scholarly journals Metabolic Adaptation is Associated With Less Weight and Fat Mass Loss in Response to Low-Energy Diets

2021 ◽  
Author(s):  
Catia Martins ◽  
Jessica Roekenes ◽  
Barbara Gower ◽  
Gary Hunter
Keyword(s):  
Fat Mass ◽  
Resting Metabolic Rate ◽  
Activity Level ◽  
Low Energy ◽  
Fat Free Mass ◽  
Metabolic Adaptation ◽  
Dietary Adherence ◽  
Air Displacement Plethysmography ◽  
Weight Loss Outcomes

Abstract Background: The practical relevance of metabolic adaptation remains a controversial issue. To the best of our knowledge, no study has properly evaluated the role of metabolic adaptation in modulating weight loss outcomes. Therefore, the aim of this study was to determine the association between metabolic adaptation, at the level of resting metabolic rate (RMR), and weight and fat mass (FM) loss after low-energy diets (LED), after adjusting for dietary adherence and other confounders. Methods: 71 individuals with obesity (BMI: 34.6±3.4 kg/m2; age: 45.4±8.2 years; 33 males) were randomized to one of three 1000 kcal/day diets for 8 weeks. Body weight, FM and fat-free mass (FFM) (air displacement plethysmography), RMR (indirect calorimetry) and physical activity level (PAL) (armbands) were measured at baseline and at week 9. Metabolic adaptation at week 9 was defined as measured – predicted RMR (using own regression model). Dietary adherence was calculated from RMR, PAL and body composition changes. Linear regression was used to assess the potential role of metabolic adaptation in predicting weight and FM loss after adjusting for dietary adherence, average PAL, sex, baseline FM and FFM and randomization group.Results: Participants lost on average 14±4 kg (13±3%) and presented with metabolic adaptation (-92±110 kcal/day, P<0.001). Metabolic adaptation was a significant predictor of both weight and FM loss (β=-0.01, P<0.001 for both), even after adjusting for confounders (R2=0.88, 0.93, respectively, P<0.001 for both). On average, an increase in metabolic adaptation of 50 kcal/day was associated with a 0.5 kg lower weight and FM loss in response to the LED. Conclusion: In individuals with obesity, metabolic adaptation at the level of RMR is associated with less weight and FM loss in response to LED. Trial registration ID: NCT02944253

scholarly journals Metabolic adaptation is associated with less weight and fat mass loss in response to low-energy diets

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Catia Martins ◽  
Jessica Roekenes ◽  
Barbara A. Gower ◽  
Gary R. Hunter
Keyword(s):  
Body Weight ◽  
Fat Mass ◽  
Resting Metabolic Rate ◽  
Activity Level ◽  
Low Energy ◽  
Fat Free Mass ◽  
Metabolic Adaptation ◽  
Dietary Adherence ◽  
Air Displacement Plethysmography

Abstract Background The practical relevance of metabolic adaptation remains a controversial issue. To the best of our knowledge, no study has properly evaluated the role of metabolic adaptation in modulating weight loss outcomes. Therefore, the aim of this study was to determine the association between metabolic adaptation, at the level of resting metabolic rate (RMR), and weight and fat mass (FM) loss after low-energy diets (LED), after adjusting for dietary adherence and other confounders. Methods 71 individuals with obesity (BMI: 34.6 ± 3.4 kg/m2; age: 45.4 ± 8.2 years; 33 males) were randomized to one of three 1000 kcal/day diets for 8 weeks. Body weight, FM and fat-free mass (FFM) (air displacement plethysmography), RMR (indirect calorimetry) and physical activity level (PAL) (armbands) were measured at baseline and at week 9. Metabolic adaptation at week 9 was defined as measured RMR minus predicted RMR at week 9. An equation to predict RMR was derived from baseline data of all participants that were part of this analysis and included age, sex, FM and FFM as predictors. Dietary adherence was calculated from RMR, PAL and body composition changes. Linear regression was used to assess the potential role of metabolic adaptation in predicting weight and FM loss after adjusting for dietary adherence, average PAL, sex, baseline FM and FFM and randomization group. Results Participants lost on average 14 ± 4 kg of body weight (13 ± 3%) and presented with metabolic adaptation (−92 ± 110 kcal/day, P < 0.001). Metabolic adaptation was a significant predictor of both weight (β = −0.009, P < 0.001) and FM loss (β = −0.008, P < 0.001), even after adjusting for confounders (R2 = 0.88, 0.93, respectively, P < 0.001 for both). On average, an increase in metabolic adaptation of 50 kcal/day was associated with a 0.5 kg lower weight and FM loss in response to the LED. Conclusion In individuals with obesity, metabolic adaptation at the level of RMR is associated with less weight and FM loss in response to LED. Trial registration ID: NCT02944253.

Resting Metabolic Rate and Thermic Effect of a Meal in Low- and Adequate-Energy Intake Male Endurance Athletes

1993 ◽  
Vol 3 (2) ◽  
pp. 194-206 ◽  
Author(s):  
Janice Thompson ◽  
Melinda M. Manore ◽  
James S. Skinner
Keyword(s):  
Metabolic Rate ◽  
Energy Intake ◽  
Weight Maintenance ◽  
Resting Metabolic Rate ◽  
Activity Level ◽  
Low Energy ◽  
Fat Free Mass ◽  
Endurance Athletes ◽  
Male Athletes ◽  
Thermic Effect

The resting metabolic rate (RMR) and thermic effect of a meal (TEM) were determined in 13 low-energy intake (LOW) and 11 adequate-energy intake (ADQ) male endurance athletes. The LOW athletes reported eating 1,490 kcal·day-1less than the ADQ group, while the activity level of both groups was similar. Despite these differences, both groups had a similar fat-free mass (FFM) and had been weight stable for at least 2 years. The RMR was significantly lower (p<0.05) in the LOW group compared to the values of the ADQ group (1.19 vs. 1.29 kcal·FFM-1·hr-l, respectively); this difference represents a lower resting expenditure of 158 kcal·day-1. No differences were found in TEM between the two groups. These results suggest that a lower RMR is one mechanism that contributes to weight maintenance in a group of low- versus adequate-energy intake male athletes.

scholarly journals Seasonal and Longitudinal Changes in Body Composition by Sport-Position in NCAA Division I Basketball Athletes

Sports ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 85 ◽  
Author(s):  
Jennifer Fields ◽  
Justin Merrigan ◽  
Jason White ◽  
Margaret Jones
Keyword(s):  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Ncaa Division I ◽  
The Body ◽  
Fat Free Mass ◽  
Strength And Conditioning ◽  
Air Displacement Plethysmography ◽  
Within Subjects

The purpose of this study was to assess the body composition of male and female basketball athletes (n = 323) across season, year, and sport-position using air displacement plethysmography. An independent sample t-test assessed sport-position differences. An analysis of variance was used to assess within-subjects across season (pre-season, in-season, and off-season), and academic year (freshman, sophomore, and junior). For both men and women basketball (MBB, WBB) athletes, guards had the lowest body fat, fat mass, fat free mass, and body mass. No seasonal differences were observed in MBB, but following in-season play for WBB, a reduction of (p = 0.03) in fat free mass (FFM) was observed. Across years, MBB showed an increase in FFM from freshman to sophomore year, yet remained unchanged through junior year. For WBB across years, no differences occurred for body mass (BM), body fat (BF%), and fat mass (FM), yet FFM increased from sophomore to junior year (p = 0.009). Sport-position differences exist in MBB and WBB: Guards were found to be smaller and leaner than forwards. Due to the importance of body composition (BC) on athletic performance, along with seasonal and longitudinal shifts in BC, strength and conditioning practitioners should periodically assess athletes BC to ensure preservation of FFM. Training and nutrition programming can then be adjusted in response to changes in BC.

Ethnic differences in sympathetic nervous system-mediated energy expenditure

1991 ◽  
Vol 261 (6) ◽  
pp. E789-E794 ◽  
Author(s):  
M. F. Saad ◽  
S. A. Alger ◽  
F. Zurlo ◽  
J. B. Young ◽  
C. Bogardus ◽  
...  
Keyword(s):  
Nervous System ◽  
Energy Expenditure ◽  
Sympathetic Nervous System ◽  
Fat Mass ◽  
Weight Maintenance ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
Beta Adrenoceptor ◽  
Sympathetic Nervous ◽  
The Impact

The impact of sympathetic nervous system (SNS) activity on energy expenditure (EE) was evaluated in nondiabetic Caucasian and Pima Indian men while on a weight-maintenance diet using two approaches as follows. 1) The relationship between 24-h EE, measured in a respiratory chamber, and 24-h urinary norepinephrine was studied in 36 Caucasians [32 +/- 8 (SD) yr, 95 +/- 41 kg, 22 +/- 13% fat] and 33 Pimas (29 +/- 6 yr, 103 +/- 28 kg, 30 +/- 9% fat). There was no difference between the two groups in 24-h EE (2,422 vs. 2,523 kcal/24 h) and in urinary norepinephrine (28 vs. 31 micrograms/24 h), even after adjusting for body size and composition. Twenty-four-hour EE correlated significantly with 24-h urinary norepinephrine in Caucasians (r = 0.78, P less than 0.001) but not in Pimas (r = 0.03), independent of fat-free mass (FFM), fat mass, and age. 2) The effect of beta-adrenoceptor blockade with propranolol (120 micrograms/kg FFM bolus and 1.2 micrograms.kg FFM-1.min-1 for 45 min) on the resting metabolic rate (RMR) was evaluated in 36 Caucasians (30 +/- 6 yr, 103 +/- 36 kg, 25 +/- 11% fat) and 32 Pimas (28 +/- 6 yr, 100 +/- 34 kg, 27 +/- 10% fat). The RMR was similar in the two groups (2,052 vs. 1,973 kcal/24 h) even after adjustment for FFM, fat mass, and age and dropped significantly after propranolol infusion in Caucasians (-3.9%, P less than 0.001) but not in Pimas (-0.8%, P = 0.07).(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Habitual meal frequency in relation to resting and activity-induced energy expenditure in human subjects: the role of fat-free mass

2003 ◽  
Vol 90 (3) ◽  
pp. 643-649 ◽  
Author(s):  
Margriet S. Westerterp-Plantenga ◽  
Annelies H. C. Goris ◽  
Erwin P. Meijer ◽  
Klaas R. Westerterp
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Human Subjects ◽  
Older Men ◽  
Activity Level ◽  
Fat Free Mass ◽  
Meal Frequency ◽  
Younger Women ◽  
Younger Men

Habitual meal frequency was assessed as a possible function of components of energy expenditure (EE) in human subjects. Fifty-six subjects participated (four categories differing in body composition): ten older women (fat-free mass (FFM) 42·0 (sd 6·3) kg, aged 59 (sd 2) years, BMI 27·5 (sd 6·9) kg/m2), fifteen younger women (FFM 45·5 (sd 5·2) kg, aged 34 (sd 10) years, BMI 21·9 (sd 2·3) kg/m2), twelve older men (FFM 56·8 (sd 5·9) kg, aged 62 (sd 4) years, BMI 25·7 (sd 3·3) kg/m2) and nineteen younger men (FFM 63·9 (sd 7·5) kg, aged 23·1 (sd 3·9) years, BMI 22·9 (sd 1·8) kg/m2). Measurements consisted of habitual meal frequency by validated food-intake diaries, physical activity by tri-axial accelerometers and resting EE by a ventilated hood system. Habitual meal frequency was expressed as a function of resting EE (including resting EE as a function of FFM), and of activity-induced EE, using regression analysis. FFM differed according to gender and age categories (P < 0·01). Physical activity level was higher in the younger men than in the other categories (P < 0·05). No relationship of meal frequency with the variables assessed was observed in subjects with a low FFM (the women). In the subjects with a medium FFM (the older men), meal frequency was positively related to resting EE (r2 0·4, P < 0·05), but not to the residuals of resting EE as a function of FFM, and inversely related to activity-induced EE (r2 0·3, P < 0·05). Resting EE explained 40% of the variation in meal frequency; adding activity-induced EE increased this to 60%. In the subjects with a high FFM (the younger men), meal frequency was inversely related to resting EE (r2 0·8, P < 0·0001) and to the residuals of resting EE as a function of FFM (P = 0·03), and positively related to activity-induced EE (r2 0·6, P < 0·0001). Resting EE explained 85% of the variation in meal frequency; adding activity-induced EE increased this to 89%. Habitual meal frequency was a function of components of EE, namely resting EE and activity-induced EE, only in subjects with a medium to high FFM (men). FFM-related differences in these relationships suggest a role of physical activity.

scholarly journals New charts for the assessment of body composition, according to air-displacement plethysmography, at birth and across the first 6 mo of life

2019 ◽  
Vol 109 (5) ◽  
pp. 1353-1360 ◽  
Author(s):  
Tom Norris ◽  
Sara E Ramel ◽  
Patrick Catalano ◽  
Carol ni Caoimh ◽  
Paola Roggero ◽  
...  
Keyword(s):  
United States ◽  
Body Composition ◽  
Preterm Infants ◽  
Fat Mass ◽  
Gestational Age ◽  
The United States ◽  
Fat Free Mass ◽  
Term Infants ◽  
Air Displacement Plethysmography ◽  
Young Infants

ABSTRACT Background Air-displacement plethysmography (ADP) is a good candidate for monitoring body composition in newborns and young infants, but reference centile curves are lacking that allow for assessment at birth and across the first 6 mo of life. Objective Using pooled data from 4 studies, we aimed to produce new charts for assessment according to gestational age at birth (30 + 1 to 41 + 6 wk) and postnatal age at measurement (1–27 wk). Methods The sample comprised 222 preterm infants born in the United States who were measured at birth; 1029 term infants born in Ireland who were measured at birth; and 149 term infants born in the United States and 57 term infants born in Italy who were measured at birth, 1 and 2 wk, and 1, 2, 3, 4, 5, and 6 mo of age. Infants whose birth weights were <3rd or >97th centile of the INTERGROWTH-21st standard were excluded, thereby ensuring that the charts depict body composition of infants whose birth weights did not indicate suboptimal fetal growth. Sex-specific centiles for fat mass (kg), fat-free mass (kg), and percentage body fat were estimated using the lambda-mu-sigma (LMS) method. Results For each sex and measure (e.g., fat mass), the new charts comprised 2 panels. The first showed centiles according to gestational age, allowing term infants to be assessed at birth and preterm infants to be monitored until they reached term. The second showed centiles according to postnatal age, allowing all infants to be monitored to age 27 wk. The LMS values underlying the charts were presented, enabling researchers and clinicians to convert measurements to centiles and z scores. Conclusions The new charts provide a single tool for the assessment of body composition, according to ADP, in infants across the first 6 mo of life and will help enhance early-life nutritional management.

scholarly journals Fat and Fat-Free Mass of Preterm and Term Infants from Birth to Six Months: A Review of Current Evidence

Nutrients ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 288 ◽  
Author(s):  
Constanze Hamatschek ◽  
Efrah I. Yousuf ◽  
Lea Sophie Möllers ◽  
Hon Yiu So ◽  
Katherine M. Morrison ◽  
...  
Keyword(s):  
Preterm Infants ◽  
Fat Mass ◽  
Infant Nutrition ◽  
Dual Energy ◽  
Fat Free Mass ◽  
Current Evidence ◽  
Term Infants ◽  
Air Displacement Plethysmography ◽  
X Ray ◽  
Postmenstrual Age

To optimize infant nutrition, the nature of weight gain must be analyzed. This study aims to review publications and develop growth charts for fat and fat-free mass for preterm and term infants. Body composition data measured by air displacement plethysmography (ADP) and dual energy X-ray absorptiometry (DXA) in preterm and term infants until six months corrected age were abstracted from publications (31 December 1990 to 30 April 2019). Age-specific percentiles were calculated. ADP measurements were used in 110 studies (2855 preterm and 22,410 term infants), and DXA was used in 28 studies (1147 preterm and 3542 term infants). At term age, preterm infants had higher percent-fat than term-born infants (16% vs. 11%, p < 0.001). At 52 weeks postmenstrual age (PMA), both reached similar percent-fat (24% vs. 25%). In contrast, at term age, preterm infants had less fat-free mass (2500 g vs. 2900 g) by 400 g. This difference decreased to 250 g by 52 weeks, and to 100 g at 60 weeks PMA (5000 g vs. 5100 g). DXA fat-free mass data were comparable with ADP. However, median percent-fat was up to 5% higher with DXA measurements compared with ADP with PMA > 50 weeks. There are methodological differences between ADP and DXA measures for infants with higher fat mass. The cause of higher fat mass in preterm infants at term age needs further investigation.

Impact of body fat mass and percent fat on metabolic rate and thermogenesis in men

1989 ◽  
Vol 256 (5) ◽  
pp. E573-E579 ◽  
Author(s):  
K. R. Segal ◽  
I. Lacayanga ◽  
A. Dunaif ◽  
B. Gutin ◽  
F. X. Pi-Sunyer
Keyword(s):  
Metabolic Rate ◽  
Body Fat ◽  
Fat Mass ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
Body Fat Mass ◽  
Thermic Effect Of Food ◽  
Group A ◽  
Effect Of Food ◽  
Thermic Effect

To clarify further the independent relationships of body composition parameters to energy expenditure, resting metabolic rate (RMR) and postprandial thermogenesis were studied in four groups who were matched for absolute fat mass (study 1) and relative fatness (study 2). In study 1, five lean [group A, 15.4 +/- 0.6% (+/- SE) body fat] and five obese men (group B, 25.0 +/- 0.9% fat) were matched on body fat mass (13.0 +/- 0.9 vs. 14.4 +/- 0.8 kg, respectively). Fat-free mass (FFM) and total weight were greater for group A than B. RMR was measured for 3 h in the fasted state and after a 720-kcal mixed meal. RMR was greater for group A than B (1.38 +/- 0.08 vs. 1.14 +/- 0.04 kcal/min, P less than 0.05). The thermic effect of food, calculated as 3 h postprandial minus fasting RMR, was greater for group A than B (65 +/- 6 vs. 23 +/- 9 kcal/3 h; P less than 0.05). In study 2, two groups (n = 6 men/group) were matched for percent body fat (33 +/- 1% fat for both) but differed in lean, fat, and total weights: 50.8 +/- 3.1 kg FFM for the lighter (group C) vs. 68.0 +/- 2.8 kg FFM for the heavier (group D) group, P less than 0.05. RMR was lower for group C than D (1.17 +/- 0.06 vs. 1.33 +/- 0.04 kcal/min, P less than 0.05), but the thermic effect of food was not significantly different (31 +/- 3 vs. 20 +/- 6 kcal/3 h).(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Metabolic Adaptation Delays Time to Reach Weight Loss Goals

2021 ◽  
Author(s):  
Catia Martins ◽  
Barbara Gower ◽  
Gary Hunter
Keyword(s):  
Weight Loss ◽  
Body Weight ◽  
Regression Model ◽  
Resting Metabolic Rate ◽  
Premenopausal Women ◽  
Compartment Model ◽  
Metabolic Adaptation ◽  
Dietary Adherence ◽  
Weight Loss Goal ◽  
Composition Changes

Abstract BackgroundThe clinical relevance of metabolic adaptation remains to be fully determined, but its role as a driver of weight regain has been dismissed. It could be hypothesized that metabolic adaptation increases the length of time needed to reach weight loss goals. The aim of this study was, therefore, to determine if metabolic adaptation, at the level of resting metabolic rate (RMR), is associated with time to reach weight loss goals, after adjusting for confounders. Methods65 premenopausal women with overweight (BMI: 28.6±1.5 kg/m2; age: 36.4±5.9 years; 36 Whites and 29 Blacks) followed an 800 kcal/day diet until body mass index ≤25 kg/m2. Body weight and composition (4 compartment model (4CM) and dual x-ray absorptiometry (DXA)) and RMR (indirect calorimetry) were measured at baseline and after weight loss (after a 4-week weight stabilization period). Dietary adherence was calculated from total energy expenditure (TEE) determined by double labeled water measures and DXA body composition changes. Metabolic adaptation was defined as a significantly lower measured vs predicted RMR (from own regression model using 4CM data). A regression model to predict time to reach weight loss goals was developed including baseline body weight, baseline TEE, dietary adherence and metabolic adaptation as predictors. ResultsParticipants 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/day, P=0.002) and this variable was a significant predictor of time to reach weight loss goal (β=-0.1, P=0.033), even after adjusting for confounders (R2 adjusted = 0.59, P<0.001). ConclusionIn premenopausal women with overweight, metabolic adaptation after a 16% weight loss increases the length of time necessary to achieve weight loss goals. Trial registration ID (JULIET study)NCT00067873

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