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Although the effect of ambient temperature on cardiovascular disease (CVDs) has been well explored, studies using years of life lost (YLLs) as the outcome especially evaluating the average life loss per death attributable to temperatures were rare. We examine the associations between ambient temperature and YLLs of CVDs, and further quantify temperature-related life loss per death. Daily YLL rates were calculated using death data from 364 locations across China during 2006–2017, and meteorological data were collected for the same period. A distributed-lag nonlinear model and meta-regression were applied to examine the relationships between temperature and YLL rates of CVDs. Subgroup analyses by age, gender, region, and cause-specific CVDs were investigated. The total YLLs and average YLLs per death attributable to temperature were further quantified to assess life loss caused by non-optimal temperature. Both high and low temperatures significantly increased YLL rates of CVDs, with greater effects for cold than heat. Cerebrovascular diseases (CEDs) account for the largest proportion (47.17%) of total YLLs of CVDs attributable to non-optimal temperature. On average, life loss per CVD death attributable to non-optimal temperatures was 1.51 (95% eCI: 1.33, 1.69) years, with 1.07 (95% eCI: 1.00, 1.15) years from moderate cold. Average life losses per death were observed higher for males (1.71, 95% eCI: 1.43, 1.99), younger population (3.82, 95% eCI: 2.86, 4.75), central China (1.62; 95% eCI: 1.41, 1.83) and hemorrhagic stroke (2.86, 95% eCI: 2.63, 3.10) than their correspondents. We found that non-optimal temperature significantly aggravated premature death of CVD, with CEDs being the most affected, and most of temperature-related life loss of CVD was attributed to moderate cold. Our findings imply that peoples with CEDs in moderate cold days are vulnerable populations, which may contribute to a better understanding the adverse effects and pathogenesis of temperature on CVDs. Unlabelled Image • This study examines the health effects of non-optimal temperature, and quantify temperature-related life loss per death. • Life loss per CVD death attributable to non-optimal temperatures was 1.51. • Most of temperature-related life loss of CVD was attributed to moderate cold. [ABSTRACT FROM AUTHOR]

Abstract: Background: Heat waves have been reported to be associated with increased mortality; however, fewer studies have examined the effect modification by heat wave characteristics, individual characteristics and community characteristics. Methods: This study investigated the effect of extreme heat on mortality in 2 urban and 2 rural communities in Guangdong Province, China during 2006–2010. The effect of extreme heat was divided into two parts: main effect due to high temperature and added effect due to prolonged heat for several consecutive days. A distributed lag non-linear model was used to calculate the relative risk with consideration of lag days and potential confounding factors. Separate models were further fit by individual characteristics (cause of death, age and gender) and heat wave characteristics (intensity, duration and timing), and potential effect modification of community characteristics was examined using a meta-regression, such as educational levels, percentage of the elderly, Gross Regional Domestic Product (GDP). Results: The overall main effects (ER=8.2%, 95% CI: 3.4%, 13.2%) were greater than the added effects (ER=0.0%, 95% CI: −3.8%, 4.0%) on the current day. The main effect peaked at lag0–2, and was higher for the two rural areas compared to the two cities, for respiratory compared to cardiovascular mortality, for those ≥75years old and for females. The modifying effects of heat wave characteristics and community characteristics on mortality were not statistically significant. Conclusion: This study suggests the effects of extreme heat were mainly driven by high temperature, which can be modified by some individual characteristics. [Copyright &y& Elsevier]

Abstract: Background: Numerous studies have reported the association between ambient temperature and mortality. However, few multicity studies have been conducted in subtropical regions in developing countries. The present study assessed the health effects of temperature on mortality in four subtropical cities of China. Methods: We used “double threshold-natural cubic spline” distributed lag non-linear model (DLNM) to investigate the cold and hot effects on mortality at different lags in four subtropical cities. Then we conducted a meta-analysis to estimate the overall cold and hot effects on mortality at different lag days. Results: A U-shaped relationship between temperature and mortality was found in the four cities. Cold effect was delayed and persisted for about 27days, whereas hot effect was acute and lasted for 3days. In Changsha, Kunming, Guangzhou and Zhuhai, a 1°C decrease of temperature under the low threshold was associated with a lag0–27 cumulative relative risk (RR) of 1.061 (95% confidence interval (CI): 1.023–1.099), 1.044 (95% CI: 1.033–1.056), 1.096 (95% CI: 1.075–1.117) and 1.111 (95% CI: 1.078–1.145) for total mortality, respectively. And RR for 1°C increase of temperature above the hot threshold at the lag0 was 1.020 (95% CI: 1.003–1.037), 1.017 (95% CI: 1.004–1.030), 1.029 (95% CI: 1.020–1.039) and 1.023 (95% CI: 1.004–1.042), respectively. The cold and hot effects were greater among the elderly in Changsha, Guangzhou and Zhuhai. Meta analysis showed that the hot effect decreased gradually with lag days, with the greatest effect at current day (RR=1.023, 95% CI: 1.015–1.031); while the cumulative cold effect increased gradually with lag days, with the highest effect at lag0–27 (RR=1.076, 95% CI: 1.046–1.107). Conclusion: Both low and high temperatures were associated with increased mortality in the four subtropical Chinese cities, and cold effect was more durable and pronounced than hot effect. [Copyright &y& Elsevier]