The potential effect of gestational exposure to phthalates on the lung function levels during childhood is unclear. Therefore, we examined this association at different ages (from 4 to 11 years) and over the whole childhood. Specifically, we measured 9 phthalate metabolites (MEP, MiBP, MnBP, MCMHP, MBzP, MEHHP, MEOHP, MECPP, MEHP) in the urine of 641 gestating women from the INMA study (Spain) and the forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁) and FEV₁/FVC in their offspring at ages 4, 7, 9 and 11. We used linear regression and mixed linear regression with a random intercept for subject to assess the association between phthalates and lung function at each study visit and for the overall childhood, respectively. We also assessed the phthalate metabolites mixture effect on lung function using a Weighted Quantile Sum (WQS) regression. We observed that the phthalate metabolites gestational levels were consistently associated with lower FVC and FEV₁ at all ages, both when assessed individually and jointly as a mixture, although most associations were not statistically significant. Of note, a 10% increase in MiBP was related to lower FVC (−0.02 (−0.04, 0)) and FEV₁ z-scores (−0.02 (−0.04, −0.01) at age 4. Similar significant reductions in FVC were observed at ages 4 and 7 associated with an increase in MEP and MnBP, respectively, and for FEV₁ at age 4 associated with an increase in MBzP. WQS regression consistently identified MBzP as an important contributor to the phthalate mixture effect. We can conclude that the gestational exposure to phthalates was associated with children's lower FVC and FEV₁, especially in early childhood, and in a statistically significant manner for MEP, MiBP, MBzP and MnBP. Given the ubiquity of phthalate exposure and its established endocrine disrupting effects in children, our findings support current regulations that limit phthalate exposure.

Non-optimum ambient temperature has been associated with a variety of health outcomes in the elderly population. However, few studies have examined its adverse effects on neurocognitive function. In this study, we explored the temperature-cognition association in elderly women. We investigated 777 elderly women from the German SALIA cohort during the 2007–2010 follow-up. Cognitive function was evaluated using the CERAD-Plus test battery. Modelled data on daily weather conditions were assigned to the residential addresses. The temperature-cognition association over lag 0–10 days was estimated using multivariable regression with distributed lag non-linear model. The daily mean temperature ranged between −6.7 and 26.0 °C during the study period for the 777 participants. We observed an inverse U-shaped association in elderly women, with the optimum temperature (15.3 °C) located at the 68th percentile of the temperature range. The average z-score of global cognitive function declined by −0.31 (95%CI: 0.73, 0.11) for extreme cold (the 2.5th percentile of temperature range) and −0.92 (95%CI: 1.50, −0.33) for extreme heat (the 97.5th percentile of temperature range), in comparison to the optimum temperature. Episodic memory was more sensitive to heat exposure, while semantic memory and executive function were the two cognitive domains sensitive to cold exposure. Individuals living in an urban area and those with a low educational level were particularly sensitive to extreme heat. In summary, non-optimum temperature was inversely associated with cognitive function in elderly women, with the effect size for heat exposure particularly substantial. The strength of association varied by cognitive domains and individual characteristics.

Pregnant women are widely exposed to organophosphate (OP) pesticides, which are potentially neurotoxicant for the developing fetus. We aimed to identify principal demographic and dietary predictors of OP pesticide exposure among 450 pregnant women participating in the New York University Children’s Health and Environment Study (enrolled 2016–19). Urinary concentrations of six dialkyl phosphate (DAP) metabolites (3 dimethyl (DM) metabolites and 3 diethyl (DE) metabolites) of OP pesticides were determined at three time points across pregnancy. At mid-gestation, the Diet History Questionnaire II was used to assess women’s dietary intake over the past year. Demographic characteristics were obtained using questionnaires and/or electronic health records. We used linear mixed models to evaluate the associations of demographic and food groups with DAP metabolite levels, and partial-linear single-index (PLSI) models to analyze the contribution proportions of food groups to DAP metabolite concentrations and the dose-response relationships between them. We observed that pregnant women in NYC had lower levels of OP pesticide metabolites than pregnant populations in Europe, Asia, and other regions in the U.S. Having lower pre-pregnancy body mass index and being Asian, employed, and single were associated with higher DAP metabolite concentrations. Fruit and grain intakes were associated with higher ∑DM, ∑DE, and ∑DAP levels. ∑DE concentrations increased 9.0% (95% confidence interval (CI) = 1.2%, 17.4%) per two-fold increase in dairy consumption, whereas ∑DE concentrations decreased 1.8% (95%CI = −3.1%, −0.4%) per two-fold increase in seafood consumption. The PLSI model indicated that among the food mixture, fruit and grains were the main food groups contributed to higher levels of ∑DAP, while meat contributed to lower levels of ∑DAP. The contribution proportions of fruit, grains, and meat were 18.7%, 17.9%, and 39.3%, respectively. Our results suggest that fruit, grains, and meat are major dietary components associated with OP pesticide exposure in urban pregnant women.

Pesticides used in agriculture are some of the most common pollutants in the world. This study aimed to investigate the effects of Organophosphorus Pesticides (OPPs) and Organochlorine Pesticides (OCPs) on the families of farmworkers in the southeast of Iran.In the present case-control study, 141 family members of farmworkers (as the case group) and 59 family members of non-farmworkers (as the controls) were recruited. Serum levels of OCPs such as α-HCH, β-HCH, γ-HCH, 2,4-DDE, 4,4-DDE, 2,4-DDT, and 4,4-DDT were determined. In addition, erythrocyte acetylcholinesterase (AChE) activity, malondialdehyde (MDA), total antioxidant capacity (TAC), protein carbonyl (PC), nitric oxide (NO) serum levels, arylesterase activity of paraoxonase 1 (PON-1), superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activity were determined in all participants. Furthermore, distance to farmlands, education, crops, type, and the number of consumed fruits were evaluated for each individual separately.The erythrocyte AChE activity and serum activities of GPx, SOD, and PON-1 and TAC levels were significantly decreased, whereas the concentration of MDA, PC, NO, and seven OCPs were significantly increased in the farmworkers’ families as compared to the controls. Spearman correlation and linear regression suggest that OCPs increase the oxidative stress in farmworkers’ family members. Moreover, distance, education, farming precedence, products, and ventilation had significant effects on the OCP levels and increased the odds ratio of OCP levels in farmworkers’ families.With regards to the data obtained in this study, it was revealed that OCPs as illegal pesticides and OPPs were higher than expected in the farmworkers’ family members. Furthermore, exposure to OCPs and OPPs, apart from the other effects on the body, leads to oxidative stress (OS) that may cause serious diseases in the exposed populations.

Urban environments are characterized by multiple exposures that may influence body mass index (BMI) growth in early life. Previous studies are few, with inconsistent results and no evaluation of simultaneous exposures. Thus, this study aimed to assess the associations between exposure to air pollution, green spaces and built environment characteristics, and BMI growth trajectories from 0 to 5 years. This longitudinal study used data from an electronic primary care health record database in Catalonia (Spain), including 79,992 children born between January 01, 2011 and December 31, 2012 in urban areas and followed until 5 years of age. Height and weight were measured frequently during childhood and BMI (kg/m²) was calculated. Urban exposures were estimated at census tract level and included: air pollution (nitrogen dioxide (NO₂), particulate matter <10 μm (PM₁₀) and <2.5 μm (PM₂.₅₎), green spaces (Normalized Difference Vegetation Index (NDVI) and % green space) and built environment (population density, street connectivity, land use mix, walkability index). Individual BMI trajectories were estimated using linear spline multilevel models with several knot points. In single exposure models, NO₂, PM₁₀, PM₂.₅, and population density were associated with small increases in BMI growth (e.g. β per IQR PM₁₀ increase = 0.023 kg/m², 95%CI: 0.013, 0.033), and NDVI, % of green spaces and land use mix with small reductions in BMI growth (e.g. β per IQR % green spaces increase = −0.015 kg/m², 95%CI: −0.026, −0.005). These associations were strongest during the first two months of life. In multiple exposure models, most associations were attenuated, with only those for PM₁₀ and land use mix remaining statistically significant. This large longitudinal study suggests that early life exposure to air pollution, green space and built environment characteristics may be associated with small changes in BMI growth trajectories during the first years of life, and that it is important to account for multiple exposures in urban settings.

Kitchen emissions are mixed indoor air pollutants with adverse health effects, but the large-scale assessment is limited by costly equipment and survey methods. This study aimed to discuss the application of backpropagation (BP) neural network models in the assessment of kitchen emissions based on the exposure marker. A total of 3686 participants were recruited for the kitchen survey, and their sleep quality was measured by the Pittsburgh sleep quality index (PSQI). After excluding the confounders, 365 participants were selected to assess their urinary hydroxy polycyclic aromatic hydrocarbons (OH-PAHs) concentrations by ultra-high-performance liquid chromatography/tandem mass spectrometry. Two BP neural network models were then set up using the survey and detection data from the 365 participants and used to predict the total urinary OH-PAHs concentrations of all participants. The total urinary OH-PAHs and 1-hydroxy-naphthalene (1-OHNap) concentrations were significantly higher among the 365 participants with poor sleep quality (global PSQI score > 5; P < 0.05). Results from internal and external validation showed that our model has high credibility (model 2). Further, the participants with higher predicted total urinary OH-PAHs concentrations were associated with the global PSQI score of >5 (odds ratio (OR) = 1.284, 95% confidence interval (CI) = 1.082–1.525 for participants with predicted total urinary OH-PAHs concentrations of over 1.897 μg/mmol creatinine in model 1, and OR = 1.467, 95% CI = 1.240–1.735 for participants with predicted total urinary OH-PAHs concentrations of over 2.253 μg/mmol creatinine in model 2) after adjusting for the confounders. Findings suggest that the BP neural network model is suitable for assessing kitchen emissions, and the urinary OH-PAHs concentrations can be taken as the model outlay.

Mosaic loss of chromosome Y (mLOY) is the most common structure somatic event that related to increased risks of various diseases and mortality. Environmental pollution and genetic susceptibility were important contributors to mLOY. We aimed to explore the associations of polycyclic aromatic hydrocarbons (PAHs) exposure, as well as their joint effects with age, smoking, and genetic variants on peripheral blood mLOY. A total of 1005 male coke-oven workers were included in this study and their internal PAHs exposure levels of 10 urinary PAH metabolites and plasma benzo[a]pyrene-r-7,t-8,t-9,c-10-tetrahydotetrol-albumin (BPDE-Alb) adducts were measured. mLOY was defined by the median log R ratio(mLRR) of 1480 probes in male-specific region of chromosome-Y from genotyping array. We found that the PAHs exposure levels were linearly associated with mLOY. A 10-fold increase in urinary 1-hydroxynaphthalene (1-OHNa), 1-hydroxyphenanthrene (1-OHPh), 2-OHPh, 1-hydroxypyrene (1-OHP), ΣOH-PAHs, and plasma BPDE-Alb adducts could generate 0.0111, 0.0085, 0.0069, 0.0103, 0.0134, and 0.0152 decrease in mLRR-Y, respectively. Additionally, mLOY accelerated with age, smoking pack-years, and TCL1A rs1122138-C allele, and we observed the most severe mLOY among subjects carrying more than 3 of the above risk factors. Our results revealed the linear dose-effect associations between PAHs exposure and mLOY. Elder male smokers carrying rs1122138CC genotype were the most susceptible subpopulations to mLOY, who should be given protections for PAHs exposure induced chromosome-Y aberration.

Inflammation may play an important role in the association between exposure to polycyclic aromatic hydrocarbons (PAHs) and atherosclerotic cardiovascular disease (ASCVD) risk. However, the underlying mechanisms remain unclear.To investigate the association of PAHs exposure with ASCVD risk and effects of mean platelet volume (MPV) or Club cell secretory protein (CC16) on the association.A total of 2022 subjects (689 men and 1333 women) were drawn from the baseline Wuhan residents of the Wuhan-Zhuhai Cohort study. Data on demography and the physical examination were obtained from each participant. Urinary monohydroxy PAH metabolites (OH-PAHs) levels were measured by a gas chromatography-mass spectrometry. We estimated the association between each OH-PAHs and the 10-year ASCVD risk or coronary heart disease (CHD) risk using logistic regression models, and further analyze the mediating effect of MPV or plasma CC16 on the association by using structural equation modeling.The results of multiple logistic regression models showed that some OH-PAHs were positively associated with ASCVD risk but not CHD risk, including 2-hydroxyfluoren (β = 1.761; 95% CI: 1.194–2.597), 9-hydroxyfluoren (β = 1.470; 95% CI: 1.139–1.898), 1-hydroxyphenanthrene (β = 1.480; 95% CI: 1.008–2.175) and ΣOH-PAHs levels (β = 1.699; 95% CI: 1.151–2.507). The analysis of structural equation modeling shows that increased MPV and increased plasma CC16 levels contributed 13.6% and 15.1%, respectively, to the association between PAHs exposure and the 10-year ASCVD risk (p < 0.05).Exposure to PAHs may increase the risk of atherosclerosis, which was partially mediated by MPV or CC16.

This study was to investigate the levels of heavy metals in PM2.5 and in blood, the prevalence of respiratory symptoms and asthma, and the related factors to them. Lead and cadmium in both PM2.5 and blood were significant higher in Guiyu (exposed area) than Haojiang (reference area) (p < 0.05), however, no significant difference was found for chromium and manganese in PM2.5 and in blood. The prevalence of cough, phlegm, dyspnea, and wheeze of children was higher in Guiyu compared to Haojiang (p < 0.05). No significant difference was found for the prevalence of asthma in children between Guiyu and Haojiang. Living in Guiyu was positively associated with blood lead (B = 0.196, p < 0.001), blood cadmium (B = 0.148, p < 0.05) and cough (OR, 2.37; 95% CI, 1.30–4.32; p < 0.01). Blood lead>5 μg/dL was significantly associated with asthma (OR, 9.50; 95% CI, 1.16–77.49). Higher blood chromium and blood manganese were associated with more cough and wheeze, respectively. Our data suggest that living in e-waste exposed area may lead to increased levels of heavy metals, and accelerated prevalence of respiratory symptoms and asthma.

During pregnancy, human exposure to endogenous estrogens and xenoestrogens (such as lignans) may comprehensively impact the gestational maintenance and fetal growth. We measured the concentrations of 5 lignans and the profile of 13 estrogen metabolites (EMs) in the urine samples of 328 pregnant women and examined their associations with birth outcomes. We found significantly positive associations between gestational age and urinary matairesinol (MAT), enterodiol (END) and enterolactone (ENL), as well as 16-hydroxylation pathway EMs. There were consistently positive relationships between END and the 16-hydroxylation pathway EMs. The positive relationships of MAT, END and ENL exposures with the length of gestation were mainly in the low exposure strata of the levels of these EMs. This study reveals that MAT, END and ENL as well as 16-hydroxylation pathway EMs are associated with birth outcomes, and that there are interactive relationships between lignans and 16-hydroxylation pathway EMs with birth outcomes.