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ABSTRACT: Purpose
We investigated nonlinear and offspring sex-specific associations of maternal birthweight (BW) with offspring BW among participants of the Omega study, a pregnancy cohort.Methods
Maternal BW was modeled as a continuous variable, linear spline and binary variable indicating low birthweight (LBW; <2500 vs. ≥2500 grams). Offspring BW was modeled as a continuous and binary variable in regression models. Nonlinearity was assessed using likelihood ratio tests (LRTs) in marginal linear spline models.Results
For every 100-gram increase of maternal BW, offspring BW increased by 22.29 (95% CI: 17.57, 27.02) or 23.41 (95% CI: 6.87, 39.96) grams among mothers with normal BW or born macrosomic, respectively, but not among LBW mothers (β = -8.61 grams; 95% CI: -22.88, 5.65; LRT P-value = .0005). For every 100-gram increase in maternal BW, BW of male offspring increased 23.47 (95% CI: 16.75, 30.19) or 25.21 (95% CI: 4.35, 46.07) grams among mothers with normal BW or born macrosomic, respectively, whereas it decreased 31.39 grams (95% CI: -51.63, -11.15) among LBW mothers (LRT P-value < .0001). Corresponding increases in BW of female offspring (16-22 grams) did not differ among mothers with LBW, normal BW or macrosomia (LRT P-value = .9163).Conclusions
Maternal and offspring BW associations are evident among normal BW and macrosomic mothers. These associations differ by offspring sex.
SUBMITTER: Ncube CN
PROVIDER: S-EPMC5548425 | biostudies-literature | 2017 May
REPOSITORIES: biostudies-literature
Ncube Collette N CN Gavin Amelia R AR Williams Michelle A MA Qiu Chunfang C Sorensen Tanya K TK Enquobahrie Daniel A DA
Annals of epidemiology 20170510 5
<h4>Purpose</h4>We investigated nonlinear and offspring sex-specific associations of maternal birthweight (BW) with offspring BW among participants of the Omega study, a pregnancy cohort.<h4>Methods</h4>Maternal BW was modeled as a continuous variable, linear spline and binary variable indicating low birthweight (LBW; <2500 vs. ≥2500 grams). Offspring BW was modeled as a continuous and binary variable in regression models. Nonlinearity was assessed using likelihood ratio tests (LRTs) in marginal ...[more]