Literature DB >> 22170365

Dynamic energy-balance model predicting gestational weight gain.

Diana M Thomas1, Jesus E Navarro-Barrientos, Daniel E Rivera, Steven B Heymsfield, Carl Bredlau, Leanne M Redman, Corby K Martin, Sally A Lederman, Linda M Collins, Nancy F Butte.   

Abstract

BACKGROUND: 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.
OBJECTIVE: 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.
DESIGN: 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.
RESULTS: 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.
CONCLUSIONS: 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.

Entities:  

Mesh:

Year:  2011        PMID: 22170365      PMCID: PMC3238455          DOI: 10.3945/ajcn.111.024307

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  25 in total

1.  Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids.

Authors:  Paula Trumbo; Sandra Schlicker; Allison A Yates; Mary Poos
Journal:  J Am Diet Assoc       Date:  2002-11

2.  The cross-sectional and longitudinal dependence of the resting metabolic rate on the fat-free mass.

Authors:  Seymour S Alpert
Journal:  Metabolism       Date:  2007-03       Impact factor: 8.694

3.  Longitudinal assessment of energy expenditure in pregnancy by the doubly labeled water method.

Authors:  G R Goldberg; A M Prentice; W A Coward; H L Davies; P R Murgatroyd; C Wensing; A E Black; M Harding; M Sawyer
Journal:  Am J Clin Nutr       Date:  1993-04       Impact factor: 7.045

4.  Pre-pregnancy body mass index and weight gain during pregnancy: relations with gestational diabetes and hypertension, and birth outcomes.

Authors:  B Heude; O Thiébaugeorges; V Goua; A Forhan; M Kaminski; B Foliguet; M Schweitzer; G Magnin; M A Charles
Journal:  Matern Child Health J       Date:  2012-02

5.  Changes in basal metabolic rate during pregnancy in relation to changes in body weight and composition, cardiac output, insulin-like growth factor I, and thyroid hormones and in relation to fetal growth.

Authors:  Marie Lof; Hanna Olausson; Karin Bostrom; Birgitta Janerot-Sjöberg; Annica Sohlstrom; Elisabet Forsum
Journal:  Am J Clin Nutr       Date:  2005-03       Impact factor: 7.045

6.  Predicting metabolic adaptation, body weight change, and energy intake in humans.

Authors:  Kevin D Hall
Journal:  Am J Physiol Endocrinol Metab       Date:  2009-11-24       Impact factor: 4.310

7.  Composition of gestational weight gain impacts maternal fat retention and infant birth weight.

Authors:  Nancy F Butte; Kenneth J Ellis; William W Wong; Judy M Hopkinson; E O'Brian Smith
Journal:  Am J Obstet Gynecol       Date:  2003-11       Impact factor: 8.661

Review 8.  Estimation of energy expenditure, net carbohydrate utilization, and net fat oxidation and synthesis by indirect calorimetry: evaluation of errors with special reference to the detailed composition of fuels.

Authors:  G Livesey; M Elia
Journal:  Am J Clin Nutr       Date:  1988-04       Impact factor: 7.045

9.  Chemical and elemental analysis of humans in vivo using improved body composition models.

Authors:  S B Heymsfield; M Waki; J Kehayias; S Lichtman; F A Dilmanian; Y Kamen; J Wang; R N Pierson
Journal:  Am J Physiol       Date:  1991-08

10.  Associations of gestational weight gain with maternal body mass index, waist circumference, and blood pressure measured 16 y after pregnancy: the Avon Longitudinal Study of Parents and Children (ALSPAC).

Authors:  Abigail Fraser; Kate Tilling; Corrie Macdonald-Wallis; Rachael Hughes; Naveed Sattar; Scott M Nelson; Debbie A Lawlor
Journal:  Am J Clin Nutr       Date:  2011-04-06       Impact factor: 7.045

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  33 in total

1.  Evidence-based recommendations for energy intake in pregnant women with obesity.

Authors:  Jasper Most; Marshall St Amant; Daniel S Hsia; Abby D Altazan; Diana M Thomas; L Anne Gilmore; Porsha M Vallo; Robbie A Beyl; Eric Ravussin; Leanne M Redman
Journal:  J Clin Invest       Date:  2019-08-01       Impact factor: 14.808

2.  Food Photography Is Not an Accurate Measure of Energy Intake in Obese, Pregnant Women.

Authors:  Jasper Most; Porsha M Vallo; Abby D Altazan; Linda Anne Gilmore; Elizabeth F Sutton; Loren E Cain; Jeffrey H Burton; Corby K Martin; Leanne M Redman
Journal:  J Nutr       Date:  2018-04-01       Impact factor: 4.798

3.  Application of mathematical models in the management of obesity during pregnancy and the postpartum period in reproductive age women.

Authors:  L Anne Gilmore; Leanne M Redman
Journal:  Nutr Res       Date:  2019-03-27       Impact factor: 3.315

4.  Hybrid Model Predictive Control for Optimizing Gestational Weight Gain Behavioral Interventions.

Authors:  Yuwen Dong; Daniel E Rivera; Danielle S Downs; Jennifer S Savage; Diana M Thomas; Linda M Collins
Journal:  Proc Am Control Conf       Date:  2013

Review 5.  Predictive Mathematical Models of Weight Loss.

Authors:  Diana M Thomas; Michael Scioletti; Steven B Heymsfield
Journal:  Curr Diab Rep       Date:  2019-08-31       Impact factor: 4.810

6.  A Dynamical Systems Model of Intrauterine Fetal Growth.

Authors:  Mohammad T Freigoun; Daniel E Rivera; Penghong Guo; Emily E Hohman; Alison D Gernand; Danielle Symons Downs; Jennifer S Savage
Journal:  Math Comput Model Dyn Syst       Date:  2018-10-07       Impact factor: 0.945

7.  Semi-physical Identification and State Estimation of Energy Intake for Interventions to Manage Gestational Weight Gain.

Authors:  Penghong Guo; Daniel E Rivera; Danielle S Downs; Jennifer S Savage
Journal:  Proc Am Control Conf       Date:  2016-08-01

8.  A "Model-on-Demand" Methodology For Energy Intake Estimation to Improve Gestational Weight Control Interventions.

Authors:  Penghong Guo; Daniel E Rivera; Abigail M Pauley; Krista S Leonard; Jennifer S Savage; Danielle S Downs
Journal:  Proc IFAC World Congress       Date:  2018-10-08

9.  Propensity for adverse pregnancy outcomes in African-American women may be explained by low energy expenditure in early pregnancy.

Authors:  Jasper Most; L Anne Gilmore; Abby D Altazan; Marshall St Amant; Robbie A Beyl; Eric Ravussin; Leanne M Redman
Journal:  Am J Clin Nutr       Date:  2018-06-01       Impact factor: 7.045

10.  An objective estimate of energy intake during weight gain using the intake-balance method.

Authors:  L Anne Gilmore; Eric Ravussin; George A Bray; Hongmei Han; Leanne M Redman
Journal:  Am J Clin Nutr       Date:  2014-07-23       Impact factor: 7.045

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