Energy Expenditure in Pregnant Women with Obesity Does Not Support Energy Intake Recommendations

Jasper Most, Porsha M Vallo, L Anne Gilmore, Marshall St Amant, Daniel S Hsia, Abby D Altazan, Robbie A Beyl, Eric Ravussin, Leanne M Redman, Jasper Most, Porsha M Vallo, L Anne Gilmore, Marshall St Amant, Daniel S Hsia, Abby D Altazan, Robbie A Beyl, Eric Ravussin, Leanne M Redman

Abstract

Objective: This study aimed to identify factors that may predispose women to excess gestational weight gain (GWG).

Methods: Seventy-two healthy women with obesity (30 class I, 24 class II, 18 class III) expecting a singleton pregnancy were studied at 13 to 16 weeks gestation. Energy expenditure (EE) was measured during sleep (SleepEE, average EE from 0200-0500 hours) in a whole-room calorimeter, and total daily EE (TDEE) over 7 days using doubly labeled water. Glucose, insulin, thyroid hormones, and catecholamines were measured.

Results: Body composition explained 70% variability in SleepEE, and SleepEE accounted for 67% to 73% of TDEE. Though there was no evidence of consistent low metabolism, there was considerable variability. Low SleepEE was associated with insulin resistance and low triiodothyronine concentrations (both P = 0.01). Physical activity level was 1.47 ± 0.02. For women with SleepEE within 100 kcal/d of their predicted EE, TDEE was significantly less than the estimate (2,530 ± 91 vs. 2,939 kcal/d; P < 0.001) provided from the most recent gestational energy requirement model.

Conclusions: Pregnant women with obesity are inactive, possibly predisposing them to excess GWG. Current energy requirement models overestimate activity and may promote excess GWG in women with obesity. Furthermore, the observed large interindividual variability in basal metabolism may be important to consider when assessing the risk for excess GWG.

Trial registration: ClinicalTrials.gov NCT01954342.

Conflict of interest statement

Disclosures: The authors declared no conflict of interest.

© 2018 The Obesity Society.

Figures

Figure 1
Figure 1
Correlations between fat-free mass, sleeping and total daily energy expenditure (A, C, E) and residuals for total daily energy expenditure (TDEE, B), sleeping EE (SleepEE, D), and activity-related EE (AREE, F), by obesity class. Each data point represents one participant. For residual SleepEE, -100 kcal/d and 100 kcal/d are used to identify low and high metabolism.
Figure 2
Figure 2
Correlations between residual SleepEE, thyroid hormone T3 and insulin resistance. Each data point represents one participant. Subjects classified as having low, average and high metabolic rates are presented as open, grey and black circles, respectively. Regression lines are significant (T3: R2=0.15, and HOMA-IR: R2=0.17, both p<0.001).

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Source: PubMed

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