The aim of this thesis was to describe the relationships between energy expenditure and body composition in healthy adults and children and in patients with metabolic disorders. In a healthy population resting energy expenditure (REE) is highly influenced by body composition, specifically lean mass (LM). Prediction equations can therefore accurately predict REE from body composition in healthy individuals. However, application of these equations to clinical patients, in whom metabolism is disordered, risks miscalculation of energy metabolism due to their dissociation between body composition and energy expenditure. Therefore new prediction equations were derived based on precise body composition measurements in healthy adults and children. Then, in patients with metabolic disorders, differences between their measured and equation-predicted REE and LM were presented as standardised Z scores. REE in healthy adults was predicted by the coefficients: age, fat mass and fat-free mass. LM in healthy adults was predicted by the coefficients: bone mineral content and height2 in men; and by fat and height2 in women. In healthy children, REE was predicted using gender specific models: by fat and LM in boys; and by solely LM in girls. REE and LM were then measured in adult and paediatric patients with metabolic disorders (Lipodystrophy, Thyrotoxicosis and Resistance to Thyroid Hormone β or α), and Z scores were calculated to highlight their deviations from the healthy populations. In adults, thyrotoxicosis patients displayed the highest REE Z scores (5.8), followed by lipodystrophy (2.9) and RTHβ cases (1.8), with RTHα demonstrating the lowest REE Z scores (-2.3). For LM, lipodystrophy patients exhibited with the highest Z scores (4.2), followed by RTHα patients (2.1), with RTHβ patients showing normal LM Z scores (-0.2) and thyrotoxicosis patients presenting with the lowest LM Z scores (-1.2). In the paediatric patients, RTHβ patients demonstrated REE Z scores similar to healthy controls (males; -0.15, females; 0.15), but RTHα patients displayed lower REE Z scores (male; -0.82, female; -2.2) compared to RTHβ patients and healthy controls. These studies highlight the disassociation between REE and body composition in patients with metabolic disorders. The application of a prediction equation for REE to calculate Z scores between measured and predicted values allows quantification of the differences between patients with metabolic disorders and healthy populations, and is a new and important concept.

The aim of this study was to determine and evaluate resting energy expenditure (REE) and the utilization of nutritional substrates in 14 polytrauma patients in the ICU. Was also assessed level of impact Overhydration (OH) on the accuracy of the determination. Diagnostic investigations using indirect calorimetry (IC) was performed in 9 men and 5 women (age 30 ± 15 years, BMI 27.5 ± 9.4 kg·m-2) with polytrauma (ISS 41 ± 16). For more accurate sizing of REE and extent of utilization of nutritional substrates were used equations derived from the equation of Weir, not Softwear calorimeter. Using IC volumes were determined only inspired an expired oxygen and carbon dioxide. To determine the rate of OH was used bioimpedance analysis methods using BCM. Almost 86% (8 men and 4 women) examined patients showed hypermetabolism. Average REE value was 2241.38 ± 854.27 kcal·day-1, which represented an average increase of prediction of 38.09 ± 49.09% due to the physiological condition. A statistically significant relationship was demonstrated between REE determined using the Weir equation according and the Harris-Bennedict equation without (P = 0,01) with deduction of OH (P = 0,007) only in men. In clinical practice, significant correlations were established between the REE-IC and BSA (P < 0,01), LTM (P < 0,05),...

The aim of this thesis was to evaluate changes in resting energy expenditure (REE) in ten lactating women between three weeks and nine months postpartum to find out whether there is any link with the parameters presented in this study. Measurements were taken at four intervals. At three weeks and at three, six and nine months postpartum. They were taken in the morning after a night fast (12 hours) and used indirect calorimetry with a canopy in awake lying subjects for approximately 25 minutes. The room was shaded with minimal noise with a temperature around 20 řC. Urine was collected over 24 hours and was examined for nitrogen concentration. The median REE was 1591,86 kcal/day at 3 weeks postpartum, 1398,08 kcal/day at 3 months, 1401,78 kcal/day at 6 months and 1455,03 kcal/day at 9 months postpartum. Values of REE per kilogram of body weight are 21,8 ± 0,36 kcal/kg and are consistent throughout the measurement period. The oxidation of lipids was dominant compared to other substrates and the lowest was oxidation of sacharides during the whole observation period. Correlations were found in parameters such as, body weight and REE per kilogram, breast milk and respiratory quotient (RQ), length of gravidity with RQ/ volume of exhaled carboxydioxide/ volume of inhaled oxygen. Another was between protein...

Background The aim of diploma thesis was to evaluate resting energy expenditure (REE) and substrate oxidation in Czech lactating women and their relation to measured anthropometric parameters. Methods The indirect calorimetry was used to asses REE. Subsequently, the oxidation of substrates was calculated. At the same time were measured anthropometric parameters of breastfeeding women. Then the correlation was investigated. The total amount of examination were three times. First was in the time three weeks after birth, the second one was three months postpartum and the last was six months after birth. Results The mean values of REE in lactating women were 1577±93 kcal/day in the time of three weeks after birth. Three months after birth it was 1622±140 kcal/day. Six months after birth it was 1545±80 kcal/day. Significant positive correlation was proved between REE and triceps skinfold thickness (r = 0,98; P < 0,05) and also chest circumference (r = 0,99; P < 0,05). Both were three weeks after birth. Breastfeeding women had a value of lipid oxidation 60 % of substrate oxidation three weeks postpartum, which decreased to 46 % three months postpartum due to sharp increase (from 8 % to 18 %) of carbohydrate oxidation value. This increase could correspond to the preferential use of glucose by the mammary...

The accurate measurement of total energy expenditure is a cornerstone of metabolic research. However, there is a lack of measurement methods that are valid, objective, inexpensive, and easy to use. Accelerometry, along with validated prediction equations for resting energy requirements, may provide an opportunity to fill this void. Twenty weight stable adults (12 female, 8 male) who recently participated in a controlled feeding study comprised the study sample. Total energy requirements were assessed from the controlled feeding period in which weight stability was achieved using the intake-balance method. Resting energy expenditure was assessed using the Mifflin-St. Jeor equation. Participants wore accelerometers to objectively assess habitual physical activity. The accelerometer data obtained along with subjects' demographic and biometric data were used to predict non-resting energy expenditure (NREE) using step-wise linear regression in JMP. Bland-Altman plots and Spearman's Rho correlations were used to determine the validity of the total energy requirements obtained from the sum of the predicted non-resting energy expenditure. Estimated resting energy expenditure was compared with the total energy requirements assessed using the intake-balance method from the controlled feeding period. The resulting prediction equation is as follows: 480.93 – 180.69(sex) + 0.21(Accelerometer kcals) + 617.98(BF%) = AEE. The sex was coded as 1 for females and 0 for males. This prediction model has a coefficient of determination of 0.74 (0.70 adjusted). On average, the model overestimates AEE by 76 kcals. This new model could be the key to accurately, inexpensively and objectively measuring total energy requirements. / Master of Science / Accurate measurement of the total amount of energy (i.e. calories) utilized by the body throughout the day, also known as total energy expenditure, is a vital component of metabolic research. However, there is a lack of measurement methods that are valid, objective, inexpensive, and easy to use. Accelerometers combined with equations designed to predict total energy expenditure may be able to fill this gap. Accelerometers are devices worn on the body that measure accelerative forces from physical activity. Twenty weight stable adults (12 female, 8 male), who recently participated in a study in which all dietary intake and exercise were closely monitored (controlled feeding study), comprised the study sample. The amount of energy needed to maintain weight (total energy requirements) was assessed from the controlled feeding period in which weight stability was achieved. Resting energy expenditure, the energy burned while the body is at rest, was assessed using an equation often used to estimate energy expenditure, the Mifflin-St. Jeor equation. Participants wore accelerometers to objectively assess habitual physical activity. The accelerometer data obtained along with subjects’ demographic (age, sex) and biometric (height, weight, BMI, etc.) data were used to predict non-resting energy expenditure (resting energy expenditure subtracted from total energy expenditure). Multiple statistical tests were used to determine the validity of the total energy requirements obtained from the sum of the predicted non-resting energy expenditure (NREE) and resting energy expenditure. Estimated resting energy expenditure was compared with the total energy requirements assessed using the intake-balance method from the controlled feeding period. The resulting prediction equation is as follows: 480.93 – 180.69(sex) + 0.21(Accelerometer kcals) + 617.98(BF%) = NREE. The sex was coded as 1 for females and 0 for males. This prediction model has a coefficient of determination of 0.74 (0.70 adjusted), which means 70% of the variation in non-resting energy expenditure was explained by changes in the variables in the equation. On average, the model overestimates NREE by 76 Calories per day. This new model could be the key to accurately, inexpensively and objectively measuring total energy requirements.

A lower resting energy expenditure (REE) has been suggested to partially explain the disproportionate prevalence of overweight/obesity among black African women, yet no studies have investigated the REE of South African (SA) children. Similarly, physical activity (PA) as a modifiable factor related to childhood energy expenditure is under-researched in the local context. The study determined the relationship between sex and population group (determinant factors), on the one hand, and REE and PA (outcomes) of 6–9-year-old SA children attending two primary schools in the City of Tshwane metropolitan area, on the other, taking phenotypic characteristics as confounders (mediating factors) and the study context into account. In a cross-sectional study with quota sampling, the REE of 6–9-year-old children attending two urban schools in SA was measured with indirect calorimetry (IC), and PA with a pedometer. Multifrequency bioelectrical impedance analysis was used to assess body composition (BC) (fat-free mass [FFM], FFM index, fat mass [FM] and FM index). Multivariate regression was used to calculate REE and PA adjusted for phenotypic confounders (z-scores of weight-for-age, height-for-age and body mass index-for-age, and BC). Sex and population differences in REE and PA (measured and adjusted) were determined with two-way ANOVA. Ninety-four healthy children (59.6% girls; 52.1% black African) with similar socio-economic status and access to PA participated in the study. Despite variations in BC, sex differences in REE were not significant (41 kcal/day ≈ 172 kJ/day; P = 0.375). The REE in black African participants was significantly lower than in their white counterparts (146 kcal/day ≈ 613 kJ/day; P = 0.002). When adjusting for BC, population differences in REE declined, especially after adjustment for FFM (91 kcal/day ≈ 382 kJ/day; P = 0.039), but remained clinically significant. Average steps/day in girls (10212 [9519;10906]) was lower than in boys (11433 [10588;12277]) (P = 0.029), and lower in black African (9280 [8538;10022]) than in white (12258 [11483;13033]) (P < 0.001) participants. No significant relationship (r = 0.05; P = 0.651) was observed between REE and PA. Within the context of a similar SES and PA environment, the REE and PA of black African children was lower than white. Differences in REE between sexes were not significant, but girls had a lower PA than boys. / Thesis (PhD (Dietetics))--University of Pretoria, 2020. / South African Sugar Association project No. 260 / Human Nutrition / PhD (Dietetics) / Unrestricted

Objectives: Most weight loss medications target reductions in energy intake while neglecting energy expenditure, a critical predictor of weight loss/regain. This pilot study examined the effect of short-acting methylphenidate (MPH) on resting energy expenditure (REE), thermic effect of food (TEF), physical activity energy expenditure (PAEE), and how changes in energy expenditure relate to changes in body composition in youth and adults living with obesity. Methods: This study was a randomized, double-blind, placebo-controlled two-parallel arm study. In total, 19 participants were screened, of which 14 participants were randomized into the study, but complete data was only collected for 12, and only analyzed for 10 participants. Those 10 participants aged 28.8 ± 6.9 yrs. (5 Male, 5 Female) were randomized to receive either MPH (0.5 mg/kg) (n = 5) or placebo (n =5) twice daily for 60 days. Participants’ REE and TEF (indirect calorimetry), were measured at baseline (no drug/placebo), and day 60 post-treatment (drug/placebo). Participants’ PAEE (Actical) was measured between screening and baseline for a 1-week period (no drug/placebo), and on day 53 for a 1-week period (drug/placebo). Participants’ anthropometrics were measured using DEXA at baseline, and day 60 post-treatment. Results: From baseline to day 60, MPH showed a relative difference to placebo in relative REE (Relative REE: F(1, 8) = 4.235, p = 0.074, d = 0.83, 2 = 0.346) of 10%, evidenced by a 6% increase in relative REE kcal/kg (18.53 ± 1.97 Kcal/day/kg at baseline, 19.71 ± 2.52 Kcal/day/kg at final) for the MPH group, and a 4% decrease (19.08 2.36 Kcal/day/kg at baseline, 18.26 ± 2.04 Kcal/day/kg at final) in placebo, translating to moderate-effect size (Cohen’s d=0.63) favouring MPH. From baseline to day 60, there were no significant differences between groups on changes in TEF (TEF AUC: F(1, 8) = 0.079, p = 0.785, d = 0.15, 2 = 0.010) or any PAEE variables such as sedentary behavior (SB: F (1, 8) = 0.455, p = 0.52, d = 0.02, 2 = 0.054), light physical activity (LPA: F (1, 8) = 0.504, p = 0.50, d = 0.16, 2 = 0.059), moderate physical activity (MPA: F (1, 8) = 0.281, p = 0.61, d = 0.19, 2 = 0.034), moderate-to-vigorous physical activity (MVPA: F (1, 8) = 0.120, p = 0.74, d = 0.15, 2 = 0.015), or vigorous physical activity (VPA: F (1, 8) = 3.495, p = 0.098, d = 0.91, 2 = 0.304) . Mean change in body weight (kg) resulted in a weight loss of roughly -2.66 ± 2.00 kg in the MPH group and -1.64 ± 1.41 kg in the placebo group, differences that were not statistically significant. Mean change in both groups for body fat% of -0.33 ± 2.08 %, mean change in fat mass of -1.05 ± 2.59 kg, and finally a mean change in fat-free mass of -0.06 ± 1.19 kg was reported. Changes in relative REE were inversely correlated with changes in body weight (r = -0.599, p = 0.067), body fat (r = -0.524, p = 0.12) and fat mass (r = -0.599, p = 0.096). These associations were stronger in the MPH group. Conclusions: Our data suggests that MPH administration may lead to a meaningful increase in relative REE, and these suggested changes were associated with reductions in adiposity among individuals with obesity. These preliminary findings suggest that MPH should be further examined using a larger sample size and study duration to determine its effectiveness in promoting weight loss and maintenance of weight loss in individuals with obesity, a population at high risk of morbidity and premature mortality.

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The nutritional care and management of patients includes provision of adequate nutrition support to ensure that they attain and maintain a desirable body weight, improve nutritional status and avoid negative outcomes associated with over- or underfeeding. The success of nutrition support relies on accurately estimating energy requirements so that adequate energy and nutrients can be provided to the patient. Energy requirements are most accurately determined by measurement of energy expenditure. Most methods for doing so however are expensive, time-consuming, require trained technicians to perform them and are therefore impractical in the clinical setting. As such, prediction equations, which are easy to use, inexpensive and universally available, are commonly used to estimate the energy requirements of hospitalised patients. The accuracy of these equations however is questionable. Recently, a new portable hand-held indirect calorimeter (MedGem(tm), HealtheTech, USA), which has been promoted for its ease of use and relatively short measurement time, has been validated in healthy subjects but is yet to be validated in patients with illnesses. Weight loss and malnutrition occur commonly in patients with cancer and are often thought to be associated with disturbances in energy metabolism caused by the tumour. Minimising weight loss is an important goal for the nutritional care of patients with cancer. The ability to accurately determine the energy requirements of these patients is therefore essential for the provision of optimal nutrition support. This research project proceeded in two phases. Phase 1 aimed to determine current methods used by dietitians for estimating adult patients' energy requirements using a descriptive study. Results of this study informed phase 2, which aimed to investigate differences in energy expenditure of cancer patients compared to healthy control subjects and to compare different methods for determining energy requirements of people with cancer in the clinical setting. To address phase 1 a national cross-sectional survey of dietitians working in acute care adult hospitals was undertaken to determine their usual dietetic practice with respect to estimating patients' energy requirements. Responses to the survey (n=307, 66.2%) indicated a large variation in dietitians' practice for estimating energy requirements particularly with respect to the application of methods involving injury factors. When applied to a case study, these inconsistencies resulted in an extremely wide range for the calculated energy requirement, suggesting that there is error inherent in the use of prediction methods, which may be associated with negative consequences associated with under- or overfeeding. The types of patients for whom dietitians estimate energy requirements appears to be heavily influenced by feeding method. Initial dietetic education was identified as the main influencing factor in the choice of method for estimation of energy requirements. Phase 2 was addressed using four studies based on the same study population - a case-control study, two clinical validation studies and a measurement methods study. Patients had histologically proven solid tumours, excluding tumours of the breast, prostate and brain, and were undergoing anti-cancer therapy (n=18). Healthy control subjects were group matched to cancer patients by gender, age, height and weight from a purposive sample (n=17). Resting energy expenditure (REE) was measured by respiratory gas exchange using a traditional indirect calorimeter (VMax 229) and the MedGem indirect calorimeter. A measurement methods side-study established that steady state defined as a three-minute period compared to a five-minute period measured REE within clinically acceptable limits. REE was also predicted from a range of prediction equations. Analyses of available data found that REE in cancer patients was not significantly different from healthy subjects, with only a 10% higher REE observed in this sample of cancer patients when adjusted for fat free mass. For both cancer patients and healthy subjects the portable MedGem indirect calorimeter and all prediction equations did not measure or estimate individual REE within clinically acceptable limits compared to the VMax 229 (limits of agreement of approximately -40% to 30% for both the MedGem and prediction equations). Collectively, the results of this research project have indicated that current practical methods for determining patients' energy requirements in a clinical setting do not accurately predict the resting energy expenditure of individual subjects, healthy or with cancer. Greater emphasis should therefore be placed on ensuring intake meets requirements. For this to occur, dietetic practice should be focused on directly monitoring both patients' actual energy intake and patient outcomes, such as weight, body composition and nutritional status, to determine whether energy requirements are being met. This research has led to multiple recommendations for dietetic practice, focusing on the standardisation of education practices. Recommendations for future research address methodological improvements.

There is a high prevalence in malnutrition among traumatic brain injury (TBI) due to the hypermetabolism and hypercatabolism which develop post injury. Traumatic brain injury patients are different, even among themselves, in their energy requirements and response to nutritional therapy. This implies that there are other factors that affect the energy intake of these patients and enhance the incidence of malnutrition. This dissertation study examines the nutritional status of TBI patients upon admission to the intensive care unit (ICU) and during their hospital stay to describe baseline status, detect changes in nutritional status over 7 days, and identify the factors affecting the adequacy of energy intake and the change in nutritional status as a consequence. Anthropometric measurements, biomedical measurements, measures of severity of illness, daily health status, level of brain injury severity, and other data were collected from the medical records of 50 patients, who were ≥ 18 years old, mechanically ventilated in the first 24 hours of ICU admission, and had a Glasgow Coma Scale score between 3-12. These data were used to examine the previous relationships. Although there was no statistically significant change found in body mass index and weight, there was a significant change detected in other nutritional markers, including hemoglobin, albumin, and total lymphocyte levels over the 7 days of ICU and hospital stay. No significant relationship was found between the adequacy of energy intake and total prescribed energy, severity of illness, level of brain injury severity, daily health status, patient age, intracranial pressure, or time of feeding initiation. Findings may be used to develop and test interventions to improve nutritional status during the acute phase of TBI. This will lay a foundation for health care providers, including nurses, to establish standards for practice and nutrition protocols to assure optimal nutrition assessment and intervention in a timely manner.