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Ozone pollution is increasingly recognized as a serious environmental threat that exacerbates dementia risks, including Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Amid rapid industrialization, China faces significant air quality challenges. However, there has been a scarcity of detailed studies assessing the health and economic impacts of ozone pollution on these conditions. This study aims to address this gap by utilizing the BenMap-CE tool and incorporating parameters obtained from systematic reviews of epidemiological studies, official statistics, and weighted averages, to accurately quantify the effects of ozone exposure in China. This research evaluated the health and economic burdens at both national and provincial levels, focusing on the additional impacts attributed to increased ozone levels. The results reveal that in 2023, compared to 2015, ozone pollution contributed to approximately 110,000 new cases (5.6 per 10,000) of AD and 1.6 million new cases (81.7 per 10,000) of MCI, imposing significant economic costs of about US $1200 million for AD and US $18,000 million for MCI, based on 2015 dollar values. Additionally, our projections indicate that reducing the 2023 ozone concentrations to 70 μg/m 3 could significantly curb these conditions, potentially preventing over 210,000 new AD cases (10.7 per 10,000) and 2.9 million (148.1 per 10,000) MCI cases. Such reductions are projected to yield substantial economic benefits, estimated at US $2200 million for AD and US $34,000 million for MCI (2015 dollar values). These findings underscore the profound implications of ozone pollution on public health and the economy in China, highlighting the urgent need for effective ozone management strategies to mitigate these impacts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This data article describes the "Typical Regional Activity Patterns" (TRAP) dataset, which is based on the Tackling Key Problems in Air Pollution Control Program. In order to explore the interaction between air pollution and physical activity, we collected activity patterns of 9,221 residents with different occupations and lifestyles for three consecutive days in typical regions (Jinan and Baoding) where air pollutant concentrations were higher than those in neighboring areas. The TRAP dataset consists of two aspects of information: demographic indicators (personal information, occupation, personal habits, and living situation) and physical activity pattern data (activity location and intensity); additionally, the exposure measures of physical activity patterns are included, which data users can match to various endpoints for their specific purpose. This dataset provides evidence for exploring the attributes of activity patterns of residents in northern China and for interdisciplinary researchers to develop strategies and measures for health education and health promotion.

Published literature considering the association between ambient air pollution and blood pressure is highly inconsistent, which may be explained by the different proportions of susceptible subpopulations. We hypothesized that hypertensive patients are more sensitive to air pollution due to the disruption of neurohumoral system. The study aimed to reveal the association between PM 2.5 and its carbon components and blood pressure, and whether this association is modified by hypertension status. We conducted a panel study in Beijing, China. Four repeated measurements were performed from 2016 to 2018. Linear mixed-effects models and generalized additive mixed models were performed to investigate the associations between PM 2.5 and its carbon components and blood pressure. Subgroup analyses were performed by hypertension status to reveal potential effect modification. Among hypertensive patients, for every 1 μg/m 3 increment of PM 2.5 , TC, OC, and EC in 1-day to 2-day MA, SBP increased from 0.16 mmHg (95% CI, 0.03 to 0.29) to 6.75 mmHg (95% CI, 2.82 to 10.68), and PP increased from 0.14 mmHg (95% CI, 0.02 to 0.26) to 6.03% (95% CI, 2.46 to 9.59%), but no significant association was observed among non-hypertensive subjects. The p values for the interaction between pollutants and hypertension status in 1-day to 2-day MA were less than 0.05. These findings suggest that hypertensive patients may be more susceptible to the adverse effects of air pollution than non-hypertensive subjects, which might provide guidance to hypertensive patients living in areas with high levels of particle pollution., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Lipidemic effect of air pollutants are still inconsistent and their joint effects are neglected. Meanwhile, identified inflammation pathways in animal have not been applied in epidemiological studies, and beneficial effect of residential greenness remained unclear. Therefore, we used data from typically air-polluted Chinese cities to answer these questions. Particulate matter (PM) with a diameter of ≤ 1 µm (PM 1 ), PM with a diameter of ≤ 2.5 µm (PM 2.5 ), PM with a diameter of ≤ 10 µm (PM 10 ), sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) were predicted by space-time extremely randomized trees model. Residential greenness was reflected by Normalized Difference Vegetation Index (NDVI). Total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured, and atherogenic coefficient (AC) and TG/HDL-C (TGH) ratio were calculated to indicate lipid metabolism. Generalized additive mixed model and quantile g-computation were respectively conducted to investigate individual and joint lipidemic effect of air pollutants. Covariates including demographical characteristics, living habits, meteorological factors, time trends, and disease information were considered to avoid confounding our results. Complement C3 and high-sensitivity C-reactive protein (hsCRP) were analyzed as potential mediators. Finally, association between NDVI and lipid markers were explored. We found that long-term air pollutants exposure were positively associated with lipid markers. Complement C3 mediated 54.72% (95% CI: 0.30, 63.10) and 72.53% (95% CI: 0.65, 77.61) of the association between PM 1 and TC and LDL-C, respectively. We found some significant associations of lipid markers with NDVI 1000 m rather than NDVI 500 m . BMI, disease status, smoke/drink habits are important effect modifiers. Results are robust in sensitive analysis. Our study indicated that air pollutants exposure may detriment lipid metabolism and inflammation may be the potential triggering pathways, while greenness may exert beneficial effects. This study provided insights for the lipidemic effects of air pollution and greenness., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Limited evidence suggests the association of air pollutants with a series of diabetic cascades including inflammatory pathways, glucose homeostasis disorder, and prediabetes and diabetes. Subclinical strategies for preventing such pollutants-induced effects remain unknown., Methods: We conducted a cross-sectional study in two typically air-polluted Chinese cities in 2018-2020. One-year average PM 1 , PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 were calculated according to participants' residence. GAM multinomial logistic regression was performed to investigate the association of air pollutants with diabetes status. GAM and quantile g-computation were respectively performed to investigate individual and joint effects of air pollutants on glucose homeostasis markers (glucose, insulin, HbA1c, HOMA-IR, HOMA-B and HOMA-S). Complement C3 and hsCRP were analyzed as potential mediators. The ABCS criteria and hemoglobin glycation index (HGI) were examined for their potential in preventive strategy., Results: Long-term air pollutants exposure was associated with the risk of prediabetes [Prevalence ratio for O 3 (PR_O 3 ) = 1.96 (95% CI: 1.24, 3.03)] and diabetes [PR_PM 1  = 1.18 (95% CI: 1.05, 1.32); PR_PM 2.5  = 1.08 (95% CI: 1.00, 1.16); PR_O 3  = 1.35 (95% CI: 1.03, 1.74)]. PM 1 , PM 10 , SO 2 or O 3 exposure was associated with glucose-homeostasis disorder. For example, O 3 exposure was associated with increased levels of glucose [7.67% (95% CI: 1.75, 13.92)], insulin [19.98% (95% CI: 4.53, 37.72)], HOMA-IR [34.88% (95% CI: 13.81, 59.84)], and decreased levels of HOMA-S [-25.88% (95% CI: -37.46, -12.16)]. Complement C3 and hsCRP played mediating roles in these relationships with proportion mediated ranging from 6.95% to 60.64%. Participants with HGI ≤ -0.53 were protected from the adverse effects of air pollutants., Conclusion: Our study provides comprehensive insights into air pollutant-associated diabetic cascade and suggests subclinical preventive strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Evidence on the hypertensive effects of long-term air pollutants exposure are mixed, and the joint hypertensive effects of air pollutants are also unclear. Sparse evidence exists regarding the modifying role of residential greenness in such effects., Methods: A cross-sectional study was conducted in typically air-polluted areas in northern China. Particulate matter with diameter < 1 μm (PM 1 ), particulate matter with diameter < 2.5 μm (PM 2.5 ), particulate matter with diameter < 10 μm (PM 10 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), and ozone (O 3 ) were predicted by space-time extremely randomized trees model. We used the Normalized Difference Vegetation Index (NDVI) to reflect residential green space. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were examined. We also calculated the pulse pressure (PP) and mean arterial pressure (MAP). Generalized additive model and quantile g-computation were, respectively, conducted to investigate individual and joint effects of air pollutants on blood pressure. Furthermore, beneficial effect of NDVI and its modification effect were explored., Results: Long-term air pollutants exposure was associated with elevated DBP and MAP. Specifically, we found a 10-μg/m 3 increase in PM 2.5 , PM 10 , and SO 2 were associated with 2.36% (95% CI: 0.97, 3.76), 1.51% (95% CI: 0.70, 2.34), and 3.54% (95% CI: 1.55, 5.56) increase in DBP; a 10-μg/m 3 increase in PM 2.5 , PM 10 , and SO 2 were associated with 1.84% (95% CI: 0.74, 2.96), 1.17% (95% CI: 0.52, 1.83), and 2.43% (95% CI: 0.71, 4.18) increase in MAP. Air pollutants mixture (one quantile increase) was positively associated with increased values of DBP (8.22%, 95% CI: 5.49, 11.02) and MAP (4.15%, 95% CI: 2.05, 6.30), respectively. These identified harmful effect of air pollutants mainly occurred among these lived with low NDVI values. And participants aged ≥50 years were more susceptible to the harmful effect of PM 2.5 and PM 10 compared to younger adults., Conclusions: Our study indicated the harmful effect of long-term exposure to air pollutants and these effects may be modified by living within higher green space place. These evidence suggest increasing residential greenness and air pollution control may have simultaneous effect on decreasing the risk of hypertension., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Mei, Zhao, Zhou, Zhao, Xu, Li, Li and Xu.)

Background: Pulmonary embolism (PE) is a life-threatening condition. Few studies have evaluated the relationship between air pollution and PE, and these results have been inconsistent. Therefore, our study aimed to investigate the association between air pollutant exposure and the risk of hospitalization due to PE., Materials and Methods: Daily PE admissions, meteorological data, and ambient pollution data from January 1, 2015, to December 31, 2018, were collected in Beijing. A quasi-Poisson regression model combined with time-stratified case-crossover design and a distributed lag nonlinear model was used to determine the effect of air pollutant exposure on PE admission. To examine the stability of air pollutants' effects, multi-pollutant analyses were performed. Stratified analyses by age and sex were further conducted., Results: There were 5060 PE admissions during the study period, with an estimated incidence of 6.5 per 100,000. PM 2.5 , PM 10 , SO 2 , O 3 and CO exposures were significantly associated with elevated risk of PE hospitalization. The highest cumulative risks were observed at a lag of 0-28 days for PM 2.5 (relative risk [RR] = 1.056, 95% confidence intervals [CI]: 1.015-1.098), PM 10 (RR = 1.042, 95%CI: 1.010-1.075), and CO (RR = 1.466, 95%CI: 1.127-1.906), at a lag of 0-27 days for SO 2 (RR = 1.674, 95%CI: 1.200-2.335), and at a lag of 0-4 days for O 3 (RR = 1.019, 95%CI: 1.001-1.038). All associations mentioned above except O 3 remained significant in multi-pollutant models. Stratified analyses showed that women and those aged ≥65 years people were more sensitive to PM 10 and CO exposure than men and those aged <65 years. The effect of PM 2.5 exposure was statistically significant in all subgroups., Conclusions: Exposure to PM 2.5 , PM 10 , SO 2 , and CO showed a positive association with PE hospitalization. High-risk PE groups should take special precautions on days with poor air quality., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Severe surface ozone pollution has become widespread in China. To protect public health, Chinese scientific communities and government agencies have striven to mitigate ozone pollution. However, makers of pollution mitigation policies rarely consider epidemiological research, and communication between epidemiological researchers and the government is poor. Therefore, this article reviews the current mitigation policies and the National Ambient Air Quality Standard (NAAQS) for ozone from an epidemiological perspective and proposes recommendations for researchers and policy makers on the basis of epidemiological evidence. We review current nationwide ozone control measures for mitigating ozone pollution from four dimensions: the integration of ozone and particulate matter control, ozone precursors control, ozone control in different seasons, and regional cooperation on the prevention of ozone pollution. In addition, we present environmental and epidemiological evidence and propose recommendations and discuss relevant ozone metrics and the criteria values of the NAAQS. We finally conclude that the disease burden attributable to ozone exposure in China may be underestimated and that the epidemiological research regarding the health effects of integrating ozone and particulate matter control is insufficient. Furthermore, atmospheric volatile organic compounds are severely detrimental to health, and related control policies are urgently required in China. We recommend a greater focus on winter ozone pollution and conclude that the health benefits of regional cooperation on ozone control and prevention are salient. We argue that daily average ozone concentration may be a more biologically relevant ozone metric than those currently used by the NAAQS, and accumulating epidemiological evidence supports revision of the standards. This review provides new insight for ozone mitigation policies and related epidemiological studies in China., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Diabetes mellitus (DM) is a common chronic disease worldwide. Ambient air pollution has long been proven to be associated with type 2 diabetes mellitus (T2DM) progression, but the underlying mechanism is not clear yet. In addition, previous studies mainly focused on the prevention of healthy people against the incidence of T2DM. We designed a panel study including two follow-ups and enrolled 39 patients with T2DM living in Beijing. Linear mixed model was fitted to assess the association between two pairs of variables (ambient air pollution exposure and C3 levels, ambient air pollution exposures and T2DM index). Mediation analysis of C3 between ambient air pollution exposure and indicators of T2DM progression was conducted. We found that PM2.5 exposures is are negatively associated with serum complement C3. Given that C3 might act as a protector of pancreas β cell, PM2.5 exposures could accelerate disease in T2DM populations. No mediation effects were found. This study reveals that exposures to PM2.5 can cause progression of diseases among T2DM populations.

Due to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM 10 ) and nitrogen dioxide (NO 2 ) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM 10 and NO 2 , and meteorological factors from January 1, 2009, to December 31, 2010, in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM 10 and NO 2 on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM and the strongest effects were identified for 2-day moving average lag 0-1. For every 10 μg/m 3 increases in concentrations of PM 10 and NO 2 , the corresponding daily cardiovascular mortality increases in 0.31% (95%CI 0.15%, 0.46%) and 1.63% (95%CI 1.11%, 2.13%), respectively. The death risk associated with air pollutants varied across different geographic districts in Beijing. We found spatially varied adverse effects of air pollution on cardiovascular deaths in Beijing. But there was insufficient evidence to show the significant spatial heterogeneity in mortality effects of PM 10 and NO 2 in this study.

Accurate spatial information of PM 2.5 is critical for air pollution control and epidemiological studies. Land use regression (LUR) models have been widely used for predicting spatial distribution of ground PM 2.5 . However, the predicted PM 2.5 spatial patterns of a LUR model has not been adequately examined due to limited ground observations. The increasing aerosol optical depth (AOD) products might be an approximation of spatially continuous observation across large areas. This study established the relationship between seasonal 1 km × 1 km MAIAC AOD and observed ground PM 2.5 in Beijing, and then seasonal PM 2.5 maps were predicted based on AOD. Seasonal LUR models were also developed, and both the AOD and LUR models were validated by hold-out monitoring sites. Finally, the spatial patterns of LUR models were comprehensively verified by the above AOD PM 2.5 maps. The results showed that AOD alone could be used directly to predict the spatial distribution of ground PM 2.5 concentration at seasonal level (R 2  ≥ 0.53 in model fitting and testing), which was comparable with the capability of LUR models (R 2  ≥ 0.81 in model fitting and testing). PM 2.5 maps derived from the two methods showed similar spatial trend and coordinated variations near traffic roads. Large discrepancies could be observed at urban-rural transition areas where land use characters varied quickly. Variable and buffer size selection was critical for LUR model as they dominated the spatial patterns of predicted PM 2.5 . Incorporating AOD into LUR model could improve model performance in spring season and provide more reliable results during testing., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Investments, especially fixed asset investments, greatly affect carbon dioxide (CO 2 ) emissions. When investments are concentrated in regions with high CO 2 emissions and high fossil energy consumption, the CO 2 emission reduction targets in these areas are difficult to reach in the short term, and the cost of CO 2 emission abatement is high. The current CO 2 emission regulations focus on existing production activities and consumption behaviors. However, whether an investment, which may affect CO 2 emissions in the long term, is effectively inhibited by CO 2 emission regulations has not been investigated in previous studies. Using panel data from 30 provinces in China between 2003 and 2012, we tested whether the amount of provincial investment was constrained or promoted by the provincial CO 2 emission regulations by creating a panel model with provincial samples. The results revealed that CO 2 emission regulations did not inhibit the growth of an investment, but they stimulated investments to varying degrees in different provinces. A relatively positive result is that provinces with stronger CO 2 emission regulations exhibited a relatively small contribution to investment promotion, while provinces with weaker CO 2 reduction policies demonstrated a relatively large contribution to investment growth. We also found that investment was correlated with the growth rate of the gross domestic product (GDP) in the northeastern and western provinces. Finally, we proposed policy implications based on the utilization of policy tools from the perspectives of investment, energy structure, and local protectionism.

There is limited evidence showing the mortality effects of temperature variability (TV) on cardiovascular diseases. The joint effects between TV and air pollutants are also less well-established. This study aims to assess the effect modification of TV-cardiovascular mortality by air pollutants in three Chinese cities (Beijing, Nanjing and Chengdu). Data of daily mortality, air pollutants and meteorological factors from 2008 to 2011 was collected from each city. TV was calculated as the standard deviation of daily maximum and minimum temperatures over exposure days. The city-specific effect estimates of TV on cardiovascular mortality were calculated using a quasi-Poisson regression model, adjusting for potential confounders (e.g., seasonality and temperature). An interaction term of TV and a three-level air pollutants stratum indicator was included in the models. Effect modifications by air pollutants were assessed by comparing the estimates of TV's effect between pollutant stratums and calculating the corresponding 95% confidential interval of the differences. Multivariate meta-analysis was conducted to obtain the pooled estimates. The data showed that TV was associated with increased risk of cardiovascular mortality, especially for longer TV exposure days (0-8 days, TV08). This association was still observed after adjusting for air pollutants on current day or the previous two days. Stronger estimates were observed in females, but no significant difference between males and females was detected, indicating the absence of evidence of effect modification by gender. Estimates of TV-cardiovascular mortality varied across two season periods (warm and cool season) and age groups, but the evidence of effect modification by age and seasons was absent. Regarding the effect modification of TV-cardiovascular mortality association by air pollutants, a significant effect modification was identified for PM 10, but not for NO 2 and SO 2 in the whole population for all TV exposure days. This finding also persisted in subgroups, specifically in females and the elderly., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Fine particulate matters with aerodynamic diameters smaller than 2.5 micrometers (PM2.5) have been a critical environmental problem in China due to the rapid road vehicle growth in recent years. To date, most methods available to estimate traffic contributions to ambient PM2.5 concentration are often hampered by the need for collecting data on traffic volume, vehicle type and emission profile., Objective: To develop a simplified and indirect method to estimate the contribution of traffic to PM2.5 concentration in Beijing, China., Methods: Hourly PM2.5 concentration data, daily meteorological data and geographic information were collected at 35 air quality monitoring (AQM) stations in Beijing between 2013 and 2014. Based on the PM2.5 concentrations of different AQM station types, a two-stage method comprising a dispersion model and generalized additive mixed model (GAMM) was developed to estimate separately the traffic and non-traffic contributions to daily PM2.5 concentration. The geographical trend of PM2.5 concentrations was investigated using generalized linear mixed model. The temporal trend of PM2.5 and non-linear relationship between PM2.5 and meteorological conditions were assessed using GAMM., Results: The medians of daily PM2.5 concentrations during 2013-2014 at 35 AQM stations in Beijing ranged from 40 to 92 μg/m³. There was a significant increasing trend of PM2.5 concentration from north to south. The contributions of road traffic to daily PM2.5 concentrations ranged from 17.2% to 37.3% with an average 30%. The greatest contribution was found at AQM stations near busy roads. On average, the contribution of road traffic at urban stations was 14% higher than that at rural stations., Conclusions: Traffic emissions account for a substantial share of daily total PM2.5 concentrations in Beijing. Our two-stage method is a useful and convenient tool in ecological and epidemiological studies to estimate the traffic contribution to PM2.5 concentrations when there is limited information on vehicle number and types and emission profile.

In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter < 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) and the risk of respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction., (Copyright © 2014 Elsevier B.V. All rights reserved.)

In recent decades, ambient air pollution has been an important public health issue in Beijing, but little is known about air pollution and health effects after the 2008 Beijing Olympics. We conduct a time-series analysis to evaluate associations between daily mortality (nonaccidental, cardiovascular and respiratory mortality) and the major air pollutants (carbon monoxide, nitrogen dioxide and particulate matter less than 10 µm in aerodynamic diameter) in Beijing during the two years (2009,2010) after the 2008 Beijing Olympics. We used generalized additive model to analyze relationship between daily mortality and air pollution. In single air pollutant model with two-day moving average concentrations of the air pollutants, increase in their interquartile range (IQR) associated with percent increase in nonaccidental mortality, 2.55 percent [95% confidence interval (CI): 1.99, 3.11] for CO, 2.54 percent (95% CI: 2.00, 3.08) for NO2 and 1.80 percent (95% CI: 1.21, 2.40) for PM10, respectively; increases in the IQR of air pollutant concentrations associated with percent increase in cardiovascular mortality, 2.88 percent (95% CI: 2.10,3.65) for CO, 2.63 percent (95% CI: 1.87, 3.39) for NO2 and 1.72 percent (95% CI: 0.88, 2.55) for PM10, respectively; and increase in IQR of air pollutant concentrations associated with respiratory mortality, 2.39 percent (95% CI: 0.68, 4.09) for CO, 1.79 percent (95% CI: 0.11, 3.47) for NO2 and 2.07 percent (95% CI: 0.21, 3.92) for PM10, respectively. We used the principal component analysis to avoid collinearity of varied air pollutants. In addition, the association stratified by sex and age was also examined. Ambient air pollution remained a significant contributor to nonaccidental and cardiopulmonary mortalities in Beijing during 2009,2010.

Few case-crossover studies were conducted in China to investigate the acute health effects of air pollution. We conducted a time-stratified case-crossover analysis to examine the association between air pollution and daily mortality in Anshan, a heavily-polluted industrial city in northeastern China. Daily mortality, air pollution, and weather data in 2004-2006 in Anshan were collected. Time-stratified case-crossover approach was used to estimate the effect of air pollutants (PM(10), SO(2), NO(2) and CO) on total and cardiopulmonary mortality. Controls were selected as matched days of the week in the same month. Potential effect modifiers, such as gender and age, were also examined. We found significant associations between air pollution and daily mortality from cardiovascular diseases in Anshan. A 10μg/m(3) elevation of 2-day moving average (lag 01) concentration in PM(10), SO(2), NO(2) and CO corresponded to 0.67% (95% CI: 0.29%, 1.04%), 0.38% (95% CI: -0.06%, 0.83%), 2.11% (95% CI: 0.22%, 4.00%) and 0.04% (95% CI: 0.01%, 0.07%) increase of cardiovascular mortality. The associations for total and respiratory mortality were generally positive but statistically insignificant. The air pollution health effects were significantly modified by age, but not by gender. Conclusively, our study showed that short-term exposure to air pollution was associated with increased cardiovascular mortality in Anshan. These findings may have implications for local environmental and social policies., (Copyright © 2010 Elsevier B.V. All rights reserved.)

Published literature considering the association between ambient air pollution and blood pressure is highly inconsistent, which may be explained by the different proportions of susceptible subpopulations. We hypothesized that hypertensive patients are more sensitive to air pollution due to the disruption of neurohumoral system. The study aimed to reveal the association between PM2.5 and its carbon components and blood pressure, and whether this association is modified by hypertension status. We conducted a panel study in Beijing, China. Four repeated measurements were performed from 2016 to 2018. Linear mixed-effects models and generalized additive mixed models were performed to investigate the associations between PM2.5 and its carbon components and blood pressure. Subgroup analyses were performed by hypertension status to reveal potential effect modification. Among hypertensive patients, for every 1 μg/m3 increment of PM2.5, TC, OC, and EC in 1-day to 2-day MA, SBP increased from 0.16 mmHg (95% CI, 0.03 to 0.29) to 6.75 mmHg (95% CI, 2.82 to 10.68), and PP increased from 0.14 mmHg (95% CI, 0.02 to 0.26) to 6.03% (95% CI, 2.46 to 9.59%), but no significant association was observed among non-hypertensive subjects. The p values for the interaction between pollutants and hypertension status in 1-day to 2-day MA were less than 0.05. These findings suggest that hypertensive patients may be more susceptible to the adverse effects of air pollution than non-hypertensive subjects, which might provide guidance to hypertensive patients living in areas with high levels of particle pollution. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is a common chronic disease worldwide. Ambient air pollution has long been proven to be associated with type 2 diabetes mellitus (T2DM) progression, but the underlying mechanism is not clear yet. In addition, previous studies mainly focused on the prevention of healthy people against the incidence of T2DM. We designed a panel study including two follow-ups and enrolled 39 patients with T2DM living in Beijing. Linear mixed model was fitted to assess the association between two pairs of variables (ambient air pollution exposure and C3 levels, ambient air pollution exposures and T2DM index). Mediation analysis of C3 between ambient air pollution exposure and indicators of T2DM progression was conducted. We found that PM2.5 exposures is are negatively associated with serum complement C3. Given that C3 might act as a protector of pancreas β cell, PM2.5 exposures could accelerate disease in T2DM populations. No mediation effects were found. This study reveals that exposures to PM2.5 can cause progression of diseases among T2DM populations. [ABSTRACT FROM AUTHOR]

The association between the particulate matters with aerodynamic diameter ≤ 2.5 μm (PM2.5) and daily respiratory deaths, particularly the concentration-response pattern, has not been fully examined and established in China. We conducted a systematic review of time-series studies to compile information on the associations between PM2.5 concentration and respiratory deaths and used metaregression to assess the concentration-response relationship. Out of 1,957 studies screened, eleven articles in English and two articles in Chinese met the eligibility criteria. For single-day lags, per 10 μg/m3 increase in PM2.5 concentration was associated with 0.30 [95% confidence interval (CI): 0.10, 0.50] percent increase in daily respiratory deaths; for multiday lags, the corresponding increase in respiratory deaths was 0.69 (95% CI: 0.55, 0.83) percent. Difference in the effects was observed between the northern cities and the south cities in China. No statistically significant concentration-response relationship between PM2.5 concentrations and their effects was found. With increasingly wider location coverage for PM2.5 data, it is crucial to further investigate the concentration-response pattern of PM2.5 effects on respiratory and other cause-specific mortality for the refinement and adaptation of global and national air quality guidelines and targets. [ABSTRACT FROM AUTHOR]

Evidence of combined mortality effects of multi-pollutant on cardiovascular diseases (CVD) and the corresponding exposure-response (ER) relationship is limited. In this paper, we examined the association between four ambient air pollutants (i.e., fine particulate matter, PM 2.5 , particulate matter, PM 10 , nitrogen dioxide, NO 2 , and sulfur dioxide, SO 2 .) and CVD mortality and the corresponding ER relationship after incorporating the potential interaction among the multiple pollutants. Bayesian kernel machine regression (BKMR) was used to evaluate the ER relationship and to explore the interactions between pollutants. The results showed that PM 10 and SO 2 were dominant pollutants from 0 to 2 days, while PM 2.5 and NO 2 had strong effect on CVD mortality from 3 to 4 days. Generally, PM 2.5 and NO 2 had the similar ER relationship across different moving average concerning the CVD mortality. For the interaction among the multiple pollutants, we found that there is no interaction between particle pollutants (i.e. PM 2.5 and PM 10 ) and gaseous pollutants (i.e.NO 2 and SO 2 ). On the contrary, there might be an interaction between PM 2.5 and PM 10 though this interaction was detected by visually comparing the slopes of ER curves of a given particle pollutant at different levels of the other particle pollutant. But there is a lack of statistical significance test for this interaction. This study suggests that different ambient air pollutants might have the dominant effect on CVD deaths during different moving average, though there might not be statistical significant interactions among the ambient air pollutants in present study. [ABSTRACT FROM AUTHOR]

Abstract: Ambient carbon monoxide (CO) is an air pollutant primarily generated by traffic. CO has been associated with increased mortality and morbidity in developed countries, but few studies have been conducted in Asian developing countries. In the China Air Pollution and Health Effects Study (CAPES), the short-term associations between ambient CO and daily mortality were examined in three Chinese cities: Shanghai, Anshan and Taiyuan. Poisson regression models incorporating natural spline smoothing functions were used to adjust for long-term and seasonal trend of mortality, as well as other time-varying covariates. Effect estimates were obtained for each city and then for the cities combined. In both individual-city and combined analysis, significant associations of CO with both total non-accidental and cardiovascular mortality were observed. In the combined analysis, a 1mg/m3 increase of 2-day moving average concentrations of CO corresponded to 2.89% (95%CI: 1.68, 4.11) and 4.17% (95%CI: 2.66, 5.68) increase of total and cardiovascular mortality, respectively. CO was not significantly associated with respiratory mortality. Sensitivity analyses showed that our findings were generally insensitive to alternative model specifications. In conclusion, ambient CO was associated with increased risk of daily mortality in these three cities. Our findings suggest that the role of exposure to CO and other traffic-related air pollutants should be further investigated in China. [Copyright &y& Elsevier]