Sex differences in energy balance, body composition, and metabolic and endocrine markers during prolonged arduous military training.

This study investigated sex differences in energy balance, body composition, and metabolic and endocrine markers during prolonged military training. Twenty-three trainees (14 women) completed 44-wk military training (three terms of 14 wk with 2-wk adventurous training). Dietary intake and total energy expenditure were measured over 10 days during each term by weighed food and doubly labeled water. Body composition was measured by dual-energy X-ray absorptiometry (DXA) at baseline and at the end of each term. Circulating metabolic and endocrine markers were measured at baseline and at the end of terms 2 and 3. Absolute energy intake and total energy expenditure were higher, and energy balance was lower, for men than women (P ≤ 0.008). Absolute energy intake and balance were lower, and total energy expenditure was higher, during term 2 than terms 1 and 3 (P < 0.001). Lean mass did not change with training (P = 0.081). Fat mass and body fat increased from term 1 to terms 2 and 3 (P ≤ 0.045). Leptin increased from baseline to terms 2 and 3 in women (P ≤ 0.002) but not in men (P ≥ 0.251). Testosterone and free androgen index increased from baseline to term 3 (P ≤ 0.018). Free thyroxine (T4) decreased and thyroid-stimulating hormone (TSH) increased from baseline to term 2 and term 3 (P ≤ 0.031). Cortisol decreased from baseline to term 3 (P = 0.030). IGF-I and total triiodothyronine (T3) did not change with training (P ≥ 0.148). Men experienced greater energy deficits than women during military training due to higher total energy expenditure.NEW & NOTEWORTHY Energy deficits are common in military training and can result in endocrine and metabolic disturbances. This study provides first investigation of sex differences in energy balance, body composition, and endocrine and metabolic markers in response to prolonged and arduous military training. Men experienced greater energy deficits than women due to higher energy expenditure, which was not compensated for by increased energy intake. These energy deficits were not associated with decreases in fat or lean mass or metabolic or endocrine function.

Nutrition and Physical Activity During British Army Officer Cadet Training: Part 1-Energy Balance and Energy Availability.

Military training is characterized by high daily energy expenditures which are difficult to match with energy intake, potentially resulting in negative energy balance (EB) and low energy availability (EA). The aim of this study was to quantify EB and EA during British Army Officer Cadet training. Thirteen (seven women) Officer Cadets (mean ± SD: age 24 ± 3 years) volunteered to participate. EB and EA were estimated from energy intake (weighing of food and food diaries) and energy expenditure (doubly labeled water) measured in three periods of training: 9 days on-camp (CAMP), a 5-day field exercise (FEX), and a 9-day mixture of both CAMP and field-based training (MIX). Variables were compared by condition and gender with a repeated-measures analysis of variance. Negative EB was greatest during FEX (-2,197 ± 455 kcal/day) compared with CAMP (-692 ± 506 kcal/day; p < .001) and MIX (-1,280 ± 309 kcal/day; p < .001). EA was greatest in CAMP (23 ± 10 kcal·kg free-fat mass [FFM]-1·day-1) compared with FEX (1 ± 16 kcal·kg FFM-1·day-1; p = .002) and MIX (10 ± 7 kcal·kg FFM-1·day-1; p = .003), with no apparent difference between FEX and MIX (p = .071). Irrespective of condition, there were no apparent differences between gender in EB (p = .375) or EA (p = .385). These data can be used to inform evidenced-based strategies to manage EA and EB during military training, and enhance the health and performance of military personnel.

The Importance of Hydration in Body Composition Assessment in Children Aged 6-16 Years.

Body composition is associated with many noncommunicable diseases. The accuracy of many simple techniques used for the assessment of body composition is influenced by the fact that they do not take into account tissue hydration and this can be particularly problematic in paediatric populations. The aims of this study were: (1) to assess the agreement of two dual energy X-ray absorptiometry (DXA) systems for determining total and regional (arms, legs, trunk) fat, lean, and bone mass and (2) to compare lean soft tissue (LST) hydration correction methods in children. One hundred and twenty four healthy children aged between 6 and 16 years old underwent DXA scans using 2 GE healthcare Lunar systems (iDXA and Prodigy). Tissue hydration was either calculated by dividing total body water (TBW), by 4-component model derived fat free mass (HFFMTBW) or by using the age and sex specific coefficients of Lohman, 1986 (HFFMLohman) and used to correct LST. Regression analysis was performed to develop cross-calibration equations between DXA systems and a paired samples t-test was conducted to assess the difference between LST hydration correction methods. iDXA resulted in significantly lower estimates of total and regional fat and lean mass, compared to Prodigy. HFFMTBW showed a much larger age/sex related variability than HFFMLohman. A 2.0 % difference in LST was observed in the boys (34.5 kg vs 33.8 kg respectively, p < 0.05) and a 2.5% difference in the girls (28.2 kg vs 27.5 kg respectively, p < 0.05) when corrected using either HFFMTBW or HFFMLohman. Care needs to be exercised when combining data from iDXA and Prodigy, as total and regional estimates of body composition can differ significantly. Furthermore, tissue hydration should be taken into account when assessing body composition as it can vary considerably within a healthy paediatric population even within specific age and/or sex groups.

Validity and reliability of an online self-report 24-h dietary recall method (Intake24): a doubly labelled water study and repeated-measures analysis.

Online self-reported 24-h dietary recall systems promise increased feasibility of dietary assessment. Comparison against interviewer-led recalls established their convergent validity; however, reliability and criterion-validity information is lacking. The validity of energy intakes (EI) reported using Intake24, an online 24-h recall system, was assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water in ninety-eight UK adults (40-65 years). Accuracy and precision of EI were assessed using correlation and Bland-Altman analysis. Test-retest reliability of energy and nutrient intakes was assessed using data from three further UK studies where participants (11-88 years) completed Intake24 at least four times; reliability was assessed using intra-class correlations (ICC). Compared with TEE, participants under-reported EI by 25 % (95 % limits of agreement -73 % to +68 %) in the first recall, 22 % (-61 % to +41 %) for average of first two, and 25 % (-60 % to +28 %) for first three recalls. Correlations between EI and TEE were 0·31 (first), 0·47 (first two) and 0·39 (first three recalls), respectively. ICC for a single recall was 0·35 for EI and ranged from 0·31 for Fe to 0·43 for non-milk extrinsic sugars (NMES). Considering pairs of recalls (first two v. third and fourth recalls), ICC was 0·52 for EI and ranged from 0·37 for fat to 0·63 for NMES. EI reported with Intake24 was moderately correlated with objectively measured TEE and underestimated on average to the same extent as seen with interviewer-led 24-h recalls and estimated weight food diaries. Online 24-h recall systems may offer low-cost, low-burden alternatives for collecting dietary information.

Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders.

BACKGROUND: Energy expenditure prediction equations are used to estimate energy intake based on general population measures. However, when using equations to compare with a disease cohort with known metabolic abnormalities, it is important to derive one's own equations based on measurement conditions matching the disease cohort. OBJECTIVE: We aimed to use newly developed prediction equations based on a healthy pediatric population to describe and predict resting energy expenditure (REE) in a cohort of pediatric patients with thyroid disorders. METHODS: Body composition was measured by DXA and REE was assessed by indirect calorimetry in 201 healthy participants. A prediction equation for REE was derived in 100 healthy participants using multiple linear regression and z scores were calculated. The equation was validated in 101 healthy participants. This method was applied to participants with resistance to thyroid hormone (RTH) disorders, due to mutations in either thyroid hormone receptor ß or α (ß: female n = 17, male n = 9; α: female n = 1, male n = 1), with deviation of REE in patients compared with the healthy population presented by the difference in z scores. RESULTS: The prediction equation for REE = 0.061 * Lean soft tissue (kg) - 0.138 * Sex (0 male, 1 female) + 2.41 (R2 = 0.816). The mean ± SD of the residuals is -0.02 ± 0.44 kJ/min. Mean ± SD REE z scores for RTHß patients are -0.02 ± 1.26. z Scores of -1.69 and -2.05 were recorded in male (n = 1) and female ( n = 1) RTHα patients. CONCLUSIONS: We have described methodology whereby differences in REE between patients with a metabolic disorder and healthy participants can be expressed as a z score. This approach also enables change in REE after a clinical intervention (e.g., thyroxine treatment of RTHα) to be monitored.

Validity of energy expenditure estimation methods during 10 days of military training.

Wearable physical activity (PA) monitors have improved the ability to estimate free-living total energy expenditure (TEE) but their application during arduous military training alongside more well-established research methods has not been widely documented. This study aimed to assess the validity of two wrist-worn activity monitors and a PA log against doubly labeled water (DLW) during British Army Officer Cadet (OC) training. For 10 days of training, twenty (10 male and 10 female) OCs (mean ± SD: age 23 ± 2 years, height 1.74 ± 0.09 m, body mass 77.0 ± 9.3 kg) wore one research-grade accelerometer (GENEActiv, Cambridge, UK) on the dominant wrist, wore one commercially available monitor (Fitbit SURGE, USA) on the non-dominant wrist, and completed a self-report PA log. Immediately prior to this 10-day period, participants consumed a bolus of DLW and provided daily urine samples, which were analyzed by mass spectrometry to determine TEE. Bivariate correlations and limits of agreement (LoA) were employed to compare TEE from each estimation method to DLW. Average daily TEE from DLW was 4112 ± 652 kcal·day-1 against which the GENEActiv showed near identical average TEE (mean bias ± LoA: -15 ± 851 kcal. day-1 ) while Fitbit tended to underestimate (-656 ± 683 kcal·day-1 ) and the PA log substantially overestimate (+1946 ± 1637 kcal·day-1 ). Wearable physical activity monitors provide a cheaper and more practical method for estimating free-living TEE than DLW in military settings. The GENEActiv accelerometer demonstrated good validity for assessing daily TEE and would appear suitable for use in large-scale, longitudinal military studies.

Erratum: Validity and reliability of an online self-report 24-hour dietary recall method (Intake24): A doubly-labelled water study and repeated measures analysis - CORRIGENDUM.

[This corrects the article DOI: 10.1017/jns.2019.20.].

Implications of the variation in biological 18 O natural abundance in body water to inform use of Bayesian methods for modelling total energy expenditure when using doubly labelled water.

RATIONALE: Variation in 18 O natural abundance can lead to errors in the calculation of total energy expenditure (TEE) when using the doubly labelled water (DLW) method. The use of Bayesian statistics allows a distribution to be assigned to 18 O natural abundance, thus allowing a best-fit value to be used in the calculation. The aim of this study was to calculate within-subject variation in 18 O natural abundance and apply this to our original working model for TEE calculation. METHODS: Urine samples from a cohort of 99 women, dosed with 50 g of 20% 2 H2 O, undertaking a 14-day breast milk intake protocol, were analysed for 18 O. The within-subject variance was calculated and applied to a Bayesian model for the calculation of TEE in a separate cohort of 36 women. This cohort of 36 women had taken part in a DLW study and had been dosed with 80 mg/kg body weight 2 H2 O and 150 mg/kg body weight H2 18 O. RESULTS: The average change in the δ18 O value from the 99 women was 1.14‰ (0.77) [0.99, 1.29], with the average within-subject 18 O natural abundance variance being 0.13‰2 (0.25) [0.08, 0.18]. There were no significant differences in TEE (9745 (1414), 9804 (1460) and 9789 (1455) kJ/day, non-Bayesian, Bluck Bayesian and modified Bayesian models, respectively) between methods. CONCLUSIONS: Our findings demonstrate that using a reduced natural variation in 18 O as calculated from a population does not impact significantly on the calculation of TEE in our model. It may therefore be more conservative to allow a larger variance to account for individual extremes.

Sex Differences in Training Loads during British Army Basic Training.

PURPOSE: To compare training loads between men and women during 14 wk of British Army standard entry basic training. METHODS: Thirty-one male (mean ± SD: age, 21 ± 4 yr; height, 1.78 ± 0.08 m; mass, 77.1 ± 10.5 kg) and 28 female (age, 22 ± 4 yr; height, 1.65 ± 0.05 m; mass, 63.9 ± 8.9 kg) British Army recruits had external (distance) and internal (HR, training impulse [TRIMP], RPE) training loads measured during weeks 1, 2, 6, 12, and 13 of basic training. Total energy expenditure was measured during weeks 1 to 2 and weeks 12 to 13. RESULTS: Daily distance was higher for men than women (13,508 ± 666 vs 11,866 ± 491 m, respectively, P < 0.001). Average daily HR (29% ± 3% vs 30% ± 3% HR reserve) and RPE (4 ± 1 vs 4 ± 1) were not different between men and women, respectively (P ≥ 0.495). Daily TRIMP was higher for women than men (492 ± 130 vs 261 ± 145 au, respectively, P < 0.001). Total energy expenditure was higher for men than women during weeks 1 to 2 (4020 ± 620 vs 2847 ± 323 kcal·d, respectively) and weeks 12 to 13 (4253 ± 556 kcal·d vs 3390 ± 344 kcal·d, respectively) (P < 0.001). Daily RPE, HR, and TRIMP were related to daily distance (R = 0.18-0.57, P ≤ 0.037), and daily RPE was related to daily TRIMP and HR (R = 0.37-0.77, P ≤ 0.001). CONCLUSIONS: Sex differences in training loads could contribute to the greater injury risk for women during basic training. Daily RPE appears a practical option for measuring internal training load during military training.

An Investigation Into the Differences in Bone Density and Body Composition Measurements Between 2 GE Lunar Densitometers and Their Comparison to a 4-Component Model.

We describe a study to assess the precision of the GE Lunar iDXA and the agreement between the iDXA and GE Lunar Prodigy densitometers for the measurement of regional- and total-body bone and body composition in normal to obese healthy adults. We compare the whole-body fat mass by dual-energy X-ray absorptiometry (DXA) to measurements by a 4-component (4-C) model. Sixty-nine participants, aged 37 ± 12 yr, with a body mass index of 26.2 ± 5.1 kg/cm2, were measured once on the Prodigy and twice on the iDXA. The 4-C model estimated fat mass from body mass, total body water by deuterium dilution, body volume by air displacement plethysmography, and bone mass by DXA. Agreements between measurements made on the 2 instruments and by the 4-C model were analyzed by Bland-Altman and linear regression analyses. Where appropriate, translational cross-calibration equations were derived. Differences between DXA software versions were investigated. iDXA precision was less than 2% of the measured value for all regional- and whole-body bone and body composition measurements with the exception of arm fat mass (2.28%). We found significant differences between iDXA and Prodigy (p < 0.05) whole-body and regional bone, fat mass (FM), and lean mass, with the exception of hip bone mass, area and density, and spine area. Compared to iDXA, Prodigy overestimated FM and underestimated lean mass. However, compared to 4-C, iDXA showed a smaller bias and narrower limits of agreement than Prodigy. No significant differences between software versions in FM estimations existed. Our results demonstrate excellent iDXA precision. However, significant differences exist between the 2 GE Lunar instruments, Prodigy and iDXA measurement values. A divergence from the reference 4-C observations remains in FM estimations made by DXA even following the recent advances in technology. Further studies are particularly warranted in individuals with large FM contents.

Probiotic supplementation prevents high-fat, overfeeding-induced insulin resistance in human subjects.

The purpose of the present study was to determine whether probiotic supplementation (Lactobacillus casei Shirota (LcS)) prevents diet-induced insulin resistance in human subjects. A total of seventeen healthy subjects were randomised to either a probiotic (n 8) or a control (n 9) group. The probiotic group consumed a LcS-fermented milk drink twice daily for 4 weeks, whereas the control group received no supplementation. Subjects maintained their normal diet for the first 3 weeks of the study, after which they consumed a high-fat (65 % of energy), high-energy (50 % increase in energy intake) diet for 7 d. Whole-body insulin sensitivity was assessed by an oral glucose tolerance test conducted before and after overfeeding. Body mass increased by 0·6 (SE 0·2) kg in the control group (P< 0·05) and by 0·3 (SE 0·2) kg in the probiotic group (P>0·05). Fasting plasma glucose concentrations increased following 7 d of overeating (control group: 5·3 (SE 0·1) v. 5·6 (SE 0·2) mmol/l before and after overfeeding, respectively, P< 0·05), whereas fasting serum insulin concentrations were maintained in both groups. Glucose AUC values increased by 10 % (from 817 (SE 45) to 899 (SE 39) mmol/l per 120 min, P< 0·05) and whole-body insulin sensitivity decreased by 27 % (from 5·3 (SE 1·4) to 3·9 (SE 0·9), P< 0·05) in the control group, whereas normal insulin sensitivity was maintained in the probiotic group (4·4 (SE 0·8) and 4·5 (SE 0·9) before and after overeating, respectively (P>0·05). These results suggest that probiotic supplementation may be useful in the prevention of diet-induced metabolic diseases such as type 2 diabetes.

Training with low muscle glycogen enhances fat metabolism in well-trained cyclists.

PURPOSE: To determine the effects of training with low muscle glycogen on exercise performance, substrate metabolism, and skeletal muscle adaptation. METHODS: Fourteen well-trained cyclists were pair-matched and randomly assigned to HIGH- or LOW-glycogen training groups. Subjects performed nine aerobic training (AT; 90 min at 70% VO2max) and nine high-intensity interval training sessions (HIT; 8 × 5-min efforts, 1-min recovery) during a 3-wk period. HIGH trained once daily, alternating between AT on day 1 and HIT the following day, whereas LOW trained twice every second day, first performing AT and then, 1 h later, performing HIT. Pretraining and posttraining measures were a resting muscle biopsy, metabolic measures during steady-state cycling, and a time trial. RESULTS: Power output during HIT was 297 ± 8 W in LOW compared with 323 ± 9 W in HIGH (P < 0.05); however, time trial performance improved by ∼10% in both groups (P < 0.05). Fat oxidation during steady-state cycling increased after training in LOW (from 26 ± 2 to 34 ± 2 µmol·kg−¹·min−¹, P < 0.01). Plasma free fatty acid oxidation was similar before and after training in both groups, but muscle-derived triacylglycerol oxidation increased after training in LOW (from 16 ± 1 to 23 ± 1 µmol·kg−¹·min−¹, P < 0.05). Training with low muscle glycogen also increased ß-hydroxyacyl-CoA-dehydrogenase protein content (P < 0.01). CONCLUSIONS: Training with low muscle glycogen reduced training intensity and, in performance, was no more effective than training with high muscle glycogen. However, fat oxidation was increased after training with low muscle glycogen, which may have been due to the enhanced metabolic adaptations in skeletal muscle.

Physical inactivity and obesity: links with insulin resistance and type 2 diabetes mellitus.

Data from the health survey for England 2006, showed that the prevalence of type 2 diabetes mellitus (T2DM) has more than doubled in men and women since 1991. In the USA certain States have a prevalence of T2DM of greater than 10%. Globally it has been reported that this increase is by no means slowing down and that the number of individuals with the disease is expected to rise from 171 million cases reported in 2000 to 366 million by the year 2030. Physical inactivity and obesity are two major risk factors for the development of T2DM. In this review we will discuss evidence of an association between physical inactivity, obesity and T2DM from prospective cohort studies and clinical trials. We will also discuss some of the potential mechanisms that are thought to link obesity and physical inactivity with the major pathophysiological precursor of T2DM, insulin resistance.

Oxidation of maltose and trehalose during prolonged moderate-intensity exercise.

PURPOSE: The aim of the present study was to compare the effects of trehalose (TRE) and maltose (MAL) ingestion on exogenous carbohydrate oxidation rates and blood metabolite responses during prolonged moderate-intensity cycling exercise. METHODS: Nine trained subjects performed three randomly assigned bouts of exercise separated by at least 1 wk. Each trial consisted of 150 min of cycling at 55% of maximal power output (Wmax) while ingesting a solution providing either 1.1 g x min(-1) TRE, 1.1 g x min(-1) MAL, or water (WAT). RESULTS: Total carbohydrate oxidation rates were significantly higher (P < 0.05) in both the MAL (2.09 +/- 0.18 g x min(-1)) and TRE (1.92 +/- 0.32 g x min(-1)) trials compared with the WAT trial (1.62 +/- 0.28 g x min(-1)). Peak exogenous carbohydrate oxidation was significantly higher in the MAL trial compared with the TRE trial (1.01 +/- 0.24 and 0.73 +/- 0.22 g x min(-1), respectively, P < 0.05). The MAL trial resulted in significantly reduced endogenous carbohydrate oxidation rates compared with the WAT trial (1.20 +/- 0.25 and 1.62 +/- 0.28 g x min(-1), respectively, P < 0.05). When compared with the WAT trial, total fat oxidation for the same period was significantly reduced in both carbohydrate trials (0.91 +/- 0.19, 0.68 +/- 0.19, and 0.79 +/- 0.19 g x min(-1) for WAT, MAL, and TRE, respectively, P < 0.05) and tended to be lower in MAL compared with TRE (P < 0.06). DISCUSSION: Both solutions maintained high plasma glucose concentrations. MAL had a "sparing" effect on endogenous carbohydrate stores. The reduced exogenous carbohydrate oxidation rate of TRE compared to MAL is probably due to a reduced enzymatic hydrolysis rate within the small intestine, causing a slower availability.

Endurance training and obesity: effect on substrate metabolism and insulin sensitivity.

PURPOSE: Obesity and type 2 diabetes mellitus are disease states associated with hallmark features such as insulin resistance and an impaired ability to oxidize lipids. It has recently been reported that an optimal exercise intensity for fat oxidation (FATmax) exists; we hypothesize that continuous exercise training at this specific intensity can lead to greater improvements in fat oxidation and insulin sensitivity than a eucaloric interval training program. METHODS: In a counterbalanced, crossover design, eight sedentary, obese, but otherwise healthy male participants performed two 4-wk blocks of endurance training, either at a predetermined intensity eliciting maximal fat oxidation (TPCON) or at 5-min intervals of +/- 20% FATmax (TPINT). During the week preceding the exercise training and 48 h after the final exercise bout, an OGTT, V O2max test, steady-state exercise, and measurements of body composition were undertaken. Diet was controlled the day before all trials (50% carbohydrate, 35% fat, and 15% protein; approximately 2900 kcal.d). Variables were compared using two-way repeated-measures analyses of variance. RESULTS: It was shown that fat oxidation rates were increased by 44% after TPCON (0.24 +/- 0.01 vs 0.35 +/- 0.03 g.min, P < 0.05) but not after TPINT, and the whole-body insulin sensitivity index was increased by 27% after TPCON (P < 0.05). These changes occurred despite no change in body weight, body mass index (BMI), waist to hip ratio (WHR), percent body fat (%BF), or V O2max. CONCLUSIONS: A continuous exercise training protocol that can elicit high rates of fat oxidation increases the contribution of fat to substrate oxidation during exercise and can significantly increase insulin sensitivity compared with a eucaloric interval protocol.

Acceleration versus heart rate for estimating energy expenditure and speed during locomotion in animals: tests with an easy model species, Homo sapiens.

An important element in the measurement of energy budgets of free-living animals is the estimation of energy costs during locomotion. Using humans as a particularly tractable model species, we conducted treadmill experiments to test the validity of tri-axial accelerometry loggers, designed for use with animals in the field, to estimate rate of oxygen consumption (VO2: an indirect measure of metabolic rate) and speed during locomotion. The predictive power of overall dynamic body acceleration (ODBA) obtained from loggers attached to different parts of the body was compared to that of heart rate (fH). When subject identity was included in the statistical analysis, ODBA was a good, though slightly poorer, predictor of VO2 and speed during locomotion on the flat (mean of two-part regressions: R2=0.91 and 0.91, from a logger placed on the neck) and VO2 during gradient walking (single regression: R2=0.77 from a logger placed on the upper back) than was fH (R2=0.96, 0.94, 0.86, respectively). For locomotion on the flat, ODBA was still a good predictor when subject identity was replaced by subject mass and height (morphometrics typically obtainable from animals in the field; R2=0.92 and 0.89) and a slightly better overall predictor than fH (R2=0.92 and 0.85). For gradient walking, ODBA predicted VO2 more accurately than before (R2=0.83) and considerably better than did fH (R2=0.77). ODBA and fH combined were the most powerful predictor of VO2 and speed during locomotion. However, ODBA alone appears to be a good predictor and suitable for use in the field in particular, given that accelerometry traces also provide information on the timing, frequency and duration of locomotion events, and also the gait being used.

Green tea extract ingestion, fat oxidation, and glucose tolerance in healthy humans.

BACKGROUND: Green tea consumption is reportedly associated with various health-promoting properties. For example, it has been shown to promote fat oxidation in humans at rest and to prevent obesity and improve insulin sensitivity in mice. OBJECTIVE: We investigated the effects of acute ingestion of green tea extract (GTE) on glucose tolerance and fat oxidation during moderate-intensity exercise in humans. DESIGN: Two studies were performed, both with a counter-balanced crossover design. In study A, 12 healthy men performed a 30-min cycling exercise at 60% of maximal oxygen consumption (VO2max) before and after supplementation. In study B, 11 healthy men took an oral-glucose-tolerance test before and after supplementation. In the 24-h period before the experimental trials, participants ingested 3 capsules containing either GTE (total: 890 +/- 13 mg polyphenols and 366 +/- 5 mg EGCG) or a corn-flour placebo (total: 1729 +/- 22 mg). RESULTS: Average fat oxidation rates were 17% higher after ingestion of GTE than after ingestion of placebo (0.41 +/- 0.03 and 0.35 +/- 0.03 g/min, respectively; P < 0.05). Moreover, the contribution of fat oxidation to total energy expenditure was also significantly higher, by a similar percentage, after GTE supplementation. The insulin area under the curve decreased in both the GTE and placebo trials (3612 +/- 301 and 4280 +/- 309 microIU/dL . 120 min, respectively; P < 0.01), and there was a concomitant increase of 13% in insulin sensitivity. CONCLUSIONS: Acute GTE ingestion can increase fat oxidation during moderate-intensity exercise and can improve insulin sensitivity and glucose tolerance in healthy young men.

Effect of acute exercise on glucose tolerance following post-exercise feeding.

It is well documented that a single bout of endurance exercise (EE) can improve insulin sensitivity, whereas relatively little is known about the acute effects of resistance exercise (RE) in humans. The objective of this study is to investigate the insulin and glucose responses to an oral glucose tolerance test (OGTT) following a high intensity bout of either EE or RE followed by post-exercise carbohydrate-protein hydrolysate ingestion. Eighteen participants were divided into two groups: a group in which nine participants completed 1 h of EE (cycle ergometry at 75% W (max)) and a RE group in which nine participants completed a RE circuit (3 sets of 10 repetitions). Participants ingested 1.5 l of a carbohydrate (200 g)-protein hydrolysate (50 g) beverage within 1 h of exercise completion. An OGTT was performed 6 h post-exercise. On the control day the endurance and resistance groups performed the above protocol without the prior exercise (CEE or CRE). The control and exercise days were counterbalanced. RE reduced plasma glucose AUC (822 +/- 68 vs. 694 +/- 23 mmol l(-1).120 min; CRE vs. RE, respectively; P < 0.05) but EE did not lead to a change (784 +/- 40 vs. 835 +/- 59 mmol l(-1).120 min; CEE vs. EE, respectively). Plasma insulin AUC remained unchanged compared to the control in both the RE and EE groups. The results suggest that the benefit of RE on glucose tolerance following CHO intake remains for 6 h even when a carbohydrate-protein hydrolysate beverage was ingested within 1 h after exercise, while the well documented benefit of EE was not observed.