The prevalence of obesity continues to increase despite considerable research and innovation regarding treatment and management strategies. When completed as prescribed, exercise training is associated with numerous health benefits and predictable levels of weight loss. However, under free-living conditions the benefits of exercise are less consistent, suggesting that non-adherence and/or a compensatory response in non-exercise activity thermogenesis (NEAT) may be occurring. The accurate quantification of all components of total energy expenditure (TEE), including TEE itself, was imperative to elucidate the primary research question relating to the impact of exercise on TEE. In addition, the measurement of changes in body composition and the response to prescribed exercise were assessed in methodological and pilot investigations. Following this extensive background, the primary research question relating to the effect of exercise on levels of TEE and the associated implications of such a compensatory response could be more rigorously investigated. The first study investigated the variability in isotopic equilibrium time under field conditions, and the impact of this variability on estimates of total body water (TBW) and body composition when using the deuterium dilution technique. Following the collection of a fasting baseline urine sample, 10 women and 10 men were dosed with deuterium oxide (0.05g/kg body weight). Urine samples were collected every hour for 8 hours. The samples were analysed using isotope ratio mass spectrometry and time to equilibration was determined using three commonly employed data analysis approaches. Isotopic equilibrium was reached by 50, 80 and 100% of participants at 4, 6 and 8 h, respectively. The mean group equilibration times determined using the three different plateau determination methods were 4.8 ± 1.5, 3.8 ± 0.8, and 4.9 ±1.4 h, respectively. Isotopic enrichment, TBW, and percent body fat estimates differed between early sampling times (3-5 h), but not later sampling times (5-8 h). Therefore, sampling < 6 hours post dose compared to sampling ≥ 6 hours resulted in greater relative measurement error in TBW and body composition estimates. Although differences in equilibration time were apparent between the three plateau determination approaches, sampling at 6 hours or later may decrease the likelihood of error in body composition estimates resultant from incomplete isotopic equilibration in a small proportion of individuals. In the second study, the aim was to measure the self-paced walking (SPW) speed of adults ranging in body size from normal to obese. The utility of heart rate monitors to estimate the energy cost of walking was also investigated. Twenty-nine participants (12 normal-weight, 17 overweight or obese) completed two outdoor walking tests to determine their SPW speed. A walking treadmill test with stages below, at, and above the SPW speed was completed to compare the energy expenditure estimates of the Polar S610 and WM42 heart rate monitors with that from indirect calorimetry. The average SPW speed was 1.7 ± 0.1 m*sec-1, which was equivalent to an exercise intensity of 48.6 ± 9.4 %VO2max (61.0 ± 7.1 %HRmax). There was no difference in the energy expenditure estimation between indirect calorimetry (4.7 ± 0.7 kcal*kg*-1*h-1), the S610 (4.8 ± 1.3 kcal*kg*-1*h-1) and the WM42 (4.8 ± 1.6 kcal*kg*-1*h-1). It was concluded that the heart rate monitors provided reasonable energy expenditure estimates at the group level. However considerable error was evident at the individual level, explained in part by exercise heart rate and fitness level, suggesting that an individualised calibration should be performed where possible. An additional finding from this study was that 145 to 215 minutes of SPW per week, dependent upon the level of adiposity, is required to meet the current American College of Sports Medicine (ACSM) guidelines for health of 1000 kcal*wk-1. The purpose of the third study was to establish the level of adherence to a specific exercise prescription (1500 kcal*wk-1) by objectively quantifying unsupervised exercise energy expenditure (ExEE) in a group of obese women. The 16-wk lifestyle intervention consisted of weekly meetings with research staff, combined with promotion of increased ExEE (1500 kcal*wk-1) and a decreased dietary intake (-500 kcal*d-1). Twenty-nine obese females (Body Mass Index = 36.8 ± 5.0 kg*m2, Body Fat = 49.6 ± 3.7 %) from a hospital-based lifestyle intervention were included in the analysis. ExEE was estimated and monitored weekly using heart rate monitoring. Body composition was measured before and after the intervention by dual-energy x-ray absorptiometry (DXA). Results indicated free-living adherence to the exercise prescription was modest and variable, with 14% of participants achieving the 1500 kcal*wk-1. The average weekly ExEE (768 kcal*wk-1) represented 51.2% of the total amount prescribed. ExEE was correlated with changes in body weight (r = 0.65, p < 0.001) and fat mass (r = 0.65, p = 0.0002). Achievement of a 5% weight loss target was dependent on an ExEE level of 1000 kcal*wk-1 (p &lt0.001). Exercise 'adherers' (> 000 kcal*wk-1) lost more weight (-9.9 vs. -4.1 kg), more fat mass (-6.8 vs. -3.0 kg), and more waist circumference (-9.8 vs. -5.6 cm) when compared to 'non-adherers' (< 1000 kcal*wk-1). The results suggest that the extent of supervision and monitoring influenced exercise adherence rates. The variability in adherence highlights the importance of objective monitoring of ExEE. Identification of individuals not complying with program targets may enable intervention staff to provide additional support or make individualised adjustments to the exercise prescription. The fourth study investigated issues relating to the management and interpretation of accelerometry data when the device is to be used to monitor levels of daily physical activity. Given the high between-individual variability in accelerometry output for a given walking speed, the use of a more individualised approach to the data management has been suggested. In addition, accelerometry was used to compare daily physical activity patterns between a supervised and unsupervised exercise prescription of the same dose (1500 kcal*wk-1) in overweight and obese women. Total energy expenditure, activity energy expenditure, and vector magnitude increased significantly during the intervention. Time spent in very low intensity movement decreased from baseline to the intervention (p < 0.01) in both the supervised (-18.6 min*d-1) and unsupervised (-68.5 min*d-1) group, whereas time spent in high and vigorous intensity movement increased significantly from baseline to the intervention (p < 0.05 and p < 0.0001, respectively). The increase in vigorous movement was significantly greater in the supervised group when compared to the unsupervised group (+11.5 vs. +5.4 min*d-1, p < 0.05). Time spent above three different moderate-intensity walking thresholds increased from baseline to the intervention (p < 0.0001). The threshold determination approach significantly affected the resultant outcomes (p < 0.0001) such that the standard threshold was significantly different to both group-specific and individualised approaches. Significant differences were also noted in accelerometer output between treadmill and overground walking (p < 0.0001). A positive finding of this study was that two different interventions aimed at increasing physical activity levels in a group of sedentary and obese women were successful in gaining modest increases in overall daily movement. The change observed appears to be a replacement of sedentary movement with more vigorous physical activity. Collectively, the differences observed between threshold determination approaches, as well as between treadmill and overground walking, highlight the need for standardised approaches to accelerometry data management and analysis. In addition, the findings suggest that obese women may benefit from a certain degree of exercise supervision to ensure compliance, however, strategies to encourage these women to continue with the exercise on their own without supervision are essential to making a sustainable long-term change to their lifestyles. The final study aimed to assess whether obese women compensate for structured exercise by decreasing their NEAT and thereby impeding weight loss. Thirteen participants were prescribed 1500 kcal*wk-1 of exercise through a structured walking program (4 week supervised followed by 4 weeks unsupervised). The energy expenditure of the walks was quantified using individually-calibrated Polar F4 heart rate monitors. The DLW technique was used to measure TEE. Accelerometry measures were also collected throughout and represented an alternative method of quantifying changes in total daily movement patterns resultant from an increase in energy expenditure through exercise. Compliance with the exercise program was excellent, with the average compliance being 94% over the 8-week intervention. The adoption of moderate-intensity exercise in this group of obese women resulted in a 12% decrease in TEE (p = 0.01) and a 67% decrease in NEAT (p < 0.05). No significant change was observed in resting metabolic rate from baseline to the postintervention time-point. Compensation was significantly correlated with dietary report bias (r= -0.84, p = 0.001), body image (r = 0.75, p < 0.01), and bodily pain (r = -0.65, p < 0.05). A linear regression model including dietary reporting bias and the pain score explained 78% of the variation in ΔTEE. Compensators were therefore less likely to underreport their dietary intake, less likely to be self-aware of their obese state, and more likely to be experiencing pain in their daily life. Self-reported dietary intake decreased significantly during the intervention (p = 0.01) with specific decreases noted in fat and carbohydrate intake. The consequence of compensation was evidenced by a lack of significant change in body weight, body composition, or blood lipids (p > 0.05). However, positive outcomes of the study included improvement in the SF-36 scores of general health (p < 0.05) and maintenance of exercise program adherence into the unsupervised phase of the intervention. Qualitative data collected via interview indicated that 85% of participants experienced increased energy and positive feedback from peers during the intervention. This study confirms that exercise prescription needs to be prescribed with an individualised approach that takes into account level of adiposity. The goal of exercise prescription for the obese should therefore be to determine the intensity and modality of exercise that does not activate compensatory behaviours, as this may in turn negate the beneficial effects of the additional energy expenditure of exercise. This study confirms that during the initial phase of an exercise-based weight loss intervention, the majority of obese women compensated for some, if not all, the energy cost of the exercise sessions by reducing NEAT. Whether this compensatory behaviour continues beyond the first month of an exercise program, particularly after training adaptations in cardiorespiratory fitness are realised, cannot be discerned from the current study. However these results do provide a rationale for why the magnitude of weight loss achieved is often less than predicted during exercise interventions. Further research is required to examine the temporal pattern of compensation in NEAT, and the relationship between the time courses of NEAT compensation relative to physical fitness improvements. The results from this thesis support the use of activity monitors such as accelerometers during weight loss interventions to track NEAT and provide objective feedback regarding compensatory behaviours to clinicians and the obese individuals.

There is an increase in the prevalence of obesity among people with schizophrenia thought to be due in part to the weight enhancing side-effects of medications commonly used to treat the symptoms of schizophrenia. Despite the deleterious health effects associated with obesity and its impact on quality of life and medication compliance, little is known about body composition and energy expenditure in this clinical group. The primary purpose of this thesis was to enhance understanding of body composition and energy expenditure, particularly resting energy expenditure in men with schizophrenia who take atypical antipsychotic medications. Unique to this investigation is the evaluation of clinical tools used to predict body composition and energy expenditure against reference methodologies in men with schizophrenia. Further, given the known links between obesity and physical activity, an additional but less comprehensive component of the thesis was a consideration of total and activity energy expenditure in addition to the interaction between psychiatric symptoms, side-effects of antipsychotic medications and physical activity also occurred as part of this thesis. Collectively, the goals of this thesis were addressed through a series of studies – the first two studies were related to the measurement and characteristics of body composition in men with schizophrenia, while the third and fourth studies were related to the measurement and characteristics of resting energy expenditure in men with schizophrenia. The fifth and sixth studies the utilised doubly labelled water technique to quantify activity and total energy expenditure in a small group of men with schizophrenia and explored the use of accelerometry in this cohort. The final study briefly considered the impact of psychiatric symptoms and self-reported medication side-effects on objectively measured physical activity. In the first study, thirty-one male adults previously diagnosed with schizophrenia and sixteen healthy male controls were recruited. Estimates of body composition derived from an anthropometry-based equation and from bioelectric impedance analysis (BIA) using deuterium dilution as the reference methodology to determine total body water were compared. The study also determined the validity of equations commonly used to predict body composition from BIA in the men with schizophrenia. A further aim was to determine the superiority of either BIA or body mass index (BMI) as an indicator of obesity in this cohort. The inclusion of the control group, closely matched for age, body size and body composition demonstrated that there was no difference in the ability of body composition prediction methods to distinguish between fat and fat-free mass (FFM) in controls and men with schizophrenia when both groups had similar body composition. However this study indicated that an anthropometry-based equation previously used in people with schizophrenia was a poor predictor of body composition in this cohort, as evidenced by wide limits of agreement (25%) and systematic variation of the bias. In comparison, the best predictor of percentage body fat (%BF) in this group was gained when impedance values were used to predict percentage body fat via the equation published by Lukaski et al (1986). Although percentage body fat was underpredicted using the Lukaski et al. (1986) equation, the mean magnitude was relatively small (1.3%), with the limits of agreement approximately 13%. Linear regression analysis revealed that %BF predicted using the Lukaski et al. (1986) equation explained 25% more of the variance in percentage body fat than BMI. Further, this study also indicated that BIA was more sensitive than BMI in distinguishing between overweight and obesity in this cohort of men with schizophrenia. Because of the almost exclusive use of BMI as an indicator of obesity in people with schizophrenia, the level of excess body fat may be in excess of that previously indicated. The second study extended the examination of body composition in men with schizophrenia. In this study, the thirty-one participants with schizophrenia (age, 34.2 ± 5.7 years; BMI, 30.2 ± 5.7 kg/m2) were individually matched with sedentary controls by age, weight and BMI. Deuterium dilution was used to distinguish between FFM and fat mass. The previous study had indicated that while BIA was a suitable group measure for obesity, on an individual level the technique lacked the precision required for investigating body composition in men with schizophrenia. Waist circumference was used as an indicator of body fat distribution. The findings of this study indicated that in comparison with healthy sedentary controls of similar body size and age, men with schizophrenia had higher levels of body fat which was more centrally distributed. Percentage body fat was on average 4% higher and waist circumference, on average 5 cm greater in men with schizophrenia than the sedentary controls of the same age and BMI. Further, this study indicates that the use of BMI to predict body fat in men with schizophrenia will result in greater bias than when it is used to predict body fat in other sedentary men. Commonly used regression equations to predict energy requirements at rest are based on the relationships between weight and resting energy expenditure (REE) and in such equations, weight acts as a surrogate measure of FFM. The objectives of study three were to measure REE in a small group of men with schizophrenia who were taking the antipsychotic medication clozapine and to determine whether REE can be predicted with sufficient accuracy to substitute for the measurement of REE in the clinical and/or research settings. Body composition was determined using deuterium dilution and REE was measured using a Deltatrac Metabolic Cart via a ventilated hood. The male participants, (aged 28.0 ± 6.7 yrs, BMI 29.8 ± 6.8 kg/m2) were weight stable at the time of the study and had been taking clozapine for 20.5 ± 12.8 months, with doses of 450 ± 140 mg/day. Of the six prediction equations evaluated, the equation of Mifflin et al. (1990) with no systematic bias, the lowest bias and the lowest limits of agreement proved to be the most suitable equation to predict REE in this cohort. The overestimation of REE can be corrected for by deducting 160 kcal/day from the predicted REE value when using the Mifflin et al. (1990) equations. However, the magnitude of the error associated with the prediction of REE for an individual is 370 kcal/day. The findings of this study indicate that REE cannot be predicted with sufficient individual accuracy in men with schizophrenia, therefore it was necessary to measure rather than predict REE in subsequent studies. In the fourth study, indirect calorimetry (Deltatrac Metabolic Cart via ventilated hood) and deuterium dilution were used to accurately determine REE, respiratory quotient (RQ) and FFM in 31 men with schizophrenia and healthy sedentary controls individually matched for age and BMI. Data from this study indicated that gross REE was lower in men with schizophrenia than in healthy sedentary controls of a similar age and body size. However, there was no difference between the groups in REE when REE was adjusted for FFM using the mathematically correct method (analysis of covariance with FFM as the covariate). There was however a statistically and clinically significant difference in resting, fasted RQ between men with schizophrenia and controls, suggesting that RQ rather than REE may be an important correlate worthy of further investigation in men with schizophrenia who take antipsychotic medications. Studies five and six involved the application of the doubly labelled water (DLW) technique to accurately determine total energy expenditure (TEE) and activity energy expenditure (AEE) in a small group of men with schizophrenia who had been taking the atypical antipsychotic medication clozapine. The participants were those who took part in study three. The purpose of these studies was to assess the validity of a commercially available tri-axial accelerometer (RT3) for predicting free-living AEE and to investigate TEE and AEE in men with schizophrenia. There was poor agreement between AEE measured using DLW and AEE predicted using the RT3. However, using the RT3 to measure inactivity explained over two-thirds of the variance in AEE. This study found that the relationship between current AEE per kilogram of body weight and change from baseline weight in men taking clozapine was strong although not significant. The sedentary nature of the group of participants in this study was reflected in physical activity levels, (PAL, 1.39 ± 0.27), AEE (435 ±352 kcal/day) and TEE (2511 ± 606 kcal/day) that fell well short of values recommended by WHO (2000) for optimal health and to prevent weight gain. Given the increasing recognition of the importance of sedentary behaviour to weight gain in the general community, further examination of the unique contributing factors such as medication side effects and symptoms of mental illness to activity levels in this clinical group is warranted. The final study used accelerometry (RT3) to objectively measure activity in a group of 31 men with schizophrenia who had been taking atypical antipsychotic medications for more than four months. The purpose of this study was to explore the relationships between psychiatric symptomatology, side-effects of medication and physical activity. Accelerometry output was analysed to provide a measure of inactivity and moderate intensity activity (MIA). The well-validated and reliable standardised clinical interview, the Positive and Negative Syndrome Scale (PANSS) was used as a measure of psychiatric symptoms. Perceived side-effects of medication were assessed using the Liverpool University Neuroleptic Rating Side-Effects Scale (LUNSER). Surprisingly, there was no relationship reported between any measures of negative symptoms and physical inactivity. However, self-reported measures of medication side-effects relating to fatigue, sleepiness during the day and extrapyramidal symptoms explained 40% of the variance in inactivity. This study found significant relationships between some negative symptoms and moderate intensity activity. Despite the expectation that as symptoms of mental illness reduce, inactivity may diminish and moderate intensity activity will increase, it may not be surprising that in practice this is an overly simplistic view. It may be that measures of social functioning and possibly therefore cognition may be better predictors of physical activity than psychiatric symptomatology per se.