Seasonal and regional short-term effects of fine particles on hospital admissions in 202 US counties, 1999-2005

Individual Risk Factors of PM2.5 Associated With Wintertime Mortality in Urban Patients With COPD

BACKGROUND

Air pollution contributes to premature mortality, but potential impacts differ in populations with existing disease, particularly for individuals with multiple risk factors. Although COPD increases vulnerability to air pollution, individuals with COPD and other individual risk factors are at the intersection of multiple risks and may be especially susceptible to the effect of acute outdoor air pollution.

RESEARCH QUESTION

What is the association between wintertime air pollution and mortality in patients with COPD and the modifying role of individual risk factors?

STUDY DESIGN AND METHODS

This study evaluated 19,243 deceased veterans with prior COPD diagnosis who had resided in 25 US metropolitan regions (2016-2019). Electronic health records included patient demographic characteristics; smoking status; and comorbidities such as asthma, coronary artery disease (CAD), obesity, and diabetes. Using geocoded addresses, individuals were assigned wintertime fine particulate matter (particulate matter smaller than 2.5 μg in diameter [PM2.5]) and nitrogen dioxide air pollution exposures. Associations between acute air pollution and mortality were estimated by using a time-stratified case-crossover design with a conditional logistic model, and individual risk differences were assessed according to stratified analysis.

RESULTS

A 1.05 (95% CI, 1.02-1.09) mortality risk was estimated for each 10 μg/m3 increase in daily wintertime PM2.5). Older patients and Black individuals displayed elevated risk. Obesity was a substantial air pollution-related mortality risk factor (OR, 1.11; 95% CI, 1.01-1.23), and the estimated risk for individuals with obesity plus CAD or obesity plus diabetes was 16% higher.

INTERPRETATION

Wintertime PM2.5 exposure was associated with elevated mortality risk in people with COPD, but individuals with multiple comorbidities, notably obesity, had high vulnerability. Our study suggests that obesity, CAD, and diabetes are understudied modifiers of air pollution-related risks for people with existing COPD.

The association between ambient air pollution and migraine: a systematic review

Some studies have shown the effect of air pollution on migraine. However, it needs to be confirmed in larger-scale studies, as scientific evidence is scarce regarding the association between air pollution and migraine. Therefore, this systematic review aims to determine whether there are associations between outdoor air pollution and migraine. A literature search was performed in Scopus, Medline (via PubMed), EMBASE, and Web of Science. A manual search for resources and related references was also conducted to complete the search. All observational studies investigating the association between ambient air pollution and migraine, with inclusion criteria, were entered into the review. Fourteen out of 1417 identified articles met the inclusion criteria and entered the study. Among the gaseous air pollutants, there was a correlation between exposure to nitrogen dioxide (NO2) (78.3% of detrimental relationships) and carbon monoxide (CO) (68.0% of detrimental relationships) and migraine, but no apparent correlation has been found for sulfur dioxide (SO2) (21.2% of detrimental relationships) and ozone (O3) (55.2% of detrimental relationships). In the case of particulate air pollutants, particulate matter with a diameter of 10 μm or less (PM10) (76.0% of detrimental relationships) and particulate matter with a diameter of 2.5 μm or less (PM2.5) (61.3% of detrimental relationships) had relationships with migraine. In conclusion, exposure to NO2, CO, PM10, and PM2.5 is associated with migraine headaches, while no conclusive evidence was found to confirm the correlation between O3 and SO2 with migraine. Further studies with precise methodology are recommended in different cities around the world for all pollutants with an emphasis on O3 and SO2.

Regional impacts on air quality and health of changing a manufacturing facility's grid-boiler to a combined heat and power system

Poor air quality is linked to numerous adverse health effects including strokes, heart attacks, and premature death. Improving energy efficiency in the industrial sector reduces air emissions and yields health benefits. One of these strategies, replacing an existing grid boiler (GB) with a combined heat and power (CHP) system, can improve a facility's energy efficiency but can also increase local air emissions, which in turn can affect health outcomes. Previous studies have considered air-emissions and health outcomes of CHP system installation at a single location, but few studies have investigated the regional air quality and health impacts of replacing an existing GB with new CHP system. This study estimates the emission changes and associated health impacts of this shift in 14 regions in the US, representing different electricity generation profiles. It assumes that one manufacturing facility in each region switches from an existing GB to a CHP system. The monetized annual US health benefits of shifting a single GB to a CHP in each of the 14 regions range from $-5.3 to 0.55 million (2022 USD), while including CHP emission control increases the benefits by 100-170% ($9,000 to 1.15 million (2022 USD)). This study also includes a sensitivity analysis, which suggests that the facility location (region, state, and county), boiler efficiency, and emission control of the CHP are key factors that would determine whether shifting from a GB to CHP system would result in health benefits or burdens.Implications: Combined heat and power (CHP) systems offer industrial facilities the opportunity to improve their energy efficiency and reduce greenhouse gas emissions. However, CHP systems also combust more fuel on site and can also increase local air emissions. This study evaluates how converting an existing grid boiler (GB) system to a CHP system (with or without emission control) affects local (from combustion) and regional emissions (from electricity consumption) and the associated health burdens in different US regions. A facility can use this study's analysis as an example for estimating the tradeoffs between local emission changes, regional emission changes, and health effects. It also provides a comparison between the incremental cost of adding SCR (compared to uncontrolled CHPs) and the NPV of the monetized health benefits associated with adding the SCR.

Exposure duration of ambient fine particulate matter determines the polarization of macrophages

Ambient fine particulate matter (FPM) promotes airway inflammation and aggravates respiratory and cardiovascular diseases. Macrophage polarization plays an essential role in FPM-induced inflammation and tissue repair. The balance of pro-inflammatory M1-type and anti-inflammatory M2-type macrophages determines the fate of tissues and is involved in the pathogenesis of various FPM-induced diseases. The mechanism of macrophage polarization induced by FPM is still not fully understood. Here, we explored the effect of ambient FPM exposure duration on the polarization of peritoneal macrophages. Mice were exposed to concentrated ambient FPM for different duration. Markers of M1-type macrophage and M2-type macrophage in peritoneal macrophages were detected. We found that macrophage polarization was affected by FPM both in vitro and in vivo. Acute FPM stimulation in vitro and short-term concentrated ambient FPM exposure in vivo promoted the expression of NLRP3 and NOS2 and inhibited the expression of ARG1 and CD206. With the extension of concentrated ambient FPM exposure time, ARG1 was gradually up-regulated, and NLRP3 was gradually down-regulated. These results indicate that FPM exposure duration interferes with macrophage polarization. This may provide new insight into the treatment of patients exposed to FPM.

Public health benefits of zero-emission electric power generation in Virginia

Curbing the worst impacts of global climate change will require rapidly transitioning away from fossil fuel across all sectors of the economy. This transition will also yield substantial co-benefits, as fossil fuel combustion releases harmful pollutants into the air. In this article, we present an analysis of the co-benefits to health and health-care costs related from decarbonization of the power sector, using the Virginia Clean Economy Act (VCEA) as a case study. Using a model that combines a source-response matrix approach to pollutant concentration modelling tied to health impact functions, our analysis shows that, by 2045, the VCEA will save up to 32 lives per year across the state, and avoid up to $355 million per year in health-related costs. Fossil-fuel free generation will also help the most disadvantaged communities, as counties in the highest poverty rate quintile also avoid the most pollutant-related deaths.

Seasonal variation in blood pressure: what is still missing?

Seasonal variation of blood pressure (BP) is a topic in cardiology that has gained more attention throughout the years. Although it is extensively documented that BP increases in seasons coupled with lower temperatures, there are still many gaps in this knowledge field that need to be explored. Notably, seasonal variation of BP phenotypes, such as masked and white coat hypertension, and the impact of air pollution, latitude, and altitude on seasonal variation of BP are still poorly described in the literature, and the levels of the existing evidence are low. Therefore, further investigations on these topics are needed to provide robust evidence that can be used in clinical practice.

Air Pollution and Cardiovascular and Thromboembolic Events in Older Adults With High-Risk Conditions

Little epidemiologic research has focused on pollution-related risks in medically vulnerable or marginalized groups. Using a nationwide 50% random sample of 2008-2016 Medicare Part D-eligible fee-for-service participants in the United States, we identified a cohort with high-risk conditions for cardiovascular and thromboembolic events (CTEs) and linked individuals with seasonal average zip-code-level concentrations of fine particulate matter (particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM2.5)). We assessed the relationship between seasonal PM2.5 exposure and hospitalization for each of 7 CTE-related causes using history-adjusted marginal structural models with adjustment for individual demographic and neighborhood socioeconomic variables, as well as baseline comorbidity, health behaviors, and health-service measures. We examined effect modification across geographically and demographically defined subgroups. The cohort included 1,934,453 individuals with high-risk conditions (mean age = 77 years; 60% female, 87% White). A 1-μg/m3 increase in PM2.5 exposure was significantly associated with increased risk of 6 out of 7 types of CTE hospitalization. Strong increases were observed for transient ischemic attack (hazard ratio (HR) = 1.039, 95% confidence interval (CI): 1.034, 1.044), venous thromboembolism (HR = 1.031, 95% CI: 1.027, 1.035), and heart failure (HR = 1.019, 95% CI: 1.017, 1.020). Asian Americans were found to be particularly susceptible to thromboembolic effects of PM2.5 (venous thromboembolism: HR = 1.063, 95% CI: 1.021, 1.106), while Native Americans were most vulnerable to cerebrovascular effects (transient ischemic attack: HR = 1.093, 95% CI: 1.030, 1.161).

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.

A new strategy for risk assessment of PM2.5-bound elements by considering the influence of wind regimes

For regulatory purposes, air pollution has been reduced to management of air quality control regions (AQCR), by inventorying pollution sources and identifying the receptors significantly affected. However, beyond being source-dependent, particulate matter can be physically and chemically altered by factors and elements of climate during transport, as they act as local environmental constraints, indirectly modulating the adverse effects of particles on the environment and human health. This case study, at an industrial site in a Brazilian coastal city - Joinville, combines different methodologies to integrate atmospheric dynamics in a strategic risk assessment approach whereby the influence of different wind regimes on environmental and health risks of exposure to PM_2.5-bound elements, are analysed. Although Joinville AQCR has been prone to stagnation/recirculation events, distinctly different horizontal wind circulation patterns indicate two airsheds within the region. The two sampling sites mirrored these two conditions and as a result we report different PM_2.5 mass concentrations, chemical profiles, geo-accumulation, and ecological and human health risks. In addition, feedback mechanisms between the airsheds seem to aggravate the air quality and its effects even under good ventilation conditions. Recognizably, the risks associated with Co, Pb, Cu, Ni, Mn, and Zn loadings were extremely high for the environment as well as being the main contributors to elevated non-carcinogenic risks. Meanwhile, higher carcinogenic risks occurred during stagnation/recirculation conditions, with Cr as the major threat. These results highlight the importance of integrating local airshed characteristics into the risk assessment of PM_2.5-bound elements since they can aggravate air pollution leading to different risks at a granular scale. This new approach to risk assessment can be employed in any city's longer-term development plan since it provides public authorities with a strategic perspective on incorporating environmental constraints into urban growth planning and development zoning regulations.

Effects of ambient air pollution on cause-specific hospitalizations in Wuhan during 2017-2019

BACKGROUND

Few studies have focused on the associations between air pollutants and multiple organ system diseases in the entire hospitalized population. The present study aims to explore the short-term effects of six routinely monitored air pollutants on the broad causes of hospital admissions and estimate the resulting hospital admission burdens.

METHODS

Daily hospital admission records from 2017 to 2019 were obtained from the Wuhan Information center of Health and Family Planning. Generalized additive models (GAMs) were employed to evaluate the effects of air pollutants on the percent increase in the cause-specific daily number of hospital admissions. Increased hospital admission numbers, days, and expenses were also estimated.

RESULTS

A total of 2636,026 hospital admissions were identified. We found that both PM_2.5 and PM₁₀ increased the risk of hospital admissions for most disease categories. Short-term exposure to PM_2.5 was positively associated with hospitalizations of several rarely studied disease categories, such as diseases of the eye and adnexa (2.83%, 95%CI: 0.96-4.73%, P < 0.01) and diseases of the musculoskeletal system and connective tissue (2.17%, 95% CI: 0.88-3.47%, P < 0.001). NO₂ was observed to have a robust effect on diseases of the respiratory system (1.36%, 95%CI: 0.74-1.98%, P < 0.001). CO was significantly associated with hospital admissions for six disease categories. Furthermore, each 10-μg/m³ increase in PM_2.5 was associated with an annual increase of 13,444 hospital admissions (95% CI: 6239-20,649), 124,344 admission days (95% CI: 57,705-190,983), and 166-million-yuan admission expenses (95% CI: 77-255).

CONCLUSION

Our study suggested that particulate matter (PM) had a short-term effect on hospital admissions of most major disease categories and resulted in a considerable hospital admission burden. In addition, the health effects of NO₂ and CO emissions require more attention in megacities.

Emergency Department Visits in Children Associated with Exposure to Ambient PM1 within Several Hours

BACKGROUND

Emerging evidence has integrated short-term exposure to PM₁ with children's morbidity and mortality. Nevertheless, most available studies have been conducted on a daily scale, ignoring the exposure variations over the span of a day.

OBJECTIVE

The main intention of this study was to examine the association between pediatric emergency department visits (PEDVs) and intra-day exposures to PM₁ and PM_2.5. We also aimed to investigate whether a high PM₁/PM_2.5 ratio elevated the risk of PEDVs independent from PM_2.5 exposure within several hours.

METHODS

We collected hourly data on aerial PM₁ and PM_2.5 concentrations, all-cause PEDVs, and meteorological factors from two megacities (i.e., Guangzhou and Shenzhen) in southern China during 2015-2016. Time-stratified case-crossover design and conditional logistic regression analysis were used to assess the associations of PEDVs with exposures to PM₁ and PM_2.5 at different lag hours. The contribution of PM₁ to PM_2.5-associated risk was quantified by introducing PM₁/PM_2.5 ratio as an additional exposure indicator in the analysis adjusting for PM_2.5. Subgroup analyses were performed stratified by sex, age, and season.

RESULTS

During this study period, 97,508 and 101,639 children were included from Guangzhou and Shenzhen, respectively. PM₁ and PM_2.5 exposures within several hours were both remarkably related to an increased risk of PEDVs. Risks for PEDVs increased by 3.9% (95% confidence interval [CI]: 2.7-5.0%) in Guangzhou and 3.2% (95% CI: 1.9-4.4%) in Shenzhen for each interquartile range (Guangzhou: 21.4 μg/m³, Shenzhen: 15.9 μg/m³) increase in PM₁ at lag 0-3 h, respectively. A high PM₁/PM_2.5 ratio was substantially correlated with increased PEDVs, with an excess risk of 2.6% (95% CI: 1.2-4.0%) at lag 73-96 h in Guangzhou and 1.2% (95% CI: 0.4-2.0%) at lag 0-3 h in Shenzhen. Stratified analysis showed a clear seasonal pattern in PM-PEDVs relationships, with notably stronger risks in cold months (October to March of the following year) than in warm months (April to September).

CONCLUSIONS

Exposures to ambient PM₁ and PM_2.5 within several hours were related to increased PEDVs. A high PM₁/PM_2.5 ratio may contribute an additional risk independent from the short-term impacts of PM_2.5. These findings highlighted the significance of reducing PM₁ in minimizing health risks due to PM_2.5 exposure in children.

Associations between short-term exposure of ambient particulate matter and hemodialysis patients death: A nationwide, longitudinal case-control study in China

BACKGROUND

Long-term exposure to particulate air pollutants can lead to an increase in mortality of hemodialysis patients, but evidence of mortality risk with short-term exposure to ambient particulate matter is lacking. This study aimed to estimate the association of short-term exposure to ambient particulate matter across a wide range of concentrations with hemodialysis patients mortality.

METHODS

We performed a time-stratified case-crossover study to estimate the association between short-term exposures to PM_2.5 and PM₁₀ and mortality of hemodialysis patients. The study included 18,114 hemodialysis death case from 279 hospitals in 41 cities since 2013. Daily particulate matter exposures were calculated by the inverse distance-weighted model based on each case's dialysis center address. Conditional logistic regression were implemented to quantify exposure-response associations. The sensitivity analysis mainly explored the lag effect of particulate matter.

RESULTS

During the study period, there were 18,114 case days and 61,726 control days. Of all case and control days, average PM_2.5 and PM₁₀ levels were 43.98 μg/m³ and 70.86 μg/m³, respectively. Each short-term increase of 10 μg/m³ in PM_2.5 and PM₁₀ were statistically significantly associated with a relative increase of 1.07 % (95 % confidence interval [CI]: 0.99 % - 1.15 %) and 0.89 % (95 % CI: 0.84 % - 0.94 %) in daily mortality rate of hemodialysis patients, respectively. There was no evidence of a threshold in the exposure-response relationship. The mean of daily exposure on the same day of death and one-day prior (Lag 01 Day) was the most plausible exposure time window.

CONCLUSIONS

This study confirms that short-term exposure to particulate matter leads to increased mortality in hemodialysis patients. Policy makers and public health practices have a clear and urgent opportunity to pass air quality control policies that care for hemodialysis populations and incorporate air quality into the daily medical management of hemodialysis patients.

Time-varying association between fetal death and gestational exposure to ambient fine particles: a nationwide epidemiological study of 49 million fetuses in the contiguous US from 1989 to 2004

BACKGROUND

Gestational exposure to fine particulate matter (PM2.5) has been reported to be associated with an increased risk of fetal death in recent studies, but earlier studies in the past century have usually reported a non-significant association. As such, it remains unknown whether this adverse effect of PM2.5 exposure varies with time.

METHODS

Nearly 49.2 million eligible birth and fetal death records from 1989 to 2004 were selected from the United States (US) birth and fetal death certificate datasets. For each record, the level of prenatal exposure to PM2.5 was taken as the average concentration in the mother's residential county during the entire gestational period, according to well-established estimates of monthly levels across the contiguous US. We first stratified the dataset by the month of the last menstrual period (LMP) and then independently evaluated the nationwide association between PM2.5 exposure and fetal death within each stratum using five typical logit models: unadjusted, covariate-adjusted, propensity-score, double robust, and diagnostic-score models. Finally, we conducted a meta-analysis to pool estimated LMP-specific associations and explored how the overall association varied by LMP month.

RESULTS

Different models showed temporal heterogeneity in the estimated association between PM2.5 exposure and fetal death. According to the meta-analysis, double robust model estimates were more homogeneous than the rest, and thus the model outcome was recognized as the main result. For each 1-µg/m3 increase in prenatal exposure to PM2.5, the pooled odds ratio (OR) of fetal death was estimated to be 1.08 [95% confidence interval (CI): 1.05, 1.10]. The LMP-specific ORs exhibited a slightly increasing trend and a significant seasonal pattern. Compared with the pooled OR among samples with the LMP in spring, the estimates for summer, fall and winter were higher by 11.1% (95% CI: 6.2%, 16.3%), 27.8% (95% CI: 22.1%, 33.8%) and 28.8% (95% CI: 23.7%, 34.1%), respectively. We also found that temporal patterns in the association between PM2.5 exposure and fetal death could be explained by several population-level indicators or modifiers (i.e. ethnicity, maternal age, gestational weight gain, previous pregnancy of abnormal termination and diabetes).

CONCLUSIONS

Prenatal exposure to PM2.5 can increase the risk of fetal death. The effects of PM2.5 exposure may be modified by complex factors, which leads to a time-varying association.

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

BACKGROUND

Short-term fine particulate matter (PM_2.5) 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 PM_2.5 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 PM_2.5 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 PM_2.5 and specific constituents were significantly associated with increased circulatory mortality. An increase of interquartile range of traffic-related PM_2.5, 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 PM_2.5 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 PM_2.5 and specific constituents with circulatory mortality. Further emissions abatement from the transportation sector and corresponding pollutants should merit a particular focus in China.

Short-term exposure to fine particulate matter constituents and mortality: case-crossover evidence from 32 counties in China

A growing number of studies associated increased mortality with exposures to specific fine particulate (PM_2.5) constituents, while great heterogeneity exists between locations. In China, evidence linking PM_2.5 constituents and mortality was extensively sparse. This study primarily aimed to quantify short-term associations between PM_2.5 constituents and non-accidental mortality among the Chinese population. We collected daily mortality records from 32 counties in China between January 1, 2011, and December 31, 2013. Daily concentrations of main PM_2.5 constituents (organic carbon (OC), elemental carbon (EC), nitrate (NO₃^-), sulfate (SO₄^2-), and ammonium (NH₄⁺)) were estimated using the modified Community Multiscale Air Quality model. Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM_2.5 mass and its constituents. Stratification analyses were done by sex, age, and season. A total of 116,959 non-accidental deaths were investigated. PM_2.5 concentrations on the day of death were averaged at 75.7 µg m^-3 (control day: 75.6 µg m^-3), with an interquartile range (IQR) of 65.2 µg m^-3. Per IQR rise in PM_2.5, EC, OC, NO₃^-, SO₄^2-, and NH₄⁺ at lag-04 day was associated with an increase in non-accidental mortality of 2.4% (95% confidence interval, (1.0-3.7), 1.7% (0.8-2.7), 2.9% (1.6-4.3), 2.1% (0.4-3.9), 1.0% (0.2-1.9), and 1.6% (0.3-2.9), respectively. Both PM_2.5 mass and its constituents were strongly associated with elevated cardiovascular mortality risks, but only PM_2.5, EC, and OC were positively associated with respiratory mortality at lag-3 day. PM_2.5 mass and its constituents associated effects on mortality varied among sex- and age-specific subpopulations. Differences in the seasonal pattern of associations exist among PM_2.5 constituents, with stronger effects related to EC and NO₃^- in warm months but SO₄^2- and NH₄⁺ in cold months. Short-term exposures to PM_2.5 compositions were positively associated with increased risks of mortality, particularly those constituents from combustion-related sources.

The Effects of Short-Term PM2.5 Exposure on Pulmonary Function among Children with Asthma-A Panel Study in Shanghai, China

Fine particulate matter (PM_2.5) has been reported to be an important risk factor for asthma. This study was designed to evaluate the relationship between PM_2.5 and lung function among children with asthma in Shanghai, China. From 2016 to 2019, a total of 70 Chinese children aged 4 to 14 in Shanghai were recruited for this panel study. The questionnaire was used to collect baseline information, and the lung function covering forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were carried out for each child more than twice during follow-up. Meanwhile, the simultaneous daily air atmospheric pollutants and meteorological data were collected. The linear mixed effect (LME) model was used to assess the relationship between air pollutants and lung function. A significantly negative association was found between PM_2.5 and lung function in children with asthma. In the single-pollutant model, the largest effects of PM_2.5 on lung function were found for lag 0-2, with FVC and FEV1 decreasing by 0.91% [95% confidence interval (CI): -1.75, -0.07] and 1.05% (95% CI: -2.09, 0.00), respectively, for each 10 μg/m³ increase in PM_2.5. In the multi-pollution model (adjusted PM_2.5 + SO₂ + O₃), the maximum effects of PM_2.5 on FVC and FEV1 also appeared for lag 0-2, with FVC and FEV1 decreasing by 1.57% (95% CI: -2.69, -0.44) and 1.67% (95% CI: -3.05, -0.26), respectively, for each 10 μg/m³ increase in PM_2.5. In the subgroup analysis, boys, preschoolers (<6 years old) and hot seasons (May to September) were more sensitive to changes. Our findings may contribute to a better understanding of the short-term exposure effects of PM_2.5 on lung function in children with asthma.

Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina

Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler ("downscaler") model, which provides spatial predictions of daily concentrations of fine particulate matter (PM2.5) and ozone (O3) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM2.5 and lower levels of O3. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM2.5 and O3, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PEPM2.5 and PEO3) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM2.5 and O3 levels decreased and O3 predictions became more reliable. However, the predictive uncertainty for PM2.5 has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM2.5. In contrast, racial isolation was associated with a greater decline in the reliability of PM2.5 predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O3 within the same time frame.

Association of ambient PM1 with hospital admission and recurrence of stroke in China

BACKGROUND

Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM₁ (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM₁ with hospital admission and recurrence of stoke in China.

METHODS

Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM₁ concentration was estimated by a generalized additive model (GAM) using PM_2.5 and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM₁ with hospital admission of stroke. A GAM model was used to estimate the association between average PM₁ exposure during hospitalization and the recurrence of stroke.

RESULTS

A total of 989,591 stroke cases were included in the study. Each 10 μg/m³ increase in PM₁ (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM₁ on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m³ increase in PM₁ was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization.

CONCLUSIONS

Short-term exposure to PM₁ may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM₁.

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population

While associations between short-term exposure to fine particulate matter (PM_2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM_2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM_2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM_2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 μg/m³ increase in PM_2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM_2.5-related health burden. This study raises the importance of considering environmental justice issues in PM_2.5-related health impacts with respect to how associations may change over time.

Air pollution exposure disparities across US population and income groups

Air pollution contributes to the global burden of disease, with ambient exposure to fine particulate matter of diameters smaller than 2.5 μm (PM2.5) being identified as the fifth-ranking risk factor for mortality globally1. Racial/ethnic minorities and lower-income groups in the USA are at a higher risk of death from exposure to PM2.5 than are other population/income groups2-5. Moreover, disparities in exposure to air pollution among population and income groups are known to exist6-17. Here we develop a data platform that links demographic data (from the US Census Bureau and American Community Survey) and PM2.5 data18 across the USA. We analyse the data at the tabulation area level of US zip codes (N is approximately 32,000) between 2000 and 2016. We show that areas with higher-than-average white and Native American populations have been consistently exposed to average PM2.5 levels that are lower than areas with higher-than-average Black, Asian and Hispanic or Latino populations. Moreover, areas with low-income populations have been consistently exposed to higher average PM2.5 levels than areas with high-income groups for the years 2004-2016. Furthermore, disparities in exposure relative to safety standards set by the US Environmental Protection Agency19 and the World Health Organization20 have been increasing over time. Our findings suggest that more-targeted PM2.5 reductions are necessary to provide all people with a similar degree of protection from environmental hazards. Our study is observational and cannot provide insight into the drivers of the identified disparities.

Air pollution and cardiovascular disease hospitalization - Are associations modified by greenness, temperature and humidity?

BACKGROUND

Studies have observed associations between long-term air pollution and cardiovascular disease hospitalization. Little is known, however, about effect modification of these associations by greenness, temperature and humidity.

METHODS

We constructed an open cohort consisting of all fee-for-service Medicare beneficiaries, aged ≥ 65, living in the contiguous US from 2000 through 2016 (~63 million individuals). We assigned annual average PM2.5, NO2 and ozone zip code concentrations. Cox-equivalent Poisson models were used to estimate associations with first cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization.

RESULTS

PM2.5 and NO2 were both positively associated with CVD, CHD and CBV hospitalization, after adjustment for potential confounders. Associations were substantially stronger at the lower end of the exposure distributions. For CVD hospitalization, the hazard ratio (HR) of PM2.5 was 1.041 (1.038, 1.045) per IQR increase (4.0 µg/m3) in the full study population and 1.327 (1.305, 1.350) per IQR increase for a subgroup with annual exposures always below 10 µg/m3 PM2.5. Ozone was only positively associated with CVD, CHD and CBV hospitalization for the low-exposure subgroup (<40 ppb). Associations of PM2.5 were stronger in areas with higher greenness, lower ozone and Ox, lower summer and winter temperature and lower summer and winter specific humidity.

CONCLUSION

PM2.5 and NO2 were positively associated with CVD, CHD and CBV hospitalization. Associations were more pronounced at low exposure levels. Associations of PM2.5 were stronger with higher greenness, lower ozone and Ox, lower temperature and lower specific humidity.

Effects of Fine Particulate Matter and Its Components on Emergency Room Visits for Pediatric Pneumonia: A Time-Stratified Case-Crossover Study

Pneumonia, one of the important causes of death in children, may be induced or aggravated by particulate matter (PM). Limited research has examined the association between PM and its constituents and pediatric pneumonia-related emergency department (ED) visits. Measurements of PM_2.5, PM₁₀, and four PM_2.5 constituents, including elemental carbon (EC), organic carbon (OC), nitrate, and sulfate, were extracted from 2007 to 2010 from one core station and two satellite stations in Kaohsiung City, Taiwan. Furthermore, the medical records of patients under 17 years old who had visited the ED in a medical center and had a diagnosis of pneumonia were collected. We used a time-stratified, case-crossover study design to estimate the effect of PM. The single-pollutant model demonstrated interquartile range increase in PM_2.5, PM₁₀, nitrate, OC, and EC on lag 3, which increased the risk of pediatric pneumonia by 18.2% (95% confidence interval (Cl), 8.8-28.4%), 13.1% (95% CI, 5.1-21.7%), 29.7% (95% CI, 16.4-44.5%), 16.8% (95% CI, 4.6-30.4%), and 14.4% (95% Cl, 6.5-22.9%), respectively. After PM_2.5, PM₁₀, and OC were adjusted for, nitrate and EC remained significant in two-pollutant models. Subgroup analyses revealed that nitrate had a greater effect on children during the warm season (April to September, interaction p = 0.035). In conclusion, pediatric pneumonia ED visit was related to PM_2.5 and its constituents. Moreover, PM_2.5 constituents, nitrate and EC, were more closely associated with ED visits for pediatric pneumonia, and children seemed to be more susceptible to nitrate during the warm season.

Risk of Cardiovascular Hospital Admission After Exposure to Fine Particulate Pollution

BACKGROUND

Heavy fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM_2.5) pollution events continue to occur frequently in developing countries.

OBJECTIVES

The authors conducted a case-crossover study aimed at exploring the association between heavy PM_2.5 pollution events and hospital admission for cardiovascular diseases.

METHODS

Hospital admissions for cardiovascular diseases were observed by Beijing Municipal Commission of Health and Family Planning Information Center from 2013 to 2017. Air pollution data were collected from the Beijing Municipal Environmental Monitoring Center. Distinct definitions were used to identify heavy and extremely heavy fine particulate pollution events. A conditional logistic regression model was used. The hospital admission burdens for cardiovascular disease were also estimated.

RESULTS

A total of 2,202,244 hospital admissions for cardiovascular diseases and 222 days of extremely heavy PM_2.5 pollution events (PM_2.5 concentration ≥150 μg/m³) were observed. The ORs associated with extremely heavy PM_2.5 pollution events lasting for 3 days or more for total cardiovascular disease, angina, myocardial infarction, ischemic stroke, and heart failure were 1.085 (95% CI: 1.077-1.093), 1.112 (95% CI: 1.095-1.130), 1.068 (95% CI: 1.037-1.100), 1.071 (95% CI: 1.053-1.090), and 1.060 (95% CI: 1.021-1.101), respectively. The numbers and days of cardiovascular disease hospital admission annually related to extremely heavy PM_2.5 pollution events lasting for 1 day or more were 3,311 (95% CI: 2,969-3,655) and 37,020 (95% CI: 33,196-40,866), respectively.

CONCLUSIONS

Heavy and extremely heavy PM_2.5 pollution events resulted in substantial increased hospital admission risk for cardiovascular disease. With higher PM_2.5 concentration and longer duration of heavy PM_2.5 pollution events, a greater risk of cardiovascular hospital admission was observed.

Relationship between fine particulate air pollution and hospital admissions for depression: a case-crossover study in Taipei

There are few apparent studies regarding the association between fine particulate matter (PM_2.5) air pollution and development of depression. Data obtained from epidemiological studies are inconsistent and controversial. The aim of this case-crossover study was to examine the association between short-term exposure to PM_2.5 alone and in combination with other pollutants and frequency of hospitalizations for depression from 2009 to 2013 in Taipei, Taiwan. In the single pollutant model without adjustment for other pollutants, 17% and 4% increase in admissions attributed to depression correlated with interquartile range (IQR) rise in PM_2.5 levels was noted on warm and cool days, respectively. Data were also analyzed using two-pollutant models and it was found that on warm days, the association continued to be significant after including one of the following pollutants: sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃) or carbon monoxide (CO). On cool days, the significance was lost. In conclusion, the relationship between ambient outdoor PM_2.5 exposure and rates of hospitalization for depression appeared to be temperature dependent in Taipei. Further research is needed to verify these observations as well as to distinguish the relative contributions of PM_2.5 and temperature to development for hospital admissions for depression.

A 10-year assessment of ambient fine particles and related health endpoints in a large Mediterranean city

Fine particles i.e., with an aerodynamic diameter lower than 2.5 μm (PM_2.5) have potentially the most significant effects on human health compared to other air pollutants. The main objectives of this study were to i) investigate the temporal variations of ambient PM_2.5 in Marseille (Southern France), where air pollution is again a major public health issue, and ii) estimate their short-term health effects and annual trend (Mann-Kendall test) over a 10-year period from 2010 to 2019. In Marseille, the main sources of PM_2.5 could be related to road traffic, industrial complexes, and oil refineries surrounded the city. The number of premature deaths and hospital admissions attributable to ambient PM_2.5 exposure for non-accidental causes, cardiovascular and respiratory diseases were estimated by using in-situ air quality data, city-specific relative risk values and baseline incidence. Despite significant reduction of PM_2.5 (- 0.80 μg m^-3 year^-1), Marseille citizens were exposed to PM_2.5 levels exceeding the World Health Organization (WHO) Air Quality Guideline for human health protection (10 μg m^-3) during entire study period. Exposure to ambient PM_2.5 substantially contributed to mortality and hospital admissions: 871 deaths for non-accidental causes, 515 deaths for cardiovascular diseases, 47 deaths for respiratory diseases, as well as 1034 hospital admissions for cardiovascular diseases and 834 for respiratory diseases were reported between 2010 and 2019. Compliance with WHO annual limit values can result in substantial socio-economic benefits by preventing premature deaths and hospital admissions. For instance, based on the value of a statistical life and average cost of a hospital admission, the associated benefit for healthcare would have been €131 million in 2019. Between 2010 and 2019, the number of PM_2.5-related non-accidental deaths decreased by 1.15 per 10⁵ inhabitants annually. Compared to 2010-2019, the restrictive measures associated to COVID-19 pandemic led to a reduction in PM_2.5 of 11% in Marseille, with 2.6 PM_2.5-related deaths averted in 2020.

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 (PM_2.5) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM_2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM_2.5 dataset.

RESULTS

For all PM_2.5 datasets, we observed positive associations between PM_2.5 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 PM_2.5. 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 PM_2.5 and CVD admissions, regardless of model choice.

Repeated exposure to fine particulate matter constituents lead to liver inflammation and proliferative response in mice

BACKGROUND

Fine particulate matter (particulate matter with aerodynamic diameter of ≦2.5 µm, PM2.5) exposure cause adverse health effects, including lung inflammation. Through intra-tracheal instillation of PM2.5 components, the study aimed to evaluate the inflammatory and proliferative effects on mice liver. PM2.5 samples were collected near an industrial complex at southern Taiwan. Mice were exposed to water extracts or insoluble particles by intra-tracheal instillation. Male C57BL/6 mice were divided into five groups: control, low dose insoluble particle exposure (LP), high dose insoluble particle exposure (HP), low dose water extract exposure (LW), and high dose water extract exposure (HW). Biochemical analysis, western blotting, histological examination, and immunohistochemistry were employed to evaluate the results.

RESULT

Enrichment factor (EF) of metallic elements showed that the EFs of trace elements (Ti, V, Ni, Zn, Pb, Cr, and Cu) in PM2.5 were above 10. Hematoxylin and Eosin (H&E) staining of the liver tissue showed inflammatory infiltration in particle exposure group; hepatocyte ballooning degeneration and karyomegaly were seen in the water extract exposure group. Upregulation of inflammatory signaling, p65 and p50, and caspase-3 (an important effector involved in apoptosis) positive hepatocytes was significantly increased in the HP group, followed by an elevation in protein levels of growth arrest and DNA damage-inducible protein 153 (GADD153). Increased protein expression of proliferating cell nuclear antigen (PCNA) was noted in the LW and HW groups. An increase in phosphorylation of regulators of cell proliferation, Akt and extracellular signal-regulated kinase (ERK) 1/2, were detected in the LW and HW groups.

CONCLUSION

The present study shows that the insoluble particle composition of PM2.5 induced inflammatory signaling and cytokines upregulation in the liver, accompanied with inflammatory cell and macrophage infiltration and an abnormal liver function. Exposure of water extract to PM2.5 induced signals of upregulated cellular proliferation, elevated markers of cell proliferation in liver, hepatocyte ballooning degeneration and karyomegaly.

Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset

BACKGROUND

Short-term exposure to fine particulate matter (PM_2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM_2·5. Policies to control PM_2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM_2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM_2·5 varied over time in the USA.

METHODS

We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM_2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate.

FINDINGS

The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM_2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 μg/m³ increase in previous-day PM_2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to -0·28% (-0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM_2·5 and circulatory hospitalisation.

INTERPRETATION

Hospitalisation risk from PM_2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM_2·5 and suggests caution in applying association estimates to a different time period.

FUNDING

US Environmental Protection Agency and Yale Institute for Biospheric Studies.

Relationship between different air pollutants and total and cause-specific emergency ambulance dispatches in Shanghai, China

OBJECTIVE

Air pollutants play a crucial role in human health and disease. Emergency ambulance dispatch data have excellent potential for public and environmental health research. This study aimed at investigating the impact of short-term exposure to air pollutants on the emergency ambulance dispatches.

METHODS

We used data on emergency ambulance dispatches in Shanghai Municipality, China, from April 1, 2016 to December 31, 2017. The association of the daily emergency ambulance dispatches with air pollutants including PM_2.5 (particles ≤ 2.5 μm in aerodynamic diameter), PM₁₀, O₃, NO₂ and SO₂ was analyzed with the use of time-series analyses.

RESULTS

A total of 310,825 emergency ambulance dispatches for acute illness occurred in Shanghai during the study period. An increase in PM_2.5 by 10 μg/m³ at lag1 and lag2 was shown to increase the risk of emergency ambulance dispatches (RR for lag1 = 1.05, 95% CI 1.00-1.11, RR for lag2 = 1.07, 95% CI 1.01-1.12). PM₁₀, NO₂, and SO₂ also showed significant associations with emergency ambulance dispatches in single-pollutant models. Cause-specific analyses showed an elevation in PM_2.5 by 10 μg/m³ was associated with an increased risk of emergency ambulance dispatches related to respiratory diseases on the current day (lag0, RR 1.17, 95% CI 1.01-1.33), while the impact on emergency ambulance dispatches related to other diseases presented 1-3 days later. The other pollutants have the similar trend.

CONCLUSIONS

Our findings show a strong relationship between ambient air pollutants and emergency ambulance dispatches. Our study contributes to the growing body of evidence describing the adverse health effects of ambient air pollution and will benefit ambulance services for early warning and effective ambulatory planning.

Spatial Analysis of Ambient Air Pollution and Cardiovascular Disease (CVD) Hospitalization Across Sweden

The associations of multiple pollutants and cardiovascular disease (CVD) morbidity, and the spatial variations of these associations have not been nationally studied in Sweden. The main aim of this study was, thus, to spatially analyze the associations between ambient air pollution (black carbon, carbon monoxide, particulate matter (both <10 µm and <2.5 µm in diameter) and Sulfur oxides considered) and CVD admissions while controlling for neighborhood deprivation across Sweden from 2005 to 2010. Annual emission estimates across Sweden along with admission records for coronary heart disease, ischemic stroke, atherosclerotic and aortic disease were obtained and aggregated at Small Areas for Market Statistics level. Global associations were analyzed using global Poisson regression and spatially autoregressive Poisson regression models. Spatial non-stationarity of the associations was analyzed using Geographically Weighted Poisson Regression. Generally, weak but significant associations were observed between most of the air pollutants and CVD admissions. These associations were non-homogeneous, with more variability in the southern parts of Sweden. Our study demonstrates significant spatially varying associations between ambient air pollution and CVD admissions across Sweden and provides an empirical basis for developing healthcare policies and intervention strategies with more emphasis on local impacts of ambient air pollution on CVD outcomes in Sweden.

Effect of ambient fine particulates (PM2.5) on hospital admissions for respiratory and cardiovascular diseases in Wuhan, China

Background

Positive associations between ambient PM_2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM_2.5 based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error.

Methods

This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM_2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM_2.5. We also conducted stratification analyses by age, sex, and season.

Results

A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM_2.5 was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m³ increase in PM_2.5 (lag0–2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01–1.45%) and 1.95% (95% CI 1.63–2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season.

Conclusions

This study contributes evidence of short-term effects of PM_2.5 on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01731-x.

Short-Term Effects of Particulate Matter and Its Constituents on Emergency Room Visits for Chronic Obstructive Pulmonary Disease: A Time-Stratified Case-Crossover Study in an Urban Area

Background: PM_2.5 exposure is associated with pulmonary and airway inflammation, and the health impact might vary by PM_2.5 constitutes. This study evaluated the effects of increased short-term exposure to PM_2.5 constituents on chronic obstructive pulmonary disease (COPD)-related emergency department (ED) visits and determined the susceptible groups. Methods: This retrospective observational study performed in a medical center from 2007 to 2010, and enrolled non-trauma patients aged >20 years who visited the emergency department (ED) and were diagnosed as COPD. Concentrations of PM_2.5, PM₁₀, and the four PM_2.5 components, including organic carbon (OC), elemental carbon (EC), nitrate (NO₃⁻), and sulfate (SO₄²⁻), were collected by three PM supersites in Kaohsiung City. We used an alternative design of the Poisson time series regression models called a time-stratified and case-crossover design to analyze the data. Results: Per interquartile range (IQR) increment in PM_2.5 level on lag 2 were associated with increments of 6.6% (95% confidence interval (CI), 0.5–13.0%) in risk of COPD exacerbation. An IQR increase in elemental carbon (EC) was significantly associated with an increment of 3.0% (95% CI, 0.1–5.9%) in risk of COPD exacerbation on lag 0. Meanwhile, an IQR increase in sulfate, nitrate, and OC levels was not significantly associated with COPD. Patients were more sensitive to the harmful effects of EC on COPD during the warm season (interaction p = 0.019). The risk of COPD exacerbation after exposure to PM_2.5 was higher in individuals who are currently smoking, with malignancy, or during cold season, but the differences did not achieve statistical significance. Conclusion: PM_2.5 and EC may play an important role in COPD events in Kaohsiung, Taiwan. Patients were more susceptible to the adverse effects of EC on COPD on warm days.

Cardiovascular morbidity and mortality associations with biomass- and fossil-fuel-combustion fine-particulate-matter exposures in Dhaka, Bangladesh

BACKGROUND

Fine-particulate-matter (i.e. with an aerodynamic diameter of ≤2.5 µm, PM2.5) air pollution is commonly treated as if it had 'equivalent toxicity', irrespective of the source and composition. We investigate the respective roles of fossil-fuel- and biomass-combustion particles in the PM2.5 relationship with cardiovascular morbidity and mortality using tracers of sources in Dhaka, Bangladesh. Results provide insight into the often observed levelling of the PM2.5 exposure-response curve at high-pollution levels.

METHODS

A time-series regression model, adjusted for potentially confounding influences, was applied to 340 758 cardiovascular disease (CVD) emergency-department visits (EDVs) during January 2014 to December 2017, 253 407 hospital admissions during September 2013 to December 2017 and 16 858 CVD deaths during January 2014 to October 2017.

RESULTS

Significant associations were confirmed between PM2.5-mass exposures and increased risk of cardiovascular EDV [0.27%, (0.07% to 0.47%)] at lag-0, hospitalizations [0.32% (0.08% to 0.55%)] at lag-0 and deaths [0.87%, (0.27% to 1.47%)] at lag-1 per 10-μg/m3 increase in PM2.5. However, the relationship of PM2.5 with morbidity and mortality effect slopes was less steep and non-significant at higher PM2.5 concentrations (during crop-burning-dominated exposures) and varied with PM2.5 source. Fossil-fuel-combustion PM2.5 had roughly a four times greater effect on CVD mortality and double the effect on CVD hospital admissions on a per-µg/m3 basis than did biomass-combustion PM2.5.

CONCLUSION

Biomass burning was responsible for most PM2.5 air pollution in Dhaka, but fossil-fuel-combustion PM2.5 dominated the CVD adverse health impacts. Such by-source variations in the health impacts of PM2.5 should be considered in conducting ambient particulate-matter risk assessments, as well as in prioritizing air-pollution-mitigation measures and clinical advice.

Change in risk of hospital admissions for ischemic heart disease after the implementation of a mass rapid transit system in Taipei

Numerous epidemiologic studies demonstrated an association between an increase in levels of fine particles (particulate matter less than 2.5 um in diameter, PM_2.5) and elevation in the number of hospital admissions for cardiovascular diseases. Air pollution levels including PM_2.5 clearly decreased in Taipei City after the mass rapid transit (MRT) system began operations in 1996. The aim of this study was to investigate the extent of changes in the risk of daily hospital admissions for ischemic heart disease (IHD) over a 17-year period after the installation of a MRT system in Taipei. The full study was divided into Period 1 (1997-2000), total track length 65.1 km; Period 2 (2001-2008), total track length 75.8 km; and Period 3 (2009-2013), total track length 121.3 km. A time-stratified case-crossover analysis was conducted to estimate relative risk (RR) of hospital admissions for IHD for each 10 ug/m³ increase in PM_2.5 for different periods. On cool days, the associated RR of IHD for Period 3 was consistently lower compared to period 2 in both our single- and two-pollutant models. However, the daily risk for IHD admissions was found to be significantly higher for period 3 compared to period 2 in our single-pollutant model and in our two-pollutant models (PM_2.5+ SO₂) on warm days. The basis for this difference is unknown. Data suggests that an MRT system may provide substantial health benefits, a finding that may be helpful to urban communities, urban planners, and public health specialists.

The Environmental and Health Impacts of Poverty Alleviation in China: From a Consumption-Based Perspective

Poverty alleviation, environmental protection, and healthcare are the three biggest challenges for the Sustainable Development Goals. However, they are also inter-linked. Therefore, it is imperative to achieve these goals in a compatible manner at the national level. Given the growing consumption caused by poverty alleviation in China, this paper investigates potential impacts of poverty alleviation on the environment and health based on an input–output approach, air quality estimation model, and health loss assessment. Due to data limitations, the base year was set as 2012. Nevertheless, the scientific value of the paper is that it offers an important supplement for a preliminary estimation on a macro level. We find that poverty alleviation could be a substantial threat to the environment and health from a consumption-based perspective, and this trade-off can be explained by the uneven pollution footprints per capita among different income groups. From a policy perspective, the government should promote green production, green lifestyles, and healthcare when reducing poverty.

Fine Particulate Matter (PM2.5) and Chronic Kidney Disease

The impact of ambient particulate matter (PM) on public health has become a great global concern, which is especially prominent in developing countries. For health purposes, PM is typically defined by size, with the smaller particles having more health impacts. Particles with a diameter <2.5 μm are called PM_2.5. Initial research studies have focused on the impact of PM_2.5 on respiratory and cardiovascular diseases; nevertheless, an increasing number of data suggested that PM_2.5 may affect every organ system in the human body, and the kidney is of no exception. The kidney is vulnerable to particulate matter because most environmental toxins are concentrated by the kidney during filtration. According to the high morbidity and mortality related to chronic kidney disease, it is necessary to determine the effect of PM_2.5 on kidney disease and its mechanism that needs to be identified. To understand the current status of PM_2.5 in the atmosphere and their potential harmful kidney effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 1998. In this review, we focus on the worldwide epidemiological evidence linking PM_2.5 with chronic kidney disease and the effect of PM_2.5 on the chronic kidney disease (CKD) progression. At the same time, we also discuss the possible mechanisms of PM_2.5 exposure leading to kidney damage, in order to emphasize the contribution of PM_2.5 to kidney damage. A global database on PM_2.5 and kidney disease should be developed to provide new ideas for the prevention and treatment of kidney disease.

Hybrid Fuel Cell—Supercritical CO2 Brayton Cycle for CO2 Sequestration-Ready Combined Heat and Power

The low prices and its relatively low carbon intensity of natural gas have encouraged the coal replacement with natural gas power generation. Such a replacement reduces greenhouse gases and other emissions. To address the significant energy penalty of carbon dioxide (CO2) sequestration in gas turbine systems, a novel high efficiency concept is proposed and analyzed, which integrates a flame-assisted fuel cell (FFC) with a supercritical CO2 (sCO2) Brayton cycle air separation. The air separation enables the exhaust from the system to be CO2 sequestration-ready. The FFC provides the heat required for the sCO2 cycle. Heat rejected from the sCO2 cycle provides the heat required for adsorption-desorption pumping to isolate oxygen via air separation. The maximum electrical efficiency of the FFC sCO2 turbine hybrid (FFCTH) without being CO2 sequestration-ready is 60%, with the maximum penalty being 0.68% at a fuel-rich equivalence ratio (Φ) of 2.8, where Φ is proportional to fuel-air ratio. This electrical efficiency is higher than the standard sCO2 cycle by 6.85%. The maximum power-to-heat ratio of the sequestration-ready FFCTH is 233 at a Φ = 2.8. Even after including the air separation penalty, the electrical efficiency is higher than in previous studies.

Acute Air Pollution Exposure and the Risk of Violent Behavior in the United States

BACKGROUND

Violence is a leading cause of death and an important public health threat, particularly among adolescents and young adults. However, the environmental causes of violent behavior are not well understood. Emerging evidence suggests exposure to air pollution may be associated with aggressive or impulsive reactions in people.

METHODS

We applied a two-stage hierarchical time-series model to estimate change in risk of violent and nonviolent criminal behavior associated with short-term air pollution in U.S. counties (2000-2013). We used daily monitoring data for ozone and fine particulate matter (PM2.5) from the Environmental Protection Agency and daily crime counts from the Federal Bureau of Investigation. We evaluated the exposure-response relation and assessed differences in risk by community characteristics of poverty, urbanicity, race, and age.

RESULTS

Our analysis spans 301 counties in 34 states, representing 86.1 million people and 721,674 days. Each 10 µg/m change in daily PM2.5 was associated with a 1.17% (95% confidence interval [CI] = 0.90, 1.43) and a 10 ppb change in ozone with a 0.59% (95% CI = 0.41, 0.78) relative risk increase (RRI) for violent crime. However, we observed no risk increase for nonviolent property crime due to PM2.5 (RRI: 0.11%; 95% CI = -0.09, 0.31) or ozone (RRI: -0.05%; 95% CI = -0.22, 0.12). Our results were robust across all community types, except rural regions. Exposure-response curves indicated increased violent crime risk at concentrations below regulatory standards.

CONCLUSIONS

Our results suggest that short-term changes in ambient air pollution may be associated with a greater risk of violent behavior, regardless of community type.

Seasonal variation in health impacts associated with visibility in Beijing, China

Visibility has been continuously and stably observed for more than half a century, while particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5) was not introduced to the national monitoring system in China until 2013. It is a scientific issue as to whether visibility can be used as an alternative to assess the health risks of air pollution in periods and areas without pollutant monitoring data. A generalized additive model (GAM) was adopted to estimate the impacts of seasonal changes in visibility on mortality in Beijing, China. Moreover, we estimated the contributions of particulate matter in the health effects of visibility by adjusting for dry extinction coefficient (β_dryext) and PM_2.5 in the model, respectively. We found that the acute health impacts of visibility varied by season, with the highest risks in winter. For respiratory mortality, the effect estimates per 1 km decrease in visibility were 0.40% (95% CI: 0.17-0.62%) in spring, 0.10% (95% CI: -0.14-0.34%) in summer, 0.27% (95% CI: 0.09-0.45%) in autumn, and 0.62% (95% CI: 0.38-0.85%) in winter. For cardiovascular mortality, the effect estimates per 1 km decrease in visibility were 0.20% (95% CI: 0.08-0.31%) in spring, 0.16% (95% CI: 0.04-0.27%) in summer, 0.25% (95% CI: 0.13-0.37%) in autumn, and 0.24% (95% CI: 0.13-0.35%) in winter. The seasonal pattern of health impacts related to visibility reflected the seasonal variations in the characteristics of air pollution emission sources and meteorological conditions that are unfavorable for pollutant dispersion. Particulate matter, particularly PM_2.5, made significant contributions to the health impacts of visibility. The results indicated that controlling pollutant emissions in winter would be of significant importance to improve air quality and mitigate the health hazard of air pollution in Beijing. Our study also provides further evidence on the feasibility of using visibility to assess the health impacts of particulate matter pollution.

The Impact of Chronic Ambient Exposure to PM2.5 and Ozone on Asthma Prevalence and COPD Mortality Rates in the Southeastern United States

Respiratory diseases affect millions of people across the United States annually. Two of the most common respiratory diseases are chronic obstructive pulmonary disease (COPD) and asthma. Mortality rates due to COPD have increased by an estimated 30% between 1980 and 2014, with significant variances among geographic regions. Both acute and chronic ambient exposures to fine particulate matter (PM_2.5) and ozone have been associated with exacerbations of respiratory diseases in numerous studies, and exposure to air pollutants are considered as the largest health risk factor globally. This study adds to the current literature by reporting the results of a time series analysis of the impact of PM_2.5 and ozone on prevalence rates of asthma and mortality rates for COPD at regional and county levels across the southeastern United States for the years 2005-2014. While general reductions in levels of PM_2.5 and ozone were demonstrated across all years, a distributed lag model showed continued strong associations between PM_2.5 and prevalence of asthma and mortality due to COPD, even at relatively small increases in ambient exposure (<1 μg/m³) across the southeastern United States. The results of the study support the need for additional research that considers factors such as patient demographics, medical histories, and health disparities in combination with ambient exposures to known pollutants.

Race or racial segregation? Modification of the PM2.5 and cardiovascular mortality association

BACKGROUND

Many studies have identified an inequitable distribution of exposure to PM2.5 (particulate matter less than 2.5 microns) by race. We investigated the association of PM2.5 and cardiovascular mortality considering both the decedents' race and neighborhood racial composition as potential modifiers.

METHODS

We obtained geocoded cardiovascular mortality records of all black and white decedents from urban block-groups in Massachusetts between 2001 and 2011 (n = 130,863). We examined the association between PM2.5 and cardiovascular mortality, and assessed effect modification by three types of racial modifiers: decedents' race, census block-group percent black and white, and two novel measures of racial segregation. The Racial Residential Segregation (RRS) quantifies the concentration of non-Hispanic blacks and whites in each block-group. The Index of Racial Dissimilarity measures dissimilarity in non-Hispanic black and white racial distribution between the smaller census block-group and larger tract.

RESULTS

We found a 2.35%(95%CI: 0.92%;3.79%) increase in mortality for each 10μg/m3 increase in two-day average exposure to PM2.5. The effect was modified by the block-group racial composition, with higher risks in block-groups with the highest percentage of black residents (interaction p-value = 0.04), and in block-groups with the lowest RRS (i.e. higher black to white resident ratio, interaction p-value = 0.072). Racial dissimilarity did not modify the associations.

CONCLUSION

Current levels of PM2.5 are associated with increased cardiovascular deaths in Massachusetts, with different risks between areas with different racial composition and segregation. This suggests that pollution reductions in neighborhoods with the highest percentage of non-Hispanic blacks would be most beneficial in reducing cardiovascular mortality and disparities.

Association between ambient air pollution and out-of-hospital cardiac arrest: are there potentially susceptible groups?

This study aimed to examine the association between air pollution and out-of-hospital cardiac arrest (OHCA), and the effects of underlying diseases. Between January 2015 and December 2016, data on particulate matter (PM)_2.5 and other air pollutants in Kaohsiung City were collected, and an emergency medical service database was used for information on patients who experienced OHCA. Overall, 3566 patients were analyzed and subgroup analyses by sex, age, and preexisting morbidities were performed. Interquartile increments in PM_2.5, PM₁₀, and O₃ levels on lag 1 and NO₂ level on lag 3 were associated with increments of 10.8%, 11.3%, 6.2%, and 1.7% in OHCA incidence, respectively. Subgroup analyses showed that patients with diabetes (1.363; interaction p = 0.009), heart disease (1.612; interaction p = 0.001), and advanced age (≥70 years, 1.297; interaction p = 0.003) were more susceptible to NO₂ on lag 3. Moreover, patients were more susceptible to O₃ during the cold season (1.194; interaction p = 0.001). We found that PM_2.5, PM₁₀, NO₂, and O₃ may play an important role in OHCA events, and the effects vary by underlying condition, age and season.

Improved risk communications with a Bayesian multipollutant Air Quality Health Index

Establishing an optimal indicator to communicate health risks of multiple air pollutants to public is much important. The Air Quality Health Index (AQHI) has been developed in many countries as a communication tool of multiple air pollutants related health risks. However, the current AQHI is based on the sum of the excess health risks which are typically derived from the single-pollutant statistical models. Such a strategy may overestimate the joint effect of multiple pollutants. We proposed an improved strategy to construct the AQHI based on a Bayesian multipollutant weighted model. Using this strategy, two improved indices - Bayesian multipollutant AQHI (BMP-AQHI) and Bayesian multipollutant AQHI with seasonal specificity (SBMP-AQHI) were calculated to present the multiple pollutants related health risks to the cardiovascular system based on data collected in Chengdu, China during 2013 to 2018. The two improved indices were compared to current Air Quality Index (AQI) and AQHI to evaluate the effectiveness of the improved indices in characterizing multipollutant health risks. The AQI risk classification suggested much smaller health risks than AQHIs. Among three AQHI types, the BMP-AQHI and SBMP-AQHI suggested slightly lower health risks to the cardiovascular system than the current AQHI. In the evaluation analysis, the SBMP-AQHI had the strongest association with the mortality of cardiovascular disease (CVD) (2.66%; 95%CI, 1.57%, 3.76%). In the subgroup analysis, an interquartile increase (IQR) of the SBMP-AQHI was associated with 3.21% (95%CI, 2.06%, 4.38%), 1.34% (95%CI, -0.13%, 2.82%), and 4.20% (95%CI, 2.59%, 5.84%) increases for CVD mortality in the elderly, male, and female subgroups, respectively. The study shows that the improved AQHIs can communicate the health information of multiple air pollutants more efficiently. The study also indicates the necessity to consider seasonal specificity in the construction of the AQHI.

Effect modification of the short-term effects of air pollution on morbidity by season: A systematic review and meta-analysis

Studies of the health effects of air pollution have traditionally controlled for ambient temperature as a confounder, and vice versa. However, season might be an important factor contributing to adverse health effects of air pollution. Given the current inconsistencies in results of previous studies on the effect modification of air pollution on morbidity by season, a systematic review and meta-analysis was conducted to synthesize the current evidence on effects of season on air pollution and morbidity. The electronic databases including PubMed, Web of Science, Embase, CNKI, and Wanfang were used to identify papers published up to the 30st of November in 2019. We identified 4284 articles, after screening, eighty papers met the inclusion criteria. Significant effect modification of CO, O₃, SO₂ and NO₂ on morbidity by season was observed, with corresponding ratio of relative risk of 1.0009 (95% CI: 1.0001-1.0018), 1.0080 (95% CI: 1.0021-1.0138), 0.9828 (95% CI: 0.9697-0.9962) and 0.9896 (95% CI: 0.9824-0.9968), respectively. Season significantly modified the effect of CO on pneumonia, the effect of SO₂ on cardiovascular disease, the effect of PM₁₀ on stroke, and the effect of O₃ on stroke, asthma and pneumonia. The effect modifications of air pollution by season were similar among males and females, while the effect estimates seem to be higher among children under 18 years old and the elderly aged 75 or over. Further research is needed to better understand the mechanisms underlying the seasonal variance of the effect of air pollutants on morbidity.

Age- and season-specific effects of ambient particles (PM1, PM2.5, and PM10) on daily emergency department visits among two Chinese metropolitan populations

BACKGROUND

Ambient PM_2.5 has been identified as the top leading cause of risk-attributable deaths worldwide, particularly in China. Evidence suggested that PM₁ contributed the most majority of PM_2.5 concentrations in Chinese cities. However, epidemiologic knowledge to date is of wide lack regarding PM₁-associated health effects.

METHODS

We collected daily records of all-cause emergency department visits (EDVs) and ground measurements of ambient air pollutants and meteorological factors in Guangzhou and Shenzhen, China, 2015-2016. Case-crossover design and conditional logistic regression models were used to comparatively assess the short-term effects of ambient PM₁, PM_2.5, and PM₁₀ on EDVs. Stratified analyses by gender, age and season were performed to identify vulnerable groups and periods.

RESULTS

PM₁, PM_2.5 and PM₁₀ were all significantly associated with increased EDVs in both cities. Population risks for EDVs increased by 2.2% [95% confidence interval, 1.8 to 2.6] in Guangzhou and 1.7% [1.0 to 2.4] in Shenzhen, for a 10 μg/m³ rise in PM₁ at lag 0-1 days and lag 0-4 days, respectively. Relatively lower risks were found to be associated with PM_2.5 and PM₁₀. PM-EDVs associations exhibited no gender differences, but varied across age groups. Compared with adults and the elderly, children under 14 years-of-age suffered higher PM-induced risks. Results from both cities suggested greatly significant effect modification by season, with consistently stronger PM-EDVs associations during cold months.

CONCLUSIONS

Our study added comparative evidence for increased EDVs risks associated with short-term exposures to ambient PM₁, PM_2.5 and PM₁₀. Besides, PM-associated effects were significantly stronger among children and during cold months.

Fine particulate air pollution and adult hospital admissions in 200 Chinese cities: a time-series analysis

BACKGROUND

The association between short-term exposure to ambient fine particulate matter (PM2.5) and morbidity risk in developing countries is not fully understood. We conducted a nationwide time-series study to estimate the short-term effect of PM2.5 on hospital admissions in Chinese adults.

METHODS

Daily counts of hospital admissions for 2014-16 were obtained from the National Urban Employee Basic Medical Insurance database. We identified more than 58 million hospitalizations from 0.28 billion insured persons in 200 Chinese cities for subjects aged 18 years or older. Generalized additive models with quasi-Poisson regression were applied to examine city-specific associations of PM2.5 concentrations with hospital admissions. National-average estimates of the association were obtained from a random-effects meta-analysis. We also investigated potential effect modifiers, such as age, sex, temperature and relative humidity.

RESULTS

An increase of 10 μg/m3 in same-day PM2.5 concentrations was positively associated with a 0.19% (95% confidence interval: 0.07-0.30) increase in the daily number of hospital admissions at the national level. PM2.5 exposure remained positively associated with hospital admissions on days when the daily concentrations met the current Chinese Ambient Air Quality Standards (75 μg/m3). Estimates of admission varied across cities and increased in cities with lower PM2.5 concentrations (p = 0.044) or higher temperatures (p = 0.002) and relative humidity (p = 0.003). The elderly were more sensitive to PM2.5 exposure (p < 0.001).

CONCLUSIONS

Short-term exposure to PM2.5 was positively associated with adult hospital admissions in China, even at levels below current Chinese Ambient Air Quality Standards.

Air Quality Index and air quality awareness among adults in the United States

BACKGROUND

Information about local air quality is reported across the United States using air quality alerts such as the Environmental Protection Agency's Air Quality Index. However, the role of such alerts in raising awareness of air quality is unknown. We conducted this study to evaluate associations between days with Air Quality Index ≥101, corresponding to a categorization of air quality as unhealthy for sensitive groups, unhealthy, very unhealthy, or hazardous, and air quality awareness among adults in the United States.

METHODS

Data from 12,396 respondents to the 2016-2018 ConsumerStyles surveys were linked by geographic location and survey year to daily Air Quality Index data. We evaluated associations between the number of days in the past year with Air Quality Index ≥101 and responses to survey questions about awareness of air quality alerts, perception of air quality, and changes in behavior to reduce air pollution exposure using logistic regression.

RESULTS

Awareness of air quality alerts (prevalence ratio [PR] = 1.23; 95% confidence interval [CI] = 1.15, 1.31), thinking/being informed air quality was bad (PR = 2.02; 95% CI = 1.81, 2.24), and changing behavior (PR = 2.27; 95% CI = 1.94, 2.67) were higher among respondents living in counties with ≥15 days with Air Quality Index ≥101 than those in counties with zero days in the past year with Air Quality Index ≥101. Each aspect of air quality awareness was higher among adults with than without asthma, but no differences were observed by heart disease status. Across quintiles of the number of days with Air Quality Index ≥101, air quality awareness increased among those with and without selected respiratory and cardiovascular diseases.

CONCLUSIONS

Among U.S. adults, air quality awareness increases with increasing days with alerts of unhealthy air. These findings improve our understanding of the extent to which air quality alerts prompt people to take actions to protect their health amidst poor air quality.

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

The fine particulate matter baseline (PMB), which includes PM_2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM_2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM_2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km² CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM_2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM_2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.

Association of short-term exposure to air pollution with myocardial infarction with and without obstructive coronary artery disease

Background

Air pollution including particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) increases the risk of acute myocardial infarction. However, whether short-term exposure to PM2.5 triggers the onset of myocardial infarction with nonobstructive coronary arteries, compared with myocardial infarction with coronary artery disease, has not been elucidated. This study aimed to estimate the association between short-term exposure to PM2.5 and admission for acute myocardial infarction, myocardial infarction with coronary artery disease, and myocardial infarction with nonobstructive coronary arteries.

Design

This was a time-stratified case-crossover study and multicenter validation study.

Methods

This study used a nationwide administrative database in Japan between April 2012–March 2016. Of 137,678 acute myocardial infarction cases, 123,633 myocardial infarction with coronary artery disease and 14,045 myocardial infarction with nonobstructive coronary arteries were identified by a validated algorithm combined with International Classification of Disease (10th revision), diagnostic, and procedure codes. Air pollutants and meteorological data were obtained from the monitoring station nearest to the admitting hospital.

Results

In spring (March–May), the short-term increase of 10 µg/m3 in PM2.5 2 days before admission was significantly associated with admission for acute myocardial infarction, myocardial infarction with nonobstructive coronary arteries, and myocardial infarction with coronary artery disease after adjustment for meteorological variables (odds ratio 1.060, 95% confidence interval 1.038–1.082; odds ratio 1.151, 1.079–1.227; odds ratio 1.049, 1.026–1.073, respectively), while the association was not significant in other variables. These associations were also observed after adjustment for other co-pollutants. The risk for myocardial infarction with nonobstructive coronary arteries (vs myocardial infarction with coronary artery disease) was associated with an even lower concentration of PM2.5 under the current environmental standards.

Conclusions

This study showed the seasonal difference of acute myocardial infarction risk attributable to PM2.5 and the difference in the threshold of triggering the onset of acute myocardial infarction subtype.