Location: Children's Nutrition Research CenterTitle: Do women know their prepregnancy weight?
|THOMAS, DIANA - Us Military Academy|
|OKEN, EMILY - Harvard Medical School|
|RIFAS-SHIMAN, SHERYL - Harvard Medical School|
|TELLEZ-ROJO, MARTHA - Instituto Nacional De Medicina Genómica (INMEGEN), Secretaría De Salud, Distrito Federal, México C|
|JUST, ALLAN - The Icahn School Of Medicine At Mount Sinai|
|SVENSSON, KATHERINE - The Icahn School Of Medicine At Mount Sinai|
|DEIERLEIN, ANDREA - New York University|
|CHANDLER-LANEY, PAULA - University Of Alabama|
|MILLER, RICHARD - St Barnabas Medical Center|
|MCNAMARA, CHRISTOPHER - Saint Georges University|
|PHELAN, SUZANNE - California Polytechnic State University|
|YOSHITANI, SHAW - Us Military Academy|
|BUTTE, NANCY - Children'S Nutrition Research Center (CNRC)|
|REDMAN, LEANNE - Pennington Biomedical Research Center|
Submitted to: Obesity
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/14/2019
Publication Date: 5/31/2019
Citation: Thomas, D.M., Oken, E., Rifas-Shiman, S.L., Tellez-Rojo, M., Just, A., Svensson, K., Deierlein, A.L., Chandler-Laney, P.C., Miller, R.C., McNamara, C., Phelan, S., Yoshitani, S., Butte, N.F., Redman, L.M. 2019. Do women know their prepregnancy weight? Obesity. 27:1161-1167. https://doi.org/10.1002/oby.22502.
Interpretive Summary: Current weight gain guidelines for pregnant women are based on prepregnancy weight. In some cases, women do not know their pregnancy weight accurately. Misclassification of the prepregnancy weight status may result in erroneous clinical counseling and excess gestation weight gain that could cause adverse outcomes such as gestational diabetes, labor and delivery problems and abnormal fetal growth. We developed and validated a regression model predicting prepregnancy weight. This tool will aid clinicians and health care providers to properly classify pregnant women and counsel patients on the appropriate amount of weight gain during pregnancy.
Technical Abstract: Prepregnancy weight may not always be known to women. A model was developed to estimate prepregnancy weight from measured pregnancy weight. 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. 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/). 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.