An exercise-induced energy deficit may affect post-exercise energy intake, physical activity energy expenditure (PAEE) and energy balance hormones. Therefore, the objective of this thesis was to investigate the impact of a single bout of exercise either of moderate (40% O2max) or high (70% O2max) intensity on post-exercise energy intake, physical activity energy expenditure and energy balance hormones in both sedentary and active males. Physical activity energy expenditure increased between 38 and 62 hours following moderate intensity exercise in sedentary males (Chapters 3 and 4). This was due to increased light intensity energy expenditure (2.4-4.79 METs) such as standing and walking activities (Chapter 4). The Change in PAEE was not associated with circulating leptin and adiponectin concentrations. There was no impact of a single bout of exercise on post-exercise energy intake in sedentary males during a buffet meal (Chapter 4). Chapter 5 aimed to determine whether changes in PAEE, energy intake, and energy balance hormones were related to physical activity status. Interestingly, plasma acylated ghrelin concentration was suppressed while total peptide YY (PYY) concentration tended to be elevated after high intensity exercise in active males (Chapter 5). However, there was no impact of either moderate or high intensity exercise on PAEE and post-exercise energy intake in active males. The final study (Chapter 6) determined whether high intensity exercise in the fed state after a few days of food restriction had an impact on circulating energy balance hormones. Circulating postprandial total PYY and pancreatic polypeptide (PP) were increased for one hour after high intensity exercise in active men. There was no change in PAEE and post-exercise energy intake after exercise.

The female athlete triad (FAT or the TRIAD) is a complex syndrome arising from associations among the trio of energy availability (EA), menstrual function (MF) and bone mineral density (BMD) along their respective continuums from health to disease state. It has been recognized that women whose energy intake (EI) does not meet the energy requirements for physiological functions subsequent to participation in exercise and physical activity could have low EA. In the TRIAD, low EA, an initiator in menstrual dysfunction (MD) and concomitant hypoestrogenism, indirectly results in low BMD. Therefore, the purpose of this study was to: (i) establish the status of EA, MF and BMD among elite Kenyan female athletes and non-athletes, (ii) explore associations between EA and MF in elite Kenyan female athletes and non-athletes, (iii) determine the relationships of EA and MF to BMD in elite Kenyan female athletes and non-athletes, and (iv) to determine the profile of the female athlete triad in elite Kenyan distance athletes and in non-athletes. Measurements of EA, MF and BMD were undertaken in 39 female participants (Middle distance athletes =12, Long distance athletes=13, Non-athletes=14). Energy intake minus exercise energy expenditure (EEE) and the remnant normalized to fat free mass (FFM) determined EA. Energy availability was determined through weight of all food and liquid consumed over three consecutive days. Exercise energy expenditure was determined after isolating and deducting energy expended in exercise or physical activity above lifestyle level from the total energy expenditure output as measured by Actigraph GT3X+. Fat free mass and BMD were assessed using dual energy x-ray absorptiometry (DXA). A nine-month daily temperature-menstrual diary was used to evaluate menstrual status. In addition, since psychological eating behaviour practice (EBP) contributes to low EA, the Eating Disorder Examination Questionnaire (EDE-Q) was used to determine presence of such practice among the participants and their relationship to EA. Overall, EA below 45 kcal.kgFFM-1.d-1 was found in 61.53% of the participants (athletes=28.07±11.45kcal.kgFFM-1.d-1, non-athletes=56.97±21.38kcal.kgFMM-1.d-1). The ANOVA showed that there was a significant difference (p<0.001) in EA among the long and middle distance runners and non-athletes; and the Tukey‘s HSD revealed that the source of the difference were the non-athletes. Results of the EDE-Q showed almost negligible presence of psychopathological eating behaviour practice among the Kenyan participants. None of the TRIAD components showed significant relationship with EBP. Results of MF showed that whereas none of the athletes presented with amenorrhea, oligomenorrhea was present among 40% athletes and 14.3% non-athletes, and amenorrhea among 14.3% non-athletes. However, there was no significant difference between athletes and non-athletes in MF. Low BMD was seen in 76% of the athletes and among 86% of the non-athletes. The analysis did not show significant difference in BMD Z-scores between athletes and non-athletes. The analysis did not show any significant association between EA and MF among the participants. The only significant relation of EA to any BMD dimension measured was between EA and total BMD in the long distance runners (r=0.560; p=.046). Significant relationship (rho=0.497; p=.001) was found between MF and BMD Z-scores among the athletes with middle distance highlighting the relationship further (rho=0.632; p=.027). Overall, the binary logistic regression revealed that MF did not predict BMD (OR=4.07, 95% CI, 0.8-20.7, p=.091). Overall, 10% of the participants (athletes=4, long distance athletes =3, middle distance athletes=1, non-athletes=0) showed simultaneous presence of all three components of the TRIAD. The independent sample t-test showed a significant difference (t=5.860; p=<.001) in the prevalence of the TRIAD between athletes and non-athletes. / PhD (Human Movement Science), North-West University, Potchefstroom Campus, 2014

The female athlete triad (FAT or the TRIAD) is a complex syndrome arising from associations among the trio of energy availability (EA), menstrual function (MF) and bone mineral density (BMD) along their respective continuums from health to disease state. It has been recognized that women whose energy intake (EI) does not meet the energy requirements for physiological functions subsequent to participation in exercise and physical activity could have low EA. In the TRIAD, low EA, an initiator in menstrual dysfunction (MD) and concomitant hypoestrogenism, indirectly results in low BMD. Therefore, the purpose of this study was to: (i) establish the status of EA, MF and BMD among elite Kenyan female athletes and non-athletes, (ii) explore associations between EA and MF in elite Kenyan female athletes and non-athletes, (iii) determine the relationships of EA and MF to BMD in elite Kenyan female athletes and non-athletes, and (iv) to determine the profile of the female athlete triad in elite Kenyan distance athletes and in non-athletes. Measurements of EA, MF and BMD were undertaken in 39 female participants (Middle distance athletes =12, Long distance athletes=13, Non-athletes=14). Energy intake minus exercise energy expenditure (EEE) and the remnant normalized to fat free mass (FFM) determined EA. Energy availability was determined through weight of all food and liquid consumed over three consecutive days. Exercise energy expenditure was determined after isolating and deducting energy expended in exercise or physical activity above lifestyle level from the total energy expenditure output as measured by Actigraph GT3X+. Fat free mass and BMD were assessed using dual energy x-ray absorptiometry (DXA). A nine-month daily temperature-menstrual diary was used to evaluate menstrual status. In addition, since psychological eating behaviour practice (EBP) contributes to low EA, the Eating Disorder Examination Questionnaire (EDE-Q) was used to determine presence of such practice among the participants and their relationship to EA. Overall, EA below 45 kcal.kgFFM-1.d-1 was found in 61.53% of the participants (athletes=28.07±11.45kcal.kgFFM-1.d-1, non-athletes=56.97±21.38kcal.kgFMM-1.d-1). The ANOVA showed that there was a significant difference (p<0.001) in EA among the long and middle distance runners and non-athletes; and the Tukey‘s HSD revealed that the source of the difference were the non-athletes. Results of the EDE-Q showed almost negligible presence of psychopathological eating behaviour practice among the Kenyan participants. None of the TRIAD components showed significant relationship with EBP. Results of MF showed that whereas none of the athletes presented with amenorrhea, oligomenorrhea was present among 40% athletes and 14.3% non-athletes, and amenorrhea among 14.3% non-athletes. However, there was no significant difference between athletes and non-athletes in MF. Low BMD was seen in 76% of the athletes and among 86% of the non-athletes. The analysis did not show significant difference in BMD Z-scores between athletes and non-athletes. The analysis did not show any significant association between EA and MF among the participants. The only significant relation of EA to any BMD dimension measured was between EA and total BMD in the long distance runners (r=0.560; p=.046). Significant relationship (rho=0.497; p=.001) was found between MF and BMD Z-scores among the athletes with middle distance highlighting the relationship further (rho=0.632; p=.027). Overall, the binary logistic regression revealed that MF did not predict BMD (OR=4.07, 95% CI, 0.8-20.7, p=.091). Overall, 10% of the participants (athletes=4, long distance athletes =3, middle distance athletes=1, non-athletes=0) showed simultaneous presence of all three components of the TRIAD. The independent sample t-test showed a significant difference (t=5.860; p=<.001) in the prevalence of the TRIAD between athletes and non-athletes. / PhD (Human Movement Science), North-West University, Potchefstroom Campus, 2014

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.