Maternal Exposure to PM2.5 and the Risk of Congenital Heart Defects in 1.4 Million Births: A Nationwide Surveillance-Based Study.

BACKGROUND: Evidence remains limited about the association of maternal exposure to ambient fine particulate matter (airborne particles with an aerodynamic diameter ≤2.5 µm [PM2.5]) with fetal congenital heart defects (CHDs) in highly polluted regions, and few studies have focused on preconception exposure. METHODS: Using a nationwide surveillance-based case-control design in China, we examined the association between maternal exposure to PM2.5 during periconception (defined as 3 months before conception until 3 months into pregnancy) and risk of CHD in offspring. The study included 1 434 998 births involving 7335 CHDs from 2014 through 2017 on the basis of the National Population-Based Birth Defects Surveillance System, covering 30 provinces, municipalities, or municipal districts in China. We assigned maternal PM2.5 exposure during the periconception period to each participant using satellite-based PM2.5 concentrations at 1-km spatial resolution. Multilevel logistic regression models were used to calculate the multivariable-adjusted odds ratio and 95% CI for CHDs in offspring associated with maternal PM2.5 exposure, and the exposure-response association was investigated using restricted cubic spline analysis. Subgroup or sensitivity analyses were conducted to identify factors that may modify the association. RESULTS: The average maternal exposure to PM2.5 levels across all participants was 56.51 µg/m3 (range, 10.95 to 182.13 µg/m3). For each 10 µg/m³ increase in maternal PM2.5 exposure, the risk of CHDs in offspring was increased by 2% (odds ratio, 1.02 [95% CI, 1.00 to 1.05]), and septal defect was the most influenced subtype (odds ratio, 1.04 [95% CI, 1.01 to 1.08]). The effect of PM2.5 on CHD risk was more pronounced during the preconception period. Mothers <35 years of age, those living in northern China, and those living in low-income areas were more susceptible to PM2.5 exposure than their counterparts (all P<0.05). PM2.5 exposure showed a linear association with total CHDs or specific CHD types. CONCLUSIONS: High maternal PM2.5 exposure, especially during the preconception period, increases risk of certain types of CHD in offspring. These findings are useful for CHD prevention and highlight the public health benefits of improving air quality in China and other highly polluted regions.

Fine Particulate Matter Exposure, Genetic Susceptibility, and the Risk of Incident Stroke: A Prospective Cohort Study.

BACKGROUND: Both genetic factors and environmental air pollution contribute to the risk of stroke. However, it is unknown whether the association between air pollution and stroke risk is influenced by the genetic susceptibilities of stroke and its risk factors. METHODS: This prospective cohort study included 40 827 Chinese adults without stroke history. Satellite-based monthly fine particulate matter (PM2.5) estimation at 1-km resolution was used for exposure assessment. Based on 534 identified genetic variants from genome-wide association studies in East Asians, we constructed 6 polygenic risk scores for stroke and its risk factors, including atrial fibrillation, blood pressure, type 2 diabetes, body mass index, and triglyceride. The Cox proportional hazards model was applied to evaluate the hazard ratios and 95% CIs for the associations of PM2.5 and polygenic risk score with incident stroke and the potential effect modifications. RESULTS: Over a median follow-up of 12.06 years, 3147 incident stroke cases were documented. Compared with the lowest quartile of PM2.5 exposure, the hazard ratio (95% CI) for stroke in the highest quartile group was 2.72 (2.42-3.06). Among individuals at high genetic risk, the relative risk of stroke was 57% (1.57; 1.40-1.76) higher than those at low genetic risk. Although no statistically significant interaction was found, participants with both the highest PM2.5 and high genetic risk showed the highest risk of stroke, with ≈4× that of the lowest PM2.5 and low genetic risk group (hazard ratio, 3.55 [95% CI, 2.84-4.44]). Similar upward gradients were observed in the risk of stroke when assessing the joint effects of PM2.5 and genetic risks of blood pressure, type 2 diabetes, body mass index, atrial fibrillation, and triglyceride. CONCLUSIONS: Long-term exposure to PM2.5 was associated with a higher risk of incident stroke across different genetic susceptibilities. Our findings highlighted the great importance of comprehensive assessment of air pollution and genetic risk in the prevention of stroke.

Outdoor fine particulate matter exposure and telomere length in humans: A systematic review and meta-analysis.

Although the association between changes in human telomere length (TL) and ambient fine particulate matter (PM2.5) has been documented, there remains disagreement among the related literature. Our study conducted a systematic review and meta-analysis of epidemiological studies to investigate the health effects of outdoor PM2.5 exposure on human TL after a thorough database search. To quantify the overall effect estimates of TL changes associated with every 10 µg/m3 increase in PM2.5 exposure, we focused on two main topics, which were outdoor long-term exposure and prenatal exposure of PM2.5. Additionally, we included a summary of short-term PM2.5 exposure and its impact on TL due to limited data availability. Our qualitative analysis included 20 studies with 483,600 participants. The meta-analysis showed a statistically significant association between outdoor PM2.5 exposure and shorter human TL, with pooled impact estimates (ß) of -0.12 (95% CI: -0.20, -0.03, I2= 95.4%) for general long-term exposure and -0.07 (95% CI: -0.15, 0.00, I2= 74.3%) for prenatal exposure. In conclusion, our findings suggest that outdoor PM2.5 exposure may contribute to TL shortening, and noteworthy associations were observed in specific subgroups, suggesting the impact of various research variables. Larger, high-quality studies using standardized methodologies are necessary to strengthen these conclusions further.

Long-term exposure to air pollution and incident non-alcoholic fatty liver disease and cirrhosis: A cohort study.

BACKGROUND AND AIMS: Epidemiological evidence regarding the association of air pollution with the risk of non-alcoholic fatty liver disease (NAFLD) is limited. This study was to examine the associations of long-term exposure to various air pollutants and overall air pollution with risk of incident NAFLD as well as cirrhosis, a major liver-related morbidity for NAFLD. METHODS: Included were 456 687 UK residents. Air pollution data included PM2.5 , PM2.5-10 , PM10 , NO2 and NOx . A weighted air pollution score was also generated from PM10 and NOx . Cox proportional hazard models were employed to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: We identified 4978 cases of NAFLD and 1575 cases of incident cirrhosis, over a median follow-up of 11.9 years. PM2.5 , PM10 , NO2 and NOx exposures contributed to the excess risk of NAFLD associated with air pollution score; and the corresponding adjusted HRs (95% CI) were 1.10 (1.05, 1.14), 1.14 (1.09, 1.20), 1.19 (1.13, 1.24) and 1.11 (1.07, 1.15), respectively, for each interquartile range increase in the above specific air pollutants. Similar patterns were also indicated for cirrhosis risk. Alcohol consumption was an effect modifier for the association between air pollution score and NAFLD risk, whereas body mass index modified the association for cirrhosis risk. CONCLUSION: Long-term exposure to air pollution was associated with risks of NAFLD and cirrhosis among the UK population.

Association of Long-Term Exposure to Ambient Fine Particulate Matter with Atherosclerotic Cardiovascular Disease Incidence Varies across Populations with Different Predicted Risks: The China-PAR Project.

Previous studies have established a significant link between ambient fine particulate matter (PM2.5) exposure and atherosclerotic cardiovascular disease (ASCVD) incidence, but whether this association varies across populations with different predicted ASCVD risks was uncertain previously. We included 109,374 Chinese adults without ASCVD at baseline from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project. We obtained PM2.5 data of participants' residential address from 2000 to 2015 using a satellite-based spatiotemporal model. Participants were classified into low-to-medium and high-risk groups according to the ASCVD 10-year and lifetime risk prediction scores. Hazard ratios (HRs) and 95% confidence intervals (CIs) for PM2.5 exposure-related incident ASCVD, as well as the multiplication and additive interaction, were calculated using stratified Cox proportional hazard models. The additive interaction between risk stratification and PM2.5 exposure was estimated by the synergy index (SI), the attributable proportion due to the interaction (API), and the relative excess risk due to interaction (RERI). Over the follow-up of 833,067 person-years, a total of 4230 incident ASCVD cases were identified. Each 10 µg/m3 increment of PM2.5 concentration was associated with 18% (HR: 1.18; 95% CI: 1.14-1.23) increased risk of ASCVD in the total population, and the association was more pronounced among individuals having a high predicted ASCVD risk than those having a low-to-medium risk, with the HR (95% CI) of 1.24 (1.19-1.30) and 1.11 (1.02-1.20) per 10 µg/m3 increment in PM2.5 concentration, respectively. The RERI, API, and SI were 1.22 (95% CI: 0.62-1.81), 0.22 (95% CI: 0.12-0.32), and 1.37 (95% CI: 1.16-1.63), respectively. Our findings demonstrate a significant synergistic effect on ASCVD between ASCVD risk stratification and PM2.5 exposure and highlight the potential health benefits of reducing PM2.5 exposure in Chinese, especially among those with high ASCVD risk.

The 17-y spatiotemporal trend of PM2.5 and its mortality burden in China.

Investigations on the chronic health effects of fine particulate matter (PM2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM2.5 levels, we aimed to estimate high-resolution, long-term PM2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R2 of 0.93 at the monthly level. For the time period outside the model training window, prediction R2 values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China.

Joint effects of meteorological factors and PM2.5 on age-related macular degeneration: a national cross-sectional study in China.

BACKGROUND: Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM2.5) on AMD. METHODS: Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM2.5 on AMD. RESULTS: The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM2.5 level during the study period was 63.1 ± 15.3 µg/m3. A significant positive association was detected between AMD and PM2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM2.5 and atmospheric pressure. CONCLUSIONS: This study is among the first to characterize the coordinated effects of meteorological factors and PM2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.

Ambient Air Pollutants and Incident Microvascular Disease: A Cohort Study.

Little is known about the links between long-term exposure to air pollution and risk of incident microvascular disease (retinopathy, peripheral neuropathy, and chronic kidney disease). This study included 396 014 UK residents free of microvascular disease and macrovascular disease at baseline. Annual means of PM2.5, PM2.5-10, PM10, NO2, and NOx were assessed by land use regression models for each participant. A weighted air pollution score was generated from PM10 and NOx. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 11.7 years, 14 327 composite microvascular disease occurred. While none of the air pollutants showed any statistically significant association with the risk of retinopathy, all the air pollutants were linked to the risk of peripheral neuropathy and chronic kidney disease. The adjusted-HRs (95% CIs) for each interquartile range increase in air pollution score were 1.07 (1.05, 1.09), 1.01 (0.94, 1.07), 1.13 (1.08, 1.19), and 1.07 (1.05, 1.10) for overall microvascular disease, retinopathy, peripheral neuropathy, and chronic kidney disease, respectively. In conclusion, long-term exposure to overall air pollution was associated with higher risks of peripheral neuropathy and chronic kidney disease among the general UK population.

Association of decreases in PM2.5 levels due to the implementation of environmental protection policies with the incidence of obesity in adolescents: A prospective cohort study.

AIMS: To explore the association between decreased levels of particulate matter (≤2.5 µm; PM2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study. METHODS: A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM2.5 exposure and the incidence of overweight/obesity. RESULTS: The average PM2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 µg/m3, 55.49 ± 3.78 µg/m3, and 42.50 ± 1.87 µg/m3, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 µg/m3 decrease in the PM2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM2.5 exposure. A 1-µg/m3 decrease in the PM2.5 level significantly decreased the body mass index (BMI), BMI z score (BMIz), and weight of adolescents (all P < 0.001). Compared with a < 20-µg/m3 decrease in the PM2.5 level, a ≥ 25-µg/m3 decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m2), BMIz (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-µg/m3 decrease in the PM2.5 level, a ≥ 25-µg/m3 decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m2), BMIz (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001). CONCLUSIONS: This study showed the etiological relevance of declining PM2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits.

Long-term PM2.5 exposure in association with chronic respiratory diseases morbidity: A cohort study in Northern China.

Several literatures have examined the risk of chronic respiratory diseases in association with short-term ambient PM2.5 exposure in China. However, little evidence has examined the chronic impacts of PM2.5 exposure on morbidity of chronic respiratory diseases in cohorts from high pollution countries. Our study aims to investigate the associations. Based on a retrospective cohort among adults in northern China, a Cox regression model with time-varying PM2.5 exposure and a concentration-response (C-R) curve model were performed to access the relationships between incidence of chronic respiratory diseases and long-term PM2.5 exposure during a mean follow-up time of 9.8 years. Individual annual average PM2.5 estimates were obtained from a satellite-based model with high resolution. The incident date of a chronic respiratory disease was identified according to self-reported physician diagnosis time and/or intake of medication for treatment. Among 38,047 urban subjects analyzed in all-cause chronic respiratory disease cohort, 482 developed new cases. In CB (38,369), asthma (38,783), and COPD (38,921) cohorts, the onsets were 276, 89, and 14, respectively. After multivariable adjustment, hazard ratio and 95% confidence interval for morbidity of all-cause chronic respiratory disease, CB, asthma, and COPD were 1.15 (1.01, 1.31), 1.20 (1.00, 1.42), 0.76 (0.55, 1.04), and 0.66 (0.29, 1.47) with each 10 µg/m3 increment in PM2.5, respectively. Stronger effect estimates were suggested in alcohol drinkers across stratified analyses. Additionally, the shape of C-R curve showed an increasing linear relationship before 75.00 µg/m3 concentrations of PM2.5 for new-onset all-cause chronic respiratory disease, and leveled off at higher levels. These findings indicated that long-term exposure to high-level PM2.5 increased the risks of incident chronic respiratory diseases in China. Further evidence of C-R curves is warranted to clarify the associations of adverse chronic respiratory outcomes involving air pollution.

Long-term impacts of ambient fine particulate matter exposure on overweight or obesity in Chinese adults: The China-PAR project.

Although emerging researches have linked ambient fine particulate matter (PM2.5) to obesity, evidence from high-polluted regions is still lacking. We thus assessed the long-term impacts of PM2.5 on body mass index (BMI) and the risk of the prevalence of overweight/obesity (BMI≥25 kg/m2), by incorporating the well-established Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project comprising 77,609 participants with satellite-based PM2.5 estimates at 1-km spatial resolution. The average of long-term PM2.5 level was 70.4 µg/m3, with the range of 32.1-94.2 µg/m3. Each 10 µg/m3 increment of PM2.5 was associated with 0.421 kg/m2 (95% confidence interval [CI]: 0.402, 0.439) and 13.5% (95% CI: 12.8%, 14.3%) increased BMI and overweight/obesity risk, respectively. Moreover, compared with the lowest quartile of PM2.5 (≤57.5 µg/m3), the relative risk of the prevalence of overweight/obesity from the highest quartile (>85.9 µg/m3) was 1.611 (95% CI: 1.566, 1.657). The exposure-response curve suggested a non-linear relationship between PM2.5 exposure and overweight/obesity. Besides, the association was modified by age, diabetes mellitus, hypertension and dyslipidemia status. Our study provides the evidence for the adverse impacts of long-term PM2.5 on BMI and overweight/obesity in China, and the findings are important for policy development on air quality, especially in severely polluted areas.

Chronic Effects of High Fine Particulate Matter Exposure on Lung Cancer in China.

Rationale: Limited cohort studies have evaluated chronic effects of high fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 µm [PM2.5]) exposure on lung cancer.Objectives: To investigate the response pattern of lung cancer associated with high PM2.5 exposure.Methods: A Chinese cohort of 118,551 participants was followed up from 1992 to 2015. By incorporating PM2.5 exposure at 1 km spatial resolution generated using the satellite-based model during 2000-2015, we estimated the association between lung cancer and time-weighted average PM2.5 concentration using Cox proportional hazard models.Measurements and Main Results: A total of 844 incident lung cancer cases were identified during 915,053 person-years of follow-up. Among them, 701 lung cancer deaths occurred later. The exposure-response curves for lung cancer associated with PM2.5 exposure were nonlinear, with steeper slopes at the higher concentrations. Adjusted for age, sex, geographical region, urbanization, education level, smoking status, alcohol consumption, work-related physical activity, and body mass index, participants exposed to the second-fifth quintiles of PM2.5 had higher risk for lung cancer incidence than those exposed to the first quintile, with hazard ratios of 1.44 (95% confidence interval [CI], 1.10-1.88), 1.49 (95% CI, 1.12-1.99), 2.08 (95% CI, 1.42-3.04), and 2.45 (95% CI, 1.83-3.29), respectively. The corresponding hazard ratios for lung cancer mortality were 1.83 (95% CI, 1.33-2.50), 1.80 (95% CI, 1.29-2.53), 2.50 (95% CI, 1.62-3.86), and 2.95 (95% CI, 2.09-4.17), respectively.Conclusions: We provide strong evidence that high PM2.5 exposure leads to an elevated risk of lung cancer incidence and mortality, highlighting that remarkable public health benefits could be obtained from the improvement of air quality in highly polluted regions.

Benefits of active commuting on cardiovascular health modified by ambient fine particulate matter in China: A prospective cohort study.

BACKGROUND: Active commuting as a contributor to daily physical activity is beneficial for cardiovascular health, but leads to more chances of exposure to ambient air pollution. This study aimed to investigate associations between active commuting to work with cardiovascular disease (CVD), mortality and life expectancy among general Chinese adults, and to further evaluate the modification effect of fine particulate matter (PM2.5) exposure on these associations. METHODS: We included 76,176 Chinese adults without CVD from three large cohorts of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project. Information about commuting mode and physical activity were collected by unified questionnaire. Satellite-based PM2.5 concentrations at 1-km spatial resolution was used for estimating PM2.5 exposure of participants. Hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD incidence, mortality and all-cause mortality were estimated using Cox proportional hazards regression models. Multiplicative interaction term of commuting mode and PM2.5 level was tested to investigate potential effect modification. RESULTS: During 448,499 person-years of follow-up, 2230 CVD events and 2777 all-cause deaths were recorded. Compared with the non-active commuters, the multivariable-adjusted HRs (95% CIs) of CVD incidence and all-cause mortality were 0.95(0.85-1.05) and 0.79(0.72-0.87) for walking commuters, respectively. Corresponding HRs (95% CIs) for cycling commuters were 0.71(0.62-0.82) and 0.67(0.59-0.76). Active commuters over 45 years old were estimated to have more CVD-free years and life expectancy than non-active commuters under lower PM2.5 concentration. However, these beneficial effects of active commuting were alleviated or counteracted by long-term exposure to high PM2.5 concentration. Significant multiplicative interaction of commuting mode and PM2.5 level was showed in all-cause mortality, with the lowest risk observed in cycling participants exposed to lower level of PM2.5. CONCLUSIONS: Active commuting was associated with lower risk of CVD, all-cause mortality, and longer life expectancy among Chinese adults under ambient settings with lower PM2.5 level. It will be valuable to encourage active commuting among adults and develop stringent strategies on ambient PM2.5 pollution control for prevention of CVD and prolongation of life expectancy.

Long-term exposure to ambient PM2.5 and stroke mortality among urban residents in northern China.

Evidence is still limited for the role of long-term PM2.5 exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM2.5 exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM2.5-mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM2.5 derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM2.5, after adjusting for individual risk factors. The cross-product term of PM2.5 exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM2.5 with stroke mortality. Among the study participants, the annual mean level of PM2.5 concentration was 66.3 µg/m3 ranging from 39.0 µg/m3 to 100.6 µg/m3. For each 10 µg/m3 increment in PM2.5, the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM2.5 decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM2.5 exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change.

Long-Term Effects of High Exposure to Ambient Fine Particulate Matter on Coronary Heart Disease Incidence: A Population-Based Chinese Cohort Study.

Evidence of long-term effects of high exposure to ambient fine particulate matter (PM2.5) on coronary heart disease (CHD) remains limited. We incorporated the high-resolution satellite-based PM2.5 estimates with a large-scale, population-based Chinese cohort comprising 118 229 individuals, to assess the CHD risk of long-term exposure to high PM2.5. During the follow-up of 908 376 person-years, 1586 incident CHD cases were identified. The long-term average PM2.5 concentration for study population was 64.96 µg/m3, ranging from 31.17 to 96.96 µg/m3. For an increment of 10 µg/m3 in PM2.5, the multivariate-adjusted hazard ratios (HRs) were 1.43 (95% confidence interval [CI]: 1.35-1.51) for total CHD, 1.45 (95% CI: 1.36-1.56) for nonfatal CHD, and 1.38 (95% CI: 1.25-1.53) for fatal CHD, respectively. The effects were different across specific CHD outcomes, with greater effects for unstable angina (HR, 1.71 [95% CI, 1.56-1.88]), and weaker effects for acute myocardial infarction (HR, 1.28 [95% CI, 1.19-1.39]) and other CHD (HR, 1.27 [95% CI, 1.10-1.48]). The exposure-response curve suggested that HRs increased with elevated PM2.5 concentration over the entire exposure range. Elderly and hypertensive individuals were more susceptible to PM2.5-induced CHD. Our findings demonstrate the adverse health effects of severe air pollution and highlight the potential health benefits of air quality improvement.

Spatio-temporal analysis of the relationship between meteorological factors and hand-foot-mouth disease in Beijing, China.

BACKGROUND: Hand-foot-mouth disease (HFMD) is a common infectious disease in China and occurs mostly in infants and children. Beijing is a densely populated megacity, in which HFMD has been increasing in the last decade. The aim of this study was to quantify spatio-temporal characteristics of HFMD and the relationship between meteorological factors and HFMD incidence in Beijing, China. METHODS: Daily counts of HFMD cases from January 2010 to December 2012 were obtained from the Beijing Center for Disease Prevention and Control (CDC). Seasonal trend decomposition with Loess smoothing was used to explore seasonal patterns and temporal trends of HFMD. Bayesian spatiotemporal Poisson regression models were used to quantify spatiotemporal patterns of HFMD incidence and associations with meteorological factors. RESULTS: There were 114,777 HFMD cases reported to Beijing CDC from 1 January 2010 to 31 December 2012 and the raw incidence was 568.6 per 100,000 people. May to July was the peak period of HFMD incidence each year. Low-incidence townships were clustered in central, northeast and southwest regions of Beijing. Mean temperature, relative humidity, wind velocity and sunshine hours were all positively associated with HFMD. The effect of wind velocity was significant with a RR of 3.30 (95%CI: 2.37, 4.60) per meter per second increase, as was sunshine hours with a RR of 1.20 (95%CI: 1.02, 1.40) per 1 hour increase. CONCLUSIONS: The distribution of HFMD in Beijing was spatiotemporally heterogeneous, and was associated with meteorological factors. Meteorological monitoring could be incorporated into prediction and surveillance of HFMD in Beijing.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique.

[Study of relationship between atmospheric fine particulate matter concentration and one grade a tertiary hospital emergency room visits during 2012 and 2013 in Beijing].

OBJECTIVE: To explore the concentration-response relationship between ambient concentration of PM2.5 and daily total hospital emergency room visits in Beijing during 2012 and 2013. This study also examined the effects of ambient PM2.5 during heavy polluted days on emergency room visits compared with the light polluted days. METHODS: We collected the daily meteorological factors monitoring data and concentrations of air pollutants in Beijing during October 1, 2012 to December 31, 2013. We also collected the daily emergency room visits from a tertiary hospital in Beijing in the same time period. Generalized additive model was fitted to estimate the association between the ambient PM2.5 and the hospital emergency room visits, by using the smooth function to adjust long term trend of time, public holidays and day of week. In addition, constrained piecewise linear function was then used to estimate the excess risk for different segment of concentration-response function. RESULTS: The annual average concentration of PM2.5 was 90.9 µg/m(3) during October 1, 2012 and December 31, 2013. There were total 64 260 cases for total emergency room visits, of which respiratory disease had 9 849 cases and cardiovascular disease had 11 168 cases. PM2.5 was positive related with PM10, NO2 and SO2. The corresponding correlation coefficients were 0.87, 0.78 and 0.62, respectively (P<0.05). And PM2.5 was positively related with relative humidity, with correlation coefficient 0.45 (P<0.05). But PM2.5 was negatively related with mean temperature (r=-0.17, P< 0.05) and wind speed (- 0.32, P<0.05). In the single polluted model, after adjusting the effects of temperature, relative humidity and wind, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits was 0.25% (95% CI: 0.07-0.43). In the two-pollutant model PM2.5+SO2 and PM2.5+NO2, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits were 1.07% (95%CI:0.83-1.30) and 0.56% (95%CI: 0.32-0.80) respectively, which were higher than the effect in single pollutant model. Average concentration of ambient particulate matters (PM2.5) was 204.16 µg/m(3) during heavy pollution, higher than control period (85.24 µg/m(3)). When PM2.5 as the primary air pollutants during heavy polluted days, we observed a significant increase in emergency room visits, and the odd ratios was 1.16 (95% CI:1.09-1.22). CONCLUSION: There were positive correlation between high concentration of ambient particulate matters (PM2.5) and increasing daily emergency room visits. Especially during the heavy polluted days, the effects of elevated concentration of PM2.5 on hospital emergency room visits were much larger.

Spatiotemporal analysis of particulate air pollution and ischemic heart disease mortality in Beijing, China.

BACKGROUND: Few studies have used spatially resolved ambient particulate matter with an aerodynamic diameter of <10 µm (PM10) to examine the impact of PM10 on ischemic heart disease (IHD) mortality in China. The aim of our study is to evaluate the short-term effects of PM10 concentrations on IHD mortality by means of spatiotemporal analysis approach. METHODS: We collected daily data on air pollution, weather conditions and IHD mortality in Beijing, China during 2008 and 2009. Ordinary kriging (OK) was used to interpolate daily PM10 concentrations at the centroid of 287 township-level areas based on 27 monitoring sites covering the whole city. A generalized additive mixed model was used to estimate quantitatively the impact of spatially resolved PM10 on the IHD mortality. The co-effects of the seasons, gender and age were studied in a stratified analysis. Generalized additive model was used to evaluate the effects of averaged PM10 concentration as well. RESULTS: The averaged spatially resolved PM10 concentration at 287 township-level areas was 120.3 ± 78.1 µg/m3. Ambient PM10 concentration was associated with IHD mortality in spatiotemporal analysis and the strongest effects were identified for the 2-day average. A 10 µg/m3 increase in PM10 was associated with an increase of 0.33% (95% confidence intervals: 0.13%, 0.52%) in daily IHD mortality. The effect estimates using spatially resolved PM10 were larger than that using averaged PM10. The seasonal stratification analysis showed that PM10 had the statistically stronger effects on IHD mortality in summer than that in the other seasons. Males and older people demonstrated the larger response to PM10 exposure. CONCLUSIONS: Our results suggest that short-term exposure to particulate air pollution is associated with increased IHD mortality. Spatial variation should be considered for assessing the impacts of particulate air pollution on mortality.

Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region.

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.