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Previous experimental studies have identified specific foods or nutrients are capable of mitigating adverse effects induced by air pollution. However, whether the dietary pattern can modify the associations between long-term particulate matter (PM) and increasing blood pressure (BP) among adults has not yet been assessed. We assessed whether the dietary pattern and various foods modify the associations between long-term exposure to PM (PM 1 , PM 2.5 , and PM 10 ), hypertensive BP (BP≥140/90 mm Hg, HBP), and BP in Chinese adults. This study included 61 081 participants from China Multi-Ethnic Cohort. PM was assessed through satellite-based random forest approaches. Outcomes were analyzed with logistic regression models and linear regression models. The dietary approaches to stop hypertension (DASH) diet was calculated for each participant. This study founds long-term exposure to PM was associated with HBP, systolic BP, and pulse pressure. The DASH diet modified the associations between PM, HBP, and some BP components. For each 10 μg/m 3 increase in PM 1 , PM 2.5 , and PM 10 , the participants with the lowest quintile of DASH score had HBP risks with odds ratios (95% CI) of 1.196 (1.084–1.319), 1.145 (1.09–1.202), and 1.080 (1.045–1.117), whereas those with the highest quintile of DASH score had lower HBP risks with odds ratios (95% CI) of 1.063 (0.953–1.185), 1.074 (1.017–1.133), and 1.038 (1.000–1.077). Consuming more fresh fruits, vegetables, dairy, and whole grains would reduce the risk of raised BP caused by PM. In conclusion, the DASH diet rich in antioxidant compounds may be a wide-reaching intervention to reduce the deleterious impact of PM.

Limited epidemiological literature identified the associations between residential greenness and hypertension in low-/middle-income countries. A random sampling strategy was adopted to recruit 39,259 residents, ≥ 18 years, and from 5 counties in central China. Blood pressure was measured based on the protocol of the American Heart Association. Hypertension was defined according to the 2010 Chinese guidelines for the management of hypertension. The satellite-derived normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were applied to estimate the residential greenness. Mixed logit model and mixed linear model were utilized to explore the relationships of residential greenness with hypertension and blood pressure. Higher residential greenness was associated with lower odds of hypertension and blood pressure levels. For instance, an interquartile range (IQR) increase in NDVI500m was linked with lower odds of hypertension (OR = 0.92, 95%CI 0.88 to 0.95), a decrease of -0.88 mm Hg (95% CI -1.17 to -0.58) and -0.64 mm Hg (95% CI -0.82 to -0.46) in SBP and DBP, respectively. The effect of residential greenness was more pronounced in males, smokers, and drinkers. Long-term exposure to residential greenness was linked with lower odds of hypertension. More prospective studies are needed to verify the hypothesis.

Summary Background Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. Methods In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000–15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. Findings We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV0–1) increased by 0·52% (95% CI 0·50−0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58–0·69), for upper-middle-income cities it was 0·50% (0·47–0·53), and for high-income cities it was 0·39% (0·33–0·46). The socioeconomic inequality in vulnerability to TV0–1 was especially evident for people aged 0–19 years (effect estimate 1·21% [1·11–1·31] for lower-middle income vs 0·52% [0·41–0·63] for high income) and people aged 60 years or older (0·60% [0·50–0·70] vs 0·43% [0·31–0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46–1·78] vs 0·56% [0·30–0·82]), respiratory diseases (1·32% [1·20–1·44] vs 0·55% [0·37–0·74]), and endocrine diseases (1·21% [0·99–1·43] vs 0·32% [0·02–0·62]). Interpretation People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations. Funding None.

Until now, the green and facile synthesis of highly fluorescent silicon nanoparticles (SiNPs) with robust luminescent stability and favorable biocompatibility for cellular imaging is still a challe...

Heavy metal pollution in soil has an increasingly serious impact on the ecological environment, quality of agricultural and livestock products, and healthy living. Researches on detection methods a...

Ambient air pollution may be associated with diabetes mellitus. However, evidence from developing countries is limited although the concentrations of air pollution are disproportionably higher in these countries. We collected daily data on diabetes mortality, air pollution, and weather conditions from 16 Chinese provincial cities during 2007–2013. A quasi-Poisson regression combined with a distributed lag model was used to quantify the city-specific mortality risk of PM10 (particulate matter with aerodynamic diameter

Smoke exposure from landscape and coal mine fires can have severe impacts on human health. The ability of health studies to accurately identify potential associations between smoke exposure and health is dependent on the techniques utilised to quantify exposure concentrations for the population at risk. The evolution of spatial modelling techniques capable of better characterising this association has potential to provide more precise health effect estimates. We reviewed the literature to identify and assess the spatial modelling techniques available to estimate smoke PM2.5 or PM10 concentrations from open biomass or coal mine fires. Four electronic databases were searched: MEDLINE, EMBASE, Scopus and Web of Science. Studies were included if they utilised any method for modelling the spatial distribution of PM2.5 or PM10 concentrations from open biomass or coal mine fires and had applied the modelled PM to health data. Studies based on un-adjusted monitoring data, or which were not in English, were excluded. We identified 28 studies which utilised five spatial modelling techniques to assess exposure from open biomass fires: dispersion models, land use regression, satellite remote sensing, spatial interpolation and blended models. No studies of coal mine fires were identified. We found the most effective models combined multiple techniques to enhance the strengths and mitigate the weaknesses of the underlying individual techniques. “Blended” models have the potential to facilitate research in regions currently under represented in biomass or coal mine fire studies as well as enhancing the power of studies to identify associations with health outcomes.

Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.

There is an increasing interest in the link between ambient temperature and sexual crime in the context of climate change. However, existing studies are limited in evaluating the acute effect of temperature and rarely estimate the attributable burden. Here, we show that in seven large US cities, every 5 °C rise in daily mean temperature was associated with a 4.5 % [95 % confidence interval (CI): 2.8–6.3 %] increase in sex offenses in the following 0–8 days. The associations were stronger in hot and cold season compared to moderate season, and could be enhanced by higher relative humidity and precipitation. The associations were only significant for sodomy, fondling and rape, and for sex offenses happened in certain locations (open space, education, street but not residence). We estimated that 2.6 % (95 %CI: 1.7–3.6 %) sex offenses were attributable to temperatures above city-specific median temperatures, corresponding to a mean annual sex offense rate of 2.9/100,000 (95 %CI: 1.9–4.0/100,000). Our findings highlight the potential rising sexual crime along with climate change and provide useful information for targeted preventions.

Background Population-based studies on the associations of long-term exposure to particulate matter (PM) with androgen and progesterone are still scant. Residential greenness is benefits health by promoting physical activity, reducing air pollution, and improving mental health, but it remains unclear whether it is related to androgen and progesterone levels among humans. Aims This study aimed to explore the individual and interactive effects of PM and residential greenness on serum testosterone and progesterone levels among rural Chinese adults. Methods A total of 6017 subjects were recruited from the baseline of the Henan Rural Cohort Study in 2016. Serum testosterone and progesterone were measured with liquid chromatography-tandem mass spectrometry. Particulate matters (PM) (PM1, PM2.5, and PM10) were assessed by machine learning algorithms. Residential greenness was assessed using the normalized difference vegetation index (NDVI) within 500-m, 1000-m, and 3000-m buffers around participants’ residences. The effects of air pollutants and residential greenness and their interaction on serum testosterone and progesterone levels were assessed using linear mixed-effects models with township as a random intercept. Results After adjusting for potential confounding factors, a 1 μg/m3 increase in PM2.5 or PM10 was associated with a 0.037 or 0.030 ng/ml increase in serum testosterone, respectively, in females and with a 0.111 or 0.182 ng/ml decrease in serum progesterone, respectively, in males. A 1 μg/m3 increase in PM1, PM2.5 or PM10 was associated with a 0.222, 0.306, or 0.295 ng/ml decrease in serum progesterone, respectively, among females. Moreover, a 0.1-unit increase in NDVI was associated with a 0.310 ng/ml increase in serum testosterone and a 0.170 ng/ml increased in serum progesterone in males, as well as with a 0.143 ng/ml increase in serum progesterone in females. Interaction effects of PM and residential greenness on serum testosterone and progesterone levels were observed, indicating that the effects of residential greenness on serum testosterone and progesterone were modified by high levels of PM. In addition, physical activity significantly mediated 2.92% of the estimated association between greenness and testosterone levels. Conclusions Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity.

The production of nutraceutical compounds through biosynthetic approaches has received considerable attention in recent years. For example, Menaquinone-7 (MK-7), a sub-type of Vitamin K2, biosynthesized from Bacillus subtilis (B. subtilis), proved to be more efficiently produced than the conventional chemical synthesis techniques. This is possible due to the development of B. subtilis as a chassis cell during the biosynthesis stages. Hence, it is imperative to provide insights on the B. subtilis membrane permeability modifications, biofilm reactors, and fermentation optimization as advanced techniques relevant to MK-7 production. Although the traditional gene-editing method of homologous recombination improves the biosynthetic pathway, CRISPR-Cas9 could potentially resolve the drawbacks of traditional genome editing techniques. For these reasons, future studies should explore the applications of CRISPRi (CRISPR interference) and CRISPRa (CRISPR activation) system gene-editing tools in the MK-7 anabolism pathway.

Background Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. Methods Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. Results The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27–1.30), 1.53 (95% CI: 1.50–1.55), and 1.46 (95% CI: 1.44–1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08–1.10), 1.10 (95% CI: 1.08–1.11), and 1.35 (95% CI: 1.32–1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54–1.42), 1.39% (95% CI: 0.82–1.97), and 0.13% (95% CI: − 1.24 to 1.48), respectively. Conclusion Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate., YC was supported by a Senior Research grant (2019R1A2C1086194) from the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies). YK was supported by JSPS KAKENHI Grant Number JP19K17104. AT was supported by the JSPS Invitational Fellowships for Research in Japan (Grant S18149). YG was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (Grants APP1107107 and APP1163693). AG was supported by the Medical Research Council UK (Grants MR/M022625/1 and MR/R013349/1), by the Natural Environment Research Council UK (Grant NE/R009384/1), and by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). YH was supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency, Japan.

This study was to investigate the effects of dietary zinc (Zn) supplementation on performance, zinc transporter gene expression, and immune function in aged laying hens. In experiment 1, twenty 31-week-old hens (young) and twenty 60-week-old hens (old) with the same genetic background were fed with the same diet for 4 weeks. In experiment 2, a basal diet supplemented with zinc sulfate (ZnS) and zinc glycine chelate (ZnG) at 30, 60, 90, and 120 mg Zn/kg to constitute nine experimental diets. Eight hundred and ten 60-week-old layers were distributed in a completely randomized experimental design with 9 treatments, 6 replicates of 15 birds each, and birds were fed for 10 weeks. In experiment 1, results showed that zinc and metallothionein (MT) concentration in the shell gland of old hens was significantly lower than young layers (P0.05). Zinc transporters ZnT1, 4, 5, 6, and 7 messenger RNA (mRNA) abundance in old layers were significantly lower versus the young (P0.05). In experiment 2, results indicated that dietary zinc supplementation did not significantly affect the laying rate, average feed intake, egg weight, feed conversion efficiency, broken egg rate, or mortality (P0.05). Supplemental ZnG significantly improved eggshell breaking strength than ZnS, with a higher alkaline phosphatase (ALP) activity and more abundant ZnT4 expression in shell gland versus ZnS (P0.05). ZnG supplementation at 90 mg Zn/kg affected the duodenal mucus by significantly increasing ZnT1, 6, 7, ZIP13, and MT-4 mRNA level (P0.05). Zinc level significantly increased bovine serum albumin (BSA) antibody concentration on 14 day after BSA injection (P0.05). Supplementation of ZnG improved eggshell quality of aged layers by upgrading zinc transporter expression in the shell gland and intestine also enhanced humoral immunity.

It is unclear how to develop a model based on the combined satellite data and ground monitoring data to accurately estimate daily NO2 levels. Furthermore, the conventional cross-validation (CV) results represent average levels but the model performance may vary greatly from grid to grid. It is an essential issue to evaluate model's prediction ability in different grids and determine the factors affecting model extrapolating ability, which have never been well examined to date. The aim of this study was to compare the ability of three different methods to estimate the daily NO2 across mainland China during 2014–2016; and to develop a novel two-stage meta-analysis method for exploring the influence of the number and the distribution of nearby sites on grid-level prediction accuracy. For better estimating the daily NO2 level, we developed and compared three methods, including universal kriging model, satellite-based method (Non-linear exposure-lag-response model & Extreme gradient boosting combined technique) and the kriging-calibrated satellite method. For exploring influencing factors, the two-stage meta-analysis method was purposed. The kriging-calibrated satellite method had an overall CV R-square and root mean square error (RMSE) of 0.85 and 7.87μg/m3, better than the Universal Kriging model and the satellite-based method (CV R2 = 0.57 and 0.81). The two-stage meta-analysis method revealed that the model performance did decrease with the sparser distribution of nearby sites. And adding 5 sites within 50 km in the random mode can bring 17.51% improvement in model extrapolating ability. The kriging-calibration can help satellite-based machine learning to provide more accurate NO2 prediction. Our novel evaluation method can provide the suggestion of adding new sites effectively within a limit budget.

BackgroundHeat exposure has been related to increased morbidity and mortality for several health outcomes. There is little evidence whether this is also true for COPD. This study quantified the relationship between ambient heat and hospitalisation for COPD in the Brazilian population.MethodsData on hospitalisations for COPD and weather conditions were collected from 1642 cities during the 2000–2015 hot seasons. A time-stratified, case-crossover design was used for city-specific analyses, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, age group and early/late hot season. Annual change in the association was examined using a random-effect meta-regression model.ResultsThe OR of hospitalisation was 1.05 (95% CI 1.04 to 1.06) for every 5℃ increase in daily mean temperature at the national level, with the effect estimate stronger in the late hot season compared with the early hot season. The effect was similar in women and in men but was greatest for those aged ≥75 years. The association was stronger in the central west and southeast regions and minimal in the northeast. Assuming a causal relationship, 7.2% of admissions were attributable to heat exposure. There was no significant temporal decline in the impact of ambient heat over the 16-year study period.ConclusionIn Brazil, exposure to ambient heat was positively associated with hospitalisation for COPD, particularly during the late hot season. These data add to the growing evidence base implicating global warming as being an important contributor to the future healthcare burden.

Evidence of the short-term effect of SO2 on hospital admissions for cause-specific cardiovascular diseases (CVD) is still limited. This study aimed to examine the short-term associations between SO2 and cause-specific CVD hospital admission in Beijing. A total of 460,938 hospitalizations for total CVD were obtained from electronic hospitalization summary reports from 2013 to 2017. A time series analysis was conducted to investigate the association between SO2 exposure and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF). Stratified analysis was also conducted by age group (18–64 years and ≥65 years), sex and season. A generalized additive quasi-Poisson model was used to examine the associations between SO2 and cause-specific CVD after controlling for seasonality, day of the week, public holidays, and weather conditions. We found an almost linear relationship between the exposure to SO2 and cause-specific CVD admissions. A 10 μg/m3 increase in the two-day average concentration (lag0-1) of SO2 was associated with an increase of 1.38% (95% CI:0.99%; 1.77%) in hospital admission for total CVD, 1.58% (95% CI: 1.16%; 2%) for CHD and 1.69% (95% CI:0.41%; 2.99%) for AF. Nevertheless, a statistically significant association was not observed for admissions for HF. The observed associations in the single-pollutant models were robust to the inclusion of pollutants in the two-pollutant model, but the estimate was attenuated when adjusting for fine particulate matter (PM2.5). No difference in the association was observed for the effect modifiers of sex, season and age. A statistically significant association between hospitalizations and SO2 was observed. The observed association between SO2 and hospitalization might not be independent of fine particulate matter ( PM 2.5 ), and further studies should be conducted to demonstrate the independent effect of SO2.

Purpose We summarized the evidence on the effects of heat and cold exposures on mortality in China. We included studies published on this topic in both Chinese and English, thereby filling a gap in knowledge using data from a country that consists of one-fifth of the world's population. Methods We conducted a systematic search of peer-reviewed studies on the association between daily mean temperature and mortality published from 2001 up to July 2018. We searched one Chinese database (China National Knowledge infrastructure, http://www.cnki.net ) and three English databases (PubMed, Scopus, Web of Science). We converted the effect estimates of heat/cold to rate ratios (RRs) associated with 1° increase/decrease beyond the heat/cold reference temperatures. For studies that provided lag-specific estimates, we used both the maximum and minimum of RR estimates. We calculated summary effect estimates for all-cause and cause-specific mortalities, as well as RRs stratified by sex, age, and socioeconomic status. We also investigated patterns of heat and cold adaptation at different latitudes, and at different reference temperatures. Results In total, 45 articles were included in this systematic review. For every 1° temperature increase/decrease beyond reference points, the rate of non-accidental mortality increased by 2% (RR, 1.02; 95% confidence interval (95% CI [1.01–1.02]) for heat and 4% (RR, 1.04; 95% CI [1.03–1.04]) for cold, respectively; the rate of cardiovascular mortality increased 3% (RR, 1.03; 95% CI [1.03–1.04]) for heat and 6% (RR, 1.06; 95% CI [1.04–1.07]) for cold; the rate of respiratory mortality increased 2% (RR, 1.02; 95% CI [1.01–1.03]) for heat and 2% (RR, 1.02; 95% CI [1.00–1.04]) for cold; the rate of cerebrovascular mortality increased 2% (RR, 1.02; 95% CI [1.02–1.03]) for heat and 3% (RR, 1.03; 95% CI [1.02–1.04]) for cold. We identified a variation in optimal temperature range related to latitude of the residential area, and differences in people's capability to adapt to heat versus cold. Conclusion We found consistent evidence of the association between temperature and mortality, as well as evidence of patterns in human adaptation, and we discussed the implications of our findings.

Background Perfluoroalkyl substances (PFASs) are synthetic chemicals widely used in industry and for commercial products. Their immunomodulatory effects are a growing health concern in children. Hand, Foot and Mouth Disease (HFMD) is a common childhood viral infection, and increased incidence of which has parallel the rise in PFAS exposure in the Asia-Pacific region. Objective We conducted the first study to assess whether prenatal exposure to PFAS was associated with a reduction in HFMD virus antibodies in infants. Methods We enrolled 201 mother-infant pairs from the Guangzhou Birth Cohort Study from July to October 2013. High performance liquid chromatography-mass spectrometry was employed to determine concentrations of specific PFAS isomers in cord blood. Neutralizing antibodies titers were measured against two HFMD viruses, enterovirus 71 (EV71) and coxsackievirus A 16 (CA16), in cord blood serum and blood serum at three months of age. Results Higher umbilical cord blood PFAS concentrations were associated with lower EV71 and CA16 antibody concentrations. A doubling in the composite sum of cord blood PFASs in three month old infants was associated with significant increase in the risk of HFMD antibody concentration below clinical protection level (≥1:8 titers) for CA16 (odds ratio, OR: 2.74 [95% confidence interval (CI): 1.33, 5.61] and for EV71 (OR = 4.55, 95% CI: 1.45, 4.28). This association was higher in boys at three months of age for CA16. Conclusions Our findings suggest that cord blood PFAS exposure is associated with lower HFMD antibody in infancy. Given the widespread nature of PFAS exposures and the high global incidence of HFMD globally, these findings have substantial public health implications and therefore, these associations need to be replicated in a larger study to more definitively address the risk.

Background Previous studies have suggested a potential relationship between temperature variability (TV) and ischaemic heart disease (IHD) but the nature and strength differ between studies. We quantify the association between TV and risk of hospitalization for IHD across Brazilian regions and examine how the relationship varies across important population subgroups. Methods Data on hospitalization for IHD and meteorological parameters were collected from 1814 cities during 2000–2015. TV was defined as the standard deviation of daily minimum and maximum temperatures during exposure days. City-specific estimates were quantified using a time-stratified case-crossover approach, and then pooled at the national level using a random-effect meta-analysis. Stratified analyses were performed by region, sex and three age-groups. Results There were 2,864,904 IHD hospitalizations during 2000–2015. The estimate of TV effect was strongest on 0–1 days' exposure: odds ratio was 1.019 [95% confidence interval (CI): 1.013–1.025] per 5 °C increase in TV. The relationship was stronger in men [1.025 (95%CI: 1.017–1.033)] than in women [1.011 (95%CI: 1.002–1.019)] and in successively older age groups [1.034 (95%CI: 1.018–1.050)]. Regional differences existed, with the association only apparent in the most ageing parts of Brazil. Conclusions Exposure to TV is associated with increased risk of hospitalization for IHD, particularly in men and in older age groups. Our findings add to the growing evidence regarding the potential impact of climatic factors on important health outcomes.

Several studies have attempted to predict ground PM2.5 concentrations using satellite aerosol optical depth (AOD) retrieval. However, over 70%–90% of aerosol retrievals are non-random missing, which limits and biases the estimation. To the best of our knowledge, this issue has not been well resolved to date. The aim of this study was to develop an interpolation technique to handle the missing data retrieval problem and to estimate the daily PM2.5 for a high coverage dataset with 3-km resolution in China by fitting the complex temporal and spatial variations. We developed a two-step interpolation method (i.e., the mixed-effect model and inverse distance weighting technology) to replace the missing values in AOD. Next, the extreme gradient boosting (XGBoost) technique that includes a non-linear exposure-lag-response model (NELRM) was proposed and validated to estimate the daily levels of PM2.5 across China during 2014–2015. After two steps of interpolation, the missing value rate of daily AOD data was reduced from 87.91% to 13.83%. The cross-validation (CV) R-square, root mean square error (RMSE) and mean absolute percentage prediction error (MAPE) of the interpolation were 0.76, 0.10 and 21.41%, respectively. The cross-validation for the prediction of daily PM2.5 resulted in R2 = 0.86, RMSE = 14.98, and MAPE = 23.72%. The results of this study indicate that the two-step interpolation method can largely resolve the non-random missing data problem and that the combined XGBoost methods have a good ability to estimate fine particulate matter concentrations.

Studies worldwide have estimated the number of deaths attributable to long-term exposure to fine airborne particles (PM2.5), but limited information is available on short-term exposure, particularly in China. In addition, most existing studies have assumed that short-term PM2.5-mortality associations were linear. For this reason, the use of linear exposure-response functions for calculating disease burden of short-term exposure to PM2.5 in China may not be appropriate. There is an urgent need for a comprehensive, evidence-based assessment of the disease burden related to short-term PM2.5 exposure in China. Here, we explored the non-linear association between short-term PM2.5 exposure and all-cause mortality in 104 counties in China; estimated county-specific mortality burdens attributable to short-term PM2.5 exposure for all counties in the country and analyzed spatial characteristics of the mortality burden due to short-term PM2.5 exposure in China. The pooled PM2.5-mortality association was non-linear, with a reversed J-shape. We found an approximately linear increased risk of mortality from 0 to 62 μg/m3 and decreased risk from 62 to 250 μg/m3. We estimated a total of 169,862 additional deaths from short-term PM2.5 exposure throughout China in 2015. Models using linear exposure-response functions for the PM2.5-mortality association estimated 32,186 deaths attributable to PM2.5 exposure, which is 5.3 times lower than estimates from the non-linear effect model. Short-term PM2.5 exposure contributed greatly to the death burden in China, approximately one seventh of the estimates from the chronic effect. It is essential and crucial to incorporate short-term PM2.5-related mortality estimations when considering the disease burden attributable to PM2.5 in developing countries such as China. Traditional linear effect models likely underestimated the mortality burden due to short-term exposure to PM2.5. Keywords: PM2.5, Short-term, Mortality burden, Non-linear

Background There is growing recognition of a potential role for environmental and climatic factors in influencing cardiovascular risk. It has been speculated that temperature variability (TV) is a risk factor for cardiac arrhythmia but evidence is limited. Objective To quantify the geographic and demographic variations in the association between TV and hospitalization for cardiac arrhythmia in Brazil during 2000–2015. Methods Data on hospitalization for arrhythmia and weather conditions were collected from 1,814 cities. TV was calculated as the standard deviation of daily maximum and minimum temperatures during exposure days. A time-stratified case-crossover approach was applied to examine the city-specific association between TV and hospitalization for arrhythmia. City-specific estimates were pooled at the national and regional levels using a random-effect meta-analysis. Stratified analyses were conducted by sex, three age-groups (0–64, 65–74 and ≥75 years), and three arrhythmia subtypes (paroxysmal tachycardia, atrial fibrillation and flutter, and other arrhythmias). Results There were 447,667 arrhythmia-related hospitalizations during 2000–2015. The odds ratio of hospitalization per 1 °C increase in TV peaked on 0–1 days’ exposure [1.012 (95% confidence interval: 1.010–1.015)]. There were no substantial differences in effect estimates of TV0-1 by region, age or sex, except for the non-significant association observed in the north. However, women were more affected by prolonged TV exposure than men. For the three arrhythmias subtypes, only paroxysmal tachycardia and other arrhythmias were sensitive to TV. Assuming a causal relationship, 35,813 (95%CI: 18,302−51,665) cases were attributable to TV0-1 in Brazil during 2000–2015, accounting for 8.0% (95%CI: 4.1–11.5%) of hospitalizations for cardiac arrhythmia. Conclusions At a population-level exposure to TV was associated with increased risk of arrhythmia-related hospitalization in Brazil, with the relationship equally distributed across most residents but varied by arrhythmia subtypes. Our findings add to the accumulating evidence-base that climatic factors can influence cardiovascular outcomes in populations.

Epidemiological studies increasingly provide evidence about the adverse health effects of temperature variability (TV), which reflects short-term intra- and inter-day temperature change. However, calculation of TV only considers the temporal variability and lacks spatial variability. This study intends to investigate whether the lack of spatial variability in TV calculations has biased the health effect estimates. We collected daily data from the fine-gridded hourly temperatures and more than 2 million all-cause mortality counts in Zhejiang province in China from 2009 to 2015. A spatiotemporal TV index was developed by calculating the standard deviation of the hourly temperatures based on records from multiple sites. This new index could be compared to the two typical temporal TV indices that are calculated based on the hourly temperatures from one-site and area-average records. The three types of TV are compared using a three-stage analytical approach: district-specific time series Poisson regression, meta-analysis, and calculation of attributable mortality fraction. We observe that both spatiotemporal and temporal TVs produce very similar TV–mortality associations, attributable mortality fractions, and model fits at the district level. For example, the mortality increase associated for every increase of 1 °C during 0–7 exposure days is 1.53% (95% CI: 1.31, 1.73) in spatiotemporal TV, whereas it is 1.48% (95% CI: 1.27, 1.68) and 1.45% (95% CI: 1.24, 1.67) in the one-site and area-average temporal TV, respectively. Thus, time series models using temporal TV index are equally good at estimating the associations between TV and mortality as spatiotemporal TV at the district level in population-based epidemiological studies in China. Epidemiological studies using temperature from one site or the averages of multiple sites in TV calculation will not bias the effect estimates of TV. Our study could provide an important guidance method for future TV-related research in China and even in other countries.

No evidence exists concerning the association between blood pressure and ambient particles with aerodynamic diameter

Backgrounds: Evidence on the association between long-term exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cardiovascular disease (CVD) is scarce in developing countries. Moreover, few studies assessed the role of the PM1 (≤1.0 μm) size fraction and CVD. We investigated the associations between PM1 and PM2.5 and CVD prevalence in Chinese adults. Methods: In 2009, we randomly recruited 24,845 adults at the age of 18–74 years from 33 communities in Northeastern China. CVD status was determined by self-report of doctor-diagnosed CVD. Three-year (2006–08) average concentrations of PM1 and PM2.5 were assigned using a satellite-based exposure. We used spatial Generalized Linear Mixed Models to evaluate the associations between air pollutants and CVD prevalence, adjusting for multiple covariates. Stratified and interaction analyses and sensitivity analyses were also performed. Results: A 10 μg/m3 increase in long-term exposure to ambient PM1 levels was associated a 12% higher odds for having CVD (OR = 1.12; 95% CI = 1.05–1.20). Compared to PM1, association between PM2.5 and CVD was lower (OR = 1.06; 95% CI = 1.01–1.11). No significant association was observed for PM1–2.5 (1–2.5 μm) size fraction (OR = 0.98; 95% CI = 0.85–1.13). Stratified analyses showed greater effect estimates in men and the elder. Conclusions: Long-term PM1 exposure was positively related to CVD, especially in men and the elder. In addition, PM1 may play a greater role than PM2.5 in associations with CVD. Further longitudinal studies are warranted to confirm our findings. Keywords: Particulate matter, Cardiovascular disease, Adults, Chinese, Cross-sectional study

Recently, studies on the application of light-responsive semiconductor nanomaterials for photodynamic therapy (PDT) of non-solid tumors have attracted tremendous attention. Herein, 6.98 nm Ag2S nanoparticles (Ag2S NPs) with excellent aqueous dispersibility, stability, and biocompatibility were synthesized by a facile strategy without any post-modification. In vitro studies indicated that Ag2S NPs could significantly inhibit the growth of human lymphoma cells (Raji cells) compared with hepatoma carcinoma cells (Hep G2 cells) under light irradiation. Further studies revealed that Ag2S NPs could specifically induce the accumulation of intracellular reactive oxidative species in Raji cells under light irradiation, and induce significant disruption of energy metabolism. This finding provides inspiration for the potential application of Ag2S semiconductor nanoparticles as a photosensitizer to significantly and specifically treat human lymphoma through PDT.

Hierarchical ellipsoid-shaped TiO2 porous nanostructures with a high specific surface area and abundant pores are fabricated by the hierarchical assembly of TiO2 nanoparticles via a simple one-pot hydrothermal process. The as-synthesized ellipsoid-shaped TiO2 exhibits significantly enhanced photocatalytic activity for MB degradation compared to P25 under ultraviolet light and sunlight irradiation, respectively.

Background The epidemiological evidence on relationships between long-term exposure to particulate matter and hypertension and blood pressure has been inconclusive. Limited evidence was available for particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) in rural areas of developing countries. Objective This study aimed to investigate the associations between long-term exposure to PM1 and hypertension and blood pressure among rural Chinese population. Methods This study included 39,259 participants who had completed the baseline survey from Henan Rural Cohort. Participants' exposure to PM1 was assessed by a satellite-based spatiotemporal model. The binary logistic regression model was used to examine the association between long-term PM1 exposure and hypertension, and multivariable linear regression model was used to investigate the associations between long-term PM1 exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Moreover, we examined potential effect modifications by demographic, lifestyle and diet factors. Results The mean concentration of PM1 for all participants during the 3-year before baseline survey was 59.98 μg/m3. Each 1 μg/m3 increase in PM1 concentration was significantly associated with an increase of 4.3% [Odds ratio(OR) = 1.043, 95% confidence interval(CI): 1.033, 1.053] in odds for hypertension, an increase of 0.401 mm Hg (95% CI, 0.335, 0.467), 0.328 mm Hg (95% CI, 0.288, 0.369), 0.353 mm Hg (95% CI, 0.307, 0.399) and 0.073 mm Hg (95% CI, 0.030, 0.116) in SBP, DBP, MAP and PP, respectively. Further stratified analyses showed that the effect of PM1 on hypertension and blood pressure could be modified by sex, lifestyle and diet. Conclusions This study suggests that long-term exposure to ambient PM1 increases the risk of hypertension and is associated with elevations in blood pressure in rural Chinese adults, especially in male and those with unhealthy habits., Highlights • Rural cohort participants were exposed to high level of PM1 during the study period. • PM1 was related to increased risk of hypertension and elevated blood pressure. • Males and those with unhealthy habits were more susceptible to the adverse effect.

Background: Most evidences regarding ambient PM2.5 or PM10 (particulate matter of median aerodynamic diameter ≤2.5 μm or ≤10 μm) and preterm birth (PTB) come from western countries which has relatively low PM pollution exposure, and the results are still inconsistent. This study aims to examine whether exposure to high concentrations of PM2.5 or PM10 was associated with PTB (

Background: The evidence for adverse effects of ambient particulate matter (PM) pollution on mental health is limited. Studies in Western countries suggested higher risk of autism spectrum disorder (ASD) associated with PM air pollution, but no such study has been done in developing countries. Methods: A case-control study was performed in Shanghai with a multi-stage random sampling design. Children's exposures to PM1, PM2.5 and PM10 (particulate matter with aerodynamic diameter

Background: Limited evidence is available on the health effects of particulate matter with an aerodynamic diameter of

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change., We thank the participants of the ISIMIP Health workshop in Barcelona in November 2018 where this work was discussed for the first time. This study was supported by the Medical Research Council UK (grant no. MR/M022625/1), the Natural Environment Research Council UK (grant no. NE/R009384/1) and the European Union’s Horizon 2020 Project Exhaustion (grant no. 820655). N.S. was supported by the NIEHS-funded HERCULES Center (P30ES019776). Y.H. was supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan (JPMEERF15S11412). J.J.J.K.J. was supported by Academy of Finland (grant no. 310372). V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant no. PCIN-2017-046) and the German Federal Ministry of Education and Research (grant no. 01LS1201A2). J.K. and A.U. were supported by the Czech Science Foundation (grant no. 20-28560S). J.M. was supported by the Fundação para a Ciência e a Tecnologia (FCT) (SFRH/BPD/115112/2016). S.R. and F.d.R. were supported by European Union’s Horizon 2020 Project EXHAUSTION (grant no. 820655). M.H. was supported by the Japan Science and Technology Agency as part of SICORP, grant no. JPMJSC20E4. Y.G. was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). S.L. was support by the Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). Y.L.L.G. was supported by the Taiwan Ministry of Science and Technology (MOST110-2918-I-002-007) as a visiting academic at the University of Sydney.

Spraying roads with water on a large scale in Chinese cities is one of the supplementary precaution or mitigation actions implemented to control severe air pollution events or heavy haze-fog events in which the mechanisms causing them are not yet fully understood. These air pollution events were usually characterized by higher air humidity. Therefore, there may be a link between this action and air pollution. In the present study, the impact of water spraying on the PM2.5 concentration and humidity in air was assessed by measuring chemical composition of the water, undertaking a simulated water spraying experiment, measuring residues and analyzing relevant data. We discovered that spraying large quantities of tap or river water on the roads leads to increased PM2.5 concentration and humidity, and that daily continuous spraying produces a cumulative effect on air pollution. Spraying the same amount of water produces greater increases in humidity and PM2.5 concentration during cool autumn and winter than during hot summer. Our results demonstrate that spraying roads with water increases, rather than decreases, the concentration of PM2.5 and thus is a new source of anthropogenic aerosol and air pollution. The higher vapor content and resultant humidity most likely create unfavorable meteorological conditions for the dispersion of air pollution in autumn and winter with low temperature.

Background In 2014, the Morwell brown coal mine, located in the Latrobe Valley of South eastern Australia, caught fire covering nearby areas in plumes of smoke over a 6-week period. Aims To investigate the association between exposure to mine fire related air pollution and the risk of mortality. Methods Time series models were used to evaluate the risk of mortality during the first 30 days of the mine fire, when the smoke was most intense, and in the following six months. Associations were also investigated between mine fire related PM2.5 and mortality. Results During the 30-day mine fire period, there was an increased risk of death from injury in the most exposed town of Morwell, however no increased risk was observed for all-cause, cardiovascular or respiratory mortality. In the broader Latrobe Valley, males and residents aged 80 and above were at greatest risk of death from injury during the mine fire. In Morwell, during the six months after the mine fire there was an increased risk of all-cause mortality and death from Ischaemic Heart Disease (IHD). Males and residents aged 80 and above in the broader Latrobe Valley, were at increased risk of death from IHD six months after the fire. Conclusions Coal mine fire exposure was associated with an increase in injury deaths during the mine fire and cardiovascular deaths in the six months after the fire. These findings assist in identifying at risk groups, and improving targeted health advice for future air pollution exposures in the community.

Background Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear. Methods A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM1), ≤2.5 μm (PM2.5) or ≤10 μm (PM10), nitrogen dioxide (NO2)) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots. Results Exposure to single air pollutant (PM1, PM2.5, PM10 or NO2) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed. Conclusion Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect.

There is an established association between air pollution and cardiovascular disease (CVD), which is likely to be mediated by systemic inflammation. The present study evaluated links between long-term exposure to ambient air pollution and high-sensitivity C reactive protein (hs-CRP) in an older Chinese adult cohort (n = 7915) enrolled in the World Health Organization (WHO) study on global aging and adult health (SAGE) China Wave 1 in 2008–2010. Multilevel linear and logistic regression models were used to assess the associations of particulate matter (PM) and nitrogen dioxide (NO2) on log-transformed hs-CRP levels and odds ratios of CVD risk derived from CRP levels adjusted for confounders. A satellite-based spatial statistical model was applied to estimate the average community exposure to outdoor air pollutants (PM with an aerodynamic diameter of 10 μm or less (PM10), 2.5 μm or less (PM2.5), and 1 μm or less (PM1) and NO2) for each participant of the study. hs-CRP levels were drawn from dried blood spots of each participant. Each 10 μg/m3 increment in PM10, PM2.5, PM1, and NO2 was associated with 12.8% (95% confidence interval, (CI): 9.1, 16.6), 15.7% (95% CI: 10.9, 20.8), 10.2% (95% CI: 7.3, 13.2), and 11.8% (95% CI: 7.9, 15.8) higher serum levels of hs-CRP, respectively. Our findings suggest that air pollution may be an important factor in increasing systemic inflammation in older Chinese adults.

Background The prevalence of metabolic syndrome (MetS) rapidly increased over the past decades. However, little evidence exists about the effects of long-term exposure to ambient air pollution on MetS in children and adolescents. Objective This study aims to assess the association between long-term ambient air pollution and the prevalence of MetS in a large population of Chinese children and adolescents. Methods In 2013, a total of 9,897 children and adolescents aged 10 to 18 years were recruited from seven provinces/municipalities in China. MetS was defined based on the recommendation by the International Diabetes Federation (IDF). Satellite based spatio-temporal models were used to estimate exposure to ambient air pollution (including particles with diameters ≤1.0 µm (PM1), ≤2.5 µm (PM2.5), and ≤10 µm (PM10), and nitrogen dioxide (NO2)). Individual exposure was calculated according to 94 schools addresses. After adjustment for a range of covariates, generalized linear mixed-effects models were utilized to evaluate the associations between air pollutants and the prevalence of MetS and its components. In addition, several stratified analyses were examined according to sex, weight status, outdoor physical activity time, and sugar-sweetened beverages (SSBs) intake. Results The prevalence of MetS was 2.8%. The odds ratio of MetS associated with a 10 μg/m3 increase in PM1, PM2.5, PM10 and NO2 was 1.20 (95%CI: 0.99, 1.46), 1.31 (95%CI: 1.05, 1.64), 1.32 (95%CI: 1.08, 1.62), and 1.33 (95%CI: 1.03, 1.72), respectively. Regarding the MetS components, we observed associations between all pollutants and abdominal obesity. In addition, long-term PM1 and NO2 exposures were associated with the prevalence of elevated fasting blood glucose. Stratified analyses detected that the associations between air pollutants and the prevalence of MetS were stronger in boys (Pinteraction Conclusions We found that long-term exposure to PM2.5, PM10, and NO2 were positively associated with the prevalence of MetS in children and adolescents. Our findings may have certain public health implications for some comprehensive strategy of environment improvement and lifestyles changes in order to reduce the burden of non-communicable disease.

Background Air pollution is a potential environmental risk for sleep disturbance. However, the evidence is very limited in China. On the other hand, physical activity (PA) is a preventive behavior that can improve insomnia, but whether PA mitigates the negative impact of air pollution on insomnia is unknown. Methods We obtained data from the baseline of China Multi-Ethnic Cohort (CMEC) survey, and examined the association between air pollution and insomnia, as well as PA's modification effect of on this association. We included 70,668 respondents and assessed insomnia by self-reported symptoms collected using electronic questionnaires. Using satellite data, we estimated the residence-specified, three-year average PM1, PM2.5, PM10 (particulate matter with aerodynamic diameters of ≤1 μm, ≤2.5 μm and 10 μm, respectively), O3 (ozone), and NO2 (nitrogen dioxide) concentrations. We established the associations between air pollutants and insomnia through logistic regression. We evaluated the modification impact of total and domain-specific PA (leisure, occupation, housework, transportation) by introducing an interaction term. Results Positive associations were observed between long-term exposure to PM1, PM2.5, PM10, and O3 and insomnia symptoms, with ORs (95% CI) of 1.09 (1.03–1.16), 1.11 (1.07–1.15), 1.07 (1.05–1.10) and 1.15 (1.11–1.20), respectively. As total PA increased, the ORs of air pollution for insomnia tended to decrease and then rise. We observed varying modification effects of domain-specific PA. With an increase in leisure PA, the ORs for PM2.5 and PM10 significantly declined. However, increased ORs of air pollutants were related to insomnia among participants with higher levels of occupational and housework PA. Conclusion Long-term exposure to higher concentrations of PM1, PM2.5, PM10, and O3 increases the risk of insomnia symptoms. Moderate to high levels of leisure PA alleviate the harmful effects of air pollution on insomnia, while high levels of occupation and housework PA intensify such effects.

Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change., Global warming is expected to increase mortality due to heat stress in many regions. Here, the authors asses how mortality due to high temperatures changes in China changes for different demographic groups and show that heat-related excess mortality is increasing under climate change, a process that is strongly amplified by population ageing.

Rice yield is not only influenced by factors of varieties and managements, but also by environmental factors. In this study, agronomic trait data of rice and climate data in eastern China were collected, and rice yields were predicted using a variety of algorithms, including the non-linear tool of feed-forward backpropagation neural networks (FFBN) and the linear model of partial least squares regression (PLSR). The results showed that both the agronomic traits and the climate data were significantly related with rice yield. The PLSR model showed that covariates occurred among the parameters, and modifications should be considered for climate data-based modelling. The FFBN model demonstrated better prediction performance than that of PLSR, in which the relation coefficient (R2) and root mean square error (RMSE) were 0.611 vs. 0.374 and 0.578 vs. 0.865 ton/ha using climate data, respectively, and 0.742 vs. 0.689 and 0.556 vs. 0.608 using agronomic trait data, respectively. When using fused data the R2 and RMSE improved to 0.843 vs. 0.746 and 0.440 vs. 0.549, respectively. The optimum architecture of the FFBN consisted of one hidden layer with 29 neurons. Therefore, the FFBN algorithm is an effective option for the prediction of rice yield in complex systems of rice production.

Evidence on the health benefits of green space in residential environments is still limited, and few studies have investigated the potential association between blue space and type 2 diabetes mellitus (T2DM) prevalence. This study included 39,019 participants who had completed the baseline survey from the Henan Rural Cohort Study, 2015&ndash, 2017. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were employed to characterize the residential green space, and the distance from the participant&rsquo, s residential address to the nearest water body was considered to represent the residential blue space. Mixed effect models were applied to evaluate the associations of the residential environment with T2DM and fasting blood glucose (FBG) levels. An interquartile range (IQR) increase in NDVI and EVI was significantly associated with a 13.4% (odds ratio (OR): 0.866, 95% Confidence interval (CI): 0.830,0.903) and 14.2% (OR: 0.858, 95% CI: 0.817,0.901) decreased risk of T2DM, respectively. The residential green space was associated with lower fasting blood glucose levels in men (%change, &minus, 2.060 in men vs. &minus, 0.972 in women) and the elderly (%change, &minus, 1.696 in elderly vs. &minus, 1.268 in young people). Additionally, people who lived more than 5 km from the water body had a 15.7% lower risk of T2DM (OR: 0.843, 95% CI: 0.770,0.923) and 1.829% lower fasting blood glucose levels (95% CI: &minus, 2.335%,&minus, 1.320%) than those who lived closer to the blue space. Our findings suggest that residential green space was beneficially associated with T2DM and fasting blood glucose levels. However, further research is needed to explore more comprehensively the relationship between residential blue space and public health.

Interpretation Chewing tobacco remains a substantial public health problem in several regions of the world, and predominantly in south Asia. We found little change in the prevalence of chewing tobacco use between 1990 and 2019, and that control efforts have had much larger effects on the prevalence of smoking tobacco use than on chewing tobacco use in some countries. Mitigating the health effects of chewing tobacco requires stronger regulations and policies that specifically target use of chewing tobacco, especially in countries with high prevalence. Findings In 2019, 273 center dot 9 million (95% uncertainty interval 258 center dot 5 to 290 center dot 9) people aged 15 years and older used chewing tobacco, and the global age-standardised prevalence of chewing tobacco use was 4 center dot 72% (4 center dot 46 to 5 center dot 01). 228 center dot 2 million (213 center dot 6 to 244 center dot 7; 83 center dot 29% [82 center dot 15 to 84 center dot 42]) chewing tobacco users lived in the south Asia region. Prevalence among young people aged 15-19 years was over 10% in seven locations in 2019. Although global agestandardised prevalence of smoking tobacco use decreased significantly between 1990 and 2019 (annualised rate of change: -1 center dot 21% [-1 center dot 26 to -1 center dot 16]), similar progress was not observed for chewing tobacco (0 center dot 46% [0 center dot 13 to 0 center dot 79]). Among the 12 highest prevalence countries (Bangladesh, Bhutan, Cambodia, India, Madagascar, Marshall Islands, Myanmar, Nepal, Pakistan, Palau, Sri Lanka, and Yemen), only Yemen had a significant decrease in the prevalence of chewing tobacco use, which was among males between 1990 and 2019 (-0 center dot 94% [-1 center dot 72 to -0 center dot 14]), compared with nine of 12 countries that had significant decreases in the prevalence of smoking tobacco. Among females, none of these 12 countries had significant decreases in prevalence of chewing tobacco use, whereas seven of 12 countries had a significant decrease in the prevalence of tobacco smoking use for the period. Summary Background Chewing tobacco and other types of smokeless tobacco use have had less attention from the global health community than smoked tobacco use. However, the practice is popular in many parts of the world and has been linked to several adverse health outcomes. Understanding trends in prevalence with age, over time, and by location and sex is important for policy setting and in relation to monitoring and assessing commitment to the WHO Framework Convention on Tobacco Control. Methods We estimated prevalence of chewing tobacco use as part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 using a modelling strategy that used information on multiple types of smokeless tobacco products. We generated a time series of prevalence of chewing tobacco use among individuals aged 15 years and older from 1990 to 2019 in 204 countries and territories, including age-sex specific estimates. We also compared these trends to those of smoked tobacco over the same time period. Findings In 2019, 273 & middot;9 million (95% uncertainty interval 258 & middot;5 to 290 & middot;9) people aged 15 years and older used chewing tobacco, and the global age-standardised prevalence of chewing tobacco use was 4 & middot;72% (4 & middot;46 to 5 & middot;01). 228 & middot;2 million (213 & middot;6 to 244 & middot;7; 83 & middot;29% [82 & middot;15 to 84 & middot;42]) chewing tobacco users lived in the south Asia region. Prevalence among young people aged 15-19 years was over 10% in seven locations in 2019. Although global age standardised prevalence of smoking tobacco use decreased significantly between 1990 and 2019 (annualised rate of change: -1 & middot;21% [-1 & middot;26 to -1 & middot;16]), similar progress was not observed for chewing tobacco (0 & middot;46% [0 & middot;13 to 0 & middot;79]). Among the 12 highest prevalence countries (Bangladesh, Bhutan, Cambodia, India, Madagascar, Marshall Islands, Myanmar, Nepal, Pakistan, Palau, Sri Lanka, and Yemen), only Yemen had a significant decrease in the prevalence of chewing tobacco use, which was among males between 1990 and 2019 (-0 & middot;94% [-1 & middot;72 to -0 & middot;14]), compared with nine of 12 countries that had significant decreases in the prevalence of smoking tobacco. Among females, none of these 12 countries had significant decreases in prevalence of chewing tobacco use, whereas seven of 12 countries had a significant decrease in the prevalence of tobacco smoking use for the period. Interpretation Chewing tobacco remains a substantial public health problem in several regions of the world, and predominantly in south Asia. We found little change in the prevalence of chewing tobacco use between 1990 and 2019, and that control efforts have had much larger effects on the prevalence of smoking tobacco use than on chewing tobacco use in some countries. Mitigating the health effects of chewing tobacco requires stronger regulations and policies that specifically target use of chewing tobacco, especially in countries with high prevalence. For complete list of authors see http://dx.doi.org/10.1016/S2468-2667(21)00065-7

Background Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting. Methods We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure–response curve and evaluated the possibility of a threshold below which health is not affected. Findings Overall, a 1 mg/m3 increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32–1·50) increase in daily total mortality. The pooled exposure–response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure–response curve was steeper at daily CO levels lower than 1 mg/m3, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m3 or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide. Interpretation This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient CO and daily mortality, even at levels well below current air quality guidelines. Further studies are warranted to disentangle its independent effect from other traffic-related pollutants., EU Horizon 2020, UK Medical Research Council, and Natural Environment Research Council

Background: Potential modification of the association between maternal particulate matter (PM) exposure and preterm delivery (PTD) by folic acid (FA) supplementation has not been studied. Objective: We examined whether FA supplementation could reduce the risk of PTD associated with maternal exposure to PM in ambient air during pregnancy. Method: In a cohort study covering 30 of the 31 provinces of mainland China in 2014, 1,229,556 primiparas of Han ethnicity were followed until labor. We collected information on their FA supplementation and pregnancy outcomes and estimated each participant’s exposure to PM with diameters of ≤10μm (PM10), 2.5μm (PM2.5), and 1μm (PM1) using satellite remote-sensing based models. Cox proportional hazard regression models were used to examine interactions between FA supplementation and PM exposures, after controlling for individual characteristics. Results: Participants who initiated FA ≥3 months prior to pregnancy (38.1%) had a 23% [hazard ratio (HR)=0.77 (95% CI: 0.76, 0.78)] lower risk of PTD than women who did not use preconception FA. Participants with PM concentrations in the highest quartile had a higher risk of PTD [HR=1.29 (95% CI: 1.26, 1.32) for PM1, 1.52 (95% CI: 1.46, 1.58) for PM2.5, and 1.22 (95% CI: 1.17, 1.27) for PM10] than those with exposures in the lowest PM quartiles. Estimated associations with a 10-μg/m3 increase in PM1 and PM2.5 were significantly lower among women who initiated FA ≥3 months prior to pregnancy [HR=1.09 (95% CI: 1.08, 1.10) for both exposures] than among women who did not use preconception FA [HR=1.12 (95% CI: 1.11, 1.13) for both exposures; pinteraction

Summary Background Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions. Methods DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985–2015) and future (2020–99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk. Findings The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by −0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2–7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4–10·3% in 2090–99. Interpretation This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health.

Background There has been an increasing interest in the association between ambient temperature and violence and crime, in the context of global warming. We aimed to evaluate the association between daily ambient temperature and intentional homicide—a proxy for overall inter-personal violence. Methods We collected daily weather and crime data from 9 large US cities (Chicago, Detroit, Fort Worth, Kansas City, Los Angeles, Louisville, New York, Tucson and Virginia Beach) from 2007 to 2017. A time-stratified case-crossover design was used. The associations were quantified by conditional logistic regression with distributed lag models, adjusting for relative humidity, precipitation and effects of public holidays. City-specific odds ratios (OR) were used to calculate the attributable fractions in each city. Results Based on 19,523 intentional homicide cases, we found a linear temperature-homicide association. Every 5 °C increase in daily mean temperature was associated with a 9.5% [95% confidence interval (CI): 4.3–15.0%] and 8.8% (95% CI: 1.5–16.6%) increase in intentional homicide over lag 0–7 days in Chicago and New York, respectively. The association was not statistically significant in the other seven cities and seemed to be stronger for cases that happened during the hot season, at night (18:00–06:00) and on the street. During the study period, 8.7% (95%CI: 4.3–12.7%) and 7.1% (95% CI: 1.4–12.0%) intentional homicide cases could be attributed to temperatures above city-specific median temperatures, corresponding to 488 and 316 excess cases in Chicago and New York, respectively. Conclusions Our study suggests that the interpersonal violence might increase with temperature in some US cities. We also provide some insights into the mechanisms and targeted prevention strategies for heat-related violence.

Background: There is increasing interest in the effect of residential greenness on respiratory health in children with inconsistent results. However, there are no studies investigating the association between greenness around schools, a representative environment for children and childhood asthma. Objectives: To investigate the association between greenness surrounding schools and asthma in schoolchildren. Methods: We recruited 59,754 schoolchildren from 94 schools in 2012–2013 from the Seven Northeast Cities Study, China. Greenness surrounding schools was measured using the normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI) at buffers from 30 to 1000 m. Asthma symptoms were collected from validated self-reported questionnaires. Logistic mixed-effects regression models were used to estimate the associations between greenness surrounding school and childhood asthma after adjustment for covariates. Results: We found that greenness surrounding schools in all buffered sizes was negatively associated with the prevalence of asthmatic symptoms in schoolchildren. A 0.1-unit increase in NDVI1000m was associated with lower odds of current asthma (odds ratio: 0.81, 95% confidential interval: 0.75, 0.86) and current wheeze (OR: 0.89, 95% CI: 0.84, 0.94) in children after covariate adjustments. Higher greenness was associated with less asthma symptoms in a dose-response pattern (P for trend < 0.05). The estimated associations appeared to be stronger in children exposure to higher air pollution level. The observed associations varied across seven cities. Conclusion: Our findings suggest beneficial associations of greenness surrounding schools with childhood asthma. Further studies are needed to confirm our results.

Background The association of airborne particulate matter of 1 μm or less (PM1) with fetal growth hasn't been studied. We aimed to investigate the association of PM1 with fetal growth parameters measured via ultrasonography and birth weight. Methods The birth cohort included 18,669 pregnant women who were pregnant between 2014 and 2017 in Tongzhou Maternal and Child Health Hospital of Beijing, China. The predicted PM1 concentration was matched with the residential addresses of each woman. The fetal abdominal circumference (AC), head circumference (HC), femur length (FL) and estimated fetal weight (EFW) were evaluated via ultrasonography, while birth weight was measured at birth. The fetal parameters and birth weight were standardized as gestational-age- and gender-adjusted Z-score. We defined undergrowth of fetal parameters, low birth weight (LBW) and small-for-gestational-age (SGA) as categorized outcomes. Generalized estimating equations and generalized linear regression were used to examine the associations of PM1 with quantitative and categorized outcomes, respectively. Results A 10 μg/m3 increase in PM1 was associated with decrement in the Z-scores of AC [-0.027, 95% confidence intervals (CI): -0.047~ -0.07]EFW (-0.055, 95%CI: -0.075~-0.035). These results remained robust after adjusting nitrogen dioxide and sulphur dioxide. We didn't observe significant results regarding the analyses of undergrowth of all fetal parameters and the analyses of birth weight outcomes. Conclusion This study identified the negative associations between PM1 and fetal parameters in utero. The findings provided robust evidence that strategies for reducing PM1 exposure can prevent early-life health.

The immense problem of missing satellite aerosol retrievals (Aerosol Optical Depth, (AOD)) detrimentally affects the prediction ability of ground-level PM2.5 concentrations and may lead to unavoidable biases. An appropriate missing-imputation method has not been well developed to date. This study developed a two-stage approach (AOD-imputation stage and PM2.5-prediction stage) to predict short-term PM2.5 exposure in mainland China from 2013–2018. At the AOD-imputation stage, geostatistical methods and machine learning (ML) algorithms were examined to interpolate 1 km satellite aerosol retrievals. At the PM2.5-prediction stage, the daily levels of PM2.5 were predicted at a resolution of 1 km, based on interpolated AOD and meteorological data. The statistical performances of the different interpolation methods were comprehensively compared at each stage. The original coverage of retrieved AOD was 15.46% on average. For the AOD-imputation stage, ML methods produced a higher coverage (98.64%) of AOD than geostatistical methods (21.43–87.31%). Among ML algorithms, random forest (RF) or extreme gradient boosted (XG-interpolated) AOD produced better interpolated quality (CV R2 = 0.89 and 0.85) than other algorithms (0.49–0.78), but XGBoost required only 15% of the computing time of RF. For the PM2.5 predicted stage, neither RF-AOD nor XG-AOD could guarantee higher accuracy in PM2.5 estimations (CV R2 = 0.88 (RF or XG-AOD) compared to 0.85 (original)), or more stable spatial and temporal extrapolation (spatial, (temporal) CV R2 = 0.83 (0.83), 0.82 (0.82), and 0.65 (0.61) for RF, XG, and original). For the AOD-imputation stage, the missing-filled efficiency depended more on external information, while the missing-filled accuracy relied more on model structure. For the PM2.5 predicted stage, efficient AOD interpolation (or the ability to eliminate the missing data) was a precondition for the stable spatial and temporal extrapolation, while the quality of interpolated AOD showed less significant improvements. It was found that XG-AOD is a better choice to estimate daily PM2.5 exposure in health assessments.

Background Little is known about the effect of ambient temperature on preterm birth, especially for the trimester-specific effects. Objective To evaluate whether exposure to relatively low or high temperature during pregnancy is associated with increasing risk of preterm birth or not. Method We analysed the data of a birth cohort with 1,281,859 singleton pregnancies during 2013–2014 and matched the home address of each pregnant women to the model based daily meteorological and air pollution data. Then we used the Cox proportional hazard regression models with random effect to estimate the non-linear associations between exposure to relatively low or high temperature at each trimester of pregnancy and the risk of preterm birth, after controlling for air pollution and individual-level covariates. Finding The overall preterm birth rate was 8.1% (104,493 preterm births). Exposure to relatively low or high temperatures during the entire pregnancy significantly increase the risk of preterm birth, with hazard ratios (HRs) [95% confidence intervals (CIs)] of 1.03 (95%CI: 1.02, 1.04) for relatively low (9.1 ℃, the 5th percentile) temperature and 1.55 (95%CI: 1.48, 1.61) for relatively high (23.0 ℃, the 95th percentile) temperature in comparison with the thresholds (12.0 ℃). Pregnant women at the early pregnancy (the 1st and 2nd trimester) are more susceptible to high temperatures while pregnant women at the late pregnancy (the 3rd trimester) are more susceptible to low temperatures. Conclusion These findings provide new evidence that exposure to relatively low or high temperatures during pregnancy increases the risk of preterm birth, which can serve as scientific evidence for prevention of preterm birth.