BACKGROUND: A "fit pregnancy" requires balancing energy expenditure with energy intake (EI) to achieve appropriate gestational weight gains (GWG), healthy infant birth weights (IBW), and minimal postpartum weight retention (PPWR). Our objective was to develop an integrated conceptual framework to assess the contribution of prepregnancy weight (PP-BMI), EI, and physical activity (PA) as determinants of GWG, IBW, and PPWR. METHODS: Pregnant women (n = 59) were recruited from prenatal classes. Energy intake was estimated using 3 24-hr diet recalls and PA using a validated PA questionnaire and a pedometer. Telephone interviews at 6-weeks postpartum assessed self-reported GWG, IBW, and PPWR. Hierarchical multiple regression analyses were used to explore the potential predictors of GWG, IBW, and PPWR. RESULTS: Prepregnancy BMI was associated with GWG, and EI was associated with IBW; each model captured only 6%-18% of the variability. In contrast, PPWR was predicted by PP-BMI, GWG, and EI, which together explained 61% of its variability, whereas GWG alone explained 51% of the variability in PPWR. CONCLUSIONS: Modeling the relationship using hierarchical models suggests that PP-BMI, prepartum PA, and EI differentially impact GWG, IBW, and PPWR.
BACKGROUND: A "fit pregnancy" requires balancing energy expenditure with energy intake (EI) to achieve appropriate gestational weight gains (GWG), healthy infant birth weights (IBW), and minimal postpartum weight retention (PPWR). Our objective was to develop an integrated conceptual framework to assess the contribution of prepregnancy weight (PP-BMI), EI, and physical activity (PA) as determinants of GWG, IBW, and PPWR. METHODS: Pregnant women (n = 59) were recruited from prenatal classes. Energy intake was estimated using 3 24-hr diet recalls and PA using a validated PA questionnaire and a pedometer. Telephone interviews at 6-weeks postpartum assessed self-reported GWG, IBW, and PPWR. Hierarchical multiple regression analyses were used to explore the potential predictors of GWG, IBW, and PPWR. RESULTS: Prepregnancy BMI was associated with GWG, and EI was associated with IBW; each model captured only 6%-18% of the variability. In contrast, PPWR was predicted by PP-BMI, GWG, and EI, which together explained 61% of its variability, whereas GWG alone explained 51% of the variability in PPWR. CONCLUSIONS: Modeling the relationship using hierarchical models suggests that PP-BMI, prepartum PA, and EI differentially impact GWG, IBW, and PPWR.
Authors: Barbara E Ainsworth; Colleen Keller; Stephen Herrmann; Michael Belyea; Kathryn Records; Allison Nagle-Williams; Sonia Vega-López; Paska Permana; Dean V Coonrod Journal: Med Sci Sports Exerc Date: 2013-07 Impact factor: 5.411