INFLUENCE OF ENERGY INTAKE ON DEVELOPMENT OF BROILER BREEDER PULLETS

1990 ◽  
Vol 70 (1) ◽  
pp. 259-266 ◽  
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

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

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.

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

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.

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

1995 ◽  
Vol 73 (3) ◽  
pp. 337-347 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Jeroen H. H. L. M. Donkers ◽  
Elisabeth W. H. M. Fredrix ◽  
Piet oekhoudt
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Body Weight ◽  
Energy Balance ◽  
Energy Expenditure ◽  
Dietary Intake ◽  
Energy Intake ◽  
Relative Size ◽  
The Body ◽  
Fat Free Mass

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.

scholarly journals Body composition and energy intake — skeletal muscle mass is the strongest predictor of food intake in obese adolescents: The HEARTY trial

2016 ◽  
Vol 41 (6) ◽  
pp. 611-617 ◽  
Author(s):  
Jameason D. Cameron ◽  
Ronald J. Sigal ◽  
Glen P. Kenny ◽  
Angela S. Alberga ◽  
Denis Prud’homme ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Composition ◽  
Body Weight ◽  
Muscle Mass ◽  
Energy Intake ◽  
Skeletal Muscle Mass ◽  
Fat Free Mass ◽  
Cross Sectional ◽  
Percentage Body Fat ◽  
Obese Adolescents

There has been renewed interest in examining the relationship between specific components of energy expenditure and the overall influence on energy intake (EI). The purpose of this cross-sectional analysis was to determine the strongest metabolic and anthropometric predictors of EI. It was hypothesized that resting metabolic rate (RMR) and skeletal muscle mass would be the strongest predictors of EI in a sample of overweight and obese adolescents. 304 post-pubertal adolescents (91 boys, 213 girls) aged 16.1 (±1.4) years with body mass index at or above the 95th percentile for age and sex OR at or above the 85th percentile plus an additional diabetes risk factor were measured for body weight, RMR (kcal/day) by indirect calorimetry, body composition by magnetic resonance imaging (fat free mass (FFM), skeletal muscle mass, fat mass (FM), and percentage body fat), and EI (kcal/day) using 3 day food records. Body weight, RMR, FFM, skeletal muscle mass, and FM were all significantly correlated with EI (p < 0.005). After adjusting the model for age, sex, height, and physical activity, only FFM (β = 21.9, p = 0.007) and skeletal muscle mass (β = 25.8, p = 0.02) remained as significant predictors of EI. FFM and skeletal muscle mass also predicted dietary protein and fat intake (p < 0.05), but not carbohydrate intake. In conclusion, with skeletal muscle mass being the best predictor of EI, our results support the hypothesis that the magnitude of the body’s lean tissue is related to absolute levels of EI in a sample of inactive adolescents with obesity.

scholarly journals Body composition and appetite: fat-free mass (but not fat mass or BMI) is positively associated with self-determined meal size and daily energy intake in humans

2011 ◽  
Vol 107 (3) ◽  
pp. 445-449 ◽  
Author(s):  
John E. Blundell ◽  
Phillipa Caudwell ◽  
Catherine Gibbons ◽  
Mark Hopkins ◽  
Erik Näslund ◽  
...  
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Food Intake ◽  
Energy Intake ◽  
Fat Mass ◽  
Meal Size ◽  
Fat Free Mass ◽  
Daily Energy Intake ◽  
Molecular Control ◽  
Daily Energy

The idea of body weight regulation implies that a biological mechanism exerts control over energy expenditure and food intake. This is a central tenet of energy homeostasis. However, the source and identity of the controlling mechanism have not been identified, although it is often presumed to be some long-acting signal related to body fat, such as leptin. Using a comprehensive experimental platform, we have investigated the relationship between biological and behavioural variables in two separate studies over a 12-week intervention period in obese adults (totaln92). All variables have been measured objectively and with a similar degree of scientific control and precision, including anthropometric factors, body composition, RMR and accumulative energy consumed at individual meals across the whole day. Results showed that meal size and daily energy intake (EI) were significantly correlated with fat-free mass (FFM,Pvalues < 0·02–0·05) but not with fat mass (FM) or BMI (Pvalues 0·11–0·45) (study 1,n58). In study 2 (n34), FFM (but not FM or BMI) predicted meal size and daily EI under two distinct dietary conditions (high-fat and low-fat). These data appear to indicate that, under these circumstances, some signal associated with lean mass (but not FM) exerts a determining effect over self-selected food consumption. This signal may be postulated to interact with a separate class of signals generated by FM. This finding may have implications for investigations of the molecular control of food intake and body weight and for the management of obesity.

scholarly journals Does regular walnut consumption lead to weight gain?

2005 ◽  
Vol 94 (5) ◽  
pp. 859-864 ◽  
Author(s):  
Joan Sabaté ◽  
Zaida Cordero-MacIntyre ◽  
Gina Siapco ◽  
Setareh Torabian ◽  
Ella Haddad
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Weight Gain ◽  
Energy Intake ◽  
Control Diet ◽  
High Energy ◽  
Daily Consumption ◽  
Dietary Compliance ◽  
Beneficial Effects ◽  
Diet Control

Studies consistently show the beneficial effects of eating nuts, but as high-energy foods, their regular consumption may lead to weight gain. We tested if daily consumption of walnuts (approximately 12% energy intake) for 6 months would modify body weight and body composition in free-living subjects. Ninety participants in a 12-month randomized cross-over trial were instructed to eat an allotted amount of walnuts (28–56g) during the walnut-supplemented diet and not to eat them during the control diet, with no further instruction. Subjects were unaware that body weight was the main outcome. Dietary compliance was about 95% and mean daily walnut consumption was 35g during the walnut-supplemented diet. The walnut-supplemented diet resulted in greater daily energy intake (557kJ (133kcal)), which should theoretically have led to a weight gain of 3·1kg over the 6-month period. For all participants, walnut supplementation increased weight (0·4 (se 0·1) kg), BMI (0·2 (se 0·1) kg/m2), fat mass (0·2 (se 0·1) kg) and lean mass (0·2 (se 0·1) kg). But, after adjusting for energy differences between the control and walnut-supplemented diets, no significant differences were observed in body weight or body composition parameters, except for BMI (0·1 (se 0·1) kg/m2). The weight gain from incorporating walnuts into the diet (control→walnut sequence) was less than the weight loss from withdrawing walnuts from the diet (walnut→control sequence). Our findings show that regular walnut intake resulted in weight gain much lower than expected and which became non-significant after controlling for differences in energy intake.

scholarly journals Techniques for the study of energy balance in man

2003 ◽  
Vol 62 (2) ◽  
pp. 529-537 ◽  
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.

scholarly journals Stav antropometrických parametrov a telesného zloženia u detí mladšieho školského veku

2017 ◽  
Vol 11 (2) ◽  
pp. 15-27
Author(s):  
Tomáš Hadžega ◽  
Václav Bunc
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Body Fat ◽  
Body Height ◽  
The Body ◽  
Fat Free Mass ◽  
Whole Body ◽  
School Age ◽  
Total Body ◽  
Frequency Apparatus

The aim of our observation was to measure selected anthropometric characteristics and to analyze actual body composition in children of younger school age from elementary schools in Prague. The group consisted of a total of 222 probands, boys (n-117) and girls (n-105) aged 8–11 years (average boys age = 9.0 ± 1.0 years, body height = 139.9 ± 8.6 cm, body weight = 32 ± 7.5 kg, BMI = 16.3 ± 2.4 kg.m–2). Average age girls = 8.9 ± 0.9 years, body height = 137.3 ± 8.8 cm, body weight = 30.5 ± 7.3 kg, BMI = 15.9 ± 2.4 kg.m–2). The BIA 2000 M multi-frequency apparatus (whole-body bioimpedance analysis) was used to analyze the body composition. Children of younger school age showed higher TBW values – total body water (boys 65.5 ± 6.0%, girls 66.6 ± 6.5%), low body fat (boys 16.1 ± 2.4%, girls 16.5 ± 2.9%) and higher ECM/BCM coefficients (boys 1.0 ± 0.13, girls 1.02 ± 0.11). The authors draws, attention to the importance of monitoring other body composition parameters. The percentage of fat-free mass (FFM) and the share of segmental distribution of body fat and muscle mass on individual parts of the human body.

Effects of dietary protein content on IGF-I, testosterone, and body composition during 8 days of severe energy deficit and arduous physical activity

2008 ◽  
Vol 105 (1) ◽  
pp. 58-64 ◽  
Author(s):  
Joseph A. Alemany ◽  
Bradley C. Nindl ◽  
Mark D. Kellogg ◽  
William J. Tharion ◽  
Andrew J. Young ◽  
...  
Keyword(s):  
Body Composition ◽  
Energy Expenditure ◽  
Protein Content ◽  
Energy Intake ◽  
Dietary Protein ◽  
High Energy ◽  
Low Energy ◽  
Fat Free Mass ◽  
Energy Deficit ◽  
Igf I

Energy restriction coupled with high energy expenditure from arduous work is associated with an altered insulin-like growth factor-I (IGF-I) system and androgens that are coincident with losses of fat-free mass. The aim of this study was to determine the effects of two levels of dietary protein content and its effects on IGF-I, androgens, and losses of fat-free mass accompanying energy deficit. We hypothesized that higher dietary protein content would attenuate the decline of anabolic hormones and, thus, prevent losses of fat-free mass. Thirty-four men [24 (SD 0.3) yr, 180.1 (SD 1.1) cm, and 83.0 (SD 1.4) kg] participated in an 8-day military exercise characterized by high energy expenditure (16.5 MJ/day), low energy intake (6.5 MJ/day), and sleep deprivation (4 h/24 h) and were randomly divided into two dietary groups: 0.9 and 0.5 g/kg dietary protein intake. IGF-I system analytes, androgens, and body composition were assessed before and on days 4 and 8 of the intervention. Total, free, and nonternary IGF-I and testosterone declined 50%, 64%, 55%, and 45%, respectively, with similar reductions in both groups. There was, however, a diet × time interaction on day 8 for total IGF-I and sex hormone-binding globulin. Decreases in body mass (3.2 kg), fat-free mass (1.2 kg), fat mass (2.0 kg), and percent body fat (1.5%) were similar in both groups ( P = 0.01). Dietary protein content of 0.5 and 0.9 g/kg minimally attenuated the decline of IGF-I, the androgenic system, and fat-free mass during 8 days of negative energy balance associated with high energy expenditure and low energy intake.

Novel Equations to Estimate Resting Energy Expenditure during Sitting and Sleeping

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

<b><i>Introduction:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> The sitting mREE and mSMR were highly correlated (<i>r</i> = 0.756, <i>p</i> &#x3c; 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. <b><i>Conclusion:</i></b> 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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