Prepregnancy weight loss and maternal metabolic and inflammatory biomarkers during pregnancy: An analysis of National Health and Nutrition Examination Survey

Abstract

AbstractAimWomen with overweight or obesity are recommended to lose weight before conception to optimize pregnancy outcomes. However, the obstetrical implications of prepregnancy weight loss have been minimally examined. The objective of this study was to investigate the association between prepregnancy weight loss and maternal metabolic and inflammatory profiles during a subsequent pregnancy.MethodsThis study was a retrospective analysis of National Health and Nutrition Examination Survey data (2003–2018). Participants were women who were pregnant at the time of assessment. Prepregnancy weight loss was described as percent weight change based on self‐reported baseline (1 year before pregnancy) and prepregnancy weight. Metabolic (e.g., blood pressure [BP]) and inflammatory biomarkers (i.e., high‐sensitivity C‐reactive protein [hs‐CRP]) were determined by standard medical tests. Statistical analyses included linear regressions with appropriate imputation, weighting, and variance estimation techniques.ResultsParticipants (N = 236) reported a mean percent weight loss of 4.6% (standard error [SE] = 0.3%) during the year before pregnancy. Regression models showed that prepregnancy weight loss was inversely associated with levels of total cholesterol (β = −1.24, p = 0.01), low‐density lipoprotein‐cholesterol (β = −0.79, p < 0.01), and high‐density lipoprotein‐cholesterol (β = −0.18, p < 0.01). The effect of prepregnancy weight loss on BP, insulin sensitivity, and hs‐CRP was not significant, although there was a trend toward higher levels of diastolic BP (β = 0.24, p = 0.07) and hs‐CRP (β = 0.10, p = 0.08).ConclusionsThis study found favorable changes in lipid profiles following prepregnancy weight loss. Due to limitations such as a relatively small sample size, self‐reported weight measures, and missing data on several outcome variables, future studies are needed to confirm study findings.