Accountability analysis of health benefits related to National Action Plan on Air Pollution Prevention and Control in China.

China is one of the largest producers and consumers of coal in the world. The National Action Plan on Air Pollution Prevention and Control in China (2013-2017) particularly aimed to reduce emissions from coal combustion. Here, we show whether the acute health effects of PM2.5 changed from 2013 to 2018 and factors that might account for any observed changes in the Beijing-Tianjin-Hebei (BTH) and the surrounding areas where there were major reductions in PM2.5 concentrations. We used a two-stage analysis strategy, with a quasi-Poisson regression model and a random effects meta-analysis, to assess the effects of PM2.5 on mortality in the 47 counties of BTH. We found that the mean daily PM2.5 levels and the SO42- component ratio dramatically decreased in the study period, which was likely related to the control of coal emissions. Subsequently, the acute effects of PM2.5 were significantly decreased for total and circulatory mortality. A 10 µg/m3 increase in PM2.5 concentrations was associated with a 0.16% (95% CI: 0.08, 0.24%) and 0.02% (95% CI: -0.09, 0.13%) increase in mortality from 2013 to 2015 and from 2016 to 2018, respectively. The changes in air pollution sources or PM2.5 components appeared to have played a core role in reducing the health effects. The air pollution control measures implemented recently targeting coal emissions taken in China may have resulted in significant health benefits.

Identifying patterns of reported findings on long-term cardiac complications of COVID-19: a systematic review and meta-analysis.

INTRODUCTION: Prior reviews synthesized findings of studies on long-term cardiac complications of COVID-19. However, the reporting and methodological quality of these studies has not been systematically evaluated. Here, we conducted a systematic review and meta-analysis on long-term cardiac complications of COVID-19 and examined patterns of reported findings by study quality and characteristics. METHODS: We searched for studies examining long-term cardiac complications of COVID-19 that persisted for 4 weeks and over. A customized Newcastle-Ottawa scale (NOS) was used to evaluate the quality of included studies. Meta-analysis was performed to generate prevalence estimates of long-term cardiac complications across studies. Stratified analyses were further conducted to examine the prevalence of each complication by study quality and characteristics. The GRADE approach was used to determine the level of evidence for complications included in the meta-analysis. RESULTS: A total number of 150 studies describing 57 long-term cardiac complications were included in this review, and 137 studies reporting 17 complications were included in the meta-analysis. Only 25.3% (n = 38) of studies were of high quality based on the NOS quality assessment. Chest pain and arrhythmia were the most widely examined long-term complications. When disregarding study quality and characteristics, summary prevalence estimates for chest and arrhythmia were 9.79% (95% CI 7.24-13.11) and 8.22% (95% CI 6.46-10.40), respectively. However, stratified analyses showed that studies with low-quality scores, small sample sizes, unsystematic sampling methods, and cross-sectional design were more likely to report a higher prevalence of complications. For example, the prevalence of chest pain was 22.17% (95% CI 14.40-32.55), 11.08% (95% CI 8.65-14.09), and 3.89% (95% CI 2.49-6.03) in studies of low, medium, and high quality, respectively. Similar patterns were observed for arrhythmia and other less examined long-term cardiac complications. CONCLUSION: There is a wide spectrum of long-term cardiac complications of COVID-19. Reported findings from previous studies are strongly related to study quality, sample sizes, sampling methods, and designs, underscoring the need for high-quality epidemiologic studies to characterize these complications and understand their etiology.

Predicting fine-scale daily NO2 over Mexico City using an ensemble modeling approach.

In recent years, there has been growing interest in developing air pollution prediction models to reduce exposure measurement error in epidemiologic studies. However, efforts for localized, fine-scale prediction models have been predominantly focused in the United States and Europe. Furthermore, the availability of new satellite instruments such as the TROPOsopheric Monitoring Instrument (TROPOMI) provides novel opportunities for modeling efforts. We estimated daily ground-level nitrogen dioxide (NO2) concentrations in the Mexico City Metropolitan Area at 1-km2 grids from 2005 to 2019 using a four-stage approach. In stage 1 (imputation stage), we imputed missing satellite NO2 column measurements from the Ozone Monitoring Instrument (OMI) and TROPOMI using the random forest (RF) approach. In stage 2 (calibration stage), we calibrated the association of column NO2 to ground-level NO2 using ground monitors and meteorological features using RF and extreme gradient boosting (XGBoost) models. In stage 3 (prediction stage), we predicted the stage 2 model over each 1-km2 grid in our study area, then ensembled the results using a generalized additive model (GAM). In stage 4 (residual stage), we used XGBoost to model the local component at the 200-m2 scale. The cross-validated R2 of the RF and XGBoost models in stage 2 were 0.75 and 0.86 respectively, and 0.87 for the ensembled GAM. Cross-validated rootmean-squared error (RMSE) of the GAM was 3.95 µg/m3. Using novel approaches and newly available remote sensing data, our multi-stage model presented high cross-validated fits and reconstructs fine-scale NO2 estimates for further epidemiologic studies in Mexico City.

Exploring Relevant Time Windows in the Association Between PM2.5 Exposure and Amyotrophic Lateral Sclerosis: A Case-Control Study in Denmark.

Studies suggest a link between particulate matter less than or equal to 2.5 µm in diameter (PM2.5) and amyotrophic lateral sclerosis (ALS), but to our knowledge critical exposure windows have not been examined. We performed a case-control study in the Danish population spanning the years 1989-2013. Cases were selected from the Danish National Patient Registry based on International Classification of Diseases codes. Five controls were randomly selected from the Danish Civil Registry and matched to a case on vital status, age, and sex. PM2.5 concentration at residential addresses was assigned using monthly predictions from a dispersion model. We used conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for confounding. We evaluated exposure to averaged PM2.5 concentrations 12-24 months, 2-6 years, and 2-11 years pre-ALS diagnosis; annual lagged exposures up to 11 years prediagnosis; and cumulative associations for exposure in lags 1-5 years and 1-10 years prediagnosis, allowing for varying association estimates by year. We identified 3,983 cases and 19,915 controls. Cumulative exposure to PM2.5 in the period 2-6 years prediagnosis was associated with ALS (OR = 1.06, 95% CI: 0.99, 1.13). Exposures in the second, third, and fourth years prediagnosis were individually associated with higher odds of ALS (e.g., for lag 1, OR = 1.04, 95% CI: 1.00, 1.08). Exposure to PM2.5 within 6 years before diagnosis may represent a critical exposure window for ALS.

Long-term cardiac symptoms following COVID-19: a systematic review and meta-analysis.

Background: There is growing body of literature on the long-term cardiac symptoms following COVID-19. We conducted a systematic review and meta-analysis to synthesize and evaluate related evidence to inform clinical management and future studies. Methods: We searched two preprint and seven peer-reviewed article databases from January 1, 2020 to January 8, 2022 for studies investigating cardiac symptoms that persisted for at least 4 weeks among individuals who survived COVID-19. A customized Newcastle-Ottawa scale was used to evaluate the quality of included studies. Random-effects meta-analyses were performed to estimate the proportion of symptoms with 95% confidence intervals (CI), and stratified analyses were conducted to quantify the proportion of symptoms by study characteristics and quality. Results: A total of 101 studies describing 49 unique long-term cardiac symptoms met the inclusion criteria. Based on quality assessment, only 15.8% of the studies (n=16) were of high quality, and most studies scored poorly on sampling representativeness. The two most examined symptoms were chest pain and arrhythmia. Meta-analysis showed that the proportion of chest pain was 10.1% (95% CI: 6.4-15.5) and arrhythmia was 9.8% (95% CI: 5.4-17.2). Stratified analyses showed that studies with low-quality score, small sample size, unsystematic sampling method, and cross-sectional design were most likely to report high proportions of symptoms. For example, the proportion of chest pain was 21.3% (95% CI: 10.5-38.5), 9.3% (95% CI: 6.0-14.0), and 4.0% (95% CI: 1.3-12.0) in studies with low, medium, and high-quality scores, respectively. Similar patterns were observed for other cardiac symptoms including hypertension, cardiac abnormalities, myocardial injury, thromboembolism, stroke, heart failure, coronary disease, and myocarditis. Discussion: There is a wide spectrum of long-term cardiac symptoms following COVID-19. Findings of existing studies are strongly related to study quality, size and design, underscoring the need for high-quality epidemiologic studies to characterize these symptoms and understand their etiology.

Short-term exposure to ozone and cause-specific mortality risks and thresholds in China: Evidence from nationally representative data, 2013-2018.

BACKGROUND: Ambient ozone pollution is steadily increasing and becoming a major environmental risk factor contributing to the global disease burden. Although the association between short-term ozone exposure and mortality has been widely studied, results are mostly reported on deaths from non-accidental or total cardiopulmonary disease rather than a spectrum of causes. In particular, a knowledge gap still exists for the potential thresholds in mortality risks. METHODS: This nationwide time-series study in China included 323 counties totaling 230,266,168 residents. Daily maximum 8-hour average was calculated as the ozone exposure metric. A two-stage statistical approach was adopted to assess ozone effects on 21 cause-specific deaths for 2013-2018. The subset approach and threshold approach were utilized to explore potential thresholds, and stratification analysis was used to evaluate population susceptibility. RESULTS: On average, the annual mean ozone concentration was 93.4 µg/m3 across 323 counties. A 10-µg/m3 increase in lag 0-1 day of ozone was associated with increases of 0.12 % in mortality risk from non-accidental disease, 0.11 % from circulatory disease, 0.09 % from respiratory disease, 0.29 % from urinary system disease, and 0.20 % from nervous system disease. There may be a "safe" threshold in the ozone-mortality association, which may be between 60 and 100 µg/m3, and vary by cause of death. Women and older adults (especially those over 75) are more affected by short-term ozone exposure. Populations in North China had a higher risk of ozone-related circulatory mortality, while populations in South China had a higher risk of ozone-related respiratory mortality. CONCLUSIONS: National findings link short-term ozone exposure to premature death from circulatory, respiratory, neurological, and urinary diseases, and provide evidence for a potential "safe" threshold in the association of ozone and mortality. These findings have important implications for helping policymakers tighten the relevant air quality standards and developing early warning systems for public health protection in China.

Traffic-related PM2.5 and its specific constituents on circulatory mortality: A nationwide modelling study in China.

BACKGROUND: Short-term fine particulate matter (PM2.5) exposure and increased circulatory mortality have been well documented. However, there are inconsistent findings on mortality effects of traffic-related pollutants from the perspective of sources or constituents. Few studies have examined such associations using source and constituents simultaneously, and even less are based on large-scale, nationally representative data. We aimed to conduct a comprehensive analysis to investigate source- and constituent-specific mortality effects due to traffic-related PM2.5 pollution in China. METHODS: We extracted daily mortality data in 280 counties from the China Disease Surveillance Points system (DSPs) from January 2013 to December 2018. Daily concentrations of traffic-related PM2.5 and specific constituents were simulated using the Community Multiscale Air Quality (CMAQ) model. The downscaling and adjustment methods were carried out to generate a refined exposure assessment. We estimated the circulatory mortality risk using a standard two-stage approach, combining generalized linear model (GLM) with a quasi-Poisson distribution and random-effects meta-analysis. RESULTS: We observed that traffic-related PM2.5 and specific constituents were significantly associated with increased circulatory mortality. An increase of interquartile range of traffic-related PM2.5, elemental carbon (EC), organic carbon (OC), and nitrate (NO3-) were associated with elevated circulatory mortality risks of 1.80 % (95 % confidence interval, CI: 1.27, 2.33), 1.85 % (1.33, 2.37), 1.42 % (0.90, 1.94), and 1.10 % (0.55, 1.66) at 3-day moving average (lag 0-2 days), respectively. We also found relatively high associations between traffic-related PM2.5 and EC exposures and cardiovascular mortality, and OC exposure and cerebrovascular mortality. Moreover, our stratified analysis demonstrated such mortality risks tended to be stronger in males, individuals age 65 years or older, and during the cold season. CONCLUSION: Our findings provided robust evidence on significant associations of traffic-related PM2.5 and specific constituents with circulatory mortality. Further emissions abatement from the transportation sector and corresponding pollutants should merit a particular focus in China.

Trends of overweight and obesity among preschool children from 2013 to 2018: a cross-sectional study in Rhine-Neckar County and the City of Heidelberg, Germany.

BACKGROUND: Early childhood overweight and obesity is a growing public health concern worldwide. Few recent studies have addressed how time trends varied by sociodemographic characteristics at the regional level using large and high-quality data. This study determines how time trends vary in the prevalence of early childhood overweight and obesity by age, gender, and migration background at the regional level. METHODS: We used a Kernel-density curve to describe the BMI distribution, and evaluated the trends of overweight and obesity by age, gender, and migration background using logistic regression. RESULTS: Mean BMI and the overall prevalence of overweight and obesity increased among preschool children aged 4-6 years in the Rhine-Neckar County and the City of Heidelberg. After adjusting for age, sex, and migration background, trends of overweight significantly increased only among male children in the age 5 year group with migration background (P < 0.05), and an upward trend of obesity was observed only among male children in the age 5 year group and female children in the age 6 year group with migration background (P < 0.05). CONCLUSIONS: BMI distribution as well as general prevalence of overweight and obesity are still increasing among preschool children. Children with migration backgrounds, particularly male children in the age 5 year groups and female children in the age 6 year group should be prioritized. Health promotion strategies for children with migration backgrounds will help address this challenge.

Intermediate- and long-term associations between air pollution and ambient temperature and glycated hemoglobin levels in women of child bearing age.

BACKGROUND: Air pollution has been linked to obesity while higher ambient temperatures typically reduce metabolic demand in a compensatory manner. Both relationships may impact glucose metabolism, thus we examined the association between intermediate- and long-term exposure to fine particulate matter (PM2.5) and ambient temperature and glycated hemoglobin(HbA1c), a longer-term marker of glucose control. METHODS: We assessed 3-month, 6-month, and 12-month average air pollution and ambient temperature at 1-km2 spatial resolution via satellite remote sensing models (2013-2019), and assessed HbA1c at four, six, and eight years postpartum in women enrolled in the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City. PM2.5 and ambient temperature were matched to participants' addresses and confirmed by GPS tracker. Using linear mixed-effects models, we examined the association between 3-month, 6-month, and 12-month average PM2.5 and ambient temperature with repeated log-transformed HbA1c values. All models included a random intercept for each woman and were adjusted for calendar year, season, and individual-level confounders (age, marital status, smoking, alcohol consumption level, and education level). RESULTS: We analyzed 1,265 HbA1c measurements of 484 women. Per 1 µg/m3 increase in 3-month and 6-month PM2.5, HbA1c levels increased by 0.28% (95% confidence interval (95 %CI): 0.14, 0.42%) and 0.28% (95 %CI: 0.04, 0.52%) respectively. No association was seen for 12-month average PM2.5. Per 1 °C increase in ambient temperature, HbA1c levels decreased by 0.63% (95 %CI: -1.06, -0.21%) and 0.61% (95 %CI: -1.08, -0.13%), while the 12-month average again is not associated with HbA1c. CONCLUSIONS: Intermediate-term exposure to PM2.5 and ambient temperature are associated with opposing changes in HbA1c levels, in this region of high PM2.5 and moderate temperature fluctuation. These effects, measurable in mid-adult life, may portend future risk of type 2 diabetes and possible heart disease.

Associations between Source-Specific Fine Particulate Matter and Mortality and Hospital Admissions in Beijing, China.

The health effects of PM2.5 exposure have become a major public concern in developing countries. Identifying major PM2.5 sources and quantifying the health effects at the population level are essential for controlling PM2.5 pollution and formulating targeted emissions reduction policies. In the current study, we have obtained PM2.5 mass data and used positive matrix factorization to identify the major sources of PM2.5. We evaluated the relationship between short-term exposure to PM2.5 sources and mortality or hospital admissions in Beijing, China, using 441 742 deaths and 9 420 305 hospital admissions from 2013 to 2018. We found positive associations for coal combustion and road dust sources with mortality. Increased hospital admission risks were significantly associated with sources of vehicle exhaust, coal combustion, secondary sulfates, and secondary nitrates. Compared to the cool season, excess mortality risk estimates of coal combustion source were significantly higher in the warm season. Our findings show that reducing more toxic sources of PM2.5, especially coal emissions, and developing clean energy alternatives can have critical implications for improving air quality and protecting public health.

Changes in Public Perception and Behaviors under Compound Heatwave in COVID-19 Epidemic - Beijing, China, 2020.

What is already known about this topic? Dramatic heatwaves frequently occurred simultaneously with the coronavirus disease 2019 (COVID-19) pandemic worldwide in 2020 and posed public health challenges. Public risk perceptions and behavioral responses to this compound risk need to be addressed. What is added by this report? During heatwaves, the proportion of individuals who perceived COVID-19 to be more concerning than heatwaves decreased by 9.4%, and the behavior of continuously wearing masks reduced by 20.6%. Heatwave exposures also corresponded to an average decline of 58% in the likelihood of continuously wearing masks and a decline of 41% in taking well-ventilated public transportation. What are the implications for public health practice? At-risk populations should be effectively prepared to respond to compounded risks from heatwaves occurring at the same time as COVID-19 outbreaks to better address threats caused by climate change.

Short-term PM2.5 and cardiovascular admissions in NY State: assessing sensitivity to exposure model choice.

BACKGROUND: Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model. METHODS: We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM2.5) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM2.5 dataset. RESULTS: For all PM2.5 datasets, we observed positive associations between PM2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m3 increase in daily PM2.5. We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available. CONCLUSIONS: Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM2.5 and CVD admissions, regardless of model choice.

Random forest model based fine scale spatiotemporal O3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017.

Ambient ozone (O3) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O3 (O3-8hmax) concentration, daily average O3 (O3-mean) concentration, and daily maximum 1h O3 (O3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R2 of sample-based O3-8hmax, O3-mean and O3-1hmax models were all greater than 0.80, while the R2 of site-based and date-based model were 0.68-0.87. From 2010 to 2017, O3-8hmax, O3-mean, and O3-1hmax concentrations in the BTH region increased by 4.18 µg/m3, 0.11 µg/m3, and 4.71 µg/m3, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O3 concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude.

Role of emission controls in reducing the 2050 climate change penalty for PM2.5 in China.

Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 µg m-3 in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 µg m-3 with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.

Heat wave characteristics, mortality and effect modification by temperature zones: a time-series study in 130 counties of China.

BACKGROUND: The substantial disease burden attributed to heat waves, and their increasing frequency and intensity due to climate change, highlight the importance of understanding the health consequences of heat waves. We explore the mortality risk due to heat wave characteristics, including the timing in the seasons, the day of the heat wave, the intensity and the duration, and the modifying effect of temperature zones. METHODS: Heat waves were defined as ≥ 2 days with a temperature ≥99th percentile for the county from 1 May through 30 September. Heat waves were characterized by their intensity, duration, timing in the season, and day of the heat wave. Within each county, we estimated the total non-accidental death and cardiovascular disease mortality during each heat wave compared with non-heat wave days by controlling for potential confounders in summer. We combined individual heat wave effect estimates using a random-effects model to calculate overall effects at the temperature zone and national levels. RESULTS: The average daily total number of non-accidental deaths was nine in the warm season (across all the counties). Approximately half of the daily total number of non-accidental deaths were cardiovascular-related deaths (approximately four persons per day). The average and maximum temperatures across the study area were 23.1 °C (range: -1.2-35.9 °C) and 28.3 °C (range: 5.4-42.8 °C), respectively. The average relative humidity during the study was 68.9% (range: 8.0-100.0%). Heat waves increase the risk of total non-accidental death by 15.7% [95% confidence interval (CI): 12.5, 18.9] compared with non-heat wave periods, and the risk of cardiovascular-related death increases by 22.0% (95% CI: 16.9, 27.4). The risk of non-accidental death during the first heat wave of the season increases by 16.3% (95% CI: 12.6, 20.2), the risk during the second heat wave increases by 6.3% (95% CI: 2.8, 9.9) and during subsequent heat waves increases by -2.1% (95% CI: -4.6, 0.4). The first day and the second to third days of heat waves increase the risk of total non-accidental death by 11.7% (95% CI: 7.6, 15.9) and 17.0% (95% CI: 13.1, 21.0), respectively. Effects of heat waves on mortality lasted more than 4 days (6.3%, 95% CI: 2.4, 10.5) and are non-significantly different from the first day of heat waves. We found non-significant differences of the heat wave-associated mortality risks across mid-, warm and subtropical temperature zones. CONCLUSIONS: In China, the effect of heat waves on mortality is acute, and varies by certain characteristics of heat waves. Given these results, national heat wave early warning systems should be developed, as well as precautions and protection warranted according to characteristics of heat waves.

Short- and intermediate-term exposure to NO2 and mortality: A multi-county analysis in China.

Nitrogen dioxide (NO2) is a well-established traffic emissions tracer and has been associated with multiple adverse health outcomes. Short- and long-term exposure to NO2 has been studied and is well-documented in existing literature, but information on intermediate-term NO2 effects and mortality is lacking, despite biological plausibility. We obtained daily NO2 and mortality data from 42 counties in China from 2013 to 2015. Distributed-lag non-linear models were employed to investigate the relationship between non-accidental mortality and NO2 up to 30 days before the event, including PM2.5, temperature, relative humidity, and holidays as covariates in a random effects meta-analysis pooling county-specific estimates. We repeated the analysis for cardiovascular- and respiratory-related mortality, and explored sex-stratified associations. Per 10 µg/m3 increase in NO2, we estimated a 0.13% (95%CI: 0.03, 0.23%), 0.57% (95%CI: -0.04, 1.18%), and -0.14% (95%CI: -1.63, 1.37%) change in non-accidental mortality for same-day and previous-day NO2 (lag0-1 cumulated), in the preceding 7 days (lag0-7 cumulated), and in the preceding 30 days (lag0-30 cumulated), respectively. The strongest estimate was observed for respiratory-related mortality in the lag0-30 cumulated effect for women (3.12%; 95%CI: -1.66, 8.13%). We observed a trend of higher effect estimates of intermediate-term NO2 exposure on respiratory mortality compared to that of the short-term, although the differences were not statistically significant. Our results at longer lags for all-cause and cardiovascular mortality were sensitive to modeling choices. Future work should further investigate intermediate-term air pollution exposure given their potential biological relevance, but in larger scale settings.

Long-term exposure to ambient fine particulate matter and fasting blood glucose level in a Chinese elderly cohort.

Fasting blood glucose level is the primary indicator for the diagnosis of diabetes. We aim to conduct a longitudinal study on the association between long-term fine particulate matter (PM2.5) exposure and fasting blood glucose concentrations. We recruited and followed up 1449 participants older than 65 years of age in 2009, 2012, 2014, and 2017 in eight counties in China. Fasting blood glucose was repeatedly measured 3697 times in total among these participants. Data on annual ground-level PM2.5 concentrations with a 0.01° spatial resolution from 2005 to 2016 were used to assess exposures. An increase of 10 µg/m3 in 3-year average exposure to PM2.5 was associated with an increase of 0.146 mmol/L (95% confidence interval [CI]: 0.045, 0.248) in fasting blood glucose in all participants. The association was more pronounced among the subgroup with diabetes compared to the subgroup without diabetes (P < .05). In conclusion, Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5. SUMMARY: Long-term PM2.5 exposure was associated with an increase in fasting blood glucose levels among elderly people. Elderly individuals with diabetes are particularly vulnerable to high level exposures of PM2.5.