Systematic review and meta-analysis of birth weight and PFNA exposures

We used a systematic review that included risk of bias and study sensitivity analysis to identify 34 studies examining changes in birth weight (BWT) in relation to PFNA biomarker measures (e.g., maternal serum/plasma or umbilical cord samples). We fit a random effects model of the overall pooled estimate and stratified estimates based on sample timing and overall study confidence. We conducted a meta-regression to further examine the impact of gestational age at biomarker sample timing. We detected a -32.9 g (95%CI: -47.0, -18.7) mean BWT deficit per each ln PFNA increase from 27 included studies. We did not detect evidence of publication bias (p_E = 0.30) or between-study heterogeneity in the summary estimate (p_Q = 0.05; I² = 36%). The twelve high confidence studies yielded a smaller pooled effect estimate (β = -28.0 g; 95%CI: -49.0, -6.9) than the ten medium (β = -39.0 g; 95%CI: -61.8, -16.3) or four low (β = -36.9 g; 95%CI: -82.9, 9.1) confidence studies. The stratum-specific results based on earlier pregnancy sampling periods in 11 studies showed smaller deficits (β = -22.0 g; 95%CI: -40.1, -4.0) compared to 10 mid- and late-pregnancy (β = -44.2 g; 95%CI: -64.8, -23.5) studies and six post-partum studies (β = -42.9 g; 95%CI: -88.0, 2.2). Using estimates of the specific gestational week of sampling, the meta-regression showed results consistent with the categorical sample analysis, in that as gestational age at sampling time increases across these studies, the summary effect estimate of a mean BWT deficit got larger. Overall, we detected mean BWT deficits for PFNA that were larger and more consistent across studies than previous PFAS meta-analyses. Compared to studies with later sampling, BWT deficits were smaller but remained sizeable for even the earliest sampling periods. Contrary to earlier meta-analyses for PFOA and PFOS, BWT deficits that were detected across all strata did not appear to be fully explained by potential bias due to pregnancy hemodynamics from sampling timing differences.