UNASSIGNED: Socioeconomically disadvantaged subpopulations are more vulnerable to fine particulate matter (PM2.5) exposure. However, as prior studies focused on individual-level socioeconomic characteristics, how contextual deprivation modifies the association of PM2.5 exposure with cardiovascular health remains unclear.
UNASSIGNED: To assess disparities in PM2.5 exposure association with cardiovascular disease among subpopulations defined by different socioeconomic characteristics.
UNASSIGNED: This cohort study used longitudinal data on participants with electronic health records (EHRs) from the All of Us Research Program between calendar years 2016 and 2022. Statistical analysis was performed from September 25, 2023, through February 23, 2024.
UNASSIGNED: Satellite-derived 5-year mean PM2.5 exposure at the 3-digit zip code level according to participants\' residential address.
UNASSIGNED: Incident myocardial infarction (MI) and stroke were obtained from the EHRs. Stratified Cox proportional hazards regression models were used to estimate the hazard ratio (HR) between PM2.5 exposure and incident MI or stroke. We evaluated subpopulations defined by 3 socioeconomic characteristics: contextual deprivation (less deprived, more deprived), annual household income (≥$50 000, <$50 000), and race and ethnicity (non-Hispanic Black, non-Hispanic White). We calculated the ratio of HRs (RHR) to quantify disparities between these subpopulations.
UNASSIGNED: A total of 210 554 participants were analyzed (40% age >60 years; 59.4% female; 16.7% Hispanic, 19.4% Non-Hispanic Black, 56.1% Non-Hispanic White, 7.9% other [American Indian, Asian, more than 1 race and ethnicity]), among whom 954 MI and 1407 stroke cases were identified. Higher PM2.5 levels were associated with higher MI and stroke risks. However, disadvantaged groups (more deprived, income <$50 000 per year, Black race) were more vulnerable to high PM2.5 levels. The disparities were most pronounced between groups defined by contextual deprivation. For instance, increasing PM2.5 from 6 to 10 μg/m3, the HR for stroke was 1.13 (95% CI, 0.85-1.51) in the less-deprived vs 2.57 (95% CI, 2.06-3.21) in the more-deprived cohort; 1.46 (95% CI, 1.07-2.01) in the $50 000 or more per year vs 2.27 (95% CI, 1.73-2.97) in the under $50 000 per year cohort; and 1.70 (95% CI, 1.35-2.16) in White individuals vs 2.76 (95% CI, 1.89-4.02) in Black individuals. The RHR was highest for contextual deprivation (2.27; 95% CI, 1.59-3.24), compared with income (1.55; 95% CI, 1.05-2.29) and race and ethnicity (1.62; 95% CI, 1.02-2.58).
UNASSIGNED: In this cohort study, while individual race and ethnicity and income remained crucial in the adverse association of PM2.5 with cardiovascular risks, contextual deprivation was a more robust socioeconomic characteristic modifying the association of PM2.5 exposure.

UNASSIGNED: Acute respiratory infection is an infectious illness caused by acute viral or bacterial infection. According to a 2018 WHO report, exposures to indoor and ambient air environmental pollution were contributing factors to a higher risk of respiratory problems following 7 million deaths of children under five globally. Housing conditions such as wall material, roof type, kitchen location, sanitation condition, and cooking fuel type are household-level predictors of acute respiratory disease among children under five years of age.
UNASSIGNED: This research used EDHS-2016 secondary data, which are nationally representative. The data collection period was from January 18, 2016, to June 27, 2016. Among the 16,650 total surveys, 10,006 households that had children below 5 years of age. The outcome variable for this study was acute respiratory infection symptoms. Analyses were performed using STATA Version 17.1. The data were weighted before performing analysis to reinstate the representativeness of the sample. In the bivariable analysis, a p value <0.2 was used to screen for multivariable. Multicollinearity was checked using the variance inflation factor. Then, a multilevel multivariable regression model was used in this study for the analysis of acute respiratory infection symptoms and possible predictor variables. Variables with a p value <0.05 in multivariable regression analysis were considered statistically significant predictors.
UNASSIGNED: Most (95.00%) households commonly used solid fuel for cooking, and household main construction materials: 81.44 and 91.03% of floors and walls of households were constructed with unprocessed natural materials, respectively. The prevalence of acute respiratory infection symptoms among children under five years of age was 7.955% (7.397, 8.551%). The findings indicated that acute respiratory infection symptoms among children under five years of age were significantly linked with the age of the children, diarrhea status, residence, region, fuel type, stool disposal, wall material, and floor material.
UNASSIGNED: Interventions should target modifiable factors such as proper stool disposal of the youngest child, informing the health effects of poor housing conditions such as improving wall and floor construction material to reduce acute respiratory infection symptoms among children under five years of age.

The phthalic acid esters (PAEs) are one class of the most abundant and frequently studied pseudo-persistent organic pollutants. Noninvasive urine is an effective substrate for evaluating PAE exposure, but repeated sampling is needed to overcome this bias. This adds much work to on-site collection and the cost of detection increases exponentially. Therefore, the aim of this study was to conduct a scope review to describe the detection methods and validity of the use of other noninvasive matrices, such as nails and hair, for assessing long-term exposure to PAEs. The PubMed, Web of Science and China National Knowledge Infrastructure (CNKI), electronic databases were searched from 1 January 2000 to 3 April 2024, and 12 studies were included. Nine and three studies used hair and nails, respectively, as noninvasive matrices for detecting PAE exposure. Five articles compared the results of nail or hair and urine tests for validity of the assessment of PAE exposure. The preprocessing and detection methods for these noninvasive samples are also described. The results of this review suggest that, compared with nails, hair may be more suitable as a noninvasive alternative matrix for assessing long-term exposure to PAEs. However, sample handling procedures such as the extraction and purification of compounds from hair are not uniform in various studies; therefore, further exploration and optimization of this process, and additional research evidence to evaluate its effectiveness, are needed to provide a scientific basis for the promotion and application of hair detection methods for assessing long-term PAE exposure levels.

Air pollution has long been a significant environmental health issue. Previous studies have employed diverse methodologies to investigate the impacts of air pollution on public health, yet few have thoroughly examined its spatiotemporal heterogeneity. Based on this, this study investigated the spatiotemporal heterogeneity of the impacts of air pollution on public health in 31 provinces in China from 2013 to 2020 based on the theoretical framework of multifactorial health decision-making and combined with the spatial durbin model and the geographically and temporally weighted regression model. The findings indicate that: (1) Air pollution and public health as measured by the incidence of respiratory diseases (IRD) in China exhibit significant spatial positive correlation and local spatial aggregation. (2) Air pollution demonstrates noteworthy spatial spillover effects. After controlling for economic development and living environment factors, including disposable income, population density, and urbanization rate, the direct and indirect spatial impacts of air pollution on IRD are measured at 3.552 and 2.848, correspondingly. (3) China\'s IRD is primarily influenced by various factors such as air pollution, economic development, living conditions, and healthcare, and the degree of its influence demonstrates an uneven spatiotemporal distribution trend. The findings of this study hold considerable practical significance for mitigating air pollution and safeguarding public health.

Systemic sclerosis (SSc) is characterised by a heterogeneous clinical expression probably reflecting the different genetic background of each patient. Progress has been made in the definition of the principal pathogenetic events of the disease that can be summarised in endothelial damage and dysfunction, inflammation with activation of immune system and fibrosis. The aetiology of the disease still remains to be clarified and probably the first events are attributable to the repeated action of environmental stimuli in genetically predisposed subjects.The aim of the present manuscript is to review the most recent and relevant data regarding the association of SSc with environmental factors.

UNASSIGNED: Mounting evidence suggests a correlation between heavy metals exposure and diabetes. Diabetic retinopathy (DR) is a prevalent and irreversible complication of diabetes that can result in blindness. However, studies focusing on the effects of exposure to heavy metals on DR remain scarce. Thus, this study aimed to investigate the potential correlation between heavy metals exposure and DR.
UNASSIGNED: A total of 1,146 diabetics from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were included in this study. Heavy metal levels were measured via urine testing. Weighted logistic regression, Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and restricted cubic spline (RCS) were utilized to investigate the potential relationships between exposure to 10 heavy metals and DR. Finally, subgroup analysis was conducted based on the glycemic control status.
UNASSIGNED: Among the 1,146 participants, 239 (20.86%) were diagnosed with DR. Those with DR had worse glycemic control and a higher prevalence of chronic kidney disease compared to those without DR. Moreover, both the WQS regression and BKMR models demonstrated a positive relationship between exposure to mixed heavy metals and the risk of DR. The results of weighted logistic regression revealed a positive correlation between cobalt (Co) and antimony (Sb) exposure and the risk of DR (OR = 1.489, 95%CI: 1.064-2.082, p = 0.021; OR = 1.475, 95% CI: 1.084-2.008, p = 0.014), while mercury (Hg) exposure was found to promote DR exclusively in the group with good glycemic control (OR = 1.509, 95% CI: 1.157-1.967, p = 0.003). These findings were corroborated by the results of the RCS analysis.
UNASSIGNED: Heavy metal exposure is associated with an increased risk of DR, especially Sb, Co, and Hg exposure. Nevertheless, well-designed prospective studies are warranted to validate these findings.

UNASSIGNED: Limited investigation is available on the correlation between environmental phenols\' exposure and estimated glomerular filtration rate (eGFR). Our target is established a robust and explainable machine learning (ML) model that associates environmental phenols\' exposure with eGFR.
UNASSIGNED: Our datasets for constructing the associations between environmental phenols\' and eGFR were collected from the National Health and Nutrition Examination Survey (NHANES, 2013-2016). Five ML models were contained and fine-tuned to eGFR regression by phenols\' exposure. Regression evaluation metrics were used to extract the limitation of the models. The most effective model was then utilized for regression, with interpretation of its features carried out using shapley additive explanations (SHAP) and the game theory python package to represent the model\'s regression capacity.
UNASSIGNED: The study identified the top-performing random forest (RF) regressor with a mean absolute error of 0.621 and a coefficient of determination of 0.998 among 3,371 participants. Six environmental phenols with eGFR in linear regression models revealed that the concentrations of triclosan (TCS) and bisphenol S (BPS) in urine were positively correlated with eGFR, and the correlation coefficients were β = 0.010 (p = 0.026) and β = 0.007 (p = 0.004) respectively. SHAP values indicate that BPS (1.38), bisphenol F (BPF) (0.97), 2,5-dichlorophenol (0.87), TCS (0.78), BP3 (0.60), bisphenol A (BPA) (0.59) and 2,4-dichlorophenol (0.47) in urinary contributed to the model.
UNASSIGNED: The RF model was efficient in identifying a correlation between phenols\' exposure and eGFR among United States NHANES 2013-2016 participants. The findings indicate that BPA, BPF, and BPS are inversely associated with eGFR.

Coal is a mixture of several chemicals, many of which have mutagenic and carcinogenic effects and are a key contributor to the global burden of mortality and disease. Previous studies suggest that coal is related to telomeric shortening in individuals occupationally exposed, however little is known about the effects of mining and burning coal on the telomeres of individuals living nearby. Therefore, the primary objective of this investigation was to assess the impact of proximity to coal power plants and coal mines on the genomic instability of individuals environmentally exposed, while also exploring potential associations with individual characteristics, oxidative stress, inflammatory responses, and the presence of inorganic elements. This study involved 80 men participants from three cities around a thermoelectric power plant and one city unexposed to coal and byproducts. DNA was extracted from peripheral blood samples obtained from each participant, and the telomeres length (TL) was assessed using quantitative real-time polymerase chain reaction (qPCR) methodology. No significant difference was observed between exposed individuals (6227 ± 2884 bp) when compared to the unexposed group (5638 ± 2452 bp). Nevertheless, TL decrease was associated with age and risk for cardiovascular disease; and longer TL was found to be linked with increased concentrations of silicon and phosphorus in blood samples. No correlations were observed between TL with comet assay (visual score), micronucleus test, oxidative stress, and inflammatory results. Additional research is required to ascertain the potential correlation between these changes and the onset of diseases and premature mortality.

暂无摘要。

OBJECTIVE: Experimental and acute exposure studies imply that manganese affects red blood cell production. Nevertheless, the association between environmental exposure and red blood cell distribution width (RDW) has yet to be explored. This research sought to assess the correlation between blood manganese levels and RDW within the general population of the United States.
METHODS: Employing weighted multiple linear regression models, data from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) were utilized to assess the correlation between manganese levels in the blood and RDW. Restricted cubic spline plots and two-piecewise linear regression models were also employed.
RESULTS: The analysis included a total of 15882 participants in which we determined an independent positive relationship between blood manganese levels and RDW among participants(β = 0.079, P<0.001). Moreover, we identified a J-shaped association between blood manganese levels and RDW in total participants (inflection point for blood manganese: 7.32 ug/L) and distinct subgroups following adjusted covariates. Women exhibited a more pronounced association, even after controlling for adjusted covariates.
CONCLUSIONS: We determined a J-shaped relationship between blood manganese levels and RDW with an inflection point at 7.32 ug/L for blood manganese. Nevertheless, fundamental research and large sample prospective studies are needed to determine the extent to which blood manganese levels correlate with RDW.