TY - JOUR
T1 - Do Women Know Their Prepregnancy Weight?
AU - Thomas, Diana M.
AU - Oken, Emily
AU - Rifas-Shiman, Sheryl L.
AU - Téllez-Rojo, Martha
AU - Just, Allan
AU - Svensson, Katherine
AU - Deierlein, Andrea L.
AU - Chandler-Laney, Paula C.
AU - Miller, Richard C.
AU - McNamara, Christopher
AU - Phelan, Suzanne
AU - Yoshitani, Shaw
AU - Butte, Nancy F.
AU - Redman, Leanne M.
N1 - Publisher Copyright:
© 2019 The Obesity Society
PY - 2019/7
Y1 - 2019/7
N2 - 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.
AB - 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.
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U2 - 10.1002/oby.22502
DO - 10.1002/oby.22502
M3 - Article
C2 - 31149770
AN - SCOPUS:85066463977
SN - 1930-7381
VL - 27
SP - 1161
EP - 1167
JO - Obesity
JF - Obesity
IS - 7
ER -