Energy intake, physical activity and body weight: a simulation model

In adults, body mass (BM) and its components fat-free mass (FFM) and fat mass (FM) are normally regulated at a constant level. Changes in FM and FFM are dependent on energy intake (EI) and energy expenditure (EE). The body defends itself against an imbalance between EI and EE by adjusting, within limits, the one to the other. When, at a given EI or EE, energy balance cannot be reached, FM and FFM will change, eventually resulting in an energy balance at a new value. A model is described which simulates changes in FM and FFM using EI and physical activity (PA) as input variables. EI can be set at a chosen value or calculated from dietary intake with a database on the net energy of foods. PA can be set at a chosen multiple of basal metabolic rate (BMR) or calculated from the activity budget with a database on the energy cost of activities in multiples of BMR. BMR is calculated from FFM and FM and, if necessary, FFM is calculated from BM, height, sex and age, using empirical equations. The model uses existing knowledge on the adaptation of energy expenditure (EE) to an imbalance between EI and EE, and to resulting changes in FM and FFM. Mobilization and storage of energy as FM and FFM are functions of the relative size of the deficit (EI/EE) and of the body composition. The model was validated with three recent studies measuring EE at a fixed EI during an interval with energy restriction, overfeeding and exercise training respectively. Discrepancies between observed and simulated changes in energy stores were within the measurement precision of EI, EE and body composition. Thus the consequences of a change in dietary intake or a change in physical activity on body weight and body composition can be simulated.

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Energy Balance and Energy Availability During a Selection Course for Belgian Paratroopers

Military Medicine ◽

10.1093/milmed/usab140 ◽

2021 ◽

Author(s):

Patrick Mullie ◽

Pieter Maes ◽

Laurens van Veelen ◽

Damien Van Tiggelen ◽

Peter Clarys

Keyword(s):

Physical Activity ◽

Energy Balance ◽

Energy Expenditure ◽

Metabolic Rate ◽

Energy Intake ◽

Rest Metabolic Rate ◽

Negative Energy ◽

Fat Free Mass ◽

Negative Energy Balance ◽

Energy Availability

ABSTRACT Introduction Adequate energy supply is a prerequisite for optimal performances and recovery. The aims of the present study were to estimate energy balance and energy availability during a selection course for Belgian paratroopers. Methods Energy expenditure by physical activity was measured with accelerometer (ActiGraph GT3X+, ActiGraph LLC, Pensacola, FL, USA) and rest metabolic rate in Cal.d−1 with Tinsley et al.’s equation based on fat-free mass = 25.9 × fat-free mass in kg + 284. Participants had only access to the French individual combat rations of 3,600 Cal.d−1, and body fat mass was measured with quadripolar impedance (Omron BF508, Omron, Osaka, Japan). Energy availability was calculated by the formula: ([energy intake in foods and beverages] − [energy expenditure physical activity])/kg FFM−1.d−1, with FFM = fat-free mass. Results Mean (SD) age of the 35 participants was 25.1 (4.18) years, and mean (SD) percentage fat mass was 12.0% (3.82). Mean (SD) total energy expenditure, i.e., the sum of rest metabolic rate, dietary-induced thermogenesis, and physical activity, was 5,262 Cal.d−1 (621.2), with percentile 25 at 4,791 Cal.d−1 and percentile 75 at 5,647 Cal.d−1, a difference of 856 Cal.d−1. Mean daily energy intake was 3,600 Cal.d−1, giving a negative energy balance of 1,662 (621.2) Cal.d−1. Mean energy availability was 9.3 Cal.kg FFM−1.d−1. Eleven of the 35 participants performed with a negative energy balance of 2,000 Cal.d−1, and only five participants out of 35 participants performed at a less than 1,000 Cal.d−1 negative energy balance level. Conclusions Energy intake is not optimal as indicated by the negative energy balance and the low energy availability, which means that the participants to this selection course had to perform in suboptimal conditions.

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

Nutrients ◽

10.3390/nu13103394 ◽

2021 ◽

Vol 13 (10) ◽

pp. 3394

Author(s):

Sarah A. Purcell ◽

Ryan J. Marker ◽

Marc-Andre Cornier ◽

Edward L. Melanson

Keyword(s):

Breast Cancer ◽

Physical Activity ◽

Energy Balance ◽

Energy Expenditure ◽

Dietary Intake ◽

Metabolic Rate ◽

Cancer Survivors ◽

Breast Cancer Survivors ◽

Resting Metabolic Rate ◽

Fat Free Mass

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.

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Abstract P022: Determinants of Energy Balance: Differences Related to Body Weight and Body Composition

Circulation ◽

10.1161/circ.127.suppl_12.ap022 ◽

2013 ◽

Vol 127 (suppl_12) ◽

Author(s):

Gregory A Hand ◽

Robin P Shook ◽

Jason R Jaggers ◽

Amanda Paluch ◽

Vivek K Prasad ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Energy Balance ◽

Energy Expenditure ◽

Energy Intake ◽

Positive Association ◽

Linear Modeling ◽

Obesity Epidemic ◽

And Storage ◽

Lean Group

Conversion, utilization and storage of energy in the regulation of energy balance is poorly understood. These misconceptions arise from confusion related to energy balance and its impact on body weight and composition, and can bias the interpretation of findings that are important for the development of policies addressing the obesity epidemic. PURPOSE: Our purpose was to examine the regulation of interactions between total daily energy intake (TDEI) and energy expenditure (TDEE) in healthy adults. METHODS: Adults not limited by gender, race or ethnicity (n=430; aged 21 to 40; BMI of 20 to 35) participated in a battery of physiological, anthropomorphic, behavioral and psychological measurements that are associated with energy balance regulation. The primary components of energy balance regulation (TDEI and TDEE) were measured by 3 random 24-hour dietary recalls and SenseWear accelerometry, respectively. Body composition was determined by dual x-ray absorptiometry (DXA). Absolute and relative resting metabolic rates (aRMR and rRMR) were determined through hooded indirect calorimetry. General linear modeling was used to examine the relationships of weight and body fatness with TDEI and macronutrient composition as well as the largest components of TDEE including aRMR, rRMR and physical activity energy expenditure (PAEE). In addition, data were compared between participants with a healthy body fat % (below 25; n=123) and obese (at or above 30%; n=241). RESULTS: All results were adjusted for age, gender and race. TDEE was positively associated (r=.47, p<.001) with TDEI. There was a positive association between aRMR (L/min) and weight (r=.743, p<.001). By contrast, rRMR (ml/kg/min) was inversely correlated with body weight (r= -.38; p<.001). TDEI was significantly higher in the lean group (2465±66 to 1878±42, p<.001) with no measureable differences in macronutrient percentages. The lean group had a higher TDEE and PAEE as compared to the obese group. CONCLUSIONS: There was a robust matching of TDEI and TDEE across weight and body composition ranges. Heavy people burned more calories than lighter people although the lighter individuals had a higher rRMR. The leaner group had a higher TDEI, reflecting a potential regulation based on the greater TDEE in this group. Further, the increased TDEE could be explained by the higher PAEE (approximately 500 kcal) in leaner individuals. These findings emphasize that energy expenditure is related to mass rather than body composition. The regulation of energy intake and body composition is multifactorial, with PAEE a significant determinant for energy storage. This study was funded through an unrestricted grant from The Coca-Cola Company.

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Body composition and dietary intake in patients with head and neck cancer during radiotherapy: a longitudinal study

BMJ Supportive & Palliative Care ◽

10.1136/bmjspcare-2020-002359 ◽

2020 ◽

pp. bmjspcare-2020-002359

Author(s):

Bing Zhuang ◽

Lichuan Zhang ◽

Yujie Wang ◽

Yiwei Cao ◽

Yian Shih ◽

...

Keyword(s):

Body Composition ◽

Head And Neck Cancer ◽

Dietary Intake ◽

Head And Neck ◽

Energy Intake ◽

Neck Cancer ◽

High Energy ◽

The Body ◽

Fat Free Mass ◽

Prospective Longitudinal

ObjectivesTo investigate the body composition and dietary intake in the patients with head and neck cancer (HNC) during radiotherapy (RT), and explore the relationship between them.MethodsThis was a prospective, longitudinal observational study. Adult patients with HNC undergoing RT between March 2017 and August 2018 were recruited. Patients’ body compositions were evaluated by bioelectrical impedance analysis, and dietary intake was recorded by 24-hour dietary recall at three time points, including baseline (T1), mid-treatment (T2) and post-treatment (T3). Patients were divided into low, middle and high energy intake groups based on the average daily energy intake (DEI). Changes in body weight (BW), fat mass (FM), fat-free mass (FFM) and skeletal muscle mass (SMM) among these three groups were compared.ResultsFrom T1 to T3, the median loss of patients’ BW, FM, FFM and SMM was 4.60, 1.90, 2.60 and 1.50 kg, respectively. The loss of BW was more dramatic from T2 to T3 than that from T1 to T2. BW loss was mainly contributed by SMM loss from T1 to T2 and by FM loss from T2 to T3. Meanwhile, patients’ dietary intake reduced during treatment. High DEI group had a significantly attenuated loss of patients’ BW, FFM, SMM and FM compared with the low DEI group.ConclusionPatients’ BW, FM, FFM and SMM all significantly reduced, especially from T2 to T3, with decreased DEI during RT, which stresses the importance of nutrition intervention during the whole course of RT.

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Techniques for the study of energy balance in man

Proceedings of The Nutrition Society ◽

10.1079/pns2003255 ◽

2003 ◽

Vol 62 (2) ◽

pp. 529-537 ◽

Cited By ~ 34

Author(s):

Marinos Elia ◽

Rebecca Stratton ◽

James Stubbs

Keyword(s):

Body Composition ◽

Measurement Error ◽

Energy Balance ◽

Energy Intake ◽

Dual Energy ◽

The Body ◽

Fat Free Mass ◽

Whole Body ◽

X Ray ◽

Body Segments

Energy balance can be estimated in tissues, body segments, individual subjects (the focus of the present article), groups of subjects and even societies. Changes in body composition in individual subjects can be translated into changes in the energy content of the body, but this method is limited by the precision of the techniques. The precision for measuring fat and fat-free mass can be as low as 0.5 kg when certain reference techniques are used (hydrodensitometry, air-displacement plethysmography, dual-energy X-ray absorptiometry), and approximately 0.7 kg for changes between two time points. Techniques associated with a measurement error of 0.7 kg for changes in fat and fat-free mass (approximately 18MJ) are of little or no value for calculating energy balance over short periods of time, but they may be of some value over long periods of time (18 MJ over 1 year corresponds to an average daily energy balance of 70 kJ, which is <1% of the normal dietary energy intake). Body composition measurements can also be useful in calculating changes in energy balance when the changes in body weight and composition are large, e.g. >5–10 kg. The same principles can be applied to the assessment of energy balance in body segments using dual-energy X-ray absorptiometry. Energy balance can be obtained over periods as short as a few minutes, e.g. during measurements of BMR. The variability in BMR between individuals of similar age, weight and height and gender is about 7–9%, most of which is of biological origin rather than measurement error, which is about 2%. Measurement of total energy expenditure during starvation (no energy intake) can also be used to estimate energy balance in a whole-body calorimeter, in patients in intensive care units being artificially ventilated and by tracer techniques. The precision of these techniques varies from 1 to 10%. Establishing energy balance by measuring the discrepancy between energy intake and expenditure has to take into consideration the combined validity and reliability of both components. The measurement error for dietary intake may be as low as 2–3% in carefully controlled environments, in which subjects are provided only with certain food items and bomb calorimetry can be undertaken on duplicate samples of the diet. Reliable results can also be obtained in hospitalised patients receiving enteral tube feeding or parenteral nutrition as the only source of nutrition. Unreliability increases to an unknown extent in free-living subjects eating a mixed and varied diet; thus, improved methodology is needed for the study of energy balance.

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INFLUENCE OF ENERGY INTAKE ON DEVELOPMENT OF BROILER BREEDER PULLETS

Canadian Journal of Animal Science ◽

10.4141/cjas90-031 ◽

1990 ◽

Vol 70 (1) ◽

pp. 259-266 ◽

Cited By ~ 4

Author(s):

C. D. BENNETT ◽

S. LEESON

Keyword(s):

Body Composition ◽

Body Weight ◽

Luteinizing Hormone ◽

Energy Intake ◽

High Energy ◽

The Body ◽

Fat Free Mass ◽

Lower Percentage ◽

Broiler Breeder ◽

Hormone Levels

One hundred and two broiler breeder pullets were reared from 10 wk of age on one of three diets formulated to contain 15% CP and provide 10.67, 11.72, or 12.89 MJ ME kg−1. All birds received the same daily feed allotment. At 20 wk of age, the pullets were light-stimulated and nine birds per treatment were slaughtered for carcass analysis. The remaining birds were slaughtered for carcass analysis at the time that they laid their first egg. Twelve birds from each treatment were blood sampled from 10–25.5 wk of age and plasma luteinizing hormone levels determined. While all birds had similar ages at first egg, birds given the high energy diet grew faster and had more fat, protein and fat-free mass in the body at first egg relative to birds consuming the least amount of energy. Birds fed the high energy diet also displayed a higher percentage of fat and lower percentage of protein at first egg than did the birds fed the low energy diet. Coefficients of variation for weight of protein and fat-free mass at first egg were 9.1 and 7.9%, respectively, compared to 24.4% for grams of fat at first egg; protein and fat-free masses appeared to be relatively constant at first egg. Linear regressions suggested a strong relationship between body composition and body weight both at 20 wk of age and first egg. Plasma luteinizing hormone levels were unaffected by diet. Key words: Broiler breeder, body composition, body weight, sexual maturity, energy intake

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Novel Equations to Estimate Resting Energy Expenditure during Sitting and Sleeping

Annals of Nutrition and Metabolism ◽

10.1159/000516174 ◽

2021 ◽

pp. 1-9

Author(s):

Akiko Uchizawa ◽

Masanobu Hibi ◽

Hiroyuki Sagayama ◽

Simeng Zhang ◽

Haruka Osumi ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Individual Characteristics ◽

The Body ◽

Fat Free Mass ◽

Middle Aged ◽

Metabolic Chamber ◽

Resting Energy

Introduction: Young and early middle-aged office workers spend most of the day sitting or sleeping. Few studies have used a metabolic chamber to report sitting resting energy expenditure (REE) or sleeping metabolic rate (SMR) estimation equations. This study aimed to develop novel equations for estimating sitting REE and SMR, and previously published equations for SMR were compared against measured values. Methods: The relationships among sitting REE, SMR, and body composition measured in clinical trials were analyzed. The body composition (fat-free mass [FFM] and fat mass) and energy metabolism of 85 healthy young and early middle-aged Japanese individuals were measured using dual-energy X-ray absorptiometry and a metabolic chamber, respectively. Novel estimate equations were developed using stepwise multiple regression analysis. Estimates of SMR using a new equation and 2 published equations were compared against measured SMR. Results: The sitting mREE and mSMR were highly correlated (r = 0.756, p < 0.01). The new FFM-based estimate accounted for 50.4% of the variance in measured sitting REE (mREE) and 82.3% of the variance in measured SMR (mSMR). The new body weight-based estimate accounted for 49.3% of the variance in sitting mREE and 82.2% of the variance in mSMR. Compared with mSMR, the SMR estimate using an FFM-based published equation was slightly underestimated. Conclusion: These novel body weight- and FFM-based equations may help estimate sitting REE and SMR in young and early middle-aged adults. Previous SMR estimated FFM-based equations were slightly underestimated against measured SMR; however, we confirmed the previous SMR estimate equations could be useful. This finding suggests that sitting REE and SMR can be easily estimated from individual characteristics and applied in clinical settings.

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Total energy expenditure in patients with colorectal cancer: associations with body composition, physical activity, and energy recommendations

American Journal of Clinical Nutrition ◽

10.1093/ajcn/nqz112 ◽

2019 ◽

Vol 110 (2) ◽

pp. 367-376 ◽

Cited By ~ 6

Author(s):

Sarah A Purcell ◽

Sarah A Elliott ◽

Peter J Walter ◽

Tom Preston ◽

Hongyi Cai ◽

...

Keyword(s):

Physical Activity ◽

Colorectal Cancer ◽

Body Composition ◽

Body Weight ◽

Energy Expenditure ◽

Total Energy ◽

Residual Activity ◽

Total Energy Expenditure ◽

Activity Level ◽

Fat Free Mass

ABSTRACT Background Total energy expenditure (TEE) data in patients with early-stage cancer are scarce, precluding an understanding of energy requirements. Objective The objective was to cross-sectionally characterize TEE in patients with colorectal cancer (CRC) and to compare measured TEE with energy recommendations. It was hypothesized that TEE would differ according to body mass, body composition, and physical activity level (PAL) and current energy recommendations would have poor individual-level accuracy. Methods Patients with newly diagnosed CRC had resting energy expenditure (REE) measured by indirect calorimetry and TEE by doubly labeled water. Hypermetabolism was defined as REE > 110% of that predicted from the Mifflin St.-Jeor equation. Body composition was assessed via DXA. Physical activity was determined as the ratio of TEE to REE (TEE:REE) (PAL) and residual activity energy expenditure (RAEE). TEE was compared with energy recommendations of 25–30 kcal/d and Dietary Reference Intakes (DRIs) using Bland–Altman analyses. Patients were stratified according to median BMI, PAL, and sex-specific ratio of fat mass (FM) to fat-free mass (FFM). Results Twenty-one patients (M:F 14:7; mean ± SD BMI: 28.3 ± 4.9 kg/m2, age: 57 ± 12 y) were included. Most (n = 20) had stage II–III disease; 1 had stage IV. Approximately half (n = 11) were hypermetabolic; TEE was not different in those with hypermetabolism and REE as a percentage of predicted was not correlated with TEE. Mean ± SD TEE was 2473 ± 499 kcal/d (range: 1562–3622 kcal/d), or 29.7 ± 6.3 kcal/kg body weight (range: 20.4–48.5 kcal/kg body weight). Mean ± SD PAL was 1.43 ± 0.27. The energy recommendation of 25 kcal/kg underestimated TEE (−12.6% ± 16.5%, P = 0.002); all energy recommendations had wide limits of agreement (the smallest was DRI with measured PAL: −21.2% to 29.3%). Patients with higher BMI and FM:FFM had higher bias using kilocalories per kilogram recommendations; bias from several recommendations was frequently lower (i.e. underestimation) in patients with higher PAL and RAEE. Conclusions TEE variability was not reflected in energy recommendations and error was related to body weight, body composition, and physical activity. This trial was registered at clinicaltrials.gov as NCT03131921.

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Short-term, mixed-diet overfeeding in man: no evidence for "luxuskonsumption"

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.1985.249.5.e470 ◽

1985 ◽

Vol 249 (5) ◽

pp. E470-E477 ◽

Cited By ~ 11

Author(s):

E. Ravussin ◽

Y. Schutz ◽

K. J. Acheson ◽

M. Dusmet ◽

L. Bourquin ◽

...

Keyword(s):

Physical Activity ◽

Body Composition ◽

Body Weight ◽

Energy Intake ◽

Body Weight Gain ◽

Weight Maintenance ◽

Excess Energy ◽

The Body ◽

Experimental Conditions ◽

Maintenance Requirements

After 13 days of weight maintenance diet (13,720 +/- 620 kJ/day, 40% fat, 15% protein, and 45% carbohydrate), five young men (71.3 +/- 7.1 kg, 181 +/- 8 cm; means +/- SD) were overfed for 9 days at 1.6 times their maintenance requirements (i.e., +8,010 kJ/day). Twenty-four-hour energy expenditure (24-h EE) and basal metabolic rate (BMR) were measured on three occasions, once after 10 days on the weight-maintenance diet and after 2 and 9 days of overfeeding. Physical activity was monitored throughout the study, body composition was measured by underwater weighing, and nitrogen balance was assessed for 3 days during the two experimental periods. Overfeeding caused an increase in body weight averaging 3.2 kg of which 56% was fat as measured by underwater weighing. After 9 days of overfeeding, BMR increased by 622 kJ/day, which could explain one-third of the increase in 24-h EE (2,038 kJ/day); the remainder was due to the thermic effect of food (which increased in proportion with excess energy intake) and the increased cost of physical activity, related to body weight gain. This study shows that approximately one-quarter of the excess energy intake was dissipated through an increase in EE, with 75% being stored in the body. Under our experimental conditions of mixed overfeeding in which body composition measurements were combined with those of energy balance, it was possible to account for all of the energy ingested in excess of maintenance requirements.

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Body Composition Modifications Due to the “Search, Rescue and Survival Training” in Male Military Firefighter Cadets

Military Medicine ◽

10.1093/milmed/usaa571 ◽

2021 ◽

Author(s):

Thiago Ramos de Barros ◽

Verônica Pinto Salerno ◽

Thalita Ponce ◽

Míriam Raquel Meira Mainenti

Keyword(s):

Body Composition ◽

Body Weight ◽

Repeated Measures ◽

Food Restriction ◽

Physical Exertion ◽

High Energy ◽

The Body ◽

Fat Free Mass ◽

Sleep Restriction ◽

Fat Percentage

ABSTRACT Introduction To train and prepare cadets for a career as firefighters in Rio de Janeiro, the second-year students of the Officers Training Course are submitted to a Search, Rescue, and Survival Training (SRST) course, which is characterized by long periods of high physical exertion and sleep restriction during a 9-day instruction module, and food restriction during a 7-day survival module. The present study investigated changes in the body composition of 39 male cadets submitted to SRST during training and 4 weeks of recovery with no restrictions in food consumption. Materials and Methods Each cadet was evaluated by anthropometric measurements at six time points: pre-SRST; after the first module; after the second module; and after 1, 2, and 4 weeks of recovery. Measurements included body girths and skinfolds, to estimate trunk (chest and waist) and limbs (arm and thigh) dimensions, as well as body composition. Repeated measures ANOVA and Friedman test were applied (depending on each data distribution). Results Statistically significant decreases in body weight (76.2; 69.8-87.2 to 63.9; 58.9-73.5 kg) and fat free mass (FFM, 69.2; 63.7-77.2 to 60.1; 56.2-68.0 kg) were observed following the second module of SRST. Following a single week of recovery, the FFM returned to pre-SRST values. Body weight returned to pre-training levels in 2 weeks. Body fat percentage and mass also significantly decreased during SRST (9.0; 7.7-12.3 to 6.5; 5.1-9.3% and 6.9; 5.6-10.0 to 6.9; 5.6-10.0 kg, respectively), which showed a slower and more gradual recovery that reached pre-SRST values after 4 weeks. The girths of arm, thigh, chest and waist significantly decreased due to SRST. The girths of the limbs (arm and thigh) returned to pre-training values after one month of recovery, while the girths of the trunk (chest and waist) did not return to pre-SRST values during the study period. Conclusions The findings suggest that men who experience periods of high energy demands and sleep restriction followed by a period of food restriction will endure unavoidable physical consequences that can be mostly reversed by a 1-month recovery.

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