Background: In the context of global climate change, studies have focused on the ambient temperature and mortality of cardiovascular diseases (CVDs). However, little is known about the effect of ambient temperature on year of life lost (YLL), especially the life loss per death caused by ambient temperature. In this study, we aimed to assess the relationship between ambient temperature and life loss and estimate the impact of ambient temperature on life loss per death. Methods: We collected daily time series of mortality and meteorological data from 70 locations in Hunan province, central China, in periods ranging from Jan. 1, 2013, to Dec. 31, 2017. Crude rates of YLL were calculated per 100,000 people per year (YLL/100,000 population) for each location. A distributed lag nonlinear model and multivariate meta-regression were used to estimate the associations between ambient temperature and YLL rates. Then, the average life loss per death attributable to ambient temperature was calculated. Results: There were 711,484 CVD deaths recorded within the study period. The exposure-response curve between ambient temperature and YLL rates was inverted J or U-shaped. Relative to the minimum YLL rate temperature, the life loss risk of extreme cold temperature lasted for 10 to 12 days, whereas the risk of extreme hot temperature appeared immediately and lasted for 3 days. On average, the life loss per death attributable to non-optimum ambient temperatures was 1.89 (95% CI, 1.21-2.56) years. Life loss was mainly caused by cold temperature (1.13, 95% CI, 0.89‑1.37), particularly moderate cold (1.00, 95% CI, 0.78‑1.23). For demographic characteristics, the mean life loss per death was relatively higher for males (2.07, 95% CI, 1.44‑2.68) and younger populations (3.72, 95% CI, 2.06‑5.46) than for females (1.88, 95% CI, 1.21-2.57) and elderly people (1.69, 95% CI, 1.28-2.10), respectively. Conclusions: We found that both cold and hot temperatures significantly aggravated premature death from CVDs. Our results indicated that the whole range of effects of ambient temperature on CVDs should be given attention.

The ambient temperature–health relationship is of growing interest as the climate changes. Previous studies have examined the association between ambient temperature and mortality or morbidity, however, there is little literature available on the ambient temperature effects on year of life lost (YLL). Thus, we aimed to quantify the YLL attributable to non-optimum ambient temperature. We obtained data from 1 January 2013 to 31 December 2017 of 70 counties in Hunan, China. In order to combine the effects of each county, we used YLL rate as a health outcome indicator. The YLL rate was equal to the total YLL divided by the population of each county, and multiplied by 100,000. We estimated the associations between ambient temperature and YLL with a distributed lag non-linear model (DNLM) in a single county, and then pooled them in a multivariate meta-regression. The daily mean YLL rates were 22.62 y/(p·100,000), 10.14 y/(p·100,000) and 2.33 y/(p·100,000) within the study period for non-accidental, cardiovascular, and respiratory disease death. Ambient temperature was responsible for advancing a substantial fraction of YLL, with attributable fractions of 10.73% (4.36–17.09%) and 16.44% (9.09–23.79%) for non-accidental and cardiovascular disease death, respectively. However, the ambient temperature effect was not significantly for respiratory disease death, corresponding to 5.47% (−2.65–13.60%). Most of the YLL burden was caused by a cold temperature than the optimum temperature, with an overall estimate of 10.27% (4.52–16.03%) and 15.94% (8.82–23.05%) for non-accidental and cardiovascular disease death, respectively. Cold and heat temperature-related YLLs were higher in the elderly and females than the young and males. Extreme cold temperature had an effect on all age groups in different kinds of disease-caused death. This study highlights that general preventative measures could be important for moderate temperatures, whereas quick and effective measures should be provided for extreme temperatures.

The evidence is limited for the mortality burden of temperature variability between neighboring days. This study developed a novel indicator to measure temperature variability between neighboring days and quantify its mortality burden. Daily mortality and meteorological data during 2006–2017 from 364 locations across China were collected. We first employed a distributed lag non-linear model and multivariable meta-analysis to investigate the association between the diurnal temperature range (DTR) with the years of life lost (YLL) rate and the association between the nocturnal temperature range (NTR) with the YLL rate. Then, we calculated the weight temperature variability between neighboring days (weight-TVN) based on the attributable YLL rate of the DTR and NTR. The relationship between the weight-TVN and YLL rate was analyzed, and the attributable fraction (AF) of the YLL and weight-TVN related life loss per death was calculated to quantify the mortality burden. Stratified analyses were conducted by region, season, gender, age group and cause of death. The DTR-YLL rate curve and NTR-YLL rate curve were both J-shaped and a higher YLL rate attributable to DTR was observed than NTR. There was a significant association between the weight-TVN and YLL rate. An estimated AF of the weight-TVN was 6.02% (95%CI: 3.71%–8.33%). The average life loss per death due to weight-TVN was 0.93 year (95%CI: 0.57–1.29). Stratification analyses showed that the AFs of weight-TVN were relatively larger in southern China, in the cold season, in the elderly, females and patients with respiratory illnesses. Although the AF of weight-TVN among the young group (AF = 4.74%, 95%CI: 1.79%–7.69%) was lower than for the elderly (AF = 6.06%, 95%CI: 3.72%–8.41%), weight-TVN related life loss per death among the young population (1.51, 95%CI: 0.57–2.45) was much higher than in the elderly (0.59, 95%CI: 0.36–0.82). A novel indicator to measure temperature variability between neighboring days was developed, and temperature fluctuation between adjacent days significantly increased the mortality burden. Our results indicate that more attention should be paid to short-term temperature fluctuation.

While ambient formaldehyde (HCHO) concentrations are increasing worldwide, there was limited research on its health effects. To assess the association of long-term exposure to ambient HCHO with the risk of respiratory (RESP) mortality and the associated mortality burden in China. Annual and seasonal RESP death and tropospheric HCHO vertical columns data were collected in 466 counties/districts across China during 2013-2016. A difference-in-differences approach combined with a generalized linear mixed-effects regression model was employed to assess the exposure-response association between long-term ambient HCHO exposure and RESP mortality risk. Additionally, we computed the attributable fraction (AF) to gauge the proportion of RESP mortality attributable to HCHO exposure. This analysis encompassed 560,929 RESP deaths. The annual mean ambient HCHO concentration across selected counties/districts was 8.02×10¹⁵ ± 2.22×10¹⁵ molec.cm^-2 during 2013-2016. Each 1.00×10¹⁵ molec.cm^-2 increase in ambient HCHO was associated with a 1.61 % increase [excess risk (ER), 95 % confidence interval (CI): 1.20 %, 2.03 %] in the RESP mortality risk. The AF of RESP mortality attributable to HCHO was 12.16 % (95 %CI:9.33 %, 14.88 %), resulting in an annual average of 125,422 (95 %CI:96,404, 153,410) attributable deaths in China. Stratified analyses suggested stronger associations in individuals aged ≥65 years old (ER=1.87 %, 95 %CI:1.43 %, 2.32 %), in cold seasons (ER=1.00 %, 95 %CI:0.56 %, 1.44 %), in urban areas (ER=1.65 %, 95 %CI:1.15 %, 2.16 %), and in chronic obstructive pulmonary disease patients (ER=1.95 %, 95 %CI:1.42 %, 2.48 %). This study suggested that long-term HCHO exposure may significantly increase the risk of RESP mortality, leading to a substantial mortality burden. Targeted measures should be implemented to control ambient HCHO pollution promptly.

Background: The Spring Festival is one of the most important traditional festivals in China. This study aimed to estimate the mortality risk attributable to the Spring Festival.Methods: Between 2013 and 2017, daily meteorological, air pollution, and mortality data were collected from 285 locations in China. The Spring Festival was divided into three periods: pre-Spring Festival (16 days before Lunar New Year's Eve), mid-Spring Festival (16 days from Lunar New Year's Eve to Lantern Festival), and post-Spring Festival (16 days after Lantern Festival). The mortality risk attributed to the Spring Festival in each location was first evaluated using a distributed lag nonlinear model (DLNM), and then it was pooled using a meta-analysis model.Results: We observed a dip/rise mortality pattern during the Spring Festival. Pre-Spring Festival was significantly associated with decreased mortality risk (ER: −1.58%, 95%CI: −3.09% to −0.05%), and mid-Spring Festival was unrelated to mortality risks, while post-Spring Festival was significantly associated with increased mortality risk (ER: 3.63%, 95%CI: 2.15–5.12%). Overall, a 48-day Spring Festival period was associated with a 2.11% (95%CI: 0.91–3.33%) increased mortality. We also found that the elderly aged over 64 years old, women, people with cardiovascular disease (CVD), and people living in urban areas were more vulnerable to the Spring Festival.Conclusion: Our study found that the Spring Festival significantly increased the mortality risk in China. These findings suggest that it is necessary to develop clinical and public health policies to alleviate the mortality burden associated with the Spring Festival.