Background:
In utero
exposure to metals lead (Pb), cadmium (Cd), and mercury (Hg) may be associated with higher childhood systolic blood pressure (SBP), while trace elements manganese (Mn) and selenium (Se) may have protective, antioxidant effects that modify metal-SBP associations. No study has examined how
in utero
co-exposure to these metals affect offspring SBP.
Objectives:
To examine the individual and joint effects of
in utero
exposure to Cd, Pb, Hg, Mn, and Se on offspring SBP.
Methods:
We used data from the Boston Birth Cohort (enrolled 2002-2013). We measured metals in maternal red blood cells collected 24-72 hours after delivery. We calculated child age-, sex-, and height-specific SBP percentile per 2017 American Academy of Pediatrics guidelines. We used linear regression models to estimate associations of each metal, and Bayesian kernel machine regression (BKMR) to examine metal co-exposures, with child SBP between 3 to 15 years of age.
Results:
Our analytic sample comprised 1194 mother-child pairs (61% Black, 20% Hispanic). Hg and Pb were not associated with child SBP. Se and Mn were inversely associated with child SBP: each log2(Se) and log2(Mn) increment was associated with a 6.23 (95% CI: 0.96-11.51) and a 2.62 (95% CI: 0.04-5.20) percentile lower child SBP, respectively. BKMR models showed similar results (
Panel A
). While Cd was not overall associated with child SBP, there was an antagonistic interaction between Cd and Mn (P-interaction = 0.036): the association of Mn and lower child SBP was stronger with higher levels of Cd (
Panel B
). Consistent with this finding,
in utero
exposure to cigarette smoke (a major source of Cd) modified the association of Mn and child SBP: among children born mothers who smoked cigarette in pregnancy, each log2(Mn) increment was associated with a 10.09 (95% CI: 2.15-18.03) percentile lower SBP (
Panel C
).
Conclusion:
Optimizing
in utero
Se levels, as well as Mn levels in pregnant women who had high Cd or smoked during pregnancy, may protect offspring from developing high BP during childhood.
Modeling the health effects of time-varying complex environmental mixtures: Mean field variational Bayes for lagged kernel machine regression