Search

Injury poses heavy burden on public health, accounting for nearly 8% of all deaths globally, but little evidence on the role of climate change on injury exists. We collect data during 2013-2019 in six provinces of China to examine the effects of temperature on injury mortality, and to project future mortality burden attributable to temperature change driven by climate change based on the assumption of constant injury mortality and population scenario. The results show that a 0.50% (95% confident interval (CI): 0.13%–0.88%) increase of injury mortality risk for each 1 °C rise in daily temperature, with higher risk for intentional injury (1.13%, 0.55%–1.71%) than that for unintentional injury (0.40%, 0.04%–0.77%). Compared to the 2010s, total injury deaths attributable to temperature change in China would increase 156,586 (37,654–272,316) in the 2090 s under representative concentration pathways 8.5 scenario with the highest for transport injury (64,764, 8,517–115,743). Populations living in Western China, people aged 15–69 years, and male may suffer more injury mortality burden from increased temperature caused by climate change. Our findings may be informative for public health policy development to effectively adapt to climate change.

Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure.The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity.The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk.Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects.

Although studies have investigated the associations between PM2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014–2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM2.5 (lag 0–3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 μg/m3 increment in PM2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [−0.60%, 1.84%]). Disparities in PM2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM2.5 with mortality risks in China and demonstrated urban-rural disparities of PM2.5-mortality associations for various causes of death.

What is already known on this topic? Clusters of COVID-19 cases often happened in small settings (e.g., families, offices, school, or workplaces) that facilitate person-to-person virus transmission, especially from a common exposure. What is added by this report? On January 10 and 11, 2021, an individual gave three product promotional lectures in Tonghua City, Jilin Province, that ultimately led to a 74-case cluster of COVID-19. Our investigation determined the outbreak to be an import-related COVID-19 superspreading cluster event in which elderly, retired people were exposed to the infected individual during his promotional lectures, which were delivered in a confined space and lasted several hours. What are the implications for public health practice? Routine activities, such as attending a lecture in a classroom, can provide an environment conducive to COVID-19 superspreading events because respiratory viruses can spread easily and widely. We suggest local government to strengthen infection control management, reduce unnecessary indoor large gathering activities, and promote wearing of masks, especially during wintertime in the north of China. Health education for elderly people should promote use of effective personal protection and emphasize the importance of wearing masks.

As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare.We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios.CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China.CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs.

BackgroundThe 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.MethodsBetween 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.ResultsWe 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.ConclusionOur 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.

Several studies have investigated the associations between diurnal temperature rage (DTR) and mortality, but little evidence has been available regarding the association of DTR with years of life lost (YLL). The aim of this study was to examine the association of DTR with YLL rate, and quantify life loss per death caused by DTR in China. Daily meteorological and death data were collected from 364 locations in China during 2006–2017. First, we calculated daily YLL rate. Then, the distributed lag nonlinear model was applied to estimate the associations of DTR with YLL rate in each location, and multivariable meta-analysis was conducted to pool the location-specific estimates. Finally, we calculated the attributable fractions of DTR on YLL rate and average life loss per death to estimate the mortality burden caused by DTR. Subgroups analyses were conducted by region, age, sex and cause of death. A J-shaped association of DTR with YLL rate was identified in China. The minimum YLL-rate DTR (MYDTR) was 3.7 °C nationwide. The overall AF of DTR in China was 6.40% [95% confidence interval (CI) 3.95–8.86%], and AFs caused by DTR were higher in females, the elderly and south China. An average of 0.96 years (95%CI 0.57–1.35) life loss per death was attributable to DTR nationwide, and life losses per death attributed to DTR were higher in female, young population, and south China. AF and life loss per death caused by DTR were much higher in cold season than that in warm season. Both high DTR and low DTR increased YLL rate in China. Mortality burdens of DTR were much higher in cold season than warm season. The effects of DTR were modified by region, demography and cause of death. Our findings suggest that vulnerable population should be protected when daily temperature change rapidly, especially in cold season.

Although studies have investigated the associations between PM2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014–2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM2.5 (lag 0–3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 μg/m3 increment in PM2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [−0.60%, 1.84%]). Disparities in PM2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM2.5 with mortality risks in China and demonstrated urban-rural disparities of PM2.5-mortality associations for various causes of death., Graphical abstract, Public summary • PM2.5 had greater effects on CVD/CED mortality in urban cities than in rural areas • PM2.5 had stronger effects on RESP mortality in rural areas than in urban cities • An annual mean of 16.5/100,000 deaths was attributable to PM2.5 in urban cities • An annual mean of 3.4//100,000 deaths was attributable to PM2.5 in rural areas • Spatially targeted measures are needed to reduce PM2.5-related mortality in China

Background Several studies have investigated the associations between ambient temperature and years of life lost (YLLs), but few focused on the difference of life loss attributable to temperature among different socioeconomic development levels. Objectives We investigated the disparity in temperature-YLL rate relationships and life loss per death attributable to nonoptimal temperature in regions with various development levels. Methods Three hundred sixty-four Chinese counties or districts were classified into 92 high-development regions (HDRs) and 272 low-development regions (LDRs) according to socioeconomic factors of each location using K-means clustering approach. We used distributed lag non-linear models (DLNM) and multivariate meta-analysis to estimate the temperature-YLL rate relationships. We calculated attributable fraction (AF) of YLL and temperature-related average life loss per death to compare mortality burden of temperature between HDRs and LDRs. Stratified analyses were conducted by region, age, sex and cause of death. Results We found that non-optimal temperatures increased YLL rates in both HDRs and LDRs, but all subgroups in LDRs were more vulnerable. The disparity of cold effects between HDRs and LDRs was significant, while the difference in heat effect was insignificant. The overall AF of non-optimal temperature in LDRs [AF = 12.2, 95% empirical confidence interval (eCI):11.0–13.5%] was higher than that in HDRs (AF = 8.9, 95% eCI: 8.3–9.5%). Subgroups analyses found that most groups in LDRs had greater AFs than that in HDRs. The average life loss per death due to non-optimal temperature in LDRs (1.91 years, 95% eCI: 1.72–2.10) was also higher than that in HDRs (1.32 years, 95% eCI: 1.23–1.41). Most of AFs and life loss per death were caused by moderate cold in both HDRs and LDRs. Conclusions Mortality burden caused by temperature was more significant in LDRs than that in HDRs, which means that more attention should be paid to vulnerable populations in LDRs in planning adaptive strategies.

Background 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. Methods 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. Results 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. Conclusions 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.

The short-term effects of ambient temperature on mortality have been widely investigated. However, the epidemiological evidence on the long-term effects of temperature on mortality is rare. In present study, we conducted a nationwide quasi-experimental design, which based on a variant of difference-in-differences (DID) approach, to examine the association between long-term exposure to ambient temperature and mortality risk in China, and to analyze the effect modification of population characteristics and socioeconomic status. Data on mortality were collected from 364 communities across China during 2006–2017, and environmental data were obtained for the same period. We estimated a 2.93 % (95 % CI: 2.68 %, 3.18 %) increase in mortality risk per 1 °C decreases in annual temperature, the greater effects were observed on respiratory diseases (5.16 %, 95 % CI: 4.53 %, 5.79 %) than cardiovascular diseases (3.43 %, 95 % CI: 3.06 %, 3.80 %), and on younger people (4.21 %, 95 % CI: 3.73 %, 4.68 %) than the elderly (2.36 %, 95 % CI: 2.06 %, 2.65 %). In seasonal analysis, per 1 °C decreases in average temperature was associated with 1.55 % (95 % CI: 1.23 %, 1.87 %), −0.53 % (95 % CI: −0.89 %, −0.16 %), 2.88 % (95 % CI: 2.45 %, 3.31 %) and 4.21 % (95 % CI: 3.98 %, 4.43 %) mortality change in spring, summer, autumn and winter, respectively. The effects of long-term temperature on total mortality were more pronounced among the communities with low urbanization, low education attainment, and low GDP per capita. In total, the decrease of average temperature in summer decreased mortality risk, while increased mortality risk in other seasons, and the associations were modified by demographic characteristics and socioeconomic status. Our findings suggest that populations with disadvantaged characteristics and socioeconomic status are vulnerable to long-term exposure of temperature, and targeted policies should be formulated to strengthen the response to the health threats of temperature exposure.

Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006–2017. YLL was divided into three age groups (0–64 years, 65–74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0–64 years, 65–74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.

Additional file 1. Supplementary Material.

Importance The aging of the population is associated with an increasing burden of fractures worldwide. However, the epidemiological features of fractures in mainland China are not well known. Objective To assess the prevalence of and factors associated with osteoporosis, clinical fractures, and vertebral fractures in an adult population 40 years or older in mainland China. Design, setting. and participants This cross-sectional study, the China Osteoporosis Prevalence Study, was conducted from December 2017 to August 2018. A random sample of individuals aged 20 years or older who represented urban and rural areas of China were enrolled, with a 99% participation rate. Main outcomes and measures Weighted prevalence of osteoporosis, clinical fracture, and vertebral fracture by age, sex, and urban vs rural residence as determined by x-ray absorptiometry, questionnaire, and radiography. Results A total of 20 416 participants were included in this study; 20 164 (98.8%; 11 443 women [56.7%]; mean [SD] age, 53 [13] years) had a qualified x-ray absorptiometry image and completed the questionnaire, and 8423 of 8800 (95.7%) had a qualified spine radiograph. The prevalence of osteoporosis among those aged 40 years or older was 5.0% (95% CI, 4.2%-5.8%) among men and 20.6% (95% CI, 19.3%-22.0%) among women. The prevalence of vertebral fracture was 10.5% (95% CI, 9.0%-12.0%) among men and 9.7% (95% CI, 8.2%-11.1%) among women. The prevalence of clinical fracture in the past 5 years was 4.1% (95% CI, 3.3%-4.9%) among men and 4.2% (95% CI, 3.6%-4.7%) among women. Among men and women, 0.3% (95% CI, 0.0%-0.7%) and 1.4% (95% CI, 0.8%-2.0%), respectively, with osteoporosis diagnosed on the basis of bone mineral density or with fracture were receiving antiosteoporosis treatment to prevent fracture. Conclusions and relevance In this cross-sectional study of an adult population in mainland China, the prevalence of osteoporosis and vertebral fracture were high and the prevalence of vertebral fracture and clinical fracture was similarly high in men and women. These findings suggest that current guidelines for screening and treatment of fractures among patients in China should focus equally on men and women and should emphasize the prevention of vertebral fractures.

Background Global warming may increase the frequency of compound hot extremes (CHEs). This study aimed to assess the current mortality burden and future mortality risk attributable to CHEs in China. Methods Daily meteorological, air pollution and mortality data were collected in 364 locations from 2006 to 2017 across China. Hot day/night was identified as a day where daily Tmax/Tmin was higher than its 90th percentile in summer. CHE was defined as a hot night with a following hot day. Mortality risk attributed to CHEs in each location was first evaluated using a distributed lag non-linear model. Location-specific association was pooled using a multivariate meta-analysis model, and attributable fraction in the current time and mortality risk from CHEs under different climate change scenarios (RCP 2.6, RCP 4.5, RCP 8.5) in the future were assessed. Results CHEs (RR: 1.23, 95%CI: 1.19–1.28) were associated with greater mortality risk, and 0.96% mortality was attributable to CHEs. We found that female, the elderly, and people living in north China were more vulnerable to CHEs. In addition, more intensive (RR: 1.07, 95%CI: 1.06–1.08) and consecutive CHEs (RR: 1.09, 95%CI: 1.02–1.17) could increase mortality risk. We further observed a seven to nineteen fold deaths attributable to CHEs in 2090s under middle and high climate change scenarios. Conclusion Our study found that CHEs significantly increased mortality risk and would cause considerable mortality burden in future. These findings suggest that it is necessary to develop clinical and public health policy to alleviate the mortality burden associated with CHEs.

Many studies have linked temperature with respiratory deaths, but epidemiological evidence of temperature-attributable years of life lost (YLL) from respiratory diseases is limited. Daily respiratory YLL rates were calculated using mortality data from 364 locations of China during 2006–2017, and meteorological data were collected for the same period. First, the distributed lag non-linear model (DLNM) was applied to estimate specific temperature-respiratory YLL rate associations in each location. Then multivariable meta-analysis was conducted to pool the location-specific estimates. Finally, we calculated the average life loss per death (LLD) to quantify the respiratory mortality burden of non-optimal temperature. Subgroup analyses were conducted by gender, age, region and cause of death. Inversely J-shaped association was observed between non-optimal temperature and respiratory YLL rate in China. The minimum YLL-rate temperature was 26.9 °C nationwide. An average of 1.37 years (95% CI: 1.06–1.65) LLD was attributable to non-optimal temperatures with 2.06 years (95% CI: 1.57–2.60) for pneumonia, 2.03 years (95% CI: 1.76–2.31) for chronic lower respiratory infections (LRTI), 0.88 years (95% CI: 0.65–1.09) for chronic obstructive pulmonary disease (COPD), most of which was attributed to moderate cold (0.73 years, 95% CI: 0.65–0.80). LLD caused by non-optimal temperature was higher in males, the young, and north China. Exposure to non-optimal temperature increases respiratory YLL rate in China, most of which were attributed to moderate cold. People with respiratory diseases including pneumonia, chronic LRTI and COPD are vulnerable to non-optimal temperature exposure. The result of this study provides useful information to reduce temperature-related respiratory disease burden.

Summary Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013–2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006–2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65–74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics., Graphical Abstract, Public Summary • Years of life lost (YLL) is used to estimate the effects of temperature • Both low and high temperatures can increase the YLLs • Average 1.02 YLL per death is attributed to temperature exposure • Temperature causes larger YLLs per death in males, younger people, and central China

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.