Validation study of energy expenditure and intake during calorie restriction using doubly labeled water and changes in body composition

Increasing the health span: unique role for exercise

Health span, that period between birth and onset of major disease(s), when adequate physical and cognitive function permit those daily living activities essential to life quality, is lower in the United States than other developed countries. Physical inactivity and excessive calorie intake occupy dominant roles both in the problem, and by redressing them, in the solution. Consequently, this review focuses on evidence that appropriate exercise engagement and calorie restriction (CR) can improve physical and mental health with a view to extending the health span. Humanity, writ large, has grasped these underlying concepts for Millennia but has been largely intransigent to them. Thus, the final section proposes a novel Monty Python-esque approach that encompasses humanity's inimical sense of humor to increase physical fitness and mental health, restore energy balance, sustain better cognitive function, and extend the health span.

Energy expenditure, intake and availability in female soccer players via doubly labelled water: Are we misrepresenting low energy availability?

Female soccer players have been identified as presenting with low energy availability (LEA), though the prevalence of LEA may be overestimated given inaccuracies associated with self-reporting dietary intakes. Accordingly, we aimed to quantify total daily energy expenditure (TDEE) via the doubly labelled water (DLW) method, energy intake (EI) and energy availability (EA). Adolescent female soccer players (n = 45; 16 ± 1 years) completed a 9-10 day 'training camp' representing their national team. Absolute and relative TDEE was 2683 ± 324 and 60 ± 7 kcal kg-1 fat free mass (FFM), respectively. Mean daily EI was lower (P < 0.01) when players self-reported using the remote food photography method (RFPM) (2047 ± 383 kcal day-1) over a 3-day period versus DLW derived EI estimates accounting for body mass (BM) changes (2545 ± 518 kcal day-1) over 7-8 days, representing a mean daily Δ of 499 ± 526 kcal day-1 and 22% error when using the RFPM. Estimated EA was different (P < 0.01) between methods (DLW: 48 ± 14 kcal kg-1 FFM, range: 22-82; RFPM: 37 ± 8 kcal kg-1 FFM, range: 22-54), such that prevalence of LEA (<30 kcal kg-1 FFM) was lower in DLW compared with RFPM (5% vs. 15%, respectively). Data demonstrate the potential to significantly underestimate EI when using self-report methods. This approach can therefore cause a misrepresentation and an over-prevalence of LEA, which is the underlying aetiology of 'relative energy deficiency in sport' (REDs). HIGHLIGHTS: What is the central question of this study? Do self-reported dietary intakes (via remote food photography method, RFPM) overestimate low energy availability (LEA) prevalence in female soccer players compared with energy intake evaluation from the doubly labelled water (DLW) method? What is the main finding and its importance? Estimated energy availability is greater with the DLW method compared with RFPM, such that the prevalence of LEA is greater when self-reporting dietary intakes. Accordingly, data demonstrate the potential to misrepresent the prevalence of LEA, an underlying factor in the aetiology of 'relative energy deficiency in sport' (REDs).

Intake Biomarkers for Nutrition and Health: Review and Discussion of Methodology Issues

Metabolomics profiles from blood, urine, or other body fluids have the potential to assess intakes of foods and nutrients objectively, thereby strengthening nutritional epidemiology research. Metabolomics platforms may include targeted components that estimate the relative concentrations for individual metabolites in a predetermined set, or global components, typically involving mass spectrometry, that estimate relative concentrations more broadly. While a specific metabolite concentration usually correlates with the intake of a single food or food group, multiple metabolites may be correlated with the intake of certain foods or with specific nutrient intakes, each of which may be expressed in absolute terms or relative to total energy intake. Here, I briefly review the progress over the past 20 years on the development and application intake biomarkers for foods/food groups, nutrients, and dietary patterns, primarily by drawing from several recent reviews. In doing so, I emphasize the criteria and study designs for candidate biomarker identification, biomarker validation, and intake biomarker application. The use of intake biomarkers for diet and chronic disease association studies is still infrequent in nutritional epidemiology research. My comments here will derive primarily from our research group's recent contributions to the Women's Health Initiative cohorts. I will complete the contribution by describing some opportunities to build on the collective 20 years of effort, including opportunities related to the metabolomics profiling of blood and urine specimens from human feeding studies that approximate habitual diets.

Biomarker-assessed total energy intake and its cohort study association with all-cause mortality in postmenopausal females

BACKGROUND

The association of total energy intake (EI) with all-cause mortality is uncertain as are the dependencies of this association on age and weight change history.

OBJECTIVES

To identify an EI biomarker suitable for use in epidemiologic association studies and to study EI associations with total mortality in a Women's Health Initiative (WHI) cohort of postmenopausal United States females (1993-present).

METHODS

EI biomarkers were developed based on doubly labeled water (DLW) total energy expenditure (TEE) and weight variation during the 2-wk DLW protocol period using the energy balance method in an embedded feeding study (n = 153). This along with 2 earlier WHI nutrition biomarker studies having TEE assessments (n = 1131 total), with 14.6 y (median) follow-up, constituted a prospective cohort for the study of EI and all-cause mortality.

RESULTS

An empirical biomarker for log(EI) was developed that had a correlation of 0.73 with log(feeding study-consumed EI). The overall association between EI and mortality was nonsignificant. The association, however, depended on age (P = 0.009), with lower EI associated with lower mortality at younger ages, and also on preceding weight change history (P = 0.03). Among participants with stable or increasing weight, mortality hazard ratios (95% confidence intervals [CIs]) for a 12% lower EI were 0.66 (95% CI: 0.51, 0.87) at age 60, 0.84 (95% CI: 0.72, 0.98) at age 70, and 1.06 (95% CI: 0.87, 1.29) at age 80. Corresponding values for participants having preceding weight loss were 0.83 (95% CI: 0.61, 1.12) at age 60, 1.05 (95% CI: 0.87, 1.26) at age 70, and 1.33 (95% CI: 1.08, 1.63) at age 80. A previously considered EI biomarker, using a theoretical model for variation in body fat and fat-free mass components over time, gave similar results following rescaling.

CONCLUSIONS

Lower EI is associated with lower all-cause mortality among younger postmenopausal females with stable or increasing weight and with higher mortality among older females with weight loss. This study was registered with clinicaltrials.gov as NCT00000611.

The impact of body composition on the degree of misreporting of food diaries

BACKGROUND/OBJECTIVES

Accurate assessments of energy intake (EI) are needed in lifestyle interventions to guarantee a negative energy balance (EB), thereby losing weight. This study aimed (1) to compare objectively measured and self-reported EI and (2) to determine the predictors of underreporting divided by sex, adiposity and BMI category.

METHODS

Seventy-three participants [mean (SD): 43.7 (9.2) years, BMI = 31.5 (4.5) kg/m2, 37% females] of the Champ4Life intervention were included in this study. EI was measured using the "intake-balance method" and self-reported through 3-day food records. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry. Bland-Altman analysis was performed to compare both EI assessments.

RESULTS

Self-reported EI was lower than measured EI during both neutral (-355 kcal/d) and negative EB (-570 kal/day). While no significant trends were observed for EI evaluation in either neutral (p = 0.315) or negative EB (p = 0.611), limits of agreement were wide (-1720 to 1010 and -1920 to 779 kcal/day, respectively). In females, the degree of misreporting (kcal/day and %) was predicted by weight (p = 0.032 and p = 0.039, respectively) and FM (p = 0.029 and p = 0.037, respectively). In males, only BMI (p = 0.036) was a predictor of misreporting (kcal/day).

CONCLUSION

Self-reported EI did not agree with measured EI. Our results show that larger body size was associated with higher levels of underestimation for EI (females only). Nevertheless, misreporting EI is a complex issue involving more associations than merely body composition. A deeper understanding could inform counseling for participants filling out food records in other to reduce misreporting and improve validity.

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

BACKGROUND

Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device.

METHODS

Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland-Altman analysis.

RESULTS

Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323-362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353-464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland-Altman analysis.

CONCLUSIONS

Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).

Predicting energy intake with an accelerometer-based intake-balance method

Nutritional interventions often rely on subjective assessments of energy intake (EI), but these are susceptible to measurement error. To introduce an accelerometer-based intake-balance method for assessing EI using data from a time-restricted eating (TRE) trial. Nineteen participants with overweight/obesity (25-63 years old; 16 females) completed a 12-week intervention (NCT03129581) in a control group (unrestricted feeding; n 8) or TRE group (n 11). At the start and end of the intervention, body composition was assessed by dual-energy X-ray absorptiometry (DXA) and daily energy expenditure (EE) was assessed for 2 weeks via wrist-worn accelerometer. EI was back-calculated as the sum of net energy storage (from DXA) and EE (from accelerometer). Accelerometer-derived EI estimates were compared against estimates from the body weight planner of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Mean EI for the control group declined by 138 and 435 kJ/day for the accelerometer and NIDDK methods, respectively (both P ≥ 0·38), v. 1255 and 1469 kJ/day, respectively, for the TRE group (both P < 0·01). At follow-up, the accelerometer and NIDDK methods showed excellent group-level agreement (mean bias of -297 kJ/day across arms; standard error of estimate 1054 kJ/day) but high variability at the individual level (limits of agreement from -2414 to +1824 kJ/day). The accelerometer-based intake-balance method showed plausible sensitivity to change, and EI estimates were biologically and behaviourally plausible. The method may be a viable alternative to self-report EI measures. Future studies should assess criterion validity using doubly labelled water.

Time-Restricted Eating Without Calorie Counting for Weight Loss in a Racially Diverse Population : A Randomized Controlled Trial

BACKGROUND

Time-restricted eating (TRE), without calorie counting, has become a popular weight loss strategy, yet long-term randomized trials evaluating its efficacy are limited.

OBJECTIVE

To determine whether TRE is more effective for weight control and cardiometabolic risk reduction compared with calorie restriction (CR) or control.

DESIGN

12-month randomized controlled trial. (ClinicalTrials.gov: NCT04692532).

SETTING

University of Illinois Chicago from January 2021 to September 2022.

PARTICIPANTS

90 adults with obesity.

INTERVENTION

8-hour TRE (eating between noon and 8:00 p.m. only, without calorie counting), CR (25% energy restriction daily), or control (eating over a period of 10 or more hours per day). Participants were not blinded.

MEASUREMENTS

Change in body weight, metabolic markers, and energy intake by month 12.

RESULTS

Seventy-seven persons completed the study. Mean age was 40 years (SD, 11), 33% were Black, and 46% were Hispanic. Mean reduction in energy intake was -425 kcal/d (SD, 531) for TRE and -405 kcal/d (SD, 712) for CR. Compared with the control group, weight loss by month 12 was -4.61 kg (95% CI, -7.37 to -1.85 kg; P ≤ 0.01) (-4.87% [CI, -7.61% to -2.13%]) for the TRE group and -5.42 kg (CI, -9.13 to -1.71 kg; P ≤ 0.01) (-5.30% [CI, -9.06% to -1.54%]) for the CR group, with no statistically significant difference between TRE and CR (0.81 kg [CI, -3.07 to 4.69 kg; P = 0.68]) (0.43% [CI, -3.48% to 4.34%]).

LIMITATION

Not blinded, not powered to detect relatively large differences in weight loss, and lack of adjustment for multiple comparisons.

CONCLUSION

Time-restricted eating is more effective in producing weight loss when compared with control but not more effective than CR in a racially diverse population.

PRIMARY FUNDING SOURCE

National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases.

Measurement of Energy Intake Using the Principle of Energy Balance Overcomes a Critical Limitation in the Assessment of Energy Availability

Prolonged low energy availability, which is the underpinning aetiology of the Relative Energy Deficiency in Sport and the Female and Male Athlete Triad frameworks, can have unfavourable impacts on both health and performance in athletes. Energy availability is calculated as energy intake minus exercise energy expenditure, expressed relative to fat free mass. The current measurement of energy intake is recognized as a major limitation for assessing energy availability due to its reliance on self-report methods, in addition to its short-term nature. This article introduces the application of the energy balance method for the measurement of energy intake, within the context of energy availability. The energy balance method requires quantification of the change in body energy stores over time, with concurrent measurement of total energy expenditure. This provides an objective calculation of energy intake, which can then be used for the assessment of energy availability. This approach, the Energy Availability - Energy Balance (EA_EB) method, increases the reliance on objective measurements, provides an indication of energy availability status over longer periods and removes athlete burden to self-report energy intake. Implementation of the EA_EB method could be used to objectively identify and detect low energy availability, with implications for the diagnosis and management of Relative Energy Deficiency in Sport and the Female and Male Athlete Triad.

Issues related to the assessment of energy balance during short-term over-, under- and refeeding in normal weight men

BACKGROUND

In humans, it is unclear how different estimates of energy balance (EB) compare with each other and whether the resulting changes in body weight (bw) and body composition (BC) are predictable and reproducible.

METHODS

This is a secondary data analysis of effects of sequential 7d over- (OF), 21d under- (UF) and 14d refeeding (RF) on EB. Energy intake (EI) was controlled at +/- 50% of energy needs in a 32 normal weight men (see Am J Clin Nutr. 2015; 102:807-819). EB was calculated (i) directly from the difference between EI and energy expenditure (EE) and (ii) indirectly from changes in BC. Changes in fat mass (FM) were compared with predicted changes according to Hall et al. (Lancet 2011; 378:826-37). Finally, within-subject reproducibility of changes in bw and BC was tested in a subgroup.

RESULTS

There were interindividual and day-by-day variabilities in changes in bw and BC. During OF and RF, the two estimates of EB were similar while with UF the indirect approach underestimated the direct estimate by 10593 ± 7506 kcal/21d (p < 0.001). Considerable differences became evident between measured and predicted changes in FM. Adjusting measured for predicted values did not reduce their interindividual variance. During UF, changes in bw and BC were reproducible, while corresponding changes during OF were not.

CONCLUSION

During hypercaloric nutrition the direct estimate of EB corresponded to the indirect estimate whereas this was not true during UF. Changes in bw and BC in response to OF were not reproducible while they were during UF.

A New Approach to Improve the Validity of Doubly Labeled Water to Assess CO2 Production during High-Energy Turnover

PURPOSE

Accurate measurement of energy expenditure (EE) using doubly labeled water depends on the estimate of total body water (TBW). The aims of this study were to 1) assess the accuracy of a new approach for estimating TBW and EE during high-energy turnover and 2) assess the accuracy of day-to-day assessment of EE with this new approach.

METHODS

EE was measured in six healthy subjects (three male) for 5 consecutive days using three doubly labeled water methods: 1) the plateau, 2) slope-intercept, and 3) overnight-slope method, with whole-room indirect calorimetry as reference method. Urine samples were collected every evening and morning. High EE (physical activity level of >2.5) was achieved by cycling 4 h·d-1.

RESULTS

Physical activity level was 2.8 ± 0.1. TBW values were 41.9 ± 6.1, 38.4 ± 5.7, and 40.4 ± 5.8 L for the plateau, slope-intercept, and overnight-slope methods, respectively. The overnight-slope method showed the highest accuracy in estimated CO2 production, when compared with indirect calorimetry over the complete 5-d period (mean ± SD difference, 0.9% ± 1.6%). The plateau method significantly overestimated CO2 production by 4.7% ± 2.6%, whereas the slope-intercept method underestimated CO2 production (-3.4% ± 2.3%). When CO2 production was assessed per day, the overnight-slope method showed an average difference of 9.4% ± 4.5% to indirect calorimetry.

CONCLUSIONS

The overnight-slope method resulted in a more accurate estimation of CO2 production and EE compared with the plateau or slope-intercept method over a 5-d period in high physical activity conditions. Day-to-day determination of EE using the overnight-slope method was more accurate than diet recall and several standard prediction equations in athletes.

Commercial Devices Provide Estimates of Energy Balance with Varying Degrees of Validity in Free-Living Adults

BACKGROUND

The challenges of accurate estimation of energy intake (EI) are well-documented, with self-reported values 12%-20% below expected values. New approaches rely on gold-standard assessments of the other components of energy balance, energy expenditure (EE) and energy storage (ES), to estimate EI.

OBJECTIVES

The purpose of this study was to evaluate the validity, repeatability, and measurement error of consumer devices when estimating energy balance in a free-living population.

METHODS

Twenty-four healthy adults (14 women, 10 men; mean ± SD age: 30.7 ± 8.2 y) completed two 14-d assessment periods, including assessments of EE and ES using gold-standard [doubly labeled water (DLW) and DXA] and commercial devices [Fitbit Alta HR activity monitor (Alta) and Fitbit Aria wireless body composition scale (Aria)], and of EI by dietician-administered recalls. Accuracy and validity were assessed using Spearman correlation, interclass correlation, mean absolute percentage error, and equivalency testing. We also applied linear measurement error modeling including error in gold-standard devices and within-subject repeated-measures design to calibrate consumer devices and quantify error.

RESULTS

There was moderate to strong agreement for EE between the Fitbit Alta and DLW at each time point (rs = 0.82 and 0.66 for Times 1 and 2, respectively). There was weak agreement for ES between the Fitbit Aria and DXA (rs = 0.15 and 0.49 for Times 1 and 2, respectively). Correlations between methods to assess EI ranged from weak to strong, with agreement between the DXA/DLW-calculated EI and dietary recalls being the highest (rs = 0.63 for Time 1 and 0.73 for Time 2). Only EE from the Fitbit Alta at Time 1 was equivalent to the DLW value using equivalency testing.

CONCLUSIONS

Commercial devices provide estimates of energy balance in free-living adults with varying degrees of validity compared to gold-standard techniques. EE estimates were the most robust overall, whereas ES estimates were generally poor.

Metabolic adaptation delays time to reach weight loss goals

OBJECTIVE

The aim of this study was to determine whether metabolic adaptation, at the level of resting metabolic rate, was associated with time to reach weight loss goals, after adjusting for confounders.

METHODS

A total of 65 premenopausal women with overweight (BMI: 28.6 ± 1.5 kg/m2 ; age: 36.4 ± 5.9 years; 36 were White, and 29 were Black) followed an 800-kcal/d diet until BMI ≤25 kg/m2 . Body weight and composition were measured at baseline and after weight loss. Dietary adherence was calculated from total energy expenditure, determined by double labeled water, and body composition changes. Metabolic adaptation was defined as a significantly lower measured versus predicted resting metabolic rate (from own regression model). A regression model to predict time to reach weight loss goals was developed including target weight loss, energy deficit, dietary adherence, and metabolic adaptation as predictors.

RESULTS

Participants lost on average 12.5 ± 3.1 kg (16.1% ± 3.4%) over 155.1 ± 49.2 days. Average dietary adherence was 63.6% ± 31.0%. There was significant metabolic adaptation after weight loss (-46 ± 113 kcal/d, p = 0.002) and this variable was a significant predictor of time to reach weight loss goals (β = -0.1, p = 0.041), even after adjusting for confounders (R2 adjusted = 0.63, p < 0.001).

CONCLUSION

In premenopausal women with overweight, metabolic adaptation after a 16% weight loss increases the length of time necessary to achieve weight loss goals.

Changes in body weight and metabolic risk during time restricted feeding in premenopausal versus postmenopausal women

BACKGROUND

Time restricted feeding (TRF) involves confining the eating window to a specific number of hours, and fasting for the remaining hours of the day.

OBJECTIVE

This study examined if changes in body weight and metabolic risk factors during TRF, differ between premenopausal and postmenopausal women.

METHODS

This is a secondary analysis of an 8-week TRF study (4-6 h eating window, 18-20 h fasting window daily) conducted in adults with obesity. Male participants were excluded, and female subjects were classified in two groups based on menstrual status: premenopausal (n = 13), or postmenopausal (n = 19). Perimenopausal women were excluded from the original study.

RESULTS

Body weight decreased by week 8 in premenopausal women (-3.3 ± 0.4%) and postmenopausal women (-3.3 ± 0.5%) (main effect of time, P < 0.001), with no difference between groups (no group × time interaction). Adherence was excellent in both groups, with premenopausal women adhering to their prescribed eating window on 6.2 ± 0.1 d/week, and postmenopausal women adhering to their window on 6.2 ± 0.2 d/week. Fat mass, lean mass, fasting insulin, insulin resistance, and 8-isoprostane (marker of oxidative stress) were reduced similarly in both groups (main effect of time, P < 0.05 for all comparisons). Visceral fat mass, relative skeletal muscle index (RSMI), blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, fasting glucose, HbA1c, TNF-alpha and IL-6 remained unchanged in both groups by week 8.

CONCLUSION

These findings suggest that the weight loss and metabolic benefits of TRF do not differ between premenopausal and postmenopausal women with obesity.

Dietary Intake and Energy Expenditure in Breast Cancer Survivors: A Review

Many breast cancer survivors (BCS) gain fat mass and lose fat-free mass during treatment (chemotherapy, radiation, surgery) and estrogen suppression therapy, which increases the risk of developing comorbidities. Whether these body composition alterations are a result of changes in dietary intake, energy expenditure, or both is unclear. Thus, we reviewed studies that have measured components of energy balance in BCS who have completed treatment. Longitudinal studies suggest that BCS reduce self-reported energy intake and increase fruit and vegetable consumption. Although some evidence suggests that resting metabolic rate is higher in BCS than in age-matched controls, no study has measured total daily energy expenditure (TDEE) in this population. Whether physical activity levels are altered in BCS is unclear, but evidence suggests that light-intensity physical activity is lower in BCS compared to age-matched controls. We also discuss the mechanisms through which estrogen suppression may impact energy balance and develop a theoretical framework of dietary intake and TDEE interactions in BCS. Preclinical and human experimental studies indicate that estrogen suppression likely elicits increased energy intake and decreased TDEE, although this has not been systematically investigated in BCS specifically. Estrogen suppression may modulate energy balance via alterations in appetite, fat-free mass, resting metabolic rate, and physical activity. There are several potential areas for future mechanistic energetic research in BCS (e.g., characterizing predictors of intervention response, appetite, dynamic changes in energy balance, and differences in cancer sub-types) that would ultimately support the development of more targeted and personalized behavioral interventions.

An objective measure of energy intake using the principle of energy balance

BACKGROUND

The measurement of energy intake is central to the understanding of energy balance and predicting changes in body weight. Until recently, the most commonly used methods of assessing intake were self-reported diet recalls, diet diaries, or food-frequency questionnaires. These methods, however, are subject to systematic biases and are often inaccurate.

AIM

Review the validations and applications of an expenditure/balance method for measuring energy intake.

METHODS

Review the literature regarding the theory and practice of objectively measuring energy intake based on the principle of energy balance i.e., energy intake is calculated from the measured total energy expenditure plus the change in body energy stores (ES). The attainable precision is modeled and compared with the accuracy and precision of validations against known energy intake.

RESULTS

Measurement of energy intake, calculated in this way, is accurate to within 2% and has a precision of 4-37% depending on the expenditure and body composition methods used and the time interval between measures. Applications of this expenditure/balance (EB) method have provided novel data on the compliance to dietary restriction and its association with physical activity interventions, and the effects of bariatric surgery on energy intake and weight gain. Practical limitations to this method, however, include cost and limited access to the analyses required by the DLW method.

CONCLUSION

The EB method of objectively measuring energy intake is objective, accurate, and reasonably precise. It is practical for moderate-sized studies.

A Novel Approach to Assess Metabolic Flexibility Overnight in a Whole-Body Room Calorimeter

OBJECTIVE

This study aimed to investigate a novel approach for determining the effects of energy-standardized dinner meals (high-fat and low-fat) on respiratory exchange ratio (RER) dynamics and metabolic flexibility.

METHODS

Using a randomized crossover study design, energy expenditure, RER, and macronutrient oxidation rates were assessed in response to a single dinner meal during an overnight stay in a whole-body room calorimeter. Eight healthy adults completed two overnight chamber stays while fed either a high-fat (60% fat, 20% carbohydrate [CHO], 20% protein; food quotient [FQ] = 0.784) or low-fat (20% fat, 60% CHO, 20% protein; FQ = 0.899) dinner containing 40% of daily energy requirements.

RESULTS

Following the low-fat meal, CHO oxidation first increased before decreasing, resulting in a 12-hour RER:FQ ratio close to 1.0 (0.986 ± 0.019, P = 0.06) and therefore resulting in a 12-hour equilibrated fat balance (29 ± 76 kcal/12 hours). Following the high-fat meal, participants had a RER:FQ ratio above 1.0 (1.061 ± 0.017, P < 0.01), resulting in a significant positive 12-hour fat balance of 376 ± 142 kcal/12 hours. Various RER trajectory parameters were significantly different following the high-fat and low-fat meals.

CONCLUSIONS

This proof-of-concept study provides an alternative approach to quantify metabolic flexibility in response to a high-fat dinner and it can be used to derive indexes of metabolic flexibility, such as the 12-hour RER:FQ ratio or the 12-hour fat balance.

Complementing subjective with objective data in analysing expertise: A machine-learning approach applied to badminton

This study aimed to assess which combination of subjective and empirical data might help to identify the expertise level. A group of 10 expert coaches classified 40 participants in 5 different expertise groups based on the video footage of the rallies. The expertise levels were determined using a typology based on a continuum of 5 conative stages: (1) structural, (2) functional, (3) technical, (4) contextual, and (5) expertise. The video allowed empirical measurement of the duration of the rallies, and tri-axial accelerometers measured the intensity of the player's involvement. A principal component analysis showed that two dimensions explained 54.9% of the total variance in the data and that conative stage and empirical parameters during rallies (duration, intensity of the game) were correlated with axis 1, whereas duration and acceleration data between rallies were correlated with axis 2. A random forest algorithm showed that among the parameters considered, acceleration, duration of the rallies, and time between rallies could predict conative stages with a prediction accuracy above possibility. This study suggests that performance analysis benefits from the confrontation of subjective and objective data in order to design training plans according to the expertise level of the participants.

Order of same-day concurrent training influences some indices of power development, but not strength, lean mass, or aerobic fitness in healthy, moderately-active men after 9 weeks of training

Background

The importance of concurrent exercise order for improving endurance and resistance adaptations remains unclear, particularly when sessions are performed a few hours apart. We investigated the effects of concurrent training (in alternate orders, separated by ~3 hours) on endurance and resistance training adaptations, compared to resistance-only training.

Materials and methods

Twenty-nine healthy, moderately-active men (mean ± SD; age 24.5 ± 4.7 y; body mass 74.9 ± 10.8 kg; height 179.7 ± 6.5 cm) performed either resistance-only training (RT, n = 9), or same-day concurrent training whereby high-intensity interval training was performed either 3 hours before (HIIT+RT, n = 10) or after resistance training (RT+HIIT, n = 10), for 3 d^.wk^-1 over 9 weeks. Training-induced changes in leg press 1-repetition maximal (1-RM) strength, countermovement jump (CMJ) performance, body composition, peak oxygen uptake (V˙O2peak), aerobic power (W˙peak), and lactate threshold (W˙LT) were assessed before, and after both 5 and 9 weeks of training.

Results

After 9 weeks, all training groups increased leg press 1-RM (~24–28%) and total lean mass (~3-4%), with no clear differences between groups. Both concurrent groups elicited similar small-to-moderate improvements in all markers of aerobic fitness (V˙O2peak ~8–9%; W˙LT ~16-20%; W˙peak ~14-15%). RT improved CMJ displacement (mean ± SD, 5.3 ± 6.3%), velocity (2.2 ± 2.7%), force (absolute: 10.1 ± 10.1%), and power (absolute: 9.8 ± 7.6%; relative: 6.0 ± 6.6%). HIIT+RT elicited comparable improvements in CMJ velocity only (2.2 ± 2.7%). Compared to RT, RT+HIIT attenuated CMJ displacement (mean difference ± 90%CI, -5.1 ± 4.3%), force (absolute: -8.2 ± 7.1%) and power (absolute: -6.0 ± 4.7%). Only RT+HIIT reduced absolute fat mass (mean ± SD, -11.0 ± 11.7%).

Conclusions

In moderately-active males, concurrent training, regardless of the exercise order, presents a viable strategy to improve lower-body maximal strength and total lean mass comparably to resistance-only training, whilst also improving indices of aerobic fitness. However, improvements in CMJ displacement, force, and power were attenuated when RT was performed before HIIT, and as such, exercise order may be an important consideration when designing training programs in which the goal is to improve lower-body power.

Acute Physiologic Effects of Performing Yoga in The Heat on Energy Expenditure, Range of Motion, and Inflammatory Biomarkers

Performing yoga in a heated environment (HY) is a popular exercise mode purported to improve range of motion (ROM), body composition, and aerobic fitness. The purpose of this investigation was to compare a session of HY to room temperature yoga (RTY) with regards to ROM, oxygen consumption, caloric expenditure, and biomarkers of acute stress and inflammation. Sixteen experienced yoga practitioners (F14, M2; 40 ± 11yr; 22.6 ± 1.8 kg/m2) completed a 1-hour standardized Bikram sequence in HY (105°F, 40°C) and RTY (74°F, 23.3°C) conditions (order of conditions randomized, humidity standardized at 40%). Intra-exercise metabolic gas exchange and heart rate (HR) was monitored using a metabolic cart. ROM measures were taken pre and post-exercise at the elbow, shoulder, hip, and knee. Cytokines interleukin 6,10 (IL-6, IL-10) and tumor-necrosis-factor alpha (TNF-α) were analyzed from blood samples collected pre- and 30-minutes post-exercise. Intra-exercise metabolic gas exchange and heart rate (HR) was monitored using a metabolic cart. Both bouts elicited similar acute changes in ROM although HY elicited a greater increase in hip abduction (RTYΔ° = 2.3 ± 1.3|HYΔ° = 6.6 ± 1.5; p < 0.05). Mean VO2, peak VO2, %VO2max, HR, and kcal expenditure did not differ between conditions. RER was lower during the HY (RTY = 0.95 ± 0.02| HY = 0.89 ± 0.02; p < 0.05) with a concomitant elevation in fat oxidation (RTY = 0.05 ± 0.01|HY = 0.09 ± 0.01, g·min-1; p < 0.05) and decrease in carbohydrate oxidation (RTY = 0.51 ± 0.04|HY = 0.44 ± 0.03, g·min-1; p < 0.05). Serum IL-6 was increased (15.5 ± 8.0-fold) following HY only (p < 0.05). HY does not significantly elevate aerobic energy cost compared to RTY but may acutely increase fat substrate utilization and hip ROM. Future studies remain needed to establish dose-response relationships for including HY or RTY into well-rounded fitness programs.

Effect of Over- and Underfeeding on Body Composition and Related Metabolic Functions in Humans

PURPOSE OF REVIEW

Methodological limitations of body composition methods limit the validity of changes in body composition that are used to interpret metabolic outcome parameters of weight loss and weight gain.

RECENT FINDINGS

Direct assessment of energy balance is necessary for the assessment of early weight changes (i.e., within the 1st week of weight change), whereas body composition analysis with a high accuracy and a low minimal detectable change is recommended to assess ongoing changes. The sequence of underfeeding and overfeeding impacts the method inherent assumptions, and the considerable day-to-day and inter-individual variance in body composition changes is a challenge to the precision of methods. Weight loss-associated changes in body composition do not resemble their changes with subsequent hypercaloric re-feeding. Individual body components are related to specific metabolic functions where the structure-function relationships change with changes in energy balance. Analysis of structure-function relationships in response to weight changes needs to address (a) the validity, precision, and different outcome parameters of body composition methods and (b) the variance of results taking into account study protocols and the dynamics of weight changes. As for future studies, repeated measurements of body weight, body composition, and metabolic functions are needed before, during, and after weight changes focusing on the intra- and interindividual variances of weight change rather than on mean data only.

DXA-derived estimates of energy balance and its relationship with changes in body composition across a season in team sport athletes

This study examined the relationship between dual-energy x-ray absorptiometry (DXA)-derived estimates of energy balance (EB) and changes in body composition across various seasonal phases in team sport athletes. Forty-five Australian rules footballers underwent six DXA scans across a 12-month period (off-season [OS, Week 0-13], early [PS1, Week 13-22] and late pre-season [PS2, Week 22-31] and early [IS1, Week 3-42] and late in-season [IS2, Week 42-51]). EB (kcal·day^-1) was estimated from changes in fat free soft tissue mass (FFSTM) and fat mass (FM) between scans according to a validated formula. An EB threshold of ± 123 kcal·day^-1 for >60 days demonstrated a very likely (>95% probability) change in FFSTM (>1.0 kg) and FM (>0.7 kg). There were small to almost perfect relationships between EB and changes in FM (r = 0.97, 95% CI, 0.96-0.98), FFSTM (r = -0.41, -0.92 to -0.52) and body mass (r = 0.27, 0.14-0.40). EB was lowest during PS1 compared to all other phases (range, -265 to -142 kcal·day^-1), with no other changes at any time. Increases in FFSTM were higher during OS compared to PS2 (1.6 ± 0.4 kg), and higher during PS1 compared to PS2, IS1, and IS2 (range, 1.6-2.1 kg). There were no changes during in-season (-0.1-0.05 kg). FM decreased only in PS1 compared to all other seasonal phases (-1.8 to -1.0 kg). Assessments of body composition can be used as a tool to estimate EB, which practically can be used to indicate athlete's training and nutrition behaviours/practices.

Methodologic considerations for measuring energy expenditure differences between diets varying in carbohydrate using the doubly labeled water method

BACKGROUND

Low-carbohydrate diets have been reported to significantly increase human energy expenditure when measured using doubly labeled water (DLW) but not by respiratory chambers. Although DLW may reveal true physiological differences undetected by respiratory chambers, an alternative possibility is that the expenditure differences resulted from failure to correctly estimate the respiratory quotient (RQ) used in the DLW calculations.

OBJECTIVE

To examine energy expenditure differences between isocaloric diets varying widely in carbohydrate and to quantitatively compare DLW data with respiratory chamber and body composition measurements within an energy balance framework.

DESIGN

DLW measurements were obtained during the final 2 wk of month-long baseline (BD; 50% carbohydrate, 35% fat, 15% protein) and isocaloric ketogenic diets (KD; 5% carbohydrate, 80% fat, 15% protein) in 17 men with a BMI of 25-35 kg/m2. Subjects resided 2 d/wk in respiratory chambers to measure energy expenditure (EEchamber). DLW expenditure was calculated using chamber-determined RQ either unadjusted (EEDLW) or adjusted (EEDLWΔRQ) for net energy imbalance using diet-specific coefficients. Accelerometers measured physical activity. Body composition changes were measured by dual-energy X-ray absorptiometry (DXA) which were combined with energy intake measurements to calculate energy expenditure by balance (EEbal).

RESULTS

After transitioning from BD to KD, neither EEchamber nor EEbal were significantly changed (∆EEchamber = 24 ± 30 kcal/d; P = 0.43 and ∆EEbal = -141 ± 118 kcal/d; P = 0.25). Similarly, physical activity (-5.1 ± 4.8%; P = 0.3) and exercise efficiency (-1.6 ± 2.4%; P = 0.52) were not significantly changed. However, EEDLW was 209 ± 83 kcal/d higher during the KD (P = 0.023) but was not significantly increased when adjusted for energy balance (EEDLWΔRQ = 139 ± 89 kcal/d; P = 0.14). After removing 2 outliers whose EEDLW were incompatible with other data, EEDLW was marginally increased during the KD by 126 ± 62 kcal/d (P = 0.063) and EEDLW∆RQ was only 46 ± 65 kcal/d higher (P = 0.49).

CONCLUSIONS

DLW calculations failing to account for diet-specific energy imbalance effects on RQ erroneously suggest that low-carbohydrate diets substantially increase energy expenditure. This trial was registered at clinicaltrials.gov as NCT01967563.

Modeling energy balance while correcting for measurement error via free knot splines

Measurements of energy balance components (energy intake, energy expenditure, changes in energy stores) are often plagued with measurement error. Doubly-labeled water can measure energy intake (EI) with negligible error, but is expensive and cumbersome. An alternative approach that is gaining popularity is to use the energy balance principle, by measuring energy expenditure (EE) and change in energy stores (ES) and then back-calculate EI. Gold standard methods for EE and ES exist and are known to give accurate measurements, albeit at a high cost. We propose a joint statistical model to assess the measurement error in cheaper, non-intrusive measures of EE and ES. We let the unknown true EE and ES for individuals be latent variables, and model them using a bivariate distribution. We try both a bivariate Normal as well as a Dirichlet Process Mixture Model, and compare the results via simulation. Our approach, is the first to account for the dependencies that exist in individuals' daily EE and ES. We employ semiparametric regression with free knot splines for measurements with error, and linear components for error free covariates. We adopt a Bayesian approach to estimation and inference and use Reversible Jump Markov Chain Monte Carlo to generate draws from the posterior distribution. Based on the semiparameteric regression, we develop a calibration equation that adjusts a cheaper, less reliable estimate, closer to the true value. Along with this calibrated value, our method also gives credible intervals to assess uncertainty. A simulation study shows our calibration helps produce a more accurate estimate. Our approach compares favorably in terms of prediction to other commonly used models.

Recent advances in understanding body weight homeostasis in humans

Presently, control of body weight is assumed to exist, but there is no consensus framework of body weight homeostasis. Three different models have been proposed, with a "set point" suggesting (i) a more or less tight and (ii) symmetric or asymmetric biological control of body weight resulting from feedback loops from peripheral organs and tissues (e.g. leptin secreted from adipose tissue) to a central control system within the hypothalamus. Alternatively, a "settling point" rather than a set point reflects metabolic adaptations to energy imbalance without any need for feedback control. Finally, the "dual intervention point" model combines both paradigms with two set points and a settling point between them. In humans, observational studies on large populations do not provide consistent evidence for a biological control of body weight, which, if it exists, may be overridden by the influences of the obesogenic environment and culture on personal behavior and experiences. To re-address the issue of body weight homeostasis, there is a need for targeted protocols based on sound concepts, e.g. lean rather than overweight subjects should be investigated before, during, and after weight loss and weight regain. In addition, improved methods and a multi-level-multi-systemic approach are needed to address the associations (i) between masses of individual body components and (ii) between masses and metabolic functions in the contexts of neurohumoral control and systemic effects. In the future, simplifications and the use of crude and non-biological phenotypes (i.e. body mass index and waist circumference) should be avoided. Since changes in body weight follow the mismatch between tightly controlled energy expenditure at loosely controlled energy intake, control (or even a set point) is more likely to be about energy expenditure rather than about body weight itself.

Energy Deficit Required for Rapid Weight Loss in Elite Collegiate Wrestlers

To determine energy density for rapid weight loss (RWL) of weight-classified sports, eight male elite wrestlers were instructed to lose 6% of body mass (BM) within 53 h. Energy deficit during the RWL was calculated by subtracting total energy expenditure (TEE) determined using the doubly labeled water method (DLW) from energy intake (EI) assessed with diet records. It was also estimated from body composition change estimated with the four-component model (4C) and other conventional methods. BM decreased significantly by 4.7 &plusmn; 0.5 kg (6.4 &plusmn; 0.5%). Total body water loss was the major component of the BM loss (71.0 &plusmn; 7.6%). TEE was 9446 &plusmn; 1422 kcal, and EI was 2366 &plusmn; 1184 kcal during the RWL of 53-h; therefore, the energy deficit was 7080 &plusmn; 1525 kcal. Thus, energy density was 1507 &plusmn; 279 kcal/kg ∆BM during the RWL, comparable with values obtained using the 4C, three-component model, dual energy X-ray absorptiometry, and stable isotope dilution. Energy density for RWL of wrestlers is lower than that commonly used (7400 or 7700 kcal/kg &Delta;BM). Although RWL is not recommended, we propose that commonly practiced extreme energy restriction such as 7400 or 7700 kcal/kg &Delta;BM during RWL appears to be meaningless.

Energy Intake Derived from an Energy Balance Equation, Validated Activity Monitors, and Dual X-Ray Absorptiometry Can Provide Acceptable Caloric Intake Data among Young Adults

BACKGROUND

Assessments of energy intake (EI) are frequently affected by measurement error. Recently, a simple equation was developed and validated to estimate EI on the basis of the energy balance equation [EI = changed body energy stores + energy expenditure (EE)].

OBJECTIVE

The purpose of this study was to compare multiple estimates of EI, including 2 calculated from the energy balance equation by using doubly labeled water (DLW) or activity monitors, in free-living adults.

METHODS

The body composition of participants (n = 195; mean age: 27.9 y; 46% women) was measured at the beginning and end of a 2-wk assessment period with the use of dual-energy X-ray absorptiometry. Resting metabolic rate (RMR) was calculated through indirect calorimetry. EE was assessed with the use of the DLW technique and an arm-based activity monitor [Sensewear Mini Armband (SWA); BodyMedia, Inc.]. Self-reported EI was calculated by using dietitian-administered 24-h dietary recalls. Two estimates of EI were calculated with the use of a validated equation: quantity of energy stores estimated from the changes in fat mass and fat-free mass occurring over the assessment period plus EE from either DLW or the SWA. To compare estimates of EI, reporting bias (estimated EI/EE from DLW × 100) and Goldberg ratios (estimated EI/RMR) were calculated.

RESULTS

Mean ± SD EEs from DLW and SWA were 2731 ± 494 and 2729 ± 559 kcal/d, respectively. Self-reported EI was 2113 ± 638 kcal/d, EI derived from DLW was 2723 ± 469 kcal/d, and EI derived from the SWA was 2720 ± 730 kcal/d. Reporting biases for self-reported EI, DLW-derived EI, and SWA-derived EI are as follows: -21.5% ± 22.2%, -0.7% ± 18.5%, and 0.2% ± 20.8%, respectively. Goldberg cutoffs for self-reported EI, DLW EI, and SWA EI are as follows: 1.39 ± 0.39, 1.77 ± 0.38, and 1.77 ± 0.38 kcal/d, respectively.

CONCLUSIONS

These results indicate that estimates of EI based on the energy balance equation can provide reasonable estimates of group mean EI in young adults. The findings suggest that, when EE derived from DLW is not feasible, an activity monitor that provides a valid estimate of EE can be substituted for EE from DLW.

Effects of alternate-day fasting or daily calorie restriction on body composition, fat distribution, and circulating adipokines: Secondary analysis of a randomized controlled trial

BACKGROUND & AIMS

Indirect comparisons suggest that alternate-day fasting (ADF) may produce greater improvements in body composition, fat distribution, and/or the adipokine profile compared to daily calorie restriction (CR), but this has not been tested directly. In a pre-planned secondary analysis of a randomized controlled trial, we compared changes in the VAT:SAT ratio, FFM:total mass ratio, and the adipokine profile between ADF and CR.

METHODS

Overweight and obese participants (n = 100) were randomized to 1) ADF (alternating every 24-h between consuming 25% or 125% of energy needs); 2) CR (consuming 75% of needs every day); or 3) control (consuming 100% of needs every day) for 24 wk.

RESULTS

The VAT:SAT ratio did not change in any group. The FFM:total mass ratio increased in both ADF (0.03 ± 0.00) and CR (0.03 ± 0.01) compared to the control group (P < 0.01), with no differences between the intervention groups. Circulating leptin decreased in both the ADF group (-18 ± 6%) and CR group (-31 ± 10%) relative to the control group (P < 0.05), with no differences between the intervention groups. Circulating levels of adiponectin, resistin, IL-6, and TNF-α did not change in either intervention group relative to the control group.

CONCLUSION

ADF and CR similarly improve the FFM:total mass ratio and reduce leptin after a 24-wk intervention.

TRIAL REGISTRATION

Clinicaltrials.gov, number NCT00960505.

Increased Physical Activity Associated with Less Weight Regain Six Years After "The Biggest Loser" Competition

OBJECTIVE

The aim of this study was to explore how physical activity (PA) and energy intake (EI) changes were related to weight loss and regain following "The Biggest Loser" competition.

METHODS

At baseline, week 6 and week 30 of the competition, and 6 years after the competition, body composition was measured via dual-energy x-ray absorptiometry, resting energy expenditure was measured by using indirect calorimetry, and EI and PA were measured by using doubly labeled water.

RESULTS

Six years after the competition, median weight loss in 14 of "The Biggest Loser" participants was 13%, with those maintaining a greater weight loss (mean ± SE) of 24.9% ± 3.8% having increased PA by 160% ± 23%, compared with a PA increase of 34% ± 25% (P = 0.0033) in the weight regainers who were 1.1% ± 4.0% heavier than the precompetition baseline. EI changes were similar between weight loss maintainers and regainers (-8.7% ± 5.6% vs. -7.4% ± 2.7%, respectively; P = 0.83). Weight regain was inversely associated with absolute changes in PA (r = -0.82; P = 0.0003) but not with changes in EI (r = -0.15; P = 0.61). EI and PA changes explained 93% of the individual weight loss variability at 6 years.

CONCLUSIONS

Consistent with previous reports, large and persistent increases in PA may be required for long-term maintenance of lost weight.

Energy Balance over One Athletic Season

INTRODUCTION

Magnitude and variation in energy balance (EB) components over an athletic season are largely unknown.

PURPOSE

We investigated the longitudinal changes in EB over one season and explored the association between EB variation and change in the main fat-free mass (FFM) components in highly trained athletes.

METHODS

Eighty athletes (54 males; handball, volleyball, basketball, triathlete, and swimming) were evaluated from the beginning of the season to the main competition stage. Resting and total energy expenditure (REE and TEE, respectively) were assessed by indirect calorimetry and doubly labeled water, respectively. Physical activity energy expenditure was calculated as TEE - 0.1 TEE - REE. Fat mass (FM), FFM, and bone mineral were evaluated with dual-energy x-ray absorptiometry; changed body energy stores were calculated as 1.0(ΔFFM/Δtime) + 9.5(ΔFM/Δtime). Total-body water (TBW) and its compartments were assessed through dilution techniques, and total-body protein was calculated from a four-compartment model, with body volume assessed by air displacement plethysmography.

RESULTS

Although a negative EB of -17.4 ± 72.7 kcal·d was observed (P < 0.05), EB varied widely among sports and across sex groups resulting in a net weight increase (0.7 ± 2.3 kg) that is attributable to significant changes in FFM (1.2 ± 1.6 kg) and FM (-0.7 ± 1.5 kg) (P < 0.05). EB was related with TBW and intracellular water (r = 0.354, r = 0.257, P < 0.05, respectively), regardless of sex, sports, and age.

CONCLUSIONS

The mean negative EB observed over the season resulted from the rate of FM use and FFM accretion, but with a large variation by sex and sports. TBW, but not total-body protein or mineral balance, explained the magnitude of EB, which means that athletes under a positive or a negative EB showed a TBW expansion or shrinkage, respectively, specifically within the cells, over one athletic season.

Randomized trial reveals that physical activity and energy expenditure are associated with weight and body composition after RYGB

OBJECTIVE

This study investigated the associations of both physical activity time (PA) and energy expenditure (EE) with weight and fat mass (FM) loss in patients following Roux-en-Y gastric bypass (RYGB) surgery.

METHODS

Ninety-six nondiabetic patients were included in this analysis. Post-RYGB patients were randomized in one of two treatments: A 6-month exercise training program (RYBG+EX) or lifestyle educational classes (RYGB). Body composition was assessed by dual-energy X-ray absorptiometry and computed tomography. Components of PA and EE were quantified by a multisensory device. Dose-response relationships of both PA and EE with weight loss and body composition were explored according to quartiles of change in steps per day.

RESULTS

Patients in the highest quartiles of steps per day change lost more FM (3rd = -19.5 kg and 4th = -22.7 kg, P < 0.05) and abdominal adipose tissue (4th = -313 cm² , P < 0.05), maintained skeletal muscle mass (3rd = -3.1 cm² and 4th = -4.5 cm² , P <  0.05), and had greater reductions in resting metabolic rate. Decreases in sedentary EE and increases in light EE and age were significant predictors of both Δweight and ΔFM (R²  = 73.8% and R²  = 70.6%, respectively).

CONCLUSIONS

Nondiabetic patients who perform higher, yet still modest, amounts of PA following RYGB have greater energy deficits and lose more weight and FM, while maintaining higher skeletal muscle mass.

Effect of Alternate-Day Fasting on Weight Loss, Weight Maintenance, and Cardioprotection Among Metabolically Healthy Obese Adults: A Randomized Clinical Trial

IMPORTANCE

Alternate-day fasting has become increasingly popular, yet, to date, no long-term randomized clinical trials have evaluated its efficacy.

OBJECTIVE

To compare the effects of alternate-day fasting vs daily calorie restriction on weight loss, weight maintenance, and risk indicators for cardiovascular disease.

DESIGN, SETTING, AND PARTICIPANTS

A single-center randomized clinical trial of obese adults (18 to 64 years of age; mean body mass index, 34) was conducted between October 1, 2011, and January 15, 2015, at an academic institution in Chicago, Illinois.

INTERVENTIONS

Participants were randomized to 1 of 3 groups for 1 year: alternate-day fasting (25% of energy needs on fast days; 125% of energy needs on alternating "feast days"), calorie restriction (75% of energy needs every day), or a no-intervention control. The trial involved a 6-month weight-loss phase followed by a 6-month weight-maintenance phase.

MAIN OUTCOMES AND MEASURES

The primary outcome was change in body weight. Secondary outcomes were adherence to the dietary intervention and risk indicators for cardiovascular disease.

RESULTS

Among the 100 participants (86 women and 14 men; mean [SD] age, 44 [11] years), the dropout rate was highest in the alternate-day fasting group (13 of 34 [38%]), vs the daily calorie restriction group (10 of 35 [29%]) and control group (8 of 31 [26%]). Mean weight loss was similar for participants in the alternate-day fasting group and those in the daily calorie restriction group at month 6 (-6.8% [95% CI, -9.1% to -4.5%] vs -6.8% [95% CI, -9.1% to -4.6%]) and month 12 (-6.0% [95% CI, -8.5% to -3.6%] vs -5.3% [95% CI, -7.6% to -3.0%]) relative to those in the control group. Participants in the alternate-day fasting group ate more than prescribed on fast days, and less than prescribed on feast days, while those in the daily calorie restriction group generally met their prescribed energy goals. There were no significant differences between the intervention groups in blood pressure, heart rate, triglycerides, fasting glucose, fasting insulin, insulin resistance, C-reactive protein, or homocysteine concentrations at month 6 or 12. Mean high-density lipoprotein cholesterol levels at month 6 significantly increased among the participants in the alternate-day fasting group (6.2 mg/dL [95% CI, 0.1-12.4 mg/dL]), but not at month 12 (1.0 mg/dL [95% CI, -5.9 to 7.8 mg/dL]), relative to those in the daily calorie restriction group. Mean low-density lipoprotein cholesterol levels were significantly elevated by month 12 among the participants in the alternate-day fasting group (11.5 mg/dL [95% CI, 1.9-21.1 mg/dL]) compared with those in the daily calorie restriction group.

CONCLUSIONS AND RELEVANCE

Alternate-day fasting did not produce superior adherence, weight loss, weight maintenance, or cardioprotection vs daily calorie restriction.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00960505.

Snap-N-Send: A valid and reliable method for assessing the energy intake of elite adolescent athletes

To ensure that elite adolescent athletes meet their unique training, growth and maturation demands, it is imperative to have access to valid measures of energy intake. Contemporary methods demand close attention-to-detail, meaning that athletes often do not fully adhere to real-time protocols. This study represents the first investigation of a real-time dietary assessment designed using a comprehensive behaviour change framework (COM-B). In a crossover design, 12 elite adolescent male rugby players recorded their energy intake via an estimated food diary (est-FD) and photography-based mobile assessment ('Snap-n-Send'), combined with a 24-h dietary recall interview. Two 4-day assessment periods were divided into three separate recording environments: 96 h free-living and researcher-observed; 72 h free-living and 10 h researcher-observed. Assessment periods were one month apart. All foods and beverages were provided and weighed by the research team to quantify actual intakes. 'Snap-n-Send' reported a small mean bias for under-reporting across 96 h (-0.75 MJ day^-1; 95% confidence interval [CI] for bias = -5.7% to -2.2%, p < .001), 72 h (-0.76 MJ day^-1; 95% CI for bias = -5.6% to -2.1%, p = .004) and 10 h (-0.72 MJ day^-1; 95% CI for bias = -8.1% to -0.1%; p = .067) environments. The est-FD reported a moderate mean bias for under-reporting across 96 h (-2.89 MJ day^-1; 95% CI for bias = -17.9% to -10.2%; p < .001), 72 h (-2.88 MJ day^-1; 95% CI for bias = -17.9% to -10.1%; p < .001) and 10 h (-2.52 MJ day^-1;-26.1% to -5.3%; p = .023) environments. Results evidence the ability of 'Snap-n-Send' to accurately assess the diet of elite adolescent athletes, signalling the exciting promise of this comprehensive and theoretical behavioural approach within valid dietary assessment.

Compensatory Changes in Energy Balance Regulation over One Athletic Season

PURPOSE

Mechanisms in energy balance (EB) regulation may include compensatory changes in energy intake (EI) and metabolic adaption (MA), but information is unavailable in athletes who often change EB components. We aim to investigate EB regulation compensatory mechanisms over one athletic season.

METHODS

Fifty-seven athletes (39 males/18 females; handball, volleyball, basketball, triathlon, and swimming) were evaluated from the beginning to the competitive phase of the season. Resting and total energy expenditure (REE and TEE, respectively) were assessed by indirect calorimetry and doubly labeled water, respectively, and physical activity energy expenditure was determined as TEE - 0.1(TEE) - REE. Fat mass (FM) and fat-free mass (FFM) were evaluated by dual-energy x-ray absorptiometry and changed body energy stores was determined by 1.0(ΔFFM/Δtime) + 9.5(ΔFM/Δtime). EI was derived as TEE + EB. REE was predicted from baseline FFM, FM, sex, and sports. %MA was calculated as 100(measured REE/predicted REE-1) and MA (kcal) as %MA/100 multiplied by baseline measured REE. Average EI minus average physical activity energy expenditure was computed as a proxy of average energy availability, assuming that a constant nonexercise EE occurred over the season.

RESULTS

Body mass increased by 0.8 ± 2.5 kg (P < 0.05), but a large individual variability was found ranging from -6.1 to 5.2 kg. The TEE raise (16.8% ± 11.7%) was compensated by an increase EI change (16.3% ± 12.0%) for the whole group (P < 0.05). MA was found in triathletes, sparing 128 ± 168 kcal·d, and basketball players, dissipating 168 ± 205 kcal·d (P < 0.05). MA was associated (P < 0.05) with EB and energy availability (r = 0.356 and r = 0.0644, respectively).

CONCLUSION

TEE increased over the season without relevant mean changes in weight, suggesting that EI compensation likely occurred. The thrifty or spendthrift phenotypes observed among sports and the demanding workloads these athletes are exposed to highlight the need for sport-specific energy requirements.

Reported Energy Intake Accuracy Compared to Doubly Labeled Water and Usability of the Mobile Food Record among Community Dwelling Adults

The mobile Food Record (mFR) is an image-based dietary assessment method for mobile devices. The study primary aim was to test the accuracy of the mFR by comparing reported energy intake (rEI) to total energy expenditure (TEE) using the doubly labeled water (DLW) method. Usability of the mFR was assessed by questionnaires before and after the study. Participants were 45 community dwelling men and women, 21-65 years. They were provided pack-out meals and snacks and encouraged to supplement with usual foods and beverages not provided. After being dosed with DLW, participants were instructed to record all eating occasions over a 7.5 days period using the mFR. Three trained analysts estimated rEI from the images sent to a secure server. rEI and TEE correlated significantly (Spearman correlation coefficient of 0.58, p < 0.0001). The mean percentage of underreporting below the lower 95% confidence interval of the ratio of rEI to TEE was 12% for men (standard deviation (SD) ± 11%) and 10% for women (SD ± 10%). The results demonstrate the accuracy of the mFR is comparable to traditional dietary records and other image-based methods. No systematic biases could be found. The mFR was received well by the participants and usability was rated as easy.

High energy expenditure is not protective against increased adiposity in children

BACKGROUND

Low levels of energy expenditure (TEE) may contribute to excess weight during childhood, but limited longitudinal data exist.

OBJECTIVES

This is to test whether low TEE during the first 6 years of life could predict excess weight status at 8 years.

METHODS

Total energy expenditure from doubly labelled water, weight, stature, waist circumference and fat mass and fat-free mass (FFM) in children at 0.25, 2, 4 and 6 years of age. This cohort includes individuals at high (n = 27) and low risk (n = 26) for childhood obesity, based upon whether pre-pregnant maternal obesity. A linear mixed effects model was fit to TEE. Individual variation was accounted for as a random effect. Residual TEE was calculated for age and individually averaged across time.

RESULTS

Fat-free mass (kg) was highly correlated (R²  = 0.91) with TEE (kcal/day), and waist circumference and sex were also significant predictors of TEE. TEE residual tracked within individuals. TEE residuals did not correlate with either BMI or %fat at age 8 years.

CONCLUSION

Using the residual TEE approach to identify high and low TEE during the first 6 years of life did not explain excess weight at 8 years of life in this cohort of children at high and low risk of obesity based upon maternal obesity status.

Nutrition Review: Dietary Considerations for Obesity Treatment

Dietary modification is critical in obesity treatment. Energy intake must fall below energy expenditure, but not so low that excess lean tissue is lost, hunger escalates, diet quality declines, and health is compromised. Reductions in energy consumption of 500 to 1000 kilocalories per day should result in appropriate rates of weight loss in most obese patients. Very low-calorie diets are sometimes used when excess body weight poses an acute risk, but such diets carry potential for many complications, and their long-term results are often no better than low-calorie diets. Macronutrient composition is not as important as overall energy defi cit in terms of weight loss, so dieters have some flexibility in choosing combinations that suit their preferences and needs, as long as they promote long-term healthy weight management. Diets with extremes of macronutrients are usually defi cient in micronutrients and are diffi cult to follow for long periods of time, so they should not be advocated. Resources for implementing dietary recommendations include registered dietitians, selected Web sites, and an assortment of products and services. Patients should be guided to resources that are evidence based and do not make unrealistic promises for weight loss. Prevention of recidivism should be built into the treatment plan.

Is breakfast the most important meal of the day?

The Bath Breakfast Project is a series of randomised controlled trials exploring the effects of extended morning fasting on energy balance and health. These trials were categorically not designed to answer whether or not breakfast is the most important meal of the day. However, this review will philosophise about the meaning of that question and about what questions we should be asking to better understand the effects of breakfast, before summarising how individual components of energy balance and health respond to breakfast v. fasting in lean and obese adults. Current evidence does not support a clear effect of regularly consuming or skipping breakfast on body mass/composition, metabolic rate or diet-induced thermogenesis. Findings regarding energy intake are variable, although the balance of evidence indicates some degree of compensatory feeding later in the day such that overall energy intake is either unaffected or slightly lower when breakfast is omitted from the diet. However, even if net energy intake is reduced, extended morning fasting may not result in expected weight loss due to compensatory adjustments in physical activity thermogenesis. Specifically, we report that both lean and obese adults expended less energy during the morning when remaining in the fasted state than when consuming a prescribed breakfast. Further research is required to examine whether particular health markers may be responsive to breakfast-induced responses of individual components of energy balance irrespective of their net effect on energy balance and therefore body mass.

Low levels of physical activity are associated with dysregulation of energy intake and fat mass gain over 1 year

BACKGROUND

Previous studies suggest that appetite may be dysregulated at low levels of activity, creating an energy imbalance that results in weight gain.

OBJECTIVE

The aim was to examine the relation between energy intake, physical activity, appetite, and weight gain during a 1-y follow-up period in a large sample of adults.

DESIGN

Participants included 421 individuals (mean ± SD age: 27.6 ± 3.8 y). Measurements included the following: energy intake with the use of interviewer-administered dietary recalls and calculated by using changes in body composition and energy expenditure, moderate-to-vigorous physical activity (MVPA) with the use of an arm-based monitor, body composition with the use of dual-energy X-ray absorptiometry, and questionnaire-derived perceptions of dietary restraint, disinhibition, hunger, and control of eating. Participants were grouped at baseline into quintiles of MVPA (min/d) by sex. Measurements were repeated every 3 mo for 1 y.

RESULTS

At baseline, an inverse relation existed between body weight and activity groups, with the least-active group (15.7 ± 9.9 min MVPA/d, 6062 ± 1778 steps/d) having the highest body weight (86.3 ± 13.2 kg) and the most-active group (174.5 ± 60.5 min MVPA/d, 10260 ± 3087 steps/d) having the lowest body weight (67.5 ± 11.0 kg). A positive relation was observed between calculated energy intake and activity group, except in the lowest quintile of activity. The lowest physical activity group reported higher levels of disinhibition (P = 0.07) and cravings for savory foods (P = 0.03) compared with the group with the highest level of physical activity. Over 1 y of follow-up, the lowest activity group gained the largest amount of fat mass (1.7 ± 0.3 kg) after adjustment for change in MVPA and baseline fat mass. The odds of gaining >3% of fat mass were between 1.8 and 3.8 times as high for individuals in the least-active group as for those in the middle activity group.

CONCLUSIONS

These results suggest that low levels of physical activity are a risk factor for fat mass gain. In the current sample, a threshold for achieving energy balance occurred at an activity level corresponding to 7116 steps/d, an amount achievable by most adults. This trial was registered at clinicaltrials.gov as NCT01746186.

Food consumption as affect modulation in borderline personality

The present study examined relationships among negative affect, borderline personality features, and eating behavior through the experimental manipulation of mood. Undergraduate women (N = 307) completed a baseline mood assessment, viewed a 39-minute sad film either with or without concurrent food presentation, then completed a second mood assessment and questionnaires assessing personality and eating attitudes/behaviors. Women reporting more borderline personality features exhibited greater negative affect across time and were more reactive to the sad film. Food presentation appeared to have a small ameliorative effect on sadness and general negative affect. However, quantity of food consumption was associated with improvements in mood only for women reporting higher levels of borderline personality features. These data suggest that women with borderline personality characteristics may be at elevated risk for developing problems with binge eating, because consuming larger quantities of food appeared to have a tempering effect on their negative mood and feelings of sadness.

An objective estimate of energy intake during weight gain using the intake-balance method

BACKGROUND

Estimates of energy intake (EI) in humans have limited validity.

OBJECTIVE

The objective was to test the accuracy and precision of the intake-balance method to estimate EI during weight gain induced by overfeeding.

DESIGN

In 2 studies of controlled overfeeding (1 inpatient study and 1 outpatient study), baseline energy requirements were determined by a doubly labeled water study and caloric titration to weight maintenance. Overfeeding was prescribed as 140% of baseline energy requirements for 56 d. Changes in weight, fat mass (FM), and fat-free mass (FFM) were used to estimate change in energy stores (ΔES). Overfeeding EI was estimated as the sum of baseline energy requirements, thermic effect of food, and ΔES. The estimated overfeeding EI was then compared with the actual EI consumed in the metabolic chamber during the last week of overfeeding.

RESULTS

In inpatient individuals, calculated EI during overfeeding determined from ΔES in FM and FFM was (mean ± SD) 3461 ± 848 kcal/d, which was not significantly (-29 ± 273 kcal/d or 0.8%; limits of agreement: -564, 505 kcal/d; P = 0.78) different from the actual EI provided (3490 ± 729 kcal/d). Estimated EI determined from ΔES in weight closely estimated actual intake (-7 ± 193 kcal/d or 0.2%; limits of agreement: -386, 370 kcal/d; P = 0.9). In free-living individuals, estimated EI during overfeeding determined from ΔES in FM and FFM was 4123 ± 500 kcal/d and underestimated actual EI (4286 ± 488 kcal/d; -162 ± 301 kcal or 3.8%; limits of agreement: -751, 427 kcal/d; P = 0.003). Estimated EI determined from ΔES in weight also underestimated actual intake (-159 ± 270 kcal/d or 3.7%; limits of agreement: -688, 370 kcal/d; P = 0.001).

CONCLUSION

The intake-balance method can be used to estimate EI during a period of weight gain as a result of 40% overfeeding in individuals who are inpatients or free-living with only a slight underestimate of actual EI by 0.2-3.8%.

Effect of dietary adherence on the body weight plateau: a mathematical model incorporating intermittent compliance with energy intake prescription

BACKGROUND

Clinical weight loss in individuals typically stabilizes at 6 mo. However, validated models of dynamic energy balance have consistently shown weight plateaus between 1 and 2 y. The cause for this discrepancy is unclear.

OBJECTIVE

We developed 2 mathematical models on the basis of the first law of thermodynamics to investigate plausible explanations for reaching an early weight plateau at 6 mo.

DESIGN

The first model was an energy-expenditure adaptation model and was applied to determine the degree of metabolic adaptation required to generate this plateau. The second model was an intermittent lack-of-adherence model formulated by using a randomly fluctuating energy intake term accounting for intermittent noncompliance in dietary intake to reach this plateau. To set model variables, validate models, and compare free-living weight-loss patterns to in-residence supervised programs, we applied the following 4 different studies: The US NHANES 1999-2004, Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) weight-loss study, the Bouchard Twin overfeeding study, and the Minnesota Starvation Experiment.

RESULTS

The metabolic adaptation model increased final weight but did not affect the predicted plateau time point. The intermittent lack-of-adherence model generated oscillating weight graphs that have been frequently observed in weight-loss studies. The model showed that a 6-mo weight-loss plateau can be attained despite what can be considered as high diet adherence. The model was programmed as a downloadable application.

CONCLUSIONS

An intermittent lack of diet adherence, not metabolic adaptation, is a major contributor to the frequently observed early weight-loss plateau. The new weight-loss prediction software, which incorporates an intermittent lack of adherence, can be used to guide and inform patients on realistic levels of adherence on the basis of patient lifestyle.

Assessment of physical activity and energy expenditure: an overview of objective measures

The ability to assess energy expenditure (EE) and estimate physical activity (PA) in free-living individuals is extremely important in the global context of non-communicable diseases including malnutrition, overnutrition (obesity), and diabetes. It is also important to appreciate that PA and EE are different constructs with PA defined as any bodily movement that results in EE and accordingly, energy is expended as a result of PA. However, total energy expenditure, best assessed using the criterion doubly labeled water (DLW) technique, includes components in addition to physical activity energy expenditure, namely resting energy expenditure and the thermic effect of food. Given the large number of assessment techniques currently used to estimate PA in humans, it is imperative to understand the relative merits of each. The goal of this review is to provide information on the utility and limitations of a range of objective measures of PA and their relationship with EE. The measures discussed include those based on EE or oxygen uptake including DLW, activity energy expenditure, physical activity level, and metabolic equivalent; those based on heart rate monitoring and motion sensors; and because of their widespread use, selected subjective measures.

Effect of physical activity on weight loss, energy expenditure, and energy intake during diet induced weight loss

OBJECTIVE

Objective measurements of physical activity (PA), energy expenditure (EE) and energy intake can provide valuable information regarding appropriate strategies for successful sustained weight loss.

DESIGN AND METHODS

The total EE was examined by doubly labeled water, resting metabolic rate by indirect calorimetry, PA with activity monitors, and energy intake by the intake/balance technique in 116 severely obese undergoing intervention with diet alone (DO) or diet plus PA (D-PA).

RESULTS

Weight loss of 9.6 ± 6.8 kg resulted in decreased EE which was not minimized in the D-PA group. Comparing the highest and lowest quartiles of increase in PA revealed a lower decrease in TDEE (-122 ± 319 vs. -376 ± 305 kcal day⁻¹), elimination of the drop in AEE (83 ± 279 vs. -211 ± 284 kcal day⁻¹) and greater weight loss (13.0 ± 7.0 vs. 8.1 ± 6.3 kg). Increased PA was associated with greater adherence to energy restriction and maintenance of greater weight loss during months 7-12.

CONCLUSION

Noncompliance to prescribed PA in the DO and D-PA groups partially masked the effects of PA to increase weight loss and to minimize the reduced EE. Increased PA was also associated with improved adherence to prescribed caloric restriction. A strong recommendation needs to be made to improve interventions that promote PA within the context of behavioral weight loss interventions.