Background Injury poses a serious threat to human health. As global warming continues to intensify, there is an urgent need to explore the impact of temperature changes on injury deaths. However limited research has focused on this issue. Objective To investigate the relationship between daily mean temperature change (Tm) and injury death, as well as to estimate the associated future death burden in Hunan Province. Methods We employed an individual-level, time-stratified case-crossing design to establish a conditional logistic regression model to analyze the exposure-response relationship between daily mean temperature change and injury death in Hunan Province from 2013 to 2018. Consequently, we conducted subgroup analysis of gender, age group, and injury type. Finally, we estimated the excess burden of injury death attributable to temperature changes under a sustainable development path [low emission scenario (SSP1-2.6)], regional competition path [high emission scenario (SSP3-7.0)], or fossil fuel development path [very high emission scenario (SSP5-8.5)]. Results The study collected 155577 injury deaths in Hunan Province. The results indicated that for each 1 ℃ increment in daily mean temperature, the cumulative excess risk (CER) of injury mortality among Hunan residents increased by 0.71% (95%CI: 0.53%, 0.90%). Notably, the CER for intentional injuries (1.06%, 95%CI: 0.51%, 1.61%) was higher than that for unintentional injuries (0.66%, 95%CI: 0.46%, 0.87%). Warmer temperatures were positively associated with CER of mortality due to drowning, falls, transport injuries, assaults, and suicides, while they were negatively associated with mortality due to poisoning. Compared with 2010–2019, for 2090–2099, the excess mortality rate (EMR) due to ambient temperature increase in Hunan Province under the SSP5-8.5 scenario (14.62/100000, 95%CI: 10.81/100000, 18.40/100000) would be higher than that of the SSP3-7.0 scenario (10.28/100000, 95%CI: 7.58/100000, 12.97/100000) and the SSP1-2.6 scenario (3.35/100000, 95%CI: 2.46/100000, 4.23/100000); the EMR would be around 2.5 times among men (20.64/100000, 95%CI: 14.44/100000, 26.8/100000) than that among women (8.33/100000, 95%CI: 3.98/100000, 12.6/100000). Among unintentional injuries, the leading contributors to EMR would be drowning (4.46/100000), falls (3.96/100000), and transport injuries (2.96/100000). And among intentional injuries, the EMR for suicide (2.08/100000) would be higher than that for assault (0.47/100000). Conclusion Climate warming will increase the total burden of injury-related deaths among residents in Hunan Province, especially in the absence of effective mitigation strategies and measures. It is necessary to strengthen the prevention and control of severe injuries closely related to temperature changes, such as drowning, falls, traffic, and suicides injuries, in order to reduce injury deaths associated with climate change.

In the context of rapid global aging, the number of vulnerable elderly individuals who are sensitive to climate change and air pollution is increasing rapidly, potentially augmenting the burden of related diseases. The intrinsic capacity (IC) of the elderly refers to the comprehensive ability of individuals in physical, cognitive, and mental health aspects, typically encompassing 5 dimensions: cognitive status, motor ability, mental health, sensory function, and vitality. This article reviewed the advancements in epidemiological research on the effects of air pollution and climate change (including meteorological factors) on the overall intrinsic capacity of the elderly and its various dimensions. The results indicated that pollutants such as fine particulate matter (PM_2.5) and ozone (O₃) are most significantly associated with the decline in the cognitive function and vitality dimensions, and extreme meteorological events like high temperatures are also related to the functional deterioration of each dimension of IC. Nevertheless, the current studies mostly focus on the impact of atmospheric environmental factors on a specific dimension of IC rather than on overall IC, and research on the combined exposure to multiple atmospheric factors is even rarer, and the exploration of associated mechanisms is insufficient. Future research should enhance the investigation of the influence and mechanism of the combined exposure to air pollution and climate change on the dynamic changes of IC, and promote multi-center research and transnational cooperation. This review is conducive to clarifying the potential impact of atmospheric environmental factors on the IC of the elderly, providing a scientific basis for formulating health intervention policies to address climate change and air pollution.

Climate change has led to an increasing frequency and intensity of extreme climate events such as heat and drought extremes with considerable global public health burden. This systematic review collected 87 domestic and international studies from 2000 to 2023, considering the impacts of heat extremes, drought extremes, and compound hot-dry events on infectious diseases attributable to various transmission pathways such as waterborne, foodborne, insect-borne, airborne, and contact-transmitted diseases. Our results showed that high temperature was associated with increased transmission risks of waterborne and foodborne diseases including infectious diarrheal diseases (cholera, dysentery, typhoid, and paratyphoid) and infectious gastroenteritis; vector-borne diseases including dengue fever, Zika virus (ZIKV) disease, chikungunya fever, malaria, West Nile fever, and Rift Valley fever; airborne diseases including influenza-like diseases, influenza A, measles, and mumps; and contact-transmitted diseases including HIV/AIDS, schistosomiasis, and leptospirosis. Additionally, drought conditions also amplified the transmission risks of waterborne and foodborne diseases including cholera, Escherichia coli infection, rotavirus infection, and hepatitis E; vector-borne diseases such as scrub typhus, schistosomiasis, hemorrhagic fever with renal syndrome, and West Nile fever; airborne diseases including meningococcal meningitis, pertussis, measles, and upper respiratory infections; and contact-transmitted diseases such as HIV/AIDS. Along with global warming, the frequency of compound high temperature and drought events shows a considerably increasing trend, causing more adverse health effects than heat or drought alone. However, there is limited research quantifying their effects on infectious diseases. These associations may be mediated through temperature and precipitation on infectious disease pathogens, transmission vectors, population susceptibility, public health services, and behaviors. In the context of climate change, the increasing occurrence of compound events of high temperatures and droughts raises health concerns, and further studies are needed to enhance our understanding of the impacts of climate change on infectious diseases and improve human adaption to climate change.

Drought is expected to be more severe and frequent due to climate change. Drought exerts not only extensive impacts on economy and environment, but also direct or indirect impacts on human health. This review systematically collected studies exploring the association between drought and human mortality, and summarized the associations between drought and all-cause mortality, chronic non-communicable disease mortality, communicable disease mortality, and injury mortality. The results revealed that drought was significantly associated with human mortality, leading to an elevated mortality risk of cardiovascular diseases, respiratory diseases, cancers, diarrhea, and injuries; serious drought increased much more mortality risk than mild drought; males in rural areas, the elderly, and children were vulnerable populations to drought. However, in-depth studies on the association of drought with human mortality are limited, which calls for related studies in the future. This review summarized the current research status and existing problems in drought and population death, and pointed out the future research direction, which can provide reference for future related research.

Background Air pollution is a major public health concern. Air Quality Health Index (AQHI) is a very important air quality risk communication tool. However, AQHI is usually constructed by single-pollutant model, which has obvious disadvantages. Objective To construct an AQHI based on the joint effects of multiple air pollutants (J-AQHI), and to provide a scientific tool for health risk warning and risk communication of air pollution. Methods Data on non-accidental deaths in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces from January 1, 2013 to December 31, 2018 were obtained from the corresponding provincial disease surveillance points systems (DSPS), including date of death, age, gender, and cause of death. Daily meteorological (temperature and relative humidity) and air pollution data (SO₂, NO₂, CO, PM_2.5, PM₁₀, and maximum 8 h O₃ concentrations) at the same period were respectively derived from China Meteorological Data Sharing Service System and National Urban Air Quality Real-time Publishing Platform. Lasso regression was first applied to select air pollutants, then a time-stratified case-crossover design was applied. Each case was matched to 3 or 4 control days which were selected on the same days of the week in the same calendar month. Then a distributed lag nonlinear model (DLNM) was used to estimate the exposure-response relationship between selected air pollutants and mortality, which was used to construct the AQHI. Finally, AQHI was classified into four levels according to the air pollutant guidance limit values from World Health Organization Global Air Quality Guidelines (AQG 2021), and the excess risks (ERs) were calculated to compare the AQHI based on single-pollutant model and the J-AQHI based on multi-pollutant model. Results PM_2.5, NO₂, SO₂, and O₃ were selected by Lasso regression to establish DLNM model. The ERs for an interquartile range (IQR) increase and 95% confidence intervals (CI) for PM_2.5, NO₂, SO₂ and O₃ were 0.71% (0.34%–1.09%), 2.46% (1.78%–3.15%), 1.25% (0.9%–1.6%), and 0.27% (−0.11%–0.65%) respectively. The distribution of J-AQHI was right-skewed, and it was divided into four levels, with ranges of 0-1 for low risk, 2-3 for moderate risk, 4-5 for high health risk, and ≥6 for severe risk, and the corresponding proportions were 11.25%, 64.61%, 19.33%, and 4.81%, respectively. The ER (95%CI) of mortality risk increased by 3.61% (2.93–4.29) for each IQR increase of the multi-pollutant based J-AQHI , while it was 3.39% (2.68–4.11) for the single-pollutant based AQHI . Conclusion The J-AQHI generated by multi-pollutant model demonstrates the actual exposure health risk of air pollution in the population and provides new ideas for further improvement of AQHI calculation methods.

In the context of global warming, the frequency, intensity, and duration of heatwaves will further increase. In recent years, plenty of studies have suggested from diversiform perspectives that heatwaves may increase mortality risk. However, the focuses of current studies on heat wave and human health are scattered, and a systematic theoretical framework has not yet been formed. We therefore systematically reviewed the previous literature in terms of possible mechanism paths and vulnerability mechanism of heatwave increasing mortality risk, summarized the vulnerability factors that influence exposure opportunities, constrain adaptive capacity, as well as affect physiological responses and behaviors. We further attempted to propose a theoretical framework from the processes of "exposure degree-modification effect-physiological behavior-health outcome". This paper summarized the research directions on heatwaves and health, which can provide ideas for future in-depth health risk assessment and adaptation to climate change.

Background It is projected that the frequency, density, and duration of compound hot extreme may increase in the 21st century in the context of global warming. Objective To explore the association between compound hot extreme and blood pressure, and identify sensitive populations. Methods This was a cross-sectional study. The study subjects were from six Guangdong Province Chronic Disease and Nutrition Surveys during 2002 through 2015. A questionnaire was administered to the participants with questions about demographic information, drinking and smoking status, and measurements on their height, weight, and blood pressure were also collected. We chose the data of May, September, and October to explore the association between compound hot extreme and blood pressure. Compound hot extreme means a hot day with a proceeding hot night. Daily meteorological data were obtained from China Meteorological Data Service Centre. We employed inverse distance weighting to interpolate the temperature and relative humidity values for each participant. A distributed lag non-linear model was used to estimate the association between compound hot extreme and blood pressure. Stratified analyses by sex, age, area, body mass index (BMI), smoking status, and drinking status were also performed to identify sensitive populations. A sensitivity analysis was conducted by adjusting the degrees of freedom for lag spline and removing relative humidity. Result A total of 10967 participants without history of hypertension were included in this study. The average systolic blood pressure (SBP) was 120.8 mmHg and the average diastolic blood pressure (DBP) was 74.5 mmHg. The proportion of participants who experienced hot day, hot night, or compound hot extreme were 9.34%, 17.95% and 2.90%, respectively. Compared to hot day, hot night and compound hot extreme were related with decreased blood pressure, and the effect of compound hot extreme was stronger: the changes and 95%CI for SBP was −6.2 (−10.3-−2.1) mmHg, and for DBP was −2.7 (−5.2-−0.2) mmHg. Compound hot extreme induced decreased SBP among male, population ≥ 65 years, and those whose BMI < 24 kg·m^-2, and their ORs (95%CIs) were −6.2 (−10.7-−1.6). −19.1 (−33.0-−5.1), and −6.7 (−11.8~−1.6) mmHg, respectively, and also decreased DBP among population ≥ 65 years, and its OR (95%CI) was −8.4 (−15.6-−1.1) mmHg. During compound hot extremes, participants living in rural areas showed decreased SBP and DBP, and the ORs (95%CIs) were −10.5 (−16.6-−4.5) and −4.4 (−7.7-−1.1) mmHg respectively, while those living in urban areas showed increased SBP, and the OR (95%CI) was 9.7 (2.9-16.5) mmHg. A significant decrease in blood pressure [OR (95%CI)] was also found in non-smokers [DBP, −3.7 (−6.6-−0.8) mmHg] and non-drinkers [SBP, −4.8 (−9.4-−0.2) mmHg; DBP, −3.4 (−6.0-−0.9) mmHg]. Conclusion Compound hot extreme is negatively associated with SBP, and being male, aged 65 years and over, and having BMI < 24 kg·m⁻² may be more sensitive to compound hot extreme.

Background In recent years, the incidence of metabolic syndrome (MS) is increasing significantly in China. Some studies have found that temperature is related to single metabolic index, but there is a lack of research on associated mechanism and identifying path of the influence of temperature on MS. Objective Based on the data of Guangdong Province, to investigate the effect of temperature on MS and its pathway. Methods A total of 8524 residents were enrolled by multi-stage random sampling from October 2015 to January 2016 in Guangdong. Basic characteristics, behavioral characteristics, health status, and physical activity level were obtained through questionnaires and physical examinations, and meteorological data were obtained from meteorological monitoring sites. We matched individual data both with the temperature data of the physical examination day and of a lag of 14 d. A generalized additive model was used to explore the exposure-effect relationship between temperature and MS and its indexes, calculate effect values, and explore the effects of single-day lag temperature. Based on the literature and the results of generalized additive model analysis, a path analysis was conducted to explore the pathways of temperature influencing MS. Results The association between daily average temperature on the current day or lag 14 day and MS risk was not statistically significant. When daily average temperature increased by 1 ℃, the change values of fasting blood-glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), and high density lipoprotein cholesterol (HDL-C) were −0.033 (95%CI: −0.040-−0.026) mmol·L⁻¹, −0.662 (95%CI: −0.741-−0.583) mmHg, −0.277 (95%CI: −0.323-−0.230) mmHg, and −0.005 (95%CI: −0.007-−0.004) mmol·L⁻¹ respectively. The effects of average daily temperature on FBG, blood pressure, HDL-C, and waist circumference lasted until lag 14 day. The effects of daily average temperature on SBP and DBP were the largest on the current day. Daily average temperature of current day had direct and indirect effects on FBG and SBP. Temperature had an indirect effect on TG, and the intermediate variables were waist circumference and FBG, with an indirect effect value of −0.011 (95%CI: −0.020-−0.002). The indirect effects of daily average temperature on SBP, FBG, and TG were weak. Conclusion There is no significant correlation between temperature and risk of MS, and daily average temperature of current day could significantly affected blood pressure and FBG with a lag effect. Daily average temperature of current day has indirect effects on FBG and TG.

Background Stroke has become a main cause of death in China. With global warming, the studies on temperature and stroke have attracted much attention. Objective To analyze he relationships between heatwave and the years of life lost (YLL) by different subtypes of stroke by controlling temporal and spatial effects with Bayesian spatio-temporal model, and to study the modifiers of the health effect of heatwave. Methods The daily information of stroke deaths, meteorological data, and air pollutant data in 40 districts and counties of Guangdong Province were collected during the warm seasons (from May to October) in the years from 2014 to 2017. The individual YLL was first calculated by matching age and gender according to the life table, and then the daily YLL rate (person-years/100 000 people) was obtained by summarizing the daily YLL and correcting it with the population of each district or county. Bayesian spatio-temporal model was used to fit a proposed exposure-response relationship between heatwave and the YLL rates of different subtypes of stroke. Finally, stratified analyses were conducted by age (<65 years, ≥65 years), gender (male, female), and region (Pearl River Delta and non-Pearl River Delta regions) to identify the major modifiers for the association between heatwave and stroke mortality. Results During the warm seasons from 2014 to 2017, a total of 23 heatwave events occurred in the 40 districts or counties of Guangdong Province, cumulatively lasting for 145 d. A total of 30 852 stroke deaths were recorded in the same time periods. The average daily YLL rate of total stroke was (2.39±3.63) person-years/100 000 people, and those for hemorrhagic stroke and ischemic stroke were (1.54±2.99) person-years/100 000 people and (0.84±1.85) person-years/100 000 people, respectively. Heatwave was associated with increased YLL rate of stroke in residents, and it had a greater impact on ischemic stroke with a lag effect. The largest cumulative effect of heatwave was at lag 0-1 day, which was associated with an increased YLL rate of total stroke and ischemic stroke by 0.17 (95%CI: 0.03-0.29) person-years/100 000 people and 0.13 (95%CI: 0.06-0.20) person-years/100 000 people, respectively. The results of stratified analyses showed that heatwave had a larger effect on ischemic stroke in residents of aged 65 years or older, male, and non-Pearl River Delta regions, and the rates of YLL increased by 1.11 (95%CI: 0.58-1.55), 0.13 (95%CI: 0.03-0.23), and 0.20 (95%CI: 0.07-0.32) person-years/100 000 people, respectively; Heatwave only had an effect on hemorrhagic stroke in residents aged 65 years or older with an increased YLL rate of 0.79 (95%CI: 0.26-1.31) person-years/100 000 people. Conclusion Heatwave could elevate the level of years of life lost associated with stroke in Guangdong residents, with greater impacts on ischemic stroke of the aged, men, and residents in non-Pearl River Delta regions, and on hemorrhagic stroke in the elderly.

Background Global warming may increase the frequency of compound hot extreme (CHE).However, there is still a lack of studies assessing the associations between CHE and preterm birth (PTB), and the underlying biological mechanisms remain unclear. Objective To estimate the association of exposure to CHE during pregnancy with PTB, and to explore the roles of inflammatory, endothelial dysfunction, and oxidative stress in the association between CHE and PTB. Methods All participants were selected from the Prenatal Environments and Offspring Health (PEOH), a prospective birth cohort conducted in Guangzhou. In this study, a total of 2449 participants who gave birth from May to October in 2014 to 2017 were enrolled, and among them blood samples were collected from 311 preterm (n=43) and full-term (n=268) pregnant women at the time of delivery. A hot day/night was identified as a day when the daily maximum temperature/minimum temperature was higher than its 90th percentile in the study period, and a CHE was defined as having both a hot night and a following hot day. The meteorological data were obtained from the China Meteorological Data Sharing Service System. Anusplin was used to assess the daily maximum temperature, daily minimum temperature, and relative humidity of the participant residence. Enzyme-linked immunosorbent assay (ELISA) was used to measure C reactive protein (CRP), endothelin-1 (ET-1), and malondialdehyde (MDA) levels in maternal serum, and their results were transformed by natural logarithm. A distributed lag nonlinear model was used to investigate the associations of exposures to hot day, hot night, and CHE during pregnancy with PTB at different lag days, and a logistic regression model was used to investigate the associations of CRP, ET-1, and MDA with PTB. Results The incidence rate of PTB was 6.2% in all selected participants. Compared with the non-hot day, the RRs (95%CIs) of CHE in lag 3, 7, and 14 days on PTB were 1.43 (1.12-1.84), 1.24 (1.08-1.43), and 1.17 (1.05-1.30), respectively, and the cumulative effects (% difference) (95%CI) of CHE in lag 14 days on maternal serum CRP, ET-1, and MDA were 0.33% (−0.45%-1.12%), 0.59% (0.11%-1.07%), and 0.57% (0.09%-1.05%), respectively. Compared with the Q1 (lowest quartile) for CRP, ET-1 and MDA, the RRs (95%CIs) of Q4 (highest quartile) for PTB were 1.27 (0.50-3.22), 1.51 (0.61-3.72), and 2.07(0.81-5.27), respectively. Conclusion Maternal exposure to CHE during pregnancy might be associated with an increased risk of PTB. Prenatal exposure to CHE is positively associated with maternal serum CRP, ET-1, and MDA, and the three biochemical indicators are also positively associated with PTB. However, the above conclusions still need further confirmation.