Effect of an Acute High Carbohydrate Diet on Body Composition Using DXA in Young Men

Article (PDF Available)inAnnals of Nutrition and Metabolism 66(4):233-236 · July 2015with 640 Reads 
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DOI: 10.1159/000435840 · Source: PubMed
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Abstract
The aim of this study is to investigate the effect of a 3-day high-carbohydrate diet (≥75% of total calories) on body composition using dual-energy X-ray absorptiometry (DXA). Twenty non-obese young men (age 22.7 ± 2.6 years, BMI 23.5 ± 2.1 kg/m(2)) completed the study. Two DXA tests were performed for the measurement of total body weight, body mass index (BMI), body fat percentage as well as total, appendicular and central lean body mass (LBM) before and after a high-carbohydrate diet for 3 days. In addition, the participants completed a food diary during the 3-day high-carbohydrate diet to determine the mean percentage of carbohydrates consumed from total kilocalories. The mean percentage of carbohydrate intake over 3 days was 83.7 ± 8.4%. Our results showed a significant increase in total body weight, BMI as well as total and appendicular LBM after the high-carbohydrate diet (p < 0.01). In addition, we observed a strong tendency for lower body fat percentage values after the intervention (p = 0.05). No significant difference was observed for central LBM. These results indicate that the effect of an acute high carbohydrate diet seems to affect body composition values using DXA, such as total LBM. This study may lead to the need of standardizing a diet prior to using DXA. © 2015 S. Karger AG, Basel.
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  • ... 22 This acute gain in lean body mass in week 11 is not entirely uncommon, considering 3 days of HC feeding and rest is associated with increased body mass (0.6 kg, p=0.001) and estimations of lean body mass (0.9 kg, p<0.0001) within nonobese men using a DXA scanner. 38 In contrast, Vargas et al demonstrated recreationally trained men consuming a non-KD increased lean body mass to a greater extent when compared to a KD group following an 8-week training intervention. 27 Baseline dietary assessment was absent, therefore, it is unknown if the non-KD group increased or sustained carbohydrate intake, thereby potentially impacting DXA reliability, for reasons previously outlined. ...
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    Fionn T McSwiney,1,2 Lorna Doyle,3 Daniel J Plews,4 Caryn Zinn4 1School of Health and Human Performance, Dublin City University, Dublin, Ireland; 2Setanta College, Thurlus, Tipperary, Ireland; 3Department of Sport and Exercise Science, Waterford Institute of Technology, Waterford, Ireland; 4Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New ZealandCorrespondence: Caryn ZinnAUT University, Sports Performance Research Institute New Zealand (Mail code P-1), Private Bag 92006, Auckland 1142, New ZealandTel +64 9 921 9999Fax +64 9 921 9960Email caryn.zinn@aut.ac.nzAbstract: The impact of a ketogenic diet (KD) (<50 g/d carbohydrate, >75% fat) on athletic performance has sparked much interest and self-experimentation in the past 3–4 years. Evidence shows 3–4-week adaptations to a KD in endurance-trained athletes were associated with maintenance of moderate (46–63% VO2max) and vigorous intensity (64–90% VO2max) endurance exercise, while at intensities >70% VO2max, increases in fat oxidation were associated with decreased economy (increased oxygen consumption), and in some cases, increased ratings of perceived exertion and heart rate. Two investigations in recreationally active endurance athletes noted no vigorous intensity exercise decrement following 3- and 12-week adaptations. Moderate (70–85% one repetition maximum) and near-maximal to maximal intensity (>85% 1RM) strength performance experienced no decrement following a 3-12-week KD adaptation. Beneficial effects were noted for 2000 m sprint and critical power test completed for short duration at vigorous intensity, while two additional tests noted no decrement. For sprint, near-maximal exercise (>91% VO2max), benefit of the KD was observed for six-second sprint, while no decrement in performance was noted for two additional maximal tests. When protein is equated (grams per kilogram), one investigation noted no decrement in muscle hypertrophy, while one noted a decrement. One investigation with matched protein noted the KD group lost more body fat. In conclusion, moderate-to-vigorous intensity exercise experiences no decrement following adaptation to a KD. Decreases in exercise economy are observed >70% VO2max in trained endurance athletes which may negate performance within field settings. Beneficial effects of the KD during short duration vigorous, and sprint bouts of exercises are often confounded by greater weight loss in the KD group. With more athletes pursuing carbohydrate-restricted diets (moderate and strict (KD)) for their proposed health benefits, more work is needed in the area to address both performance and health outcomes.Keywords: keto-adaptation, performance, endurance, strength, high intensity, low carbohydrate
  • ... the present study found the administration of ccp along with either exercise regimen decreased BW and BF% similarly to previous research conducted on both males and females of diverse age groups (i.e., 21-51 years old). 7,9 however, a greater reduction in BF% was observed in p2 who performed Mrt compared to p1 who performed hrt ( Figure 1). Factors that may have contributed to this difference were p1 had a baseline BF% of 7.6, which is lower than the average range among athletes (9-15%) 10 and consumed more energy compared to p2. therefore, during hrt, the primary source of energy for p1 was cho 4 which reduced lipolysis (i.e., utilization of stored body fat) during training sessions resulting in a 1.1% BF reduction, which is consistent with previous research. ...
    Article
    BACKGROUND Carbohydrate (CHO) resources are limited during moderate- to high-intensity resistance exercises (RE) which may limit performance. Increased intake of CHO prior to RE has been shown to enhance performance. The purpose of the study was to investigate the effect of self-implemented CHO cycling program (CCP) and RE on collegiate athlete body builders. METHODS Two body builders [males, participant-1 (P1):21 y and participant-2 (P2): 22 y] at a Division I University performed a dual energy X-ray absorptiometry scan before and after a five-week CCP to measure body fat percent (BF%) and bone mineral density (BMD). P1 performed high-intensity [60-90 mins, 75-90% of one repetition max (1RM)] resistance training (HRT) and P2 performed moderate-intensity (30-45 mins, 60-75%1RM) resistance training (MRT). RESULTS Total BF% was reduced by 1.1% in P1 and 3.6% in P2. The decrease in BF% among both the participants can be primarily attributed to the moderate- to high-intensity resistance exercise program. Although P2 performed MRT, a greater relative decrease in BF% was recorded (24.5%) compared to P1 (14.5%). However, P1 had a lower baseline BF% (7.6) than P2 (14.7). CONCLUSIONS Longer duration MRT may be more effective in reducing BF% if baseline values are at higher end of average athlete recommendation (9-15%).
  • ... Additionally, the participants' diets were controlled and sufficient energy and protein intake were assured. No differences regarding dietary intake were detected, which is in our view important, since a glycogen increase from a higher carbohydrate intake might have confounded the body composition results (Bone et al., 2017;Rouillier, David-Riel, Brazeau, St-Pierre, & Karelis, 2015). We accounted for variation in TBW throughout the intervention, with no significant changes being detected. ...
    Article
    β-hydroxy-β-methylbutyrate (calcium: HMB-Ca and free acid: HMB-FA) and α-hydroxyisocaproic acid (α-HICA) are leucine metabolites that have been proposed to improve body composition and strength when combined with resistance exercise training (RET). In this double-blind randomized controlled pragmatic trial, we evaluated the effects of off-the-shelf supplements: α-HICA, HMB-FA and HMB-Ca, on RET-induced changes in body composition and performance. Forty men were blocked randomized to receive α-HICA (n = 10, fat-free mass [FFM] = 62.0 ± 7.1 kg), HMB-FA (n = 11, FFM = 62.7 ± 10.5 kg), HMB-Ca (n = 9, FFM = 65.6 ± 10.1 kg) or placebo (PLA; n = 10, FFM = 64.2 ± 5.7 kg). The training protocol consisted of a whole-body resistance training routine, thrice weekly for 8 weeks. Body composition was assessed by dual-energy x-ray absorptiometry (DXA) and total body water (TBW) by whole-body bioimpedance spectroscopy (BIS), both at baseline and at the end of weeks 4 and 8. Time-dependent changes were observed for increase in trunk FFM (p < 0.05). No statistically significant between-group or group-by-time interactions were observed. Supplementation with HMB (FA and Ca) or α-HICA failed to enhance body composition to a greater extent than placebo. We do not recommend these leucine metabolites for improving body composition changes with RET in young adult resistance trained men.
  • ... Muscle glycogen levels and water content are considered two limiting factors during DXA FFM assessment because both factors can markedly change in humans and DXA does not provide a direct measure of water and muscle glycogen content (Lohman & Chen, 2005). We instructed the participants to consume a normal evening meal the night prior to testing and to avoid strenuous exercise for 24 hours prior to testing in order to minimize the influence of muscle glycogen content on the determination of FFM, as an acute high-carbohydrate diet has been shown to increase muscle glycogen content in young men (Rouillier, David-Riel, Brazeau, St-Pierre, & Karelis, 2015). Although participants were instructed to consume a normal evening meal the night prior to testing and to be hydrated following a strict protocol, the evening meal prior to use DXA was not standardized and hydration status of the study subjects was not determined before the FFM assessment. ...
    Article
    This study determined the most effective field method for quantifying fat-free mass (FFM) in elite youth male soccer players compared to dual X-ray absorptiometry (DXA) values and to develop prediction equations for FFM based on anthropometric variables. Forty-one male elite-standard youth soccer players, ages 16.2–18.0 years, undertook FFM assessments including bioelectrical impedance analysis, and different skinfold-based prediction equations. DXA provided a criterion measure of FFM. Correlation coefficients, bias, limits of agreement, and differences were used as validity measures, and regression analyses to develop soccer-specific prediction equations. Slaughter et al (1988), Durnin and Wormersley (1974), and Sarria et al (1998) equations showed the lowest biases, and no significant, standardized, and substantial differences against DXA. The new youth soccer-specific anthropometric equation explained 91% of the DXA-derived FFM variance using three circumferences, eight skinfolds, and one bone breadth. All field methods compared in this study may not be adequate for estimating FFM in elite youth male soccer players, except the equations of Slaughter et al (1988), Durnin and Wormersley (1974), and Sarria et al (1998). We recommend the use of the new soccer-specific equation proposed in this study as a valid alternative to DXA to quantify FFM among elite youth male players.
  • ... Recently, there has been increased awareness that, although DXA is useful for body composition assessment, it is not impervious to biological error induced by variation in subject presentation. Acute food and fluid intake, as well as manipulation of muscle glycogen and creatine stores, can artificially influence body composition estimates, particularly lean mass (Bone et al., 2017;Nana et al., 2012;Rouillier et al., 2015;Tinsley et al., 2017). Due to the confounding influence of the bone arrangement and organ mass in the trunk region and the likelihood that much of gastrointestinal content will appear as LST, it is theoretically appealing to remove this region for nonfasted body composition assessments. ...
    Article
    Implementation of an overnight fast is a pervasive recommendation prior to body composition assessment, but this is not always feasible. Previous research has indicated that, for dual-energy x-ray absorptiometry (DXA) scans, the trunk region may be particularly susceptible to biological error induced by food and fluid intake. This analysis explored the potential utility of excluding the trunk region from non-fasted DXA scans. Recreationally active adults were assessed by DXA after an overnight fast and again after consumption of standardized high-carbohydrate (HC) and low-carbohydrate (LC) diets. The effects of food consumption on total and appendicular lean soft tissue (LST; ALST) and ALST-derived skeletal muscle mass (SMM) were evaluated via analysis of variance, and metrics of reliability were calculated. In both conditions, constant error of non-fasted assessments was slightly lower when the trunk was excluded (ALST and SMM: 0.7 - 1.2%; LST: 1.5%). However, in both conditions, the total error (TE), SEE and limits of agreement (LOA) were higher for ALST and SMM (TE: 2.4 to 3.0%; SEE: 2.2 to 2.8%; LOA: 4.5 to 5.6%) than LST (TE: 2.1%; SEE: 1.3 to 1.4%; LOA: 2.5 to 2.8%) when expressed relative to mean values. The added technical error due to demarcation of body regions for ALST and SMM appears to outweigh the removal of biological error due to exclusion of the trunk. Although elimination of the trunk region is theoretically appealing for non-fasted DXA assessments, it is apparently an inferior method as compared to utilizing whole-body LST.
  • ... Additionally, significant increases in body mass, lean body mass, and appendicular body mass using DXA scans following a 3-day high carbohydrate diet have been reported 17 . Thus while we only observed a trend for increased MT, it is possible that systemic changes in muscle composition contributed to increased BIA predicted skeletal muscle mass which is similar to other reports utilizing various techniques 22,23 . ...
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    Full-text available
    Introduction: This pilot study examined the effects of carbohydrate loading (CHO) and oral creatine monohydrate loading (Cr) on ultrasound measurements of the lower limbs. Methods: Twelve recreationally-active males (25.5 ± 6.2 y, 81.5 ± 9.6 kg, 180.9 ± 8.8 cm) completed baseline (BL) bioelectrical impedance analysis (BIA) and muscle ultrasound imaging of the rectus femoris (RF) and the vastus lateralis (VL). Following baseline measurements, participants completed one day of CHO loading (10g CHO/kg), and five days of Cr loading (20g/day). Following each treatment, participants reported to the lab after an overnight fast for BIA and ultrasound testing in which muscle thickness (MT), cross-sectional area (CSA) and echo intensity (EI) were assessed on the RF and VL. A repeated measures analyses of variance were used for each variable to assess differences between dietary conditions. Results: Significant main effects (p<0.05) were observed for RF and VL MT, RF CSA. RF MT increased from BL-Cr (p<0.00, +6.85%) and CHO-Cr (p=0.002, +4.59%). VL MT increased from BL-Cr (p=0.008, +6.46%) and CHO-Cr (p=0.006, +3.71%). RF CSA increased between CHO-Cr (p=0.034, +3.58%). No significant differences were seen for EI. Conclusions: These data show that acute dietary manipulations may influence muscular ultrasound measurements of MT and CSA.
  • ... Additionally, the participants' diets were controlled and sufficient energy and protein intake were assured. No differences regarding dietary intake were detected, which is in our view important, since a glycogen increase from a higher carbohydrate intake might have confounded the body composition results (Bone et al., 2017;Rouillier, David-Riel, Brazeau, St-Pierre, & Karelis, 2015). We accounted for variation in TBW throughout the intervention, with no significant changes being detected. ...
  • ... Technical factors such as discrepancies in machine software/hardware (Toombs et al. 2012), subject positioning (Nana et al. 2012) or technician expertise (Hume and Marfell-Jones 2008) affect precision, whereas biological factors influenced by subject presentation play an important role (Bunt et al. 1989;Dixon et al. 2009;Kerr et al. 2017;Nana et al. 2012). Exercise, plus food and fluid intake prior to assessment Heiss et al. 2009;Dixon et al. 2009;Gallagher et al. 1998;Rouillier et al. 2015), core body temperature fluctuations (Fields et al. 2004) as well as muscle creatine and glycogen changes (Bone et al. 2016) are known to impact results. Arriving for assessment without controlling for these variables is referred to as non-standardised presentation. ...
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    Purpose: High precision body composition assessment methods accurately monitor physique traits in athletes. The acute impact of subject presentation (ad libitum food and fluid intake plus physical activity) on body composition estimation using field and laboratory methods has been quantified, but the impact on interpretation of longitudinal change is unknown. This study evaluated the impact of athlete presentation (standardised versus non-standardised) on interpretation of change in physique traits over time. Thirty athletic males (31.2 ± 7.5 years; 182.2 ± 6.5 cm; 91.7 ± 10.3 kg; 27.6 ± 2.6 kg/m2) underwent two testing sessions on 1 day including surface anthropometry, dual-energy X-ray absorptiometry (DXA), bioelectrical impedance spectroscopy (BIS) and air displacement plethysmography (via the BOD POD), with combinations of these used to establish three-compartment (3C) and four-compartment (4C) models. Methods: Tests were conducted after an overnight fast (BASEam) and ~ 7 h later after ad libitum food/fluid and physical activity (BASEpm). This procedure was repeated 6 months later (POSTam and POSTpm). Magnitude of changes in the mean was assessed by standardisation. Results: After 6 months of self-selected training and diet, standardised presentation testing (BASEam to POSTam) identified trivial changes from the smallest worthwhile effect (SWE) in fat-free mass (FFM) and fat mass (FM) for all methods except for BIS (FM) where there was a large change (7.2%) from the SWE. Non-standardised follow-up testing (BASEam to POSTpm) showed trivial changes from the SWE except for small changes in FFM (BOD POD) of 1.1%, and in FM (3C and 4C models) of 6.4 and 3.5%. Large changes from the SWE were found in FFM (BIS, 3C and 4C models) of 2.2, 1.8 and 1.8% and in FM (BIS) of 6.4%. Non-standardised presentation testing (BASEpm to POSTpm) identified trivial changes from the SWE in FFM except for BIS which was small (1.1%). A moderate change from the SWE was found for BOD POD (3.3%) and large for BIS (9.4%) in FM estimations. Conclusions: Changes in body composition utilising non-standardised presentation were more substantial and often in the opposite direction to those identified using standardised presentation, causing misinterpretation of change in physique traits. Standardised presentation prior to body composition assessment for athletic populations should be advocated to enhance interpretation of true change.
  • ... In this study, we aimed to identify the genetic variants that influence an individual's potential for body fat loss. Our study was motivated by the results of previous studies, which demonstrated that each individual has a genetic different predisposition and can thus benefit from a specific diet and exercise regime [19][20][21][22][23][24]. An individual's response to changes in nutrient intake or physical activity may depend on the number of risk alleles. ...
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    Full-text available
    The past decade has witnessed the discovery of obesity-related genetic variants and their functions through genome-wide association studies. Combinations of risk alleles can influence obesity phenotypes with different degrees of effectiveness across various individuals by interacting with environmental factors. We examined the interaction between genetic variation and changes in dietary habits or exercise that influences body fat loss from a large Korean cohort (n= 8840). Out of 673 obesity-related SNPs, a total of 100 SNPs (37 for carbohydrate intake; 19 for fat intake; 44 for total calories intake; 25 for exercise onset) identified to have gene-environment interaction effect in generalized linear model were used to calculate genetic risk scores (GRS). Based on the GRS distribution, we divided the population into four levels, namely, "very insensitive", "insensitive", "sensitive", and "very sensitive" for each of the four categories, "carbohydrate intake", "fat intake", "total calories intake", and "exercise". Overall, the mean body fat loss became larger when the sensitivity level was increased. In conclusion, genetic variants influence the effectiveness of dietary regimes for body fat loss. Based on our findings, we suggest a platform for personalized body fat management by providing the most suitable and effective nutrition or activity plan specific to an individual.
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    Fat-free mass index (FFMI) is a height-adjusted metric of fat-free mass which has been suggested as a useful method of body composition assessment in athletic populations. The purpose of this study was to determine sport-specific FFMI values and the natural upper threshold of FFMI in female athletes. 372 female collegiate athletes (Mean±SD; 20.03±1.55 years, 167.55±7.50 cm, 69.46±13.04 kg, 24.18±5.48% bodyfat) underwent body composition assessment via dual-energy x-ray absorptiometry. FFMI was adjusted to height via linear regression and sport-specific reference values were determined. Between-sport differences were identified using one-way ANOVA with Tukey post-hoc tests. Average FFMI was 18.82±2.08 kg/m²; height-adjusted values were not significantly different (p<0.05) than unadjusted values. FFMI in rugby athletes (20.09±2.23 kg/m²) was found to be significantly higher (p<0.05) than in gymnastics (18.62±1.12 kg/m²), ice hockey (17.96±1.04 kg/m²), lacrosse (18.58±1.84 kg/m²), swim & dive (18.16±1.67 kg/m²), and volleyball (18.04±1.13 kg/m²). FFMI in cross country (16.56±1.14 kg/m²) and synchronized swimming (17.27±1.47 kg/m²) was significantly lower (p<0.05) than in Olympic weightlifting (19.69±1.98 kg/m²), wrestling (19.15±2.47 kg/m²), and rugby. The upper threshold for FFMI in female athletes (97.5th percentile) was 23.90 kg/m². These results can be used to guide personnel decisions and assist with long-term body composition, training, and nutritional goals.
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    Abstract A comparative evaluation of the ability of activity monitors to predict energy expenditure (EE) is necessary to aid in the investigation of the effect of EE on health. The purpose of this study was to validate and compare the RT3, the SWA and the IDEEA at measuring EE in adults and children. Twenty-six adults and 22 children completed a resting metabolic rate (RMR) test and performed four treadmill activities at 3 km.h(-1), 6 km.h(-1), 6 km.h(-1) at a 10% incline, 9 km.h(-1). EE was assessed throughout the protocol by the RT3, the SWA and the IDEEA. Indirect calorimetry (IC) was used as a criterion measure of EE against which each monitor was compared. Mean bias was assessed by subtracting EE from IC from EE from each monitor for each activity. Limit of agreement plots were used to assess the agreement between each monitor and IC. Limits of agreement for resting EE were narrowest for the RT3 for adults and children. Although the IDEEA displayed the smallest mean bias between measures at 3 km.h(-1), 6 km.h(-1) and 9 km.h(-1) in adults and children, the SWA agreed closest with IC at 6 km.h(-1), 6 km.h(-1) at a 10% incline and 9 km.h(-1). Limits of agreement were closest for the SWA at 9 km.h(-1) in adults representing 42% of the overall mean EE. Although the RT3 provided the best estimate of resting EE in adults and children, the SWA provided the most accurate estimate of EE across a range of physical activity intensities.
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    Objective methods to measure daily energy expenditure in studies of aging are needed. We sought to determine the accuracy of total energy expenditure (TEE) and activity energy expenditure (AEE) estimates from the SenseWear Pro armband (SWA) using software versions 6.1 (SWA 6.1) and 5.1 (SWA 5.1) relative to criterion methods in free-living older adults. Participants (n = 19, mean age 82.0 years) wore a SWA for a mean ± SD 12.5 ± 1.1 days, including while sleeping. During this same period, criterion values for TEE were assessed with doubly labeled water and for resting metabolic rate (RMR) with indirect calorimetry. AEE was calculated as 0.9 TEE - RMR. For TEE, there was no difference in mean ± SD values from doubly labeled water (2,040 ± 472 kcal/day) versus SWA 6.1 (2,012 ± 497 kcal/day, p = .593) or SWA 5.1 (2,066 ± 474 kcal/day, p = .606); individual values were highly correlated between methods (SWA 6.1 r = .893, p < .001; SWA 5.1 r = .901, p < .001) and demonstrated strong agreement (SWA 6.1 intraclass correlation coefficient = .896; SWA 5.1 intraclass correlation coefficient = .904). For AEE, mean values from SWA 6.1 (427 ± 304 kcal/day) were lower by 26.8% than criterion values (583 ± 242 kcal/day, p = .003), and mean values from SWA 5.1 (475 ± 299 kcal/day) were lower by 18.5% than criterion values (p = .021); however, individual values were highly correlated between methods (SWA 6.1 r = .760, p < .001; SWA 5.1 r = .786, p < .001) and demonstrated moderate agreement (SWA 6.1 intraclass correlation coefficient = .645; SWA 5.1 intraclass correlation coefficient = .720). Bland-Altman plots identified no systematic bias for TEE or AEE. Acceptable levels of agreement were observed between SWA and criterion measurements of TEE and AEE in older adults.
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    Accelerometers offer considerable promise for improving estimates of physical activity (PA) and energy expenditure (EE) in free-living subjects. Differences in calibration equations and cut-off points have made it difficult to determine the most accurate way to process these data. The objective of this study was to compare the accuracy of various calibration equations and algorithms that are currently used with the MTI Actigraph (MTI) and the Sensewear Pro II (SP2) armband monitor. College-age participants (n=30) wore an MTI and an SP2 while participating in normal activities of daily living. Activity patterns were simultaneously monitored with the Intelligent Device for Estimating Energy Expenditure and Activity (IDEEA) monitor to provide an accurate estimate (criterion measure) of EE and PA for this field-based method comparison study. The EE estimates from various MTI equations varied considerably, with mean differences ranging from -1.10 to 0.46 METS. The EE estimates from the two SP2 equations were within 0.10 METS of the value from the IDEEA. Estimates of time spent in PA from the MTI and SP2 ranged from 34.3 to 107.1 minutes per day, while the IDEEA yielded estimates of 52 minutes per day. The lowest errors in estimation of time spent in PA and the highest correlations were found for the new SP2 equation and for the recently proposed MTI cut-off point of 760 counts/min (Matthews, 2005). The study indicates that the Matthews MTI cut-off point and the new SP2 equation provide the most accurate indicators of PA.
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    The SenseWear Armband (SWA) has been shown to be a valid and practical tool to assess energy expenditure during habitual physical activity. However, previous studies have focused on low-to-moderate intensity activities. The purpose of this study was to assess the validity of the SWA during high intensity exercise. Twenty (ten males, ten females) endurance trained subjects, 24.3 (±2.8) years of age, performed three 10-min treadmill runs at 65, 75, and 85% of their VO(2max) each and also ran outside for 30 min at their preferred speed. Energy expenditure was measured with the SWA (software version 6.1) and a portable indirect calorimetry system (Jaeger Oxycon Mobile(®)). The SWA showed a ceiling effect around an intensity of ten METs. Since all subjects exceeded that intensity range during the exercise trials, the SWA significantly underestimated energy expenditure at high intensities. The intra-individual correlations between MET values calculated by the SWA and values derived from the Oxycon, however, were significant for all but two subjects (r = 0.390-0.933, mean = 0.66 ± 0.25). While providing accurate results for energy expenditure during low-to-moderate intensity physical activities, the SWA does not provide accurate estimates of energy expenditure at high intensity levels. The threshold for accurate measurements seems to be around an intensity of ten METs.
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    There is a need to develop accurate devices for measuring daily energy expenditure under free-living conditions, particularly given our current obesity epidemic. 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. 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. 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. 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.
  • Article
    The present study reviews the most recently developed and commonly used methods for the determination of human body composition in vivo with relevance for nutritional assessment. Body composition measurement methods are continuously being perfected with the most commonly used methods being bioelectrical impedance analysis, dilution techniques, air displacement plethysmography, dual energy X-ray absorptiometry, and MRI or magnetic resonance spectroscopy. Recent developments include three-dimensional photonic scanning and quantitative magnetic resonance. Collectively, these techniques allow for the measurement of fat, fat-free mass, bone mineral content, total body water, extracellular water, total adipose tissue and its subdepots (visceral, subcutaneous, and intermuscular), skeletal muscle, select organs, and ectopic fat depots. There is an ongoing need to perfect methods that provide information beyond mass and structure (static measures) to kinetic measures that yield information on metabolic and biological functions. On the basis of the wide range of measurable properties, analytical methods and known body composition models, clinicians and scientists can quantify a number of body components and with longitudinal assessment, can track changes in health and disease with implications for understanding efficacy of nutritional and clinical interventions, diagnosis, prevention, and treatment in clinical settings. With the greater need to understand precursors of health risk beginning in childhood, a gap exists in appropriate in-vivo measurement methods beginning at birth.
  • Article
    19 subjects performed prolonged heavy arm and leg exercise after which they had a protein and fat diet for three days. Thereafter they switched to a carbohydrate enriched diet during a 4-day period. The measurements were performed on the 3rd day and then repeated on the 7th day. The glycogen concentration in the thigh and the arm muscles was 4.5 and 2.6 g/kg wet muscle on the 3rd day and increased with the carbohydrate enriched diet to 19.9 and 16.9 g/kg wet muscle, respectively. Body weight increased 2.4 kg during this period of 4 days. The total body water increased 2.2 1 which is assumed to be caused by the glycogen storage in the muscles and the liver. The amount of glycogen stored was calculated to be at least 500 g, which means that 3—4 g of water is bound with each gram of glycogen.