Environmental Health最新文献

Background: Workers in artisanal and small-scale gold mining (ASGM) are exposed to metals and metalloids (referred to here as "metals") while mixing milled ore and elemental mercury to produce a gold-mercury amalgam. Although concentrations of metals in surface waters near ASGM activities have been described, little is known about concentrations of metals in the water-ore-mercury slurry with which workers have extensive dermal contact. We sought to characterize those concentrations.

Methods: Water samples (n = 76) were collected from amalgamation basins and milled ore washing ponds at 13 ASGM sites in Western Kenya. Samples were filtered and metals in the filtrate and metals retained on filters were analyzed for trace elements by inductively coupled plasma mass spectrometry (ICP-MS). Based upon the volume filtered and ICP-MS results, total metal concentrations in the original samples (pre-filtration), were calculated.

Results: Concentrations of metals in the amalgamation basins were high. The median concentrations of arsenic (240.23 µg/L), chromium (312.97 µg/L) and total mercury (3.52 µg/L) all exceeded Kenya's drinking water standard by several fold. Only 3.38% of arsenic, 0.28% of chromium, 40.51% of manganese, 0.22% of mercury and 0.01% of lead mass were in filtrate, with the remainder of the metal mass retained on filters.

Conclusions: Concentrations of arsenic, chromium, manganese and lead to which ASGM workers are exposed in the amalgamation process were approximately 5-100-fold higher concentrations than reported in prior studies of metals in surface waters near ASGM sites. These findings should be useful in assessments of exposure and health risk of the many thousands ASGM workers who amalgamate milled ore. The high concentrations of As, Mn and Hg put at risk the health of children who live near or work at ASGM sites. Policy measures and changes in occupational practices are urgently needed to reduce Hg use in ASGM and to protect individuals from metals present in milled ore.

Background: While several studies have found positive associations between exposure to oil spill cleanup-related chemicals and hypertension, no study has examined these associations longitudinally.

Objective: This study examined associations of oil spill-related benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H) exposures, individually and as both the aggregate sum (total) of BTEX-H and the BTEX-H mixture with incident hypertension among Gulf Long-term Follow-up (GuLF) Study participants.

Methods: Participants were 18,619 Deepwater Horizon (DWH) oil spill cleanup and response workers who enrolled in the GuLF Study (2011-2013). Cumulative exposures to each BTEX-H chemical were estimated with a job-exposure matrix linking detailed self-reported DWH participant work histories to exposure group estimates developed from air monitoring data. We defined incident hypertension as the first self-reported physician diagnosis of hypertension or high blood pressure after each worker's last date of cleanup work, as reported at enrollment or a follow-up interview (2013-2016 or 2017-2021). We used Cox proportional hazards regression to estimate hazard ratios (HR) and 95% confidence intervals (CI). We used quantile g-computation to estimate the joint effect of the BTEX-H mixture.

Results: Approximately 20% (n = 3,779) of workers reported an incident hypertension diagnosis. Exposures to the individual BTEX-H chemicals were highly correlated (r = 0.87-0.95). The HRs comparing the highest to lowest quartiles of individual BTEX-H and total BTEX-H exposures ranged from 1.27 to 1.35. We found evidence of exposure-response trends across increasing quartiles of exposure. Each one quartile increase in the BTEX-H mixture was positively associated with incident hypertension (HR: 1.10, 95% CI: 1.07, 1.14).

Discussion: Oil spill cleanup work-related BTEX-H exposures were associated with the risk of incident hypertension, extending prior findings of cross-sectional associations. Since BTEX-H exposures are common in occupational and population settings, these findings may have broader public health implications.

Mounting evidence links air pollution to dementia, the most prevalent cause of cognitive impairment in older people. Here we investigated individual and compound effects of particulate matters (PM₁₀, PM_2.5, PM_coarse, PM_abs) and nitric oxides (NO₂, NO) on risk of all-cause dementia, and its most common subtypes, Alzheimer's disease (AD) and vascular dementia (VAD), using data from UK Biobank. We addressed factors that hinder causal interpretation of associations previously shown in the literature and their translation into clear public health policies. Specifically: 1) spatial confounding by area-level covariates, 2) collinearity among and identification of the most relevant air pollutants, and 3) the time window for pollution exposure. Furthermore, we used chronic obstructive pulmonary disease (COPD) and frequency of oily fish intake in positive and negative control analyses. We found NO₂ to be the strongest risk factor for dementia, especially when considering participants with longer permanence at residential address as proxy for longer periods ([Formula: see text] years) of exposure (all-cause dementia hazard ratio HR=1.06, 1.02-1.11 per 9.86 [Formula: see text] interquartile range). There was stronger evidence of an effect on risk for AD than VAD. Positive control analysis did not provide any evidence against causality, although the analyses of spatial confounding and negative control analyses revealed the presence of some residual bias, thus warranting care in the interpretation of the results. Together, our results highlight that targeting air pollution, in particular NO₂ levels, could inform preventive public health policies for dementia.

Background: Inorganic lead exposure is a relevant occupational health issue in many industry sectors. European regulations set specific limits for time-weighted chemical airborne exposure and for biological exposure. While blood lead monitoring is the current standard, saliva sampling offers a less invasive alternative for biomonitoring. This study evaluates the potential of salivary lead assessment as an alternative biological matrix for occupational exposure monitoring.

Methods: An observational study was conducted at a lead-acid battery production facility in Central Italy from July to December 2024. Ninety-two male workers participated: 46 occupationally exposed and 46 non-exposed workers. Salivary lead levels were measured using ICP-MS in all participants. Blood lead levels and personal airborne lead assessments were performed in the exposed group. Socio-demographic data were collected through self-administered questionnaires.

Results: Mean salivary lead levels were significantly higher in exposed workers (23.3 ± 41.4 ng/swab) compared to non-exposed workers (0.3 ± 0.6 ng/swab, p < 0.001). A moderate positive correlation was found between environmental and salivary lead levels (ρ = 0.5587, p = 0.0003). No significant correlations were observed between blood and salivary lead levels or between environmental and blood lead levels. Occupational exposure and alcohol consumption were significant predictors of salivary lead levels.

Conclusions: Saliva appears to be a promising alternative matrix for recent lead exposure monitoring, showing better correlation with environmental exposure than blood lead levels. Further research is needed to establish reference values and standardize salivary lead biomonitoring protocols.

Background: Organophosphate esters (OPEs) are replacement flame retardants that have been implicated as metabolic disruptors and linked to birth size across a number of epidemiologic studies. Little is known about how OPEs impact maternal weight and body composition from pregnancy through the postpartum period.

Methods: We measured OPE metabolites in mid-pregnancy urine samples from participants in a pregnancy cohort study based in Rochester, NY, USA. We calculated total gestational weight gain (GWG) based on clinical records (n = 278) and additionally measured weight retention and body fat percentage through bioelectric impedance at 6 (n = 205) and 12 months postpartum (n = 167). We fitted adjusted linear and logistic regression models examining OPE concentrations in relation to the outcome measures and secondarily, fitted models stratified by earliest pregnancy BMI (< 25 kg/m² versus ≥ 25 kg/m²).

Results: In main models, most associations were null. Several highly prevalent OPEs such as bis(1,3-dichloro-2-propyl) phosphate (BDCPP; β: -1.02 lbs 95%CI: -2.00, -0.03) were associated with lower GWG, while detection of other, less prevalent OPEs like BMPP (bis(methylphenyl) phosphate; β: 2.86 lbs, 95%CI: -0.21, 5.94) was associated with greater GWG. In stratified analyses, associations tended to be stronger in women who started pregnancy overweight or obese, including findings that several OPEs were associated with higher fat percentage at 6 and 12 months postpartum. Few associations with postpartum weight retention were observed.

Discussion: Evidence linking gestational OPE exposure with GWG and body composition in the postpartum was limited and mixed, with the strongest associations observed for BDCPP. In light of the growing literature on OPEs' impacts on birth size and child outcomes, greater research into maternal metabolic disruption is warranted.

Purpose: To investigate the associations between residential proximity to nuclear power plants and ZIP code-level cancer incidence among Massachusetts residents.

Methods: We assessed proximity of Massachusetts ZIP codes to nuclear power plants using an inverse-distance weighted metric. We obtained cancer incidence data (2000-2018) from the Massachusetts Cancer Registry. We applied two approaches: (1) longitudinal Generalized Estimating Equation (GEE) Poisson regression to evaluate yearly incidences for all cancers combined, and (2) cross-sectional log-linear Poisson regression for site-specific cancers. We adjusted models for PM2.5, demographic, socioeconomic, environmental, and healthcare covariates, and stratified analyses by sex and four age groups (45-54, 55-64, 65-74, 75 +).

Results: Proximity to plants significantly increased cancer incidence, with risk declining by distance. At 2 km, females showed RRs of 1.52 (95% CI: 1.20-1.94) for ages 55-64, 2.00 (1.59-2.52) for 65-74, and 2.53 (1.98-3.22) for 75 + . Males showed RRs of 1.97 (1.57-2.48), 1.75 (1.42-2.16), and 1.63 (1.29-2.06), respectively. Cancer site-specific analyses showed significant associations for lung, prostate, breast, colorectal, bladder, melanoma, leukemia, thyroid, uterine, kidney, laryngeal, pancreatic, oral, esophageal, and Hodgkin lymphoma, with variation by sex and age. We estimated 10,815 female and 9,803 male cancer cases attributable to proximity, corresponding to attributable fractions of 4.1% (95% CI: 2.4-5.7%) and 3.5% (95% CI: 1.8-5.2%).

Conclusions: Residential proximity to nuclear plants in Massachusetts is associated with elevated cancer risks, particularly among older adults, underscoring the need for continued epidemiologic monitoring amid renewed interest in nuclear energy.

Background: Poor air quality due to smoke from distant wildfires is a growing risk for the Northeastern United States, a region largely unaffected by these events until recently. Despite this emerging threat, few studies have examined the effect of wildfire smoke on respiratory health in this region. We investigated the association between wildfire smoke exposure and pediatric asthma control in Vermont and upstate New York.

Methods: We extracted data from the electronic health records of youth aged 3-21 years diagnosed with asthma within a single regional healthcare system and included three clinical measures of asthma control: Test for Respiratory and Asthma Control in Kids (3-4 years), Asthma Therapy Assessment Questionnaire (5-21 years), and the National Heart, Lung and Blood Institute (NHLBI) asthma control guidelines (3-21 years). We first compared asthma control in the smoke-affected summer of 2023 to the largely unaffected summers of 2022 and 2024 using regression models, controlling for pollen exposure. We then obtained airborne particulate matter (PM_2.5) values within ZIP codes and used regression models to investigate the association between asthma control and PM_2.5 during the smoke-affected summer of 2023.

Results: The study sample included 1,217 encounters (mean age 9.1 ± 4.4 years, 57% male). Asthma control was significantly worse in the severely smoke-affected summer of 2023 versus 2022 for two of the three clinical measures but was not different between 2023 and 2024 for any of the clinical measures. Within summer 2023, there were no significant associations between ZIP code-level PM_2.5 and asthma control for any of the three clinical measures.

Conclusions: Wildfire smoke exposure in the Northeast was associated with decreased asthma control in this pediatric population, though not consistently across years and all clinical measures. As climate change drives longer and more intense wildfire seasons, continued monitoring is needed to understand the impact on pediatric respiratory health in this historically low-exposed region.

Background: Exposure to fine particles (PM_2.5) has been associated with adverse health outcomes, even at low exposure levels (< 10 µg/m³). Burden of disease assessments can quantify these associations; however, their sensitivity to methodological choices limits comparability between studies.

Methods: This study aimed to quantify the impact of methodological choices on disease burden attributable to low levels of ambient PM_2.5, using Norway as a case study. Key methodological choices included (i) population exposure data, (ii) concentration-response curves, and (iii) population health data. Data from national and international sources were applied, including the global burden of disease (GBD) study. Attributable mortality and disability-adjusted life years (DALY) were estimated using burden of disease methodology. Additionally, the impact of choices related to concentration-response curves was assessed for higher exposure levels, using a scenario where exposure distributions were shifted to mean exposures up to 30 µg/m³.

Results: Methodological choices related to the concentration-response curves had the largest impacts on the estimated attributable deaths, ranging from - 91% to 104% change relative to the reference estimate (1,448 deaths, 95% CI 502-1497). These choices had a smaller impact on higher exposure levels, varying from - 46% to 53%. The choice of exposure and population health data led to 40% differences in attributable death estimates. DALYs attributable to PM_2.5 were predominantly driven by years of life lost (YLL: 74%). The choice of relative risk (RR) for the concentration response curve caused around 30% variation in DALY estimates relative to the reference (11,730 DALYs; 5,980 - 16,790), with larger differences for ischemic heart disease (-44 to 79%).

Conclusion: Attributable burden estimates for PM_2.5 are highly sensitive to key methodological choices, particularly at low exposure levels. Consequently, transparent reporting of the methodological choices and data sources in PM_2.5 health risk assessments are required to improve comparability and facilitate interpretations of the burden estimates.