Early pregnancy essential and non-essential metal mixtures and gestational glucose concentrations in the 2nd trimester: Results from project viva.

Metals are involved in glucose metabolism, and some may alter glycemic regulation. However, joint effects of essential and non-essential metals on glucose concentrations during pregnancy are unclear. This study explored the joint associations of pregnancy exposures to essential (copper, magnesium, manganese, selenium, zinc) and non-essential (arsenic, barium, cadmium, cesium, lead, mercury) metals with gestational glucose concentrations using 1,311 women enrolled 1999-2002 in Project Viva, a Boston, MA-area pregnancy cohort. The study measured erythrocyte metal concentrations from 1st trimester blood samples and used glucose concentrations measured 1 h after non-fasting 50-gram glucose challenge tests (GCT) from clinical gestational diabetes screening at 26-28 weeks gestation. Bayesian Kernel Machine Regression (BKMR) and quantile-based g-computation were applied to model the associations of metal mixtures-including their interactions-with glucose concentrations post-GCT. We tested for reproducibility of BKMR results using generalized additive models. The BKMR model showed an inverse U-shaped association for barium and a linear inverse association for mercury. Specifically, estimated mean glucose concentrations were highest around 75th percentile of barium concentrations [2.1 (95% confidence interval: -0.2, 4.4) mg/dL higher comparing to the 25th percentile], and each interquartile range increase of erythrocyte mercury was associated with 1.9 mg/dL lower mean glucose concentrations (95% credible interval: -4.2, 0.4). Quantile g-computation showed joint associations of all metals, essential-metals, and non-essential metals on gestational glucose concentrations were all null, however, we observed evidences of interaction for barium and lead. Overall, we found early pregnancy barium and mercury erythrocytic concentrations were associated with altered post-load glucose concentrations in later pregnancy, with potential interactions between barium and lead.

Evaluating associations between early pregnancy trace elements mixture and 2nd trimester gestational glucose levels: A comparison of three statistical approaches.

OBJECTIVE: Studies have shown that individual trace element levels might be associated with abnormal glycemic status, with implications for diabetes. Few studies have considered these trace elements as a mixture and their impact on gestational glucose levels. Comparing three statistical approaches, we assessed the associations between essential trace elements mixture and gestational glucose levels. METHODS: We used data from 1720 women enrolled in the Eunice Kennedy Shriver National Institute of Child Health and Human Development's Fetal Growth Study, for whom trace element concentrations (zinc, selenium, copper, molybdenum) were measured by inductively coupled plasma mass spectrometry (ICP-MS) using plasma collected during the 1st trimester. Non-fasting glucose levels were measured during the gestational diabetes mellitus (GDM) screening test in the 2nd trimester. We applied (1) Bayesian Kernel Machine Regression (BKMR); (2) adaptive Least Absolute Shrinkage and Selection Operator (LASSO) in a mutually adjusted linear regression model; and (3) generalized additive models (GAMs) to evaluate the joint associations between trace elements mixture and glucose levels adjusting for potential confounders. RESULTS: Using BKMR, we observed a mean 2.7 mg/dL higher glucose level for each interquartile increase of plasma copper (95% credible interval: 0.9, 4.5). The positive association between plasma copper and glucose levels was more pronounced at higher quartiles of zinc. Similar associations were detected using adaptive LASSO and GAM. In addition, results from adaptive LASSO and GAM suggested a super-additive interaction between molybdenum and selenium (both p-values = 0.04). CONCLUSION: Employing different statistical methods, we found consistent evidence of higher gestational glucose levels associated with higher copper and potential synergism between zinc and copper on glucose levels.

A Prospective Study of Early Pregnancy Essential Metal(loid)s and Glucose Levels Late in the Second Trimester.

CONTEXT: Studies suggest many essential trace metal(loid)s are involved in glucose metabolism, but the associations among pregnant women are unclear. OBJECTIVE: To assess associations between early pregnancy plasma zinc, selenium, copper, and molybdenum levels and blood glucose levels later in the second trimester. DESIGN: The Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies‒Singleton Cohort is a prospective cohort study conducted between July 2009 and January 2013. SETTING: Twelve academic research hospitals in the United States. PATIENTS: A total of 1857 multiracial, nonobese, healthy women. MAIN OUTCOME MEASURE: Blood glucose levels from 1-hour 50-g gestational load test (GLT) at 24 to 28 weeks of gestation. RESULTS: Higher concentrations of first-trimester copper were associated with higher glucose levels from the GLT (i.e., every 50% increase in copper concentration was related to 4.9 mg/dL higher glucose level; 95% CI: 2.2, 7.5 mg/dL) adjusted for maternal sociodemographic characteristics and reproductive history. In contrast, every 50% increase in molybdenum concentration was associated with 1.2 mg/dL lower mean glucose level (95% CI: -2.3, -0.1 mg/dL). The magnitude of these associations was greater at the upper tails of glucose level distribution based on quantile regressions of the 10th, 50th, and 90th percentiles. CONCLUSIONS: Higher copper and lower molybdenum concentrations could increase the risk of glucose dysregulation during pregnancy, with women at higher risk of gestational diabetes mellitus potentially affected to a greater extent. Further work is needed to understand the mechanisms involved with early pregnancy essential metal(loid)s to inform clinical diagnosis and prevention of glucose intolerance during pregnancy.

Validity of the posttraumatic stress disorders (PTSD) checklist in pregnant women.

BACKGROUND: The PTSD Checklist-civilian (PCL-C) is one of the most commonly used self-report measures of PTSD symptoms, however, little is known about its validity when used in pregnancy. This study aims to evaluate the reliability and validity of the PCL-C as a screen for detecting PTSD symptoms among pregnant women. METHODS: A total of 3372 pregnant women who attended their first prenatal care visit in Lima, Peru participated in the study. We assessed the reliability of the PCL-C items using Cronbach's alpha. Criterion validity and performance characteristics of PCL-C were assessed against an independent, blinded Clinician-Administered PTSD Scale (CAPS) interview using measures of sensitivity, specificity and receiver operating characteristics (ROC) curves. We tested construct validity using exploratory and confirmatory factor analytic approaches. RESULTS: The reliability of the PCL-C was excellent (Cronbach's alpha =0.90). ROC analysis showed that a cut-off score of 26 offered optimal discriminatory power, with a sensitivity of 0.86 (95% CI: 0.78-0.92) and a specificity of 0.63 (95% CI: 0.62-0.65). The area under the ROC curve was 0.75 (95% CI: 0.71-0.78). A three-factor solution was extracted using exploratory factor analysis and was further complemented with three other models using confirmatory factor analysis (CFA). In a CFA, a three-factor model based on DSM-IV symptom structure had reasonable fit statistics with comparative fit index of 0.86 and root mean square error of approximation of 0.09. CONCLUSION: The Spanish-language version of the PCL-C may be used as a screening tool for pregnant women. The PCL-C has good reliability, criterion validity and factorial validity. The optimal cut-off score obtained by maximizing the sensitivity and specificity should be considered cautiously; women who screened positive may require further investigation to confirm PTSD diagnosis.