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Epidemiology. 2018 Nov 30. doi: 10.1097/EDE.0000000000000962. [Epub ahead of print]

Prenatal metal concentrations and childhood cardio-metabolic risk using Bayesian Kernel Machine Regression to assess mixture and interaction effects.

Author information

1
Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA.
2
Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
3
National Institute of Perinatology, Mexico City, Mexico.
4
Center for Research on Nutrition and Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico.
5
Department of Epidemiology, Brown University, Providence, Rhode Island.
6
Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA.

Abstract

BACKGROUND:

Trace metal concentrations may affect cardio-metabolic risk, but the role of prenatal exposure is unclear. We examined: 1) the relationship between blood metal concentrations during pregnancy and child cardio-metabolic risk factors; 2) overall effects of metals mixture (essential vs. nonessential); and 3) interactions between metals.

METHODS:

We measured 11 metals in maternal 2 trimester whole blood in a prospective birth cohort in Mexico City. In children 4-6 years old, we measured body mass index (BMI), percent body fat, and blood pressure (N=609); and plasma hemoglobin A1C (HbA1c) , non-high density lipoprotein (HDL) cholesterol, triglycerides, leptin, and adiponectin (N=411). We constructed cardio-metabolic component scores using age- and sex-adjusted z-scores and averaged five scores to create a global risk score. We estimated linear associations of each metal with individual z-scores and used Bayesian Kernel Machine Regression to assess metal mixtures and interactions.

RESULTS:

Higher total metals were associated with lower HbA1c, leptin, and systolic blood pressure, and with higher adiponectin and non-HDL cholesterol. We observed no interactions between metals. Higher selenium was associated with lower triglycerides in linear (β=-1.01 z-score units per 1 unit ln(Se), 95%CI = -1.84; -0.18) and Bayesian Kernel Machine Regression models. Manganese was associated with decreased HbA1c in linear models (β = -0.32 and 95% CI: -0.61, -0.03). Antimony and arsenic were associated with lower leptin in Bayesian Kernel Machine Regression models. Essential metals were more strongly associated with cardio-metabolic risk than were nonessential metals.

CONCLUSIONS:

Low essential metals during pregnancy were associated with increased cardio-metabolic risk factors in childhood.

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