Vitamin D Deficiency, Excessive Gestational Weight Gain, and Oxidative Stress Predict Small for Gestational Age Newborns Using an Artificial Neural Network Model.

(1) Background: Size at birth is an important early determinant of health later in life. The prevalence of small for gestational age (SGA) newborns is high worldwide and may be associated with maternal nutritional and metabolic factors. Thus, estimation of fetal growth is warranted. (2) Methods: In this work, we developed an artificial neural network (ANN) model based on first-trimester maternal body fat composition, biochemical and oxidative stress biomarkers, and gestational weight gain (GWG) to predict an SGA newborn in pregnancies with or without obesity. A sensibility analysis to classify maternal features was conducted, and a simulator based on the ANN algorithm was constructed to predict the SGA outcome. Several predictions were performed by varying the most critical maternal features attained by the model to obtain different scenarios leading to SGA. (3) Results: The ANN model showed good performance between the actual and simulated data (R2 = 0.938) and an AUROC of 0.8 on an independent dataset. The top-five maternal predictors in the first trimester were protein and lipid oxidation biomarkers (carbonylated proteins and malondialdehyde), GWG, vitamin D, and total antioxidant capacity. Finally, excessive GWG and redox imbalance predicted SGA newborns in the implemented simulator. Significantly, vitamin D deficiency also predicted simulated SGA independently of GWG or redox status. (4) Conclusions: The study provided a computational model for the early prediction of SGA, in addition to a promising simulator that facilitates hypothesis-driven constructions, to be further validated as an application.

Diet Quality Is Associated with a High Newborn Size and Reduction in the Risk of Low Birth Weight and Small for Gestational Age in a Group of Mexican Pregnant Women: An Observational Study.

A high-quality diet during pregnancy may have positive effects on fetal growth and nutritional status at birth, and it may modify the risk of developing chronic diseases later in life. The aim of this study was to evaluate the association between diet quality and newborn nutritional status in a group of pregnant Mexican women. As part of the ongoing Mexican prospective cohort study, OBESO, we studied 226 healthy pregnant women. We adapted the Alternated Healthy Eating Index-2010 for pregnancy (AHEI-10P). The association between maternal diet and newborn nutritional status was investigated by multiple linear regression and logistic regression models. We applied three 24-h recalls during the second half of gestation. As the AHEI-10P score improved by 5 units, the birth weight and length increased (ß = 74.8 ± 35.0 g and ß = 0.3 ± 0.4 cm, respectively, p < 0.05). Similarly, the risk of low birth weight (LBW) and small for gestational age (SGA) decreased (OR: 0.47, 95%CI: 0.27-0.82 and OR: 0.55, 95%CI: 0.36-0.85, respectively). In women without preeclampsia and/or GDM, the risk of stunting decreased as the diet quality score increased (+5 units) (OR: 0.62, 95%IC: 0.40-0.96). A high-quality diet during pregnancy was associated with a higher newborn size and a reduced risk of LBW and SGA in this group of pregnant Mexican women.