Environmental Health Perspectives最新文献

Background: Large prospective cohort studies have been fruitful for identifying exposure-disease associations. In a cohort where biospecimens (e.g., blood, urine) were collected at enrollment, analysts can exploit a case-cohort approach: Biospecimens from a random sample of cohort participants, called the "subcohort," plus a sample of incident cases that were not part of the subcohort are assayed. Reusing subcohort data for multiple disease outcomes can reduce costs and conserve specimen archives. Pooling biospecimen samples before assay could both save money and reduce depletion of the archive but has not been studied for cohort studies.

Objectives: We develop and evaluate a biospecimen pooling strategy for case-cohort analyses that relate an exposure to risk of a rare disease.

Methods: Our approach involves constructing pooling sets for cases not in the subcohort after grouping them according to time of diagnosis (e.g., age). In contrast, members of the subcohort are grouped by age at entry before constructing pooling sets. The analyst then fits a logistic regression model that jointly stratifies by age at risk and pooling set size and adjusts for confounders. We used simulations (288 sampling scenarios with 1,000 simulated datasets each) to evaluate the performance of this approach for several sizes of pooling sets and illustrated its application to environmental epidemiologic studies by reanalyzing Sister Study data.

Results: Parameter estimates were nearly unbiased, and 95% confidence intervals constructed using a bootstrap estimate of the standard error performed well. In statistical tests also based on the bootstrap standard error, pooling up to 8 specimens per pool caused only modest loss of power. Assigning more cohort members to the subcohort and commensurately increasing the number of specimens per pool improved power and precision substantially while reducing the number of assays.

Discussion: When using case-cohort analysis to study disease outcomes in relation to exposures assessed using biospecimens in a cohort study, epidemiologists should consider biospecimen pooling as a way to improve statistical power, conserve irreplaceable archives, and save money. https://doi.org/10.1289/EHP14476.

Background: Endocrine-disrupting chemicals (EDCs) are exogenous chemical compounds that interfere with the normal function of the endocrine system and are linked to direct and inherited adverse effects in both humans and wildlife. Legacy EDCs such as polychlorinated biphenyls (PCBs) are no longer used yet remain detectable in biological specimens around the world; concurrently, we are exposed to newer EDCs like the fungicide vinclozolin (VIN). This combination of individuals' direct environmental chemical exposures and any heritable changes caused by their ancestors' chemical exposures leads to a layered pattern of both direct and ancestrally inherited exposures that might have cumulative effects over generations.

Objectives: We assessed consequences of both direct and ancestral exposure to EDCs over six generations, examining anxiety-like behaviors in maternal and paternal lines of female rats. We used the "two hits, three generations apart" multigenerational exposure model to explore how two distinct EDCs-the weakly estrogenic PCB mixture Aroclor 1221 (A1221) and the antiandrogenic VIN-interact on behavior across generations. We also explored serum hormones as a potential mechanism.

Methods: Rats were prenatally exposed to A1221, VIN, or vehicle (DMSO) in the F1 generation, and a second exposure (same or different) was administered to the F4 generation. Anxiety-like behavior was measured in the Open Field test, Light:Dark box, and Elevated Plus Maze in the F1, F3, F4, and F6 generations. Serum concentrations of estradiol and corticosterone were analyzed.

Results: Behavioral effects were not detectable in the F1 generation but emerged and became more robust across generations. Rats with ancestral VIN exposure demonstrated less anxiety-like behavior in the F3 paternal line in comparison with controls. Rats exposed to ancestral then prenatal A1221/VIN and VIN/A1221 had more anxiety-like behavior in the F4 maternal line, and those with two ancestral hits of VIN/VIN had more anxiety in the F6 paternal line, in comparison with controls.

Discussion: Our findings suggest that anxiety-like behavioral phenotypes can manifest in rats following germline exposure to EDCs and that subsequent exposures across generations can intensify these effects in a lineage-dependent manner. https://doi.org/10.1289/EHP15621.

Higher ${\mathrm{NO}}_2$ exposure was associated with increased risk of ovarian cancer. Results hinted that age at exposure might matter.

Background: The Global Calculator is an open-source model of the world's energy, land, and food systems. It is a pioneering online calculator to project the impact of interventions to mitigate climate change on global temperature. A few studies have been conducted to evaluate the health co-benefits of climate change mitigation, though they are still fragmentary.

Objectives: Our objectives are to identify which sectors could yield the greatest results in terms of climate change mitigation and suggest whether existing evidence could be used to weight mitigation actions based on their ancillary impacts on human health or health co-benefits.

Methods: Using the International Energy Agency (IEA) 4DS scenario as a referent (i.e., the "4-degree Celsius increase scenario"), we simulated changes in different policy "levers" (encompassing 43 potential technological and behavioral interventions, grouped by 14 sectors) and assessed the relative importance of each lever in terms of changes in annual greenhouse gas emissions in 2050 and cumulative emissions by 2100. In addition, we examined existing estimates for the health co-benefits associated with different interventions, using evidence from the Lancet Pathfinder and four other tools.

Discussion: Our simulations suggest that-after accounting for demographic change-transition from fossil fuels to renewables and changes in agriculture, forestry, land use, and food production are key sectors for climate change mitigation. The role of interventions in other sectors, like carbon capture and storage (CCS) or nuclear power, is more modest. Our work also identifies mitigation actions that are likely to have large health co-benefits, including shifts to renewable energy and changes in land use as well as dietary and travel behaviors. In conclusion, some of the sectors/interventions which have been at the center of policy debate (e.g., CCS or nuclear power) are likely to be far less important than changes in areas such as dietary habits or forestry practices by 2050. https://doi.org/10.1289/EHP14906.

Racial and ethnic differences in exposures to phthalates and their replacements through use of soaps, lotions, etc. appear to begin in childhood.

Background: Benzene is classified as carcinogenic to humans based on evidence that benzene causes acute myeloid leukemia. However, there is limited evidence that benzene causes lung cancer.

Objectives: We performed a systematic review, quality assessment, and meta-analysis of published cohort and case-control studies on the association between occupational benzene exposure and lung cancer risk.

Methods: We reviewed the relevant human epidemiological studies from PubMed and Embase databases to 19 August 2024. Data extraction included study characteristics, effect estimates, and exposure assessment details. Two investigators independently evaluated study quality using the Newcastle-Ottawa scale (NOS) framework and exposure assessment quality based on a priori criteria. Six risk of bias (ROB) domains were constructed from the NOS criteria to identify and quantify possible biases and their impacts on parameter estimates. Meta-analysis relative risk (pooled RR) and associated confidence intervals were calculated using random-effects models, and a flexible exposure-response meta-regression was fitted to assess the shape of the association. Subgroup analyses were conducted to explore the consistency of results.

Results: Of 252 articles identified, 13 studies covering 366,975 participants (17,030 lung cancer cases) were included in our analysis. The meta-analysis of ever occupational benzene exposure showed an elevated risk of lung cancer (pooled $\text{RR}=1.14$; 95% CI: 1.03, 1.27; $I²=72$). Subgroup analyses revealed that larger pooled RRs in studies based on highly exposed groups had higher overall quality and better exposure assessments and included both males and females (as opposed to only males). A positive linear trend was observed in the exposure-response meta-analysis.

Discussion: Our meta-analysis supports an association between occupational benzene exposure and an increased risk of lung cancer. https://doi.org/10.1289/EHP15086.

Background: While water, sanitation, and hygiene (WASH) interventions can reduce diarrheal disease, many large-scale trials have not found the expected health gains for young children in low-resource settings. Evidence-based guidance is needed to improve interventions and remove barriers to diarrheal disease reduction.

Objectives: We aimed to estimate how sensitive WASH intervention effectiveness was to underlying contextual and intervention factors in the WASH Benefits (WASH-B) Bangladesh cluster-randomized controlled trial.

Methods: The investigators measured diarrheal prevalence in children enrolled in the WASH-B trial at three time points approximately 1 year apart ($n=\mathrm{17,187}$ observations). We developed a susceptible-infectious-susceptible model with transmission across multiple environmental pathways and evaluated each of four interventions [water (W), sanitation (S), hygiene (H), and nutrition (N) applied individually and in combination], compliance with interventions, and the impact of individuals not enrolled in the study. Leveraging a set of mechanistic parameter combinations fit to the WASH-B Bangladesh trial using a hybrid Bayesian sampling-importance resampling and maximum-likelihood estimation approach, we simulated trial outcomes under counterfactual scenarios to estimate how changes in six WASH factors (preexisting WASH conditions, disease transmission potential, intervention compliance, intervenable fraction of transmission, intervention efficacy, and community coverage) impacted intervention effectiveness.

Results: Increasing community coverage had the greatest impact on intervention effectiveness (e.g., median increases in effectiveness of 34.0 and 45.5 percentage points in the WSH and WSHN intervention arms when increasing coverage to 20%). The effect of community coverage on effectiveness depended on how much transmission was along pathways not modified by the interventions. Intervention effectiveness was reduced by lower levels of preexisting WASH conditions or increased baseline disease burden. Individual interventions had complementary but not synergistic effects when combined.

Discussion: To realize the expected health gains, future WASH interventions must address community coverage and transmission along pathways not traditionally covered by WASH. The effectiveness of individual-level WASH improvements is reduced more the further the community is from achieving the coverage needed for herd protection. https://doi.org/10.1289/EHP15200.