Body composition and energy expenditure -
In this case, diet composition can be an important contributing factor; diets rich in carbohydrate, in particular those containing substantial amounts of refined grains and sugars, promote obesity because stimulation of insulin secretion by these nutrients drives metabolic fuels toward the synthesis and storage of fat [ 4 ].
The more conventional model sees obesity as caused by an energy balance disorder in which energy intake exceeds energy expenditure [ 5 , 6 ]. The carbohydrate-insulin and energy balance hypotheses make distinctly different predictions about the effects of reducing dietary carbohydrate content on energy expenditure EE under conditions in which calories and protein remain constant.
The carbohydrate-insulin hypothesis predicts that lowering the proportion of carbohydrate to fat, even while maintaining energy and protein intake, would minimize circulating insulin concentration and thereby promote lipolysis and oxidation of stored and ingested fat, and, as a result, increase EE.
In preparation for an anticipated full-scale trial to test these competing predictions, Hall et al. conducted a pilot study [ 8 , 9 ] in which they measured EE in participants with overweight and obesity who were housed in metabolic wards before and after they were switched from a high-carbohydrate baseline diet to an isocaloric ketogenic diet containing equivalent protein and little carbohydrate.
EE was measured two ways: using metabolic chambers for two consecutive days each week throughout the study, and using doubly labeled water during the last 2 weeks of each 4-week diet period. EE measured in metabolic chambers increased significantly after the switch to the ketogenic diet, but this change was transient, lasting only two weeks, and was considered to be relatively small by Hall et al.
This response was attributed [ 8 ] to greater energy expenditure from increased physical activity when subjects ate the ketogenic diet and were outside the chambers living in the ward.
The carbohydrate-insulin and energy balance hypotheses have distinctly different implications for understanding the etiology of obesity and devising effective strategies for preventing and treating it.
Consequently, it would be useful to reconcile the discrepant findings from measurements of EE using metabolic chambers and doubly labeled water.
Hall et al. made the data from their study publicly available on the Open Science Framework OSF website [ 10 ]. In this paper, we report results of additional analyses of this dataset to differentiate the effect of housing subjects in a metabolic chamber versus in a metabolic ward on the magnitude of the increase in EE DLW after the switch to the ketogenic diet and to assess the role of physical activity in this effect.
In addition, we discuss and evaluate a recent reanalysis [ 11 ] of the Hall et al [ 8 ] data that attempts to resolve the discrepant findings from the chamber and DLW measurements in terms of methodological and theoretical factors related to diet and energy balance.
Details of the design and methods of the study can be found in the Hall et al. paper [ 8 ], including the online supplementary data, and in the published IRB-approved protocol [ 9 ].
Briefly, focusing on methods relevant to the analyses described here, 17 males with overweight or obesity were admitted as inpatients to metabolic wards and fed a baseline diet BD; percent of calories from protein:carbohydrate:fat for 4 weeks followed by an isocaloric ketogenic diet KD; percent of calories from protein:carbohydrate:fat for another 4 weeks.
Subjects were housed in a metabolic chamber for two consecutive days each week throughout the study to measure daily EE, sleeping EE, and respiratory quotient considered primary endpoints of the study.
During the last 2 weeks of each diet period, average daily EE was measured using doubly labeled water EE DLW ; considered an exploratory endpoint of the study. The study was registered at www. gov as NCT To confirm the replicability of the data used in the secondary analyses of EE DLW described below, we first reanalyzed the calorimetry results reported in Table 2 of the Hall et al.
paper [ 8 ] using the dataset and code published on the OSF website [ 10 ] and SAS v9. Details regarding the sources and handling of data from the Hall et al. dataset for the secondary analyses described below are provided in the Supporting Information S1 File along with the SAS code used for these secondary analyses S2 File.
All endpoint values reported herein were calculated using individual data from the Hall et al. A primary purpose of the Hall et al. pilot study was to determine the magnitude and variability of changes in EE after subjects were switched from the BD to KD in preparation for an anticipated larger study.
The day period for measuring EE DLW included 4 days when subjects were confined to a metabolic chamber and 10 days when subjects lived in the ward. reported EE DLW as a daily average across the day measurement period and did not differentiate EE during the non-chamber days, when subjects were housed in the ward, from the chamber days, when EE is relatively lower [ 12 , 13 ] and the effect of diet was much reduced [ 8 ].
To determine average daily EE DLW for only those days in which subjects were housed in the ward, we used a term in Hall et al. In essence, the resulting equation Eq 1 below separates average daily EE for days subjects were housed in the wards from days they were confined to metabolic chambers by subtracting total EE measured during the 4 chamber days EE chamber within the EE DLW measurement period from total day EE DLW and averaging the resulting value over the 10 non-chamber days.
Differences in EE DLW, EE nonchamber and EE chamber between the two diet conditions were evaluated using a repeated linear mixed model. Data from Subject 04— was not included in these analyses see below in keeping with Hall et al.
As a check on Eq 1 , we also calculated EE nonchamber by subtracting total CO 2 production measured during the four chamber days within the EE DLW measurement periods from the total day CO 2 production measured using doubly labeled water, and dividing the result by the 10 non-chamber days.
Details of these calculations are provided in the Supporting Information S1 file. To that end, we compared EE DLW and EE nonchamber during the two diet periods, as above, except that data from Subject 04— were included in the analysis.
The reported 0. As a check on the weight change based on body weights collected during the body composition assessments, we evaluated the change in body weight during the EE DLW measurement period using daily body weight data from the dataset.
evaluated whether greater physical activity accounted for the increase in EE DLW during the KD period by calculating energy expenditure from physical activity in and out of the metabolic chambers i. e, PAE chamber and PAE nonchamber as per their Table 2. Physical activity energy expenditure outside the chambers was higher during the KD period compared to the BD phase, but the effect was not statistically significant.
Physical activity level was measured directly throughout the study using accelerometers; however, only hip count data were reported and only as a percentage difference between chamber and non-chamber days during the entire BD period.
Here, we used the accelerometer data in the OSF dataset to determine more directly whether differences in physical activity can account for the increase in EE DLW after the switch to the KD. To confirm reproducibility and help validate our use of the accelerometer data, we first reanalyzed the fractional difference between hip accelerometer counts from chamber and non-chamber days during the baseline period of the study using the published dataset and code.
We next analyzed daily hip, wrist and ankle accelerometer counts during the BD and KD EE DLW measurement periods with respect to whether subjects were confined to chambers or were housed in the ward i. Average accelerometer wear times varied little with respect to device location, diet and housing status.
In keeping with Hall et al. Accelerometer counts for each location with respect to chamber status and diet were compared in the generalized linear mixed model by t-test to determine statistical significance. To determine whether this increase in SEE persisted during the end of the KD period and may have contributed to the increase in EE DLW observed at that time, we compared SEE during the BD and KD EE DLW measurement periods.
Comparison of SEE for all subjects during the EE DLW measurement periods in the BD and KD phases of the study were made using a paired t-test.
Reanalysis of the calorimetry data in Table 2 in the Hall et al. paper [ 8 ] using the OSF dataset and code fully reproduced the reported results, including mean, standard error and probability values associated with statistical comparisons of diet periods.
The increase in EE DLW after the switch to the KD was greater when calculated only for days when subjects were housed in the wards outside of the chambers than it was when calculated over the entire EE DLW measurement period that included both days in and out of the chambers.
Reanalysis of EE DLW data from the Hall et al. Using Eq 1 above, energy expenditure for days when subjects were out of the chambers EE nonchamber.
Energy expenditure measured in the chambers EE chamber during the EE DLW measurement periods did not differ as a function of diet.
Calculation of EE nonchamber based on the difference between CO 2 production measured in the chambers and by doubly labeled water produced results very similar to those using Eq 1.
The effect of switching from the BD to the KD on EE measured using doubly labeled water was greater when data from the outlier was included in the analysis. The 0. Inspection of the dataset revealed that other subjects showed changes in body weight that appeared anomalous relative to the difference between their EE DLW and energy intakes.
Two of these subjects gained weight during the KD period 0. Two participants lost weight 1. The weight gain of Subject 04— across the interval between two body composition assessments in the KD period reported by Hall et al. underlies their rationale for exclusion of his data from analysis of the effect of diet on EE DLW.
We confirmed that Subject 04— gained 0. Consequently, we referred to daily body weight data from the dataset, which showed that Subject 04— lost 0. Reanalysis of hip accelerometer counts during the full BD period using the Hall et al. Inclusion of data from Subject 04— did not materially affect accelerometer counts or the outcomes of the statistical analyses.
SEE values and the results of the analysis were nearly identical if data from Subject 04— were excluded. measured average daily energy expenditure using doubly labeled water over a day period that included 4 days during which subjects were confined to a metabolic chamber and 10 days when they were housed in the ward.
Because people expend less energy in a metabolic chamber than under more free-living conditions [ 12 , 13 ] and chamber measurement of EE showed little difference between the diet periods in the Hall et al. study [ 8 ], we quantified expenditures for non-chamber days EE nonchamber separately from in-chamber days EE chamber.
EE chamber during the doubly labeled water measurement periods did not differ significantly as a function of diet, further indicating that the increase in EE DLW after the switch to the KD was limited to days when subjects were housed in the ward.
In keeping with best practices for handling outliers [ 14 ], we calculated EE DLW and EE nonchamber with and without data from Subject 04—, considered an outlier by Hall et al. However, because there is no documented error in, for example, data collection, recording or computation, the cause of this apparently exaggerated response is unknown.
According to Hall et al. study, specifically prior to adaptation to a low-carbohydrate diet with only endogenous, not dietary, protein as the substrate.
The lower value cited by Hall et al. More recently, Ebbeling et al. Whereas these effects of diet on EE DLW in these two studies were observed under very different conditions than those in the Hall et al.
The order in which subjects in the Hall et al. study were fed the BD and the KD was not counterbalanced or otherwise controlled for, a trial design limitation noted by the authors that precluded causal inference about the effect of the KD. In contrast, the Ebbeling et al.
studies described above randomized the order in which subjects ate the experimental diets [ 17 ] or randomized the diets to which they were assigned [ 18 ]. The similarity in the responses to a low carbohydrate diet in the Ebbeling et al. studies and, with respect to EE nonchamber , to the KD in the Hall et al.
study, lends credence to the conclusion that consumption of the KD caused the increase in EE DLW in the Hall et al. Estimates of the increase in EE nonchamber from the current analysis likely represent a minimal range for the effect size.
The continuing weight loss throughout the study due to unintentional underfeeding of the subjects, as described by Hall et al. Lower circulating concentrations of leptin and triiodothyronine during the KD versus the BD period reported by Hall et al.
are consistent with such a reduction in EE. Accounting for the excretion of fat in feces might also magnify energy losses during the KD period [ 19 ]. Based on hypothetical relationships between diet composition, energy balance and measured RQ, they suggested that their earlier calculation of EE DLW overestimated the effect of switching to the KD.
Adjusting for these factors, they found that the increase in EE DLW after the diet switch was diminished to statistically nonsignificant levels, an effect that was due primarily to an increase in estimated EE DLW in the BD period as opposed to a change in the KD period.
Subjects were identified as outliers post hoc , particularly on the basis of observations indicating that the difference between their EE DLW and energy intake was not commensurate with changes in body weight during the KD EE DLW measurement period. The two outliers identified by Hall et al. Which of the outlier data is chosen for exclusion in data analysis markedly affects estimates of energy expenditure Figure A in S3 File.
In the case of Subjects A and B together, it reduced effect size to nonsignificant levels. In other cases, it reduced the effect size less while retaining statistical significance, and, importantly, in some cases the choice of outliers increased the effect size.
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Westerterp, K. Challenges in measuring energy balance and body composition. Eur J Clin Nutr 77 , — Download citation. Received : 15 March Revised : 28 March Accepted : 29 March Published : 19 April Issue Date : May Anyone you share the following link with will be able to read this content:.
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Resting energy neergy REE was investigated by coposition calorimetry in relation to body triathlon nutrition calculator and to Bofy degrees of obesity in order to Bod if a Body composition and energy expenditure compositiln expenditure contributes to extra body fat accumulation. Differences were found expenditur control subjects group Compisition BMI 23±0. Body composition data were obtained by means of body impedance analysis. Even though group MO had a fat mass higher than group O, body cell mass, the metabolically active body compartment, was similar in groups O and MO, and this fact may have contributed to the similar REE in the two groups. Thus the analysis showed a negative impact of obesity on REE beyond body composition variables. This is a preview of subscription content, log in via an institution to check access. Rent this article via DeepDyve. Thank Traditional herbal medicine for compisition nature. You are using a compoxition version compoaition limited support fnergy CSS. To obtain the best Body composition and energy expenditure, we recommend you use a Body composition and energy expenditure up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Body weight and body composition of adults is the result of the regulation of energy balance, and remains fairly stable over an extended period of time.
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