Search

Background: Dysphagia can lead to serious complications such as aspiration and aspiration pneumonia, timely and effective rehabilitation training can improve the swallowing function of patients. However, the conventional rehabilitation training methods used in clinical settings have shortcomings such as poor adherence of patients. We present the study design of a randomized controlled trial that evaluated whether video-game based swallowing rehabilitation training can effectively improve swallowing in patients with dysphagia and whether it has additional benefits compared with conventional training methods to improve swallowing function and training compliance among patients with dysphagia. Methods: A randomized controlled trial with 4 weeks of intervention and 4 weeks of follow-up will be conducted in a rehabilitation center in Beijing, China. We will enroll 78 patients aged 18–80 years with dysphagia. Participants will be randomly assigned to the experimental group (video-game based swallowing function training) and the control group (conventional swallowing function training). All participants will receive 30 min of training per day, 5 times per week, for a total of 4 weeks. The primary outcome is swallowing function. Secondary outcomes include patients' quality of life, training compliance, and training satisfaction. Outcomes are assessed at baseline (pre-treatment), 4 weeks of treatment (post-treatment), and 8 weeks (follow-up), and the assessor is not aware of the participants' grouping. Discussion: The protocol describes a new rehabilitation training method for dysphagia, which involves participant eligibility recruitment, recruitment strategies, and data analysis plan. The results of the study will inform the rehabilitation training and clinical care management of swallowing function in patients with dysphagia. Trial registration: ClinicalTrials.gov, NCT05978700. Registered on 28 July 2023. [ABSTRACT FROM AUTHOR]

Objective was to evaluate the pharmacokinetic parameters of MP-AzeFlu compared with the commercially available mono-components. Methods: Both studies were a randomized, open-label, three-period, six-sequence, single-dose cross-over trial (William's design) conducted at Beijing Hospital (Beijing, China) in September and October of 2019 in 30 healthy adult male and female volunteers. The natural log transformed parameters: AUC0-tlast, AUC0-∞ and Cmax were analyzed. Results: The comparison of PK parameters between MP-AzeFlu and Aze (commercially available) showed that the LS mean ratios (90% CI) values for, AUC0–tlast, AUC 0–∞ and Cmax were 100.29% (94.31– 106.66%), 100.76% (94.60– 107.32%) and 93.14% (81.47– 106.48%). The comparison of PK parameters between MP-AzeFlu and Flu (commercially available) for the bioavailability evaluation showed that the LS mean ratios (90% CI) values for, AUC0–tlast, AUC 0–∞ and Cmax were 83.48% (69.81– 99.82%), 100.19% (87.34– 114.94%) and 81.91% (68.50– 97.95%). Conclusion: The study results confirm that neither the FLU or the AZE component in the combination product (MP-AzeFlu), nor the existing qualitative and quantitative differences in the formulation between the currently marketed AZE and FLU mono-product, display significant potential to impact the systemic exposure of AZE or FLU in Chinese subjects. [ABSTRACT FROM AUTHOR]

Extensive researches have linked air pollutants with cardiovascular disease (CVD) and respiratory diseases (RD), however, there is limited evidence on causal effects of air pollutants on morbidity of CVD or RD with comorbidities, particularly diabetes mellitus in elder patients. We included hospital admissions for CVD or RD among elder (≥65 years) diabetic patients between 2014 and 2019 in Beijing. A time‐stratified case‐crossover design based on negative‐control exposure was used to assess causal associations of short‐term exposure to air pollutants with CVD and RD among diabetic patients with the maximum lag of 7 days. A random forest regression model was used to calculate the contribution magnitude of air pollutants. A total of 493,046 hospital admissions were recorded. Per 10 μg/m3 uptick in PM1, PM2.5, PM10, SO2, NO2, O3, and 1 mg/m3 in CO was associated with 0.29 (0.05, 0.53), 0.14 (0.02, 0.26), 0.06 (0.00, 0.12), 0.36 (0.01, 0.70), 0.21 (0.02, 0.40), −0.08 (−0.25, 0.09), and 4.59 (0.56, 8.61) causal effect estimator for admission of CVD among diabetic patients, corresponding to 0.12 (0.05, 0.18), 0.09 (0.05, 0.13), 0.05, 0.23 (0.06, 0.41), 0.10 (0.02, 0.19), −0.04 (−0.06, −0.01), and 3.91(1.81, 6.01) causal effect estimator for RD among diabetic patients. The effect of gaseous pollutants was higher than particulate pollutants in random forest model. Short‐term exposure to air pollution was causally associated with increased admission of CVD and RD among elder diabetic patients. Gaseous pollutants had a greater contribution to CVD and RD among elder diabetic patients. Plain Language Summary: Although researches for cardiovascular disease (CVD) and respiratory diseases (RD) with air pollutants are widely reported, there is little evidence for causal associations of air pollution with CVD combined with diabetes mellitus (CVD‐DM) and RD combined with diabetes mellitus (RD‐DM) in elder patients. We included elder hospital admissions (aged ≥65 years) on comorbid CVD‐DM and RD‐DM patients between 2014 and 2019 in Beijing, China, to assess associations and causal inferences between air pollutants with CVD‐DM and RD‐DM. Random forest regression model was used to calculate the contribution magnitude of air pollutants. We found that exposure to air pollution increased admissions of CVD‐DM and RD‐DM in the elderly. Gaseous pollutants had a greater contribution to CVD‐DM and RD‐DM. The finding may lead to policy changes to reduce air pollution concentration, particularly gaseous pollutants to decrease hospital admissions. Key Points: Investigated causal associations of air pollutants on comorbid elderly populationA stable and accurate effect of air pollution was gained base on large sample sizesThe effects of gaseous pollutants are stronger than those of PM for the elderly [ABSTRACT FROM AUTHOR]

As one of the important components of hydrological cycle, evapotranspiration spatial distribution is of great significance to regional water resources planning and rational utilization. This research used Surface Energy Balance System model to estimate the daily evapotranspiration (ET) in Beijing based on Landsat 8 observations. Results showed that the daily ET in Beijing ranged from 3.469 to 5.474 mm/day. ET is known to decrease with the increase of land surface temperature (LST) and to increase with the increase of Normalized Difference Vegetation Index (NDVI). NDVI primarily decreased from the northwest to the southeast. When the NDVI value was 0.4–0.6, the average ET peaked at 4.88 mm/day, and then slightly decreased by 3.7%. The coefficient of determination of NDVI (0.95) was much greater than that of LST (0.30) upon linear fitting, showing LST was not the main factor controlling ET in Beijing. In contrast to the linear fitting results, the spatial correlation between LST and ET is more significant than that between NDVI and ET in the global bivariate spatial analysis, where the absolute value of global bivariate Moran's I of LST (0.51) was higher than that of NDVI (0.21) at a resolution of 150 m. And the univariate spatial autocorrelation indices of LST, ET, and NDVI equaled 0.84, 0.65, and 0.51, respectively. Furthermore, the complex spatial distribution pattern of variables could significantly affect the correlation analysis results. Local bivariate spatial analysis showed that over 60% of the Beijing area had a significant correlation, of which the negative correlation area of LST accounted for about 85%, and the positive correlation area of NDVI accounted for 74%. By improving the correlation analysis accuracy, the regional conditions for the establishment of correlation analysis results were clarified from the overall correlation analysis results. [ABSTRACT FROM AUTHOR]

Background: Prior studies have investigated the association of PM2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM2.5 exposure on the arterial stiffness index.Methods: We used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively.Results: The association between PM2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82-1.50, P = 0.497). There was - 0.16% (95% CI: - 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72-1.37%) increase in baPWV annually with each increment of 10 μg/m3 average PM2.5 concentration.Conclusions: Long-term exposure to PM2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness. [ABSTRACT FROM AUTHOR]

Background: Few studies have considered the interplay between commuting mode and air pollution on obesity. The aim of this study was to examine whether workplace air pollutants exposure modifying the associations between different commuting mode and obesity. Methods: A cross-sectional study of workers in Beijing was conducted in 2016. The study sample comprised 10,524 participants aged 18 to 65 years old. Outcomes were defined as overall obesity (BMI≥ 28 kg/m2) and abdominal obesity (WC ≥ 85 cm in men and WC ≥ 80 cm in women). Commuting modes were divided into walking, cycling, bus, subway, and car or taxi. Logistic regression models were used to estimate odds ratios relating commuting mode to overall and abdominal obesity and stratified by gender, controlling for covariates. Results: The association between commuting mode and obesity was more strongly in men than women. In the fully adjusted models, compared with car or taxi commuters, cycling (men: OR=0.37, 95% CI=0.20 to 0.68) or bus (men: OR=0.58, 95% CI=0.36 to 0.94) counterparts had a lower risk of overall obesity. Compared with car or taxi commuters, walking (men: OR=0.57, 95% CI=0.36 to 0.91), bus (men: OR=0.59, 95% CI=0.39 to 0.89), or subway (men: OR=0.59, 95% CI=0.39 to 0.89) counterparts had a lower risk of abdominal obesity. We observed significant interactions between exposure PM10 and cycling on overall obesity in men. After adjusting for air pollutants, the association between commuting mode and obesity was slightly strengthened. Conclusion: This study findings indicate that active (walking or cycling) or public (bus or subway) commuting modes were protected factors for overall and abdominal obesity among men. Air pollutants do not obscure the benefits of active or public commuting for obesity. These associations support the policy for increasing active or public commuting as a strategy to reduce the prevalence of obesity. [ABSTRACT FROM AUTHOR]

Two parallel field studies were conducted simultaneously at both urban and rural sites in Beijing from 1 to 29 November 2016. An online single-particle chemical composition analysis was used as a tracer system to investigate the impact of heating activities and the formation of haze events. Central heating elevated EC-Nit (elemental carbon-nitrate), EC-Nit-Sul (EC-nitrate-sulfate), and ECOC-Nit (ECOC: internal-mixed elemental carbon and organic carbon) levels by 1.5–2.0 times due to the increased use of coal in the urban areas. However, in the rural areas, residential heating, which mainly consumes low-quality coal, and biomass burning elevated ECOC-Nit-Sul, NaK-Nit, and OC-Sul levels by 1.2–1.5 times. Four severe haze events (hourly PM 2.5 > 200 µ g m -3) occurred at both sites during the studies. In each event, a pattern of transport and accumulation was found. In the first stage of the pattern, particles were regionally transported from the south and southwest and accumulated under air stagnation, creating significant secondary formation, then PM 2.5 was elevated to 300 µ g m -3. At both sites, the severe haze occurred due to different patterns of local emission, transport, and secondary processes. At Pinggu (PG), the sulfate-rich residential coal burning particles were dominant. The regional transport between PG and Peking University (PKU) was simulated using the Weather Research and Forecasting HYbrid Single-Particle Lagrangian Integrated Trajectory (WRF-HYSPLIT) model, confirming that the transport from PG to PKU was significant, but PKU to PG occurred occasionally. These cases can explain the serious air pollution in the urban areas of Beijing and the interaction between urban and rural areas. This study can provide references for enhancing our understanding of haze formation in Beijing. [ABSTRACT FROM AUTHOR]

Two single-particle aerosol mass spectrometers (SPAMSs) were deployed simultaneously at an urban and a rural site in Beijing during an intensive field campaign from 1 to 29 November 2016 to investigate the source and process of airborne particles in Beijing. In the first part of this research, we report the single-particle chemical composition, mixing state, and evolution at both sites. A total of 96 % and 98 % of collected particles were carbonaceous at the urban and rural sites, respectively. Five particle categories, including elemental carbon (EC), organic carbon (OC), internal-mixed EC and OC (ECOC), potassium-rich (K-rich), and metals, were observed at both sites. The categories were partitioned into particle types depending on different atmospheric processing stages. A total of 17 particle types were shared at both sites. In the urban area, nitrate-containing particle types, such as EC-Nit (Nit: nitrate) and ECOC-Nit, were enriched especially at night, sulfate-containing particles were transported when wind speed was high, and ECOC-Nit-Sul (Sul: sulfate) were mostly aged locally. In sum, these processed particles added up to 85.3 % in the urban areas. In the rural area, regional particles were abundant, but freshly emitted ECOC and OC had distinct patterns that were pronounced at cooking and heating times. Biomass burning, traffic, and coal burning were major sources of particulate matter (PM 2.5) in both rural and urban areas. Moreover, particles from the steel industry located in the south were also identified. In summary, the chemical composition of urban and rural particle types was similar in Beijing; the urban particles were influenced significantly by rural processing and transport. The work is useful to understand the evolution of urban and rural particles in Beijing during winter. [ABSTRACT FROM AUTHOR]

Beijing has suffered from heavy local emissions as well as regional transport of air pollutants, resulting in severe atmospheric fine-particle (PM 2.5) pollution. This study developed a combined method to investigate source types of PM 2.5 and its source regions during winter 2016 in Beijing, which include the receptor model (positive matrix factorization, PMF), footprint and an air quality model. The PMF model was performed with high-time-resolution measurements of trace elements, water soluble ions, organic carbon and elemental carbon using online instruments during the wintertime campaign of the Air Pollution and Human Health in a Chinese Megacity – Beijing (APHH-Beijing) program in 2016. Source types and their contributions estimated by PMF model using online measurements were linked with source regions identified by the footprint model, and the regional transport contribution was estimated by an air quality model (the Nested Air Quality Prediction Model System, NAQPMS) to analyze the specific sources and source regions during haze episodes. Our results show that secondary and biomass-burning sources were dominated by regional transport, while the coal combustion source increased with local contribution, suggesting that strict control strategies for local coal combustion in Beijing and a reduction of biomass-burning and gaseous precursor emissions in surrounding areas were essential to improve air quality in Beijing. The combination of PMF with footprint results revealed that secondary sources were mainly associated with southern footprints (53 %). The northern footprint was characterized by a high dust source contribution (11 %), while industrial sources increased with the eastern footprint (10 %). The results demonstrated the power of combining receptor model-based source apportionment with other models in understanding the formation of haze episodes and identifying specific sources from different source regions affecting air quality in Beijing. [ABSTRACT FROM AUTHOR]

Context: Understanding how landscape components affect the urban heat islands is crucial for urban ecological planning and sustainable development. Objective: The purpose of this study was to quantify the spatial pattern of land surface temperatures (LSTs) and associated heat fluxes in relation to land-cover types in Beijing, China, using portable infrared thermometers, thermal infrared imagers, and the moderate resolution imaging spectroradiometer. Methods: The spatial differences and the relationships between LSTs and the hierarchical landscape structure were analyzed with in situ observations of surface radiation and heat fluxes. Results: Large LST differences were found among various land-use/land-cover types, urban structures, and building materials. Within the urban area, the mean LST of urban impervious surfaces was about 6-12 °C higher than that of the urban green space. LSTs of built-up areas were on average 3-6 °C higher than LSTs of rural areas. The observations for surface radiation and heat fluxes indicated that the differences were caused by different fractions of sensible heat or latent heat flux in net radiation. LSTs decreased with increasing elevation and normalized difference vegetation index. Conclusions: Variations in building materials and urban structure significantly influenced the spatial pattern of LSTs in urban areas. By contrast, elevation and vegetation cover are the major determinants of the LST pattern in rural areas. To alleviate urban heat island intensity, urban planners and policy makers should pay special attention to the selection of appropriate building materials, the reasonable arrangement of urban structures, and the rational design of landscape components. [ABSTRACT FROM AUTHOR]

Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM 2.5 and PM 10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM 2.5 corresponded to 1.91% (95% CI: 1.33–2.49%), 2.16% (95% CI: 1.08–3.25%), and 1.92% (95% CI: 1.46–2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0–8 days, lag 8 days, and lag 8 days. The effect size of PM 2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM 10 were 3.86% (95% CI: 2.48–5.27%), 3.73% (95% CI: 1.72–5.79%), and 3.92% (95% CI: 2.65–5.21%), respectively, at lag 0–13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM 10 on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM 2.5 was higher in patients with T2D than those without T2D. [Display omitted] • Short-term PM exposures were associated with increased admissions for RD and for RD with and without T2D. • The effect of PM 2.5 on RD was significantly higher in patients with T2D than those without T2D. • Significant difference could be found between three different RD groups for effects of PM 10 on RD without T2D. • E-R curves varied by sex, age and T2D conditions for the associations between PM and RD. [ABSTRACT FROM AUTHOR]

Fine particulate matter (PM 2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM 2.5 concentrations in Beijing during the 2013–2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM 2.5 concentrations based on long-term monitoring data. The results illustrated that PM 2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM 2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM 2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM 2.5 and gaseous pollutants (SO 2 , NO 2 , and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM 2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this. Image 1 • PM 2.5 concentrations decreased during 2013–2018. • Wind speed was the major factor affecting the distribution of PM 2.5. • Trace of precipitation had essentially no effect on reducing PM 2.5. • Vehicle exhaust emissions were an important source of PM 2.5 pollution. [ABSTRACT FROM AUTHOR]

Despite the significant role water-soluble organic carbon (WSOC) plays in climate and human health, sources and formation mechanisms of atmospheric WSOC are still unclear; especially in some heavily polluted areas. In this study, near real-time WSOC measurement was conducted in Beijing for the first time with a particle-into-liquid-sampler coupled to a total organic carbon analyzer during the springtime, together with collocated online measurements of other chemical components in fine particulate matter with a 1 h time resolution, including elemental carbon (EC), organic carbon (OC), multiple metals, and water-soluble ions. Good correlations of WSOC with primary OC, as well as carbon monoxide, indicated that major sources of WSOC were primary instead of secondary during the study period. The positive matrix factorization model-based source apportionment results quantified that 68 ± 19% of WSOC could be attributed to primary sources, with predominant contributions by biomass burning during the study period. This finding was further confirmed by the estimate with the modified EC-tracer method, suggesting significant contribution of primary sources to WSOC. However, the relative contribution of secondary source to WSOC increased during haze episodes. The WSOC/OC ratio exhibited similar diurnal distributions with O3 and correlated well with secondary WSOC, suggesting that the WSOC/OC ratio might act as an indicator of secondary formation when WSOC was dominated by primary sources. This study provided evidence that primary sources could be major sources of WSOC in some polluted megacities, such as Beijing. From this study, it can be seen that WSOC cannot be simply used as a surrogate of secondary organic aerosol, and its major sources could vary by season and location. [ABSTRACT FROM AUTHOR]

Background: Air pollution and cardiovascular disease are increasing problems in China. However, the short-term association between fine particulate matter (PM2.5) and cardiovascular disease (CVD) is not well documented. The purpose of this study is to estimate the short-term effects of PM2.5 on CVD admissions in Beijing, China.Methods: In total, 460,938 electronic hospitalization summary reports for CVD between 2013 and 2017 were obtained. A generalized additive model using a quasi-Poisson distribution was used to investigate the association between exposure to PM2.5 and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) after controlling for the season, the day of the week, public holidays, and weather conditions. A stratified analysis was also conducted for age (18-64 and ≥ 65 years), sex and season.Results: For every 10 μg/m3 increase in the PM2.5 concentration from the previous day to the current (lag 0-1) there was a significant increase in total CVD admissions (0.30, 95% CI: 0.20, 0.39%), with a strong association for older adults (aged ≥65 years), CHD (0.34, 95% CI: 0.22 to 0.45%) and AF (0.29, 95% CI, 0.03 to 0.55%). However, the observed increased risk was not statistically significant for HF hospitalizations. The associations in the single-pollutant models were robust to the inclusion of other pollutants in a two-pollutant model. No differences were found after stratification by sex and season.Conclusions: Exposure to PM2.5 increased the risk of hospitalizations from CVD, especially for CHD, and appeared to have more influence in the elderly. Precautions and protective measures and efforts to reduce exposure to PM2.5 should be strengthened, especially for the elderly. [ABSTRACT FROM AUTHOR]

Due to the lack of black carbon (BC) measurement data in some cases, elemental carbon (EC) is often used as a surrogate of BC, with a simple assumption that they are interchangeable. Such assumption will inevitably lead to uncertainties in radiative forcing estimation and health impact assessment. In order to quantitatively and systematically evaluate the relationship between BC and EC as well as factors responsible for their difference, 3-year collocated equivalent BC (eBC) and EC measurements with 1-h resolution were performed in Beijing, China continuously from 2016 to 2019. EBC concentration was measured by the multi-wavelength aethalometer (AE-33) based on optical analysis, while EC concentration was determined by semi-continuous OC/EC analyzer with thermal-optical method. The results showed that around 90% of eBC concentration was higher than that of EC, with average difference between eBC and EC as 1.21 μg m−3 (accounting for 33% of average eBC in Beijing). EBC and EC concentrations exhibited strong correlation (r = 0.90) during the whole study period, but the slopes (or eBC/EC ratio) and correlation coefficients varied across seasons (spring: 1.67 and 0.94; summer: 0.91 and 0.65; fall: 1.15 and 0.88; winter: 1.09 and 0.91, respectively). Based on the information from shell/core ratios by Single Particle Soot Photometer (SP2), source apportionment results by positive matrix factorization model, and chemical composition of PM 2.5 , the differences between eBC and EC concentrations were found to be primarily related to BC aging process and secondary components as evidenced by strong positive correlation with secondary species (e.g., secondary organic carbon and nitrate). This study provided seasonal specific conversion factors of eBC and EC in Beijing and helpful reference for other areas, which will contribute new knowledge of carbonaceous aerosol and reduce uncertainty in assessing future climate change and health studies of BC. • About 90% of eBC mass were higher than EC in Beijing based on 3-year measurement. •EBC and EC were strongly correlated whereas eBC/EC ratios varied with season. •The difference between eBC and EC was related to BC aging and secondary species. [ABSTRACT FROM AUTHOR]

Evidence of the short-term effect of SO 2 on hospital admissions for cause-specific cardiovascular diseases (CVD) is still limited. This study aimed to examine the short-term associations between SO 2 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 SO 2 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 SO 2 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 SO 2 and cause-specific CVD admissions. A 10 μg/m3 increase in the two-day average concentration (lag0-1) of SO 2 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 (PM 2.5). No difference in the association was observed for the effect modifiers of sex, season and age. A statistically significant association between hospitalizations and SO 2 was observed. The observed association between SO 2 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 SO 2. • SO 2 has adverse short-term effects of on total and cause-specific cardiovascular disease (CVD) hospital admission. • No difference of association was found for effect modifier of sex, season and age. • The association between SO 2 and cause-specific CVD admission might not be independent of PM 2.5. [ABSTRACT FROM AUTHOR]

• A physical model test based on cross passage freezing was conducted. • A hydro-thermal coupling model of AGF was proposed. • The effect of four indicators on formation of frozen wall was investigated. Artificial ground freezing is an environmentally friendly and reliable method for ground improvement during subway cross passage construction under variable hydrological conditions. However, natural or induced seepage flow influences significantly the closure of frozen wall, as it supplies a substantial source of heat. In this study, a physical model test was conducted based on the freezing project of a subway cross passage in Beijing Subway Line 19. A series of thermistors were installed in some representative locations to measure the temperature distribution and further calculate power demand. Besides, a hydro-thermal coupling model of freezing process under seepage conditions was derived to consider the variations of physical and thermodynamic parameters of the porous media and the latent heat of ice/water phase transition. The numerical approach was validated by the experimental results. Furthermore, four crucial indicators affecting the closure time during AGF process were quantitatively evaluated. The results showed that the closure time at seepage velocities of 0, 25.6 and 51.2 m/d were respectively 60, 110 and 441 min. Nevertheless, it was impossible to form continuous frozen bodies at 76.8 m/d. Among these indicators, the seepage velocity had the greatest effect on the thickness and shape of frozen body, while seepage temperature had the least impact. [ABSTRACT FROM AUTHOR]

Exposure to ambient air pollution is the largest environmental source of global disease burden. Accurate assessment of air pollutant exposure at finely-resolved spatial and temporal scales is critical for valid estimation of health effects. Limitations of exposure assessment approaches include computational burden and unreliable or complex input data. We aimed to develop an accurate, easy-to-use, high-resolution statistical model to estimate ambient PM 2.5 concentrations in Beijing. We implemented a model that estimates long- and short-term trends in pollutant concentrations based on observations from regulatory monitors, geographic covariates, and spatial smoothing. It also allows for inclusion of spatiotemporal covariates. We used observations from 19 monitors around Beijing and 90 geographic covariates, including road density, meteorological covariates, population and building density, land use types, topography, and vegetation cover to produce predictions of daily PM 2.5 concentrations for 2015–2017. The model yields predictions at any geographic point, and here we summarize results for a 500m × 500m scale. The daily and long-term average cross validated R 2 were 0.96 and 0.93, with RMSE of 13.1 and 1.7, respectively. The addition of temperature as a spatiotemporal covariate did not change the results materially. Over the study period, annual and seasonal PM 2.5 concentrations in Beijing declined substantially, although they remained high relative to recommended level by WHO. We developed an easy-to-use, less computationally-intensive statistical model utilizing readily available input data to provide highly accurate estimates of PM 2.5 concentrations in Beijing at a fine spatiotemporal scale. Model predictions have already been used in a publicly available mobile application designed to provide exposure estimates for epidemiological analyses of the effects of PM 2.5 among residents of Beijing. [Display omitted] • We built an accurate, less computationally-intensive fine-scale spatiotemporal PM 2.5 model. • Beijing's ambient PM 2.5 levels declined over 2015–2017, but remain high. • Current epidemiologic applications include a publicly available mobile application. [ABSTRACT FROM AUTHOR]

[Display omitted] • The first comprehensive description of the relationship between air pollution and hospital admissions, length of stay, and costs for patients with cardiovascular disease with comorbid diabetes mellites. • First application of WHO 2021 air quality standards to a real-world study. • PM 2.5 and PM 10 are positively associated with hospital admissions, hospital cost and length of hospital stay for patients with cardiovascular disease with comorbid diabetes mellites. • Policy changes to reduce air pollutants exposure may reduce cardiovascular disease with comorbid diabetes mellites admissions and substantial savings in health care spending and hospital stay. Evidence on the effects of the air pollutants on the hospital admissions, hospital cost and length of stay (LOS) among patients with comorbidities remains limited in China, particularly for patients with cardiovascular diseases and comorbid diabetes mellitus (CVD-DM). We collected daily data on CVD-DM patients from 242 hospitals in Beijing between 2014 and 2019. Generalized additive model was employed to quantify the associations between admissions, LOS, and hospital cost for CVD-DM patients and air pollutants. We further evaluated the attributable risk posed by air pollutants to CVD-DM patients, using both Chinese and WHO air quality guidelines as reference. Per 10 ug/m3 increase of particles with an aerodynamic diameter < 2.5 μm (PM 2.5), particles with an aerodynamic diameter < 10 μm (PM 10), sulfur dioxide (SO 2), nitrogen dioxide (NO 2), carbonic oxide (CO) and ozone (O 3) corresponded to a 0.64% (95% CI : 0.57 to 0.71), 0.52% (95% CI : 0.46 to 0.57), 0.93% (95% CI : 0.67 to 1.20), 0.98% (95% CI : 0.81 to 1.16), 1.66% (95% CI : 1.18 to 2.14) and 0.53% (95% CI : 0.45 to 0.61) increment for CVD-DM patients' admissions. Among the six pollutants, particulate pollutants (PM 2.5 and PM 10) in most lag days exhibited adverse effects on LOS and hospital cost. For every 10 ug/m3 increase in PM 2.5 and PM 10 , the absolute increase with LOS will increase 62.08 days (95% CI : 28.93 to 95.23) and 51.77 days (95% CI :22.88 to 80.66), respectively. The absolute increase with hospital cost will increase 105.04 Chinese Yuan (CNY) (95% CI : 49.27 to 160.81) and 81.76 CNY (95% CI : 42.01 to 121.51) in PM 2.5 and PM 10 , respectively. Given WHO 2021 air quality guideline as the reference, PM 2.5 had the maximum attributable fraction of 3.34% (95% CI : 2.94% to 3.75%), corresponding to an avoidable of 65,845 (95% CI : 57,953 to 73,812) patients with CVD-DM. PM 2.5 and PM 10 are positively associated with hospital admissions, hospital cost and LOS for patients with CVD-DM. Policy changes to reduce air pollutants exposure may reduce CVD-DM admissions and substantial savings in health care spending and LOS. [ABSTRACT FROM AUTHOR]

There has been increasing concern about the health effects of air pollution in China, and many measures have been implemented to control air pollution. To investigate the impacts of air quality improvement on mortality from non-accidental causes (NAD), cardiovascular disease (CD), and respiratory disease (RD), a longitudinal comparative study was conducted in Beijing. This study investigated the effects of air pollutants on outcomes across five periods (stages 1–5). Health effect data from stage1–5 (1990–2013) were obtained through a systematic literature search of studies published before 2021. Daily atmospheric pollutant, meteorological, and cause-specific death data were collected to determine the effects in stage 5 (2015–2017). Poisson generalized additive models were used to analyze the associations between short-term exposure to air pollutants and mortality. Random-effects meta-analysis models were used to estimate the pooled effects at each stage. The effects of changes in air quality were analyzed through a difference-in-differences approach. Our results indicate that the absolute change of concentrations of sulfur dioxide (SO 2), nitrogen dioxide (NO 2), and particulate matter with aerodynamic diameter≤ 10 μm (PM 10) and≤ 2.5 μm (PM 2.5) decreased by up to 42%, 10%, 33%, and 15% (stage 5), respectively. The effects of SO 2 on deaths from CD and RD decreased by up to 2.76% and 1.43% (stage 3). The effects of NO 2 on mortality from NAD, CD, and RD decreased by up to 0.39%, 0.74%, and 0.37% (stage 5). The effects of PM 10 on death decreased by up to 0.11% (stage 3). The effects of PM 2.5 on deaths from CD and RD decreased by up to 0.33% and 0.13% (stage 5). The results indicate that continued improvements in air quality have reduced the acute impact of air pollutants on population health. [Display omitted] • It's a longitudinal comparative study on air quality and mortality in 1990–2017. • Beijing have consistently reduced the concentration of SO 2 , NO 2 , PM 10 , and PM 2.5. • Continuous improvements in air quality decreased the relative risk of death. [ABSTRACT FROM AUTHOR]