Different Mortality Effects of Extreme Temperature Stress in Three Large City Clusters of Northern and Southern China
Lingyan Zhang , Zhao Zhang , Chenzhi Wang , Maigeng Zhou , Peng Yin
International Journal of Disaster Risk Science ›› 2017, Vol. 8 ›› Issue (4) : 445 -456.
Different Mortality Effects of Extreme Temperature Stress in Three Large City Clusters of Northern and Southern China
Extreme temperature events have affected Chinese city residents more frequently and intensively since the early 2000s, but few studies have identified the impacts of extreme temperature on mortality in different city clusters of China. This study first used a distributed lag, nonlinear model to estimate the county/district-specific effects of extreme temperature on nonaccidental and cardiovascular mortality. The authors then applied a multivariate meta-analysis to pool the estimated effects in order to derive regional temperature–mortality relationship in three large city clusters—the Beijing-Tianjin-Hebei (BTH) region, the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which represent northern and southern regions. With 0–3 days’ lag, the strongest heat-related mortality effect was observed in the BTH region (with relative risk (RR) of 1.29; 95% confidence interval (CI): 1.13–1.47), followed by the YRD (RR = 1.25; 95% CI: 1.13–1.35) and the PRD (RR = 1.14; 95% CI: 1.01–1.28) areas. With 0–21 days’ lag, the cold effect was pronounced in all city clusters, with the highest extreme cold-related mortality risk found in the PRD area (RR = 2.27; 95% CI: 1.63–3.16), followed by the YRD area (RR = 1.85; 95% CI: 1.56–2.20) and BTH region (RR = 1.33; 95% CI: 0.96–1.83). People in the southern regions tended to be more vulnerable to cold stress, but the northern population was more sensitive to heat stress. By examining the effects of extreme temperature in city clusters of different regions, our findings underline the role of adaptation towards heat and cold, which has important implications for public health policy making and practice.
China / City cluster / Extreme temperature stress / Health risk / Mortality risk
| [1] |
|
| [2] |
Akaike, H. 1973. Information theory and the extension of the maximum likelihood principle. In Proceedings of the International Symposium on Information Theory, ed. B.N. Petrov and F. Czaki, 267–281. Akademia Kiadoo, Budapest, Hungary. |
| [3] |
|
| [4] |
|
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
IPCC (Intergovernmental Panel on Climate Change). 2014. Climate change 2014: Synthesis report. Contribution of Working Groups I, II and III to the Fifth assessment report of the Intergovernmental Panel on Climate Change, ed. R.K. Pachauri and L.A. Meyer. Geneva: IPCC. |
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
National Bureau of Statistics of China. 2015. China city statistical yearbook 2015. Pages 13–19, 83–90, 98–104 (Table 2–1, Table 2–11 and Table 2–13). China Statistics Press, Beijing. |
| [34] |
NDRC (National Development and Reform Commission). 2016. City climate action planning. Beijing: NDRC. http://www.ndrc.gov.cn/gzdt/201608/W020160804337181231042.pdf. Accessed 31 Oct 2017. |
| [35] |
|
| [36] |
RDCT (R Development Core Team) R: A language and environment for statistical computing, 2016, Vienna: R Foundation for Statistical Computing |
| [37] |
|
| [38] |
Schuster, C., K. Burkart, and T. Lakes. 2014. Heat mortality in Berlin—Spatial variability at the neighborhood scale. Urban Climate 10(part 1): 134–147. |
| [39] |
|
| [40] |
|
| [41] |
|
| [42] |
World Health Organization. 2011. International statistical classification of diseases and health related problems, 10th revision, version for 2007. http://apps.who.int/classifications/apps/icd/icd10online2007/. Accessed 31 Oct 2017. |
| [43] |
|
| [44] |
|
| [45] |
|
| [46] |
|
| [47] |
Zhang, Y. 2009. An overview of the 3C-STAR project. Paper presented at the EGU General Assembly Conference, 19–24 April 2009, Vienna, Austria. |
/
| 〈 |
|
〉 |