Abstract
The impact of prenatal exposure to a mixture of heavy metals on birth weight in newborns has been a topic of ongoing interest. In this study, 258 mothers and infants from the New Hampshire Birth Cohort Study (NHBCS) were selected as the study subjects, and the concentrations of seven heavy metals in the placenta, including Aluminum (Al), Cobalt (Co), Chromium (Cr), Nickel (Ni), Plumbum (Pb), Selenium (Se) and Arsenic (As) were collected. And the birth weight of newborns, the relevant covariates of mothers and newborns were collected. Three analytical methods, Weighted Quantile Sum (WQS) regression, Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) were employed. After adjusting for maternal gestational age, pre-pregnancy BMI, smoking status, education level, parity, gestational age and newborn gender, the combined three methods showed that the total effect of mixed exposure of seven heavy metals on birth weight was negative. Specifically, the WQS analysis revealed that Se had the greatest impact on birth weight, followed by Al. The QGC results showed that the heavy metal associated with the reduction of birth weight was mainly Se and Al in female and male infants, respectively. The BKMR analysis demonstrated a negative combined effect of the seven heavy metals on birth weight in both male and female infants, with Se having the highest posterior inclusion probabilities (PIPs) for female infants (0.45), and Al having the highest PIPs for male infants (0.64) after stratification by gender. In summary, mixed exposure to heavy metals during pregnancy was associated with a decrease in newborn birth weight. Furthermore, there are gender effects with Se and Al associated with decreased birth weight in female and male infants, respectively. These findings provide a theoretical basis for the development of public health policies aimed at preventing adverse pregnancy outcomes and improving the health of newborns.
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More From: Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
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