The Short-Term Effect of Ambient Temperature on Mortality in Wuhan, China: A Time-Series Study Using a Distributed Lag Non-Linear Model

Abstract

Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality.

Association between Severe Fever with Thrombocytopenia Syndrome Incidence and Ambient Temperature

“…Distributed lag nonlinear model has been widely used in the analysis of the burden of ambient air pollution on years of life lost, effects of ambient temperature on stroke hospital admissions, short-term effect of ambient temperature on mortality, and so on. [23][24][25] Furthermore, DLNM has also been used in the study of associations between meteorological factors and communicable diseases. Xiang et al 26 found reversed U-shaped nonlinear associations between ambient temperature, relative humidity, extreme wind velocity, and dengue.…”

Using a distributed lag non-linear model to identify impact of temperature variables on haemorrhagic fever with renal syndrome in Shandong Province

“…This methodology rests on the definition of a crossbasis, a bi-dimensional space of functions describing the dependency along the space of the predictor and along lags. Therefore, DLNM can simultaneously investigate the non-linear exposure-response relationships and delayed effects in a flexible way and it has been widely used to examine the relationships and delayed effects of meteorological variables on human health [20,21] and has been widely used in various diseases [22][23][24][25][26][27][28]. Also the quasi-Poisson generalised linear regression, as a link function, was used to try to avoid the overdispersion problems of data.…”

Diurnal Temperature Range in Relation to Daily Mortality and Years of Life Lost in Wuhan, China

“…This study was conducted in the capital city of Hubei Province, central China—Wuhan. Known as the largest city in central China, Wuhan is located in the middle of the Yangzi River and has a typical subtropical monsoon climate [ 26 , 27 ]. Two urban districts, namely Jiang’an and Qiaokou, were selected as the study area, with a total of about 1.22 million permanent residents in 2010 and an urban area of 111.7 km 2 .…”