Effects of diurnal exercise timing on appetite, energy intake and body composition: A parallel randomized trial

Appetite ◽  
2021 ◽  
pp. 105600
Author(s):  
ShaunY.M. Teo ◽  
Jill A. Kanaley ◽  
Kym J. Guelfi ◽  
James A. Dimmock ◽  
Ben Jackson ◽  
...  
Keyword(s):  
Body Composition ◽  
Randomized Trial ◽  
Energy Intake ◽  
Exercise Timing

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.

Comparison of energy expenditure, body composition, metabolic disorders, and energy intake between obese children with a history of craniopharyngioma and children with multifactorial obesity

2015 ◽  
Vol 28 (11-12) ◽  
Author(s):  
Ilanit Bomer ◽  
Carola Saure ◽  
Carolina Caminiti ◽  
Javier Gonzales Ramos ◽  
Graciela Zuccaro ◽  
...  
Keyword(s):  
Body Composition ◽  
Energy Expenditure ◽  
Energy Intake ◽  
Positive Association ◽  
Bioelectrical Impedance ◽  
Fat Free Mass ◽  
Control Group ◽  
Model Assessment ◽  
Obese Children ◽  
Mass Percentage

AbstractCraniopharyngioma is a histologically benign brain malformation with a fundamental role in satiety modulation, causing obesity in up to 52% of patients.To evaluate cardiovascular risk factors, body composition, resting energy expenditure (REE), and energy intake in craniopharyngioma patients and to compare the data with those from children with multifactorial obesity.All obese children and adolescents who underwent craniopharyngioma resection and a control group of children with multifactorial obesity in follow-up between May 2012 and April 2013.Anthropometric measurements, bioelectrical impedance, indirect calorimetry, energy intake, homeostatic model assessment insulin resistance (HOMA-IR), and dyslipidemia were evaluated.Twenty-three patients with craniopharyngioma and 43 controls were included. Children with craniopharyngioma-related obesity had a lower fat-free mass percentage (62.4 vs. 67.5; p=0.01) and a higher fat mass percentage (37.5 vs. 32.5; p=0.01) compared to those with multifactorial obesity. A positive association was found between %REE and %fat-free mass in subjects with multifactorial obesity (68±1% in normal REE vs. 62.6±1% in low REE; p=0.04), but not in craniopharyngioma patients (62±2.7 in normal REE vs. 61.2±1.8% in low REE; p=0.8). No differences were found in metabolic involvement or energy intake.REE was lower in craniopharyngioma patients compared to children with multifactorial obesity regardless of the amount of fat-free mass, suggesting that other factors may be responsible for the lower REE.

Excretion of urinary catecholamine metabolites in anorexia nervosa: effect of body composition and energy intake

1984 ◽  
Vol 40 (5) ◽  
pp. 1001-1006 ◽  
Author(s):  
J L Johnston ◽  
L A Leiter ◽  
G N Burrow ◽  
P E Garfinkel ◽  
G H Anderson
Keyword(s):  
Body Composition ◽  
Anorexia Nervosa ◽  
Energy Intake ◽  
Urinary Catecholamine ◽  
Catecholamine Metabolites

scholarly journals Telemedicine Intervention to Improve Long-Term Risk Factor Control and Body Composition in Persons with High Cardiovascular Risk: Results from a Randomized Trial

Global Heart ◽  
2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Nana Pogosova ◽  
Yulia Yufereva ◽  
Olga Sokolova ◽  
Anara Yusubova ◽  
Alexander Suvorov ◽  
...  
Keyword(s):  
Body Composition ◽  
Risk Factor ◽  
Cardiovascular Risk ◽  
Randomized Trial ◽  
High Cardiovascular Risk ◽  
Risk Factor Control

scholarly journals The LEAF questionnaire is a good screening tool for the identification of the Female Athlete Triad/Relative Energy Deficiency in Sport among young football players

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12118
Author(s):  
Edyta Łuszczki ◽  
Pawel Jagielski ◽  
Anna Bartosiewicz ◽  
Maciej Kuchciak ◽  
Katarzyna Dereń ◽  
...  
Keyword(s):  
At Risk ◽  
Body Composition ◽  
Energy Intake ◽  
Female Athlete ◽  
Relative Energy ◽  
Screening Tools ◽  
Football Players ◽  
Female Athlete Triad ◽  
Energy Deficiency ◽  
Not At Risk

Background It has been noticed that Female Athlete Triad (Fat) and Relative Energy Deficiency (Red-S) in Sport are characterized by the symptoms of impaired endocrine-metabolic function and bone health in female athletes. In addition, it may be evaluated with a qualitative tool, such as Low Energy Availability in Females questionnaire (LEAF-Q) and quantitative measurements: bone mineral density (BMD), resting energy expenditure (REE), body composition, 24-hour dietary recall. Methods The aim of this study was to assess the prevalence of Triad and Red-S using the LEAF-Q in youth female football players. Additionally, the difference in the BMD, body composition, REE and energy intake (EI) were assessed between the Triad/Red-S risk and not at-risk groups. Results Almost two thirds (64.7%) of participants are classified as being at-risk for the triad according to their LEAF-Q scores. There were no statistically significant differences (p > 0.05) between most of the values among children from the analyzed groups. There was a statistically significant difference (p < 0.001) between the EI values among girls from the two analyzed groups: at-risk (1,773.18 kcal ±  232.57) and not at-risk (2,054.00 kcal ±  191.39). Girls who did not meet the energy intake recommendations were 10.00 as likely to be in the Triad/Red-S risk group. Conclusion Early identification of Fat/Red-S symptoms by screening tools such as the LEAF questionnaire is important in protecting young athletes from long-term damage due to the progression of the risk factors associated with the Fat/Red-S.

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