Zan Ding1, Liujiu Li2, Ruqin Wei2, Wenya Dong3, Pi Guo3, Shaoyi Yang3, Ju Liu3, Qingying Zhang4. 1. Department of Preventive Medicine, Shantou University Medical College, Shantou, Guangdong 515041, China; Yuxi Center for Disease Control and Prevention, Yuxi, Yunnan 653000, China. 2. Yuxi Center for Disease Control and Prevention, Yuxi, Yunnan 653000, China. 3. Department of Preventive Medicine, Shantou University Medical College, Shantou, Guangdong 515041, China. 4. Department of Preventive Medicine, Shantou University Medical College, Shantou, Guangdong 515041, China. Electronic address: qyzhang@stu.edu.cn.
Abstract
BACKGROUND: Consistent evidence has shown excess mortality associated with cold temperature, but some important details of the cold-mortality association (e.g. slope and threshold) have not been adequately investigated and few studies focused on the cold effect in high-altitude areas of developing countries. We attempted to quantify the cold effect on mortality, identify the details, and evaluate effect modification in the distinct subtropical plateau monsoon climate of Yuxi, a high plateau region in southwest China. METHODS: From daily mortality and meteorological data during 2009-2014, we used a quasi-Poisson model combined with a "natural cubic spline-natural cubic spline" distributed lag non-linear model to estimate the temperature-mortality relationship and then a simpler "hockey-stick" model to investigate the cold effect and details. RESULTS: Cold temperature was associated with increased mortality, and the relative risk of cold effect (1st relative to 10th temperature percentile) on non-accidental, cardiovascular, and respiratory mortality for lag 0-21 days was 1.40 (95% confidence interval: 1.19-1.66), 1.61 (1.28-2.02), and 1.13 (0.78-1.64), respectively. A 1°C decrease below a cold threshold of 9.1°C (8th percentile) for lags 0-21 was associated with a 7.35% (3.75-11.09%) increase in non-accidental mortality. The cold-mortality association was not significantly affected by cause-specific mortality, gender, age, marital status, ethnicity, occupation, or previous history of hypertension. CONCLUSIONS: There is an adverse impact of cold on mortality in Yuxi, China, and a temperature of 9.1°C is an important cut-off for cold-related mortality for residents.
BACKGROUND: Consistent evidence has shown excess mortality associated with cold temperature, but some important details of the cold-mortality association (e.g. slope and threshold) have not been adequately investigated and few studies focused on the cold effect in high-altitude areas of developing countries. We attempted to quantify the cold effect on mortality, identify the details, and evaluate effect modification in the distinct subtropical plateau monsoon climate of Yuxi, a high plateau region in southwest China. METHODS: From daily mortality and meteorological data during 2009-2014, we used a quasi-Poisson model combined with a "natural cubic spline-natural cubic spline" distributed lag non-linear model to estimate the temperature-mortality relationship and then a simpler "hockey-stick" model to investigate the cold effect and details. RESULTS: Cold temperature was associated with increased mortality, and the relative risk of cold effect (1st relative to 10th temperature percentile) on non-accidental, cardiovascular, and respiratory mortality for lag 0-21 days was 1.40 (95% confidence interval: 1.19-1.66), 1.61 (1.28-2.02), and 1.13 (0.78-1.64), respectively. A 1°C decrease below a cold threshold of 9.1°C (8th percentile) for lags 0-21 was associated with a 7.35% (3.75-11.09%) increase in non-accidental mortality. The cold-mortality association was not significantly affected by cause-specific mortality, gender, age, marital status, ethnicity, occupation, or previous history of hypertension. CONCLUSIONS: There is an adverse impact of cold on mortality in Yuxi, China, and a temperature of 9.1°C is an important cut-off for cold-related mortality for residents.
Authors: Sida Liu; Emily Yang Ying Chan; William Bernard Goggins; Zhe Huang Journal: Int J Environ Res Public Health Date: 2020-10-07 Impact factor: 3.390