The inherent oxidation potential (OP) of atmospheric particulate matter has been shown to be an important metric in assessing the biological activity of inhaled particulate matter and is associated with the composition of PM₂.₅. The current study examined the chemical composition of 388 personal PM₂.₅ samples collected from students and guards living in urban and suburban areas of Beijing, and assessed the ability to predict OP from the calculated metrics of carcinogenic risk, represented by ELCR (excess lifetime cancer risk), non-carcinogenic risk represented by HI (hazard index), and the composition and sources of the particulate matter using multiple linear regression methods. The correlations between calculated ELCR and HI and the measured OP were 0.37 and 0.7, respectively. HI was a better predictor of OP than ELCR. The prediction models based on pollutants (Model_1) and pollution sources (Model_2) were constructed by multiple linear regression method, and Pearson correlation coefficients between the predicted results of Model_1 and Model_2 with the measured volume normalized OP are 0.81 and 0.80, showing good prediction ability. Previous investigations in Europe and North America have developed location-specific relationships between the chemical composition of particulate matter and OP using regression methods. We also examined the ability of relationships between OP and composition, sources, developed in Europe and North America, to predict the OP of particulate matter in Beijing from the composition and sources determined in Beijing. The relationships developed in Europe and North America provided good predictive ability in Beijing and it suggests that these relationships can be used to predict OP from the chemical composition measured in other regions of the world.

Individual-level studies with adjustment for important COVID-19 risk factors suggest positive associations of long-term air pollution exposure (particulate matter and nitrogen dioxide) with COVID-19 infection, hospitalisations and mortality. The evidence, however, remains limited and mechanisms unclear. We aimed to investigate these associations within UK Biobank, and to examine the role of underlying chronic disease as a potential mechanism. UK Biobank COVID-19 positive laboratory test results were ascertained via Public Health England and general practitioner record linkage, COVID-19 hospitalisations via Hospital Episode Statistics, and COVID-19 mortality via Office for National Statistics mortality records from March–December 2020. We used annual average outdoor air pollution modelled at 2010 residential addresses of UK Biobank participants who resided in England (n = 424,721). We obtained important COVID-19 risk factors from baseline UK Biobank questionnaire responses (2006–2010) and general practitioner record linkage. We used logistic regression models to assess associations of air pollution with COVID-19 outcomes, adjusted for relevant confounders, and conducted sensitivity analyses. We found positive associations of fine particulate matter (PM₂.₅) and nitrogen dioxide (NO₂) with COVID-19 positive test result after adjustment for confounders and COVID-19 risk factors, with odds ratios of 1.05 (95% confidence intervals (CI) = 1.02, 1.08), and 1.05 (95% CI = 1.01, 1.08), respectively. PM 2.5 and NO 2 were positively associated with COVID-19 hospitalisations and deaths in minimally adjusted models, but not in fully adjusted models. No associations for PM₁₀ were found. In analyses with additional adjustment for pre-existing chronic disease, effect estimates were not substantially attenuated, indicating that underlying chronic disease may not fully explain associations. We found some evidence that long-term exposure to PM₂.₅ and NO₂ was associated with a COVID-19 positive test result in UK Biobank, though not with COVID-19 hospitalisations or deaths.

Many cities across the world face the challenge of severe fine particulate matter (PM₂.₅) pollution. Among the many factors that affect PM₂.₅ pollution, there is an increasing interest in the impacts of urban structure. However, quantifying these impacts in China has been difficult due to differences of study area and scale in existing research, as well as limited sample sizes. Here, we conducted a continental study focusing on 301 prefectural cities in mainland China to investigate the effects of urban structure, including urban size and urban compactness, on PM₂.₅ concentrations. Based on PM₂.₅ raster and land cover data, we used quantile regression and a general multilinear model to estimate the effects and relative contributions of urban size and urban compactness on urban PM₂.₅ pollution, with explicit consideration for pollution level, urban size and geographical location. We found: (1) nationwide, the larger and more compact that cities were, the heavier the PM₂.₅ pollution tended to be. Additionally, this relationship became stronger with increasing levels of pollution. (2) In general, urban size played a more important role than urban form, and there were no significant interactive effects between the two metrics on urban PM₂.₅ concentrations at the national scale. (3) The impacts of urban size and form varied by city size and geographical location. The impacts of urban size were only significant for small or medium-large cities but not for large cities. Among large cities, only urban form had a significantly positive effect on urban PM₂.₅ concentrations. The further north and west that cities were, the more dependent PM₂.₅ pollution was on urban form, whereas the further south and east that cities were, the greater the impact of urban size. These results provide insights into how urban design and planning can be used to alleviate air pollution.

Emerging evidence witnesses the association of air pollution exposure with sleep disorders or the risk of obstructive sleep apnea (OSA); however, the results are not consistent. OSA patients with or without a low arousal threshold (LAT) have different pathology and therapeutic schemes. No study has evaluated the potential diverse effects of air pollution on the phenotypes of OSA. The current study aimed to evaluate the associations of short-term and long-term exposure to air pollution with sleep-disordered measures and OSA phenotypes. This cross-sectional study consisted of 4634 participants from a sleep center in Taipei from January 2015 to April 2019. The personal exposure to ambient PM₂.₅ and NO₂ was assessed by a spatial-temporal model. Overnight polysomnography was used to measure the sleep parameters. According to a developed clinical tool, we defined the low arousal threshold (LAT) and identified the OSA patients with or without LAT. We applied a generalized linear model and multinomial logistic regression model to estimate the change of sleep measures and risk of the OSA phenotypes, respectively, associated with an interquartile range (IQR) increment of personal pollution exposure after adjusting for the essential confounders. In the single-pollutant model, we observed the associations of NO₂ with sleep-disordered measures by decreasing the total sleep time, sleep efficiency, extending the time of wake after sleep onset, and the association of NO₂ with the increased risk of LAT OSA by around 15%. The two-pollutant model with both long-term and short-term exposures confirmed the most robust associations of long-term NO₂ exposure with sleep measures. An IQR increment of NO₂ averaged over the past year (6.0 ppb) decreased 3.32 min of total sleep time and 0.85% of sleep efficiency. Mitigating exposure to air pollution may improve sleep quality and reduce the risk of LAT OSA.

The fetus is prenatally exposed to a mixture of organochlorine pesticides (OCPs), mercury (Hg), docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and selenium (Se) through maternal seafood consumption in real-life scenario. Prenatal exposure to these contaminants and nutrients has been suggested to affect thyroid hormone (TH) status in newborns, but the potential relationships between them are unclear and the joint effects of the mixture are seldom analyzed. The aim of the study is to investigate the associations of prenatal exposure to a mixture of OCPs, Hg, DHA, EPA and Se with TH parameters in newborns. 228 mother-infant pairs in Shanghai, China were included. We measured 20 OCPs, total Hg, DHA, EPA and Se in cord blood samples as exposure variables. The total thyroxine (TT4), free thyroxine (FT4), total triiodothyronine (TT3), free triiodothyronine (FT3), and thyroid-stimulating hormone (TSH) levels and the FT3/FT4 ratio in cord serum were determined as outcomes. Using linear regression models, generalized additive models and Bayesian kernel machine regression, we found dose-response relationships of the mixture component with outcomes: among the contaminants, p,p'-DDE was the most important positive predictor of TT3, while HCB was predominantly positively associated with FT3 and the FT3/FT4 ratio, indicating different mechanisms underlying these relationships; among the nutrients, EPA was first found to be positively related to the FT3/FT4 ratio. Additionally, we found suggestive evidence of interactions between p,p'-DDE and HCB on both TT3 and FT3, and EPA by HCB interactions for TT3, FT3 and FT3/FT4 ratio. However, the overall effects of the mixture on thyroid hormone parameters were not significant. Our result suggests that prenatal exposure to p,p’-DDE, HCB and EPA as part of a mixture might affect thyroid function of newborns in independent and interactive ways. The potential biological mechanisms merit further investigation.

Carbonaceous aerosols pose significant climatic impact, however, their sources and respective contribution to light absorption vary and remain poorly understood. In this work, filter-based PM₂.₅ samples were collected in winter of 2021 at three urban sites in Yibin, a fast-growing city in the south of Sichuan Basin, China. The composition characteristics of PM₂.₅, light absorption and source of carbonaceous aerosol were analyzed. The city-wide average concentration of PM₂.₅ was 87.4 ± 31.0 μg/m³ in winter. Carbonaceous aerosol was the most abundant species, accounting for 42.5% of the total PM₂.₅. Source apportionment results showed that vehicular emission was the main source of PM₂.₅ during winter, contributing 34.6% to PM₂.₅. The light absorption of black carbon (BC) and brown carbon (BrC) were derived from a simplified two-component model. We apportioned the light absorption of carbonaceous aerosols to BC and BrC using the Least Squares Linear Regression with optimal angstrom absorption exponent of BC (AAEBC). The average absorption of BC and BrC at 405 nm were 51.6 ± 21.5 Mm⁻¹ and 17.7 ± 8.0 Mm⁻¹, respectively, with mean AAEBC = 0.82 ± 0.02. The contribution of BrC to the absorption of carbonaceous reached 26.1% at 405 nm. Based on the PM₂.₅ source apportionment and the mass absorption cross-section (MAC) value of BrC at 405 nm, vehicle emission was found to be the dominant source of BrC in winter, contributing up to 56.4%. Therefore, vehicle emissions mitigation should be the primary and an effective way to improve atmospheric visibility in this fast-developing city.

Vaccines are essential for children to defend against infection. Per- and polyfluoroalkyl substances (PFAS) are emerging contaminants with the characteristics of persistence and bioaccumulation. PFAS exposure can affect the function of the nervous, endocrine, and immune system of animals and humans. We aimed to conduct a systematic review and meta-analysis of the epidemiological studies investigating potential relationships between PFAS exposure and vaccine antibody levels, and assessed whether PFAS would affect vaccine response in healthy children. A literature search was conducted in PubMed, Web of Science, and Scopus databases up to February 2022. We chose studies that measured serum vaccines antibodies and PFAS concentrations of the participants. Essential information, including mean difference of percentage change, regression coefficient, odds ratio, Spearman correlation coefficient, and 95% confidence intervals, were extracted from the selected studies to conduct descriptive analysis and meta-analysis where appropriate. The qualities of these studies were evaluated as well. Finally, nine epidemiological studies about children met our inclusion criteria. A high degree of heterogeneity is observed in terms of breastfeeding time, confounder control, and detection method. Exposure to perfluorooctanoic acid and perfluorohexane sulfonic acid is negatively associated with tetanus antibody level in children without heterogeneity by Cochran's Q test (p = 0.26; p = 0.55), and exposure to perfluorohexane sulfonate is negatively associated with tetanus antibody level but with heterogeneity (p = 0.04). This comprehensive review suggests that PFAS can have adverse health effects on children by hindering the production of vaccine antibodies. There are some consistent and negative associations between children exposure to certain PFAS and tetanus antibody level. The association of the other four vaccines (measles, rubella, mumps, and influenza) with PFAS remains uncertain, because very few studies are available. Further studies are needed to validate the possible associations.

We aimed to explore the effects of mixtures of lead and various metals on blood pressure (BP) and the odds of pre-hypertension (systolic blood pressure (SBP) 120–139 mmHg, and/or diastolic blood pressure (DBP) 80–89 mmHg) and hypertension (SBP/DBP ≥140/90 mmHg) among Chinese adults in a cross-sectional study. This study included 11,037 adults aged 18 years or older from the 2017–2018 China National Human Biomonitoring. Average BP and 13 metals (lead, antimony, arsenic, cadmium, mercury, thallium, chromium, cobalt, molybdenum, manganese, nickel, selenium, and tin) in blood and urine were measured and lifestyle and demographic data were collected. Weighted multiple linear regressions were used to estimate associations of metals with BP in both single and multiple metal models. Weighted quantile sum (WQS) regression was performed to assess the relationship between metal mixture levels and BP. In the single metal model, after adjusting for potential confounding factors, the blood lead levels in the highest quartile were associated with the greater odds of both pre-hypertension (odds ratio (OR): 1.56, 95% CI: 1.22–1.99) and hypertension (OR:1.75, 95% CI: 1.28–2.40) when compared with the lowest quartile. We also found that blood arsenic levels were associated with increased odds of pre-hypertension (OR:1.31, 95% CI:1.00–1.74), while urinary molybdenum levels were associated with lower odds of hypertension (OR:0.68, 95% CI:0.50–0.93). No significant associations were found for the other 10 metals. WQS regression analysis showed that metal mixture levels in blood were significantly associated with higher SBP (β = 1.56, P < 0.05) and DBP (β = 1.56, P < 0.05), with the largest contributor being lead (49.9% and 66.8%, respectively). The finding suggests that exposure to mixtures of metals as measured in blood were positively associated with BP, and that lead exposure may play a critical role in hypertension development.

Previous studies have indicated that maternal exposure to particles with aerodynamic diameter <2.5 μm (PM₂.₅) is associated with adverse birth outcomes. However, the critical exposure windows remain inconsistent. A retrospective cohort study was conducted in Huai River Basin, Henan, China during 2013–2018. Daily PM₂.₅ concentration was collected using Chinese Air Quality Reanalysis datasets. We calculated exposures for each participant based on the residential address during pregnancy. Binary logistic regression was used to examine the trimester-specific association of PM₂.₅ exposure with preterm birth (PTB), low birth weight (LBW) and term LBW (tLBW), and we further estimated monthly and weekly association using distributed lag models. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for each 10 μg/m³ increase in PM₂.₅ exposure. Stratified analyses were performed by maternal age, infant gender, parity, and socioeconomic status (SES). In total, 196,780 eligible births were identified, including 4257 (2.2%) PTBs, 3483 (1.8%) LBWs and 1770 (0.9%) tLBWs. Maternal PM₂.₅ exposure during the second trimester were associated with the risk of PTB and LBW. At the monthly level, the PTB and LBW risks were associated with PM₂.₅ exposure mainly in the 4th -6th month. By estimating the weekly-specific association, we observed that critical exposure windows of PM₂.₅ exposure and PTB were in the 18th- 27th gestational weeks. Stronger associations were found in younger, multiparous mothers and those with a female baby and in low SES. In conclusion, the results indicate that maternal PM₂.₅ exposure during the second trimester was associated with PTB and LBW. Younger, multiparous mothers and those with female babies and in low SES were susceptible.

Adipokines, cytokines secreted by adipose tissue, may contribute to obesity-related metabolic disease. The role of environmental phenols and parabens in racial difference in metabolic disease burden has been suggested, but there is limited evidence. We examined the cross-sectional associations of urinary phenols and parabens with adipokines and effect modification by race. Urinary concentrations of 6 phenols (bisphenol-A, bisphenol-F, 2,4-diclorophenol, 2,5-diclorophenol, triclosan, benzophenone-3) and 4 parabens (methyl-paraben, ethyl-paraben, propyl-paraben, butyl-paraben) were measured in 2002–2003 among 1200 women (mean age = 52.6) enrolled in the Study of Women's Health Across the Nation Multi-Pollutant Study. Serum adipokines included adiponectin, high molecular weight (HMW)-adiponectin, leptin, soluble leptin receptor (sOB-R). Linear regression models were used to estimate the adjusted percentage change in adipokines per inter-quantile range (IQR) increase in standardized and log-transformed levels of individual urinary phenols and parabens. Bayesian kernel machine regression (BKMR) was used to evaluate the joint effect of urinary phenols and parabens as mixtures. Participants included white (52.5%), black (19.3%), and Asian (28.1%) women. Urinary 2,4-dichlorophenol was associated with 6.02% (95% CI: 1.20%, 10.83%) higher HMW-adiponectin and urinary bisphenol-F was associated with 2.60% (0.48%, 4.71%) higher sOB-R. Urinary methyl-paraben was associated with lower leptin in all women but this association differed by race: 8.58% (−13.99%, −3.18%) lower leptin in white women but 11.68% (3.52%, 19.84%) higher leptin in black women (P interaction = 0.001). No significant associations were observed in Asian women. Additionally, we observed a significant positive overall effect of urinary phenols and parabens mixtures in relation to leptin levels in black, but not in white or Asian women. Urinary bisphenol-F, 2,4-dichlorophenol and methyl-paraben may be associated with favorable profiles of adipokines, but methyl-paraben, widely used in hair and personal care products, was associated with unfavorable leptin levels in black women. Future studies are needed to confirm this racial difference.