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2 pp. / The energy content of food is measured in calories. The number of calories, or energy, an athlete needs to maintain weight depends upon: age, body weight, gender, Resting Energy Expenditure (REE) and physical Activity Energy Expenditure (AEE) levels.

Energy intake (EI) and energy expenditure (EE) across the menstrual cycle (MC), while considering body adiposity, have not been previously evaluated in the same individuals. This study mainly examined the variations in energy balance (EB) across MC. Seventeen women (Body fat-DXA:28.5%) participated in three identical sessions during distinct phases of the MC: Early-follicular, Late-follicular/ovulation and Mid-luteal (confirmed by basal temperature and sex-steroid hormones). EI, resting metabolic rate (RMR), physical-activity EE (PAEE), severity of PMS, leptin and relative-reinforcing value (RRV) of preferred foods were measured during each phase. No differences in body fat, EI, RMR, PAEE, leptin and RRV of food were noted across MC. Trends were noted in preferred snack (p=0.06) and combined snack/fruit (p=0.06) intakes, while differences were noted in severity of PMS (p<0.05) across phases. Changes in EB across the MC were not noted. PMS was more severe, and preferred snack and combined snack/fruit intakes were slightly higher during mid-luteal phase.

Energy intake (EI) and energy expenditure (EE) across the menstrual cycle (MC), while considering body adiposity, have not been previously evaluated in the same individuals. This study mainly examined the variations in energy balance (EB) across MC. Seventeen women (Body fat-DXA:28.5%) participated in three identical sessions during distinct phases of the MC: Early-follicular, Late-follicular/ovulation and Mid-luteal (confirmed by basal temperature and sex-steroid hormones). EI, resting metabolic rate (RMR), physical-activity EE (PAEE), severity of PMS, leptin and relative-reinforcing value (RRV) of preferred foods were measured during each phase. No differences in body fat, EI, RMR, PAEE, leptin and RRV of food were noted across MC. Trends were noted in preferred snack (p=0.06) and combined snack/fruit (p=0.06) intakes, while differences were noted in severity of PMS (p<0.05) across phases. Changes in EB across the MC were not noted. PMS was more severe, and preferred snack and combined snack/fruit intakes were slightly higher during mid-luteal phase.

Energy intake (EI) and energy expenditure (EE) across the menstrual cycle (MC), while considering body adiposity, have not been previously evaluated in the same individuals. This study mainly examined the variations in energy balance (EB) across MC. Seventeen women (Body fat-DXA:28.5%) participated in three identical sessions during distinct phases of the MC: Early-follicular, Late-follicular/ovulation and Mid-luteal (confirmed by basal temperature and sex-steroid hormones). EI, resting metabolic rate (RMR), physical-activity EE (PAEE), severity of PMS, leptin and relative-reinforcing value (RRV) of preferred foods were measured during each phase. No differences in body fat, EI, RMR, PAEE, leptin and RRV of food were noted across MC. Trends were noted in preferred snack (p=0.06) and combined snack/fruit (p=0.06) intakes, while differences were noted in severity of PMS (p<0.05) across phases. Changes in EB across the MC were not noted. PMS was more severe, and preferred snack and combined snack/fruit intakes were slightly higher during mid-luteal phase.

Energy intake (EI) and energy expenditure (EE) across the menstrual cycle (MC), while considering body adiposity, have not been previously evaluated in the same individuals. This study mainly examined the variations in energy balance (EB) across MC. Seventeen women (Body fat-DXA:28.5%) participated in three identical sessions during distinct phases of the MC: Early-follicular, Late-follicular/ovulation and Mid-luteal (confirmed by basal temperature and sex-steroid hormones). EI, resting metabolic rate (RMR), physical-activity EE (PAEE), severity of PMS, leptin and relative-reinforcing value (RRV) of preferred foods were measured during each phase. No differences in body fat, EI, RMR, PAEE, leptin and RRV of food were noted across MC. Trends were noted in preferred snack (p=0.06) and combined snack/fruit (p=0.06) intakes, while differences were noted in severity of PMS (p<0.05) across phases. Changes in EB across the MC were not noted. PMS was more severe, and preferred snack and combined snack/fruit intakes were slightly higher during mid-luteal phase.

Insufficient sleep may be associated with obesity via increased energy intake and/or decreased energy expenditure. The present study therefore aimed to investigate effects of sleep restriction on energy balance in healthy young adults. Participants (14 men, 13 women) aged 35.3 ± 1.0 y with 23.6 ± 0.2 kg/m2 BMI completed a randomized, crossover study exposed to short and habitual sleep with 4 wk washout. Controlled diets were provided during the first 4 d, followed by 2 d of ad libitum eating. Ad libitum energy intake, energy expenditure and physical activity level were determined as well as energy balance and body weight. Results showed that ad libitum energy intake (p = 0.031), as well as total fat (p = 0.018) increased after short compared with habitual sleep, but physical activity level, energy expenditure, energy balance, and body weight remained unaffected by sleep duration. In conclusion, sleep deprivation elevates energy intake, which may lead to positive energy balance over time and increase the risk of weight gain and/or obesity.

Insufficient sleep may be associated with obesity via increased energy intake and/or decreased energy expenditure. The present study therefore aimed to investigate effects of sleep restriction on energy balance in healthy young adults. Participants (14 men, 13 women) aged 35.3 ± 1.0 y with 23.6 ± 0.2 kg/m2 BMI completed a randomized, crossover study exposed to short and habitual sleep with 4 wk washout. Controlled diets were provided during the first 4 d, followed by 2 d of ad libitum eating. Ad libitum energy intake, energy expenditure and physical activity level were determined as well as energy balance and body weight. Results showed that ad libitum energy intake (p = 0.031), as well as total fat (p = 0.018) increased after short compared with habitual sleep, but physical activity level, energy expenditure, energy balance, and body weight remained unaffected by sleep duration. In conclusion, sleep deprivation elevates energy intake, which may lead to positive energy balance over time and increase the risk of weight gain and/or obesity.

Consistently, reports in the literature have identified that a sedentary lifestyle contributes to the progression of a range of chronic degenerative diseases. The measurement of energy expenditure and physical activity pattern in children is a challenge for all professionals interested in paediatric health and from a broader perspective, the public health fraternity charged with considering longer term health consequences of physical inactivity. The primary objective of this thesis was to identify a suitable indirect and objective measurement technique for the assessment of energy expenditure and physical activity pattern in children. The ideal characteristics of such a technique are that it should be reproducible and have been validated against a criterion reference method. To achieve this goal, a series of methodological studies were undertaken (Chapters II and III). This work was essential to increase accuracy during the individualised laboratory calibration process and further minimise prediction errors when analysing data from 7 days of monitoring under free-living conditions in the second part of the study (Chapters IV and V). In the first study to verify the combined effect of body position, apparatus and distraction on children's resting metabolic rate (RMR), experiments were carried out on 14 children aged 8-12 (mean age = 10.1 years ± 1.4). Each participant underwent 2 test sessions, one week apart under three different situations: a) using mouthpiece and nose-clip (MN) or facemask (FM); b) sitting (SEAT) or lying (LY) and c) TV viewing (TV) or no TV viewing. In the first session, following 20 min rest and watching TV, the following protocol was used: LY: 20 min - stabilisation; 10 min using MN and 10 min using FM. Body position was then changed to seated: 20 min stabilisation; 10 min using FM; 10 min using MN. In the second session, FM and MN order was changed and participants did not watch TV. Data were analysed according to the eight combinations among the three studied parameters. Repeated measures ANOVA indicated statistically significant differences for &VO2 (p=0.01) and RMR (p=0.02), with TVMNSEAT showing higher values than TVFMLY. Bland-Altman analysis showed a bias for &VO2, &VCO2, RQ and RMR between TVFMLY and TVMNSEAT of -17.8±14.5 ml.min-1, -8.8±14.5 ml. min-1, 0.03±0.05 and -115.2±101.9 kcal.d-1, respectively. There were no differences in RMR measurements due to body position and apparatus when each variable was isolated. Analyses of distraction in three of four combinations indicated no difference between TV and no TV. In summary, different parameter combinations can result in increased bias and variability and thereby reported differences among children's RMR measurement. The second study dealt with treadmill adaptation and determination of self-selected (SS) walking speed. Assessment of individual and group differences in metabolic energy expenditure using oxygen uptake requires that individuals are comfortable with, and can accommodate to, the equipment being utilised. In this study, a detailed proposal for an adaptation protocol based on the SS was developed. Experiments were carried out on 27 children aged 8-12 (mean age = 10.3±1.2 yr). Results from three treadmill tests following the adaptation protocol showed similar results for step length with no significant differences among tests and lower and no statistically significant variability within- and between-days. Additionally, no statistically significant differences between SS determined over-ground and on a treadmill were verified. These results suggest that SS speed determined over-ground is reproducible on a treadmill and the 10 min familiarisation protocol based on this speed provided sufficient exposure to achieve accommodation to the treadmill. The purpose of the third study was to verify within- and between-day repeatability and variability in children's oxygen uptake ( &VO2), gross economy (GE) [ &VO2 divided by speed] and heart rate (HR) during treadmill walking based on SS. 14 children (mean age = 10.2±1.4 yr) undertook 3 testing sessions over 2 days in which four walking speeds, including SS, were tested. Within- and between-day repeatability was assessed using the Bland and Altman method and coefficients of variability (CV) were determined for each child across exercise bouts and averaged to obtain a mean group CV value for &VO2, GE and HR per speed. Repeated measures ANOVA showed no statistically significant differences in within- or between-day CV for &VO2, GE or HR at any speed. Repeatability within and between-day for &VO2, GE and HR for all speeds was verified. These results suggest that submaximal &V O2 during treadmill walking is stable and reproducible at a range of speeds based on children's SS. In the fourth study, the objective was to establish the effect of walking speed on substrate oxidation during a treadmill protocol based on SS. Experiments were carried out on 12 girls aged 8-12 (mean age = 9.9±1.4 yr). Each participant underwent 2 test sessions, one week apart. Workloads on the treadmill included 2 speeds slower than SS (1.6 [V1] and 0.8 km.h-1 [V2] slower than SS), SS (V3), and a speed 0.8 km.h-1 faster than SS (V4). Indirect calorimetry from respired gas measurements enabled total fat (FO) and carbohydrate (CHO) oxidation rates to be calculated according to the non-protein respiratory quotient (Peronnet and Massicote, 1991) and percentage of CHO and FO calculations using equations from McGilvery and Goldstein (1983). Repeated measures ANOVA followed by a Tukey Post Hoc test (p< 0.05) was used to verify differences in CHO and FO rates among speeds. Paired T-test was used to verify differences in CHO and FO rates between tests per velocity. The reliability between-day was assessed using intraclass correlation coefficient (ICC). Results showed significant differences for CHO among all speeds, as well as significant differences for FO between V1 and V2 against V3 and V4 in both tests. Analyses between trials per velocity showed no significant substrate use differences as well as acceptable reliability. At the self-selected speed (V3) there was an accentuation in FO reduction as well as an increase in CHO oxidation. The purpose of the fifth study was to determine whether there were differences in substrate oxidation between girls (G) and women (W) during a treadmill protocol based on SS. Experiments were carried out on 12 G aged 8-12 (mean age = 9.9±1.4 yr) and 12 W aged 25-38 (mean age = 32.3±3.8 yr). The treadmill protocol included 6 min workloads followed by 5 min rest periods. Workloads included 2 speeds slower than SS (1.6 (V1) and 0.8 km.h-1 (V2) slower than SS), SS (V3), and a speed 0.8 km.h-1 faster than SS (V4). Total fat and carbohydrate (CHO) oxidation rates were calculated from indirect calorimetry according to the non-protein respiratory quotient. Repeated measures ANOVA followed by a Tukey Post Hoc test was used to verify intra-test differences in CHO and fat oxidation rates among speeds. Intergroup differences were analysed using paired T-test. Fat utilisation in W achieved a plateau at a relative velocity 0.8 km.h-1 slower than SS, but for G, fat utilisation increased until SS, and then stabilised upon reaching the higher velocity. CHO oxidation curves rose abruptly above V2 for W, while for G the acute increase occurred after SS (V3). Collectively, these results indicate that as walking intensity increases G are able to meet the energy demands of the work by increasing fat oxidation together with the increased CHO oxidation up to SS. In contrast for W, increasing CHO oxidation is associated with an early decrease in fat utilisation at a velocity slower than the self-selected speed. The sixth study dealt with validation of indirect techniques for the measurement of energy expenditure in free-living conditions against the DLW technique. Experiments were carried out on 19 children aged 8-12 (mean age = 10.3±1.0 yr). To indirectly predict energy expenditure 12 different procedures were used. Only one procedure, combining activity and heart rate (AHbranched), was based on a group equation, the others were based on individualised regression. Three of the individually-based techniques were able to accurately predict energy expenditure in free-living conditions. These tecniques were HRPAnetRMR using HRnet [HR exercise minus sleep HR (SHR)] against PAnet (measured PA exercise minus measured RMR) and upper and lower body equations corrected by RMR; HRPAnet4act using the same procedure but corrected by the mean resting &VO2 for 4 resting activities [(4act) = supine watching TV, sitting watching TV, sitting playing computer games and standing], and HRPALBnet4act using only lower body activities and corrected by 4act. HRPAnetRMR was only slightly more accurate than HRPAnet4act and HRPALBnet4act, but this technique is only adjusted by RMR whereas the other two are heavily dependent on more complex laboratory calibration. Bland and Altman (1986) analyses showed no significant differences between AHbranched predicted and measured TEE using the DLW technique. A SEE of 79 kcal.d-1 and a mean difference of 72 kcal.d-1, with a 95% CI ranging from -238 to 93.9 kcal.d-1 was found. In addition, no significant differences between predicted HRPAnetRMR and measured TEE using DLW were found, showing an SEE of 99 kcal.d-1 and a mean difference of -67 kcal.d-1, and a 95% CI ranging from -276.6 to 141.9 kcal.d-1. AHbranched and HRPAnetRMR were both valid and similarly suitable for the prediction of energy expenditure in children under free-living conditions. Significant associations between DLWAEE and the after-school time window indicated that this time window as an important discretionary period representative of children physical activity. However, the duration of the after-school time windows should be more carefully considered. Accelerometer data showed a better association between the largest after-school time window (3.5 hr) and measured TEE. The final study, completed with 19 children aged 8-12 (10.3±1.0 yr) highlighted, under laboratory conditions across a range of walking and running speeds, the inadequacy of the use of the standard MET in children. This traditional approach overestimates energy expenditure with an increased difference linearly related to speed increments. Minute-by-minute analyses of 7 days of free-living monitoring showed an average overestimation of 64 minutes per day for moderate-to-vigorousphysical- activity (MVPA) using the standard MET compared with the individually measured MET. For all intensities, these differences were statistically significant (p< 0.001). The second part of this study showed a variability of 20% in the average time spent at MVPA when comparing HR I 140 bpm and HR > 50%P &VO2 (P &VO2 = the highest &VO2 observed during an exercise test to exhaustion). Results of the current study compared to observations in the literature showed that HR I 140 bpm consistently estimates lower MVPA time than HR > 50%P &VO2. When these two PA indices were compared with individual and standard MET measured minute-byminute, statistically significant differences were verified among all of them at MPA, but no differences were verified at VPA, except between individual and standard METs. However, whether each one of the PA indices used are under- or overestimating time at MVPA is still debatable due to the lack of a gold standard. Finally, each index used in this study classified different numbers of participants as achieving the PA target of 60 min.d-1. The wide variability between indices when attempting to classify children who are achieving the recommended target is cause for great concern because habitually these indices are utilised as screening tools in paediatric and public health settings and used to guide behavioural interventions.