Prenatal exposure to mixtures of persistent endocrine disrupting chemicals and early menarche in a population-based cohort of British girls

Exposure to endocrine disrupting chemicals (EDCs) is ubiquitous. EDC exposure, especially during critical periods of development like the prenatal window, may interfere with the body’s endocrine system, which can affect growth and developmental outcomes such as puberty. Most studies have examined one EDC at a time in relation to disease; however, humans are exposed to many EDCs. By studying mixtures, the human experience can be more closely replicated. We investigated the association of prenatal exposure to persistent EDCs (poly- and perfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), and organochlorine pesticides (OCPs)) as mixtures with early menarche among female offspring in a nested case-control study within the Avon Longitudinal Study of Parents and Children (ALSPAC) recruited in the United Kingdom in 1991–1992. Concentrations of 52 EDCs were quantified in maternal serum samples collected during pregnancy. Daughter’s age at menarche was ascertained through mailed questionnaires sent annually. We used repeated holdout weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) to examine the association between prenatal exposure to multiple EDCs and early menarche (<11.5 (n = 218) vs. ≥11.5 years (n = 230)) for each chemical class separately (PFAS, PCBs, and OCPs) and for all three classes combined. Models adjusted for maternal age at menarche, maternal education, parity, pre-pregnancy body mass index, maternal age, prenatal smoking, and gestational week at sample collection. Mixture models showed null associations between prenatal exposure to EDC mixtures and early menarche. Using WQS regression, the odds ratio for early menarche for a one-decile increase in chemical concentrations for all three classes combined was 0.89 (95% CI: 0.76, 1.05); using BKMR, the odds ratio when all exposures were at the 60th percentile compared to the median was 0.98 (95% CI: 0.91, 1.05). Results suggest the overall effect of prenatal exposure to persistent EDC mixtures is not associated with early menarche

Comprehensive Assessment of Maize Aflatoxin Levels in Eastern Kenya, 2005–2007

Background: Aflatoxin, a potent fungal toxin, contaminates 25% of crops worldwide. Since 2004, 477 aflatoxin poisonings associated with eating contaminated maize have been documented in Eastern Kenya, with a case-fatality rate of 40%

Analyzing Limitations in Exposure Estimates Based on Self-Reported Dietary Intake of Caffeinated Beverages in the Baltimore-Washington Infant Study, 1981-1989

Caffeine, a mild central nervous system stimulant, is a natural component of common hot and cold beverages like coffee, tea, sodas and cocoa. Animal studies have demonstrated caffeine’s teratogenic effects when administered at high concentrations; however, epidemiologic studies have yielded inconsistent results in humans. Because caffeine containing beverages are commonly consumed by pregnant women, we examined the prevalence of use and explored possible associations of maternal caffeine consumption with cardiovascular malformations in 3,274 cases matched with 3,519 controls enrolled in the 1981-89 “Baltimore-Washington Infant Study,” a population-based case-control investigation. We explored several key aspects of the quality of and distribution of measurements of caffeine consumption among mothers in the study population. We concluded with recommendations for refining data collection to reduce potential bias associated with assessing both caffeine content and changes in caffeine consumption during pregnancy in order to inform future research studies and birth defects/adverse birth outcomes surveillance programs

Arsenic in private well water and birth outcomes in the United States.

BackgroundPrenatal exposure to drinking water with arsenic concentrations &gt;50&nbsp;μg/L is associated with adverse birth outcomes, with inconclusive evidence for concentrations ≤50&nbsp;μg/L. In a collaborative effort by public health experts, hydrologists, and geologists, we used published machine learning model estimates to characterize arsenic concentrations in private wells-federally unregulated for drinking water contaminants-and evaluated associations with birth outcomes throughout the conterminous U.S.MethodsUsing several machine learning models, including boosted regression trees (BRT) and random forest classification (RFC), developed from measured groundwater arsenic concentrations of ∼20,000 private wells, we characterized the probability that arsenic concentrations occurred within specific ranges in groundwater. Probabilistic model estimates and private well usage data were linked by county to all live birth certificates from 2016 (n&nbsp;=&nbsp;3.6 million). We evaluated associations with gestational age and term birth weight using mixed-effects models, adjusted for potential confounders and incorporated random intercepts for spatial clustering.ResultsWe generally observed inverse associations with term birth weight. For instance, when using BRT estimates, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 5&nbsp;μg/L was associated with a -1.83&nbsp;g (95% CI: -3.30, -0.38) lower term birth weight after adjusting for covariates. Similarly, a 10-percentage point increase in the probability that private well arsenic concentrations exceeded 10&nbsp;μg/L was associated with a -2.79&nbsp;g (95% CI: -4.99, -0.58) lower term birth weight. Associations with gestational age were null.ConclusionIn this largest epidemiologic study of arsenic and birth outcomes to date, we did not observe associations of modeled arsenic estimates in private wells with gestational age and found modest inverse associations with term birth weight. Study limitations may have obscured true associations, including measurement error stemming from a lack of individual-level information on primary water sources, water arsenic concentrations, and water consumption patterns