Increase In PM2 Research Articles

DNA methylation mediates the effects of PM2.5 and O3 on ceramide metabolism: A novel mechanistic link between air pollution and insulin resistance

Insulin resistance (IR), linked to air pollution, is an initial stage of early-onset Type 2 diabetes mellitus (T2DM). While ceramide metabolism plays an important role in IR pathogenesis, the effects of air pollution on this process and its mechanisms remain unclear. We recruited young adults aged 18–30 years to a panel study in Wuhan, China. Using personal portable devices and stationary monitoring stations, we tracked particulate matter with aerodynamic diameters≤ 2.5 µm (PM2.5) and Ozone (O3) levels. Liquid chromatography/mass spectrometry (LC-MS) based metabolomics quantified ceramide metabolism, and Illumina Infinium Human Methylation 850 kBeadChip assay measured deoxyribonucleic acid (DNA) methylation. Linear mixed-effects models assessed relationships of air pollution with i) IR indexes, ii) ceramide metabolism, and iii) DNA methylation. Mediation analysis was subsequently performed to evaluate the potential mediating effect of DNA methylation in the association between air pollution and ceramide metabolism. PM2.5 and O3 were associated with elevated IR. Specifically, each 10 μg/m3 increase in PM2.5 and O3 at lag0–12 h significantly increased triglyceride‑glucose index (TyG index) and TyG-BMI (TyG - Body mass index) by 0.88%, 0.89% and 0.26%, 0.26%, respectively. Furthermore, levels of eight ceramides were altered by air pollution exposure, and nine methylated CpG sites in inflammation genes mediated the effects of air pollution on ceramide metabolism. Our findings imply the existence of a novel mechanism connecting air pollution to IR.

Short term exposure to low level ambient fine particulate matter and natural cause, cardiovascular, and respiratory morbidity among US adults with health insurance: case time series study

ObjectiveTo estimate the excess relative and absolute risks of hospital admissions and emergency department visits for natural causes, cardiovascular disease, and respiratory disease associated with daily exposure to fine particulate...

Ambient particulate matter and surrounding greenness in relation to sleep quality among pregnant women: A nationwide cohort study

BackgroundParticulate air pollution and residential greenness are associated with sleep quality in the general population; however, their influence on maternal sleep quality during pregnancy has not been assessed. ObjectiveThis cross-sectional study investigated the individual and interactive effects of exposure to particulate matter (PM) air pollution and residential greenness on sleep quality in pregnant women. MethodsPregnant women (n = 4933) enrolled in the Korean Children's Environmental Health Study with sleep quality information and residential address were included. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The average concentrations of PM (PM2.5 and PM10) during pregnancy were estimated through land use regression, and residential greenness in a 1000 m buffer area around participants' residences was estimated using the Normalized Difference Vegetation Index (NDVI1000-m). Modified Poisson regression models were used to estimate the associations between PM and NDVI and poor sleep quality (PSQI >5) after controlling for a range of covariates. A four-way mediation analysis was conducted to examine the mediating effects of PM. ResultsAfter adjusting for confounders, each 10 μg/m3 increase in PM2.5 and PM10 exposure was associated with a higher risk of poor sleep quality (relative risk [RR]: 1.06; 95% confidence interval [CI]: 1.01, 1.11; and RR: 1.09; 95% CI: 1.06, 1.13, respectively), and each 0.1-unit increase in NDVI1000-m was associated with a lower risk of poor sleep quality (RR: 0.97; 95% CI: 0.95, 0.99). Mediation analysis showed that PM mediated approximately 37%–56% of the association between residential greenness and poor sleep quality. ConclusionsThis study identified a positive association between residential greenness and sleep quality. Furthermore, these associations are mediated by a reduction in exposure to particulate air pollution and highlight the link between green areas, air pollution control, and human health.

Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection

The association between PM2.5 and non-respiratory infections is unclear. Using data from Medicare beneficiaries and high-resolution datasets of PM2.5 and its constituents across 39,296 ZIP codes in the U.S between 2000 and 2016, we investigated the associations between annual PM2.5, PM2.5 constituents, source-specific PM2.5, and hospital admissions from non-respiratory infections. Each standard deviation (3.7-μg m−3) increase in PM2.5 was associated with a 10.8% (95%CI 10.8–11.2%) increase in rate of hospital admissions from non-respiratory infections. Sulfates (30.8%), Nickel (22.5%) and Copper (15.3%) contributed the largest weights in the observed associations. Each standard deviation increase in PM2.5 components sourced from oil combustion, coal burning, traffic, dirt, and regionally transported nitrates was associated with 14.5% (95%CI 7.6–21.8%), 18.2% (95%CI 7.2–30.2%), 20.6% (95%CI 5.6–37.9%), 8.9% (95%CI 0.3–18.4%) and 7.8% (95%CI 0.6–15.5%) increases in hospital admissions from non-respiratory infections. Our results suggested that non-respiratory infections are an under-appreciated health effect of PM2.5.

Fine-particulate air pollution and behaviorally inclusive mortality impacts of China’s winter heating policy, 2013–2018

China’s spatially discontinuous winter heating policy has been used to examine how sustained exposure to air pollution impacts health. This influential literature exploits quasi-experimental cross-sectional variation in atmospheric emissions in a geographically vast and populous nation. Our study introduces an alternative external definition of the winter heating boundary and takes advantage of an unprecedented expansion of pollution and mortality surveillance, covering at least 10 times more sites and finer-grained pollution particle sizes that are more relevant to health standards today. We estimate spatial discontinuities in pollution and mortality that shrink over time, consistent with tighter emissions regulations, higher quality medical care, and increased air quality disclosure to – and defensive behavior by – the public. We find that in 2013–2015 a 10-μg/m3 increase in PM2.5 raised behaviorally inclusive mortality for cardiovascular and respiratory causes by 11% (95% confidence interval = 2–20%) and lung cancer mortality by 20% (95% CI = 4–37%).

Variations of PM2.5 and Health Risk Assessment in the City of Mashhad During 2010-2018

Background: Air pollution stands as a significant environmental threat impacting human health across the globe, encompassing both developed and developing nations. This study aimed to survey the temporal variations of PM2.5 and gauge its potential health effects in the city of Mashhad over the period of 2010-2018. Methods: This cross-sectional study was carried out among the residents of Mashhad city. PM2.5 concentration data spanning the years 2008-2019 were collected and subjected to analysis using Excel and AirQ software. Results: The results indicate that the highest concentration of PM2.5 was associated with the year 2010, while the lowest concentration was observed in 2015. The analytical findings demonstrated that for each 10 µg/m3 increase in PM2.5 concentrations, the relative risk for total mortality increased by 10.47%. Furthermore, based on the Air Quality Index (AQI) results, 2010 exhibited the most adverse condition in terms of PM2.5 concentrations in Mashhad city. Conclusion: In general, long-term exposure to ambient PM2.5 significantly contributed to mortality in the megacity of Mashhad. As air pollution is a modifiable risk factor, it is advisable to implement sustainable control policies to protect public health.

Long-term exposure to air pollution and incidence of gastric and the upper aerodigestive tract cancers in a pooled European cohort: The ELAPSE project.

Air pollution has been shown to significantly impact human health including cancer. Gastric and upper aerodigestive tract (UADT) cancers are common and increased risk has been associated with smoking and occupational exposures. However, the association with air pollution remains unclear. We pooled European subcohorts (N = 287,576 participants for gastric and N = 297,406 for UADT analyses) and investigated the association between residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone in the warm season (O3w) with gastric and UADT cancer. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. During 5,305,133 and 5,434,843 person-years, 872 gastric and 1139 UADT incident cancer cases were observed, respectively. For gastric cancer, we found no association with PM2.5, NO2 and BC while for UADT the hazard ratios (95% confidence interval) were 1.15 (95% CI: 1.00-1.33) per 5 μg/m3 increase in PM2.5, 1.19 (1.08-1.30) per 10 μg/m3 increase in NO2, 1.14 (1.04-1.26) per 0.5 × 10-5 m-1 increase in BC and 0.81 (0.72-0.92) per 10 μg/m3 increase in O3w. We found no association between long-term ambient air pollution exposure and incidence of gastric cancer, while for long-term exposure to PM2.5, NO2 and BC increased incidence of UADT cancer was observed.

Association between prenatal and childhood PM2.5 exposure and preadolescent anxiety and depressive symptoms.

Fine particulate matter (PM2.5) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise. We examined the association between early-life PM2.5 exposure and symptoms of anxiety and depression in a cohort of 8-11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children's Manifest Anxiety Scale and Children's Depression Inventory. Daily PM2.5 was estimated using a satellite-based exposure model and averaged over several early and recent exposure windows. Linear and logistic regression models were used to estimate the change in symptoms with each 5-µg/m3 increase in PM2.5. Models were adjusted for child's age, child's sex, maternal age, maternal socioeconomic status, season of conception, and temperature. Average anxiety and depressive symptom T-scores were 51.0 (range 33-73) and 53.4 (range 44-90), respectively. We observed consistent findings for exposures around the fourth year of life, as this was present for both continuous and dichotomized anxiety symptoms, in both independent exposure models and distributed lag modeling approaches. This window was also observed for elevated depressive symptoms. An additional consistent finding was for PM2.5 exposure during early pregnancy in relation to both clinically elevated anxiety and depressive symptoms, this was seen in both traditional and distributed lag modeling approaches. Both early life and recent PM2.5 exposure were associated with higher mental health symptoms in the child highlighting the role of PM2.5 in the etiology of these conditions.

Exposure to particulate matter and ozone, locations of regulatory monitors, and sociodemographic disparities in the city of Rio de Janeiro: Based on local air pollution estimates generated from machine learning models

South America is underrepresented in research on air pollution exposure disparities by sociodemographic factors, although such disparities have been observed in other parts of the world. We investigated whether exposure to and information about air pollution differs by sociodemographic factors in the city of Rio de Janeiro, the second most populous city in Brazil with dense urban areas, for 2012–2017. We developed machine learning-based models to estimate daily levels of O3, PM10, and PM2.5 using high-dimensional datasets from satellite remote sensing, atmospheric and land variables, and land use information. Cross-validations demonstrated good agreement between the estimated levels and measurements from ground-based monitoring stations: overall R2 of 76.8 %, 63.9 %, and 69.1 % for O3, PM2.5, and PM10, respectively. We conducted univariate regression analyses to investigate whether long-term exposure to O3, PM2.5, PM10 and distance to regulatory monitors differs by socioeconomic indicators, the percentages of residents who were children (0-17 years) or age 65+ years in 154 neighborhoods. We also examined the number of days exceeding the Brazilian National Air Quality Standard (BNAQS). Long-term exposures to O3 and PM2.5 were higher in more socially deprived neighborhoods. An interquartile range (IQR) increment of the social development index (SDI) was associated with a 3.6 μg/m3 (95 % confidence interval [CI]: 2.9, 4.4; p-value≤0.001) decrease in O3, and 0.3 μg/m3 (95 % CI: 0.2, 0.5; p-value = 0.010) decrease in PM2.5. An IQR increase in the percentage of residents who are children was associated with a 4.1 μg/m3 (95 % CI: 3.1, 5.0; p-value≤0.001) increase in O3, and 0.4 μg/m3 (95 % CI: 0.3, 0.6; p-value = 0.009) increase in PM2.5. An IQR increase in the percentage of residents age ≥65was associated with a 3.3 μg/m3 (95 % CI: 2.4, 4.3; p-value=<0.001) decrease in O3, and 0.3 μg/m3 (95 % CI: 0.1, 0.5; p-value = 0.058) decrease in PM2.5. There were no apparent associations for PM10. The association for daily O3 levels exceeding the BNAQS daily standard was 0.4 %p–0.8 %p different by the IQR of variables, indicating a 7–15 days difference in the six-year period. The association for daily PM2.5 levels exceeding the BNAQS daily standard showed a 0.7–1.5 %p difference by the IQR, meaning a 13–27 days difference in the period. We did not find statistically significant associations between the distance to monitors and neighborhood characteristics but some indication regarding SDI. We found that O3 levels were higher in neighborhoods situated farther from monitoring stations, suggesting that elevated levels of air pollution may not be routinely measured. Exposure disparity patterns may vary by pollutants, suggesting a complex interplay between environmental and socioeconomic factors in environmental justice.

Association of short-term PM2.5 exposure with airway innate immune response, microbiota and metabolism alterations in human airways

Exposure to fine particulate matter (PM2.5) has been associated with impaired airway innate immunity, leading to diverse lung disorders. However, the mechanisms of the adverse effects of PM2.5 on the airway innate immune system has not been adequately elucidated. This study aimed to investigate the association between short-term exposure to ambient PM2.5 and airway innate immune responses. A panel study of 53 undergraduate students was conducted in November 2020 and April 2021. Levels of airway innate immune biomarkers including interleukin-1β (IL-1β), IL-4, IL-6, IL-8, IL-17, interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), myeloperoxidase (MPO), and matrix metalloproteinase-9 (MMP-9) in induced sputum were measured, and airway microbiota and metabolites examined. Linear mixed-effect model was used to evaluate the effects of short-term exposure to PM2.5 on the above-listed airway immune biomarkers. The results indicated that for every 10 μg/m3 increase in PM2.5 concentration (at lag3), was associated with an increase of 21.3 % (5.4 %–37.1 %), 26.2 % (0.30 %–52.1 %), 22.4 % (0.70 %–44.2 %), 27.4 % (6.6 %–48.3 %), 18.3 % (4.6 %–31.9 %), 3.9 % (0.20 %–7.6 %) or 2.4 % (0.10 %–4.7 %) in IL-6, TNF-α, IL-17, IL-4, IFN-γ, MPO, or MMP-9 levels, respectively. Meanwhile, exposure to higher levels of ambient PM2.5 was found to significantly modulate airway microbiota and metabolite profile. Specifically, Prevotella and Fusobacterium, as well as 96 different metabolites were associated with PM2.5 levels. The metabolic pathways associated with these metabolites mainly included amino acid biosynthesis and metabolism. Notably, PM2.5 exposure-induced alterations of some airway microbiota were significantly correlated with specific airway metabolic change. Taken together, these results demonstrated that short-term exposure to PM2.5 was associated with alterations of airway immune response, microbial dysbiosis and changes of metabolites. This study provided insights into the mechanisms underlying PM2.5-induced airway innate immune responses.

Exploring the link between particulate matter pollution and acute respiratory infection risk in children using generalized estimating equations analysis: a robust statistical approach

BackgroundIndia is facing a burdensome public health challenge due to air pollution, with a particularly high burden of acute respiratory infections (ARI) among children. To address this issue, our study aims to evaluate the association between exposure to fine particulate matter (PM2.5) and ARI incidence in young children in India.Materials and methodsOur study used PM2.5 data provided by the Atmospheric Composition Analysis Group at Washington University to assess the association between PM2.5 exposure and ARI incidence in 223,375 children sampled from the 2019–2021 Demographic Health Survey in India. We employed the generalized estimating equation and reported odds ratios and 95% confidence intervals for a 10 µg/m3 increase in PM2.5 and quartiles of PM2.5 exposure.ResultsEach 10 µg/m3 increase in PM2.5 levels was associated with an increased odds of ARI (OR: 1.23, 95% CI: 1.19–1.27). A change from the first quartile of PM2.5 (2.5–34.4 µg/m3) to the second quartile (34.5–51.5 µg/m3) of PM2.5 was associated with a two-fold change (OR: 2.06, 95% CI: 1.60–2.66) in the odds of developing ARI. Similarly, comparing the first quartile to the fourth quartile of PM2.5 exposure (78.3–128.9 µg/m3) resulted in an over four-fold increase in the odds of ARI (OR: 4.45, 95% CI: 3.37–5.87).ConclusionMitigation efforts must be continued implementing higher restrictions in India and to bring new interventions to ensure safe levels of air for reducing the burden of disease and mortality associated with air pollution in India.

Air pollution is associated with increased incidence-rate of head and neck cancers: A nationally representative ecological study

IntroductionEarly studies show conflicting findings regarding particulate matter ≤ 2.5 μm in diameter (PM2.5) exposure and development of head and neck cancers (HNC). We analyzed the relationship between PM2.5 exposure and various types of HNC in a nationally representative ecological sample. MethodsWe determined HNC incidence in 608 US counties from 2011 to 2019 using the Surveillance, Epidemiology and End Results (SEER) Program from the National Cancer Institute. We also collected information on sociodemographic factors from SEER and data on smoking and alcohol intake from CDC data frames (county level). PM2.5 exposure levels were estimated using satellite and meteorological data via previously validated general additive models. Flexible semi-nonparametric regression models were used to test the relationship between PM2.5 exposure levels and HNC incidence, adjusting for demographics, socioeconomic factors, and comorbidity. ResultsIncreased PM2.5 exposure levels were associated with higher incidence-rates of oral cavity and pharyngeal cancers controlling for confounders in our primary analyses (IRR = 1.04, 95 % CI 1.01, 1.07, p = 0.02 per 1 μg/m3 increase in PM2.5). This relationship was maintained after adjusting for multiple testing (Holm s method, p = 0.04) and in ordinary least squares (OLS) regression (β = 0.17, 95 % CI 0.01, 0.57, p = 0.01). Increased exposure was also associated with other HNC: esophagus (IRR = 1.06, 95 % CI 1.01, 1.11, p = 0.02), lip (IRR = 1.16, 95 % CI 1.03, 1.31, p = 0.01), tonsil (IRR = 1.10, 95 % CI 1.03, 1.16, p < 0.01). However, these relationships were not maintained in secondary analyses. ConclusionsThis nationally representative ecological study shows that increased levels of air pollution are associated with increased incidence of overall oral cavity and pharyngeal cancers in the US.

Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand.

Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous. This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels. Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p&lt;0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p&lt;0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p&lt;0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak. Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.

Modification of Food Allergy on the Associations between Early Life Exposure to Size-Specific Particulate Matter and Childhood Allergic Rhinitis.

Previous studies have reported the association between particulate matter (PM) and childhood allergic rhinitis (AR). However, it is unclear whether food allergy (FA) modifies the PM-AR association. We aimed at evaluating the effect of the modification of FA on PM-AR association in preschool children. We adopted a cross-sectional study and conducted a questionnaire survey among preschool children aged 3-6 years in 7 cities in China from June 2019 to June 2020 to collect information on AR and FA. We used a combination of multilevel logistic regression and restricted cubic spline functions to quantitatively assess whether FA modifies the associations between size-specific PM exposure (1 × 1 km) and the risk of AR. The adjusted odds ratios (ORs) for AR among the children with FA as per a 10 μg/m3 increase in early life PM1, PM2.5, and PM10 were significantly higher than the corresponding ORs among the children without FA [e.g., OR: 1.58, 95% CI: (1.32, 1.90) vs 1.29, 95% CI: (1.18, 1.41), per 10 μg/m3 increase in PM1]. The interactions between FA and size-specific PM exposure and their effects on AR were statistically significant (all p-int < 0.001). FA, as an important part of the allergic disease progression, may modify the PM-AR association in preschool children.

Significantly Elevated Urinary OH-PAHs and Oxidative Damage Concentrations Attributable to PM2.5 Exposure: A Panel Study of Preaging Females in Chiang Mai, Thailand

Exposure to ambient particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) has been associated with oxidative damage. This study investigated the PM2.5-bound polycyclic aromatic hydrocarbon (PAH) exposure levels during elevated PM2.5 levels and the oxidative damage among a preaging females in Chiang Mai, Thailand. The 64 female participants, aged between 50 and 65 years old, were followed for 5 weeks consecutively during the non-haze rainy season as the baseline and haze episodes. The morning void urine sample was collected weekly and analyzed for 8 species of hydroxylated-polycyclic aromatic hydrocarbons (OH-PAHs) and malondialdehyde (MDA). The results showed that the high increase in PM2.5 levels was positively associated with OH-PAH levels. In addition, for every 1 µg/gCre increase in individual urinary OH-PAH concentrations, the MDA concentration increased from 0.073 to 2.071 µg/gCre. Therefore, the present study suggested that detected urinary OH-PAHs were attributable to PM2.5-bound PAH exposure, particularly from inhalation. These study results provide useful information for policy makers and public health agencies to mitigate the chain effects of PM2.5 exposure from haze pollution. Keywords: Air pollution, Hydroxylated-PAHs, Oxidative stress, Urinary biomarkers

Significantly Increased Accumulations of PAHs in Scalp Hair During Smoke-haze Period Among Female Adolescents in Chiang Mai, Thailand

Limitations in reporting polycyclic aromatic hydrocarbons (PAHs) accumulated in humans arise from the impact of intense biomass burning and air pollution in upper Southeast Asia. This study analyzed PAHs in human hair samples and explored the associations between ambient PM2.5 and hair PAH concentrations. Follow-up hair collections were conducted on 111 female students, and hair samples with a length of 4 cm were analyzed. Ten different PAHs were identified in the subjects' hair samples. The most substantial pooled estimate of cumulative effects of PM2.5 exposure was observed at lag04 (4-month average). At lag04, every 10 μg/m3 increase in PM2.5 concentration was significantly associated with 0.33, 0.29, 0.35, 0.16, 0.04, 0.64, and 1.66 ng/g hair increases in Acy, Ace, Flu, Ant, Chr, BaP, and total PAHs, respectively (P &lt; 0.05). The findings underscore the significant contribution of ambient PM2.5 exposure to the elevation of PAHs in human hair. Specifically, each centimeter of hair represents a one-month exposure to ambient PM2.5. Moreover, the accumulation of BaP, a carcinogenic PAH, significantly increased at heightened PM2.5 levels, emphasizing the importance of hair analysis in assessing PAH exposure risks and obtaining reliable and comprehensive health risk information. Keywords: Polycyclic aromatic hydrocarbons, Hair analysis, PM2.5

Spatial spillover effect of environmental factors on the tuberculosis occurrence among the elderly: a surveillance analysis for nearly a dozen years in eastern China

BackgroundIn many areas of China, over 30% of tuberculosis cases occur among the elderly. We aimed to investigate the spatial distribution and environmental factors that predicted the occurence of tuberculosis in this group.MethodsData were collected on notified pulmonary tuberculosis (PTB) cases aged ≥ 65 years in Zhejiang Province from 2010 to 2021. We performed spatial autocorrelation and spatial-temporal scan statistics to determine the clusters of epidemics. Spatial Durbin Model (SDM) analysis was used to identify significant environmental factors and their spatial spillover effects.Results77,405 cases of PTB among the elderly were notified, showing a decreasing trend in the notification rate. Spatial-temporal analysis showed clustering of epidemics in the western area of Zhejiang Province. The results of the SDM indicated that a one-unit increase in PM2.5 led to a 0.396% increase in the local notification rate. The annual mean temperature and precipitation had direct effects and spatial spillover effects on the rate, while complexity of the shape of the greenspace (SHAPE_AM) and SO2 had negative spatial spillover effects.ConclusionTargeted interventions among the elderly in Western Zhejiang may be more efficient than broad, province-wide interventions. Low annual mean temperature and high annual mean precipitation in local and neighboring areas tend to have higher PTB onset among the elderly.

Exposure to PM2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China.

Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.

Intrauterine and early postnatal exposures to submicron particulate matter and childhood allergic rhinitis: A multicity cross-sectional study in China

BackgroundAirborne particulate matter pollution has been linked to occurrence of childhood allergic rhinitis (AR). However, the relationships between exposure to particulate matter with an aerodynamic diameter ≤1 μm (PM1) during early life (in utero and first year of life) and the onset of childhood AR remain largely unknown. This study aims to investigate potential associations of in utero and first-year exposures to size-segregated PMs, including PM1, PM1–2.5, PM2.5, PM2.5–10, and PM10, with childhood AR. MethodsWe investigated 29286 preschool children aged 3–6 years in 7 Chinese major cities during 2019–2020 as the Phase II of the China Children, Families, Health Study. Machine learning-based space-time models were utilized to estimate early-life residential exposure to PM1, PM2.5, and PM10 at 1 × 1-km resolutions. The concentrations of PM1–2.5 and PM2.5–10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multiple mixed-effects logistic models were used to assess the odds ratios (ORs) and 95% confidence intervals (CIs) of childhood AR associated with per 10-μg/m3 increase in exposure to particulate air pollution during in utero period and the first year of life. ResultsAmong the 29286 children surveyed (mean ± standard deviation, 4.9 ± 0.9 years), 3652 (12.5%) were reported to be diagnosed with AR. Average PM1 concentrations during in utero period and the first year since birth were 36.3 ± 8.6 μg/m3 and 33.1 ± 6.9 μg/m3, respectively. Exposure to PM1 and PM2.5 during pregnancy and the first year of life was associated with an increased risk of AR in children, and the OR estimates were higher for each 10-μg/m3 increase in PM1 than for PM2.5 (e.g., 1.132 [95% CI: 1.022–1.254] vs. 1.079 [95% CI: 1.014–1.149] in pregnancy; 1.151 [95% CI: 1.014–1.306] vs. 1.095 [95% CI: 1.008–1.189] in the first year of life). No associations were observed between AR and both pre- and post-natal exposure to PM1–2.5, indicating that PM1 rather than PM1–2.5 contributed to the association between PM2.5 and childhood AR. In trimester-stratified analysis, childhood AR was only found to be associated with exposure to PM1 (OR = 1.077, 95% CI: 1.027–1.128), PM2.5 (OR = 1.048, 95% CI: 1.018–1.078), and PM10 (OR = 1.032, 95% CI: 1.007–1.058) during the third trimester of pregnancy. Subgroup analysis suggested stronger PM-AR associations among younger (<5 years old) and winter-born children. ConclusionsPrenatal and postnatal exposures to ambient PM1 and PM2.5 were associated with an increased risk of childhood AR, and PM2.5-related hazards could be predominantly attributed to PM1. These findings highlighted public health significance of formulating air quality guideline for ambient PM1 in mitigating children's AR burden caused by particulate air pollution.

Maternal PM2.5 exposure is associated with preterm birth and gestational diabetes mellitus, and mitochondrial OXPHOS dysfunction in cord blood

Maternal exposure to fine particulate matter (PM2.5) is associated with adverse pregnancy and neonatal health outcomes. To explore the mechanism, we performed mRNA sequencing of neonatal cord blood. From an ongoing prospective cohort, Air Pollution on Pregnancy Outcome (APPO) study, 454 pregnant women from six centers between January 2021 and June 2022 were recruited. Individual PM2.5 exposure was calculated using a time-weighted average model. In the APPO study, age-matched cord blood samples from the High PM2.5 (˃15 ug/m3; n = 10) and Low PM2.5 (≤ 15 ug/m3; n = 30) groups were randomly selected for mRNA sequencing. After selecting genes with differential expression in the two groups (p-value < 0.05 and log2 fold change > 1.5), pathway enrichment analysis was performed, and the mitochondrial pathway was analyzed using MitoCarta3.0. The risk of preterm birth (PTB) increased with every 5 µg/m3 increase of PM2.5 in the second trimester (odds ratio 1.391, p = 0.019) after adjusting for confounding variables. The risk of gestational diabetes mellitus (GDM) increased in the second (odds ratio 1.238, p = 0.041) and third trimester (odds ratio 1.290, p = 0.029), and entire pregnancy (odds ratio 1.295, p = 0.029). The mRNA-sequencing of cord blood showed that genes related to mitochondrial activity (FAM210B, KRT1, FOXO4, TRIM58, and FBXO7) and PTB-related genes (ADIPOR1, YBX1, OPTN, NFkB1, HBG2) were upregulated in the High PM2.5 group. In addition, exposure to high PM2.5 affected mitochondrial oxidative phosphorylation (OXPHOS) and proteins in the electron transport chain, a subunit of OXPHOS. These results suggest that exposure to high PM2.5 during pregnancy may increase the risk of PTB and GDM, and dysregulate PTB-related genes. Alterations in mitochondrial OXPHOS by high PM2.5 exposure may occur not only in preterm infants but also in normal newborns. Further studies with larger sample sizes are required.