scholarly journals Association between ambient temperature and mortality risk and burden: time series study in 272 main Chinese cities

BMJ ◽  
2018 ◽  
pp. k4306 ◽  
Author(s):  
Renjie Chen ◽  
Peng Yin ◽  
Lijun Wang ◽  
Cong Liu ◽  
Yue Niu ◽  
...  

Abstract Objectives To examine the association between temperature and cause specific mortality, and to quantify the corresponding disease burden attributable to non-optimum ambient temperatures. Design Time series analysis. Setting 272 main cities in China. Population Non-accidental deaths in 272 cities covered by the Disease Surveillance Point System of China, from January 2013 to December 2015. Main outcomes and measures Daily numbers of deaths from all non-accidental causes and main cardiorespiratory diseases. Potential effect modifiers included demographic, climatic, geographical, and socioeconomic characteristics. The analysis used distributed lag non-linear models to estimate city specific associations, and multivariate meta-regression analysis to obtain the effect estimates at national and regional levels. Results 1 826 186 non-accidental deaths from total causes were recorded in the study period. Temperature and mortality consistently showed inversely J shaped associations. At the national average level, relative to the minimum mortality temperature (22.8°C, 79.1st centile), the mortality risk of extreme cold temperature (at −1.4°C, the 2.5th centile) lasted for more than 14 days, whereas the risk of extreme hot temperature (at 29.0°C, the 97.5th centile) appeared immediately and lasted for two to three days. 14.33% of non-accidental total mortality was attributable to non-optimum temperatures, of which moderate cold (ranging from −1.4 to 22.8°C), moderate heat (22.8 to 29.0°C), extreme cold (−6.4 to −1.4°C), and extreme heat (29.0 to 31.6°C) temperatures corresponded to attributable fractions of 10.49%, 2.08%, 1.14%, and 0.63%, respectively. The attributable fractions were 17.48% for overall cardiovascular disease, 18.76% for coronary heart disease, 16.11% for overall stroke, 14.09% for ischaemic stroke, 18.10% for haemorrhagic stroke, 10.57% for overall respiratory disease, and 12.57% for chronic obstructive pulmonary diseases. The mortality risk and burden were more prominent in the temperate monsoon and subtropical monsoon climatic zones, in specific subgroups (female sex, age ≥75 years, and ≤9 years spent in education), and in cities characterised by higher urbanisations rates and shorter durations of central heating. Conclusions This nationwide study provides a comprehensive picture of the non-linear associations between ambient temperature and mortality from all natural causes and main cardiorespiratory diseases, as well as the corresponding disease burden that is mainly attributable to moderate cold temperatures in China. The findings on vulnerability characteristics can help improve clinical and public health practices to reduce disease burden associated with current and future abnormal weather.

2021 ◽  
Author(s):  
Yanbing Li ◽  
Jingtao Wu ◽  
Jiayuan Hao ◽  
Qiujun Dou ◽  
Hao Xiang ◽  
...  

Abstract Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1st, 2014 to December 31st, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4 days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.


Author(s):  
Ray Huffaker ◽  
Marco Bittelli ◽  
Rodolfo Rosa

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjects of science, such as mathematical topology, relativity or particle physics. For this reason, the tools of NLTS have been confined and utilized mostly in the fields of mathematics and physics. However, many natural phenomena investigated I many fields have been revealing deterministic non linear structures. In this book we aim at presenting the theory and the empirical of NLTS to a broader audience, to make this very powerful area of science available to many scientific areas. This book targets students and professionals in physics, engineering, biology, agriculture, economy and social sciences as a textbook in Nonlinear Time Series Analysis (NLTS) using the R computer language.


2021 ◽  
pp. 109963622199387
Author(s):  
Mathilde Jean-St-Laurent ◽  
Marie-Laure Dano ◽  
Marie-Josée Potvin

The effect of extreme cold temperatures on the quasi-static indentation and the low velocity impact behavior of woven carbon/epoxy composite sandwich panels with Nomex honeycomb core was investigated. Impact tests were performed at room temperature, –70°C, and –150°C. Two sizes of hemispherical impactor were used combined to three different impactor masses. All the impact tests were performed at the same initial impact velocity. The effect of temperature on the impact behavior is investigated by studying the load history, load-displacement curves and transmitted energy as a function of time curves. Impact damage induced at various temperatures was studied using different non-destructive and destructive techniques. Globally, more damages are induced with impact temperature decreasing. The results also show that the effect of temperature on the impact behavior is function of the impactor size.


2020 ◽  
Author(s):  
E. Priyadarshini ◽  
G. Raj Gayathri ◽  
M. Vidhya ◽  
A. Govindarajan ◽  
Samuel Chakkravarthi

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