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The estimation of energy expenditure is key to resolve ecological questions and conservation strategies. The puma (Puma concolor (Linnaeus, 1771)) has been the subject of several efforts to measure the daily energy expenditure (DEE). Most of the estimations have been made using movement or activity models that have been questioned because of discrepancies with kill rates. This study looks at one movement model estimation and validates it using doubly labeled water (DLW), which can also account for energy expenditures beyond those associated with activity. We captured six pumas (51.5 ± 9.9 (SD) kg) during the winter in Colorado that were GPS collared and injected with DLW for an approximately 3-week trial. We found that DEE obtained from the DLW (14.5 ± 6.1 MJ·day−1) did not differ from that estimated using the movement model or from the predicted allometric equation based on DLW studies on other mammals. Decreasing air temperature and increasing daily distance movement were correlated with increasing DEE for monitored pumas. Both DLW and movement models provide a reasonable proxy to estimate DEE at the population level but exhibit low precision in estimating individual values for free-ranging puma. [ABSTRACT FROM AUTHOR]

The purpose of this study was to identify and compare energy requirements specific to Special Operations Forces in field training, in both cool and hot environments. Three separate training sessions were evaluated, 2 in a hot environment ( n = 21) and 1 in a cool environment ( n = 8). Total energy expenditure was calculated using doubly labeled water. Dietary intake was assessed via self-report at the end of each training mission day, and macronutrient intakes were calculated. Across the 3 missions, mean energy expenditure (4618 ± 1350 kcal/day) exceeded mean energy intake (2429 ± 838 kcal/day) by an average of 2200 kcal/day. Macronutrient intakes (carbohydrates (g/(kg·day body weight (bw))−1) = 3.2 ± 1.2; protein (g/(kg·day bw)−1) = 1.3 ± 0.7; fat (g/(kg·day bw)−1) = 1.2 ± 0.7) showed inadequate carbohydrate and possibly protein intake across the study period, compared with common recommendations. Total energy expenditures were found to be similar between hot (4664 ± 1399 kcal/day) and cool (4549 ± 1221 kcal/day) environments. However, energy intake was found to be higher in the cool (3001 ± 900 kcal/day) compared with hot (2200 ± 711 kcal/day) environments. Based on the identified energy deficit, high variation in energy expenditures, and poor macronutrient intake, a greater attention to feeding practices during similar training scenarios for Special Operations Forces is needed to help maintain performance and health. The differences in environmental heat stress between the 2 climates/environments had no observed effect on energy expenditures, but may have influenced intakes. [ABSTRACT FROM AUTHOR]

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to ( i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and ( ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity. [ABSTRACT FROM AUTHOR]

The Husab Sand Lizard ( Pedioplanis husabensis Berger-Dell'Mour and Mayer, 1989) is a recently described lacertid lizard endemic to a small region in the central Namib Desert. Although this species is of conservation concern, very little is known about how this lizard functions in its environment. We used the doubly labeled water method to measure the field energetics in this lizard species and we report on its foraging behavior. Pedioplanis husabensis had summer field metabolic rates (330 ± 140 J·d−1) that were similar to those of other similarly sized sit-and-wait foraging lizards (360 J·d−1), but only 43% that of an active foraging lizard of the same mass (770 J·d−1), despite using a movement-intensive, active foraging strategy. Additionally, the mean water influx rate (0.06 ± 0.03 mL·d−1) was 67% that of a desert reptile of the same size (0.09 mL·d−1). Active body temperatures were significantly lower in summer (34.3 ± 1.7 °C) than they were in autumn (36.8 ± 1.6 °C), and daily activity of lizards increased from 2.6 ± 0.9 h·d−1 in summer to 4.3 ± 1.9 h·d−1 in autumn. Relative to other species of actively foraging desert lizards, P. husabensis has lower energy requirements. [ABSTRACT FROM AUTHOR]

Small Unit Tactics (SUT) is a 64-day phase of the Special Forces Qualification Course designed to simulate real-world combat operations. Assessing the metabolic and physiological responses of such intense training allows greater insights into nutritional requirements of soldiers during combat. The purpose of this study was to examine energy balance around specific training events, as well as changes in body mass and composition. Data were collected from 4 groups of soldiers ( n = 36) across 10-day periods. Participants were 28 ± 5 years old, 177 ± 6 cm tall, and weighed 83 ± 7 kg. Doubly labeled water (D218O) was used to assess energy expenditure. Energy intake was calculated by subtracting energy in uneaten foods from known energy in distributed foods in individually packaged combat rations or in the dining facility. Body composition was estimated from skinfold thickness measurements on days 0 and 64 of the course. Simulated urban combat elicited that largest energy deficit (11.3 ± 2.3 MJ·day−1 (2700 ± 550 kcal·day−1); p < 0.05), and reduction in body mass (3.3 ± 1.9 kg; p < 0.05), during SUT, while energy balance was maintained during weapons familiarization training and platoon size raids. Over the entire course body mass decreased by 4.2 ± 3.7 kg ( p < 0.01), with fat mass decreasing by 2.8 ± 2.0 kg ( p < 0.01) and fat-free mass decreasing by 1.4 ± 2.8 kg ( p < 0.05). The overall reduction in body mass suggests that soldiers were in a negative energy balance during SUT, with high energy deficit being observed during strenuous field training. [ABSTRACT FROM AUTHOR]

Exenatide is a medication similar in structure and effect to native glucagon-like peptide-1, an incretin hormone with glucose-lowering properties. The aim of the study was to measure the change in total energy expenditure (TEE) and body composition during exenatide administration and by deduction the relative contributions of energy expenditure and energy intake to exenatide-induced weight loss. Forty-five obese (body mass index, 30-40 kg·m-2) subjects were identified. After exclusion criteria application, 28 subjects entered into the study and 18 subjects (12 female, 6 male) completed the study, which consisted of 6 visits over 14 weeks and injection of exenatide for an average of 84 ± 5 days. Respiratory gas analysis and doubly labeled water measurements were performed before initiation of exenatide and after approximately 3 months of exenatide administration. The average weight loss from the beginning of injection period to the end of the study in completed subjects was 2.0 ± 2.8 kg ( p = 0.01). Fat mass declined by 1.3 ± 1.8 kg ( p = 0.01) while the fat-free mass trended downward but was not significant (0.8 ± 2.2 kg, p = 0.14). There was no change in weight-adjusted TEE ( p = 0.20), resting metabolic rate ( p = 0.51), or physical activity energy expenditure ( p = 0.38) and no change in the unadjusted thermic effect of a meal ( p = 0.37). The significant weight loss because of exenatide administration was thus the result of decreasing energy intake. In obese nondiabetic subjects, exenatide administration did not increase TEE and by deduction the significant weight loss and loss of fat mass was due to decreased energy intake. [ABSTRACT FROM AUTHOR]

The purpose of this cross-sectional study was to examine the association between the metabolic syndrome (MetS) and physical activity energy expenditure (PAEE) in overweight and obese sedentary postmenopausal women. The study population consisted of 137 overweight and obese sedentary postmenopausal women (age, 57.7 ± 4.8 years; BMI, 32.4 ± 4.6 kg·m-2). Subjects had the MetS if 3 out of the following 5 criteria were met: visceral fat > 130 cm2, high-density lipoprotein (HDL) cholesterol < 1.29 mmol·L-1, fasting triglycerides >= 1.7 mmol·L-1, blood pressure >= 130/85 mmHg, and fasting glucose >=5.6 mmol·L-1. We measured (i) body composition (by dual-energy X-ray absorptiometry); (ii) visceral fat (by computed tomography); (iii) insulin sensitivity (using the hyperinsulinemic-euglycemic clamp); (iv) plasma lipids, fasting glucose, and insulin, as well as 2 h glucose during an oral glucose tolerance test; (v) resting blood pressure; (vi) peak oxygen consumption (VO2 peak); (vii) PAEE (using doubly labeled water); and (viii) lower-body muscle strength (using weight-training equipment). Forty-two women (30.7%) had the MetS in our cohort. Individuals without the MetS had significantly higher levels of PAEE (962 ± 296 vs. 837 ± 271 kcal·d-1; p < 0.05), VO2 peak (18.2 ± 3.0 vs. 16.7 ± 3.2 mL·min-1·kg-1; p < 0.05), and insulin sensitivity, as well as significantly lower levels of 2 h glucose and central lean body mass. No differences in total energy expenditure, resting metabolic rate, and muscle strength between groups were observed. Logistic regression analysis showed that 2 h glucose (odds ratio (OR): 1.50 (95% CI 1.17-1.92)), central lean body mass (OR: 1.17 (95% CI 1.05-1.31)), and PAEE (OR: 0.998 (95% CI 0.997-1.000)), but not VO2 peak and (or) muscle strength, were independent predictors of the MetS. Lower levels of PAEE and higher levels of 2 h glucose, as well as central lean body mass, are independent determinants of the MetS in our cohort of overweight and obese postmenopausal women. [ABSTRACT FROM AUTHOR]

Menopause transition is associated with detrimental changes in physical activity, body composition, and metabolic profile. Although physical activity energy expenditure (PAEE) is inversely associated with metabolic syndrome (MetS) in individuals at higher risk of cardiovascular disease, the association is unknown in low-risk individuals. The aim of the study was to investigate the association between PAEE and MetS (prevalence and severity) in inactive overweight or obese postmenopausal women with a low Framingham Risk Score (<10%). Cross-sectional data of 126 participants were divided into quartiles based on PAEE (Quartile (Q)1 = lowest PAEE) while fat-free mass (FFM) and fat mass were measured by dual-energy X-ray absorptiometry. MetS prevalence was significantly different between Q1 and Q4 (37.9% vs 13.3%, p = 0.03). After controlling for potential confounders, MetS severity was negatively associated with PAEE (B = -0.057, p < 0.01) and positively with FFM (B = 0.038, p < 0.001). Moderation analyses indicated that a greater FFM exacerbated the association between PAEE and MetS severity in Q1 and Q2 (PAEE × FFM; B = -0.004; p = 0.1). Our results suggest that displaying a low FRS and lower PAEE increase MetS prevalence and severity. In addition, greater FFM interacts with lower PAEE to worsens MetS severity, while higher PAEE lessened this effect. Novelty: Inactive individuals displaying higher daily PAEE also have a lower MetS prevalence. Greater FFM is associated with a worse MetS severity where a higher PAEE mitigated this deleterious effect in our cohort.