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Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled

Background Gestational diabetes (GDM) is prevalent and benefits from timely and effective treatment, given the short window to impact glycemic control. Clinicians face major barriers to choosing effectively among treatment modalities [medical nutrition therapy (MNT) with or without pharmacologic treatment (antidiabetic oral agents and/or insulin)]. We investigated whether clinical data at varied stages of pregnancy can predict GDM treatment modality. Methods Among a population-based cohort of 30,474 pregnancies with GDM delivered at Kaiser Permanente Northern California in 2007–2017, we selected those in 2007–2016 as the discovery set and 2017 as the temporal/future validation set. Potential predictors were extracted from electronic health records at different timepoints (levels 1–4): (1) 1-year preconception to the last menstrual period, (2) the last menstrual period to GDM diagnosis, (3) at GDM diagnosis, and (4) 1 week after GDM diagnosis. We compared transparent and ensemble machine learning prediction methods, including least absolute shrinkage and selection operator (LASSO) regression and super learner, containing classification and regression tree, LASSO regression, random forest, and extreme gradient boosting algorithms, to predict risks for pharmacologic treatment beyond MNT. Results The super learner using levels 1–4 predictors had higher predictability [tenfold cross-validated C-statistic in discovery/validation set: 0.934 (95% CI: 0.931–0.936)/0.815 (0.800–0.829)], compared to levels 1, 1–2, and 1–3 (discovery/validation set C-statistic: 0.683–0.869/0.634–0.754). A simpler, more interpretable model, including timing of GDM diagnosis, diagnostic fasting glucose value, and the status and frequency of glycemic control at fasting during one-week post diagnosis, was developed using tenfold cross-validated logistic regression based on super learner-selected predictors. This model compared to the super learner had only a modest reduction in predictability [discovery/validation set C-statistic: 0.825 (0.820–0.830)/0.798 (95% CI: 0.783–0.813)]. Conclusions Clinical data demonstrated reasonably high predictability for GDM treatment modality at the time of GDM diagnosis and high predictability at 1-week post GDM diagnosis. These population-based, clinically oriented models may support algorithm-based risk-stratification for treatment modality, inform timely treatment, and catalyze more effective management of GDM.

Background Diarrhea and acute respiratory infection (ARI) are leading causes of death in children. The WASH Benefits Bangladesh trial implemented a multicomponent sanitation intervention that led to a 39% reduction in the prevalence of diarrhea among children and a 25% reduction for ARI, measured 1 to 2 years after intervention implementation. We measured longer-term intervention effects on these outcomes between 1 to 3.5 years after intervention implementation, including periods with differing intensity of behavioral promotion. Methods and findings WASH Benefits Bangladesh was a cluster-randomized controlled trial of water, sanitation, hygiene, and nutrition interventions (NCT01590095). The sanitation intervention included provision of or upgrades to improved latrines, sani-scoops for feces removal, children’s potties, and in-person behavioral promotion. Promotion was intensive up to 2 years after intervention initiation, decreased in intensity between years 2 to 3, and stopped after 3 years. Access to and reported use of latrines was high in both arms, and latrine quality was significantly improved by the intervention, while use of child feces management tools was low. We enrolled a random subset of households from the sanitation and control arms into a longitudinal substudy, which measured child health with quarterly visits between 1 to 3.5 years after intervention implementation. The study period therefore included approximately 1 year of high-intensity promotion, 1 year of low-intensity promotion, and 6 months with no promotion. We assessed intervention effects on diarrhea and ARI prevalence among children p = 0.05; prevalence difference [PD] = −0.027, 95% CI −0.053, 0, p = 0.05). ARI prevalence did not differ between sanitation (21.3%) and control (22.7%) arms (PR = 0.93, 95% CI 0.82, 1.05, p = 0.23; PD = −0.016, 95% CI −0.043, 0.010, p = 0.23). There were no significant differences in intervention effects between periods with high-intensity versus low-intensity/no promotion. Study limitations include use of caregiver-reported symptoms to define health outcomes and limited data collected after promotion ceased. Conclusions The observed effect of the WASH Benefits Bangladesh sanitation intervention on diarrhea in children appeared to be sustained for at least 3.5 years after implementation, including 1.5 years after heavy promotion ceased. Existing latrine access was high in the study setting, suggesting that improving on-site latrine quality can deliver health benefits when latrine use practices are in place. Further work is needed to understand how latrine adoption can be achieved and sustained in settings with low existing access and how sanitation programs can adopt transformative approaches of excreta management, including safe disposal of child and animal feces, to generate a hygienic home environment. Trial registration ClinicalTrials.gov; NCT01590095; https://clinicaltrials.gov/ct2/show/NCT01590095.

BackgroundHousehold-level sanitation interventions have had limited effects on child health or environmental contamination, potentially due to low community coverage. Higher community-level coverage with safely managed sanitation can reduce opportunities for disease transmission.MethodsWe estimated associations between community sanitation coverage, environmental fecal contamination, and child health among 360 compounds in the control arm of the WASH Benefits trial in rural Bangladesh (NCT01590095). In each compound, we enumerated E. coli in environmental samples and recorded the 7-day prevalence of caregiver-reported diarrheal disease and acute respiratory infections (ARI) in children under five. We observed indicators of latrine access and quality among all neighboring compounds within 100m of study compounds. We defined community coverage as the proportion of neighboring compounds with (1) at least one latrine, and (2) exclusively hygienic latrines (improved facility observed to safely contain feces), within both 50m and 100m of study compounds. We assessed effect modification by population density and season.ResultsAdjusted for confounders, study compounds surrounded by 100% coverage of at least one latrine per compound within 50m had slightly lower log10E. coli counts in stored water (Δlog=-0.13, 95% CI -0.26, -0.01), child hand rinses (Δlog=-0.13, 95% CI -0.24, -0.02), and caregiver hand rinses (Δlog=-0.16, 95% CI -0.29, -0.03) and marginally lower prevalence of diarrheal disease (prevalence ratio [PR]=0.82, 95% CI 0.64, 1.04) and ARI (PR=0.84, 95% CI 0.69, 1.03) compared to compounds surrounded by

Several recently developed methods have the potential to harness machine learning in the pursuit of target quantities inspired by causal inference, including inverse weighting, doubly robust estimating equations and substitution estimators like targeted maximum likelihood estimation. There are even more recent augmentations of these procedures that can increase robustness, by adding a layer of cross-validation (cross-validated targeted maximum likelihood estimation and double machine learning, as applied to substitution and estimating equation approaches, respectively). While these methods have been evaluated individually on simulated and experimental data sets, a comprehensive analysis of their performance across ``real-world'' simulations have yet to be conducted. In this work, we benchmark multiple widely used methods for estimation of the average treatment effect using ten different nutrition intervention studies data. A realistic set of simulations, based on a novel method, highly adaptive lasso, for estimating the data-generating distribution that guarantees a certain level of complexity (undersmoothing) is used to better mimic the complexity of the true data-generating distribution. We have applied this novel method for estimating the data-generating distribution by individual study and to subsequently use these fits to simulate data and estimate treatment effects parameters as well as their standard errors and resulting confidence intervals. Based on the analytic results, a general recommendation is put forth for use of the cross-validated variants of both substitution and estimating equation estimators. We conclude that the additional layer of cross-validation helps in avoiding unintentional over-fitting of nuisance parameter functionals and leads to more robust inferences.

Nuclear receptors (NRs) are important biological targets of endocrine-disrupting chemicals (EDCs). Identifying chemicals that can act as EDCs and modulate the function of NRs is difficult because of the time and cost of in vitro and in vivo screening to determine the potential hazards of the 100 000s of chemicals that humans are exposed to. Hence, there is a need for computational approaches to prioritize chemicals for biological testing. Machine learning (ML) techniques are alternative methods that can quickly screen millions of chemicals and identify those that may be an EDC. Computational models of chemical binding to multiple NRs have begun to emerge. Recently, a Nuclear Receptor Activity (NuRA) dataset, describing experimentally derived small-molecule activity against various NRs has been created. We have used the NuRA dataset to develop an ensemble of ML-based models to predict the agonism, antagonism, binding and effector binding of small molecules to nine different human NRs. We defined the applicability domain of the ML models as a measure of Tanimoto similarity to the molecules in the training set, which enhanced the performance of the developed classifiers. We further developed a user-friendly web server named ‘NR-ToxPred’ to predict the binding of chemicals to the nine NRs using the best-performing models for each receptor. This web server is freely accessible at http://nr-toxpred.cchem.berkeley.edu. Users can upload individual chemicals using Simplified Molecular-Input Line-Entry System, CAS numbers or sketch the molecule in the provided space to predict the compound’s activity against the different NRs and predict the binding mode for each.

IntroductionRisk factors for interpersonal violence-related injury (IPVRI) in low-income and middle-income countries (LMICs) remain poorly defined. We describe associations between IPVRI and select social determinants of health (SDH) in Cameroon.MethodsWe conducted a cross-sectional analysis of prospective trauma registry data collected from injured patients >15 years old between October 2017 and January 2020 at four Cameroonian hospitals. Our primary outcome was IPVRI, compared with unintentional injury. Explanatory SDH variables included education level, employment status, household socioeconomic status (SES) and alcohol use. The EconomicClusters model grouped patients into household SES clusters: rural, urban poor, urban middle-class (MC) homeowners, urban MC tenants and urban wealthy. Results were stratified by sex. Categorical variables were compared via Pearson’s χ2 statistic. Associations with IPVRI were estimated using adjusted odds ratios (aOR) with 95% confidence intervals (95%CI).ResultsAmong 7605 patients, 5488 (72.2%) were men. Unemployment was associated with increased odds of IPVRI for men (aOR 2.44 (95% CI 1.95 to 3.06), pConclusionLower educational attainment, unemployment, lower household SES and alcohol use are risk factors for IPVRI in Cameroon. Future research should explore LMIC-appropriate interventions to address SDH risk factors for IPVRI.

Background: Hundreds of thousands of biodigesters have been constructed in Nepal. These household-level systems use human and animal waste to produce clean-burning biogas used for cooking, which can reduce household air pollution from woodburning cookstoves and prevent respiratory illnesses. The biodigesters, typically operated by female caregivers, require the handling of animal waste, which may increase domestic fecal contamination, exposure to diarrheal pathogens, and the risk of enteric infections, especially among young children. Objective: We estimated the effect of daily reported biogas cookstove use on incident diarrhea among children

Metformin and weight loss relationships with epigenetic age measures—biological aging biomarkers—remain understudied. We performed a post-hoc analysis of a randomized controlled trial among overweight/obese breast cancer survivors (N = 192) assigned to metformin, placebo, weight loss with metformin, or weight loss with placebo interventions for 6 months. Epigenetic age was correlated with chronological age (r = 0.20–0.86; P Trial Registration: Registry Name: ClincialTrials.Gov.Registration Number: NCT01302379.Date of Registration: February 2011.URL:https://clinicaltrials.gov/ct2/show/NCT01302379

BackgroundIncreasing influenza vaccination coverage in school-aged children may substantially reduce community transmission. School-located influenza vaccinations (SLIV) aim to promote vaccinations by increasing accessibility, which may be especially beneficial to race/ethnicity groups that face high barriers to preventative care. Here, we evaluate the effectiveness of a city-wide SLIV program by race/ethnicity from 2014 to 2018.MethodsWe used multivariate matching to pair schools in the intervention district in Oakland, CA with schools in a comparison district in West Contra Costa County, CA. We distributed cross-sectional surveys to measure caregiver-reported student vaccination status and estimated differences in vaccination coverage levels and reasons for non-vaccination between districts stratifying by race/ethnicity. We estimated difference-in-differences (DID) of laboratory confirmed influenza hospitalization incidence between districts stratified by race/ethnicity using surveillance data.ResultsDifferences in influenza vaccination coverage in the intervention vs. comparison district were larger among White (2017-18: 21.0% difference [95% CI: 9.7%, 32.3%]) and Hispanic/Latino (13.4% [8.8%, 18.0%]) students than Asian/Pacific Islander (API) (8.9% [1.3%, 16.5%]), Black (5.9% [-2.2%, 14.0%]), and multiracial (6.3% [-1.8%, 14.3%)) students. Concerns about vaccine effectiveness or safety were more common among Black and multiracial caregivers. Logistical barriers were less common in the intervention vs. comparison district, with the largest difference among White students. In both districts, hospitalizations in 2017-18 were higher in Blacks (Intervention: 111.5 hospitalizations per 100,00; Comparison: 134.1 per 100,000) vs. other races/ethnicities. All-age influenza hospitalization incidence was lower in the intervention site vs. comparison site among White/API individuals in 2016-17 (DID -25.14 per 100,000 [95% CI: -40.14, -10.14]) and 2017-18 (-36.6 per 100,000 [-52.7, -20.5]) and Black older adults in 2017-18 (-282.2 per 100,000 (-508.4, -56.1]), but not in other groups.ConclusionsSLIV was associated with higher vaccination coverage and lower influenza hospitalization, but associations varied by race/ethnicity. SLIV alone may be insufficient to ensure equitable influenza outcomes.

BackgroundWe hypothesized that drinking water, sanitation, handwashing (WSH), and nutritional interventions would improve environmental enteric dysfunction (EED), a potential contributor to stunting.MethodsWithin a subsample of a cluster-randomized, controlled trial in rural Bangladesh, we enrolled pregnant women in 4 arms: control, WSH, child nutrition counseling plus lipid-based nutrient supplements (N), and nutrition plus WSH (N+WSH). Among the birth cohort, we measured biomarkers of gut inflammation (myeloperoxidase, neopterin), permeability (alpha-1-antitrypsin, lactulose, mannitol), and repair (regenerating gene 1β) at median ages 3, 14, and 28 months. Analysis was intention-to-treat.ResultsWe assessed 1512 children. At age 3 months, compared to controls, neopterin was reduced by nutrition (-0.21 log nmol/L; 95% confidence interval [CI], -.37, -.05) and N+WSH (-0.20 log nmol/L; 95% CI, -.34, -.06) interventions; similar reductions were observed at 14 months. At 3 months, all interventions reduced lactulose and mannitol (-0.60 to -0.69 log mmol/L). At 28 months, myeloperoxidase was elevated in the WSH and nutrition arms (0.23-0.27 log ng/mL) and lactulose was higher in the WSH arm (0.30 log mmol/L; 95% CI, .07, .53).ConclusionsReductions in permeability and inflammation at ages 3 and 14 months suggest that the interventions promoted healthy intestinal maturation; however, by 28 months, the WSH and nutrition arms showed elevated EED biomarkers. These results underscore the importance of developing a better understanding of EED pathophysiology and targeting interventions early in childhood, when they are likely to have the largest benefit to intestinal health.Clinical trials registrationNCT01590095.

Sanitation improvements have had limited effectiveness in reducing the spread of fecal pathogens into the environment. We conducted environmental measurements within a randomized controlled trial in Bangladesh that implemented individual and combined water treatment, sanitation, handwashing (WSH) and nutrition interventions (WASH Benefits, NCT01590095). Following approximately 4 months of intervention, we enrolled households in the trial’s control, sanitation and combined WSH arms to assess whether sanitation improvements, alone and coupled with water treatment and handwashing, reduce fecal contamination in the domestic environment. We quantified fecal indicator bacteria in samples of drinking and ambient waters, child hands, food given to young children, courtyard soil and flies. In the WSH arm, Escherichia coli prevalence in stored drinking water was reduced by 62% (prevalence ratio = 0.38 (0.32, 0.44)) and E. coli concentration by 1-log (Δlog10 = −0.88 (−1.01, −0.75)). The interventions did not reduce E. coli along other sampled pathways. Ambient contamination remained high among intervention households. Potential reasons include noncommunity-level sanitation coverage, child open defecation, animal fecal sources, or naturalized E. coli in the environment. Future studies should explore potential threshold effects of different levels of community sanitation coverage on environmental contamination.

The trial found that individual handwashing and sanitation interventions significantly reduced childhood Giardia infections. Combined interventions provided no additional benefit. To reduce Giardia infection, individual interventions may be more feasible and cost-effective than combined interventions in similar rural, low-income settings., Background We evaluated effects of individual and combined water, sanitation, handwashing (WSH), and nutritional interventions on protozoan infections in children. Methods We randomized geographical clusters of pregnant women in rural Bangladesh into chlorinated drinking water, hygienic sanitation, handwashing, nutrition, combined WSH, nutrition plus WSH (N+WSH), or control arms. Participants were not masked. After approximately 2.5 years of intervention, we measured Giardia, Cryptosporidium, and Entamoeba histolytica prevalence and infection intensity by multiplex real-time polymerase chain reaction of child stool. Analysis was intention-to-treat. Results Between May 2012 and July 2013, we randomized 5551 pregnant women. At follow-up, among 4102 available women, we enrolled 6694 children into the protozoan assessment. We analyzed stool from 5933 children (aged ~31 months) for protozoan infections. Compared with 35.5% prevalence among controls, Giardia infection prevalence was lower in the sanitation (26.5%; prevalence ratio [PR], 0.75 [95% confidence interval {CI}, .64–.88]), handwashing (28.2%; PR, 0.80 [95% CI, .66–.96]), WSH (29.7%; PR, 0.83 [95% CI, .72–.96]), and N+WSH (26.7%; PR, 0.75 [95% CI, .64–.88]) arms. Water and nutrition interventions had no effect. Low prevalence of E. histolytica and Cryptosporidium (

Objectives. To evaluate whether the quality of implementation of a water, sanitation, and hygiene program called SHEWA-B and delivered by UNICEF to 20 million people in rural Bangladesh was associated with health behaviors and sanitation infrastructure access. Methods. We surveyed 33 027 households targeted by SHEWA-B and 1110 SHEWA-B hygiene promoters in 2011 and 2012. We developed an implementation quality index and compared the probability of health behaviors and sanitation infrastructure access in counterfactual scenarios over the range of implementation quality. Results. Forty-seven percent of households (n = 14 622) had met a SHEWA-B hygiene promoter, and 47% of hygiene promoters (n = 527) could recall all key program messages. The frequency of hygiene promoter visits was not associated with improved outcomes. Higher implementation quality was not associated with better health behaviors or infrastructure access. Outcomes differed by only 1% to 3% in scenarios in which all clusters received low versus high implementation quality. Conclusions. SHEWA-B did not meet UNICEF’s ideal implementation quality in any area. Improved implementation quality would have resulted in marginal changes in health behaviors or infrastructure access. This suggests that SHEWA-B’s design was suboptimal for improving these outcomes.

Multiple sclerosis (MS) is an autoimmune disease with both genetic and environmental risk factors. Recent studies indicate that childhood and adolescent obesity double the risk of MS, but this association may reflect unmeasured confounders rather than causal effects of obesity. We used separate-sample Mendelian randomization to estimate the causal effect of body mass index (BMI) on susceptibility to MS. Using data from non-Hispanic white members of the Kaiser Permanente Medical Care Plan of Northern California (KPNC) (2006-2014; 1,104 cases of MS and 10,536 controls) and a replication data set from Sweden (the Epidemiological Investigation of MS (EIMS) and the Genes and Environment in MS (GEMS) studies, 2005-2013; 5,133 MS cases and 4,718 controls), we constructed a weighted genetic risk score using 97 variants previously established to predict BMI. Results were adjusted for birth year, sex, education, smoking status, ancestry, and genetic predictors of MS. Estimates in KPNC and Swedish data sets suggested that higher genetically induced BMI predicted greater susceptibility to MS (odds ratio = 1.13, 95% confidence interval: 1.04, 1.22 for the KPNC sample; odds ratio = 1.09, 95% confidence interval: 1.03, 1.15 for the Swedish sample). Although the mechanism remains unclear, to our knowledge, these findings support a causal effect of increased BMI on susceptibility to MS for the first time, and they suggest a role for inflammatory pathways that characterize both obesity and the MS disease process.

The mechanism of toxicity of the leukemogen benzene is not entirely known. This pilot study used RNA-sequencing (RNA-seq) technology to examine the effect of benzene exposure on gene expression in peripheral blood mononuclear cells obtained from 10 workers occupationally exposed to high levels of benzene (≥5 ppm) in air and 10 matched unexposed control workers, from a large study (n = 125) in which gene expression was previously measured by microarray. RNA-seq is more sensitive and has a wider dynamic range for the quantification of gene expression. Further, it has the ability to detect novel transcripts and alternative splice variants. The main conclusions from our analysis of the 20 workers by RNA-seq are as follows: The Pearson correlation between the two technical replicates for the RNA-seq experiments was 0.98 and the correlation between RNA-seq and microarray signals for the 20 subjects was around 0.6. 60% of the transcripts with detected reads from the RNA-seq experiments did not have corresponding probes on the microarrays. Fifty-three percent of the transcripts detected by RNA-seq and 99% of those with probes on the microarray were protein-coding. There was a significant overlap (P < 0.05) in transcripts declared differentially expressed due to benzene exposure using the two technologies. About 20% of the transcripts declared differentially expressed using the RNA-seq data were non-coding transcripts. Six transcripts were determined (false-discovery rate < 0.05) to be alternatively spliced as a result of benzene exposure. Overall, this pilot study shows that RNA-seq can complement the information obtained by microarray in the analysis of changes in transcript expression from chemical exposures.

Objective To delineate the trajectories of Aβ42 level in cerebrospinal fluid (CSF), fludeoxyglucose F18 (FDG) uptake using positron emission tomography, and hippocampal volume using magnetic resonance imaging and their relative associations with cognitive change at different stages in aging and Alzheimer disease (AD). Design Cohort study. Setting The 59 study sites for the Alzheimer's Disease Neuroimaging Initiative. Participants A total of 819 participants 55 to 90 years of age with normal cognition, mild cognitive impairment, and AD who were followed up during the period from 2005 to 2007. Main Outcome Measures Rates of change in level of Aβ42 in CSF, FDG uptake, hippocampal volume, and the Alzheimer Disease's Assessment Scale–cognitive subscale score during up to 36 months of follow-up by diagnostic group as well as prediction of cognitive change by each biomarker. Results Reductions in the level of Aβ42 in CSF were numerically greater in participants with normal cognition than in participants with mild cognitive impairment or AD; whereas both glucose metabolic decline and hippocampal atrophy were significantly slower in participants with normal cognition than in participants with mild cognitive impairment or AD. Positive APOE4 status accelerated hippocampal atrophic changes in participants with mild cognitive impairment or AD, but did not modify rates of change in level of Aβ42 in CSF or FDG uptake. The Alzheimer Disease's Assessment Scale–cognitive subscale scores were related only to the baseline level of Aβ42 in CSF and the baseline FDG uptake in participants with normal cognition, which were about equally associated with change in FDG uptake and hippocampal volume in participants with mild cognitive impairment and best modeled by change in FDG uptake in participants with AD. Conclusion Trajectories of Aβ42 level in CSF, FDG uptake, and hippocampal volume vary across different cognitive stages. The longitudinal patterns support a hypothetical sequence of AD pathology in which amyloid deposition is an early event before hypometabolism or hippocampal atrophy, suggesting that biomarker prediction for cognitive change is stage dependent.