Effect of calorie restriction on resting metabolic rate and spontaneous physical activity

Objective: It is unclear if resting metabolic rate (RMR) and spontaneous physical activity (SPA) decrease in weight‐reduced non‐obese participants. Additionally, it is unknown if changes in SPA, measured in a respiratory chamber, reflect changes in free‐living physical activity level (PAL). Research Methods and Procedures: Participants (N = 48) were randomized into 4 groups for 6 months: calorie restriction (CR, 25% restriction), CR plus structured exercise (CR+EX, 12.5% restriction plus 12.5% increased energy expenditure via exercise), low‐calorie diet (LCD, 890 kcal/d supplement diet until 15% weight loss, then weight maintenance), and control (weight maintenance). Measurements were collected at baseline, Month 3, and Month 6. Body composition and RMR were measured by DXA and indirect calorimetry, respectively. Two measures of SPA were collected in a respiratory chamber (percent of time active and kcal/d). Free‐living PAL (PAL = total daily energy expenditure by doubly labeled water/RMR) was also measured. Regression equations at baseline were used to adjust RMR for fat‐free mass and SPA (kcal/d) for body weight. Results: Adjusted RMR decreased at Month 3 in the CR group and at Month 6 in the CR+EX and LCD groups. Neither measure of SPA decreased significantly in any group. PAL decreased at Month 3 in the CR and LCD groups, but not in the CR+EX group, who engaged in structured exercise. Changes in SPA in the chamber and free‐living PAL were not related. Discussion: Body weight is defended in non‐obese participants during modest caloric restriction, evidenced by metabolic adaptation of RMR and reduced energy expenditure through physical activity.     

Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due to a difference in RMR while AEE levels were similar in both groups, even though female mice were more active. Interestingly, the higher activity did not result in a difference in AEE because female mice had a lower caloric cost of activity, which was likely due to their lower body weight. In conclusion, TEE decomposition by means of penalised spline regression provides robust estimates of the time-dependent AEE and RMR and can be applied to data generated with generic metabolic chamber and indirect calorimetry set-ups.     

Is the ArteACC Index a Valid Indicator of Free‐Living Physical Activity in Adolescents?

Objective: The principal aim of this study was to validate a proposed new index of physical activity, the activity‐related time equivalent based on accelerometry (ArteACC), in adolescents. A secondary aim was to develop regression equations for prediction of total energy expenditure (TEE) and activity energy expenditure [AEE = 0.9 × TEE ? resting metabolic rate (RMR)]. Research Methods and Procedures: RMR and energy expenditure (EE) under standardized exercises were measured by indirect calorimetry in 36 adolescents (14 to 19 years old). TEE was measured by the doubly labeled water method, and physical activity was assessed simultaneously with an accelerometer for 14 days. AEE, AEE in relation to body weight (AEE per kilogram), and activity‐related time equivalent based on energy expenditure (ArteEE = AEE/[EE reference activity ? RMR]) were calculated from laboratory and free‐living EE data. ArteACC was calculated as total activity counts/activity counts of reference activity. Results: ArteACC was significantly related to AEE per kilogram (r = 0.57; p < 0.0001) and ArteEE (r = 0.68; p < 0.001). The absolute amount of time (minutes per day) spent in physical activity was significantly lower when calculated from ArteACC than from ArteEE (p < 0.001). TEE was significantly influenced by RMR, sex, and ArteACC (r² = 0.89). AEE was significantly influenced by sex and ArteACC (r² = 0.59). Discussion: Despite an absolute difference between the two indexes, ArteEE and ArteACC, ArteACC seems to be a valid indicator of free‐living physical activity. It contributed significantly, by 3.3% and 12.5%, to the explained variations in TEE and AEE, respectively.     

Resistance training increases total energy expenditure and free-living physical activity in older adults.

The purpose of this study was to determine what effects 26 wk of resistance training have on resting energy expenditure (REE), total free-living energy expenditure (TEE), activity-related energy expenditure (AEE), engagement in free-living physical activity as measured by the activity-related time equivalent (ARTE) index, and respiratory exchange ratio (RER) in 61- to 77-yr-old men (n = 8) and women (n = 7). Before and after training, body composition (four-compartment model), strength, REE, TEE (doubly labeled water), AEE (TEE - REE + thermic response to meals), and ARTE (AEE adjusted for energy cost of standard activities) were evaluated. Strength (36%) and fat-free mass (2 kg) significantly increased, but body weight did not change. REE increased 6.8%, whereas resting RER decreased from 0.86 to 0.83. TEE (12%) and ARTE (38%) increased significantly, and AEE (30%) approached significance (P = 0.06). The TEE increase remained significant even after adjustment for the energy expenditure of the resistance training. In response to resistance training, TEE increased and RER decreased. The increase in TEE occurred as a result of increases in both REE and physical activity. These results suggest that resistance training may have value in increasing energy expenditure and lipid oxidation rates in older adults, thereby improving their metabolic profiles.     

Approaches for quantifying energy intake and %calorie restriction during calorie restriction interventions in humans: the multicenter CALERIE study

Calorie restriction (CR) is a component of most weight loss interventions and a potential strategy to slow aging. Accurate determination of energy intake and %CR is critical when interpreting the results of CR interventions; this is most accurately achieved using the doubly labeled water method to quantify total energy expenditure (TEE). However, the costs and analytical requirements of this method preclude its repeated use in many clinical trials. Our aims were to determine 1) the optimal TEE assessment time points for quantifying average energy intake and %CR during long-term CR interventions and 2) the optimal approach for quantifying short-term changes in body energy stores to determine energy intake and %CR during 2-wk DLW periods. Adults randomized to a CR intervention in the multicenter CALERIE study underwent measurements of TEE by doubly labeled water and body composition at baseline and months 1, 3, and 6. Average %CR achieved during the intervention was 24.9 ± 8.7%, which was computed using an approach that included four TEE assessment time points (i.e., TEE(baseline, months 1, 3, and 6)) plus the 6-mo change in body composition. Approaches that included fewer TEE assessments yielded %CR values of 23.4 ± 9.0 (TEE(baseline,) months 3 and 6), 25.0 ± 8.7 (TEE(baseline,) months 1 and 6), and 20.9 ± 7.1% (TEE(baseline, month 6)); the latter approach differed significantly from approach 1 (P < 0.001). TEE declined 9.6 ± 9.9% within 2-4 wk of CR beginning and then stabilized. Regression of daily home weights provided the most reliable estimate of short-term change in energy stores. In summary, optimal quantification of energy intake and %CR during weight loss necessitates a TEE measurement within the first month of CR to capture the rapid reduction in TEE.     

Muscle metabolic function and free-living physical activity.

We have previously shown that muscle metabolic function measured during exercise is related to exercise performance and subsequent 1-yr weight gain. Because it is well established that physical activity is important in weight maintenance, we examined muscle function relationships with free-living energy expenditure and physical activity. Subjects were 71 premenopausal black and white women. Muscle metabolism was evaluated by (31)P magnetic resonance spectroscopy during 90-s isometric plantar flexion contractions (45% maximum). Free-living energy expenditure (TEE) was measured using doubly labeled water, activity-related energy expenditure (AEE) was calculated as 0.9 x TEE - sleeping energy expenditure from room calorimetry, and free-living physical activity (ARTE) was calculated by dividing AEE by energy cost of standard physical activities. At the end of exercise, anaerobic glycolytic rate (ANGLY) and muscle concentration of phosphomonoesters (PME) were negatively related to TEE, AEE, and ARTE (P < 0.05). Multiple regression analysis showed that both PME (partial r = -0.29, <0.02) and ANGLY (partial r = -0.24, P < 0.04) were independently related to ARTE. PME, primarily glucose-6-phosphate and fructose-6-phosphate, was significantly related to ratings of perceived exertion (r = 0.21, P < or = 0.05) during a maximal treadmill test. PME was not related to ARTE after inclusion of RPE in the multiple regression model, suggesting that PME may be obtaining its relationship with ARTE through an increased perception of effort during physical activity. In conclusion, physically inactive individuals tend to be more dependent on anaerobic glycolysis during exercise while relying on a glycolytic pathway that may not be functioning optimally.     

Pubertal alterations in growth and body composition. V. Energy expenditure, adiposity, and fat distribution

We determined whether activity energy expenditure (AEE, from doubly labeled water and indirect calorimetry) or physical activity [7-day physical activity recall (PAR)] was more related to adiposity and the validity of PAR estimated total energy expenditure (TEE(PAR)) in prepubertal and pubertal boys (n = 14 and 15) and girls (n = 13 and 18). AEE, but not physical activity hours, was inversely related to fat mass (FM) after accounting for the fat-free mass, maturation, and age (partial r = -0.35, P < or = 0.01). From forward stepwise regression, pubertal maturation, AEE, and gender predicted FM (r(2) = 0.36). Abdominal visceral fat and subcutaneous fat were not related to AEE or activity hours after partial correlation with FM, maturation, and age. When assuming one metabolic equivalent (MET) equals 1 kcal. kg body wt(-1). h(-1), TEE(PAR) underestimated TEE from doubly labeled water (TEE bias) by 555 kcal/day +/- 2 SD limits of agreement of 913 kcal/day. The measured basal metabolic rate (BMR) was >1 kcal. kg body wt(-1). h(-1) and remained so until 16 yr of age. TEE bias was reduced when setting 1 MET equal to the measured (bias = 60 +/- 51 kcal/day) or predicted (bias = 53 +/- 50 kcal/day) BMR but was not consistent for an individual child (+/- 2 SD limits of agreement of 784 and 764 kcal/day, respectively) or across all maturation groups. After BMR was corrected, TEE bias remained greatest in the prepubertal girls. In conclusion, in children and adolescents, FM is more strongly related to AEE than activity time, and AEE, pubertal maturation, and gender explain 36% of the variance in FM. PAR should not be used to determine TEE of individual children and adolescents in a research setting but may have utility in large population-based pediatric studies, if an appropriate MET value is used to convert physical activity data to TEE data.     

The effect of caloric restriction interventions on growth hormone secretion in nonobese men and women

Lifespan in rodents is prolonged by caloric restriction (CR) and by mutations affecting the somatotropic axis. It is not known if CR can alter the age‐associated decline in growth hormone (GH), insulin‐like growth factor (IGF)‐1 and GH secretion. To evaluate the effect of CR on GH secretory dynamics; forty‐three young (36.8 ± 1.0 years), overweight (BMI 27.8 ± 0.7) men (n = 20) and women (n = 23) were randomized into four groups; control = 100% of energy requirements; CR = 25% caloric restriction; CR + EX = 12.5% CR + 12.5% increase in energy expenditure by structured exercise; LCD = low calorie diet until 15% weight reduction followed by weight maintenance. At baseline and after 6 months, body composition (DXA), abdominal visceral fat (CT) 11 h GH secretion (blood sampling every 10 min for 11 h; 21:00–08:00 hours) and deconvolution analysis were measured. After 6 months, weight (control: ?1 ± 1%, CR: ?10 ± 1%, CR + EX: ?10 ± 1%, LCD: ?14 ± 1%), fat mass (control: ?2 ± 3%, CR: ?24 ± 3%, CR + EX: ?25 ± 3%, LCD: ?31 ± 2%) and visceral fat (control: ?2 ± 4%, CR: ?28 ± 4%, CR + EX: ?27 ± 3%, LCD: ?36 ± 2%) were significantly (P < 0.001) reduced in the three intervention groups compared to control. Mean 11 h GH concentrations were not changed in CR or control but increased in CR + EX (P < 0.0001) and LCD (P < 0.0001) because of increased secretory burst mass (CR + EX: 34 ± 13%, LCD: 27 ± 22%, P < 0.05) and amplitude (CR + EX: 34 ± 14%, LCD: 30 ± 20%, P < 0.05) but not to changes in secretory burst frequency or GH half‐life. Fasting ghrelin was significantly increased from baseline in all three intervention groups; however, total IGF‐1 concentrations were increased only in CR + EX (10 ± 7%, P < 0.05) and LCD (19 ± 4%, P < 0.001). A 25% CR diet for 6 months does not change GH, GH secretion or IGF‐1 in nonobese men and women.     

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.     

Pattern and cost of weight gain in previously obese women

Weight gain is common among postobese individuals, providing an opportunity to address the cost of weight regain on energy expenditure. We investigated the energy cost of weight regain over 1 yr in 28 women [age 39.5 +/- 1.3 (SE) yr; body mass index 24.2 +/- 0.5 kg/m(2)] with recent weight loss (>12 kg). Body composition, total energy expenditure (TEE) using doubly labeled water, resting metabolic rate (RMR), and thermic effect of a meal (TEM) were assessed at 0 and 12 mo. Metabolizable energy intake (MEI) was calculated from TEE and change in body composition. Fourteen women had a weight gain of 13.2 +/- 2.1 kg. Twelve-month cumulative excess MEI, calculated as the intake in excess of TEE at month 0, was 749 +/- 149 MJ. Of this, 462 +/- 83 MJ (62%) were stored as accrued tissue, and 287 +/- 72 MJ (38%) was increased TEE. Expressed per kilogram of body weight gain, the energy cost of weight gain was calculated to be 54.8 +/- 4.6 MJ/kg. Interestingly, weight regain time courses fell into three distinct patterns, possibly requiring varying countermeasures.     

Impact of 6‐month Caloric Restriction on Autonomic Nervous System Activity in Healthy,Overweight, Individuals

Caloric restriction (CR) increases maximum lifespan but the mechanisms are unclear. Dominance of the sympathetic nervous system (SNS) over the parasympathetic nervous system (PNS) has been shown to be a strong risk factor for cardiovascular disease. Obesity and aging are associated with increased SNS activity, and weight loss and/or exercise seem to have positive effects on this balance. We therefore evaluated the effect of different approaches of CR on autonomic function in 28 overweight individuals participating in the Comprehensive Assessment of Long‐term Effects of Reducing Intake of Energy (CALERIE) trial. Participants were randomized to either control, CR: 25% decrease in energy intake, CREX: 12.5% CR + 12.5% increase in energy expenditure, or LCD: low‐calorie diet until 15% weight reduction followed by weight maintenance. Autonomic function was assessed by spectral analysis of heart‐rate variability (HRV) while fasting and after a meal. Measurements were performed at baseline and 6 months. HR and SNS index decreased and PNS index increased in all intervention groups but reached significance only in CREX. HR and SNS index increased and PNS index decreased in response to the meal in all intervention groups. The results therefore suggest that weight loss improved SNS/PNS balance especially when CR is combined with exercise.     

Metabolic Differences in Response to a High-Fat vs. a High-Carbohydrate Diet

Energy expenditure was measured in a group of 7 subjects who received two isocaloric isonitrogenous diets for a period of 9–21 days with a 4–10-day break between diets. Diet 1 was a high-fat diet (83.5 ± 3.6% of total energy). Diet 2 was a high carbohydrate diet (83.1 ± 3.7% of total energy). Resting and postprandial resting metabolic rate were measured by open circuit indirect calorimetry 2–4 times during each metabolic period. Total energy expenditure (TEE) was measured by the doubly labeled water method over an 8–13-day period. The respiratory quotient was measured 2–4 hours after a meal during each metabolic period for the calculation of total energy expenditure by the doubly labeled water method. Levels of total T₃ (TT₃), T₃ uptake, free thyroid index and T₄ were measured at the end of each metabolic period. No significant changes in resting metabolic rate (RMR) were apparent on the two diets (1567 ± 426 kcal/d high-fat diet and 1503 ± 412 kcal/d high-carbohydrate diet n=7, p<0.15). Total energy expenditure measured in 5 subjects was significantly higher during the high-carbohydrate phase of the diet (2443 ± 422 vs. 2078 ± 482 kcal/d p<0.05). Activity estimated from TEE/RMR was greater on the high-carbohydrate diet but only approached statistical significance (p<0.06). Total T₃ was significantly lower and free thyroid index and T₃ uptake were significantly higher at the end of the high fat diet in comparison to the high-carbohydrate diet. These data suggest that individual tolerance to a high-fat diet varies considerably and may significantly lower TEE by changing levels of physical activity. The explanation for changes in thyroid hormone levels independent of changes in metabolic rate remains unclear.     

Estimation of Free‐Living Energy Expenditure Using a Novel Activity Monitor Designed to Minimize Obtrusiveness

The aim of this study was to investigate the ability of a novel activity monitor designed to be minimally obtrusive in predicting free‐living energy expenditure. Subjects were 18 men and 12 women (age: 41 ± 11 years, BMI: 24.4 ± 3 kg/m²). The habitual physical activity was monitored for 14 days using a DirectLife triaxial accelerometer for movement registration (Tracmor_D) (Philips New Wellness Solutions, Lifestyle Incubator, the Netherlands). Tracmor_D output was expressed as activity counts per day (Cnts/d). Simultaneously, total energy expenditure (TEE) was measured in free living conditions using doubly labeled water (DLW). Activity energy expenditure (AEE) and the physical activity level (PAL) were determined from TEE and sleeping metabolic rate (SMR). A multiple‐linear regression model predicted 76% of the variance in TEE, using as independent variables SMR (partial‐r² = 0.55, P < 0.001), and Cnts/d (partial r² = 0.21, P < 0.001). The s.e. of TEE estimates was 0.9 MJ/day or 7.4% of the average TEE. A model based on body mass (partial‐r² = 0.31, P < 0.001) and Cnts/d (partial‐r² = 0.23, P < 0.001) predicted 54% of the variance in TEE. Cnts/d were significantly and positively associated with AEE (r = 0.54, P < 0.01), PAL (r = 0.68, P < 0.001), and AEE corrected by body mass (r = 0.71, P < 0.001). This study showed that the Tracmor_D is a highly accurate instrument for predicting free‐living energy expenditure. The miniaturized design did not harm the ability of the instrument in measuring physical activity and in determining outcome parameters of physical activity such as TEE, AEE, and PAL.     

Estimating Activity‐related Energy Expenditure Under Sedentary Conditions Using a Tri‐axial Seismic Accelerometer

Activity‐related energy expenditure (AEE) is difficult to quantify, especially under sedentary conditions. Here, a model was developed using the detected type of physical activity (PA) and movement intensity (MI), based on a tri‐axial seismic accelerometer (DynaPort MiniMod; McRoberts B.V., The Hague, the Netherlands), with energy expenditure for PA as a reference. The relation between AEE (J/min/kg), MI, and the type of PA was determined for standardized PAs as performed in a laboratory including: lying, sitting, standing, and walking. AEE (J/min/kg) was calculated from total energy expenditure (TEE) and sleeping metabolic rate (SMR) as assessed with indirect calorimetry ((TEE × 0.9) ‐ SMR). Subsequently, the model was validated over 23‐h intervals in a respiration chamber. Subjects were 15 healthy women (age: 22 ± 2 years; BMI: 24.0 ± 4.0 kg/m²). Predicted AEE in the chamber was significantly related to measured AEE both within (r² = 0.81 ± 0.06, P < 0.00001) and between (r² = 0.70, P < 0.001) subjects. The explained variation in AEE by the model was higher than the explained variation by MI alone. This shows that a tri‐axial seismic accelerometer is a valid tool for estimating AEE under sedentary conditions.     

Weight-Loss Induced Changes in Physical Activity and Activity Energy Expenditure in Overweight and Obese Subjects before and after Energy Restriction

Activity energy expenditure (AEE) is the component of daily energy expenditure that is mainly influenced by the amount of physical activity (PA) and by the weight of the body displaced. This study aimed at analyzing the effect of weight loss on PA and AEE. The body weight and PA of 66 overweight and obese subjects were measured at baseline and after 12 weeks of 67% energy restriction. PA was measured using a tri-axial accelerometer for movement registration (Tracmor) and quantified in activity counts. Tracmor recordings were also processed using a classification algorithm to recognize 6 common activity types engaged in during the day. A doubly-labeled water validated equation based on Tracmor output was used to estimate AEE. After weight loss, body weight decreased by 13±4%, daily activity counts augmented by 9% (95% CI: +2%, +15%), and this increase was weakly associated with the decrease in body weight (R² = 7%; P<0.05). After weight loss subjects were significantly (P<0.05) less sedentary (–26 min/d), and increased the time spent walking (+11 min/d) and bicycling (+4 min/d). However, AEE decreased by 0.6±0.4 MJ/d after weight loss. On average, a 2-hour/day reduction of sedentary time by increasing ambulatory and generic activities was required to restore baseline levels of AEE. In conclusion, after weight loss PA increased but the related metabolic demand did not offset the reduction in AEE due to the lower body weight. Promoting physical activity according to the extent of weight loss might increase successfulness of weight maintenance.     

Metabolic and Behavioral Compensations in Response to Caloric Restriction: Implications for the Maintenance of Weight Loss

Background

Metabolic and behavioral adaptations to caloric restriction (CR) in free-living conditions have not yet been objectively measured.

Methodology and Principal Findings

Forty-eight (36.8±1.0 y), overweight (BMI 27.8±0.7 kg/m²) participants were randomized to four groups for 6-months; Control: energy intake at 100% of energy requirements; CR: 25% calorie restriction; CR+EX: 12.5% CR plus 12.5% increase in energy expenditure by structured exercise; LCD: low calorie diet (890 kcal/d) until 15% weight reduction followed by weight maintenance. Body composition (DXA) and total daily energy expenditure (TDEE) over 14-days by doubly labeled water (DLW) and activity related energy activity (AREE) were measured after 3 (M3) and 6 (M6) months of intervention. Weight changes at M6 were −1.0±1.1% (Control), −10.4±0.9% (CR), −10.0±0.8% (CR+EX) and −13.9±0.8% (LCD). At M3, absolute TDEE was significantly reduced in CR (−454±76 kcal/d) and LCD (−633±66 kcal/d) but not in CR+EX or controls. At M6 the reduction in TDEE remained lower than baseline in CR (−316±118 kcal/d) and LCD (−389±124 kcal/d) but reached significance only when CR and LCD were combined (−351±83 kcal/d). In response to caloric restriction (CR/LCD combined), TDEE adjusted for body composition, was significantly lower by −431±51 and −240±83 kcal/d at M3 and M6, respectively, indicating a metabolic adaptation. Likewise, physical activity (TDEE adjusted for sleeping metabolic rate) was significantly reduced from baseline at both time points. For control and CR+EX, adjusted TDEE (body composition or sleeping metabolic rate) was not changed at either M3 or M6.

Conclusions

For the first time we show that in free-living conditions, CR results in a metabolic adaptation and a behavioral adaptation with decreased physical activity levels. These data also suggest potential mechanisms by which CR causes large inter-individual variability in the rates of weight loss and how exercise may influence weight loss and weight loss maintenance.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00099151","term_id":"NCT00099151"}}NCT00099151     

Effect of 6-month calorie restriction and exercise on serum and liver lipids and markers of liver function

Objective: Nonalcoholic fatty liver disease (NAFLD) and its association with insulin resistance are increasingly recognized as major health burdens. The main objectives of this study were to assess the relation between liver lipid content and serum lipids, markers of liver function and inflammation in healthy overweight subjects, and to determine whether caloric restriction (CR) (which improves insulin resistance) reduces liver lipids in association with these same measures. Methods and Procedures: Forty‐six white and black overweight men and women (BMI = 24.7–31.3 kg/m²) were randomized to “control (CO)” = 100% energy requirements; “CR” = 25%; “caloric restriction and increased structured exercise (CR+EX)”= 12.5% CR + 12.5% increase in energy expenditure through exercise; or “low‐calorie diet (LCD)” = 15% weight loss by liquid diet followed by weight‐maintenance, for 6 months. Liver lipid content was assessed by magnetic resonance spectroscopy (MRS) and computed tomography (CT). Lipid concentrations, markers of liver function (alanine aminotransferase (ALT), alkaline phosphatase (ALK)), and whole‐body inflammation (tumor necrosis factor‐α (TNF‐α), interleukin‐6 (IL‐6), high‐sensitivity C‐reactive protein (hsCRP)) were measured in fasting blood. Results: At baseline, increased liver lipid content (by MRS) correlated (P < 0.05) with elevated fasting triglyceride (r = 0.52), ALT (r = 0.42), and hsCRP (r = 0.33) concentrations after adjusting for sex, race, and alcohol consumption. With CR, liver lipid content was significantly lowered by CR, CR+EX, and LCD (detected by MRS only). The reduction in liver lipid content, however, was not significantly correlated with the reduction in triglycerides (r = 0.26; P = 0.11) or with the changes in ALT, high‐density lipoprotein (HDL)‐cholesterol, or markers of whole‐body inflammation. Discussion: CR may be beneficial for reducing liver lipid and lowering triglycerides in overweight subjects without known NAFLD.     

Measuring Free‐Living Energy Expenditure and Physical Activity with Triaxial Accelerometry

Objective: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity‐related EE (AEE) in free‐living conditions. Research Methods and Procedures: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD‐X, ACD‐Y, ACD‐Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE × SMR^?1, and AEE was calculated as [(0.9 × TEE) ? SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three‐compartment model. Results: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) = 1.00 MJ/d] and 81% of the variation in AEE (SEE = 0.70 MJ/d). The partial correlations for ACD were 0.73 (p < 0.001) and 0.79 (p < 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE = 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p < 0.05). Discussion: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial.     

Determinants of Free-Living Energy Expenditure in Normal Weight and Obese Women Measured by Doubly Labeled Water

Total free-living energy expenditure (TEE) was measured in 9 normal weight controls and 5 obese women using the doubly labeled water (DLW) method. Resting energy expenditure (REE) and the thermic effect of food (TEF) were measured by indirect calorimetry and the energy cost of physical activity (PA) calculated by deduction, in order to quantify the components and identify determinants of free-living TEE. Although REE was quantitatively the major component of TEE in both groups, PA best explained the variability, contributing 76% to the variance in free-living TEE. The obese women had elevated values for TEE (12397+/-2565 vs. 8339+/-1787 kJ/d, mean+/-SD; p<0.00S), compared with the control women. PA (5071+/-2385 vs. 2552+/-1452; p<0.0S) and REE (6393+/-678 vs. 5084+/-259; p<0.000S) were also raised in the obese, whereas TEF was not significantly different between the groups, accounting for 7.6% of energy expenditure for the obese and 8% for the control subjects. Body weight was the single best determinant of mean daily free-living TEE across both groups. We conclude that PA and body weight are the main determinants of free-living TEE .     

Energy Expenditure and Adiposity in Nigerian and African‐American Women

Objective: Obesity is a prevalent condition in industrialized societies and is increasing around the world. We sought to assess the relative importance of resting energy expenditure (REE) and activity EE (AEE) in two populations with different rates of obesity. Methods and Procedures: Women of African descent between 18 and 59 years of age were recruited from rural Nigeria and from metropolitan Chicago. Total EE (TEE) was measured using the doubly labeled water (DLW) technique and REE by indirect calorimetry; AEE was calculated as the difference between TEE and the sum of REE plus a factor for the thermic effect of food. In the analyses all EE parameters were adjusted for body size using a regression method. Comparisons were made between the groups and associations between EE and adiposity examined. Results: A total of 149 Nigerian and 172 African‐American women completed the protocol. All body size measurements were lower in the Nigerian women. Adjusted TEE and REE were higher in the Nigerian cohort but adjusted AEE did not differ significantly. Adjustment for parity, seasonality, and recent illness did not modify mean AEE or adiposity. In neither cohort was there a meaningful association between measures of AEE and adiposity. Discussion: In these cohorts of women from very different environments, AEE did not differ significantly nor was it associated cross‐sectionally with adiposity. If generalizable, these findings suggest that reduction in AEE may have less of a role in the development of obesity than anticipated. The possibility remains that variation in type and duration of activity plays a role not captured by total AEE.