Title

Prenatal lead exposure and fetal growth: Smaller infants have heightened susceptibility.

Year of Publication

2017

Number of Pages

228-233

Date Published

2017 Feb

ISSN Number

1873-6750

Abstract

<p><strong>BACKGROUND: </strong>As population lead levels decrease, the toxic effects of lead may be distributed to more sensitive populations, such as infants with poor fetal growth.</p>

<p><strong>OBJECTIVES: </strong>To determine the association of prenatal lead exposure and fetal growth; and to evaluate whether infants with poor fetal growth are more susceptible to lead toxicity than those with normal fetal growth.</p>

<p><strong>METHODS: </strong>We examined the association of second trimester maternal blood lead levels (BLL) with birthweight-for-gestational age (BWGA) z-score in 944 mother-infant participants of the PROGRESS cohort. We determined the association between maternal BLL and BWGA z-score by using both linear and quantile regression. We estimated odds ratios for small-for-gestational age (SGA) infants between maternal BLL quartiles using logistic regression. Maternal age, body mass index, socioeconomic status, parity, household smoking exposure, hemoglobin levels, and infant sex were included as confounders.</p>

<p><strong>RESULTS: </strong>While linear regression showed a negative association between maternal BLL and BWGA z-score (β=-0.06 z-score units per log BLL increase; 95% CI: -0.13, 0.003; P=0.06), quantile regression revealed larger magnitudes of this association in the &lt;30th percentiles of BWGA z-score (β range [-0.08, -0.13] z-score units per log BLL increase; all P values&lt;0.05). Mothers in the highest BLL quartile had an odds ratio of 1.62 (95% CI: 0.99-2.65) for having a SGA infant compared to the lowest BLL quartile.</p>

<p><strong>CONCLUSIONS: </strong>While both linear and quantile regression showed a negative association between prenatal lead exposure and birthweight, quantile regression revealed that smaller infants may represent a more susceptible subpopulation.</p>

DOI

10.1016/j.envint.2016.11.023

Alternate Title

Environ Int

PMID

27923585

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