wang SG, Hu YL, Yue M, Zhang TT, Liu Y, et al. Impact of ambient temperature on morbidity and mortality: an overview of reviews. Sci Total Environ. 2017;586:241–54.

    Article  CAS  Google Scholar 

  7. Huang CR, Barnett AG, Wang XM, Tong SL. The impact of temperature on years of life lost in Brisbane, Australia. Nat Clim Change. 2012;2:265–70.

    Article  Google Scholar 

  8. Yang J, Ou CQ, Song YF, Li L, Chen PY, Liu QY. Estimating years of life lost from cardiovascular mortality related to air pollution in Guangzhou, China. Sci Total Environ. 2016;573:1566–72.

    Article  CAS  Google Scholar 

  9. Steenland K, Armstrong B. An overview of methods for calculating the burden of disease due to specific risk factors. Epidemiology. 2006;17:512–9.

    Article  Google Scholar 

  10. Chen RJ, Yin P, Wang LJ, Liu C, Niu Y, Wang WD, et al. Association between ambient temperature and mortality risk and burden: time series study in 272 main Chinese cities. Br Med J. 2018;363:k4306.

  11. Gasparrini A, Guo YM, Hashizume M, Lavigne E, Zanobetti A, Schwartz J, et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet. 2015;386:369–75.

    Article  Google Scholar 

  12. Zhang YQ, Peng MJ, Wang L, Yu CH. Association of diurnal temperature range with daily mortality in England and Wales: a nationwide time-series study. Sci Total Environ. 2018;619:291–300.

    Article  Google Scholar 

  13. Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models. Stat Med. 2010;29:2224–34.

    Article  CAS  Google Scholar 

  14. Guo YM, Li SS, Tian ZX, Pan XC, Zhang JL, Williams G. The burden of air pollution on years of life lost in Beijing, China, 2004-08: retrospective regression analysis of daily deaths. Br Med J. 2013;347:f7139.

  15. Yang J, Ou CQ, Guo YM, Li L, Guo C, Chen PY, et al. The burden of ambient temperature on years of life lost in Guangzhou, China. Sci Rep. 2015;5:12250.

  16. Gasparrini A, Leone M. Attributable risk from distributed lag models. BMC Med Res Methodol. 2014;14:55.

  17. Ma WJ, Chen RJ, Kan HD. Temperature-related mortality in 17 large Chinese cities: how heat and cold affect mortality in China. Environ Res. 2014;134:127–33.

    Article  CAS  Google Scholar 

  18. Wu W, Xiao YZ, Li GC, Zeng WL, Lin HL, Rutherford S, et al. Temperature-mortality relationship in four subtropical Chinese cities: a time-series study using a distributed lag non-linear model. Sci Total Environ. 2013;449:355–62.

    Article  CAS  Google Scholar 

  19. Vicedo-Cabrera AM, Sera F, Guo Y, Chung Y, Arbuthnott K, Tong S, et al. A multi-country analysis on potential adaptive mechanisms to cold and heat in a changing climate. Environ Int. 2018;111:239–46.

    Article  Google Scholar 

  20. Li GX, Huang J, Xu GZ, Pan XC, Qian XJ, Xu JY, et al. Temporal variation in associations between temperature and years of life lost in a southern China city with typical subtropical climate. Sci Rep. 2017;7:4650.

  21. Yang J, Ou CQ, Ding Y, Zhou YX, Chen PY. Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou. Environ Health. 2012;11:63.

  22. Zhang YQ, Yu CH, Peng MJ, Zhang L. The burden of ambient temperature on years of life lost: a multi-community analysis in Hubei, China. Sci Total Environ. 2018;621:1491–8.

    Article  CAS  Google Scholar 

  23. Zhang J, Li TT, Tan JG, Huang CR, Kan HD. Impact of temperature on mortality in three major Chinese cities. Biomed Environ Sci. 2014;27:485–94.

    PubMed  Google Scholar 

  24. Kouis P, Kakkoura M, Ziogas K, Paschalidou AK, Papatheodorou SI. The effect of ambient air temperature on cardiovascular and respiratory mortality in Thessaloniki, Greece. Sci Total Environ. 2019;647:1351–8.

    Article  CAS  Google Scholar 

  25. Yang J, Yin P, Zhou MG, Ou CQ, Guo YM, Gasparrini A, et al. Cardiovascular mortality risk attributable to ambient temperature in China. Heart. 2015;101:1966–72.

    Article  Google Scholar 

  26. Yang J, Yin P, Zhou MG, Ou CQ, Li MM, Li J, et al. The burden of stroke mortality attributable to cold and hot ambient temperatures: epidemiological evidence from China. Environ Int. 2016;92–93:232–8.

    Article  Google Scholar 

  27. Lee W, Choi HM, Kim D, Honda Y, Guo YLL, Kim H. Temporal changes in mortality attributed to heat extremes for 57 cities in Northeast Asia. Sci Total Environ. 2018;616:703–9.

    Article  Google Scholar 

  28. Guo YM, Barnett AG, Zhang YS, Tong SL, Yu WW, Pan XC. The short-term effect of air pollution on cardiovascular mortality in Tianjin, China: comparison of time series and case-crossover analyses. Sci Total Environ. 2010;409:300–6.

    Article  CAS  Google Scholar 

  29. Zhu JY, Zhang XH, Zhang X, Dong M, Wu JM, Dong YQ, et al. The burden of ambient air pollution on years of life lost in Wuxi, China, 2012-2015: a time-series study using a distributed lag non-linear model. Environ Pollut. 2017;224:689–97.

    Article  CAS  Google Scholar 

  30. Gardner JW, Sanborn JS. Years of potential life lost (YPLL)-what does it measure? Epidemiol. 1990;1:322–9.

    Article  CAS  Google Scholar 

  31. Analitis A, Katsouyanni K, Biggeri A, Baccini M, Forsberg B, Bisanti L, et al. Effects of cold weather on mortality: results from 15 European cities within the PHEWE project. Am J Epidemiol. 2008;168:1397–408.

    Article  CAS  Google Scholar 

  32. Baccini M, Biggeri A, Accetta G, Kosatsky T, Katsouyanni K, Analitis A, et al. Heat effects on mortality in 15 European cities. Epidemiol. 2008;19:711–9.

    Article  Google Scholar 

  33. Zhou MG, Wang HD, Zhu J, Chen WQ, Wang LH, Liu SW, et al. Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. Lancet. 2016;387:251–72.

    Article  Google Scholar 

  34. Yang J, Zhou MG, Ou CQ, Yin P, Li MM, Tong SL, et al. Seasonal variations of temperature-related mortality burden from cardiovascular disease and myocardial infarction in China. Environ Pollut. 2017;224:400–6.

    Article  CAS  Google Scholar 

  35. Yu WW, Vaneckova P, Mengersen K, Pan XC, Tong SL. Is the association between temperature and mortality modified by age, gender and socio-economic status? Sci Total Environ. 2010;408:3513–8.

    Article  CAS  Google Scholar 

  36. Zanobetti A, O’Neill MS, Gronlund CJ, Schwartz JD. Susceptibility to mortality in weather extremes effect modification by personal and small-area characteristics. Epidemiol. 2013;24:809–19.

    Article  Google Scholar 

  37. Le Y, Ren J, Shen J, Li T, Zhang CF. The changing gender differences in life expectancy in Chinese cities 2005-2010. PLoS ONE 2015;10:e0123320.

  38. Medalia C, Chang VW. Gender equality, development, and cross-national sex gaps in life expectancy. Int J Comp Sociol. 2011;52:371–89.

    Article  Google Scholar 

  39. Seifarth JE, McGowan CL, Milne KJ. Sex and life expectancy. Gend Med. 2012;9:390–401.

    Article  Google Scholar 

  40. Li YH, Cheng YB, Cui GQ, Peng CQ, Xu Y, Wang YL, et al. Association between high temperature and mortality in metropolitan areas of four cities in various climatic zones in China: a time-series study. Environ Health. 2014;13:65.

  41. Burse RL. Sex differences in human thermoregulatory response to heat and cold stress. Hum Factors. 1979;21:687–99.

    Article  CAS  Google Scholar 

  42. Medina-Ramon M, Schwartz J. Temperature, temperature extremes, and mortality: a study of acclimatisation and effect modification in 50 US cities. Occup Environ Med. 2007;64:827–33.

    Article  CAS  Google Scholar 

  43. Bhaskaran K, Gasparrini A, Hajat S, Smeeth L, Armstrong B. Time series regression studies in environmental epidemiology. Int J Epidemiol. 2013;42:1187–95.

    Article  Google Scholar 

Download references

Acknowledgements

We thank all staff from the Center for Disease Control and Prevention of Shenzhen who have made a great contribution to the data collection, supplements, auditing, and database management. This study was supported by the National Natural Science Foundation of China (No. 81573262). The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all data in the study, and had the final responsibility for the decision to submit for publication.

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  1. These authors contributed equally: Hongyan Li, Yao Yao

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, Hubei, China

    Hongyan Li, Yanran Duan, Siyu Yan, Xuehan Liu, Ping Yin & Hongwei Jiang

  2. Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, 430030, Hubei, China

    Yao Yao

  3. Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen, 518055, Guangdong, China

    Yao Yao, Yi Liao, Zhiguang Zhao, Yingbin Fu & Jinquan Cheng

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Li, H., Yao, Y., Duan, Y. et al. Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study. J Expo Sci Environ Epidemiol 31, 187–196 (2021). https://doi.org/10.1038/s41370-020-0202-x

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