A new method to estimate the temperature-CVD mortality relationship
- 122 Downloads
Few detailed, individual-focused studies have researched the added effect of temperature on cardiovascular disease (CVD), particularly in China. Moreover, no prior studies have explored the exposure-response relationship among all populations and different sub-sociodemographic groups. A distributed lag nonlinear model (DLNM) was applied to evaluate the adverse health effects of temperature on CVD mortality for all populations and different sub-sociodemographic groups (by age, sex, educational level, living arrangement, and occupation) in Beijing. Based on the exposure-response relationships, firstly, we proposed a new model (COCKTAIL, Code Of Climate Key To An Ill) for revealing the split-and-merge relationships of the temperature-CVD mortality curve. This method could be used to apply the CVD deaths in a studied area to forecast the exposure-response relationships in the same area in the future. Secondly, this is the most detailed study to analyze the relationship between temperature and CVD mortality for different subgroups among the existing researches for developed and developing countries. We found that the cold temperature (at − 14 °C) was the risk factor for people with low socioeconomic status, especially for single people (including unmarried, divorced, and widowed), for indoor workers, and for people with low education, compared with the minimum mortality temperature, with a cumulative increase of 3.9 (80%CI, 2.9–5.4), 3.8 (80%CI, 2.8–5.1), and 4.5 (80%CI, 3.1–6.3) times respectively. Meanwhile, the hot temperature (at 35 °C) was the risk factor for CVD death, with a cumulative increase of 2.6 (80%CI, 2.0–3.4) for females, and 3.1 (80%CI, 2.4–4.2) for single people. The varying CVD vulnerability in terms of CVD mortality among various groups may assist governments in preparing health resources and taking measures to prevent or reduce temperature-related deaths.
KeywordsTemperature Cardiovascular disease COCKTAIL
This work was supported by the National Natural Science Foundation of China (grant nos. 41531179 and 41421001) and the Ministry of Science and Technology of China (grant no. 2014FY121100). The funders played no role in determining the study design, data collection, or analysis methods employed; in our decision to publish; or in preparing the manuscript.
Compliance with ethical standards
The authors declare that they have no conflict of interest.
- Becker JA, Stewart LK (2011) Heat–related illness. Am Fam Physician 83:1325–1330Google Scholar
- China Meteorological Data Sharing Service System (CMDS) (2017) Available: http://cdc.nmic.cn/home.do [Accessed on 5 August 2014]
- D’Ippoliti D, Michelozzi P, Marino C, de’Donato F, Menne B, Katsouyanni K et al (2010) The impact of heat waves on mortality in 9 European cities: results from the Euro HEAT project. Environ Health 9:358–366Google Scholar
- Feng X, Li ZL, Gao Y (2005) Effects of income, marriage and family on life satisfaction of elderly people. China Public Health 21:142–147Google Scholar
- Stafoggia M, Forastiere F, Agostini D, Biggeri A, Bisanti L, Cadum E, Caranci N, de??Donato F, de Lisio S, de Maria M, Michelozzi P, Miglio R, Pandolfi P, Picciotto S, Rognoni M, Russo A, Scarnato C, Perucci CA (2006) Vulnerability to heat–related mortality: a multicity, population–based, case–crossover analysis. Epidemiology 17:315–323Google Scholar
- Tord K (2009) Climate change, direct heat exposure, health and well–being in low and middle–income countries. Glob Health Action 2:920–928Google Scholar
- Tsangari H, Paschalidou A, Vardoulakis S, Heaviside C, Konsoula Z, Christou S et al (2015) Human mortality in Cyprus: the role of temperature and particulate air pollution. Reg Environ Chang. https://doi.org/10.1007/s10113-015-0793-2
- Wang MZ, Zheng S, He SL, Li B, Teng HJ, Wang SG et al (2013) The association between diurnal temperature range and emergency room admissions for cardiovascular, respiratory, digestive and genitourinary disease among the elderly: a time series study. Sci. Total Environ 456–457:370–375CrossRefGoogle Scholar
- Yang J, Ou CQ, Guo YM, Li L, Guo C, Chen PY (2015b) The burden of ambient temperature on years of life lost in Guangzhou, China. Sci Rep 5(12250):1–9Google Scholar