Objectifs. Pour augmenter l’activité physique populationnelle et réduire les inégalités relatives à l’environnement bâti, on doit identifier le rôle des profils sociodémographiques individuels dans les niveaux d’activité physique et d’exposition aux environnements bâtis favorables au mode de vie actif. Méthodes. Cette étude combine des données d’accélérométrie et de GPS collectées auprès de 820 participants durant 10 à 30 jours entre 2018 et 2020 dans les études INTErventions urbaines, Recherche-Action, Communautés et sanTé (INTERACT) et Réseau Express Métropolitain (REM). Différents modèles de régressions multiniveaux ‒journées nichées dans des individus‒ testent les associations et les interactions entre les profils sociodémographiques, les niveaux d’exposition à des facteurs environnementaux susceptibles de favoriser le mode de vie actif (infrastructures de transports, commerces, densité bâtie et espaces verts) et la proportion journalière de minutes actives. Les résultats sur l’échantillon de l’application EthicaData sont comparés à ceux sur l’appareil SenseDoc. Résultats. Les participants plus âgés, universitaires ou sans emploi ainsi que les femmes sont moins actifs. Les participants plus âgés, non-universitaires, sans emploi ou à haut revenu ainsi que les hommes sont moins exposés à l’environnement bâti favorable à l’activité physique. Discussion. Les niveaux d’activité physique et d’exposition à l’environnement bâti ainsi que les effets de l’exposition environnementale ne varient pas systématiquement en défaveur des groupes désavantagés systémiquement. Des associations sont inattendues entre l’exposition à l’environnement bâti et le mode de vie actif. Les résultats basés sur le GPS sont concordants entre EthicaData et SenseDoc, mais discordants pour ceux basés sur l’accélérométrie. / Aim. To increase population levels of physical activity and reduce inequalities related to built environment, we must identify the role of individual-level sociodemographic profiles in physical activity levels, and in levels of exposure to built environment that may contribute to active living. Method. This study combines accelerometry and GPS data collected among 820 participants during 10 to 30 days between 2018 and 2020 within the INTErventions, Research, and Action in Cities Team (INTERACT) and Reseau Express Metropolitain (REM) studies. Multiple multilevel models ‒days nested within individuals‒ test associations and interactions between socio demographic profiles, levels of exposure to environmental factors susceptible to promote active living (transport infrastructures, shops, built density and green spaces) and the daily proportion of active minutes. Results on the EthicaData application subset are compared to those on the SenseDoc device subset. Results. Participants who are older, have a university profile or are unemployed, along with women, are less active. Participants who are older, don’t have a university profile, are unemployed or have a higher income, along with men, are less exposed to built environment that may contribute to physical activity. Discussion. The levels of physical activity and exposure to built environment, and the effects of environmental exposure on physical activity, do not vary systematically in disfavor of systemically disadvantaged groups. Some associations between exposed built environment and active living are unexpected. Results based on the GPS are consistent between EthicaData and SenseDoc, but inconsistent for those based on accelerometry.

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.

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.

Background: Knee osteoarthritis is a degenerative disease characterized by damaged joint tissues (e.g., cartilage) that leads to joint pain, and reduced mobility and quality of life. Various factors are involved in disease progression, including biomechanical, patient-reported outcome and mobility measures. This thesis provides important longitudinal data on the role of these factors in disease progression, and the trajectory of biomechanical factors in persons with knee osteoarthritis. Objectives: (1) Determine the extent to which changes over 2.5 years in knee cartilage thickness and volume in persons with knee osteoarthritis were predicted by the knee adduction and flexion moment peaks, and knee adduction moment impulse and loading frequency. (2) Determine the extent to which changes over 2 years in walking and stair-climbing mobility in women with knee osteoarthritis were predicted by quadriceps strength and power, pain and self-efficacy. (3) Estimate the relative and absolute test-retest reliabilities of biomechanical risk factors for knee osteoarthritis progression. Methods: Data were collected at 3-month intervals during a longitudinal (3-year), observational study of persons with clinical knee osteoarthritis (n=64). Magnetic resonance imaging of the study knee was acquired at the first and last assessments, and used to determine cartilage thickness and volume. Accelerometry and dynamometry data were acquired every 3 months, and used to determine knee loading frequency and knee muscle strength and power, respectively. Walking and stair-climbing mobility, as well as pain and self-efficacy data, were also collected every 3 months. Gait analyses were performed every 6 months, and used to calculate lower-extremity kinematics and kinetics. Results: (1) The knee adduction moment peak and impulse each interacted with body mass index to predict loss of medial tibial cartilage volume over 2.5 years. These interactions suggested that larger joint loads in those with a higher body mass index were associated with greater loss of cartilage volume. (2) In women, lower baseline self-efficacy predicted decreased walking and stair ascent performances over 2 years. Higher baseline pain intensity/frequency also predicted decreased walking performance. Quadriceps strength and power each interacted with self-efficacy to predict worsening stair ascent times. These interactions suggested that the impact of lesser quadriceps strength and power on worsening stair ascent performance was more important among women with lower self-efficacy. (3) Relative reliabilities were high for the knee adduction moment peak and impulse, quadriceps strength and power, and body mass index (i.e., intraclass correlation coefficients >0.80). Absolute reliabilities were high for quadriceps strength and body mass index (standard errors of measurement <15% of the mean). Data supported the use of interventions effective in reducing the knee adduction moment and body mass index, and increasing quadriceps strength, in persons with knee osteoarthritis. Conclusion: Findings from this thesis suggest that biomechanical factors play a modest independent role in the progression of knee osteoarthritis. However, in the presence of other circumstances (e.g., obesity, low self-efficacy, high pain intensity/frequency), biomechanical factors can vastly worsen the disease. Strategies aiming to curb structural progression and improve clinical outcomes in knee osteoarthritis should target biomechanical and clinical outcomes simultaneously. / Thesis / Doctor of Philosophy (PhD) / Knee osteoarthritis is a multifactorial disease whose progression involves worsening joint structure, symptoms, and mobility. Various factors are linked to the progression of this disease, including biomechanical, patient-reported outcome and mobility measures. This thesis provides important information on how these factors, separately and collectively, are involved in worsening disease over time, as well as benchmarks that are useful to clinicians and researchers in interpreting results from interventional or longitudinal research. First, we examined how different elements of knee loading were associated with changes in knee cartilage quantity over time in persons with knee osteoarthritis. Second, we examined how different elements of knee muscle capacity and patient-reported outcomes were related to changes in mobility over time in persons with knee osteoarthritis. Third, we examined the stability over time of various biomechanical risk factors for the progression of knee osteoarthritis. Novel results from this thesis showed that: (1) larger knee loads predicted cartilage loss over 2.5 years in obese individuals with knee osteoarthritis but not in persons of normal weight or overweight; (2) among women with knee osteoarthritis with lower self-efficacy (or confidence), lesser knee muscle capacity (strength, power) was an important predictor of declining stair-climbing performance over 2 years; and (3) clinical interventions that can positively alter knee biomechanics include weight loss, knee muscle strengthening, as well as specific knee surgery and alterations during walking to reduce knee loads. Interventions for knee osteoarthritis should target biomechanical and clinical outcomes simultaneously.