|Thomas, Diana -|
|Navarro-Barrientos, Jesus -|
|Rivera, Daniel -|
|Heymsfield, Steven -|
|Bredlau, Carl -|
|Redman, Leanne -|
|Martin, Corby -|
|Lederman, Sally -|
|Collins, Linda -|
|Butte, Nancy -|
Submitted to: American Journal of Clinical Nutrition
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 14, 2011
Publication Date: January 1, 2012
Citation: Thomas, D., Navarro-Barrientos, J.E., Rivera, D.E., Heymsfield, S.B., Bredlau, C., Redman, L.M., Martin, C.K., Lederman, S.A., Collins, L.M., Butte, N.F. 2012. Dynamic energy-balance model predicting gestational weight gain. American Journal of Clinical Nutrition. 95(1):115-122. Interpretive Summary: Adequate weight gain during pregnancy is important for optimal infant and maternal outcomes. We developed a new mathematical model that can help pregnant women stay within their appropriate weight-gain range. The idea is that this model can inform women how much energy intake is required for them to stay within their recommended pregnancy weight gain range. A web-based app was developed that requires the input of the woman's preconception age, height, and weight. By varying the energy intake at a given trimester, the model will predict the resulting weight gain. This will be a very useful tool for counseling pregnant women by physicians, dietitians, and other health professionals.
Technical Abstract: Gestational weight gains (GWGs) that exceed the 2009 Institute of Medicine recommended ranges increase risk of long-term postpartum weight retention; conversely, GWGs within the recommended ranges are more likely to result in positive maternal and fetal outcomes. Despite this evidence, recent epidemiologic studies have shown that the majority of pregnant women gain outside the target GWG ranges. A mathematical model that predicts GWG and energy intake could provide a clinical tool for setting precise goals during early pregnancy and continuous objective feedback throughout pregnancy. The purpose of this study was to develop and validate a differential equation model for energy balance during pregnancy that predicts GWG that results from changes in energy intakes. A set of prepregnancy BMI–dependent mathematical models that predict GWG were developed by using data from a longitudinal study that measured gestational-changes in fat-free mass, fat mass, total body water, and total energy expenditure in 63 subjects. Mathematical models developed for women with low, normal, and high prepregnancy BMI were shown to fit the original data. In 2 independent studies used for validation, model predictions of fat-free mass, fat mass, and total body water matched actual measurements within 1 kg. Our energy-balance model provides plausible predictions of GWG that results from changes in energy intakes. Because the model was implemented as a Web-based applet, it can be widely used by pregnant women and their health care providers.