The relation between pesticides exposure and metabolic syndrome (MetS) has not been clearly identified. Performing a systematic review and meta-analysis, PubMed, Cochrane Library, Embase, and ScienceDirect were searched for studies reporting the risk of MetS following pesticides exposure and their contaminants. We included 12 studies for a total of 6789 participants, in which 1981 (29.1%) had a MetS. Overall exposure to pesticides and their contaminants increased the risk of MetS by 30% (95CI 22%–37%). Overall organochlorine increased the risk of MetS by 23% (14–32%), as well as for most types of organochlorines: hexachlorocyclohexane increased the risk by 53% (28–78%), hexachlorobenzene by 40% (0.01–80%), dichlorodiphenyldichloroethylene by 22% (9–34%), dichlorodiphenyltrichloroethane by 28% (5–50%), oxychlordane by 24% (1–47%), and transnonchlor by 35% (19–52%). Sensitivity analyses confirmed that overall exposure to pesticides and their contaminants increased the risk by 46% (35–56%) using crude data or by 19% (10–29%) using fully-adjusted model. The risk for overall pesticides and types of pesticides was also significant with crude data but only for hexachlorocyclohexane (36% risk increase, 17–55%) and transnonchlor (25% risk increase, 3–48%) with fully-adjusted models. Metaregressions demonstrated that hexachlorocyclohexane increased the risk of MetS in comparison to most other pesticides. The risk increased for more recent periods (Coefficient = 0.28, 95CI 0.20 to 0.37, by year). We demonstrated an inverse relationship with body mass index and male gender. In conclusion, pesticides exposure is a major risk factor for MetS. Besides organochlorine exposure, data are lacking for other types of pesticides. The risk increased with time, reflecting a probable increase of the use of pesticides worldwide. The inverse relationship with body mass index may signify a stockage of pesticides and contaminants in fat tissue.

Considerable investigations have been carried out to address the relationship between ambient fine particulate matter (PM₂.₅) and blood pressure (BP) in patients with hypertension. However, few studies have explored the influence of PM₂.₅ and its constituents on Trimethylamine N-oxide (TMAO), an established risk factor for hypertension and cardiovascular disease (CVD), particularly in severely air-polluted areas. To explore the potential impact of PM₂.₅ constituents on BP, plasma hormones, and TMAO, a panel study was conducted to investigate changes in BP, plasma hormones, and TMAO in response to ambient air pollution exposure in stage 1 hypertensive young adults. Linear mixed effect models were used to estimate the cumulative effects of fine particulate matters (PM₂.₅) and its constituents on BP, plasma hormones and TMAO. We found that one interquartile range (IQR) (35 μg/m³) increase in 0–1 day moving-average PM₂.₅ concentrations was statistically significantly associated with elevated systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) with estimated values of 0.13 (95% confidence interval (CI): 0.03 to 0.23) mmHg, 0.18 (95% CI: 0.08 to 0.28) mmHg, and 0.17 (95% CI: 0.09 to 0.26) mmHg, respectively. Hormone disturbance in the renin-angiotensin-aldosterone system was also associated with PM₂.₅ exposure. Elevated TMAO levels with an IQR increase for 0–4, 0–5, 0–6 moving-average concentrations of PM₂.₅ were found, and the increased values ranged from 26.28 (95% CI: 2.92 to 49.64) to 60.78 (31.95–89.61) ng/ml. More importantly, the PM₂.₅-bound metal constituents, such as manganese (Mn), titanium (Ti), and selenium (Se) showed robust associations with elevated BP and plasma TMAO levels. This study demonstrates associations between PM₂.₅ metal constituents and increased BP, changes in plasma hormones and TMAO, in stage 1 hypertensive young adults. Source control, aiming to reduce the emission of PM₂.₅-bound metals should be implemented to reduce the risk of hypertension and CVD.

Ambient particulate air pollution is a risk factor for cardiovascular and respiratory disease, yet the biological mechanisms underlying this association are not well understood. The current study aimed to investigate the mediation role of microRNAs on the association between personal PM₂.₅ exposure and blood pressure and lung function. One hundred and twenty adults (60 truck drivers and 60 office workers) aged 18–46 years were assessed on the June 15, 2008 and at follow-up (1- to 2-weeks later). MicroRNAs were extracted from the peripheral blood samples. Compared to truck drivers, there is a significant increase in FEF₂₅₋₇₅, FEV₁, and FEV₁/FVC and a decrease in PM₂.₅ in office workers (all p < 0.05). According to the Bonferroni corrected threshold p-value < 6.81 × 10⁻⁵ (0.05/734) used, personal PM₂.₅ data showed a significant positive association with miR-644 after the adjustment for age, BMI, smoking status, and habitual alcohol use. The mediation effect of miR-644 on the association between personal PM₂.₅ exposure and FEF₂₅₋₇₅ [B (95%CI) = −1.342 (−2.810, −0.113)], PEF [B (95%CI) = -1.793 (−3.926, −0.195)], and FEV₁/FVC [B (95%CI) = −0.119‰ (−0.224‰, −0.026‰)] was significant only for truck drivers after the adjustment for covariates. There were no similar associations with blood pressure. These results demonstrate microRNAs to potentially mediate association of PM₂.₅ with lung function. Subsequent studies are needed to further elucidate the potential mechanisms of action by which the mediation effect of microRNAs is achieved with this process.

Mutations are an important origin of antibiotic resistance in bacteria. While there is increasing evidence showing promoted resistance mutations by environmental stresses, no retrospective research has yet been conducted on this phenomenon and its mechanisms. Herein, we summarized the phenomena of stress-elevated resistance mutations in bacteria, generalized the regulatory mechanisms and discussed the environmental and human health implications. It is shown that both chemical pollutants, such as antibiotics and other pharmaceuticals, biocides, metals, nanoparticles and disinfection byproducts, and non-chemical stressors, such as ultraviolet radiation, electrical stimulation and starvation, are capable of elevating resistance mutations in bacteria. Notably, resistance mutations are more likely to occur under sublethal or subinhibitory levels of these stresses, suggesting a considerable environmental concern. Further, mechanisms for stress-induced mutations are summarized in several points, namely oxidative stress, SOS response, DNA replication and repair systems, RpoS regulon and biofilm formation, all of which are readily provoked by common environmental stresses. Given bacteria in the environment are confronted with a variety of unfavorable conditions, we propose that the stress-elevated resistance mutations are a universal phenomenon in the environment and represent a nonnegligible risk factor for ecosystems and human health. The present review identifies a need for taking into account the pollutants’ ability to elevate resistance mutations when assessing their environmental and human health risks and highlights the necessity of including resistance mutations as a target to prevent antibiotic resistance evolution.

Most amyotrophic lateral sclerosis (ALS) cases are sporadic (∼90%) and environmental exposures are implicated in their etiology. Large industrial facilities are permitted the airborne release of certain chemicals with hazardous properties and report the amounts to the US Environmental Protection Agency (EPA) as part of its Toxics Release Inventory (TRI) monitoring program. The objective of this project was to identify industrial chemicals released into the air that may be associated with ALS etiology. We geospatially estimated residential exposure to contaminants using a de-identified medical claims database, the SYMPHONY Integrated Dataverse®, with ∼26,000 nationally distributed ALS patients, and non-ALS controls matched for age and gender. We mapped TRI data on industrial releases of 523 airborne contaminants to estimate local residential exposure and used a dynamic categorization algorithm to solve the problem of zero-inflation in the dataset. In an independent validation study, we used residential histories to estimate exposure in each year prior to diagnosis. Air releases with positive associations in both the SYMPHONY analysis and the spatio-temporal validation study included styrene (false discovery rate (FDR) 5.4e-5), chromium (FDR 2.4e-4), nickel (FDR 1.6e-3), and dichloromethane (FDR 4.8e-4). Using a large de-identified healthcare claims dataset, we identified geospatial environmental contaminants associated with ALS. The analytic pipeline used may be applied to other diseases and identify novel targets for exposure mitigation. Our results support the future evaluation of these environmental chemicals as potential etiologic contributors to sporadic ALS risk.

Cadmium (Cd) is a toxic metal found in tobacco, air and food. Recent cross-sectional studies have suggested that Cd negatively impacts physical performance, but the prospective association is uncertain.We used data from 2548 older adults from the Seniors-ENRICA II cohort in Madrid, Spain. Whole blood Cd levels were measured at baseline using inductively coupled plasma-mass spectrometry. At baseline (2017) and follow-up (2019), overall physical function was evaluated using the physical component summary (PCS) of the SF 12-Item Health questionnaire, lower-extremity performance with the Short Physical Performance Battery (SPPB), muscle weakness with a hand dynamometer, and frailty with a Deficit Accumulation index. Mobility limitations and disability in instrumental activities of daily living (IADL) were ascertained with standardized questionnaires. Analyses were adjusted for relevant confounders, including tobacco smoke, number of cigarettes smoked per day and time since cessation in former smokers.In cross-sectional analyses, odds ratios (95% confidence interval) per two-fold increase in blood Cd were 1.16 (1.03; 1.31) for low PCS scores, 1.08 (0.97; 1.20) for impaired lower-extremity performance, 1.10 (0.98; 1.23) for low grip strength, 1.11 (1.02; 1.20) for mobility limitations, 1.16 (1.02; 1.31) for frailty, and 1.26 (1.08; 1.47) for IADL disability. In longitudinal analyses, corresponding hazard ratios were 1.25 (1.03; 1.51) for low PCS scores, 1.14 (1.03; 1.27) for impaired lower-extremity performance, 1.02 (0.92; 1.13) for low grip strength, 1.03 (0.91; 1.16) for mobility limitations, and 1.16 (1.00; 1.35) for frailty. All the associations where consistent when current smokers were excluded from the analyses.Our results support the role of Cd as a risk factor for physical function impairments in older adults.

Exposure to outdoor fine particulate matter (PM₂.₅)-bound polycyclic aromatic hydrocarbons (PAHs) is linked to reproductive dysfunction. However, it is unclear which component of PAHs is responsible for the adverse outcomes. In the Male Reproductive Health in Chongqing College Students (MARHCS) cohort study, we measured the exposure levels of 16 PAHs by collecting air PM₂.₅ particles and assessed eight PAHs metabolites from four parent PAHs, including naphthalene, fluorene, phenanthrene, and pyrene in urine samples. We investigated compositional profiles and variation characteristics for 16 PAHs in PM₂.₅, and then assessed the association between PAHs exposure and semen routine parameters, sperm chromatin structure, and serum hormone levels in 1452 samples. The results showed that naphthalene (95% CI: −17.989, −8.101), chrysene (95% CI: −64.894, −47.575), benzo[a]anthracene (95% CI: −63.227, −45.936) and all the high molecular weight (HMW) PAHs in PM₂.₅ were negatively associated with sperm normal morphology. Most of the low molecular weight (LMW) PAHs, such as acenaphthylene, fluorene, phenanthrene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, ∑LMW PAHs and ∑16 PAHs, were correlated with increased sperm motility (all corrected P < 0.05). On the other hand, sperm normal morphology was all negatively associated with urinary metabolites of ∑OH-Nap (95% CI: −5.611, −0.536), ∑OH-Phe (95% CI: −5.741, −0.957), and ∑OH-PAHs (95% CI: −5.274, −0.361). Urinary concentrations of ∑OH-PAHs were found to be negatively associated with sperm high DNA stainability (HDS) (P = 0.023), while ∑OH-Phe were negatively associated with serum testosterone level and sperm HDS (P = 0.004). Spearman correlation analysis showed that except for the urinary OH-Nap metabolites, the rest of the urinary OH-PAHs metabolites were negatively correlated with their parent PAHs in air. The results of this study suggest that various PAHs’ components may affect reproductive parameters differently. Inhalation of PAHs in air, especially HMW PAHs, may be a potential risk factor for male reproductive health.

Air pollution has been an important risk factor for female reproductive health. However, epidemiological evidence of ambient air pollution on the predictor for ovarian reserve (antral follicle count, AFC) is deficient. We aim to comprehensively evaluate the association of long-term exposure to ambient air pollution with AFC among women of reproductive age in Shanxi of north China. 600 women with spontaneous menstrual cycle, not using controlled ovarian stimulation, were enrolled in the retrospective study. Two distinct periods of antral follicle development were designed as exposure windows. Generalized linear model was employed to estimate the change of AFC associated with exposure of atmospheric pollutants (SO₂, NO₂, PM₁₀, PM₂.₅, CO and O₃). Stratification analysis based on age (<30, ≥30 years), university degree (yes, no), years of exposure (2013–2016, 2017–2019) and duration of infertility (<2, 2–5, >5 years) along with two pollutants model were employed to further illustrate the association. We found every 10 μg/m³ increase in SO₂ concentration level during the entire development stage of antral follicle was associated with a −0.01 change in AFC (95% confidence interval: −0.016, −0.002) adjusting for the confounders including age, BMI, parity and infertility diagnosis factors. The significant association of increased SO₂ level with decreased AFC was particularly observed during the early transition from primary follicle to preantral follicle stage by 10 μg/m³ increase in SO₂ exposure level with a −0.01 change (95% CI: -0.015, −0.002) in AFC. The negative association was pronounced among women aged ≥30 years old, and also significant in two pollutants model after adjusting the confounders. No significant associations between other air pollutants and AFC were observed. Our finding suggests that long-term exposure to air pollutant SO₂ is associated with lower AFC, raising our concern that atmospheric SO₂ exposure may have potential adverse impact on women ovarian reserve.

In this study, we evaluated the effects of geo-climatic parameters and other potential risk factors on the prevalence of chronic toxoplasmosis (CT) in pregnant women. We searched PubMed/MEDLINE, Web of Science, EMBASE, Scopus, and SciELO databases for seroepidemiological studies published between January 1988, and February 2021. We performed meta-analysis and meta-regression by using a random effect model to synthesize data. A total of 360 eligible datasets, including 1,289,605 pregnant women from 94 countries, were included in this study. The highest and lowest prevalence rates were estimated for latitudes of 0–10° (49.4%) and ≥50° (26.8%); and for the longitude of 80–90° (44.2%) and 110–120° (7.8%), respectively. Concerning climatic parameters, the highest and lowest prevalence rates were estimated in regions with the mean relative humidities of >80% (46.6%) and <40% (27.0); annual precipitation between 1000 and 1500 mm (39.2%) and 250–500 mm (26.8%); and mean annual temperature of 20–30 °C (36.5%), and <7 °C (24.9%), respectively. Meta-regression analyses indicated significant increasing trends in prevalence of CT in pregnant women with decrease in geographical latitude (coefficient, = −0.0035), and geographical longitudes (C = −0.0017). While it was positively associated (P < 0.01) with the mean environmental temperature (C = 0.0047), annual precipitation (C = 0.000064), and mean relative humidity (C = 0.002). Our results highlighted various effects of environmental parameters on the prevalence of CT. Therefore, different regions in the world may benefit from different types of interventions, and thus, novel preventive measures in a region should be developed according to local climate, agricultural activities and people culture.

Ambient fine particulate matter (PM₂.₅) has been ranked as the sixth leading risk factor globally for death and disability. Modelling methods based on having access to a limited number of monitor stations are required for capturing PM₂.₅ spatial and temporal continuous variations with a sufficient resolution. This study utilized a land use regression (LUR) model with machine learning to assess the spatial-temporal variability of PM₂.₅. Daily average PM₂.₅ data was collected from 73 fixed air quality monitoring stations that belonged to the Taiwan EPA on the main island of Taiwan. Nearly 280,000 observations from 2006 to 2016 were used for the analysis. Several datasets were collected to determine spatial predictor variables, including the EPA environmental resources dataset, a meteorological dataset, a land-use inventory, a landmark dataset, a digital road network map, a digital terrain model, MODIS Normalized Difference Vegetation Index (NDVI) database, and a power plant distribution dataset. First, conventional LUR and Hybrid Kriging-LUR were utilized to identify the important predictor variables. Then, deep neural network, random forest, and XGBoost algorithms were used to fit the prediction model based on the variables selected by the LUR models. Data splitting, 10-fold cross validation, external data verification, and seasonal-based and county-based validation methods were used to verify the robustness of the developed models. The results demonstrated that the proposed conventional LUR and Hybrid Kriging-LUR models captured 58% and 89% of PM₂.₅ variations, respectively. When XGBoost algorithm was incorporated, the explanatory power of the models increased to 73% and 94%, respectively. The Hybrid Kriging-LUR with XGBoost algorithm outperformed the other integrated methods. This study demonstrates the value of combining Hybrid Kriging-LUR model and an XGBoost algorithm for estimating the spatial-temporal variability of PM₂.₅ exposures.