Energy Expenditure and Changes in Body Composition During Submarine Deployment—An Observational Study “DasBoost 2-2017”

The present study was designed to objectively assess the effects of 3-months submarine deployment on behavioural and metabolic determinants of metabolic health. In 13 healthy, non-obese volunteers, we using stable isotope dilution, and plasma and urinary biochemistry to characterize metabolic health before and after a 3-month submarine deployment. Volunteers worked in 6-h shifts. After deployment, we observed reduced fat-free mass (mean ± SD, −4.1 ± 3.3 kg, p = 0.003) and increased adiposity (21.9 ± 3.2% fat mass to 24.4 ± 4.7%, p = 0.01). Changes in fat-free mass were positively associated with physical activity (+0.8 kg per 0.1 increase in PAL, p = 0.03). The average physical activity level was 1.64 ± 0.26 and total energy expenditure during deployment was 2937 ± 498 kcal/d, while energy intake was 3158 ± 786 kcal/d. Fasting glucose (p = 0.03), and triglycerides (p = 0.01) declined, whereas fasting free fatty acids increased (p = 0.04). Plasma vitamin D and B12 concentrations decreased (−14%, p = 0.04, and −44%, p = 0.001, respectively), and plasma calcium, and magnesium increased (+51%, p = 0.01, and +5%, p = 0.02). Haemoglobin was unchanged, but haematocrit decreased (−2.2 ± 2.1%, p = 0.005). In conclusion, submarine deployment impairs fat-free mass maintenance and promotes adiposity. High physical activity may prevent the decline in fat-free mass. Our study confirms the need to counteract Vitamin D and B12 deficiencies, and suggests impairments in erythrocyte metabolism.

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

British Journal Of Nutrition ◽

10.1079/bjn2003940 ◽

2003 ◽

Vol 90 (3) ◽

pp. 643-649 ◽

Cited By ~ 14

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.

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

British Journal Of Nutrition ◽

10.1079/bjn20031000 ◽

2003 ◽

Vol 90 (6) ◽

pp. 1133-1139 ◽

Cited By ~ 18

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.

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Abstract P125: Multiple Measures of Energy Expenditure and Substrate Oxidation in Non-obese White and African American Young Adults

Circulation ◽

10.1161/circ.137.suppl_1.p125 ◽

2018 ◽

Vol 137 (suppl_1) ◽

Author(s):

Peter T Katzmarzyk ◽

Eric Ravussin

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Fat Oxidation ◽

Substrate Oxidation ◽

Activity Level ◽

Fat Free Mass ◽

Free Living ◽

Multiple Measures ◽

Oxidation Rates ◽

Increased Risk

Introduction: African Americans (AA) experience higher rates of obesity and related disorders than the general U.S. population. It has been hypothesized that the increased risk of obesity among AA may be explained, in part, by lower levels of energy expenditure (EE) and lower levels of fat oxidation. However, many different measures of EE and substrate oxidation have been employed across previous studies. Objective: The objective of this study was to compare multiple measures of EE and substrate oxidation among White (W) and AA adults. We hypothesize that AA will have lower EE and lower fat oxidation rates than W. Methods: A sample of 12 young (ages 22 to 35 y), non-obese AA adults was recruited from the local community and pair-matched by age, sex and body mass index (BMI) to a sample of 12 W adults. Height and weight were measured and BMI was calculated (kg/m 2 ). Total fat mass (FM) and fat free mass (FFM) were measured using dual energy x-ray absorptiometry. Resting EE (REE) and respiratory quotient (RQ) were measured in a fasting state using a metabolic cart; 24-hour EE, 24-h RQ, sleep EE and sleep RQ were measured in a whole room calorimeter; and free-living total daily EE (TDEE) was measured over two weeks using doubly labelled water. Physical activity level (PAL) was computed as TDEE/REE. Differences between W and AA were determined using general linear models, adjusting for FFM. Results: The analytic sample had a mean age of 27.0 y (SD 4.3 y) and mean BMI of 22.9 kg/m 2 (SD 2.9 kg/m 2 ). There were no significant differences in age, BMI, FM or FFM between W and AA (all p>0.05). However, W had significantly higher REE (1459 vs 1305 kcal/day; p=0.001), 24-h EE (1826 versus 1737 kcal/day; p=0.02), sleep EE (1509 vs 1405 kcal/day; p=0.005); but not TDEE (2452 vs 2313 kcal/day; p=0.30) compared to AA. There were no race differences in RQ (0.83 vs 0.83; p=0.93), 24-h RQ (0.86 vs 0.88; p=0.24) or sleep RQ (0.86 vs 0.87; p=0.44). On the other hand, AA had higher PAL (1.34 vs 1.26; p=0.04) compared to W. Conclusions: Non-obese W adults demonstrated higher REE, 24-h EE, and sleep EE compared to AA, but had similar levels of free-living TDEE. It appears as though some AA adults may compensate for lower REE by increased physical activity, which may be an effective strategy to prevent weight gain and obesity.

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Influence of habitual physical activity on gastric emptying in healthy males and relationships with body composition and energy expenditure

British Journal Of Nutrition ◽

10.1017/s0007114515002044 ◽

2015 ◽

Vol 114 (3) ◽

pp. 489-496 ◽

Cited By ~ 17

Author(s):

Katy M. Horner ◽

Nuala M. Byrne ◽

Geoffrey J. Cleghorn ◽

Neil A. King

Keyword(s):

Physical Activity ◽

Body Composition ◽

Gastric Emptying ◽

Energy Expenditure ◽

Fat Mass ◽

Physical Activity Level ◽

Activity Level ◽

Habitual Physical Activity ◽

Fat Free Mass ◽

Lower Percentage

Although a number of studies have examined the role of gastric emptying (GE) in obesity, the influences of habitual physical activity level, body composition and energy expenditure (EE) on GE have received very little consideration. In the present study, we compared GE in active and inactive males, and characterised relationships with body composition (fat mass and fat-free mass) and EE. A total of forty-four males (activen22, inactiven22; BMI 21–36 kg/m2; percentage of fat mass 9–42 %) were studied, with GE of a standardised (1676 kJ) pancake meal being assessed by the [13C]octanoic acid breath test, body composition by air displacement plethysmography, RMR by indirect calorimetry, and activity EE (AEE) by accelerometry. The results showed that GE was faster in active compared with inactive males (mean half-time (t1/2): active 157 (sd18) and inactive 179 (sd21) min,P< 0·001). When data from both groups were pooled, GEt1/2was associated with percentage of fat mass (r0·39,P< 0·01) and AEE (r− 0·46,P< 0·01). After controlling for habitual physical activity status, the association between AEE and GE remained, but not that for percentage of fat mass and GE. BMI and RMR were not associated with GE. In summary, faster GE is considered to be a marker of a habitually active lifestyle in males, and is associated with a higher AEE level and a lower percentage of fat mass. The possibility that GE contributes to a gross physiological regulation (or dysregulation) of food intake with physical activity level deserves further investigation.

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Physical Activity Level Using Doubly-Labeled Water in Relation to Body Composition and Physical Fitness in Preschoolers

Medicina ◽

10.3390/medicina55010002 ◽

2018 ◽

Vol 55 (1) ◽

pp. 2 ◽

Cited By ~ 1

Author(s):

Marja Leppänen ◽

Pontus Henriksson ◽

Hanna Henriksson ◽

Christine Delisle Nyström ◽

Francisco Llorente-Cantarero ◽

...

Keyword(s):

Physical Activity ◽

Body Composition ◽

Energy Expenditure ◽

Physical Fitness ◽

Basal Metabolic Rate ◽

Muscular Strength ◽

Total Energy Expenditure ◽

Activity Level ◽

Fat Free Mass ◽

Doubly Labeled Water

Background and objectives: There is a lack of studies investigating associations of physical activity level (PAL) and activity energy expenditure (AEE) using the doubly-labeled water (DLW) method with body composition and physical fitness in young children. Thus, we aimed to examine cross-sectional associations of PAL and AEE with body composition indices and physical fitness components in Swedish preschool children. Materials and methods: PAL was calculated as total energy expenditure measured using DLW divided by the predicted basal metabolic rate in 40 children aged 5.5 (standard deviation 0.2) years. AEE was calculated as total energy expenditure minus basal metabolic rate and the thermic effect of food, and divided by fat-free mass. Body composition was assessed using the 3-component model by combining measurements based on isotope dilution and air-displacement plethysmography. Physical fitness (muscular strength, motor fitness, and cardiorespiratory fitness) was evaluated using the PREFIT test battery. Multiple linear regression models were conducted. Results: PAL and AEE were negatively associated with body mass index, percent body fat, and fat mass index (PAL: standardized β −0.35, −0.41, and −0.45, all p < 0.036; AEE: standardized β −0.44, −0.44, and −0.47, all p < 0.006, respectively). Furthermore, PAL and AEE were positively associated with the standing long jump test (PAL: standardized β 0.37, p = 0.017; AEE: standardized β 0.38, p = 0.014). There were no statistically significant associations found regarding PAL or AEE with fat-free mass index or any other physical fitness test. Conclusions: Greater PAL and AEE at the age 5.5 were significantly associated with body fatness and improved lower-body muscular strength. Therefore, increasing physical activity, and thus energy expenditure, at young ages may be beneficial for preventing overweight/obesity. However, further studies with larger sample sizes are needed to confirm the results.

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The impact of the Luton social prescribing programme on energy expenditure: a quantitative before-and-after study

BMJ Open ◽

10.1136/bmjopen-2018-026862 ◽

2019 ◽

Vol 9 (6) ◽

pp. e026862

Author(s):

Julia Vera Pescheny ◽

Laura H Gunn ◽

Gurch Randhawa ◽

Yannis Pappas

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Activity Level ◽

Service Users ◽

Activity Levels ◽

Post Intervention ◽

Social Prescribing ◽

Physical Activity Levels ◽

Before And After ◽

Negative Effect

ObjectivesThe objective of this study was to assess the change in energy expenditure levels of service users after participation in the Luton social prescribing programme.DesignUncontrolled before-and-after study.SettingThis study was set in the East of England (Luton).ParticipantsService users with complete covariate information and baseline measurements (n=146) were included in the analysis.InterventionSocial prescribing, which is an initiative that aims to link patients in primary care with sources of support within the community sector to improve their health, well-being and care experience. Service users were referred to 12 sessions (free of charge), usually provided by third sector organisations.Primary outcome measureEnergy expenditure measured as metabolic equivalent (MET) minutes per week.ResultsUsing a Bayesian zero-inflated negative binomial model to account for a large number of observed zeros in the data, 95% posterior intervals show that energy expenditure from all levels of physical activities increased post intervention (walking 41.7% (40.31%, 43.11%); moderate 5.0% (2.94%, 7.09%); vigorous 107.3% (98.19%, 116.20%) and total 56.3% (54.77%, 57.69%)). The probability of engaging in physical activity post intervention increased, in three of four MET physical activity levels, for those individuals who were inactive at the start of the programme. Age has a negative effect on energy expenditure from any physical activity level. Similarly, working status has a negative effect on energy expenditure in all but one MET physical activity level. No consistent pattern was observed across physical activity levels in the association between gender and energy expenditure.ConclusionThis study shows that social prescribing may have the potential to increase the physical activity levels of service users and promote the uptake of physical activity in inactive patient groups. Results of this study can inform future research in the field, which could be of use for commissioners and policy makers.

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Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer

Journal of Applied Physiology ◽

10.1152/japplphysiol.00150.2009 ◽

2009 ◽

Vol 107 (3) ◽

pp. 655-661 ◽

Cited By ~ 132

Author(s):

A. G. Bonomi ◽

G. Plasqui ◽

A. H. C. Goris ◽

K. R. Westerterp

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Classification Tree ◽

The Body ◽

Activity Level ◽

Fat Free Mass ◽

Activity Type ◽

Tree Model ◽

Classification Tree Model ◽

Activity Types

Accelerometers are often used to quantify the acceleration of the body in arbitrary units (counts) to measure physical activity (PA) and to estimate energy expenditure. The present study investigated whether the identification of types of PA with one accelerometer could improve the estimation of energy expenditure compared with activity counts. Total energy expenditure (TEE) of 15 subjects was measured with the use of double-labeled water. The physical activity level (PAL) was derived by dividing TEE by sleeping metabolic rate. Simultaneously, PA was measured with one accelerometer. Accelerometer output was processed to calculate activity counts per day (ACD) and to determine the daily duration of six types of common activities identified with a classification tree model. A daily metabolic value (METD) was calculated as mean of the MET compendium value of each activity type weighed by the daily duration. TEE was predicted by ACD and body weight and by ACD and fat-free mass, with a standard error of estimate (SEE) of 1.47 MJ/day, and 1.2 MJ/day, respectively. The replacement in these models of ACD with METD increased the explained variation in TEE by 9%, decreasing SEE by 0.14 MJ/day and 0.18 MJ/day, respectively. The correlation between PAL and METD ( R2 = 51%) was higher than that between PAL and ACD ( R2 = 46%). We conclude that identification of activity types combined with MET intensity values improves the assessment of energy expenditure compared with activity counts. Future studies could develop models to objectively assess activity type and intensity to further increase accuracy of the energy expenditure estimation.

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Physical activity in aging: Comparison among young, aged, and nonagenarian individuals

Journal of Applied Physiology ◽

10.1152/japplphysiol.90450.2008 ◽

2008 ◽

Vol 105 (2) ◽

pp. 495-501 ◽

Cited By ~ 35

Author(s):

Darcy L. Johannsen ◽

James P. DeLany ◽

Madlyn I. Frisard ◽

Michael A. Welsch ◽

Christina K. Rowley ◽

...

Keyword(s):

Physical Activity ◽

Energy Expenditure ◽

Resting Metabolic Rate ◽

Daily Basis ◽

Activity Level ◽

Fat Free Mass ◽

Moderate Activity ◽

Timed Test ◽

Reliable Methods ◽

Physical Functionality

Physical activity (PA) is known to decline with age; however, there is a paucity of data on activity in persons who are in their nineties and beyond. We used objective and reliable methods to measure PA in nonagenarians (≥90 yr; n = 98) and hypothesized that activity would be similar to that of aged (60–74 yr; n = 58) subjects but less than in young (20–34 yr; n = 53) volunteers. Total energy expenditure (TEE) was measured by doubly labeled water over 14 days and resting metabolic rate (RMR) by indirect calorimetry. Measures of PA included activity energy expenditure adjusted for body composition, TEE adjusted for RMR, physical activity level (PAL), and activity over 14 days by accelerometry expressed as average daily durations of light and moderate activity. RMR and TEE were lower with increasing age group ( P < 0.01); however, RMR was not different between aged and nonagenarian subjects after adjusting for fat-free mass, fat mass, and sex. Nonagenarians had a lower PAL and were more sedentary than the aged and young groups ( P < 0.01); however, the nonagenarians who were more active on a daily basis walked further during a timed test, indicating higher physical functionality. For all measures of activity, no differences were found between young and aged volunteers. PA was markedly lower in nonagenarians compared with young and aged adults. Interestingly, PA was similar between young volunteers and those who were in their 60s and 70s, likely due to the sedentary nature of our society, particularly in young adults.

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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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Resistance training increases total energy expenditure and free-living physical activity in older adults

Journal of Applied Physiology ◽

10.1152/jappl.2000.89.3.977 ◽

2000 ◽

Vol 89 (3) ◽

pp. 977-984 ◽

Cited By ~ 158

Author(s):

Gary R. Hunter ◽

Carla J. Wetzstein ◽

David A. Fields ◽

Amanda Brown ◽

Marcas M. Bamman

Keyword(s):

Physical Activity ◽

Older Adults ◽

Resistance Training ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Compartment Model ◽

Fat Free Mass ◽

Free Living ◽

Oxidation Rates ◽

Before And After

The purpose of this study was to determine what effects 26 wk of resistance training have on resting energy expenditure (REE), total free-living energy expenditure (TEE), activity-related energy expenditure (AEE), engagement in free-living physical activity as measured by the activity-related time equivalent (ARTE) index, and respiratory exchange ratio (RER) in 61- to 77-yr-old men ( n = 8) and women ( n = 7). Before and after training, body composition (four-compartment model), strength, REE, TEE (doubly labeled water), AEE (TEE − REE + thermic response to meals), and ARTE (AEE adjusted for energy cost of standard activities) were evaluated. Strength (36%) and fat-free mass (2 kg) significantly increased, but body weight did not change. REE increased 6.8%, whereas resting RER decreased from 0.86 to 0.83. TEE (12%) and ARTE (38%) increased significantly, and AEE (30%) approached significance ( P = 0.06). The TEE increase remained significant even after adjustment for the energy expenditure of the resistance training. In response to resistance training, TEE increased and RER decreased. The increase in TEE occurred as a result of increases in both REE and physical activity. These results suggest that resistance training may have value in increasing energy expenditure and lipid oxidation rates in older adults, thereby improving their metabolic profiles.

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