Increase In PM2 Research Articles

A Review on the Impact of Outdoor Environment on Indoor Thermal Environment

Outdoor environment exchanges heat with indoor environment, enabling pollutants to infiltrate indoors, affecting buildings’ energy efficiency, comfort, and indoor air quality. Investigating the impact of the outdoor environment on the indoor thermal environment is crucial. Firstly, this paper reviews the coupling method to link the outdoor environment with the indoor environment. Secondly, it examines the impact of the outdoor physical environment, including neighboring buildings, greening, road surface, water body, and sky, on the indoor thermal environment. During the hottest summer, an increase of 17% in trees can reduce indoor temperature by 1.1 °C. Thirdly, the impact of weather conditions, including outdoor temperature, outdoor humidity, external wind, global warming, extreme weather conditions, and solar radiation, on the indoor thermal environment is studied. Due to global warming, cooling energy consumption and heating energy consumption in 2050 could increase by 223% to 1050%, and heating demand could decrease by 36% to 58%. Finally, the impact of outdoor air pollution on indoor environment and energy consumption is analyzed. For every 75 μg/m3 increase in PM2.5 concentration, average power consumption could increase by 11.2%. Recommendations for future research are provided. This study contributes to the understanding of the outdoor–indoor thermal relationship and offers insights into enhancing indoor thermal comfort and reducing building energy consumption.

Long-term association of air pollution and incidence of lung cancer among older Americans: A national study in the Medicare cohort

BackgroundDespite strong evidence of the association of fine particulate matter (PM2.5) exposure with an increased risk of lung cancer mortality, few studies had investigated associations of multiple pollutants simultaneously, or with incidence, or using causal methods. Disparities were also understudied. ObjectivesWe investigated long-term effects of PM2.5, nitrogen dioxide (NO2), warm-season ozone, and particle radioactivity (PR) exposures on lung cancer incidence in a nationwide cohort. MethodsWe conducted a cohort study with Medicare beneficiaries (aged ≥ 65 years) continuously enrolled in the fee-for-service program in the contiguous US from 2001 to 2016. Air pollution exposure was averaged across three years and assigned based on ZIP code of residence. We fitted Cox proportional hazards models to estimate the hazard ratio (HR) for lung cancer incidence, adjusted for individual- and neighborhood-level confounders. As a sensitivity analysis, we evaluated the causal relationships using inverse probability weights. We further assessed effect modifications by individual- and neighborhood-level covariates. ResultsWe identified 166,860 lung cancer cases of 12,429,951 studied beneficiaries. In the multi-pollutant model, PM2.5 and NO2 exposures were statistically significantly associated with increased lung cancer incidence, while PR was marginally significantly associated. Specifically, the HR was 1.008 (95% confidence interval [CI]: 1.005, 1.011) per 1-μg/m3 increase in PM2.5, 1.013 (95% CI: 1.012, 1.013) per 1-ppb increase in NO2, and 1.005 (0.999, 1.012) per 1-mBq/m3 increase in PR. At low exposure levels, all pollutants were associated with increased lung cancer incidence. Men, older individuals, Blacks, and residents of low-income neighborhoods experienced larger effects of PM2.5 and PR. DiscussionLong-term PM2.5, NO2, and PR exposures were independently associated with increased lung cancer incidence among the national elderly population. Low-exposure analysis indicated that current national standards for PM2.5 and NO2 were not restrictive enough to protect public health, underscoring the need for more stringent air quality regulations.

Association of PM2.5 mass and its components with ovarian reserve in a northern peninsular province, China: The critical exposure period and components

BackgroundA possible role of PM2.5 components on ovarian reserve has not been adequately unexplored. ObjectiveTo evaluate the association between PM2.5 components and women’ ovarian reserve over critical exposure periods in northern China, where the level of air pollution is among the nation’s highest. MethodsWe included 15,102 women with serum anti-Müllerian hormone (AMH) measurements from the Center for Reproductive Medicine of Shandong University during 2015–2019. Concentrations of PM2.5 and its five major components (0.1° × 0.1°), including sulfate, nitrate, ammonium, organic matter, and black carbon, were assigned to each residential address. Multivariable linear mixed effect models combined with constituent-residual models were performed to estimate the effect sizes of essential components over six short- to long-term exposure periods. ResultsThe strength of association was stronger during the process from primary to small antral follicle compared with other longer windows. For every interquartile range increase in PM2.5 mass was associated with − 8.7% (95%CI: −12.3%, −4.9%) change in AMH and the effect size was greatest for sulfate. Women with the lower level of attained education and those living inland were more susceptible compared with other population subgroups. ConclusionExposure to specific components of air pollution during critical exposure windows is associated with a decline in ovarian reserve. These data add to the growing body of evidence that environmental factors have adverse effects on reproductive health, particularly for vulnerable population subgroups.

Short-term effects of air pollution on hospitalization of children with acute upper respiratory infections: A time series analysis in Lanzhou, China.

Short-term air pollution exposure is correlated with childhood acute upper respiratory infections (AURI) hospitalizations. We surveyed the relationship between AURI hospitalizations and air pollutant concentrations in children aged 0-14 years from 1 January 2014 to 31 December 2019 in Lanzhou City. We collected both data on air pollutant concentrations and children's AURI hospitalizations during the study period. Distributional lagged nonlinear models were adopted to assess the short-term effects of air pollutants on children's AURI hospitalizations. We also performed subgroup analysis and sensitivity analysis. A total of 15,881 children were hospitalized for AURI during the study period. The results showed that for each 10 µg/m3 increase in PM2.5 , SO2 , and NO2 concentrations at lag0-6, the relative risk (RR) values for children hospitalized for AURI were RR = 1.0247 (95% CI: 1.0092,1.0405), RR = 1.0928 (95% CI: 1.0562, 1.1308), and RR = 1.0715 (95% CI: 1.0495, 1.0940), respectively. PM10 was significantly associated with AURI hospitalization in children only at lag0, RR = 1.0028 (95% CI: 1.0000, 1.0056). Short-term exposures to PM2.5 , PM10 , SO2 , and NO2 all increase the risk of AURI hospitalization in children variously.

Long-term exposure to air pollution and mortality in Scotland: A register-based individual-level longitudinal study

BackgroundAir pollution is associated with several adverse health outcomes. However, heterogeneity in the size of effect estimates between cohort studies for long-term exposures exist and pollutants like SO2 and mental/behavioural health outcomes are little studied. This study examines the association between long-term exposure to multiple ambient air pollutants and all-cause and cause-specific mortality from both physical and mental illnesses. MethodsWe used individual-level administrative data from the Scottish-Longitudinal-Study (SLS) on 202,237 individuals aged 17 and older, followed between 2002 and 2017. The SLS dataset was linked to annual concentrations of NO2, SO2, and particulate-matter (PM10, PM2.5) pollution at 1 km2 spatial resolution using the individuals’ residential postcode. We applied survival analysis to assess the association between air pollution and all-cause, cardiovascular, respiratory, cancer, mental/behavioural disorders/suicides, and other-causes mortality. ResultsHigher all-cause mortality was associated with increasing concentrations of PM2.5, PM10, NO2, and SO2 pollutants. NO2, PM10, and PM2.5 were also associated with cardiovascular, respiratory, cancer and other-causes mortality. For example, the mortality hazard from respiratory diseases was 1.062 (95%CI = 1.028–1.096), 1.025 (95%CI = 1.005–1.045), and 1.013 (95%CI = 1.007–1.020) per 1 μg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. In contrast, mortality from mental and behavioural disorders was associated with 1 μg/m3 higher exposure to SO2 pollutant (HR = 1.042; 95%CI = 1.015–1.069). ConclusionThis study revealed an association between long-term (16-years) exposure to ambient air pollution and all-cause and cause-specific mortality. The results suggest that policies and interventions to enhance air quality would reduce the mortality hazard from cardio-respiratory, cancer, and mental/behavioural disorders in the long-term.

Acute Health Effects of Wildfire Smoke Exposure During a Compound Event: A Case-Crossover Study of the 2016 Great Smoky Mountain Wildfires.

In 2016, unprecedented intense wildfires burned over 150,000 acres in the southern Appalachian Mountains in the United States. Smoke from these fires greatly impacted the region and exposure to this smoke was significant. A bidirectional case-crossover design was applied to assess the relationship between PM2.5 (a surrogate for wildfire smoke) exposure and respiratory- and cardiovascular-related emergency department (ED) visits in Western North Carolina during these events. For 0-, 3-, and 7-day lags, findings indicated a significant increase in the odds of being admitted to the ED for a respiratory (ORs: 1.055, 95% CI: 1.048-1.063; 1.083, 1.074-1.092; 1.066, 1.058-1.074; respectively) or cardiovascular event (ORs: 1.052, 95% CI: 1.045-1.060; 1.074, 1.066-1.081; 1.067, 1.060-1.075; respectively) for every 5μg/m3 increase in PM2.5 over a chosen cutpoint of 20.4μg/m3. For all endpoints assessed except for emphysema, there were statistically significant increases in odds from 5.1% to 8.3%. In general, this increase was most pronounced 3days after exposure. Additionally, individuals aged 55+ generally experience higher odds of heart disease at the 3- and 7-day lag points, and Black/African Americans generally experience higher odds of asthma at the 3-day lag point. In general, larger fires and increased numbers of fires within counties resulted in higher health burden at same day exposure. In a secondary analysis, the odds of an ED visit increased by over 40% in several cases among people exposed to days above the Environmental Protection Agency 24-hr PM2.5 standard of 35μg/m3. Our findings provide new understanding on the health impacts of wildfires on rural populations in the southeastern US.

Association of Fine Particulate Matter Constituents with the Predicted 10-Year Atherosclerotic Cardiovascular Disease Risk: Evidence from a Large-Scale Cross-Sectional Study.

Little is known concerning the associations of fine particulate matter (PM2.5) and its constituents with atherosclerotic cardiovascular disease (ASCVD). A total of 31,162 participants enrolled from the Henan Rural Cohort were used to specify associations of PM2.5 and its constituents with ASCVD. Hybrid machine learning was utilized to estimate the 3-year average concentration of PM2.5 and its constituents (black carbon [BC], nitrate [NO3-], ammonium [NH4+], inorganic sulfate [SO42-], organic matter [OM], and soil particles [SOIL]). Constituent concentration, proportion, and residual models were utilized to examine the associations of PM2.5 constituents with 10-year ASCVD risk and to identify the most hazardous constituent. The isochronous substitution model (ISM) was employed to analyze the substitution effect between PM2.5 constituents. We found that each 1 μg/m3 increase in PM2.5, BC, NH4+, NO3-, OM, SO42-, and SOIL was associated with a 3.5%, 49.3%, 19.4%, 10.5%, 21.4%, 14%, and 28.5% higher 10-year ASCVD risk, respectively (all p < 0.05). Comparable results were observed in proportion and residual models. The ISM found that replacing BC with other constituents will generate the greatest health benefits. The results indicated that long-term exposure to PM2.5 and its constituents were associated with increased risks of ASCVD, with BC being the most attributable constituent.

Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China

Abstract. Atmospheric age reflects how long particles have been suspended in the atmosphere, which is closely associated with the evolution of air pollutants. Severe regional haze events occur frequently in China, influencing air quality, human health, and regional climate. Previous studies have explored the characteristics of mass concentrations and compositions of fine particulate matter (PM2.5) during haze events, but the evolution of atmospheric age remains unclear. In this study, the age-resolved University of California, Davis/California Institute of Technology (UCD/CIT) model was developed and applied to simulate the concentration and age distribution of PM2.5 during a severe regional haze episode in eastern China. The results indicated that PM2.5 concentrations in the North China Plain (NCP) gradually accumulated due to stagnant weather conditions during the beginning stage of the haze event. Accordingly, the atmospheric age of elemental carbon (EC), primary organic aerosol (POA), sulfate (SO42-), and secondary organic aerosol (SOA) gradually increased. The subsequent PM2.5 concentration growth was driven by the local chemical formation of nitrate (NO3-) under high relative humidity. The newly formed NO3- particles led to a decrease in the mean atmospheric age of NO3- particles. During the regional transport stage, aged particles from the NCP moved to the downwind Yangtze River Delta (YRD) region, leading to a sharp increase in PM2.5 concentrations and the average age of EC, POA, SO42-, and SOA in YRD. In contrast, the average age of NO3- and ammonium remained unchanged or even slightly decreased due to continuous local formation in the YRD region. Different evolution of the atmospheric age among these components provides a unique perspective on the formation of PM2.5 components during the regional haze event. The information can also be used for designing effective control strategies for different components of PM2.5.

Urban-rural differences in the association between long-term exposure to ambient particulate matter (PM) and malnutrition status among children under five years old: A cross-sectional study in China.

The evidence regarding the relationship between postnatal exposure of air pollution and child malnutrition indicators, as well as the corresponding urban-rural disparities, is limited, especially in low-pollution area of low- and middle-income countries (LMICs). Therefore, our aim was to contrast the effect estimates of varying ambient particulate matter (PM) on malnutrition indicators between urban and rural areas in Tibet, China. Six malnutrition indicators were evaluated in this study, namely, Z-scores of height for age (HFA), Z-scores of weight for age (WFA), Z-scores of weight for height (WFH), stunting, underweight, and wasting. Exposure to particles with an aerodynamic diameter ≤2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter ≤10 μm (PM10) and particles with an aerodynamic diameter between 2.5 and 10 μm (PMc) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between PM and the above malnutrition indicators. Furthermore, the effect estimates of different PM were contrasted between urban and rural areas. A total of 2511 children under five years old were included in this study. We found long-term exposure to PM2.5, PMc, and PM10 was associated with an increased risk of stunting and a decreased risk of underweight. Of these air pollutants, PMc had the strongest association for Z-scores of HFA and stunting, while PM2.5 had the strongest association for underweight. The results showed that the odds ratio (OR) for stunting were 1.36 (95% confidence interval (CI) = 1.06 to 1.75) per interquartile range (IQR) microgrammes per cubic metre (μg/m3) increase in PM2.5, 1.80 (95% CI = 1.30 to 2.50) per IQR μg/m3 increase in PMc and 1.55 (95% CI = 1.17 to 2.05) per IQR μg/m3 increase in PM10. The concentrations of PM were higher in urban areas, and the effects of PM on malnutrition indicators among urban children were higher than those of rural children. Our results suggested that PM exposure might be an important trigger of child malnutrition. Further prospective researches are needed to provide important scientific literature for understanding child malnutrition risk concerning postnatal exposure of air pollutants and formulating synthetically social and environmental policies for malnutrition prevention.

Partiküler Hava Kirliliğinin Bebek Ölümlerine Kısa Dönemdeki Etkisi: 2018-2020 Yılları Ankara İli Örneği

Background: Today, nine out of 10 people on a global scale live in an air pollution environment above the limit values determined. It is predicted that particulate air pollution is a risk factor for 5.3% of deaths under the age of one in Türkiye. In order to examine the causes of infant deaths and take necessary precautions, it is important to investigate air pollution and the possibilities of infant death due to. Aims: This study was carried out to examine the relationship between Particulate Matter (PM) 2.5 and (PM)10 levels observed in Ankara between the years 2018-2020 and infant deaths that occurred at that time. Methods: To examine the relationship poisson regression model, in which the terms formed by the flexible cubic spline function, were mainly used. The effect of each 10 μg/m3 increase in PM2.5 and PM10 on infant mortality, taking into account lags of up to seven days by adjusting for seasonal trends and air temperature effects, was determined by relative risk (RR) and 95% confidence intervals (CI) analyzed by calculation. Results: In the evaluated period, 1295 infant deaths occurred in 754 of 1096 days. The three-year average of the daily average PM2.5 and PM10 levels detected in Ankara is above the limit values. Conclusion: The effect of particulate air pollution on infant mortality in the first week was not detected, this relationship may become detectable when different variables such as possible effect modifiers are included in the models applied. The subject should also be examined under such different conditions.

Differential effects of size-specific particulate matter on lower respiratory infections in children: A time-series analysis in Lanzhou, China

This study aimed to assess the differential effects of size-specific PM (PM2.5, PM10–2.5, and PM10) on daily outpatients for Lower Respiratory Infection (LRI), Pneumonia, and Bronchitis among children in Lanzhou, China. A distributed lag nonlinear model (DLNM) was employed to evaluate the non-linear and delayed effects. The models were fitted with different lag structures, including single lag days from the current to the previous seven days (lag0 to lag7) and moving average concentrations over seven lag days (lag0–1 to lag0–7). We found that different PM fractions were significantly associated with hospital visits for LRI, pneumonia, and bronchitis, and cumulative effects increased with the increasing number of lag days investigated. Relative risk (RR) of LRI outpatient visits among children per 10 µg/m3 increase in PM2.5, PM10–2.5, and PM10 were 1.070 (95% CI: 1.059, 1.081), 1.010 (95% CI: 1.006, 1.015), and 1.013 (95% CI: 1.010, 1.016), respectively. For every 10 μg/m3 increase in PM2.5, PM10–2.5, and PM10, the RR values for pneumonia were 1.081, 1.013, and 1.019, and those for bronchitis were 1.069, 1.009, and 1.012, respectively. Boys and children aged 0–3 years were more sensitive to PM exposure. We also found significantly higher effects of PM in cold seasons than that in warm seasons. Our results suggested that short-term exposure to size-specific PM, PM2.5 in particular, might be an important trigger of outpatient visits for overall and cause-specific LRI.

Lagging effects and prediction of pollutants and their interaction modifiers on influenza in northeastern China

BackgroundPrevious studies have typically explored the daily lagged relations between influenza and meteorology, but few have explored seasonally the monthly lagged relationship, interaction and multiple prediction between influenza and pollution. Our specific objectives are to evaluate the lagged and interaction effects of pollution factors and construct models for estimating influenza incidence in a hierarchical manner.MethodsOur researchers collect influenza case data from 2005 to 2018 with meteorological and contaminative factors in Northeast China. We develop a generalized additive model with up to 6 months of maximum lag to analyze the impact of pollution factors on influenza cases and their interaction effects. We employ LASSO regression to identify the most significant environmental factors and conduct multiple complex regression analysis. In addition, quantile regression is taken to model the relation between influenza morbidity and specific percentiles (or quantiles) of meteorological factors.ResultsThe influenza epidemic in Northeast China has shown an upward trend year by year. The excessive incidence of influenza in Northeast China may be attributed to the suspected primary air pollutant, NO2, which has been observed to have overall low levels during January, March, and June. The Age 15–24 group shows an increase in the relative risk of influenza with an increase in PM2.5 concentration, with a lag of 0–6 months (ERR 1.08, 95% CI 0.10–2.07). In the quantitative analysis of the interaction model, PM10 at the level of 100–120 μg/m3, PM2.5 at the level of 60–80 μg/m3, and NO2 at the level of 60 μg/m3 or more have the greatest effect on the onset of influenza. The GPR model behaves better among prediction models.ConclusionsExposure to the air pollutant NO2 is associated with an increased risk of influenza with a cumulative lag effect. Prioritizing winter and spring pollution monitoring and influenza prediction modeling should be our focus.

Long-term exposure to ambient PM2.5 and its constituents is associated with MAFLD

Existing evidence suggests that long-term exposure to ambient fine particulate pollution (PM2.5) may increase metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, there is still limited evidence on the association of PM2.5 constituents with MAFLD. Therefore, this study explores the associations between the five main chemical constituents of PM2.5 and MAFLD to provide more explicit information on the liver exposome. A total of 76,727 participants derived from the China Multi-Ethnic Cohort, a large-scale epidemic survey in southwest China, were included in this study. Multiple linear regression models were used to estimate the pollutant-specific association with MAFLD. Weighted quantile sum regression was used to evaluate the joint effect of the pollutant-mixture on MAFLD and identify which constituents contribute most to it. Three-year exposure to PM2.5 constituents was associated with a higher MAFLD risk and more severe liver fibrosis. Odds ratios for MAFLD were 1.480, 1.426, 1.294, 1.561, 1.618, and 1.368 per standard deviation increase in PM2.5, black carbon, organic matter, ammonium, sulfate, and nitrate, respectively. Joint exposure to the five major chemical constituents was also positively associated with MAFLD (odds ratio 1.490, 95% CI 1.360-1.632). Nitrate contributed most to the joint effect of the pollutant-mixture. Further stratified analyses indicate that males, current smokers, and individuals with a high-fat diet might be more susceptible to ambient PM2.5 exposure than others. Long-term exposure to PM2.5 and its five major chemical constituents may increase the risk of MAFLD. Nitrate might contribute most to MAFLD, which may provide new clues for liver health. Males, current smokers, and participants with high-fat diets were more susceptible to these associations. This large-scale epidemiologic study explored the associations between constituents of fine particulate pollution (PM2.5) and metabolic dysfunction-associated fatty liver disease (MAFLD), and further revealed which constituents play a more important role in increasing the risk of MAFLD. In contrast to previous studies that examined the effects of PM2.5 as a whole substance, this study carefully explored the health effects of the individual constituents of PM2.5. These findings could (1) help researchers to identify the specific particles responsible for hepatotoxicity, and (2) indicate possible directions for policymakers to efficiently control ambient air pollution, such as targeting the sources of nitrate pollution.

Effects of PM2.5 emissions from household fuel combustion on biomarkers and pulmonary function in rural areas of Fenwei Plain, China

Rural household solid fuel combustion poses serious health risks in China. This study investigated the effects of PM2.5 and its organic carbon (OC) and elemental carbon (EC) emissions from various solid fuel combustion on biomarkers (i.e., interleukin-6 [IL-6], 8-hydrox-2′-deoxyguanosine [8-OHdG], and vascular endothelial growth factor [VEGF]) in human urine (u) and saliva (s) as well as on lung function. A total of 148 villagers burned various solid fuels (i.e., clean briquette coal, raw coal chunk, and biomass) in rural areas of Fenwei Plain in China were selected. The biomass group demonstrated the highest u-IL-6, s-IL-6, and s-8-OHdG levels, which were 1.2–3.1 times those of coal groups, whereas the clean briquette coal group exhibited the highest u-8-OHdG, and u-VEGF levels. In linear regression controlled for variables, a 1 g kg−1 increase in PM2.5 emission factor (EF) resulted in a decline in u-VEGF levels by 0.553 μg mol−1 UCr and increases in s-IL-6 and s-8-OHdG levels by 0.119 and 0.545 μg mol−1 UCr, respectively. A 1 g kg−1 increase in OC EF was associated with the upregulation of s-IL-6 and s-8-OHdG levels by 0.187 and 14.421 pg mL−1, respectively, a 1 g kg−1 increase in EC EF led to an increase in s-IL-6 by 0.354 pg mL−1. No significant differences in pulmonary function were observed among the three groups, nor did PM2.5 and its OC and EC significantly affect lung function. Through noninvasive tests, this study provided evidence on the effect of PM2.5 emitted from household fuel combustion emissions on human inflammation and oxidative stress responses.

Associations of long-term exposure to air pollution and green space with reproductive hormones among women undergoing assisted reproductive technology: A longitudinal study

Studies investigating the association between long-term exposure to air pollution (AP)/green space and female reproductive hormones are still limited. Furthermore, their interactive effects remain unclear. Our study sought to explore the separate and interactive impacts of AP/green space on reproductive hormones among women undergoing assisted reproductive technology. We measured estradiol (E2), progesterone (P), testosterone (T), and follicle-stimulating hormone (FSH) from the longitudinal assisted reproduction cohort in Anhui, China. The annual mean concentrations of air pollutants were calculated at the residential level. Normalized Difference Vegetation Index (NDVI) within 500-m represented green space exposure. To assess the effect of AP/green space on hormones, we employed multivariable linear mixed-effect models. Our results showed that each one-interquartile range (IQR) increment in particulate matter (PM2.5 and PM10) and sulfur dioxide (SO2) was associated with −0.03[−0.05, −0.01], −0.03[−0.05, −0.02], and −0.03[−0.05, −0.01] decrease in P. An IQR increase in PM2.5, PM10, SO2, and carbon monoxide (CO) was associated with a −0.16[−0.17, −0.15], −0.15[−0.16, −0.14], −0.15[−0.16, −0.14], and −0.12[−0.13, −0.11] decrease in T and a −0.31[−0.35, −0.27], −0.30[−0.34, −0.26], −0.26[−0.30, −0.22], and −0.21[−0.25, −0.17] decrease in FSH. Conversely, NDVI500-m was associated with higher levels of P, T, and FSH, with β of 0.05[0.02, 0.08], 0.06[0.04, 0.08], and 0.07[0.00, 0.14]. Moreover, we observed the “U” or “J” exposure-response curves between PM2.5, PM10, and SO2 concentrations and E2 and P levels, as well as “inverted-J” curves between NDVI500-m and T and FSH levels. Furthermore, we found statistically significant interactions of SO2 and NDVI500-m on E2 and P as well as CO and NDVI500-m on E2. These findings indicated that green space might mitigate the negative effects of SO2 on E2 and P, as well as the effect of CO on E2. Future research is needed to determine these findings and underlying mechanisms.

Air pollution and out-of-hospital cardiac arrest risk: a 7-year study from a highly polluted area.

Globally, nearly 20% of cardiovascular disease deaths were attributable to air pollution. Out-of-hospital cardiac arrest (OHCA) represents a major public health problem; therefore, the identification of novel OHCA triggers is of crucial relevance. The aim of the study was to evaluate the association between air pollution (short-, mid-, and long-term exposures) and OHCA risk, during a 7-year period in a highly polluted urban area in northern Italy, with a high density of automated external defibrillators (AEDs). Out-of-hospital cardiac arrests were prospectively collected from the 'Progetto Vita Database' between 1 January 2010 and 31 December 2017; day-by-day air pollution levels were extracted from the Environmental Protection Agency stations. Electrocardiograms of OHCA interventions were collected from the AED data cards. Day-by-day particulate matter (PM) 2.5 and 10, ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) levels were measured. A total of 880 OHCAs occurred in 748 days. A significant increase in OHCA risk with a progressive increase in PM2.5, PM10, CO, and NO2 levels was found. After adjustment for temperature and seasons, a 9% and 12% increase in OHCA risk for each 10 μg/m3 increase in PM10 (P < 0.0001) and PM2.5 (P < 0.0001) levels was found. Air pollutant levels were associated with both asystole and shockable rhythm risk, while no correlation was found with pulseless electrical activity. Short- and mid-term exposures to PM2.5 and PM10 are independently associated with the risk of OHCA due to asystole or shockable rhythm.

Air pollution, mortality, and hospital admissions in Scotland: A 16 years register-based study

BackgroundAir pollution is associated with poor health and higher mortality. However, studies that link high spatial resolution air pollution data for several pollutants to individual-level data over prolonged period (&gt;10 years) and assess multiple health outcomes are limited. In this study, we investigated the association between 16-years exposure to air pollution and all-cause and cause-specific (cardiovascular, respiratory, cancer, infectious, and mental/behavioural disorders) mortality and hospital admissions in Scotland.&#x0D; MethodsIndividual-level data from the “Scottish Longitudinal Study” for 202,237 individuals (2002-2017) were linked to yearly concentrations of NO2, SO2, PM10, and PM2.5 pollutants at 1-Km2 spatial resolution using the individual’s residential postcode. The association between air pollution and mortality and hospital admissions was examined using Cox Proportional-Hazards and multilevel mixed-effects negative binomial models, respectively.&#x0D; ResultsIncreasing concentrations of PM2.5, PM10, and NO2 pollutants were associated with higher rates of all-cause, cardiovascular, respiratory, cancer, and infectious mortality and hospital admissions. Mortality from respiratory diseases increased by 6.2% (95%CI=2.8%-9.6%), 2.5% (95%CI=0.5%-4.5%), and 1.2% (95%CI=0.5%-1.9%) per 1 µg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. Exposure to SO2 was mainly linked to mental/behavioural disorders mortality (HR=1.05; 95%CI=1.02-1.07) and respiratory hospital admissions (IRR=1.02; 95%CI=1.01-1.03).&#x0D; ConclusionsThis study revealed a positive association between air pollution and mortality and hospital admissions in Scotland. Interventions on air pollution through stricter environmental regulations could help ease the mortality and hospital admission burden, for both physical and mental illness.

Gestational age modifies the association between exposure to fine particles and fetal death: findings from a nationwide epidemiological study in the contiguous United States

BackgroundsThe vulnerability of fetuses differs at different developmental stages, in response to environmental stressors such as fine particulate matter (PM2.5), a ubiquitous air pollutant. Whether gestational age (GA) modifies the association between prenatal fine particulate matter (PM2.5) exposure and fetal death remains unclear.MethodsWe selected approximately 47.8 million eligible United States (US) livebirth and fetal death (defined as a termination at a GA of 20–43 weeks) records from 1989 to 2004. For each record, we took the level of prenatal exposure to PM2.5 as the average concentration in the mother’s residential county during the entire gestational period, or a specific trimester (i.e., GA-specific exposure), according to well-established estimates of monthly levels across the contiguous US. First, we evaluated the associations between PM2.5 exposure and fetal death at a specific GA (i.e., GA-specific outcome) using five different logit models (unadjusted, covariate-adjusted, propensity-score, double robust, and diagnostic-score models). Double robust model was selected as the main model due to its advantages in causal inference. Then, we conducted meta-analyses to pool the estimated GA-specific associations, and explored how the pooled estimates varied with GA.ResultsAccording to the meta-analysis, all models suggested gestational PM2.5 exposure was associated with fetal death. However, there was slight heterogeneity in the estimated effects, as different models revealed a range of 3.6–10.7% increase in the odds of fetal death per 5-µg/m3 increment of PM2.5. Each 5-µg/m3 increase in PM2.5 exposure during the entire gestation period significantly increased the odds of fetal death, by 8.1% (95% confidence interval [CI]: 5.1–11.2%). In terms of GA-specific outcomes, the odds of fetal death at a GA of 20–27, 28–36, or ≥ 37 weeks increased by 11.0% (5.9–16.4%), 5.2% (0.4–10.1%), and 8.3% (2.5–14.5%), respectively. In terms of GA-specific exposure, the odds of fetal death increased by 6.0% (3.9–8.2%), 4.1% (3.9–8.2%), and 4.3% (0.5–8.2%) with 5-µg/m3 increases in PM2.5 exposure during the first, second, and third trimester, respectively. The association had the largest effect size (odds ratio = 1.098, 95% CI: 1.061–1.137) between PM2.5 exposure during early gestation (i.e., first trimester) and early fetal death (i.e., 20–27 weeks).ConclusionsPrenatal exposure to PM2.5 was significantly associated with an increased risk of fetal death. The association was varied by gestational-age-specific exposures or outcomes, suggesting gestation age as a potential modifier on the effect of PM2.5. The fetus was most vulnerable during the early stage of development to death associated with PM2.5 exposure.

Long-Term Exposure to Ambient PM2.5 and Hospitalizations for Myocardial Infarction Among US Residents: A Difference-in-Differences Analysis.

Background Air pollution has been recognized as an untraditional risk factor for myocardial infarction (MI). However, the MI risk attributable to long-term exposure to fine particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5) is unclear, especially in younger populations, and few studies have represented the general population or had power to examine comorbidities. Methods and Results We applied the difference-in-differences approach to estimate the relationship between annual PM2.5 exposure and hospitalizations for MI among US residents and further identified potential susceptible subpopulations. All hospital admissions for MI in 10 US states over the period 2002 to 2016 were obtained from the Healthcare Cost and Utilization Project State Inpatient Database. In total, 1 914 684 MI hospital admissions from 8106 zip codes were included in this study. We observed a 1.35% (95% CI, 1.11-1.59) increase in MI hospitalization rate for 1-μg/m3 increase in annual PM2.5 exposure. The estimate was robust to adjustment for surface pressure, relative humidity, and copollutants. In the population exposed to ≤12 μg/m3, there was a larger increment of 2.17% (95% CI, 1.79-2.56) in hospitalization rate associated with 1-μg/m3 increase in PM2.5. Young people (0-34 years of age) and elderly people (≥75 years of age) were the 2 most susceptible age groups. Residents living in more densely populated or poorer areas and individuals with comorbidities were observed to be at a greater risk. Conclusions This study indicates long-term residential exposure to PM2.5 could increase risk of MI among the general US population, people with comorbidities, and poorer individuals. The association persists below current standards.

Impact of short-term exposure to ambient air pollution on osteoarthritis: a multi-city time-series analysis in Central-Eastern China.

Osteoarthritis (OA) is a threat to public health issue with high morbidity and disability worldwide. However, unequivocal evidence on the link between air pollution and OA remains little, especially in multi-study sites. This study aimed to explore the relationship between short-term exposure to main air pollutants and the risk of OA outpatient visits in multi-study sites. A multi-city time-series analysis was performed in Anhui Province, Central-Eastern China from January 1, 2015, to December 31, 2020. We used a two-stage analysis to assess the association between air pollution and daily OA outpatient visits. City-specific associations were estimated with a distributed lag nonlinear model and then pooled by random-effects or fixed-effects meta-analysis. Stratified analysis was conducted by gender, age, and season. Additionally, the disease burden of OA attributable to air pollutant exposure was calculated. A total of 35,700 OA outpatients were included during the study period. The pooled exposure-response curves showed that PM2.5 and PM10 concentrations below the reference values could increase the risk of OA outpatient visits. Concretely, per 10 ug/m3 increase in PM2.5 concentration was linked to an elevated risk of OA outpatient visits at lag 2 and lag 3days, where the effect reached its highest value on lag 2day (RR: 1.023, 95%CI: 1.005-1.041). We observed that a 10μg/m3 increase in PM10 was positively correlated with OA outpatient visits (lag2day, RR: 1.011, 95%CI: 1.001-1.025). Nevertheless, no statistical significance was discovered in gaseous pollutants (including SO2, O3, and CO). Additionally, a significant difference was found between cold and warm seasons, but not between different genders or age groups. This study reveals that particulate matter is an important factor for the onset of OA in Anhui Province, China. However, there is no evidence of a relationship of gaseous pollutants with OA in this area.