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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, 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. Results PM2.5, 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 . 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.
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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.
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Background Climate change has resulted in long-term impacts on human health. Implementing efficient adaptation strategies among primary healthcare facilities is well determined by whether staff of different genders recognize the health risks related to climate change and are willing to take active measures. Objective To investigate gender differences on perceptions of health risks and attitude towards adaptation strategies among primary healthcare workers in China, and provide relevant suggestions. Methods By adopting a multi-stage cluster sampling method, we selected 21 urban and 10 rural healthcare facilities in Guangdong Province to collect information with a questionnaire. Then chi-square test, Wilcoxon rank sum test, and logistic regression analysis were used to explore the gender differences in climate change-related health risk cognition, knowledge acquisition channels, attitudes towards adaptation strategies, main obstacles, and resource requirements among the healthcare workers. Results Of 733 participants, 38.47% (282 participants) were male and 61.53% (451 participants) were female. The percentages of male healthcare workers who agreed that climate change is happening and recognized the causes of climate change (70.21%, 60.99%) were higher than the percentages of female counterparts (59.87%, 49.00%) (both Ps＜0.05), but no obvious gender differences existed in recognizing health risks of heatwaves and infectious diseases as well as sensitive population identification (all Ps＞0.05). Most of the participants (92.50%) received climate change and health-related information from mass media like TV, radio, and newspapers. Meanwhile less men chose new media channels than women (OR=0.62, 95%CI∶ 0.41-0.94). Only 30.56% of the participants (33.69% of men and 28.60% of women) reported involvement of relevant training and lectures. Most of them (90.96%) agreed to take active measures to deal with the health threats associated with climate change without gender differences for various measures (all Ps＞0.05). The leading obstacles were hard to integrate health adaptation to climate change into main work of institutions (most female agreed, 72.28%) and the lack of funds (most male agreed, 77.66%). Increasing funding for primary health care was regarded as the most needed resource by male (86.88%) and female (89.14%). After controlling the influence of other social factors, more men agreed with the lack of funds than women (OR=1.57, 95%CI∶ 1.10-2.24). Conclusion There are some gender differences in the perceptions of health risks and adaptation strategies of climate change among primary healthcare workers: Male staff are more likely to agree with climate change and regard the lack of funds as the main obstacle, while women prefer to choose new media channels to obtain information. It’s suggested that the government and relevant institutions focus on the learning and training of climate change and health-related knowledge and expand diversified information access, and promote capacity building to cope with health threats at grass-root level, in the light of recognized gender differences among primary healthcare workers.
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Background Dengue fever is a mosquito-borne disease transmitted by Aedes aegypti and Aedes albopictus. Under the background of climate change, there are great challenges in the prevention and control of dengue fever, posing a serious health risk to the population. Objective To analyze the mechanism of temperature on dengue fever transmission and estimate the risk of dengue fever under different climate change scenarios by establishing a coupled human-mosquito dynamics model using Guangzhou as a research site, and to provide reference for adaptation to climate change. Methods Reported dengue fever cases and meteorological data from January 1, 2015 to December 31, 2019 in Guangzhou were collected from Guangdong Provincial Center for Disease Control and Prevention and China Meteorological Data Service Centre, respectively. The temperature data under three Representative Concentration Pahtyway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2030s (2031–2040), 2060s (2061–2070), and 2090s (2091–2099) were calculated by five general circulation models (GCMs) provided by the fifth phase of the Coupled Model Intercomparison Project. A dengue fever transmission dynamics (ELPSEI-SEIR) model was constructed to analyze the mechanism of temperature affecting dengue fever transmission by fitting the dengue fever epidemic trend from 2015–2019, and then the daily mean temperature under selected RCP scenarios for 2030s, 2060s, and 2090s was incorporated into the established dynamics model to predict the risk of dengue fever under different climate change scenarios in the future. Results From January 1, 2015 to December 31, 2019, a total of 4 234 cases of dengue fever were reported in Guangzhou, including 3741 local cases and 493 imported cases. The regression results showed that the model well fitted the dengue fever cases in Guangzhou from 2015 to 2019, and the coefficient of determination R2 to evaluate goodness of fit and the root mean squared error were 0.82 and 1.96, respectively. A U-shaped or inverted U-shaped relationship between temperature and mosquito habits could directly affect the number of mosquitoes and the transmission of dengue fever. We also found that temperature increase in most future scenarios could promote the transmission of dengue fever, and the epidemic period was significantly wider than the baseline stage. The epidemic of dengue fever would peak in the 2060s under the scenarios of RCP2.6 and RCP4.5. The estimated incidence of dengue fever was predicated to be highest in the 2030s and then decrease in the following years under RCP8.5, and in the 2090s, the incidence would decrease significantly, but the incidence peak would be earlier in each year, mainly from May to July. Conclusion Temperature can directly affect mosquito population and dengue fever transmission by affecting mosquito habits. The cases of dengue fever will increase under most climate scenarios in the future. However, the epidemic risk of dengue fever may be suppressed, and the epidemic season may be advanced under RCP8.5.
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Background Climate change leads to frequent heavy rainfall events, and higher incidences of bacillary dysentery after heavy rainfall have been observed. The impacts of heavy rainfall and its antecedent rainfall conditions on the disease are worth paying attention to. Objective To quantitatively analyze how the relationship between heavy rainfall events and bacillary dysentery occurrence is modified by antecedent rainfall conditions in Anhui Province and explore the different moderation effects in urban and rural contexts. Methods CN05.1 meteorological data of Anhui Province and cases of bacillary dysentery of the same area were collected from January 1, 2006 to August 31, 2017. An exposure-response Poisson regression model of heavy rainfall events and the number of daily cases was constructed to explore the moderation effect of antecedent rainfall conditions on the incidence of bacillary dysentery, and further stratified by urban and rural areas. Results This study included 129 459 cases of bacillary dysentery, with a daily average of 30.39. Compared with dry antecedent conditions without heavy rainfall, dry antecedent conditions with heavy rainfall had no obvious different effect on the incidence of bacillary dysentery for the whole province (P>0.05). But wet antecedent conditions significantly increased the risk of bacillary dysentery for the whole province after heavy rainfall (wet antecedent conditions without heavy rainfall: RR=1.281, 95%CI: 1.264-1.298; wet antecedent conditions with heavy rainfall: RR=1.267, 95%CI: 1.167-1.376). After urban and rural stratification, antecedent rainfall conditions also showed a significant moderation effect on the incidence of bacillary dysentery following heavy rainfall events. Compared with dry antecedent conditions without heavy rainfall, dry antecedent conditions with heavy rainfall had no obvious effect on the incidence of bacillary dysentery for the urban and the rural populations (P > 0.05). However, wet antecedent conditions without heavy rainfall (urban: RR=1.391, 95%CI: 1.362-1.421; rural: RR=1.222, 95%CI: 1.201-1.243) and wet antecedent conditions with heavy rainfall (urban: RR=1.364, 95%CI: 1.193-1.559; rural: RR=1.218, 95%CI: 1.098-1.352) significantly increased the risk of bacillary dysentery in both rural and urban areas. Conclusion In the influence of heavy rainfall on the incidence of bacillary dysentery in Anhui Province, antecedent rainfall conditions have a certain moderation effect in the whole province and in both urban and rural areas, and the risk of bacillary dysentery is increased under wet antecedent conditions.
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Infectious diarrhea is an important public health problem, which has a significant impact on global disease burden. Under the background of climate change, rainstorms increase and floods occur frequently. Most studies show that the incidences of infectious diarrhea disease increase significantly after rainstorm and flood events. However, there is a lack of systematic summary on the path of rainstorm and flood events affecting the incidence of infectious diarrhea, including the key links and mechanisms underlying environmental-social interaction. This study comprehensively combed the literature from environmental factors, socio-economic and cultural factors, and population and individual susceptibility factors. The potential mechanisms of infectious diarrhea caused by rainstorm and flood events were discussed from the aspects of spreading of pathogens, affecting sanitation facilities and (or) drinking water treatment infrastructure, the regulatory role of individual and behavioral factors, and long-term effects. Based on the "pressure-state-response" model, a social driving process model of rainstorm and flood leading to incidence of infectious diarrhea was constructed. This model could provide reference for future quantitative modeling and other research directions. It is helpful to guide the public health departments to accurately identify factors affecting the incidence of infectious diarrhea after rainstorm and flood, so as to take targeted intervention measures.
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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.
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Background Preterm birth-related complications are the leading cause of death in newborns and children under the age of 5 years. Maternal heat exposure has been associated with both sleep status during pregnancy and the increased risk of preterm birth. However, whether sleep status could mediate the association between heat exposure and preterm birth remains unclear. Objective To evaluate the association between maternal heat exposure in early pregnancy and preterm birth, and to further explore potential mediation effect of sleep status on the association between heat exposure and preterm birth. Methods A birth cohort was established in Guangzhou Panyu Maternal Child Health Hospital (Guangzhou Panyu District He Xian Memorial Hospital) from 2017 until now. Pregnant women (with gestational age between 8 and 13 weeks) were included in this study when they presented to the hospital for their first prenatal care visit and signed an informed consent. Then they were followed up until delivery. A total of 3 268 pregnant women were included for the final analysis. Questionnaires were distributed to collect the demographic characteristics, lifestyles, and sleep status of pregnant women. Daily meteorological data during the study period were collected from meteorological monitoring stations in Guangzhou and the average ambient mean temperature of four weeks before the survey was calculated and assigned for each pregnancy. The 75th, 80th, 85th, 90th, and 95th percentiles (P75, P80, P85, P90, and P95) of the average ambient temperature of all pregnant women were used as the thresholds to define heat exposure. Logistic regression was used to evaluate the effects of heat exposure in different definitions on preterm birth and sleep status (sleep duration, night sleep timing, and wake up timing). The mediation effects of sleep status on the relationship between heat exposure and preterm birth were also analyzed. Results Among all the included participants, 165 newborns were preterm births with an incidence rate of 5.0%. Heat exposures with thresholds of P90 and P95 increased the risk of preterm birth, with ORs (95%CIs) of 1.66 (1.04-2.57) and 1.90 (1.03-3.33), respectively (P<0.05). Heat exposures with thresholds of P75, P80, P85, P90, and P95 decreased the sleep duration (<9 h vs. ≥9 h, control group: ≥9 h), and the ORs (95%CIs) were 1.51 (1.25-1.83), 1.44 (1.17-1.77), 1.35 (1.08-1.70), 1.43 (1.09-1.87), and 1.45 (1.00-2.13), respectively. Heat exposures with P75 and P80 thresholds resulted in earlier wake up timing (<8: 00 vs. ≥8: 00, control group: <8: 00), with ORs (95%CIs) of 0.77 (0.63-0.93) and 0.76(0.61-0.93), respectively. No significant association was observed between heat exposure and night sleep timing. The mediation analyses showed that under heat exposure with P90 threshold, a statistically significant mediation effect was observed for sleep duration, and the proportion mediated was 6.07% (95%CI: 0.17%-25.00%) (P<0.05). No significant mediation effect was observed for night sleep timing and wake up timing. Conclusion An elevated risk of preterm birth after heat exposure in early pregnancy may be partly mediated through reducing sleep duration.
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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.
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Background Under the background of global climate change, temperature has increased dramatically. Most studies about association between temperature and human health are conducted in low-altitude areas, but rarely focus on plateau areas. Objective To examine the association between temperature and non-accidental mortality risk in Tibet Plateau, China and to identify vulnerable populations for formulating targeted policies of climate change adaptation. Methods The mortality data, meteorological data, and pollutant data of Tibet area between 2013 to 2019 were collected. Based on time-stratified case-crossover design, conditional logistic regression models were used to analyze the exposure-response relationship between temperature and cause-specific mortality, which was linearized to obtain excess risk for 1 ℃ change; attributable fraction was calculated for assessing burden attributable to temperature; and stratified analyses were further conducted by gender, age (＜65 years old, ≥65 years old), and causes of death (cardiovascular diseases, cerebrovascular diseases, and respiratory diseases). Sensitivity analyses were conducted by adjusting model parameters and variables. Results A total of 26 045 non-accidental deaths were collected in Tibet during 2013 and 2019, and the P50 of temperature was 5.0 ℃. The non-accidental mortality risk increased as temperature become colder. A 1 ℃ decrease in temperature was associated with a 2.01% (95%CI: 0.94%-3.07%) increase in total non-accidental mortality, while the association changed to 2.05% (95%CI: 0.62%-3.47%) for male and 1.96% (95%CI: 0.34%-3.56%) for female, both of statistial significance; 1.45% (95%CI: −0.10%-2.98%) for the people <65 years old (not of significance) and 2.52% (95% CI : 1.04%-3.99%) for the people ≥65 years old (of significance); the excess risk for cardiovascular mortality was 2.65% (95%CI: 1.03%-4.24%), for cerebrovascular mortality was 3.70% (95%CI: 0.74%-6.57%), both of statistical significance, and for respiratory mortality was 2.18% (95%CI: −0.14%-4.44%), without significance. The total attribution number of non-accidental mortality was 5340 (95%CI: 2719-7528), and the total attributable fraction was 20.50% (95%CI: 10.44%-28.91%). The attributable fractions were higher in specific subgroups like male (20.72%), people ≥65 years (23.33%), and people with cardiovascular diseases (26.07%). Conclusion The exposure-response relationship between temperature and non-accidental mortality in Tibet showes that the non-accidental mortality risk increase as temperature become colder. The attributable burden of disease is heavy. Residents being male, ≥65 years, with cardiovascular diseases and respiratory diseases may be vulnerable to nonoptimal temperature.
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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.
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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.
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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.
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The threats to human health caused by climate change have become a global public health issue. However, at present, most studies regarding the health-related mechanisms of climate change are limited to biological mechanisms, and most of these mechanisms are not totally clear. In this special column: Mechanisms underlying human health effects of climate change, we offered several papers which investigated the effects of different meteorological factors (temperature and rainfall) on various health outcomes (preterm birth, death, diarrhea, infectious diseases, etc.), and also elaborated associated potential biological mechanisms, vulnerability mechanisms, social driving process and transmission dynamics mechanisms. These studies can deepen our understanding of the health effects of climate change, provide references to make targeted adaptative measures, and also provide scientific and technological supports for improving ability to address the health risks of climate change in China.
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Plant biology is a basic course for students majoring in biological science. Under the guidance of developmental biology, we have constructed a comprehensive, systematic and dynamic new curriculum system for plant biology. There are still some problems existing in the current curriculum teaching mode, e.g. the students do not listen carefully to the lecture due to single classroom teaching mode, the mismatch between theoretical and experimental courses in terms of content and timing, the incomplete understanding on plants and the difficulty of integrating learning and practicing due to insufficient field practices. In view of these problems, a series of new teaching strategies for bioscience major of Harbin Institute of Technology were proposed and implemented. The combination of lectures and high quality massive open online courses (MOOC) were used for theoretical study, to which the flipped classroom was added. In addition, the theoretical study and the experiment work were combined. Moreover, the plant cognitive practices were carried out in the campus and the botanical garden in early spring, late spring and summer, respectively. Satisfactory results were achieved after two rounds of teaching practice, which fulfilled the education requirements and laid foundations for students to continue follow-up basic and professional courses.
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Humans , Biological Science Disciplines , Biology , Curriculum , Learning , StudentsABSTRACT
Objective:To determine the seroprevalence of celiac disease in susceptible population, and to analyze the relationship between demographic characteristics, dietary habits, lifestyle and serological positivity so as to provide guidance for the prevention and treatment of celiac disease in Southern China.Methods:A total of 1 273 individuals who participated in Guangdong Province Health Screening Program in 2015, were selected as serologically positive subjects of celiac disease, including people with irritable bowel syndrome, colitis, diarrhea, anemia, low BMI, short stature, type 1 diabetes mellitus (T1DM), rheumatoid arthritis (RA), ankylosing spondylitis, psoriasis and bristol grade=6 or 7. All subjects were tested for serum IgA anti-tissue transglutaminase antibodies (TTGA), IgA antibodies against deamidated gliadin peptides(DGPA) and IgG against deamidated gliadin peptides (DGPG). Dietary habits, lifestyle and demographic characteristics were compared in subgroups.Results:The seroprevalence of celiac disease in susceptible population was 0.94% (95% CI 0.54%-1.64%) including 0.08% (1/1 273) for TTGA, 0.47% (6/1 273) for DGPA, and 0.39% (5/1 273) for DGPG. The seropositive rate was 3.6% (1/28) in patients with psoriasis, 2.1% (2/95) in the low BMI group, 1.9% (1/53) in T1DM group, 1.8% (3/169) in diarrhea group and 1.1% (5/463) in RA group. No significant difference was found in age, gender, high carbohydrate diet or lifestyle between the negative and the positive subjects. Conclusions:In Southern China, the seropositive rate of celiac disease is 0.94% in susceptible population, which prompts an urgent need of serological screening for early diagnosis.
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Background The aging of the labor force has become a global trend, and various occupational activities can affect blood biochemical indexes and increase the risk of metabolic diseases. Elderly workers are the main laborers in the solar greenhouse industry, and their blood biochemical indexes need more attention. Objective The purpose of this study is to explore the alternation of selected blood biochemical indexes and provide clues for conducting management programs of metabolic diseases in the elderly solar greenhouse workers. Methods The research subjects of the greenhouse group and the non-greenhouse group were selected from a vegetable production base in Northwest China. The elderly workers were selected from a recruited subjects pool for an earlier project by means of matching and non-matching respectively. The matching conditions were gender (consistent), age (±2 years old), body mass index (BMI) (±1 kg·m−2), education level (±1 level), smoking (consistent), and drinking (consistent). Routine clinical tests were used to detect serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), fasting blood glucose (GLU), and albumin (ALB), and single-factor and multi-factor analyse were used to identify different indexes in matching and non-matching samples, respectively. The matching and the non-matching samples included 80 pairs of subjects and 327 subjects, respectively. Results In the matching sample set, the greenhouse group's HDLC [(1.61±0.34) mmol·L−1] was lower than the non-greenhouse group's [(2.09±0.37) mmol·L−1] (P<0.05), the level of TG/HDLC in the greenhouse group was (1.17±0.74), higher than that in the non-greenhouse group (0.78±0.47) (P<0.05), and the level of LDLC/HDLC in the greenhouse group was (1.87±0.36), also higher than that in the non-greenhouse group(P<0.05), while there was no statistical difference of the other indexes between the two groups (all Ps>0.05). In the non-matching sample set, the results of multiple linear regression analysis showed that solar greenhouse working correlated with decreased HDLC, and increased TG/HDLC and LDLC/HDLC among the elderly workers (all Ps<0.05). Conclusion Solar greenhouse working may correlate with variations of selected blood biochemical indexes in elderly workers, and the occupational health surveillance of elderly workers should be strengthened.
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Background As a new type of vegetable production method, solar greenhouse has been widely promoted nationwide. The influence of solar greenhouse working on blood lipid cannot be ignored. Objective The aim of the study is to explore the relationship between solar greenhouse working and blood lipid and family clustering. Methods A total of 744 solar greenhouse workers in northwestern China were selected as the greenhouse group, and 231 general open field farmers in the same area were selected as the non-greenhouse group. The levels of serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), and low-density lipoprotein cholesterol (LDLC) in the two groups were detected. Dyslipidemia was determined by a two-classification criteria in the national guideline of 2007. Multiple logistic regression model and multilevel multiple linear regression model were used to explore the relationship of blood lipid with solar greenhouse working, and its family clustering. Results The number of dyslipidemia cases in the greenhouse group and non-greenhouse group was 142 (19.1%) and 43 (18.6%), respectively, and the difference was not statistically significant (P>0.05). The results of multiple logistic regression analysis showed that increasing age (OR=1.019, 95% CI: 1.001-1.038) and increased BMI (OR=1.162, 95% CI: 1.106-1.220) were related to elevated risk of dyslipidemia (all Ps<0.05). The results of multilevel multiple linear regression model showed that the changes of TC, HDLC, and TG/HDLC had family clustering (b=0.238, 95%CI: 0.132-0.430; b=0.044, 95%CI: 0.033-0.065; b=1.003, 95%CI: 0.947-1.059) (all Ps<0.05). Conclusion Solar greenhouse working does not significantly increase the incidence of dyslipidemia, but the levels of TC, HDLC, and TG/HDLC levels in the solar greenhouse workers have family clusters.
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Background Due to long working time and complex and changeable lighting conditions, greenhouse workers' anisometropia is an issue of concern. Objective This study is conducted to evaluate the relationship between solar greenhouse working and anisometropia of workers. Methods Subjects of a solar greenhouse group and a non-greenhouse group in northwest area of China were selected. Questionnaire survey was used to collect general demographicinformation. Standard Logarithmic Visual Acuity Chart (GB 11533—2011) was used to measure naked eye vision before working, the absolute value of binocular visual acuity difference was calculated and converted into classification variables, and both anisometropia absolute value and classification variables of anisometropia were used as indicators to compare the difference of the two groups. A cumulative exposure index that multiplies exposure time and number of greenhouses was further introduced to evaluate cumulative exposure levels of the greenhouse workers and was used to divide them into low, medium, and high cumulative exposure subgroups. Generalized linear model and logistic regression model were used to analyze possible risk factors associated with anisometropia. Results A total of 1002 subjects were enrolled in this study, including 739 workers in the greenhouse group and 263 workers in the non-greenhouse group. The medians (interquartile intervals) of anisometropia of the greenhouse group and non-greenhouse group were 0.1 (0, 0.2) and 0 (0, 0.1) respectively, and the difference was statistically significant (P<0.05). The proportions of anisometropia=0, ≤0.2, and >0.2 in the greenhouse group were 34.2%, 55.2%, and 10.6%, respectively, and those in the non-greenhouse group were 58.2%, 34.6%, and 7.2%, respectively. The difference of anisometropia distribution between the two groups was statistically significant (P<0.05). According to the cumulative exposure index, the greenhouse group was divided into low, medium, and high cumulative exposure subgroups, with 154 (21.0%), 188 (25.6%), and 392 (53.4%) workers, respectively. There was no statistical significance in anisometropia among workers with different cumulative exposure levels (P>0.05). The results of multiple generalized linear analysis showed that greenhouse working was a risk factor of anisometropia (b=0.053, P<0.05), and the results of multiple logistic regression analysis showed that greenhouse working was associated with an increased risk of anisometropia (OR=2.586, 95%CI: 1.473-4.539). The results of multiple generalized linear analysis showed that medium exposure level increased the degree of anisometropia after adjusting age, gender, and other factors (b=0.054, P<0.05). Conclusion Solar greenhouse working may be a risk factor for increasing anisometropia in workers.
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Background In the process of greenhouse working, labor intensity is high and repetitive work involves multiple body parts such as limbs, neck, upper back, and lower back. The prevalence and comorbidity of work-related musculoskeletal disorders (WMSDs) in greenhouse workers are worthy of attention. Objective This study is conducted to investigate the prevalence and comorbidity, as well as potential influencing factors of WMSDs in greenhouse workers. Methods A total of 722 greenhouse workers were selected as the subjects for a cross-sectional epidemiological survey. Through questionnaire survey and physical examination, basic information of the subjects and the prevalence of WMSDs were collected. The participants were divided into low, medium, and high cumulative exposure groups by cumulative exposure index matrix. Chi-square test was used to analyze the difference of prevalence among different cumulative exposure levels, the correlation between the prevalence of WMSDs in paired sites was calculated as prevalence ratio (PR) by using the log-binomial model, the prevalence of multi-site WMSDs in each group was compared by Wilcoxon rank sum test, and the influencing factors of multi-site WMSDs were evaluated by multi-classification logistic regression model. Results The prevalence rate of WMSDs in the greenhouse workers was 78.7% (568/722). The main affected sites of body were lower back, legs, neck, and shoulders, and associated prevalence rates were 47.6%, 46.0%, 27.1%, and 23.8%, respectively. By constructing a cumulative exposure index matrix, the low, medium, and high cumulative exposure groups contained 121, 196, and 405 workers respectively. The prevalence rates of WMSDs in lower back, legs, or shoulders were significantly different among groups with different exposure levels (P<0.05), and the prevalence rates increased with higher cumulative exposure levels (lower back, \begin{document}${χ} _{{{\rm{trend}}}}