Elevated Maternal Lipid Metabolism Is Associated With Exceeding Gestational Weight Gain Guidelines

Abstract

Only 30% of women achieve gestational weight gain (GWG) within recommended ranges set forth by National Academy of Medicine (NAM). Because extreme deviations from these recommendations for GWG have been associated with unfavorable maternal outcomes, a greater understanding of maternal metabolic factors that influence GWG is warranted. PURPOSE: The purpose of this study was to explore the potential link between maternal lipid metabolism and GWG. METHODS: Thirty-two women with a lean pre-pregnancy BMI were recruited during late pregnancy and fasting metabolic measurements using indirect calorimetry were assessed after an overnight fast. Fasting lipid oxidation rates were calculated using standardized equations. Pre-pregnancy weight and final delivery weight were self-reported and used to calculate total GWG, which was then categorized as follows: inadequate (below the NAM guidelines), adequate (adhered to the NAM guidelines), or excess (exceeded the NAM guidelines). One-way ANOVA with post-hoc Tukey tests were used to compare lipid oxidation rates across GWG categories and correlation coefficients were used to assess the relationship between GWG and maternal lipid oxidation. RESULTS: Fasting lipid oxidation was significantly higher (p < 0.05) among women with excess GWG compared to women with adequate GWG. Absolute GWG was positively correlated to lipid oxidation (r = 0.507, p = 0.003). CONCLUSIONS: The results from this study indicate that fasting lipid oxidation may play an important role in GWG. A better understanding of the metabolic profile of women during pregnancy may be critical in truly understanding a woman’s risk of GWG outside the recommendations. Mounting evidence suggests that GWG counseling during prenatal care may need to be tailored to women based not just on their weight status, but other metabolic characteristic, in order to achieve GWG for optimal maternal health. Funding was provided by NIH NIGMS IDeA Grant 5P20GM103436 and WKU RCAP Grant 17-8011.