Increase In PM2 Research Articles

The Association of Air Pollution Exposure With Glucose and Lipid Levels: The Role of an Extreme Air Pollution Event Alongside 2 Decades of Moderate Exposure.

Extreme air pollution events and moderate exposure to fine particulate matter (PM2.5) are associated with increased cardiometabolic risk. The World Trade Center (WTC) Health Program general responder cohort includes responders to the WTC disaster. We investigated whether their exposure to this extreme air pollution event (2001) was associated with long-term metabolic outcomes, independently from the associations of intermediate-term PM2.5 exposure later in life (2004-2019). We included 22,447 cohort members with cholesterol (n= 96,155) and glucose (n= 81,599) laboratory results. Self-reported WTC exposure was derived from a questionnaire. PM2.5 exposure was derived from a satellite-based model. We observed an increase of 0.78 mg/dL (95% confidence interval (CI): 0.30, 1.26) in glucose and 0.67 mg/dL (95% CI: 1.00, 2.35) in cholesterol levels associated with an interquartile range increase in PM2.5 averaged 6 months before the study visit. Higher WTC-exposure categories were also associated with higher cholesterol (0.99 mg/dL, 95% CI: 0.30, 1.67, for intermediate exposure) and glucose (0.82 mg/dL, 95% CI: 0.22, 1.43, for high exposure) levels. Most associations were larger among people with diabetes. Extreme air pollution events and intermediate PM2.5 exposure have independent metabolic consequences. These exposures contributed to higher glucose and lipids levels among WTC responders, which may be translated into increased cardiovascular risk.

Leisure-time physical activity mitigated the cognitive effect of PM2.5 and PM2.5 components exposure: Evidence from a nationwide longitudinal study

BackgroundExposure to fine particulate matter (PM2.5) impairs cognition, while physical activity (PA) improves cognitive function. However, whether taking PA with PM2.5 exposure is still beneficial to cognition remains unknown. MethodsWe utilized national representative longitudinal data from the China Family Panel Study (CFPS), comprising a total sample of 108,099 from 2010 to 2018 in three waves. Cognitive performance and leisure-time PA were measured using the standard cognitive module and Godin-Shephard Leisure-Time Physical Activity Questionnaire. Gridded overall PM2.5 and major chemical components of PM2.5 were estimated using a two-stage machine learning model and matched to each participant based on their residential location. Mixed-effect models and difference-in-difference models were employed to investigate the individual and joint effects of total PM2.5, PM2.5 components, and leisure-time PA on cognition. ResultsEvery 1 μg/m3 increase in PM2.5 was associated with a −0.035 (95% confidence interval [CI] = −0.052, −0.018) point change in cognitive score. All PM2.5 components exhibited negative associations with cognitive change, with black carbon (BC) contributing the most significant cognitive decline (β = −1.025, 95% CI = −1.367, −0.683). Every one-time (or one-hour) increase in leisure-time PA frequency (or PA time) per week was associated with an increase in cognitive score by 0.576 (0.270) points (PA frequency: 95% CI = 0.544, 0.608, PA time: 95% CI = 0.248, 0.293). PA frequency (β = −0.005, 95% CI = −0.006, −0.003) and PA time (β = −0.002, 95% CI = −0.003, −0.001) exhibited interactive effects with PM2.5. Increased PA frequency and time were more beneficial to cognitive function in the low PM2.5 exposure group compared to those exposed to high PM2.5 levels. Moreover, relative to lower PM2.5 exposure, the cognitive benefits of physically active individuals with higher PM2.5 exposure were attenuated but still improved cognition when compared to those with no PA. ConclusionEngaging in leisure-time PA provides cognitive benefits even under PM2.5 exposure, although PM2.5 exposure attenuates these benefits. Among all PM2.5 components, BC demonstrated the most significant cognitive hazard and interaction with leisure-time PA. Promoting PA as a preventive measure may offer a cost-effective and convenient strategy to mitigate the negative impact of PM2.5 exposure on cognition. There is no excuse to avoid PA under PM2.5 exposure, as its cognitive benefits persist even in polluted environments.

The mediation role of blood lipids on the path from air pollution exposure to MAFLD: A longitudinal cohort study

Background & aimsRecent cross-sectional studies found that exposure to ambient air pollution (AP) was associated with an increased risk of metabolic dysfunction-associated fatty liver disease (MAFLD). The alternation of blood lipids may explain the association, but epidemiological evidence is lacking. We aimed to examine whether and to what extent the association between long-term exposure to AP and incident MAFLD is mediated by blood lipids and dyslipidemia in a prospective cohort. MethodsWe included 6350 participants from the China Multi-Ethnic Cohort (CMEC, baseline 2018–2019, follow-up 2020–2021). Three-year average (2016–2018) of AP (PM1, PM2.5, PM10, NO2), blood lipids (TC, LDL-C, HDL-C, TG with their combinations) and incident MAFLD for each individual were assessed chronologically. Linear and logistic regression was used to assess the associations among AP, blood lipids, and MAFLD, and the potential mediation effects of blood lipids were evaluated using causal mediation analysis. ResultsA total of 744 participants were newly diagnosed with MAFLD at follow-up. The odds ratios of MAFLD associated with a 10 μm increase in PM1, PM2.5, and NO2 were 1.35 (95 % CI: 1.14, 1.58), 1.34 (1.10, 1.65) and 1.28 (1.14, 1.44), respectively. Blood lipids are important mediators between AP and incident MAFLD. LDL-C (Proportion Mediated: 6.9 %), non-HDL (13.4 %), HDL-C (20.7 %), LDL/HDL (30.1 %), and dyslipidemia (6.5 %) significantly mediated the association between PM2.5 and MAFLD. For PM1, the indirect effects were similar to those for PM2.5, with a larger value for the direct effect, and the mediation proportion by blood lipids was less for NO2. ConclusionBlood lipids are important mediators between AP and MAFLD, and can explain 5 %–30 % of the association between AP and incident MAFLD, particularly cholesterol-related variables, indicating that AP could lead to MAFLD through the alternation of blood lipids. These findings provided mechanical evidence of AP leading to MAFLD in epidemiological studies.

Longitudinal associations of neighbourhood environmental exposures with mental health problems during adolescence: Findings from the TRAILS study

BackgroundCross-sectional studies have found associations between neighbourhood environments and adolescent mental health, but the few longitudinal studies mainly focused on single exposure-based analyses and rarely assessed the mental health associations with environmental changes. ObjectivesWe assessed longitudinal within- and between-person associations of multiple neighbourhood time-varying physical and social environmental exposures with externalising and internalising problems throughout adolescence. MethodsWe used four waves of TRAILS (Tracking Adolescents’ Individual Lives Survey) data on self-reported externalising and internalising problems at ages 11, 13, 16, and 19 among 2,135 adolescents in the Netherlands. We measured residence-based time-varying environmental exposures, including green space, air pollution (fine particulate matter (PM2.5)), noise, deprivation, and social fragmentation. We fitted random-effect within-between regression models to assess the environment-mental health associations. ResultsAt the within-person level, an interquartile range (IQR) increase in PM2.5 was associated with a 0.056 IQR (95% CI: 0.014, 0.099) increase in externalising problems, while an IQR social fragmentation increase was associated with a 0.010 IQR (95% CI: −0.020, −0.001) decrease in externalising problems. Stratification revealed that the association with PM2.5 was significant only for movers, whereas the association with social fragmentation remained only for non-movers. At the between-person level, an IQR higher noise was associated with a 0.100 IQR (95% CI: 0.031, 0.169) more externalising problems, while higher deprivation (β = 0.080; 95% CI: 0.022, 0.138) and lower fragmentation (β = -0.073; 95% CI: −0.128, −0.018) were associated with more internalising problems. We also observed positive between-person associations between PM2.5, noise, and internalising problems, but both associations were unstable due to the high PM2.5-noise correlation. Further, we observed a non-linear between-person PM2.5-externalising problems association turning positive when PM2.5 > 15 µg/m3. Null associations were found for green space. ConclusionOur findings suggested that air pollution, noise, and neighbourhood deprivation are risk factors for adolescent mental health. Not only exposure levels but also exposure changes matter for adolescent mental health.

Residential greenness alleviated the adverse associations of long-term exposure to ambient PM1 with cardiac conduction abnormalities in rural adults

Ambient air pollution was linked to elevated risks of adverse cardiovascular events, and alterations in electrophysiological properties of the heart might be potential pathways. However, there is still lacking research exploring the associations between PM1 exposure and cardiac conduction parameters. Additionally, the interactive effects of PM1 and residential greenness on cardiac conduction parameters in resource-limited areas remain unknown. A total of 27483 individuals were enrolled from Henan Rural Cohort study. Cardiac conduction parameters were tested by 12-lead electrocardiograms. Concentrations of PM1 were predicted by satellite-based spatiotemporal models. Levels of residential greenness were assessed using Enhanced Vegetation Index (EVI) and Normalized difference vegetation index (NDVI). Logistic regression models and restricted cubic splines were fitted to explore the associations of PM1 and residential greenness exposure with cardiac conduction abnormalities risk, interaction plot method was performed to visualize their interaction effects. The 3-year median concentration of PM1 was 56.47 (2.55) μg/m3, the adjusted odds rate (ORs) and 95% confidence intervals (CIs) for abnormal HR, PR, QRS, and QTc interval risk in response to 1 μg/m3 increase in PM1 were 1.064 (1.044, 1.085), 1.037 (1.002, 1.074), 1.061 (1.044, 1.077) and 1.046 (1.028, 1.065), respectively. Participants exposure to higher levels of PM1 had increased risks of abnormal HR (OR = 1.221, 95%CI: 1.144, 1.303), PR (OR = 1.061, 95%CI: 0.940, 1.196), QRS (OR = 1.225, 95%CI: 1.161, 1.294) and QTc interval (OR = 1.193, 95%CI: 1.121, 1.271) compared with lower levels of PM1. Negative interactive effects of exposure to PM1 and residential greenness on abnormal HR, QRS, and QTc intervals were observed (Pfor interaction < 0.05). Long-term PM1 exposure was associated with elevated cardiac conduction abnormalities risks, and this adverse association might be mitigated by residential greenness to some extent. These findings emphasize that controlling PM1 pollution and increasing greenness levels might be effective strategies to reduce cardiovascular disease burdens in resource-limited areas.

Association of fine particulate matter and its constituents with hypertension: the modifying effect of dietary patterns

BackgroundStudies have shown that nutritional supplements could reduce the adverse effects induced by air pollution. However, whether dietary patterns can modify the association of long-term exposure to fine particulate matter (PM2.5) and its constituents with hypertension defined by the 2017 ACC/AHA guideline has not been evaluated.MethodsWe included 47,501 Chinese adults from a nationwide cross-sectional study. PM2.5 and five constituents were estimated by satellite-based random forest models. Dietary approaches to stop hypertension (DASH) and alternative Mediterranean diet (AMED) scores were calculated for each participant. Interactions between dietary patterns and air pollution were examined by adding a multiplicative interaction term to logistic models.ResultsLong-term exposure to PM2.5 and its constituents was associated with an increased risk of hypertension and stage 1–2 hypertension. The DASH and AMED scores significantly modified these associations, as individuals with higher scores had a significantly lower risk of air pollution-related hypertension and stage 1–2 hypertension (P-interaction < 0.05), except for interaction between PM2.5, sulfate, nitrate, ammonium, and AMED score on stage 1 hypertension. For each IQR increase in PM2.5, participants with the lowest DASH and AMED quintiles had hypertension risk with ORs (95%CI) of 1.20 (1.10, 1.30) and 1.19 (1.09, 1.29), whereas those with the highest DASH and AMED quintiles had lower risks with 0.98 (0.91, 1.05) and 1.04 (0.97, 1.11). The stratified analysis found modification effect was more prominent in the < 65 years age group. Consuming more fresh vegetables, fruits, whole grains, and dairy would reduce the risk of hypertension caused by PM2.5 and its constituents.ConclusionsDietary patterns rich in antioxidants can reduce long-term exposure to PM2.5 and its constituents-induced hypertension defined by the 2017 ACC/AHA guideline, especially in young and middle-aged individuals. Compared to the Mediterranean diet, the DASH diet offers superior dietary guidance to prevent stage 1 hypertension caused by air pollution.

An urban air quality assessment based on a meteorological perspective.

An integrated approach to understanding all measured pollutants with multi-discipline in different time scales and understanding the mechanisms hidden under low air quality (AQ) conditions is essential for tackling potential air pollution issues. In this study, the air pollution of Sivas province was analyzed with meteorological and PM2.5 data over six years to assess the city's AQ in terms of PM2.5 pollution and analyze the effect of meteorological factors on it. It was found that the winter period (January-February-November-December) of every year except 2019-which has missing data-is the period with the highest air pollution in the province. In addition, the days exceeding the daily PM2.5 limit values in 2016, 2017, 2020, and 2021 were also seen in the spring and summer months, which inclined the study to focus on additional pollutant sources such as long-range dust transport and road vehicles. The year 2017 has the highest values and was analyzed in detail. Pollution periods with the most increased episodes in 2018 were analyzed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Dust Regional Atmospheric Model (DREAM) models. As a result of the study, the average PM2.5 values in 2017 were 31.66 ± 19.2µg/m3 and a correlation of -0.49 between temperature and PM2.5. As a result of model outputs, it was found that the inversion is intensely observed in the province, which is associated with an increase of PM2.5 during the episodes. Dust transport from northwestern Iraq and northeastern Syria is observed, especially on days with daily average PM2.5 values above 100µg/m3. Additionally, planetary boundary layer (PBL) data analysis with PM pollution revealed a significant negative correlation (r = -0.61). Air pollutants, particularly PM2.5, were found to be higher during lower PBL levels.

Long-term exposure to the components of fine particulate matters and disability after stroke: Findings from the China National Stroke Screening Surveys

BackgroundLong-term exposure to ambient fine particulate matter (PM2.5) has been linked to an increased risk of stroke. However, the effect of long-term exposure to PM2.5 and its major components on the functional disability of stroke patients remains unclear. MethodsBased on China National Stroke Screening Survey data obtained from 2013 to 2019, we conducted a national multicenter longitudinal study of the associations of long-term exposure to PM2.5 and its components with the risk of disability after stroke in China. Post-stroke disability was assessed using the modified Rankin scale (mRS), which ranges from 0 to 5, with higher scores indicating greater disability. Long-term exposure to PM2.5 and its five components [sulfate (SO42-), nitrate (NO3-), ammonium salt (NH4+), organic matter (OM), and black carbon (BC)] was determined based on average concentrations during the 3 years preceding mRS administration according to the geographic coordinates of residential communities, using state-of-the-art estimates from multiple sources. We used a fixed-effect model to evaluate the associations between mRS scores and PM2.5 exposure, with adjustment for multiple covariates. ResultsEvery 10 µg/m3 increase in PM2.5 was associated with a 0.019 (95% confidence interval, 0.003, 0.036) increase in mRS score, but the effect was not significant after adjusting for all covariates [0.016 (95% CI, −0.003, 0.032)]. For PM2.5 components, each IQR (7.92 µg/m3) increment in OM exposure was associated significantly with 0.062 (95% CI, 0.013, 0.111) increment in the mRS score. A significant association was observed between SO42- exposure and the mRS score [0.057 (95% CI, 0.003, 0.112), per IQR: 6.28 µg/m3]. However, no significant association was found with BC, NO3-, or NH4+ exposure. Furthermore, the nonlinear curves were observed for the exposure-response relationship between PM2.5 exposure and the mRS score. ConclusionGreater PM2.5 exposure increased the mRS score and was associated with post-stroke functional disability among stroke patients. However, different chemical components showed unequal neurotoxic effects, and long-term exposure to OM and SO42- may play a more important role. SynopsisThis study reports fine particulate matter at higher concentrations damages the functional ability among specific stroke patients, and PM2.5 components have different neurotoxicities.

Air pollution and the sequelae of COVID-19 patients: A multistate analysis

ImportanceRecent evidence links air pollution to the severity COVID-19 symptoms and to death from the disease. To date, however, few studies have assessed whether air pollution affects the sequelae to more severe states or recovery from COVID-19 in a cohort with individual data. ObjectiveTo assess how air pollution affects the transition to more severe COVID-19 states or to recovery from COVID-19 infection in a cohort with detailed patient information. Design and OutcomesWe used a cohort design that followed patients admitted to hospital in the Kaiser Permanente Southern California (KPSC) Health System, which has 4.7 million members with characteristics similar to the general population. Enrollment began on 06/01/2020 and ran until 01/30/2021 for all patients admitted to hospital while ill with COVID-19. All possible states of sequelae were considered, including deterioration to intensive care, to death, discharge to recovery, or discharge to death. Transition risks were estimated with a multistate model. We assessed exposure using chemical transport model that predicted ambient concentrations of nitrogen dioxide, ozone, and fine particulate matter (PM2.5) at a 1 km scale. ResultsEach increase in PM2.5 concentration equivalent to the interquartile range was associated with increased risk of deterioration to intensive care (HR of 1.16; 95% CI: 1.12–1.20) and deterioration to death (HR of 1.11; 95% CI: 1.04–1.17). Results for ozone were consistent with PM2.5 effects, but ozone also affected the transition from recovery to death: HR of 1.24 (95% CI: 1.01–1.51). NO2 had weaker effects but displayed some elevated risks. ConclusionsPM2.5 and ozone were significantly associated with transitions to more severe states while in hospital and to death after discharge from hospital. Reducing air pollution could therefore lead to improved prognosis for COVID-19 patients and a sustainable means of reducing the health impacts of coronaviruses now and in the future.

Short-term joint effects of ambient PM2.5 and O3 on mortality in Beijing, China.

In recent years, air pollution caused by co-occurring PM2.5 and O3, named combined air pollution (CAP), has been observed in Beijing, China, although the health effects of CAP on population mortality are unclear. We employed Poisson generalized additive models (GAMs) to evaluate the individual and joint effects of PM2.5 and O3 on mortality (nonaccidental, respiratory, and cardiovascular mortality) in Beijing, China, during the whole period (2014-2016) and the CAP period. Adverse health effects were assessed for percentage increases (%) in the three mortality categories with each 10-μg/m3 increase in PM2.5 and O3. The cumulative risk index (CRI) was adopted as a novel approach to quantify the joint effects. The results suggested that both PM2.5 and O3 exhibited the greatest individual effects on the three mortality categories with cumulative lag day 01. Increases in the nonaccidental, cardiovascular, and respiratory mortality categories were 0.32%, 0.36%, and 0.43% for PM2.5 (lag day 01) and 0.22%, 0.37%, and 0.25% for O3 (lag day 01), respectively. There were remarkably synergistic interactions between PM2.5 and O3 on the three mortality categories. The study showed that the combined effects of PM2.5 and O3 on nonaccidental, cardiovascular, and respiratory mortality were 0.34%, 0.43%, and 0.46%, respectively, during the whole period and 0.58%, 0.79%, and 0.75%, respectively, during the CAP period. Our findings suggest that combined exposure to PM2.5 and O3, particularly during CAP periods, could further exacerbate their single-pollutant health risks. These findings provide essential scientific evidence for the possible creation and implementation of environmental protection strategies by policymakers.

Short-term ambient air pollution risk for ischemic stroke hospitalization and related economic burden: A multi-city time-series study in southwest China

Short-term exposure to air pollution is associated with hospitalization for ischemic stroke (IS); however, evidence of the impact of the exposure on IS in highly polluted developing regions is limited. This study aimed to assess the relationships between air pollutants and IS hospitalization, as well as economic burden attributable to the hospitalization in Sichuan, China. Records from 160,555 IS hospitalizations were collected from medical institutions in nine cities in Sichuan from 2017 to 2019, along with simultaneous meteorological and air pollution data. Generalized additive model (GAM) was used to analyze the relationship between air pollutants and IS hospitalizations. The economic burden due to air pollutants exposure were further assessed using a cost-of-illness (COI) method. All p values were corrected for multiple comparisons. The single pollutant model showed that the effects of each interquartile range (IQR) increase in PM2.5, PM10, O3, and CO, on IS hospitalization peaked on lag 07, with relative risk values of 1.057(95% CI: 1.030–1.085), 1.060(95% CI:1.032–1.090), 1.110(95% CI:1.043–1.181), and 1.096 (95% CI:1.060–1.132), respectively. Stratified analysis shows that older people are more susceptible to the impact of air pollutants, and compared to the warm season, IS hospitalization in the cold season is more susceptible to exposure to O3 and CO. It has been determined that during the study period, the number of IS hospitalizations attributable to PM2.5 pollution was 5,157 and to PM10 pollution was 3,650, with an economic cost of CNY 67, 966, 100 and 48, 107, 900, respectively. In this study, we found that short-term exposure to PM2.5, PM10, O3, and CO can lead to increased hospitalizations for stroke and a quantifiably greater economic burden.

Long-term exposure to ambient air pollution, genetic susceptibility, and the incidence of bipolar disorder: A prospective cohort study

There is mounting recent evidence showing that air pollution exposure may be related to the risk of mental health, yet the association between long-term exposure to air pollution and the risk of incident bipolar disorder (BD) remains unclear. Thus we aim to identify associations between air pollution and the incidence of BD in a prospective population-based cohort. In total, 482,726 participants who were free of BD from the UK Biobank were included in this prospective study. We applied time-varying Cox proportional hazards models, accounting for relevant confounders, and used annual-year moving averages of air pollution as time-varying exposures. The genetic risk for BD was categorized into three categories (low, intermediate, and high) according to the tertiles of polygenic risk score. During a median of 10.79-year follow-up, 923 incident BD events were recorded. Long-term exposures to PM2.5, PM10, NO2, and NOx were associated with increased BD risk. Estimated HRs (95% CIs) for each interquartile range increase in PM2.5, PM10, NO2, and NOx concentrations were 1.31 (1.18–1.45), 1.19 (1.09–1.31), 1.19 (1.08–1.30), and 1.16 (1.07–1.26), respectively. Associations were still observed and even stronger at pollutant concentrations lower than WHO air quality guideline. In subgroup analysis stratified by genetic risk, we observed consistent associations between all pollutants and BD risk in intermediate and high genetic risk groups, but not in low genetic risk group. For example, the HRs (95% CIs) for PM2.5 were 1.00 (0.94–1.53), 1.30 (1.06–1.59), and 1.34 (1.16–1.54) in low, intermediate, and high genetic groups, respectively. In conclusion, long-term exposure to air pollution was significantly associated with an elevated risk of BD. Associations of air pollution with BD occurred only within intermediate and high genetic risk categories and were even stronger at the pollutants levels below WHO air quality guidelines. These findings could help inform policy makers regarding ambient air quality standards and BD management.

Long non-coding RNAs mediate the association between short-term PM2.5 exposure and circulating biomarkers of systemic inflammation

Although short-term fine particulate matter (PM2.5) exposure is associated with systemic inflammation, the effect of lncRNA on these association remains unknown. This study aims to investigate whether the plasma lncRNA mediate the effect of short-term PM2.5 exposure on systemic inflammation. In this cross-sectional study, plasma Clara cell protein 16 (CC16), interleukin 6 (IL-6), IL-8, tumor necrosis factor-α (TNF-α) and lncRNA expression levels were measured in 161 adults between March and April in 2018 in Shijiazhuang, China. PM2.5 concentrations were estimated 0–3 days prior to the examination date and the moving averages were calculated. Multiple linear regressions were used to evaluate the associations between PM2.5, the four biomarkers and lncRNA expression levels. Mediation analyses were performed to explore the potential roles of lncRNA expression in these associations. The median concentration of PM2.5 ranged from 39.65 to 60.91 mg/m3 across different lag days. The most significant effects on IL-6 and TNF-α per interquartile range increase in PM2.5 were observed at lag 0–3 days, with increases of 0.70 pg/mL (95% CI: 0.33, 1.07) and 0.21 pg/mL (95% CI: 0.06, 0.36), respectively. While the associations between PM2.5 and IL-8 (0.68 pg/mL, 95% CI: 0.34, 1.02) and CC16 (3.86 ng/mL, 95% CI: 1.60, 6.13) were stronger at lag 0 day. Interestingly, a negative association between PM2.5 and the expression of four novel lncRNAs (lnc-ACAD11–1:1, lnc-PRICKLE1-4:1, lnc-GPR39–7:2, and lnc-MTRNR2L12–3:6) were observed at each lag days. Furthermore, these lncRNAs mediated the effects of PM2.5 on the four biomarkers, with proportions of mediation ranged from 2.27% (95% CI: 1.19%, 9.82%) for CC16 to 35.60% (95% CI: 17.16%, 175.45%) for IL-6. Our findings suggested that plasma lncRNA expression mediat the acute effects of PM2.5 exposure on systematic inflammation. These highlight a need to consider circulating lncRNA expression as biomarkers to reduce health risks associated with PM2.5.

The air we breathe: An In-depth analysis of PM2.5 pollution in 1312 cities from 2000 to 2020.

In recent decades, the phenomenon of rapid urbanization in various parts of the world has led to a significant increase in PM2.5 concentration, which has emerged as a growing social concern. In order to achieve the objective of sustainable development, the United Nations Global Sustainable Development Goals (SDGs) have established the goal of creating inclusive, safe, resilient, and sustainable cities and human habitats (SDG 11). Goal 11.6 aims to decrease the negative environmental impact per capita in cities, with an emphasis on urban air quality and waste management. However, the global distribution of PM2.5 pollution varies due to disparities in urbanization development in different regions. The purpose of this paper is to explore the global spatial distribution and temporal variation of PM2.5 in cities with populations greater than 300,000 from 2000 to 2020, to gain insight into the issue. The findings indicate that PM2.5 concentrations are expected to continue increasing as urbanization progresses, but the rate of evolution of PM2.5 concentration varies depending on the continent, country, and city. From 2000 to 2020, PM2.5 concentration increased significantly in Asia and Africa, with the majority of the increased concentrations located in Asian countries and some African countries. On the other hand, most European and American countries had lower PM2.5 concentrations. The results of this study have the potential to inform urbanization policy formulation by providing knowledge about the spatial distribution of PM2.5 pollution during global urbanization. Addressing the issue of PM2.5 pollution is critical in achieving SDG 11.6 and promoting sustainable and coordinated development in cities worldwide.

Long-Term PM2.5 Exposure, Lung Function, and Cognitive Function Among Middle-Aged and Older Adults in China.

Long-term exposure to PM2.5 is related to poor lung function and cognitive impairment, but less is known about the pathway involved in this association. We aimed to explore whether the effect of PM2.5 on cognitive function was mediated by lung function. A total of 7 915 adults older than 45 years old were derived from the China Health and Retirement Longitudinal Study (CHARLS) collected in 2011 and 2015. PM2.5 exposure was estimated using a geographically weighted regression model. Lung function was measured by peak expiratory flow (PEF). Cognitive function was evaluated through a structured questionnaire with 4 dimensions: episodic memory, attention, orientation, and visuoconstruction. Under the counterfactual framework, causal mediation analysis was applied to examine direct and indirect associations. An interquartile range (IQR) increase in PM2.5 change was significantly related to an 8.480 (95% confidence interval [CI]: 3.116, 13.845) decrease in PEF change and a 0.301 (95% CI: 0.100, 0.575) decrease in global cognitive score change. The direct and indirect effects of PM2.5 exposure on global cognitive performance were -0.279 (95% CI: -0.551, -0.060) and -0.023 (95% CI: -0.041, -0.010), respectively. The proportion of the indirect effect was 7.48% (p = .010). The same significant association appeared in only 2 dimensions, episodic memory and attention, which were both mediated by PEF. Lung function played a partially mediating role in the association between long-term PM2.5 exposure and cognition. More clean air actions should be undertaken to improve lung function and cognitive function in older adults.

Associations of particulate matter, gaseous pollutants, and road traffic noise with the prevalence of asthma in children

The purposes of this study were to elucidate the associations between exposure to particulate matter, gaseous pollutants, and road traffic noise and asthma prevalence and to determine the interaction between exposure to multiple pollutants and asthma in children. A total of 3,246 children were recruited from 11 kindergartens in New Taipei City, Taiwan. Land use regression (LUR) was used to establish predictive models for estimating individual exposure levels of particulate matter, gaseous pollutants, and the 24 h A-weighted equivalent sound pressure level (LAeq,24). Multiple logistic regression was performed to test the associations between exposure to these environmental factors and asthma prevalence in children. Multiple-exposure models revealed that an interquartile-range (IQR) increase in PM2.5 (1.17 μg/m3) and PM10 (10.69 μg/m3) caused a 1.34-fold (95% confidence interval [CI] = 1.05–1.70) and 1.17-fold (95% CI = 1.01–1.36) increase in risk of asthma prevalence in children after adjusting for LAeq,24 and NO2. Co-exposure to PM2.5, LAeq,24, and O3, SO2, or CO, as well as co-exposure to PM10, LAeq,24, and CO produced similar findings. Only exposure to one IQR of SO2 (0.15 ppb) was observed a significant association (odds ratio = 1.16, 95% CI = 1.00–1.34) with the asthma prevalence in children after adjusting for PM10 and LAeq,24. Exposure to PM2.5, PM10, and SO2 may be associated with a higher asthma prevalence in children, while other gaseous pollutants and road traffic noise did not demonstrate significant associations. The interaction of exposure to air pollutants and road traffic noise on asthma prevalence in children was not observed in this study.

Long-term exposure to low concentrations of air pollution and decline in lung function in people with idiopathic pulmonary fibrosis: Evidence from Australia.

Little is known about the association between ambient air pollution and idiopathic pulmonary fibrosis (IPF) in areas with lower levels of exposure. We aimed to investigate the impact of air pollution on lung function and rapid progression of IPF in Australia. Participants were recruited from the Australian IPF Registry (n = 570). The impact of air pollution on changes in lung function was assessed using linear mixed models and Cox regression was used to investigate the association with rapid progression. Median (25th-75th percentiles) annual fine particulate matter (<2.5 μm, PM2.5 ) and nitrogen dioxide (NO2 ) were 6.8 (5.7, 7.9) μg/m3 and 6.7 (4.9, 8.2) ppb, respectively. Compared to living more than 100 m from a major road, living within 100 m was associated with a 1.3% predicted/year (95% confidence interval [CI] -2.4 to -0.3) faster annual decline in diffusing capacity of the lungs for carbon monoxide (DLco). Each interquartile range (IQR) of 2.2 μg/m3 increase in PM2.5 was associated with a 0.9% predicted/year (95% CI -1.6 to -0.3) faster annual decline in DLco, while there was no association observed with NO2 . There was also no association between air pollution and rapid progression of IPF. Living near a major road and increased PM2.5 were both associated with an increased rate of annual decline in DLco. This study adds to the evidence supporting the negative effects of air pollution on lung function decline in people with IPF living at low-level concentrations of exposure.

Association between long-term exposure to low level air pollutants and incident end-stage kidney disease in the UK Biobank: A prospective cohort

BackgroundPrevious studies suggest that air pollution can increase the risk of incident chronic kidney disease (CKD). However, the association between end-stage kidney disease (ESKD) and co-exposure to relatively low-level air pollutants remains unclear. MethodsA prospective cohort was designed based on UK Biobank. From 1 January 2010 to 12 November 2021, 453,347 participants were followed up over a median of 11.87 years. Principal component analysis was used to identify major patterns of five air pollutants, including PM2.5, PM2.5-10, PM10, NO2, and NOx. Sub-distribution hazards models were used to estimate the associations between air pollution, individually or jointly, and incident ESKD, CKD, and all-cause death, respectively. ResultsPrincipal component analysis identified two principal components, namely RC1 (PM2.5, NO2, and NOx) and RC2 (PM2.5-10 and PM10). An elevated risk of incident ESKD was associated with an interquartile range (IQR) increase in PM2.5 (hazard ratio: 1.11, 95% confidence interval: 1.02–1.22), NO2 (1.16, 1.04–1.30), NOx (1.08, 1.00–1.17), and RC1 (1.12, 1.02–1.23). An elevated risk of incident CKD was associated with an IQR increase in PM2.5 (1.05, 1.03–1.07), NO2 (1.04, 1.02–1.06), NOx (1.03, 1.02–1.05), and RC1 (1.04, 1.02–1.06). An increased risk of all-cause mortality was associated with an IQR increase in PM2.5 (1.02, 1.00–1.04). Restricted cubic spline analyses indicated a monotonic elevating association of PM2.5, NO2, NOx, and RC1 with ESKD incidence. ConclusionsLong-term exposure to PM2.5, NO2, NOx, and their complex was associated with elevated ESKD incidence, even at relatively lower levels of air pollution.

Chemical Characteristics and Source Apportionment of Organic Aerosols in Urban Shanghai During Cold Season Based on High Time-resolution Measurements of Organic Molecular Markers

Organic aerosols (OA) are closely related to the formation of both PM2.5 and O3 in the atmosphere. In this study, a thermal desorption aerosol GC/MS (TAG) online system was adopted to measure hourly concentrations of 94 total organic molecular markers in PM2.5 at an urban site in Shanghai from November 6th to December 31st, 2021. Combined with air mass cluster analysis and other online measurement data, the chemical characteristics of OA under the influence of different air masses, oxidant levels, and relative humidity (RH) levels were investigated. The results showed that OA was characterized by higher mass percentages of primary organic molecular markers (e.g., saturated fatty acids, unsaturated fatty acids, and alkanes) under the influence of local air masses. Further, high loadings of biomass burning tracers were observed in OA under the influence of long-range transported air masses. In contrast, OA impacted by marine air masses was laden with significantly higher fractions of secondary organic molecular markers, such as dicarboxylic acids and hydroxyl dicarboxylic acids, which were formed from a wide range of volatile organic precursors through photochemical and aqueous-phase processing. With the application of the positive matrix factorization (PMF) model, seven total primary source factors and five secondary source factors were resolved for PM2.5 and OA during the observation. Among them, secondary nitrate was the highest contributor to PM2.5 mass with a mass percentage of 25.2%, whereas vehicle emissions were the top contributor (24.0%) to OA mass. Primary source factors, including coal combustion, vehicle emission, and cooking emission as well as their corresponding secondary source factors (e.g., secondary nitrate, secondary organic aerosols 2, etc.) showed elevated contributions in PM2.5 and OA with the increase in PM2.5 masses, indicating that more stringent controls of local emission sources (e.g., coal combustion, vehicle emission, and cooking emission) are needed to further lower PM2.5 pollution and improve air quality in Shanghai.

Immortal Time Bias With Time-Varying Exposures in Environmental Epidemiology: A Case Study in Lung Cancer Survival.

Immortal time bias is a well-recognized bias in clinical epidemiology but is rarely discussed in environmental epidemiology. Under the target trial framework, this bias is formally conceptualized as a misalignment between the start of study follow-up (time 0) and treatment assignment. This misalignment can occur when attained duration of follow-up is encoded into treatment assignment using minimums, maximums, or averages. The bias can be exacerbated in the presence of time trends commonly found in environmental exposures. Using lung cancer cases from the California Cancer Registry (2000-2010) linked with estimated concentrations of particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5), we replicated previous studies that averaged PM2.5 exposure over follow-up in a time-to-event model. We compared this approach with one that ensures alignment between time 0 and treatment assignment, a discrete-time approach. In the former approach, the estimated overall hazard ratio for a 5-μg/m3 increase in PM2.5 was 1.38 (95% confidence interval: 1.36, 1.40). Under the discrete-time approach, the estimated pooled odds ratio was 0.99 (95% confidence interval: 0.98, 1.00). We conclude that the strong estimated effect in the former approach was likely driven by immortal time bias, due to misalignment at time 0. Our findings highlight the importance of appropriately conceptualizing a time-varying environmental exposure under the target trial framework to avoid introducing preventable systematic errors.