Metabolic adaptation is not observed after 8 weeks of overfeeding but energy expenditure variability is associated with weight recovery.

BACKGROUND: A metabolic adaptation, defined as an increase in energy expenditure (EE) beyond what is expected with weight gain during overfeeding (OF), has been reported but also refuted. Much of the inconsistency stems from the difficulty in conducting large, well-controlled OF studies in humans. OBJECTIVES: The primary aim of this study was to determine whether a metabolic adaptation to OF exists and if so, attenuates weight gain. METHODS: Thirty-five young adults consumed 40% above their baseline energy requirements for 8 wk, and sleeping metabolic rate (SMR) and 24-h sedentary energy expenditure (24h-EE) were measured before and after OF. Subjects were asked to return for a 6-mo post-OF follow-up visit to measure body weight, body composition, and physical activity. RESULTS: After adjusting for gains in fat-free mass and fat mass, SMR increased by 43 ± 123 kcal/d more than expected (P = 0.05) and 24h-EE by 23 ± 139 kcal/d (P = 0.34), indicating an overall lack of metabolic adaptation during OF despite a wide variability in the response. Among the 30 subjects who returned for the 6-mo follow-up visit, those who had a lower-than-predicted SMR (basal EE) retained more of the fat gained during OF. Likewise, subjects displaying a higher-than-predicted sedentary 24h-EE lost significantly more fat during the 6-mo follow-up. CONCLUSIONS: Metabolic adaptation to OF was on average very small but variable between subjects, revealing "thrifty" or "spendthrift" metabolic phenotypes related to body weight loss 6 mo later. This trial was registered at clinicaltrials.gov as NCT01672632.

Determinants of sedentary 24-h energy expenditure: equations for energy prescription and adjustment in a respiratory chamber.

BACKGROUND: Achieving energy balance is critical for the interpretation of results obtained in respiratory chambers. However, 24-h energy expenditure (24EE) predictions based on estimated resting metabolic rate and physical activity level are often inaccurate and imprecise. OBJECTIVE: We aimed to develop and validate equations to better achieve energy balance in a respiratory chamber by adding or subtracting food items. DESIGN: By using a randomized data set with measures of 24EE (n = 241) performed at the Pennington Biomedical Research Center, we developed equations to predict 24EE from anthropometric, demographic, and body composition variables before and at 3 and 7 h into the chamber measurement. The equations were tested on an independent data set (n = 240) and compared with published predictive equations. RESULTS: By using anthropometric and demographic variables, the equation was as follows: 24EE (kcal/d) = 11.6 [weight (kg)] + 8.03 [height (cm)] - 3.45 [age (y)] + 217 (male) - 52 (African American) - 235. The mean prediction error was -9 ± 155 kcal/d (2046 ± 305 compared with 2055 ± 343 kcal/d for measured 24EE; P = 0.36). The prediction achieved a precision of ±10% of measured 24EE in 83% of the participants. Energy prescription was then refined by equations with the use of energy expenditure values after 3 h, 7 h, or both into the chamber study. These later equations improved the precision (±10% of measured 24EE) to 92% (P = 0.003) and 96% (P < 0.0001) of the participants at 3 and 7 h, respectively. Body composition did not improve 24EE predictions. CONCLUSIONS: We showed the use of a set of equations to prescribe and adjust energy intake to achieve energy balance in respiratory chambers over 24 h. These equations may be used in most respiratory chambers and modified to accommodate exercise or specific feeding protocols.

Accuracy of armband monitors for measuring daily energy expenditure in healthy adults.

INTRODUCTION: There is a need to develop accurate devices for measuring daily energy expenditure under free-living conditions, particularly given our current obesity epidemic. PURPOSE: The purpose of the present study was to evaluate the validity of energy expenditure estimates from two portable armband devices, the SenseWear Pro3 Armband (SWA) monitor and the SenseWear Mini Armband (Mini) monitor, under free-living conditions. METHODS: Participants in the study (30 healthy adults aged 24-60 yr) wore both monitors for 14 consecutive days, including while sleeping. Criterion values for total energy expenditure (TEE) were determined using doubly labeled water (DLW), the established criterion standard method for free-living energy expenditure assessment. RESULTS: The average TEE estimates were within 112 kcal·d−¹ for the SWA and within 22 kcal·d−¹ for the Mini, but the absolute error rates (computed as the average absolute value of the individual errors) were similar for the two monitors (SWA = 8.1% ± 6.8%, Mini = 8.3% ± 6.5%). Using intraclass correlation (ICC) analysis, significant agreements were found between the SWA and DLW estimates of energy expenditure (ICC = 0.80, 95% CI = 0.89-0.70) and between the Mini and DLW (ICC = 0.85, 95% CI = 0.92-0.76). Graphical plots of the DLW TEE values against the difference between DLW and monitor estimates of TEE showed that the agreement was consistent across a range of TEE values. CONCLUSIONS: The SenseWear Pro3 and the SenseWear Mini armbands show promise for accurately measuring daily energy expenditure under free-living conditions. However, more work is needed to improve the ability of these monitors to accurately measure energy expenditure at higher levels of expenditure.

Differences in daily energy expenditure in lean and obese women: the role of posture allocation.

OBJECTIVE: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat-free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. METHODS AND PROCEDURES: Twenty healthy, non-smoking, pre-menopausal women (10 lean and 10 obese) participated in this 14-day observational study on free-living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X-ray absorptiometry (DXA). RESULTS: RMR was similar in the obese vs. lean women (1601 +/- 109 vs. 1505 +/- 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 +/- 3.2 h vs. 10.1 +/- 2.0 h, P < 0.05), stood 2 h less (2.7 +/- 1.0 h vs. 4.7 +/- 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 +/- 1.5 h vs. 5.4 +/- 1.9 h, P = 0.002). DISCUSSION: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.

The use of a handheld calorimetry unit to estimate energy expenditure during different physiological conditions.

BACKGROUND: Accurately determining rates of energy expenditure (EE) under free-living conditions is important in understanding the mechanisms involved in the development and prevention of obesity. Metabolic carts are not portable enough for most free-living situations. The purpose of this study was to compare a portable, handheld indirect calorimetry device (HealtheTech Incorporated, Golden, CO) to a metabolic cart (Physio-Dyne Instrument Corporation, Quogue, NY) during 3 different physiologic states. METHODS: EE was measured by both the handheld calorimeter (5-10 minutes) and the metabolic cart (15-20 minutes) in 20 healthy subjects (18-35 years of age). Measurements were made during 3 physiologic states: (1) postabsorptive rest (REE), (2) postprandial rest (fed energy expenditure, FEE), and (3) while walking in place (activity energy expenditure, AEE). RESULTS: There were no significant differences between the means of the cart vs the hand-held device for REE (mean +/- SE; kcal/d; 1552 +/- 64 vs 1551 +/- 63), FEE (1875 +/- 99 vs 1825 +/- 86), and AEE (3333 +/- 218 vs 3489 +/- 152). The range over which the techniques were tested was 1300-5000 kcal/d. The agreement between the 2 methods was excellent for REE (0.80, p < .0001), FEE (0.89, p < .0001), and AEE (0.75, p < .0002). CONCLUSIONS: Compared with the metabolic cart, the handheld device provided similar estimates of energy expenditure during resting, postprandial, and physically active states. This suggests that portable indirect calorimetry devices can provide reliable and valuable information in free-living research situations for which maximal energy expenditure is <5000 kcal/d.