A stronger association of mental disorders with smaller particulate matter and a modifying effect of air temperature.

Mental disorders (MDs) can be triggered by adverse weather conditions and particulate matter (PM) such as PM2.5 and PM10 (aerodynamic diameter ≤2.5 µm and ≤10 µm). However, there is a dearth of evidence on the role of smaller PM (e.g. PM1, aerodynamic diameter ≤1 µm) and the potential modifying effects of weather conditions. We aimed to collect daily data on emergency department visits and hospitalisations for schizophrenia-, mood-, and stress-related disorders in a densely populated Chinese city (Hefei) between 2016 and 2019. A time-stratified case-crossover analysis was used to examine the short-term association of MDs with PM1, PM2.5, and PM10. The potential modifying effects of air temperature conditions (cold and warm days) were also explored. The three size-fractioned PMs were all associated with an increased risk of MDs; however, the association differed between emergency department visit and hospitalisation. Specifically, PM1 was primarily associated with an increased risk of emergency department visit, whereas PM2.5 was primarily associated with an increased risk of hospitalisation, and PM10 was associated with an increased risk of both emergency department visit and hospitalisation. The PM-MD association appeared to be greatest (although not significant) for PM1 (odds ratio range: 1.014-1.055), followed by PM2.5 (odds ratio range: 1.001-1.009) and PM10 (odds ratio range: 1.001-1.006). Furthermore, the PM-MD association was observed on cold days; notably, the association between PM and schizophrenia-related disorders was significant on both cold and warm days. Our results suggest that the smaller the PM, the greater the risk of MDs, and that the PM-MD association could be determined by air temperature conditions.

Medium-term exposure to size-fractioned particulate matter and asthma exacerbations in China: A longitudinal study of asthmatics with poor medication adherence.

BACKGROUND: Studies have shown that short- and long-term exposure to particulate matter (PM) can increase the risk of asthma morbidity and mortality. However, the effect of medium-term exposure remains unknown. We aim to examine the effect of medium-term exposure to size-fractioned PM on asthma exacerbations among asthmatics with poor medication adherence. METHODS: We conducted a longitudinal study in China based on the National Mobile Asthma Management System Project that specifically and routinely followed asthma exacerbations in asthmatics with poor medication adherence from April 2017 to May 2019. High-resolution satellite remote-sensing data were used to estimate each participant's medium-term exposure (on average 90 days) to size-fractioned PM (PM1, PM2.5, and PM10) based on the residential address and the date of the follow-up when asthma exacerbations (e.g., hospitalizations and emergency room visits) occurred or the end of the follow-up. The Cox proportional hazards model was employed to examine the hazard ratio of asthma exacerbations associated with each PM after controlling for sex, age, BMI, education level, geographic region, and temperature. RESULTS: Modelling results revealed nonlinear exposure-response associations of asthma exacerbations with medium-term exposure to PM1, PM2.5, and PM10. Specifically, for emergency room visits, we found an increased hazard ratio for PM1 above 22.8 µg/m3 (1.060, 95 % CI: 1.025-1.096, per 1 µg/m3 increase), PM2.5 above 38.2 µg/m3 (1.032, 95 % CI: 1.010-1.054), and PM10 above 78.6 µg/m3 (1.019, 95 % CI: 1.006-1.032). For hospitalizations, we also found an increased hazard ratio for PM1 above 20.3 µg/m3 (1.055, 95 % CI: 1.001-1.111) and PM2.5 above 39.2 µg/m3 (1.038, 95 % CI: 1.003-1.074). Furthermore, the effects of PM were greater for a longer exposure window (90-180 days) and among participants with a high BMI. CONCLUSION: This study suggests that medium-term exposure to PM is associated with an increased risk of asthma exacerbations in asthmatics with poor medication adherence, with a higher risk from smaller PM.

The 2022 Summer record-breaking heatwave and health information-seeking behaviours: an infodemiology study in Mainland China.

INTRODUCTION: Heatwave is a major global health concern. Many countries including China suffered a record-breaking heatwave during the summer of 2022, which may have a significant effect on population health or health information-seeking behaviours but is yet to be examined. METHODS: We derived health information-seeking data from the Baidu search engine (similar to Google search engine). The data included city-specific daily search queries (also referred to Baidu Search Index) for heat-sensitive diseases from 2021 to 2022, including heatstroke, hospital visits, cardiovascular diseases and diabetes, respiratory diseases, mental health and urological diseases. For each city, the record-breaking heatwave days in 2022 were matched to days in the same calendar month in 2021. RESULTS: The 2022 record-breaking heatwave hit most cities (83.64%) in Mainland China. The average heatwave duration was 13 days and the maximum temperature was 3.60°C higher than that in 2021 (p<0.05). We observed increased population behaviours of seeking information on respiratory diseases (RR=1.014, 95% CI: 1.008 to 1.020), urological diseases (RR=1.011, 95% CI: 1.006 to 1.016) and heatstroke (RR=1.026, 95% CI: 1.016 to 1.036) associated with the heatwave intensity in 2022 (per 1°C increase). The heatwave duration in 2022 (per 1 day increase) was also associated with an increase in seeking information on cardiovascular diseases and diabetes (RR=1.003, 95% CI: 1.002 to 1.004), urological diseases (RR=1.005, 95% CI: 1.002 to 1.008), mental health (RR=1.009, 95% CI: 1.006 to 1.012) and heatstroke (RR=1.038, 95% CI: 1.032 to 1.043). However, there were substantial geographical variations in the effect of the 2022 heatwave intensity and duration on health information-seeking behaviours. CONCLUSION: This infodemiology study suggests that the 2022 summer unprecedented heatwave in Mainland China has significantly increased population demand for health-related information, especially for heatstroke, urological diseases and mental health. Population-based research of real-time disease data is urgently needed to estimate the negative health impact of the exceptional heatwave in Mainland China and elsewhere.

Seasonal peak and the role of local weather in schizophrenia occurrence: A global analysis of epidemiological evidence.

BACKGROUND: Many studies have shown that the onset of schizophrenia peaked in certain months within a year and the local weather conditions could affect the morbidity risk of schizophrenia. This study aimed to conduct a systematic analysis of schizophrenia seasonality in different countries of the world and to explore the effects of weather factors globally. METHODS: We searched three databases (PubMed, Web of Science, and China National Knowledge Infrastructure) for eligible studies published up to September 2022. Schizophrenia seasonality was compared between hemispheres and within China. A meta-analysis was conducted to pool excess risk (ER, absolute percentage increase in risk) of the onset of schizophrenia associated with various weather factors including temperature (an increase or decrease of temperature as a reflection of high or low temperature; heatwave; temperature variation), precipitation, etc. RESULTS: We identified 84 relevant articles from 22 countries, mainly in China. The seasonality analysis found that the onset of schizophrenia mostly peaked in the cold season in the southern hemisphere but in the warm season in the northern hemisphere. Interestingly in China, schizophrenia seasonality presented two peaks, respectively in the late cold and warm seasons. The meta-analysis further revealed an increased risk of schizophrenia after short-term exposure to high temperature [ER%: 0.45 % (95 % confidence interval (CI): 0.14 % to 0.76 %)], low temperature [ER%: 0.52 % (95%CI: 0.29 % to 0.75 %)], heatwave [ER%: 7.26 % (95%CI: 4.45 % to 10.14 %)], temperature variation [ER%: 1.02 % (95%CI: 0.55 % to 1.50 %)], extreme precipitation [ER%: 3.96 % (95%CI: 2.29 % to 5.67 %)]. The effect of other weather factors such as sunlight on schizophrenia was scarcely investigated with inconsistent findings. CONCLUSION: This study provided evidence of intra- and inter-country variations in schizophrenia seasonality, especially the double-peak seasons in China. Exposure to local weather conditions mainly temperature changes and precipitation could affect the onset risk of schizophrenia.

Impacts of PM2.5 before and after COVID-19 outbreak on emergency mental disorders: A population-based quasi-experimental and case-crossover study.

The ongoing COVID-19 pandemic is a great challenge to mental health, but fine particulate matter (PM2.5), an increasingly reported risk factor for mental disorders, has been greatly alleviated during the pandemic in many countries. It remains unknown whether COVID-19 outbreak can affect the association between PM2.5 exposure and the risk of mental disorders. This study aimed to investigate the associations of total and cause-specific mental disorders with PM2.5 exposure before and after the COVID-19 outbreak in China. Data on daily emergency department visits (EDVs) and hospitalizations of mental disorders from 2016 to 2021 were obtained from Anhui Mental Health Center for Hefei city. An interrupted time series analysis was used to quantify the impact of COVID-19 outbreak on EDVs and hospitalizations of mental disorders. A time-stratified case-crossover analysis was employed to evaluate the association of mental disorders with PM2.5 exposure before and after the COVID-19 outbreak, especially in the three months following the COVID-19 outbreak. After COVID-19 outbreak, there was an immediate and significant decrease in total mental disorders, including a reduction of 15% (95% CI: 3%-26%) in EDVs and 44% (95% CI: 36%-51%) in hospitalizations. PM2.5 exposure was associated with increased risk of EDVs and hospitalizations for total and cause-specific mental disorders (schizophrenia, schizotypal and delusional disorders; neurotic, stress-related, and somatoform disorders) before COVID-19 outbreak, but this PM2.5-related risk elevation significantly decreased after COVID-19 outbreak, with greater risk reduction at the first month after the outbreak. However, young people (0-45 years) were still vulnerable to PM2.5 exposure after the COVID-19 outbreak. This study first reveals that the risk of PM2.5-related emergency mental disorders decreased after the COVID-19 outbreak in China. The low concentration of PM2.5 might benefit mental health and greater efforts are required to mitigate air pollution in the post-COVID-19 era.

Daytime and nighttime high temperatures differentially increased the risk of cardiovascular disease: A nationwide hospital-based study in China.

Short-term exposure to ambient high temperature (heat) could increase the risk of cardiovascular disease (CVD). However, available evidence on the burden of daytime and nighttime heat on CVD is limited and vulnerable populations remain unknown so far. We aimed to examine and differentiate the impact of daytime and nighttime heat on CVD in China. Data on daily outpatient visits for CVD were collected from 15 Chinese cities spanning multiple geographical regions, climates, and socio-economic conditions. The population-weighted temperature was used to calculate excess heat exposure in warm seasons (June-September) from 2011 to 2015. Hot day excess (HDE) and hot night excess (HNE), the sum of temperature above the heat threshold during daytime and nighttime respectively, were used to represent daytime and nighttime excess heat. A distributed lag non-linear model was employed to estimate the city-level association between HDE/HNE and daily CVD cases. The city-level association was then pooled by multivariate meta-analysis. We further estimated the disease burden of CVD attributable to HDE and HNE by geographical regions, gender, and age. A total of 729,409 cases of CVD were included in this study. Both HDE and HNE were associated with an increased risk of CVD, with greater effects from nighttime heat (relative risk (RR): 1.38; 95% confidence interval (CI): 1.18-1.61) than daytime heat (RR: 1.10; 95% CI: 1.05-1.15). The proportion of CVD cases attributable to HNE was 15.7%, which was almost three times as high as HDE (4.6%, p for difference <0.05). Males, people living in northern cities, and those aged less than 45 years were more vulnerable to HNE. Our findings for the first time revealed an intra-day difference in the heat effect on CVD, with a greater impact from nighttime heat exposure, which should be considered to protect vulnerable populations on hot days.

Three-Dimensional Strawlike MoSe2-Ni(Fe)Se Electrocatalysts for Overall Water Splitting.

The development of efficient and low-cost transition-metal electrocatalysts is of great significance for hydrogen production from water splitting. Herein, we synthesized three-dimensional strawlike MoSe2-NiSe composed of microrods on nickel foam (NF) by a one-step hydrothermal reaction. The as-prepared MoSe2-NiSe/NF exhibited effective hydrogen evolution reaction (HER) activity (low overpotential of 79 mV at 10 mA cm-2 and stability of 21 h in 1 M KOH), benefiting from the large electrochemically active area provided by strawlike structures, proper Se content, and synergistic effect of active phases. The enhanced oxygen evolution reaction (OER) activity (the low overpotential of 217 mV at 10 mA cm-2 and maintaining stability for 47 h in 1 M KOH) was further observed for Fe-doped MoSe2-NiSe/NF (MoSe2-NiFeSe/NF) prepared by facile soaking, which can be mainly ascribed to optimized active phases formed on the OER process after Fe doping. The two-electrode system (MoSe2-NiSe/NF||MoSe2-NiFeSe/NF) requires a low cell voltage of 1.54 V to obtain a current density of 10 mA cm-2 in 1 M KOH, which provides an interesting idea for constructing an effective overall water splitting system.

A systematic review and meta-analysis of air pollution and angina pectoris attacks: identification of hazardous pollutant, short-term effect, and vulnerable population.

We conducted a systematic review and meta-analysis of global epidemiological studies of air pollution and angina pectoris, aiming to explore the deleterious air pollutant(s) and vulnerable sub-populations. PubMed and Web of Science databases were searched for eligible articles published between database inception and October 2021. Meta-analysis weighted by inverse-variance was utilized to pool effect estimates based on the type of air pollutant, including particulate matters (PM2.5 and PM10: particulate matter with an aerodynamic diameter ≤ 2.5 µm and ≤ 10 µm), gaseous pollutants (NO2: nitrogen dioxide; CO: carbon monoxide; SO2: sulfur dioxide, and O3: ozone). Study-specific effect estimates were standardized and calculated with percentage change of angina pectoris for each 10 µg/m3 increase in air pollutant concentration. Twelve studies involving 663,276 angina events from Asia, America, Oceania, and Europe were finally included. Meta-analysis showed that each 10 µg/m3 increase in PM2.5 and PM10 concentration was associated with an increase of 0.66% (95%CI: 0.58%, 0.73%; p < 0.001) and 0.57% (95%CI: 0.20%, 0.94%; p = 0.003) in the risk of angina pectoris on the second day of exposure. Adverse effects were also observed for NO2 (0.67%, 95%CI: 0.33%, 1.02%; p < v0.001) on the second day, CO (0.010%, 95%CI: 0.006%, 0.014%; p < 0.001). The elderly and patients with coronary artery disease (CAD) appeared to be at higher risk of angina pectoris. Our findings suggest that short-term exposure to PM2.5, PM10, NO2, and CO was associated with an increased risk of angina pectoris, which may have implications for cardiologists and patients to prevent negative cardiovascular outcomes.

Urban-rural disparity in heatwave effects on diabetes mortality in eastern China: A case-crossover analysis in 2016-2019.

Diabetics are sensitive to high ambient temperature due to impaired thermoregulation. However, available evidence on the impact of prolonged high temperature (i.e., heatwave) on diabetes deaths is limited and whether urban and rural areas differ in heatwave vulnerability remains unknown so far. A time-stratified case-crossover analysis was employed to estimate the association between heatwaves and diabetes deaths in 1486 districts (509 urban and 977 rural areas) of eastern China (Jiangsu Province), 2016-2019. For each decedent, residential heatwave exposure was measured by matching daily mean temperatures to the geocoded residential address. We adopted nine-tiered heatwave definitions incorporating intensity and duration. Stratified analyses by decedents' characteristics (gender, age, and education) were also conducted. During the study period, there were 18,685 deaths from diabetes (urban proportion: 36.95 %, p-value for urban-rural difference < 0.05). Heatwaves were associated with an increased risk of diabetes deaths, with greater and longer-lasting effects in rural areas than urban areas [e.g., rural odds ratio (OR): 1.19 (95 % confidence interval (CI): 1.14, 1.25) vs. urban OR: 1.09 (95 % CI: 1.05, 1.12)]. Risk of diabetes deaths increased with the intensity of heatwaves in rural areas (p-value for trend <0.01), but not in urban areas. Stratified analyses in rural areas suggested that females and less-educated people were more vulnerable to heatwave-related diabetes deaths. Our findings revealed the urban-rural disparity in the risk of diabetes deaths associated with heatwaves. Rural diabetics should be made aware of the increased death risk posed by heatwaves in the context of warming climate.

Abnormal ambient temperature change increases the risk of out-of-hospital cardiac arrest: A systematic review and meta-analysis of exposure types, risk, and vulnerable populations.

BACKGROUND: There is growing evidence in support of a short-term association between ambient temperature and cardiac arrest attacks that is a serious manifestation of cardiovascular disease and has a high incidence and low survival rate. However, it remains unrecognized about the hazardous temperature exposure types, exposure risk magnitude, and vulnerable populations. OBJECTIVES: We comprehensively summarize prior epidemiological studies looking at the short-term associations of out-of-hospital cardiac arrest (OHCA) with various temperature exposures among different populations. METHODS: We searched PubMed and Web of Science databases from inception to October 2021 for eligible English language. Temperature exposure was categorized into three types: heat (included high temperature, extreme heat, and heatwave), cold (included low temperature and extreme cold), and temperature variation (included diurnal temperature range and temperature change between two adjacent days). Meta-analysis weighted by inverse variance was used to pool effect estimates. RESULTS: This study included 15 studies from 8 countries, totaling around 1 million OHCA events. Extreme heat and extreme cold were significantly associated with an increased risk of OHCA, and the pooled relative risks (RRs) were 1.071 [95 % confidence interval (CI): 1.019-1.126] and 1.662 (95%CI: 1.138-2.427), respectively. The risk of OHCA was also elevated by heatwaves (RR = 1.248, 95%CI: 1.091-1.427) and more intensive heatwaves had a greater effect. Notably, the elderly and males seemed to be more vulnerable to the effects of heat and cold. However, we did not observe a significant association between temperature variation and the risk of OHCA (1.005, 95%CI: 0.999-1.012). CONCLUSION: Short-term exposure to heat and cold may be novel risk factors for OHCA. Considering available studies in limited regions, the temperature effect on OHCA should be urgently confirmed in different regions.

The increased medical burden associated with frailty is partly attributable to household solid fuel: A nationwide prospective study of middle-aged and older people in China.

BACKGROUND: Frail individuals often face a high medical burden, and household solid fuel use is associated with a range of functional declines or diseases, but evidence on the relationship between household solid fuel and frailty and the resulting medical burden is limited. We aim to investigate the effect of household solid fuel on frailty and further quantify how much of the increased medical burden associated with frailty is attributable to household solid fuel. METHODS: The prospective data were from the China Health and Retirement Longitudinal Study, 4685 non-frail participants at baseline were included. Inverse probability weighting was used to balance the covariates between groups. The modified Poisson regression was used to analyze the association of household solid fuel (including baseline and switching across three-wave survey) with frailty, and the generalized linear model was used to analyze the association of frailty with the change in medical burden. Further, the increased medical burden associated with frailty attributable to household solid fuel was quantified. RESULTS: Using solid fuel for cooking (RR = 1.29, 95%CI, 1.07-1.57), heating (RR = 1.38, 95%CI, 1.09-1.73), or both (RR = 1.40, 95%CI, 1.05-1.86) had a higher risk of frailty than using clean fuel. In addition, the risk of frailty generally increases with the times of solid fuel use across the three-wave survey. Then, frailty participants had a greater increase in the annual number of hospitalizations (ß = 0.11, 95%CI, 0.02-0.19) and annual costs of hospitalizations (ß = 2953.35, 95%CI, 1149.87-4756.83) than those non-frailty. Heating coal caused the largest frailty-related increase in the annual number of hospitalizations and annual costs of hospitalizations, with 0.04 and 1195.40, respectively. CONCLUSION: The increased medical burden associated with frailty was partly attributable to household solid fuel, which suggested that intervention targeting household solid fuels can delay frailty and thus reduce individual medical burden.

Impact of cold spells on COPD mortality in Jiangsu Province, China.

Ambient cold is associated with substantial population attributable fraction of mortality in China, and respiratory health is vulnerable to cold exposure. This study aimed to examine the effect of cold spells on risk of deaths from chronic obstructive pulmonary disease (COPD). We collected daily data on deaths from COPD and climatic factors from 1 January 2016 to 31 December 2019 in 13 cities of Jiangsu Province, China. We used a quasi-Poisson generalized linear model coupled with a distributed lag non-linear model to quantify the association between risk of COPD deaths and exposure to cold spells (defined as 2 or more consecutive days with mean temperature ≤ 5th percentile of daily mean temperature distribution in cold months). Stratification analyses by age, sex, education, and occupation were undertaken to identify vulnerable subgroups. The results suggested that exposure to cold spells was associated with a higher risk of COPD deaths in Lianyungang (relative risk (RR): 1.70; 95% confidence interval (CI): 1.31, 2.21), Nanjing (RR: 1.54; 95% CI: 1.16, 2.04), Nantong (RR: 1.97; 95% CI: 1.68, 2.31), Suzhou (RR: 1.97; 95% CI: 1.55, 2.50), Suqian (RR: 1.68; 95% CI: 1.23, 2.29), Taizhou (RR: 1.70; 95% CI: 1.32, 2.19), Wuxi (RR: 1.99; 95% CI: 1.53, 2.60), Xuzhou (RR: 1.71; 95% CI: 1.01, 2.90), Yancheng (RR: 1.78; 95% CI: 1.53, 2.06), Yangzhou (RR: 2.78; 95% CI: 2.06, 3.76), and Zhenjiang (RR: 1.79; 95% CI: 1.26, 2.55). All subgroups seemed to be vulnerable to the effect of cold spells. The recommendation of this study is that individuals with pre-existing COPD, regardless of age, sex, education, or occupation, should be made aware of the health risk posed by cold spells and should be encouraged to take cold adaptation actions before cold season arrives. The main limitation of this study is that it is subject to ecological fallacy.

Associations between household solid fuel use and activities of daily living trajectories: A nationwide longitudinal study of middle and older adults in China.

BACKGROUND: More studies focus on reporting the effects of ambient air pollution on physical activity while ignoring the hazards of indoor air pollution caused by household solid fuel use. Moreover, the impact of individual cognitive and depressive status on the health effects of air pollution is often overlooked. OBJECTIVE: We examined the association between household solid fuel and activities of daily living (ADL) trajectories, and further examined this association in homogeneous subgroups of cognitive or depressive trajectories. METHODS: Participants were from the China Health and Retirement Longitudinal Study, which conducted four waves of surveys from 2011 to 2018. We collected information on participants' household fuel use, then the ADL, cognitive and depressive performances were assessed in each wave. The latent growth mixture model (LGMM) was used to identify the optimal trajectory class for ADL, cognition, and depression. Then, the multinomial logistic regression was used to assess the association between solid fuel use and ADL trajectories in total population, as well as subgroups with different cognitive or depression trajectories. Furthermore, we examined the association between switching household fuel types and ADL trajectories across the four-wave survey. RESULTS: The study sample included 7052 participants. We identified three ADL trajectory classes in total population: "Low-stable", "Moderate-anterior rise", and "Moderate-posterior rise". The multinomial logistic regression results showed that solid fuel use was associated with elevated odds for the adverse ADL trajectories, and this association was still shown in homogeneous subgroups of cognitive or depressive trajectories, while some effects were less significant. In addition, the risk of adverse ADL trajectories generally increases with the times of solid fuel use across the four-wave survey. CONCLUSIONS: For middle and older adults in China, household solid fuel use was not conducive to physical activity development, which inspires that a further transformation to cleaner fuels is an important intervention.

A systematic review and meta-analysis of intraday effects of ambient air pollution and temperature on cardiorespiratory morbidities: First few hours of exposure matters to life.

BACKGROUND: A growing number of studies have reported an increased risk of cardiovascular disease (CVD) and respiratory disease (RD) within hours after exposure to ambient air pollution or temperature. We assemble published evidence on the sub-daily associations of CVD and RD with ambient air pollution and temperature. METHODS: Databases of PubMed and Web of Science were searched for original case-crossover and time-series designs of English articles examining the intra-day effects of ambient air pollution [particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5), ≤10 µm (PM10), 2.5-10µm (PM10-2.5), and < 7 µm (SPM), O3, SO2, NO2, CO, and NO] and temperatures (heat and cold) on cardiorespiratory diseases within 24 h after exposure in the general population by comparing with exposure at different exposure levels or periods. Meta-analyses were conducted to pool excess risks (ERs, absolute percentage increase in risk) of CVD and RD morbidities associated with an increase of 10 µg/m3 in particulate matters, 0.1 ppm in CO, and 10 ppb in other gaseous pollutants. FINDINGS: Final analysis included thirty-three papers from North America, Europe, Oceania, and Asia. Meta-analysis found an increased risk of total CVD morbidity within 3 h after exposure to PM2.5 [ER%: 2.65% (95% CI: 1.00% to 4.34%)], PM10-2.5 [0.31% (0.02% to 0.59%)], O3 [1.42% (0.14% to 2.73%)], and CO [0.41% (0.01% to 0.81%)]. The risk of total RD morbidity elevated at lag 7-12 h after exposure to PM2.5 [0.69% (0.14% to 1.24%)] and PM10 [0.38% (0.02% to 0.73%)] and at lag 12-24 h after exposure to SO2 [2.68% (0.94% to 4.44%)]. Cause-specific CVD analysis observed an increased risk of myocardial infarction morbidity within 6 h after exposure to PM2.5, PM10, and NO2, and an increased risk of out-of-hospital cardiac arrest morbidity within 12 h after exposure to CO. Risk of total CVD also increased within 24 h after exposure to heat. INTERPRETATION: This study supports a sudden risk increase of cardiorespiratory diseases within a few hours after exposure to air pollution or heat, and some acute and highly lethal diseases such as myocardial infarction and cardiac arrest could be affected within a shorter time. FUNDING: The National Natural Science Foundation of China (Grant No. 42105165; 81773518), the High-level Scientific Research Foundation of Anhui Medical University (Grant No. 0305044201), and the Discipline Construction of Anhui Medical University (Grant No. 0301001836).

Protective effect of pneumococcal conjugate vaccination on the short-term association between low temperatures and childhood pneumonia hospitalizations: Interrupted time-series and case-crossover analyses in Matlab, Bangladesh.

Studies have shown that ambient extreme temperatures (heat and cold) were associated with an increased risk of childhood pneumonia, but the evidence is very limited in low-middle-income countries. It also remains unknown whether pneumococcal conjugate vaccine (PCV) could prevent temperature-related childhood pneumonia. This study collected data on ambient temperature and hospitalizations for childhood pneumonia in Matlab, Bangladesh from 2012 to 2016. Interrupted time series (ITS) analysis was employed to assess the impact of PCV (10-valent) intervention on childhood pneumonia hospitalizations. A time-stratified case-crossover analysis with a conditional logistic regression was performed to examine the association of childhood pneumonia hospitalizations with extreme temperatures and heatwaves before and after PCV10 intervention. Subgroup analyses were conducted to explore the modification effects of seasons, age, gender, and socioeconomic levels on temperature-related childhood pneumonia hospitalizations. We found that after PCV10 intervention, there was a sharp decrease in hospitalizations for childhood pneumonia (relative risk (RR): 0.59, 95% confidence interval (CI): 0.43-0.83). During the study period, heat effects on childhood pneumonia appeared immediately on the current day (odds ratio (OR): 1.28; 95% CI: 1.02-1.60, lag 0), while cold effects appeared 4 weeks later (OR: 1.53, 95% CI: 1.06-2.22, lag 28). Importantly, cold effects decreased significantly after PCV10 (p-value＜0.05), but heat and heatwave effects increased after PCV10 (p-value＜0.05). Particularly, children from families with a middle or low socioeconomic level, boys, and infants were more susceptible to heat-related pneumonia. This study suggests that PCV10 intervention in Bangladesh may help decrease cold-related not heat-related childhood pneumonia.

How to improve infectious disease prediction by integrating environmental data: an application of a novel ensemble analysis strategy to predict HFMD.

This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM10, SO2 and NO2 were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R2, average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (-24.88%; t = -5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (-16.69%; t = -4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.

Summary of the COVID-19 epidemic and estimating the effects of emergency responses in China.

Coronavirus disease-2019 (COVID-19) pandemic has affected millions of people since December 2019. Summarizing the development of COVID-19 and assessing the effects of control measures are very critical to China and other countries. A logistic growth curve model was employed to compare the development of COVID-19 before and after the emergency response took effect. We found that the number of confirmed cases peaked 9-14 days after the first detection of an imported case, but there was a peak lag in the province where the outbreak was concentrated. Results of the growth curves indicated that the fitted cumulative confirmed cases were close to the actual observed cases, and the R2 of all models was above 0.95. The average growth rate decreased by 44.42% nationally and by 32.5% outside Hubei Province. The average growth rate in the 12 high-risk areas decreased by 29.9%. The average growth rate of cumulative confirmed cases decreased by approximately 50% after the emergency response. Areas with frequent population migration have a high risk of outbreak. The emergency response taken by the Chinese government was able to effectively control the COVID-19 outbreak. Our study provides references for other countries and regions to control the COVID-19 outbreak.