DST-Mahamana Centre of Excellence in Climate Change Research, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India; Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India.
Sci Total Environ. 2019 May 15;665:453-464. doi: 10.1016/j.scitotenv.2019.02.074. Epub 2019 Feb 7.
Climate extremes are often associated with increased human mortality and such association varies considerably with space and time. We therefore, aimed to systematically investigate the effects of temperature extremes, daily means and diurnal temperature variations (DTV) on mortality in the city of Varanasi, India during 2009-2016. Time series data on daily mortality, air quality (SO, NO, O and PM) and weather variables were obtained from the routinely collected secondary sources. A semiparametric quasi-Poisson regression model estimated the effects of temperature extremes on daily all-cause mortality adjusting nonlinear confounding effects of time trend, relative humidity and air pollution; stratified by seasons. An effect modification by age, gender and place of death as semi-economic indicator were also explored. Daily mean temperature was strongly associated with excess mortality, both during summer (5.61% with 95% CI: 4.69-6.53% per unit increase in mean temperature) and winter (1.53% with 95% CI: 0.88-2.18% per unit decrease in mean temperature). Daily mortality was found to be increased by 12.02% (with 95% CI: 4.21-19.84%) due to heat wave. The DTV has exhibited downward trend over the years and showed a negative association with all-cause mortality. Significant association of mortality and different metric of temperature extreme along with decreasing trend in DTV clearly indicate the potential impact of climate change on human health in the city of Varanasi. The finding may well be useful to prioritize the government policies to curb the factors that causes the climate change and for developing early warning system.
气候极端事件通常与人类死亡率的增加有关，这种关联在空间和时间上有很大的差异。因此，我们旨在系统地研究温度极端、日均值和日较差（DTV）对印度瓦拉纳西市 2009-2016 年期间死亡率的影响。从常规收集的二手资料中获取了每日死亡率、空气质量（SO、NO、O 和 PM）和气象变量的时间序列数据。半参数拟泊松回归模型估计了温度极端对每日全因死亡率的影响，调整了时间趋势、相对湿度和空气污染的非线性混杂效应；按季节分层。还探讨了年龄、性别和死亡地点（作为半经济指标）的效应修饰作用。日平均温度与超额死亡率密切相关，夏季（每单位平均温度升高 5.61%，95%置信区间：4.69-6.53%）和冬季（每单位平均温度降低 1.53%，95%置信区间：0.88-2.18%）均如此。由于热浪，每日死亡率增加了 12.02%（95%置信区间：4.21-19.84%）。多年来，DTV 呈下降趋势，与全因死亡率呈负相关。死亡率与不同的温度极端指标的显著关联以及 DTV 的下降趋势清楚地表明了气候变化对瓦拉纳西市人类健康的潜在影响。这一发现对于优先考虑政府政策以遏制导致气候变化的因素以及开发早期预警系统可能非常有用。
