Limits to sustainable human metabolic rate

2001 ◽  
Vol 204 (18) ◽  
pp. 3183-3187 ◽  
Author(s):  
Klaas R. Westerterp
Keyword(s):  
Physical Activity ◽  
Metabolic Rate ◽  
Activity Level ◽  
Fat Free Mass ◽  
Endurance Athletes ◽  
Mount Everest ◽  
Doubly Labelled Water ◽  
Upper Limit ◽  
Energy Mobilization ◽  
Access To Food

SUMMARY There is a limit to the performance of an organism set by energy intake and energy mobilization. Here, the focus is on humans with unlimited access to food and for whom physical activity can be limited by energy mobilization. The physical activity level (PAL) in the general population, calculated as doubly-labelled-water-assessed average daily metabolic rate as a multiple of basal metabolic rate, has an upper limit of 2.2–2.5. The upper limit of sustainable metabolic rate is approximately twice as high in endurance athletes, mainly because of long-term exercise training with simultaneous consumption of carbohydrate-rich food during exercise. Endurance athletes have an increased fat-free mass and can maintain energy balance at a PAL value of 4.0–5.0. High altitude limits exercise performance as a result of combined effects on nutrient supply and the capacity to process nutrients. Thus, trained subjects climbing Mount Everest reached PAL values of 2.0–2.7, well below the observed upper limit at sea level.

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 Body composition and physical activity in New Zealand Maori, Pacific and European children aged 5–14 years

2003 ◽  
Vol 90 (6) ◽  
pp. 1133-1139 ◽  
Author(s):  
Elaine C. Rush ◽  
Lindsay D. Plank ◽  
Peter S. W. Davies ◽  
Patsy Watson ◽  
Clare R. Wall
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Body Fat ◽  
Fat Mass ◽  
Activity Patterns ◽  
The Body ◽  
Activity Level ◽  
Fat Free Mass ◽  
Healthy Children ◽  
Doubly Labelled Water

Body fatness and the components of energy expenditure in children aged 5–14 years were investigated. In a group of seventy-nine healthy children (thirty-nine female, forty male), mean age 10·0 (sd 2·8) years, comprising twenty-seven Maori, twenty-six Pacific Island and twenty-six European, total energy expenditure (TEE) was determined over 10 d using the doubly-labelled water method. Resting metabolic rate (RMR) was measured by indirect calorimetry and physical activity level (PAL) was calculated as TEE:RMR. Fat-free mass (FFM), and hence fat mass, was derived from the 18O-dilution space using appropriate values for FFM hydration in children. Qualitative information on physical activity patterns was obtained by questionnaire. Maori and Pacific children had a higher BMI than European children (P<0·003), but % body fat was similar for the three ethnic groups. The % body fat increased with age for girls (r 0·42, P=0·008), but not for boys. Ethnicity was not a significant predictor of RMR adjusted for FFM and fat mass. TEE and PAL, adjusted for body weight and age, were higher in Maori than European children (P<0·02), with Pacific children having intermediate values. PAL was inversely correlated with % body fat in boys (r −0·43, P=0·006), but was not significantly associated in girls. The % body fat was not correlated with reported time spent inactive or outdoors. Ethnic-related differences in total and activity-related energy expenditure that might account for higher obesity rates in Maori and Pacific children were not seen. Low levels of physical activity were associated with increased body fat in boys but not in girls.

scholarly journals Physical Activity and/or High Protein Intake Maintains Fat-Free Mass in Older People with Mild Disability; the Fukuoka Island City Study: A Cross-Sectional Study

Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2595 ◽  
Author(s):  
Rie Takae ◽  
Yoichi Hatamoto ◽  
Jun Yasukata ◽  
Yujiro Kose ◽  
Takaaki Komiyama ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older People ◽  
Protein Intake ◽  
Vigorous Physical Activity ◽  
Linear Regression Analysis ◽  
Activity Level ◽  
Fat Free Mass ◽  
Doubly Labelled Water ◽  
Cross Sectional ◽  
Mild Disability

Body composition changes with age, with fat mass (FM) increasing and fat-free mass (FFM) decreasing. Higher physical activity and high or adequate protein intake are thought to be beneficial in preventing the loss of skeletal muscle mass in the elderly. We aimed to investigate the relationships between physical activity, protein intake, and FFM in older people with mild disability. Total energy expenditure (TEE) under free-living conditions was assessed using the doubly-labelled water (DLW) method, and physical activity was measured using a triaxial accelerometer. Dietary intake was assessed using a self-recorded food intake diary during the DLW period. Percent FFM was significantly positively correlated with protein intake and physical activity level (PAL) after adjustment for age and sex (protein intake r = 0.652, p < 0.001, PAL r = 0.345, p = 0.011). In multiple linear regression analysis, when PAL, moderate-to-vigorous physical activity (MVPA), or protein intake were included, 31%, 32%, and 55%, respectively, of the variation in %FFM was explained. Moreover, the addition of both PAL/MVPA and protein intake explained 61%/60%, respectively, of the variation in %FFM. Either protein intake above the currently recommended level or higher levels of physical activity would be beneficial for the maintenance of high %FFM.

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

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.

scholarly journals Effect of early determinants on adolescent fat-free mass

2020 ◽  
Vol 54 ◽  
pp. 113
Author(s):  
Raina Jansen Cutrim Propp Lima ◽  
Rosângela Fernandes Lucena Batista ◽  
Cecília Claudia Costa Ribeiro ◽  
Vanda Maria Ferreira Simões
Keyword(s):  
Physical Activity ◽  
Socioeconomic Status ◽  
Birth Weight ◽  
Physical Activity Level ◽  
Structural Equation ◽  
Activity Level ◽  
Fat Free Mass ◽  
Equation Modeling ◽  
Adolescent Physical Activity ◽  
Negative Effect

OBJECTIVE: To analyze the effects of early determinants on adolescent fat-free mass. METHODS: A c ohort s tudy w ith 5 79 a dolescents e valuated a t b irth a nd a dolescence i n a birth cohort in São Luís, Maranhão. In the proposed model, estimated by structural equation modeling, socioeconomic status (SES) at birth, maternal age, pregestational body mass index (BMI), gestational smoking, gestational weight gain, type of delivery, gestational age, sex of the newborn, length and weight at birth, adolescent socioeconomic status, “neither study/nor work” generation, adolescent physical activity level and alcohol consumption were tested as early determinants of adolescent fat-free mass (FFM). RESULTS: A higher pregestational BMI resulted in higher FFM in adolescence (Standardized Coefficient, SC = 0.152; p < 0.001). Being female implied a lower FFM in adolescence (SC = -0.633; p < 0.001). The negative effect of gender on FFM was direct (SC = -0.523; p < 0.001), but there was an indirect negative effect via physical activity level (SC = -0.085; p < 0.001). Women were less active (p < 0.001). An increase of 0.5 kg (1 Standard Deviation, SD) in birth weight led to a gain of 0.25 kg/m2 (0.106 SD) in adolescent FFM index (p = 0.034). Not studying or working had a negative effect on the adolescent’s FFM (SC = -0.106; p = 0.015). Elevation of 1 SD in the adolescent’s physical activity level represented an increase of 0.5 kg/m2 (0.207 SD) in FFM index (p < 0.001). CONCLUSIONS: The early determinants with the greatest effects on adolescent FFM are gender, adolescent physical activity level, pregestational BMI, birth weight and belonging to the “neither-nor” generation.

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

Nutrients ◽  
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.

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 Individual differences in physical activity are closely associated with changes in body weight in adult female rhesus monkeys (Macaca mulatta)

2006 ◽  
Vol 291 (3) ◽  
pp. R633-R642 ◽  
Author(s):  
Elinor L. Sullivan ◽  
Frank H. Koegler ◽  
Judy L. Cameron
Keyword(s):  
Physical Activity ◽  
Weight Gain ◽  
Food Intake ◽  
Metabolic Rate ◽  
Rhesus Monkeys ◽  
Caloric Intake ◽  
Activity Level ◽  
Female Rhesus ◽  
Measured Activity ◽  
Low Activity

The increased prevalence of overweight adults has serious health consequences. Epidemiological studies suggest an association between low activity and being overweight; however, few studies have objectively measured activity during a period of weight gain, so it is unknown whether low activity is a cause or consequence of being overweight. To determine whether individual differences in adult weight gain are linked to an individual’s activity level, we measured activity, via accelerometry, over a prolonged period (9 mo) in 18 adult female rhesus monkeys. Weight, food intake, metabolic rate, and activity were first monitored over a 3-mo period. During this period, there was mild but significant weight gain (5.5 ± 0.88%; t =−6.3, df = 17, P < 0.0001), whereas caloric intake and activity remained stable. Metabolic rate increased, as expected, with weight gain. Activity level correlated with weight gain ( r = −0.52, P = 0.04), and the most active monkeys gained less weight than the least active monkeys ( t = −2.74, df = 8, P = 0.03). Moreover, there was an eightfold difference in activity between the most and least active monkeys, and initial activity of each monkey was highly correlated with their activity after 9 mo ( r = 0.85, P < 0.0001). In contrast, food intake did not correlate with weight gain, and there was no difference in weight gain between monkeys with the highest vs. lowest caloric intake, total metabolic rate, or basal metabolic rate. We conclude that physical activity is a particularly important factor contributing to weight change in adulthood and that there are large, but stable, differences in physical activity among individuals.

scholarly journals Water loss as a function of energy intake, physical activity and season

2005 ◽  
Vol 93 (2) ◽  
pp. 199-203 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Guy Plasqui ◽  
Annelies H. C. Goris
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Energy Intake ◽  
Water Intake ◽  
Water Loss ◽  
Resting Energy Expenditure ◽  
Activity Level ◽  
Seasonal Effects ◽  
Water Turnover ◽  
Doubly Labelled Water

Although water is an important nutrient, there are no recommended intake values. Here, water intake, energy intake, physical activity and water loss was measured over 1 week in summer and in winter. Subjects were healthy volunteers, forty-two women and ten men, mean age of 29 (sd 7) years and mean BMI 21·8 (sd 2·2) kg/m2. Water intake was measured with a 7 d food and water record. Physical activity level (PAL) was observed as the ratio of total energy expenditure, as measured with doubly labelled water, to resting energy expenditure as measured in a respiration chamber. Water loss was measured with the deuterium elimination method. Water loss was highly reproducible and ranged from 0·20 to 0·35 l/MJ, independent of season and activity level, with higher values in women. Water loss was related to water and energy intake in summer (r 0·96, P<0·0001 and r 0·68, P<0·001, respectively) as well as in winter (r 0·98, P<0·0001 and r 0·63, P<0·01, respectively). Water loss was, for men, higher in subjects with a higher physical activity in summer (r 0·94, P<0·0001) and in winter (r 0·70, P<0·05). Normalizing water loss for differences in energy expenditure by expressing water loss in litres per MJ resulted in the same value for men in summer and winter. For women, physical activity-adjusted values of water loss were higher, especially in summer. In men, water turnover was determined by energy intake and physical activity, while seasonal effects appeared through energy expenditure. Women showed a higher water turnover that was unrelated to physical activity.

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