Search

Background: Global warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. Methods: CHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index

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

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006–2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030–2039), 2060 s (2060–2069), and 2090 s (2090–2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

ObjectiveTo investigate the prevalence and influencing factors of stroke in residents aged 40 years and older in Guangdong province for developing stroke prevention and control policies. MethodsTotally 21 176 permanent residents aged 40 years and older were recruited with multistage random cluster sampling in urban and rural regions of 5 municipalities in Guangdong province for a survey conducted during July – December 2020. All the participants undertook face-to-face interview with a questionnaire designed by domestic experts, physical examination and laboratory tests. Unconditional multivariate logistic regression model was used to analyze influencing factors of stroke. ResultsAmong 16 993 participants surveyed effectively, 361 stroke sufferers were identified and the crude and age-adjusted stroke prevalence were 2 124.40/100 000 and 1 725.25/100 000, respectively. Multivariate unconditional logistic regression analysis revealed following risk factors of stroke among the participants: ≥ 50 years old, smoking, lack of physical activity, family history of stroke, hypertension, diabetes, dyslipidemia, high homocysteine, and atrial fibrillation or valvular heart disease; while, being female and with an individual annual income of 5 000 – 10 000 or more than 20 000 Chinese yuan were protective factors against stroke. ConclusionThe prevalence of stroke was relatively low and influenced mainly by gender, age, annual personal income, smoking, lack of physical activity, family history of stroke, hypertension, diabetes, dyslipidemia, high homocysteine, atrial fibrillation or valvular heart disease among urban and rural residents aged 40 years and older in Guangdong province.

Background: Although the health impacts of ambient ozone (O3) have been widely assessed, studies simultaneously investigating the acute and chronic effects of O3 on mortality from respiratory diseases (RESP) are scarce. Methods: We extracted personal information of all recorded deaths from RESP throughout 2013–2018 in six provinces in China. The daily, seasonal, and annual mean air pollutant concentrations at the township/subdistrict level were estimated by a random forest model. The acute association between the maximum daily average 8h ozone (MDA8 O3) and RESP mortality was examined by a time-stratified case-crossover study design, and the chronic association was estimated by a difference-in-differences (DID) analysis approach. We also calculated the attributable fraction (AF) of RESP mortality attributable to MDA8 O3. Results: There were 1,034,226 RESP deaths included in this study. The excess risks (ERs) of overall RESP mortality for each 10 μg/m3 increase in short-term (lag03 days) and long-term (one-year average) exposure to MDA8 O3 were 0.38 % (95%CI: 0.26 %, 0.50 %) and 4.37 % (3.91 %, 4.84 %), respectively. The AFs of overall RESP mortality ascribed to short- and long-term MDA8 O3 exposures were 3.00 % (2.03 %, 3.95 %) and 29.45 % (26.86 %, 31.95 %), respectively. The average annual number of RESP deaths attributable to short-term MDA8 O3 exposure was 30,790 and 302,254 were attributable to long-term MDA8 O3 exposure across China during 2013–2018. Conclusion: Both short- and long-term exposure to ambient MDA8 O3 were positively associated with RESP mortality, and long-term exposure to MDA8 O3 may lead to a greater RESP mortality burden than short-term exposure to MDA8 O3.

Abstract Background Globally, coronary artery disease (CAD) and cancer are the leading causes of death. Studies focusing on the proportion and spectrum of cancer mortality among CAD patients are lacking. We aim to characterize the proportion and spectrum of cancer‐specific mortality among patients with CAD. Methods We analyzed 93,797 hospitalized survivors with angiographically documented CAD between 2007 and 2020 (mean age: 62.8 ± 11.1 years, 24.7% female) from Cardiorenal ImprovemeNt II (CIN‐II) cohort. Results During the median follow‐up of 4.8 years (IQR: 2.6–7.5), 13,162 (14.0%) patients died after discharge. A total of 1223/7703 (15.8% of cause‐specific death) CAD patients died of cancer. The three most common types of cancer‐specific death were lung (36.1%), liver (13.3%), and colorectum cancer (12.8%). Furthermore, male (adjusted HR 2.38, 95% CI: 1.99–2.85) and older (≥60 vs.

Abstract Background Among patients with acute coronary syndrome and percutaneous coronary intervention, stress hyperglycemia ratio (SHR) is primarily associated with short-term unfavorable outcomes. However, the relationship between SHR and long-term worsen prognosis in acute myocardial infarction (AMI) patients admitted in intensive care unit (ICU) are not fully investigated, especially in those with different ethnicity. This study aimed to clarify the association of SHR with all-cause mortality in critical AMI patients from American and Chinese cohorts. Methods Overall 4,337 AMI patients with their first ICU admission from the American Medical Information Mart for Intensive Care (MIMIC)-IV database (n = 2,166) and Chinese multicenter registry cohort Cardiorenal ImprovemeNt II (CIN-II, n = 2,171) were included in this study. The patients were divided into 4 groups based on quantiles of SHR in both two cohorts. Results The total mortality was 23.8% (maximum follow-up time: 12.1 years) in American MIMIC-IV and 29.1% (maximum follow-up time: 14.1 years) in Chinese CIN-II. In MIMIC-IV cohort, patients with SHR of quartile 4 had higher risk of 1-year (adjusted hazard radio [aHR] = 1.87; 95% CI: 1.40–2.50) and long-term (aHR = 1.63; 95% CI: 1.27–2.09) all-cause mortality than quartile 2 (as reference). Similar results were observed in CIN-II cohort (1-year mortality: aHR = 1.44; 95%CI: 1.03–2.02; long-term mortality: aHR = 1.32; 95%CI: 1.05–1.66). In both two group, restricted cubic splines indicated a J-shaped correlation between SHR and all-cause mortality. In subgroup analysis, SHR was significantly associated with higher 1-year and long-term all-cause mortality among patients without diabetes in both MIMIC-IV and CIN-II cohort. Conclusion Among critical AMI patients, elevated SHR is significantly associated with and 1-year and long-term all-cause mortality, especially in those without diabetes, and the results are consistently in both American and Chinese cohorts.

Abstract Background Coronary catheterization (CC) procedure inevitably exposes patients with cardiovascular disease (CVD) to radiation, while cumulative radiation exposure may lead to higher risk of cancer. Methods This multi-center, retrospective study was based on the CC procedure in Cardiorenal ImprovemeNt II cohort (CIN-II, NCT05050877) among five regional central tertiary teaching hospitals in China between 2007 and 2020. Patients without known cancer were stratified according to the times they received CC procedure. Baseline information from their last CC procedure was analyzed. Cox regression and Fine-Gray competing risk models were used to assess the relationship between cumulative radiation exposure from CC procedures and cancer-specific, all-cause and cardiovascular mortality. Results Of 136,495 hospitalized survivors without cancer at baseline (mean age: 62.3 ± 11.1 years, 30.9% female), 116,992 patients (85.7%) underwent CC procedure once, 15,184 patients (11.1%) on twice, and 4,319 patients (3.2%) underwent CC procedure more than three times. During the median follow-up of 4.7 years (IQR: 2.5 to 7.4), totally 18,656 patients (13.7%) died after discharge, of which 617 (0.5%) died of lung cancer. Compared with the patients who underwent CC procedure once, the risk of lung cancer mortality increased significantly with the increase of the number of CC procedure (CC 2 times vs. 1 time: HR 1.42, 95% CI 1.13 to 1.78, P

BackgroundAir 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.ObjectiveTo 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.MethodsData 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, PM2.5, 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.ResultsPM2.5, 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 PM2.5, 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 .ConclusionThe 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.

Injury poses heavy burden on public health, but little evidence on the potential role of climate change on injury exists. Here, the authors collect data during 2013-2019 in six provinces of China to estimate the associations between temperature and injury mortality, and to project future mortality burden attributable to temperature change driven by climate change.

BackgroundDrowning is a serious public health problem worldwide. Previous epidemiological studies on the association between meteorological factors and drowning mainly focused on individual weather factors, and the combined effect of mixed exposure to multiple meteorological factors on drowning is unclear. ObjectiveWe aimed to investigate the combined effects of multiple meteorological factors on unintentional drowning mortality in China and to identify the important meteorological factors contributing to drowning mortality. MethodsUnintentional drowning death data (based on International Classification of Diseases, 10th Edition, codes W65-74) from January 1, 2013, to December 31, 2018, were collected from the Disease Surveillance Points System for Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces, China. Daily meteorological data, including daily mean temperature, relative humidity, sunlight duration, and rainfall in the same period were obtained from the Chinese Academy of Meteorological Science Data Center. We constructed a time-stratified case-crossover design and applied a generalized additive model to examine the effect of individual weather factors on drowning mortality, and then used quantile g-computation to estimate the joint effect of the mixed exposure to meteorological factors. ResultsA total of 46,179 drowning deaths were reported in the 5 provinces in China from 2013 to 2018. In an effect analysis of individual exposure, we observed a positive effect for sunlight duration, a negative effect for relative humidity, and U-shaped associations for temperature and rainfall with drowning mortality. In a joint effect analysis of the above 4 meteorological factors, a 2.99% (95% CI 0.26%-5.80%) increase in drowning mortality was observed per quartile rise in exposure mixture. For the total population, sunlight duration was the most important weather factor for drowning mortality, with a 93.1% positive contribution to the overall effects, while rainfall was mainly a negative factor for drowning deaths (90.5%) and temperature and relative humidity contributed 6.9% and –9.5% to the overall effects, respectively. ConclusionsThis study found that mixed exposure to temperature, relative humidity, sunlight duration, and rainfall was positively associated with drowning mortality and that sunlight duration, rather than temperature, may be the most important meteorological factor for drowning mortality. These findings imply that it is necessary to incorporate sunshine hours and temperature into early warning systems for drowning prevention in the future.

Although studies have estimated the associations of PM2.5 with total mortality or cardiopulmonary mortality, few have comprehensively examined cause-specific mortality risk and burden caused by ambient PM2.5. Thus, this study investigated the association of short-term exposure to PM2.5 with cause-specific mortality using a death-spectrum wide association study (DWAS). Individual information of 5,450,764 deaths during 2013–2018 were collected from six provinces in China. Daily PM2.5 concentration in the case and control days were estimated by a random forest model. A time-stratified case-crossover study design was applied to estimate the associations (access risk, ER) of PM2.5 with cause-specific mortality, which was then used to calculate the population-attributable fraction (PAF) of mortality and the corresponding mortality burden caused by PM2.5. Each 10 μg/m3 increase in PM2.5 concentration (lag03) was associated with a 0.80 % [95 % confidence interval (CI): 0.73 %, 0.86 %] rise in total mortality. We found greater mortality effect at PM2.5 concentrations

Properly analyzing and reporting data remains a challenging task in epidemiologic research, as underreporting of data is often overlooked. The evaluation on the effect of underreporting remains understudied. In this study, we examined the effect of different scenarios of mortality underreporting on the relationship between PM10, temperature, and mortality. Mortality data, PM10, and temperature data in seven cities were obtained from Provincial Center for Disease Control and Prevention (CDC), China Meteorological Data Sharing Service System, and China National Environmental Monitoring Center, respectively. A time-series design with a distributed lag nonlinear model (DLNM) was used to examine the effects of five mortality underreporting scenarios: 1) Random underreporting of mortality; 2) Underreporting is monotonically increasing (MI) or monotonically decreasing (MD); 3) Underreporting due to holiday and weekends; 4) Underreporting occurs before the 20th day of each month, and these underreporting will be added after the 20th day of the month; and 5) Underreporting due to holiday, weekends, MI, and MD. We observed that underreporting at random (UAR) scenario had little effect on the association between PM10, temperature, and daily mortality. However, other four underreporting not at random (UNAR) scenarios mentioned above had varying degrees of influence on the association between PM10, temperature, and daily mortality. Additionally, in addition to imputation under UAR, the variation of minimum mortality temperature (MMT) and attributable fraction (AF) of mortality attributed to temperature in the same imputation scenarios is inconsistent in different cities. Finally, we observed that the pooled excess risk (ER) below MMT was negatively associated with mortality and the pooled ER above MMT was positively associated with mortality. This study showed that UNAR impacted the association between PM10, temperature, and mortality, and potential underreporting should be dealt with before analyzing data to avoid drawing invalid conclusions.

BackgroundStroke has become a main cause of death in China. With global warming, the studies on temperature and stroke have attracted much attention.ObjectiveTo 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.MethodsThe 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 (

BackgroundIn 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.ObjectiveBased on the data of Guangdong Province, to investigate the effect of temperature on MS and its pathway.MethodsA 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.ResultsThe 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.ConclusionThere 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.

BackgroundIt is projected that the frequency, density, and duration of compound hot extreme may increase in the 21st century in the context of global warming.ObjectiveTo explore the association between compound hot extreme and blood pressure, and identify sensitive populations.MethodsThis 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.ResultA 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].ConclusionCompound 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: 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. Methods: 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. Results: 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. Conclusion: 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.

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.

Drowning is a major public health problem and a leading cause of death in children living in developing countries. We seek better machine learning (ML) algorithms to provide a novel risk-assessment insight on non-fatal drowning prediction. The data on non-fatal drowning were collected in Qingyuan city, Guangdong Province, China. We developed four ML models to predict the non-fatal drowning risk, including a logistic regression model (LR), random forest model (RF), support vector machine model (SVM), and stacking-based model, on three primary learners (LR, RF, SVM). The area under the curve (AUC), F1 value, accuracy, sensitivity, and specificity were calculated to evaluate the predictive ability of the different learning algorithms. This study included a total of 8390 children. Of those, 12.07% (1013) had experienced non-fatal drowning. We found the following risk factors are closely associated with the risk of non-fatal drowning: the frequency of swimming in open water, distance between the school and the surrounding open waters, swimming skills, personality (introvert) and relationality with family members. Compared to the other three base models, the stacking generalization model achieved a superior performance in the non-fatal drowning dataset (AUC = 0.741, sensitivity = 0.625, F1 value = 0.359, accuracy = 0.739 and specificity = 0.754). This study indicates that applying stacking ensemble algorithms in the non-fatal drowning dataset may outperform other ML models.

Abstract Background Drowning is a leading cause of accidental death in children under 14 years of age in Guangdong, China. We developed a statistical model to classify the risk of drowning among children based on the risk factors. Methods A multiple-stage cluster random sampling was employed to select the students in Grades 3 to 9 in two townships in Qingyuan, Guangdong. Questionnaire was a self-reported measure consisting of general information, knowledge, attitudes and activities. A univariate logistic regression model was used to preliminarily select the independent variables at a P value of 0.1 for multivariable model. Three-quarters of the participants were randomly selected as a training sample to establish the model, and the remaining were treated as a testing sample to validate the model. Results A total of 8390 children were included in this study, about 12.18% (1013) experienced drowning during the past one year. In the univariate logistic regression model, introvert personality, unclear distributions of water areas on the way to school, and bad relationships with their classmates and families were positively associated with drowning. However, females, older age and lower swimming skills were negatively associated with drowning. After employing the prediction model with these factors to estimate drowning risk of the students in the testing samples, the results of Hosmer-Lemeshow tests showed non-significant differences between the predictive results and actual risk (χ2 = 5.97, P = 0.65). Conclusions Male, younger children, higher swimming skills, bad relationship with their classmates and families, introvert personality and unclear distributions of water areas on the way to school were important risk factors of non-fatal drowning among children. The prediction model based on these variables has an acceptable predictive ability.

Abstract Background As the fourth leading cause of death, injury is an important public health concern in Guangdong Province, China. The epidemiological characteristics of injury mortality is changing along with the social development. This study described the epidemiological characteristics of injury mortality in Guangdong Province by analyzing the death surveillance data in a few areas in Guangdong Province in 2015. Methods Using the mortality data from the Disease Surveillance Points (DSP) system, injury deaths were classified according to the International Classification of Disease-10th Revision (ICD-10). The data were stratified by areas (urban/rural), gender, age groups, injury types, and then overall and type-specific injury mortality rates were estimated for the whole Guangdong Province, China. Results We estimated that about 38,200 individuals died from injury in Guangdong Province in 2015, producing a mortality rate of 43.11/100,000. The overall age-standardized injury mortality in men was higher in rural areas compared with urban areas (41.29/100,000 versus 24.89/100,000). In terms of injury intent, unintentional injuries were the commonnest injury type, which accounted for 83.93% of the overall injury deaths, however, the deaths caused by suicide should not be ignored, which occupied 12.67% of the total injury deaths. In terms of injury cause type, falls, road-traffic accidents, suicide, drowning, and accidental poisoning were the top five leading types of injury deaths. Conclusions In Guangdong Province, injury is an important cause of death. Road-traffic accidents, falls, suicide, drowning, and accidental poisoning should be the priorities of intervention. Moreover, in rural areas, the men were the most targeted subpopulation of the prevention activities.

In this work, we investigate the effect of sidewall angle, height and space of an air cavity extractor (AC-Extractor) on the polarization-dependent light extraction efficiency (LEE) for AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) using three-dimensional finite difference time-domain method. Compared to the reported inclined sidewall metal reflector (SM-Reflector), DUV LED with AC-Extractor shows better light extraction at any height and inclined angle due to different light extraction mechanisms. The light in SM-Reflector DUV LED is extracted mainly through mirror reflection. However, total internal reflection from the sidewall dominants the contribution to LEE for the AC-Extractor with smaller inclined angle such that the space has little impact, while Fresnel scattering is more important for the AC-Extractor with larger inclined angle and that the additional out-light channel as well as the space play a critical role in enhancing the LEE. And the analysis is further developed into a three-escape-cones analytic model theory. In particular, the AC-Extractor with vertical sidewall is more beneficial to enhance the LEE of DUV LED than that with inclined sidewall, which can be rationally explained based on the three-escape-cones analytic model.

An inclined sidewall scattering structure with air cavity characterized by a metal bottom and flat parallel top (Bottom_metal) is proposed to enhance the light extraction efficiency (LEE) for AlGaN-based deep ultraviolet light-emitting diodes (DUV LEDs). Compared to the reported sidewall metal inclined sidewall (Sidewall_metal) structure, the Bottom_metal structure can greatly enhance the LEE of DUV LEDs based on three-dimensional finite difference time domain simulations. Further analysis indicates that the existence of the air cavity promotes the Bottom_metal DUV LEDs to mainly utilize the total internal reflection and the Fresnel scattering to scatter the light into the escape cone, which avoids the light absorption from the sidewall metal mirror in the Sidewall_metal structure. Moreover, the unique air cavity having a bottom metal also enhances the scattering ability of the Bottom_metal DUV LEDs because any light within the cavity directing downward will be reflected back, and the parallel top interface of air cavity/AlGaN functions as additional out-light planes not limited by total internal reflection.

β-Ga2O3, characterized with high n-type conductivity, little lattice mismatch with III-Nitrides, high transparency (>80%) in blue, and UVA (400–320 nm) as well as UVB (320–280 nm) regions, has great potential as the substrate for vertical structure blue and especially ultra violet LEDs (light emitting diodes). Large efforts have been made to improve the quality of III-Nitrides epilayers on β-Ga2O3. Furthermore, the fabrication of vertical blue LEDs has been preliminarily realized with the best result that output power reaches to 4.82 W (under a current of 10 A) and internal quantum efficiency (IQE) exceeds 78% by different groups, respectively, while there is nearly no demonstration of UV-LEDs on β-Ga2O3. In this review, with the perspective from materials to devices, we first describe the basic properties, growth method, as well as doping of β-Ga2O3, then introduce in detail the progress in growth of GaN on (1 0 0) and (−2 0 1) β-Ga2O3, followed by the epitaxy of AlGaN on gallium oxide. Finally, the advances in fabrication and performance of vertical structure LED (VLED) are presented.