Extreme temperature and mortality: evidence from China

The temporal variation in the effects of extreme temperature on respiratory mortality: Evidence from 136 cities in China, 2006-2019

BACKGROUND

In the context of climate change and urbanization, the temporal variation of the adverse health effect of extreme temperature has attracted increasing attention.

METHODS

The meteorological data and the daily death records of mortality from respiratory diseases of 136 Chinese cities were from 2006 to 2019. Heat wave and cold spell were selected as the indicator events of extreme high temperature and extreme low temperature, respectively. The generalized linear model and time-varying distributed lag model were used to perform a two-stage time-series analysis to evaluate the temporal variation of the mortality risk associated with extreme temperature in the total population, sub-populations (sex- and age- specific) and different regions (climatic zone and relative humidity level).

RESULTS

During the study period, relative risk (RR) of respiratory mortality associated with heat wave decreased from 1.22 (95 %CI: 1.07-1.39) to 1.13 (95 %CI: 1.01-1.26) in the total population, and RR of respiratory mortality associated with cold spell decreased from 1.30 (95 %CI: 1.14-1.49) to 1.17 (95 %CI: 1.08-1.26). The impact of heat wave reduced in the males (P = 0.044) and in the females as with cold spell (P < 0.001). The respiratory mortality risk of people over 65 associated with cold spell decreased (P = 0.040 for people aged 65-74 and P < 0.001 for people over 75). The effect of cold spell reduced in cities from tropical or arid zone (P = 0.035). The effects of both heat wave and cold spell decreased in cities with the relative humidity in the first quartile (P = 0.046 and 0.010, respectively).

CONCLUSION

The impact of heat wave on mortality of respiratory diseases decreased mainly in males and cities with the lowest relative humidity, while the impact of cold spell reduced in females, people over 65 and tropical and arid zone, suggesting adaptation to extreme temperature of Chinese residents to some extent.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Short-term exposure to extreme temperature and outpatient visits for respiratory diseases among children in the northern city of China: a time-series study

BACKGROUND

Although studies have indicated that extreme temperature is strongly associated with respiratory diseases, there is a dearth of studies focused on children, especially in China. We aimed to explore the association between extreme temperature and children's outpatient visits for respiratory diseases and seasonal modification effects in Harbin, China.

METHODS

A distributed lag nonlinear model (DLNM) was used to explore the effect of extreme temperature on daily outpatient visits for respiratory diseases among children, as well as lag effects and seasonal modification effects.

RESULTS

Extremely low temperatures were defined as the 1st percentile and 2.5th percentile of temperature. Extremely high temperatures were defined as the 97.5th percentile and 99th percentile of temperature. At extremely high temperatures, both 26 °C (97.5th) and 27 °C (99th) showed adverse effects at lag 0-6 days, with relative risks (RRs) of 1.34 [95% confidence interval (CI): 1.21-1.48] and 1.38 (95% CI: 1.24-1.53), respectively. However, at extremely low temperatures, both - 26 °C (1st) and - 23 °C (2.5th) showed protective effects on children's outpatient visits for respiratory diseases at lag 0-10 days, with RRs of 0.86 (95% CI: 0.76-0.97) and 0.85 (95% CI: 0.75-0.95), respectively. We also found seasonal modification effects, with the association being stronger in the warm season than in the cold season at extremely high temperatures.

CONCLUSIONS

Our study indicated that extremely hot temperatures increase the risk of children's outpatient visits for respiratory diseases. Efforts to reduce the exposure of children to extremely high temperatures could potentially alleviate the burden of pediatric respiratory diseases, especially during the warm season.

Association between temperature and mortality: a multi-city time series study in Sichuan Basin, southwest China

BACKGROUND

There are few multi-city studies on the association between temperature and mortality in basin climates. This study was based on the Sichuan Basin in southwest China to assess the association of basin temperature with non-accidental mortality in the population and with the temperature-related mortality burden.

METHODS

Daily mortality data, meteorological and air pollution data were collected for four cities in the Sichuan Basin of southwest China. We used a two-stage time-series analysis to quantify the association between temperature and non-accidental mortality in each city, and a multivariate meta-analysis was performed to obtain the overall cumulative risk. The attributable fractions (AFs) were calculated to access the mortality burden attributable to non-optimal temperature. Additionally, we performed a stratified analyses by gender, age group, education level, and marital status.

RESULTS

A total of 751,930 non-accidental deaths were collected in our study. Overall, 10.16% of non-accidental deaths could be attributed to non-optimal temperatures. A majority of temperature-related non-accidental deaths were caused by low temperature, accounting for 9.10% (95% eCI: 5.50%, 12.19%), and heat effects accounted for only 1.06% (95% eCI: 0.76%, 1.33%). The mortality burden attributable to non-optimal temperatures was higher among those under 65 years old, females, those with a low education level, and those with an alternative marriage status.

CONCLUSIONS

Our study suggested that a significant association between non-optimal temperature and non-accidental mortality. Those under 65 years old, females, and those with a low educational level or alternative marriage status had the highest attributable burden.

Assessment of mortality risks due to a strong cold spell in 2022 in China

Background

With the intensification of global climate warming, extreme low temperature events such as cold spells have become an increasingly significant threat to public health. Few studies have examined the relationship between cold spells and mortality in multiple Chinese provinces.

Methods

We employed health impact functions for temperature and mortality to quantify the health risks of the first winter cold spell in China on November 26th, 2022, and analyzed the reasons for the stronger development of the cold spell in terms of the circulation field.

Results

This cold spell was a result of the continuous reinforcement of the blocking high-pressure system in the Ural Mountains, leading to the deepening of the cold vortex in front of it. Temperature changes associated with the movement of cold fronts produced additional mortality risks and mortality burdens. In general, the average excess risk (ER) of death during the cold spell in China was 2.75%, with a total cumulative excess of 369,056 deaths. The health risks associated with temperatures were unevenly distributed spatially in China, with the ER values ranging from a minimum of 0.14% to a maximum of 5.72%, and temperature drops disproportionately affect southern regions of China more than northern regions. The cumulative excess deaths exibited the highest in eastern and central China, with 87,655 and 80,230 respectively, and the lowest in northwest China with 27,474 deaths. Among the provinces, excess deaths pronounced the highest in Shandong with 29,492 and the lowest in Tibet with only 196.

Conclusion

The study can provide some insight into the mortality burden of cold spells in China, while emphasising the importance of understanding the complex relationship between extreme low temperature events and human health. The outcomes could provide valuable revelations for informing pertinent public health policies.

The challenge of population aging for mitigating deaths from PM2.5 air pollution in China

Estimating the health burden of air pollution against the background of population aging is of great significance for achieving the Sustainable Development Goal 3.9 which aims to substantially reduce the deaths and illnesses from air pollution. Here, we estimated spatiotemporal changes in deaths attributable to PM2.5 air pollution in China from 2000 to 2035 and examined the drivers. The results show that from 2019 to 2035, deaths were projected to decease 15.4% (6.6%-20.7%, 95% CI) and 8.4% (0.6%-13.5%) under the SSP1-2.6 and SSP5-8.5 scenario, respectively, but increase 10.4% (5.1%-20.5%) and 18.1% (13.0%-28.3%) under SSP2-4.5 and SSP3-7.0 scenarios. Population aging will be the leading contributor to increased deaths attributable to PM2.5 air pollution, which will counter the positive gains achieved by improvements in air pollution and healthcare. Region-specific measures are required to mitigate the health burden of air pollution and this requires long-term efforts and mutual cooperation among regions in China.

Mapping health vulnerability to short-term summer heat exposure based on a directional interaction network: Hotspots and coping strategies

Health risk resulting from non-optimal temperature exposure, referred to as "systematic risk", has been a sustainable-development challenge in the context of global warming. Previous studies have recognized interactions between and among system components while assessing the vulnerability to climate change, but have left open the question of indicator directional interactions. The question is important, not least because indicator directional association analysis provides guidance to address climate risks by revealing the key nodes and pathways. The purpose of this work was to assess health vulnerability to short-term summer heat exposure based on a directional interaction network. Bayesian network model and network analysis were used to conduct a directional interaction network. Using indicator directional associations as weights, a weighted technique for the order of preference by similarity to ideal solution method was then proposed to assess heat-related health vulnerability. Finally, hotspots and coping strategies were explored based on the directional interaction network and health vulnerability assessments. The results showed that (1) indicator directional interactions were revealed in the health vulnerability framework, and the interactions differed between northern and southern China; (2) there was a dramatic spatial imbalance of health vulnerability in China, with the Beijing-Tianjin-Hebei Region and the Yangtze River Basin identified as hotspots; (3) particulate matter and ozone were recognized as priority indicators in the most vulnerable cities of northern China, while summer heat exposure level and variation were priority indicators in southern China; and (4) adaptive capacity could alter the extent of risk; thus, mitigation and adaptation should be implemented in an integrated way. Our study has important implications for strengthening the theoretical basis for the vulnerability assessment framework by providing indicator directional associations and for guiding policy design in dealing with heat-related health vulnerability in China.

Long-Term Apparent Temperature, Extreme Temperature Exposure, and Depressive Symptoms: A Longitudinal Study in China

Temperature is increasingly understood to impact mental health. However, evidence of the long-term effect of temperature exposure on the risk of depressive symptoms is still scarce. Based on the China Health and Retirement Longitudinal Study (CHARLS), this study estimated associations between long-term apparent temperature, extreme temperature, and depressive symptoms in middle-aged and older adults. Results showed that a 1 °C increase or decrease from optimum apparent temperature (12.72 °C) was associated with a 2.7% (95% CI: 1.3%, 4.1%) and 2.3% (95% CI: 1.1%, 3.5%) increased risk of depressive symptoms, respectively. This study also found that each percent increase in annual change in ice days, cool nights, cool days, cold spell durations, and tropical nights was associated with higher risk of depressive symptoms, with HRs (95%CI) of 1.289 (1.114-1.491), 2.064 (1.507-2.825), 1.315 (1.061-1.631), 1.645 (1.306-2.072), and 1.344 (1.127-1.602), respectively. The results also indicated that people living in northern China have attenuated risk of low apparent temperature. Older people were also observed at higher risk relating to more cool nights. Middle-aged people, rural residents, and people with lower household income might have higher related risk of depressive symptoms due to increased tropical nights. Given the dual effect of climate change and global aging, these findings have great significance for policy making and adaptive strategies for long-term temperature and extreme temperature exposure.

County level study of the interaction effect of PM2.5 and climate sustainability on mortality in China

Introduction

PM2.5 and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution.

Methods

In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM2.5.

Results and discussions

Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM2.5 is more than 35 μg/m3, the influence on mortality is significantly increased as PM2.5 concentration rises; when PM2.5 is above 70 μg/m3, the trend is sharp. A nonlinear antagonistic effect between CLS and PM2.5 was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM2.5 was higher (above 35 μg/m3), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM2.5 on mortality varies in different geographical regions. A negative and positive influence of CLS and PM2.5 was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.

Global Population Exposure to Extreme Temperatures and Disease Burden

The frequency and duration of extreme temperature events continues to increase worldwide. However, the scale of population exposure and its quantitative relationship with health risks remains unknown on a global scale, limiting our ability to identify policy priorities in response to climate change. Based on data from 171 countries between 2010 and 2019, this study estimated the exposure of vulnerable populations to extreme temperatures, and their contemporary and lag associations with disease burden attributed to non-optimal temperatures. Fixed-effects models and dynamic panel models were applied. Increased vulnerable population exposure to extreme temperatures had adverse contemporary effects on the burden of disease attributed to non-optimal temperature. Health risks stemming from extreme cold could accumulate to a greater extent, exhibiting a larger lag effect. Population exposure to extreme cold was mainly distributed in high-income countries, while extreme heat occurred more in low-income and middle-income countries. However, the association between population exposure to extreme cold and burden of disease was much stronger in low-income and middle-income countries than in high-income countries, whereas the effect size of population exposure to extreme heat was similar. Our study highlighted that differential strategies should be determined and implemented according to the characteristics in different countries.

The effects of temperature variability on mortality in patients with chronic obstructive pulmonary disease: a time-series analysis in Hangzhou, China

Chronic obstructive pulmonary disease (COPD) is a leading cause of death in people aged over 60 years old. Research has been reported that ambient temperature and diurnal temperature range (DTR), as representative indices of temperature variability, are contributors to the development and exacerbation of COPD. However, few studies are available in Chinese population. In this study, we aimed to assess the associations of temperature variability on COPD mortality in a fast developing city in China. Using the mortality surveillance system, we obtained a total of 7,863 deaths attributed to COPD from 2014 to 2016. Quasi-Poisson generalized linear regression with distributed lag non-linear model was applied to explore the associations between temperature variability and COPD deaths, after controlling for the potential confounders, including relative humidity, day of week, public holiday, and long-term trend. A J-shaped association of DTR and a reversely J-shaped association of temperature for COPD mortality were observed. Risk estimates showed that the relative risks (RRs) of COPD mortality with extreme high DTR at lag 0 and 0-7 days were 1.045 (95% CI: 0.949-1.151) and 1.460 (95% CI: 1.118-1.908), and the extreme high temperature at lag 0 and 0-7 days were 1.090 (95% CI: 0.945-1.256) and 1.352 (95% CI: 1.163-1.572). Our findings suggest that short-term exposure to extreme temperature was associated with mortality for COPD in Hangzhou. The evidence has implications for policy decision-making and targeted interventions.

The effect of air temperature on mortality from cerebrovascular diseases in Brazil between 1996 and 2017

Abstract Cerebrovascular diseases (CVD) are one of the leading causes of mortality globally. Air temperature is one of the risk factors for CVD; however, few studies have investigated the relationship between air temperature and mortality from these diseases in Brazil. This time series study investigated the relationship between air temperature and CVD mortality in 10 microregions located across Brazil’s five regions during the period 1996 to 2017 using mortality data from the national health information system, DATASUS and daily mean temperature data. The association between mean air temperature and mortality from CVD was measured using generalized additive models with Poisson distribution and relative and attributable risks were estimated together with 95% confidence intervals using distributed lag non-linear models and a 14-day lag. There were 531,733 deaths from CVD during the study period, 21,220 of which (11,138-30,546) were attributable to air temperature. Minimum mortality temperatures ranged from 20.1ºC in Curitiba to 29.6ºC in Belém. Associations between suboptimal air temperatures and increased risk of death from CVD were observed in all of Brazil’s five regions. Relative risk from the cold was highest in Manaus (RR 1.53; 1.22-1.91) and Campo Grande (RR 1.52; 1.18-1.94), while relative risk from heat was highest in Manaus (RR 1.75; 1.35-2.26) and Brasília (RR 1.36; 1.15-1.60).

The effect of air temperature on mortality from cerebrovascular diseases in Brazil between 1996 and 2017

Cerebrovascular diseases (CVD) are one of the leading causes of mortality globally. Air temperature is one of the risk factors for CVD; however, few studies have investigated the relationship between air temperature and mortality from these diseases in Brazil. This time series study investigated the relationship between air temperature and CVD mortality in 10 microregions located across Brazil's five regions during the period 1996 to 2017 using mortality data from the national health information system, DATASUS and daily mean temperature data. The association between mean air temperature and mortality from CVD was measured using generalized additive models with Poisson distribution and relative and attributable risks were estimated together with 95% confidence intervals using distributed lag non-linear models and a 14-day lag. There were 531,733 deaths from CVD during the study period, 21,220 of which (11,138-30,546) were attributable to air temperature. Minimum mortality temperatures ranged from 20.1ºC in Curitiba to 29.6ºC in Belém. Associations between suboptimal air temperatures and increased risk of death from CVD were observed in all of Brazil's five regions. Relative risk from the cold was highest in Manaus (RR 1.53; 1.22-1.91) and Campo Grande (RR 1.52; 1.18-1.94), while relative risk from heat was highest in Manaus (RR 1.75; 1.35-2.26) and Brasília (RR 1.36; 1.15-1.60).

The effect of ambient temperature on in-hospital mortality: a study in Nanjing, China

To reduce the inpatient mortality and improve the quality of hospital management, we explore the relationship between temperatures and in-hospital mortality in a large sample across 10 years in Nanjing, Jiangsu. We collected 10 years’ data on patient deaths from a large research hospital. Distributed lag non-linear model (DLNM) was used to find the association between daily mean temperatures and in-hospital mortality. A total of 6160 in-hospital deaths were documented. Overall, peak RR appeared at 8 °C, with the range of 1 to 20 °C having a significantly high mortality risk. In the elderly (age ≥ 65 years), peak RR appeared at 5 °C, with range − 3 to 21 °C having a significantly high mortality risk. In males, peak RR appeared at 8 °C, with the range 0 to 24 °C having a significantly high mortality risk. Moderate cold (define as 2.5th percentile of daily mean temperatures to the MT), not extreme temperatures (≤ 2.5th percentile or ≥ 97.5th percentile of daily mean temperatures), increased the risk of death in hospital patients, especially in elderly and male in-hospital patients.

The impact of extreme temperatures on human mortality in the most populated cities of Romania

The impact of extreme weather conditions on humans is one of the most important topics in biometeorology studies. The main objective of this study is to analyze the relationship between temperature-related weather conditions and natural mortality in the five most populated cities of Romania, namely, Bucharest, Cluj-Napoca, Constanța, Iași, and Timișoara. The results of this study aim to bridge a gap in national research. In the present paper, we used daily natural mortality data and daily minimum and maximum air temperatures. The distributed lag nonlinear model (DLNM) allowed us to identify weather conditions associated with natural mortality. The most important results are as follows: (i) a higher daily mortality is related to a high frequency of heat stress conditions; (ii) a higher maximum temperature increases the relative risk (RR) of natural mortality; (iii) the maximum number of fatalities is recorded on the first day of high-temperature events; and (iv) individuals much more easily adapt to cold stress conditions. The main conclusion in this study is that the inhabitants of the most populated cities in Romania are more sensitive to high-temperature stress than to low-temperature stress.

The Space and Terrestrial Weather Variations as Possible Factors for Ischemia Events in Saint Petersburg

The Space and Terrestrial Weather (Weather Complex) impact on ischemia cases in Saint Petersburg is investigated. The results show the main feature of the Weather Complex when it was related to the days of the different ischemia situations in the different ischemia people gender groups. The data treatment was done with some elements of the Folder Epochs Method, Cluster Analysis and the Mann–Whitney hypothesis test criterion.

Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

A systematic review on the association between total and cardiopulmonary mortality/morbidity or cardiovascular risk factors with long-term exposure to increased or decreased ambient temperature

The health effects of acute exposure to temperature extremes are established; those of long-term exposure only recently received attention. We performed a systematic review to assess the associations of long-term (>3 months) exposure to higher or lower temperature on total and cardiopulmonary mortality and morbidity, screening 3455 studies and selecting 34. The studies were classified in those observing associations within a population over years with changing annual temperature indices and those comparing areas with a different climate. We also assessed the risk of bias, adapting appropriately an instrument developed by the World Health Organization for air pollution. Studies reported that annual temperature indices for extremes and variability were associated with annual increases in mortality, indicating that effects of temperature extremes cannot be attributed only to short-term mortality displacement. Studies on cardiovascular mortality indicated stronger associations with cold rather than hot temperature, whilst those on respiratory outcomes reported effects of both heat and cold but were few and used diverse health outcomes. Interactions with air pollution were not generally assessed. The few studies investigating effect modification showed stronger effects among the elderly and those socially deprived. Comparisons of health outcome prevalence between areas reported lower blood pressure and a tendency for higher obesity in populations living in warmer climates. Our review indicated interesting associations between long-term exposure to unusual temperature levels in specific areas and differences in health outcomes and cardiovascular risk factors between geographical locations with different climate, but the number of studies by design and health outcome was small. Risk of bias was identified because of the use of crude exposure assessment and inadequate adjustment for confounding. More and better designed studies, including the investigation of effect modifiers, are needed.

Global Observations and CMIP6 Simulations of Compound Extremes of Monthly Temperature and Precipitation

Compound climate extremes, such as events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. This paper aims to analyze temporal and spatial characteristics of compound extremes of monthly temperature and precipitation, evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating compound extremes, and investigate their future changes under Shared Socioeconomic Pathways (SSPs). The results show a significant increase in the frequency of compound warm extremes (warm/dry and warm/wet) but a decrease in compound cold extremes (cold/dry and cold/wet) during 1985-2014 relative to 1955-1984. The observed upward trends of compound warm extremes over China are much higher than those worldwide during the period of interest. A multi-model ensemble (MME) of CMIP6 models performs well in simulating temporal changes of warm/wet extremes, and temporal correlation coefficients between MME and observations are above 0.86. Under future scenarios, CMIP6 simulations show substantial rises in compound warm extremes and declines in compound cold extremes. Globally, the average frequency of warm/wet extremes over a 30-yr period is projected to increase for 2070-2099 relative to 1985-2014 by 18.53, 34.15, 48.79, and 59.60 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Inter-model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremes. The projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070-2099 and especially high for the Amazon and the Tibetan Plateau.

The association between extreme temperature and pulmonary tuberculosis in Shandong Province, China, 2005-2016: a mixed method evaluation

BACKGROUND

The effects of extreme temperature on infectious diseases are complex and far-reaching. There are few studies to access the relationship of pulmonary tuberculosis (PTB) with extreme temperature. The study aimed to identify whether there was association between extreme temperature and the reported morbidity of PTB in Shandong Province, China, from 2005 to 2016.

METHODS

A generalized additive model (GAM) was firstly conducted to evaluate the relationship between daily reported incidence rate of PTB and extreme temperature events in the prefecture-level cities. Then, the effect estimates were pooled using meta-analysis at the provincial level. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test.

RESULTS

Among the 446,016 PTB reported cases, the majority of reported cases occurred in spring. The higher reported incidence rate areas were located in Liaocheng, Taian, Linyi and Heze. Extreme low temperature had an impact on the reported incidence of PTB in only one prefecture-level city, i.e., Binzhou (RR = 0.903, 95% CI: 0.817-0.999). While, extreme high temperature was found to have a positive effect on reported morbidity of PTB in Binzhou (RR = 0.924, 95% CI: 0.856-0.997) and Weihai (RR = 0.910, 95% CI: 0.843-0.982). Meta-analysis showed that extreme high temperature was associated with a decreased risk of PTB (RR = 0.982, 95% CI: 0.966-0.998). However, extreme low temperature was no relationship with the reported incidence of PTB.

CONCLUSION

Our findings are suggested that extreme high temperature has significantly decreased the risk of PTB at the provincial levels. The findings have implications for developing strategies to response to climate change.

Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study

To assess YLL and mortality burden attributable to non-optimum ambient temperature, we collected mortality and environmental data from June 1, 2012 to December 30, 2017 in Shenzhen. We applied distributed lag nonlinear models with 21 days of lag to examine temperature-YLL and temperature-mortality associations, and calculated the attributable fractions of YLL and deaths for non-optimum temperature, including four subranges, mild cold, mild heat, extreme cold, and extreme heat. Cold and heat were distinguished by the optimum temperature, and each was separated into extreme and mild by cutoffs at 2.5th (12.2 °C) and 97.5th (30.4 °C) temperature percentile further. The optimum temperature was defined as the temperature that had minimum effect on YLL or mortality risk. The optimum temperature for non-accidental YLL was 24.5 °C, and for mortality it was 25.4 °C. Except for the population older than 65 years, the optimum temperature was generally lower in the YLL model than the mortality model. Of the total 61,576 non-accidental deaths and 1,350,835.7 YLL within the study period, 17.28% (95% empirical CI 9.42-25.14%) of YLL and 17.27% (12.70-21.34%) of mortality were attributable to non-optimum temperature. More YLL was caused by cold (10.14%, 3.94-16.36%) than by heat (7.14%, 0.47-13.88%). Mild cold (12.2-24.5 °C) was responsible for far more YLL (8.78%, 3.00-14.61%) than extreme cold (3.5-12.2 °C). As for cardiovascular deaths, only the fractions attributable to overall and cold temperature were significant, with mild cold contributing the largest fraction to YLL (16.31%, 6.85-25.82%) and mortality (16.08%, 9.77-21.22%). Most of the temperature-related YLL and mortality was attributable to mild but non-optimum weather, especially mild cold, while the YLL model implied a more prominent heat effect on premature death. Our findings can supply additional evidence from multiperspectives for health planners to define priorities and make targeted policies for mitigating the burden of adverse temperatures.

New insights into the immune regulation and tissue repair of Litopenaeus vannamei during temperature fluctuation using TMT-based proteomics

To investigate shrimp immunoregulation and tissue self-repair mechanism during temperature fluctuation stage, Litopenaeus vannamei (L. vannamei) was treated under conditions of gradual cooling from an acclimation temperature (28 °C, C group) to 13 °C (T group) in 2 days with a cooling rate of 7.5 °C/d and then rewarmed to 28 °C (R group) with the same rate. Tandem mass tags (TMT) -based proteomics technology was used to investigate the protein abundance changes of intestine in L. vannamei during temperature fluctuation. The results showed that a total of 5796 proteins with function annotation were identified. Of which, the abundances of 1978 proteins (34%) decreased after cooling and then increased after rewarming, 1498 proteins (26%) increased during the whole stage, 1263 proteins (22%) increased after cooling and then decreased after rewarming and 1057 proteins (18%) decreased during the whole stage. Differentially expressed proteins such as C-lectin, NFκBIA and Caspase may contributed to the regulation of immunity and tissue repair of shrimp intestine during the temperature fluctuation stage. These findings contribute to the better understanding of shrimp' regulatory mechanism against adverse environment.

The immune defense response of Pacific white shrimp (Litopenaeus vannamei) to temperature fluctuation

Temperature is a significant environmental factor contributing to the success of aquaculture. To investigate the immune defense response during temperature fluctuation, Litopenaeus vannamei (L. vannamei) was treated under conditions of gradual cooling from an acclimation temperature of 28 °C (C group) to 13 °C (T group) in 2 days with a cooling rate of 7.5 °C/d and then rewarmed to 28 °C (R group) using the same rate. Relative expression of immune defense system-related genes and intestinal microbial composition in L. vannamei were investigated. The results showed that with a decrease in temperature, the expression of TLR, IMD, proPO and Casp3 in intestine was significantly decreased, while the expression of Muc-3A, Muc-5AC, Muc-17, IAP, p53, HSP70, MT and Fer was significantly increased after cooling. After temperature recovery, gene expression generally showed a trend of recovering to the normal level (C). Intestinal microbial analysis showed that, compared with the C group, the Chao and Ace indexes, the relative abundance of microflora from the Phylum Bacteroidetes, Class Alphaproteobacteria, and Class Bacteroidia, significantly decreased in the R group. The results revealed that cold-stress may decrease microbial community richness, alter the bacterial community in general and reduce shrimp immunity to pathogens and antibacterial activity. As a result, during temperature fluctuation shrimp may mobilize the immune defense system through upregulating the expression of Muc genes, anti-apoptosis related genes, and antioxidant related genes in order to maintain organism homeostasis as well as to repair damaged intestinal tissue.

Extreme Temperature Events during 1960–2017 in the Arid Region of Northwest China: Spatiotemporal Dynamics and Associated Large-Scale Atmospheric Circulation

Studying the dynamic changes of extreme temperatures and associated large-scale atmospheric circulation is important for predicting the occurrence of extreme temperatures and reducing their adverse impact and damage. Based on the surface temperature data sets collected from 87 weather stations over the arid region of Northwest China (ARNC) during 1960–2017, the Sen’s slope estimator, Mann–Kendall test, Cumulative anomaly, Moving t-test, and Synthetic analysis methods were used to analyze the spatiotemporal dynamics and breaking-point change characteristics of extreme temperatures, and to discuss its associated large-scale atmospheric circulation. The results revealed that at the temporal scale, summer days (SU25), warm days (TX90p), warm nights (TN90p), and warm spell duration indicator (WSDI) showed a remarkable increasing trend at the rates of 2.27, 1.49, 3, and 2.28 days/decade, respectively. The frost days (FD), cold days (TX10p), cold nights (TN10p), and cold spell duration indicator (CSDI) significantly decreased at the rates of −3.71, −0.86, −1.77, and −0.76 days/decade, respectively, during the study period. Spatially, the warming trend in the study area is very obvious as a whole, despite pronounced spatial differences in warming rate. After the breakpoint years, the frequency and probability distribution for extreme warm and cold indices were all inclined to the hotter part of the density distribution. This indicates that the climate over the study region shifted sharply and tended to be warmer. The analysis of large-scale atmospheric circulation indicates that the warming trend in the arid region of Northwest China (ARNC) is positively correlated with geopotential height at 500 hPa and negatively correlated with total cloudiness. The findings from this study have important implications for forecasting extreme temperature events and mitigating the impacts of climatological disasters in this region.