Do Women Know Their Prepregnancy Weight?

Diana M. Thomas, Emily Oken, Sheryl L. Rifas-Shiman, Martha Téllez-Rojo, Allan Just, Katherine Svensson, Andrea L. Deierlein, Paula C. Chandler-Laney, Richard C. Miller, Christopher McNamara, Suzanne Phelan, Shaw Yoshitani, Nancy F. Butte, Leanne M. Redman

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Prepregnancy weight may not always be known to women. A model was developed to estimate prepregnancy weight from measured pregnancy weight. Methods: The model was developed and validated using participants from two studies (Project Viva, n = 301, model development; and Fit for Delivery [FFD], n = 401, model validation). Data from the third study (Programming Research in Obesity, Growth, Environment and Social Stressors [PROGRESS]), which included women from Mexico City, were used to demonstrate the utility of the newly developed model to objectively quantify prepregnancy weight. Results: The model developed from the Project Viva study validated well with low bias (R2 = 0.95; y = 1.02x − 0.69; bias = 0.68 kg; 95% CI: −4.86 to 6.21). Predictions in women from FFD demonstrated good agreement (R2 = 0.96; y = 0.96x + 4.35; bias = 1.60 kg; 95% CI: −4.40 to 7.54; error range = −11.25 kg to 14.73 kg). High deviations from model predictions were observed in the Programming Research in PROGRESS (R2 = 0.81; y = 0.89x + 9.61; bias = 2.83 kg; 95% CI: −7.70 to 12.31; error range = −39.17 kg to 25.73 kg). The model was programmed into software (https://www.pbrc.edu/research-and-faculty/calculators/prepregnancy/). Conclusions: The developed model provides an alternative to determine prepregnancy weight in populations receiving routine health care that may not have accurate knowledge of prepregnancy weight. The software can identify misreporting and classification into incorrect gestational weight gain categories.

Original languageEnglish (US)
Pages (from-to)1161-1167
Number of pages7
JournalObesity
Volume27
Issue number7
DOIs
StatePublished - Jul 2019

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Nutrition and Dietetics

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