Physical inactivity is a modifiable risk factor for cardiovascular diseases and other chronic diseases of life. In countries undergoing economic transition from underdeveloped to being developed, there is an increasing rate of physical inactivity. Accurate assessment of physical activity behaviours is important for determining the presence of physical inactivity, for setting goals for physical therapy interventions to increase physical activity and to utilize physical activity as an outcome measure for physical therapy interventions. There are different techniques used to measure physical activity, namely questionnaires, motion sensors (pedometers and accelerometers) and doubly labelled water. The most used method in large epidemiological research is questionnaires because of their affordability and feasibility. Limitations of physical activity questionnaires include the exclusion of house-hold activities, intensity of work done, bicycling, duration and frequency of leisure time activities. Motion sensors have been mostly used in developed and westernized countries. In the North West Province (NWP) of South Africa the only method that has been used to determine physical activity among the Tswana speaking people was the Transition of Health during urbanization physical activity questionnaire (THUSA-PAQ). The application of other methods such as the motion sensors has never been done. Objectives: The study comprised two major objectives: The first objective was to determine the physical activity levels of the rural and urban Tswana speaking people of the NWP using the THUS A questionnaire and pedometers. The second objective was to determine whether there is a relationship in physical activity determined by the THUSA-PAQ, promotional pedometer and an accelerometer determined activity. Methods The participants recruited for this study form part of the larger prospective urban and rural epidemiology (PURE) longitudinal study running over 12 years which started in 2005. A subsample of 200 was randomly selected of which hundred and eighty signed the informed consent (90 urban and 90 rural) to participate in the study. The participants completed the THUSA-PAQ with the assistance help of the fieldworkers in their native language and wore pedometers for seven consecutive days. The number of steps taken per day distance travelled and energy expenditure were recorded in a logbook. Another thirty eight participants from a co-hort in the same geographical area were issued with accelerometers to wear simultaneously with pedometers for a period of twenty four hours and also completed the THUSA-PAQ. Results The rural male and female participants reported higher average physical activity index (PAT) with the THUSA questionnaire (9.49 ± 3.67 and 8.10 ± 1.26) than urban male and female participants (8.13 ± 2.47 and 7.51 ± 1.65) respectively. The same trend was observed with the objectively determined physical activity with the pedometers. A partial correlation adjusted for age and gender showed no statistical significance between the subjectively determined physical activity index (PAT) and the objectively determined activity (average steps per day). Results from the co-hort participants indicated that both male and female participants spent a larger percentage of their time on sedentary activities (66.45 ± 15.84% and 70.13 ± 8.39%) respectively. Most of the participants, 64.7% females and 52.1% males, recorded fewer than 5000 steps per day with a pedometer and reported high PAI (9.61 ± 1.83 males and 7.79 ± 1.26 females) with the THUSA-PAQ. On this population partial correlation analyses that was adjusted for age and body mass index (BMT) showed a statistical significant relationship between (p<0.05) time spent on vigorous activities and commute index between male and female participants. There was no statistical significant relationship between the PAI (THUSA-PAQ), activity energy expenditure (AEE) determined with an accelerometer and the number of steps per day determined with a pedometer. Conclusion The major conclusion that can be drawn from this study is that the participants did not meet the recommended physical activity levels (30 min moderate physical activity or 10 000 pedometer determined steps per day). The participants reported high subjective physical activity index (PAI) with the THXJSA-PAQ which did not correlate with the low objectively determined number of steps per day using the pedometer and AEE. Possible reasons for this include the influence of perception toward physical activity, social desrrabiUty, seasonal changes, reactivity and time of the year. Motion sensors gave a better indication of habitual physical activity among the Tswana speaking people of the NWP and should be considered for further research. / Thesis (M.Sc. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.

Thesis (M.A. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.

Physical inactivity is a modifiable risk factor for cardiovascular diseases and other chronic diseases of life. In countries undergoing economic transition from underdeveloped to being developed, there is an increasing rate of physical inactivity. Accurate assessment of physical activity behaviours is important for determining the presence of physical inactivity, for setting goals for physical therapy interventions to increase physical activity and to utilize physical activity as an outcome measure for physical therapy interventions. There are different techniques used to measure physical activity, namely questionnaires, motion sensors (pedometers and accelerometers) and doubly labelled water. The most used method in large epidemiological research is questionnaires because of their affordability and feasibility. Limitations of physical activity questionnaires include the exclusion of house-hold activities, intensity of work done, bicycling, duration and frequency of leisure time activities. Motion sensors have been mostly used in developed and westernized countries. In the North West Province (NWP) of South Africa the only method that has been used to determine physical activity among the Tswana speaking people was the Transition of Health during urbanization physical activity questionnaire (THUSA-PAQ). The application of other methods such as the motion sensors has never been done. Objectives: The study comprised two major objectives: The first objective was to determine the physical activity levels of the rural and urban Tswana speaking people of the NWP using the THUS A questionnaire and pedometers. The second objective was to determine whether there is a relationship in physical activity determined by the THUSA-PAQ, promotional pedometer and an accelerometer determined activity. Methods The participants recruited for this study form part of the larger prospective urban and rural epidemiology (PURE) longitudinal study running over 12 years which started in 2005. A subsample of 200 was randomly selected of which hundred and eighty signed the informed consent (90 urban and 90 rural) to participate in the study. The participants completed the THUSA-PAQ with the assistance help of the fieldworkers in their native language and wore pedometers for seven consecutive days. The number of steps taken per day distance travelled and energy expenditure were recorded in a logbook. Another thirty eight participants from a co-hort in the same geographical area were issued with accelerometers to wear simultaneously with pedometers for a period of twenty four hours and also completed the THUSA-PAQ. Results The rural male and female participants reported higher average physical activity index (PAT) with the THUSA questionnaire (9.49 ± 3.67 and 8.10 ± 1.26) than urban male and female participants (8.13 ± 2.47 and 7.51 ± 1.65) respectively. The same trend was observed with the objectively determined physical activity with the pedometers. A partial correlation adjusted for age and gender showed no statistical significance between the subjectively determined physical activity index (PAT) and the objectively determined activity (average steps per day). Results from the co-hort participants indicated that both male and female participants spent a larger percentage of their time on sedentary activities (66.45 ± 15.84% and 70.13 ± 8.39%) respectively. Most of the participants, 64.7% females and 52.1% males, recorded fewer than 5000 steps per day with a pedometer and reported high PAI (9.61 ± 1.83 males and 7.79 ± 1.26 females) with the THUSA-PAQ. On this population partial correlation analyses that was adjusted for age and body mass index (BMT) showed a statistical significant relationship between (p<0.05) time spent on vigorous activities and commute index between male and female participants. There was no statistical significant relationship between the PAI (THUSA-PAQ), activity energy expenditure (AEE) determined with an accelerometer and the number of steps per day determined with a pedometer. Conclusion The major conclusion that can be drawn from this study is that the participants did not meet the recommended physical activity levels (30 min moderate physical activity or 10 000 pedometer determined steps per day). The participants reported high subjective physical activity index (PAI) with the THXJSA-PAQ which did not correlate with the low objectively determined number of steps per day using the pedometer and AEE. Possible reasons for this include the influence of perception toward physical activity, social desrrabiUty, seasonal changes, reactivity and time of the year. Motion sensors gave a better indication of habitual physical activity among the Tswana speaking people of the NWP and should be considered for further research. / Thesis (M.Sc. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.

Thesis (M.A. (Human Movement Science))--North-West University, Potchefstroom Campus, 2009.

Physical activity has multiple health benefits, however, physical activity can also lead to the development of excessive exercise, disturbed eating patterns, negative body image and social physique anxiety. This study investigated the relationship between social physique anxiety (SPA), physical activity type, frequency of physical activity, and motives to exercise. Participants were female undergraduates (N=108) enrolled at the University of Victoria. Female students were recruited from Exercise, Physical and Health Education classes that were open to all students from different faculties. A cross-sectional survey assessed social physique anxiety, frequency of physical activity and motives for exercise as well as dividing students according to physical activity type (Varsity, Intramural, High Strenuous Exerciser, Low Strenuous Exerciser). An analysis of variance revealed no association between SPA and physical activity type. Additionally, correlations showed that SPA and frequency of physical activity was not significant. Interestingly, SPA was significant for all motives that include Interest (r=-.371, p<.01), Competence (r=-.330, p<.01), Appearance (r=.430), Fitness (r=-.215, p<.05), and Social (r=-.406, p<.01). A linear regression revealed that only Appearance and Social motives predicted SPA. / Graduate / 0573 / 0347 / 0566 / fawniar@uvic.ca

Objective: To explore the informational and behavioural factors, that affect women’s participation in physical activity (PA) and body weight changes during perimenopause. Methods: An environmental scan of online health websites to determine availability and quality of information for women about body weight changes during transition to menopause. An interpretive descriptive qualitative study of women age 40 – 60 to explore factors influencing their PA. Descriptive and inductive qualitative analysis were used. Results: Six of 52 websites (11.5%) contained information specific to perimenopausal women, with one site citing evidence. For 26 women interviewed, the most common enabling factors were daily structure, positive feelings, and accountability; while common barriers were disruptions in daily structure, competing demands, and self - sacrifice. Conclusions: There is a lack of information regarding body weight changes for perimenopausal women. Perimenopausal women attribute their PA participation to psychosocial factors, and not the physiology of menopause.

Using ecological task analysis as a conceptual framework, this study sought to describe the experiences of choice in physical activity contexts for adults with mobility impairments. Experiences of 3 female and 2 male participants with mobility impairments, ages 18-23 years were explored using the phenomenological research methods of interviews, written stories, and field notes. Thematic analysis revealed three themes: (a) Interpreting the setting described participants interpretation of the environment, person, and task when making movement choices; (b) It just felt right described how participants actively engaged in a process of analyzing alternatives and choosing among them; and (c) Implications of choices made described participants evaluations of good and bad choices and what could be learned. The implications of this exploratory study include enhanced understanding of the assumptions surrounding choice, and appreciation for the multiple layers of affordances and constraints that influence choices in physical activity contexts.

Objective: To explore the informational and behavioural factors, that affect women’s participation in physical activity (PA) and body weight changes during perimenopause. Methods: An environmental scan of online health websites to determine availability and quality of information for women about body weight changes during transition to menopause. An interpretive descriptive qualitative study of women age 40 – 60 to explore factors influencing their PA. Descriptive and inductive qualitative analysis were used. Results: Six of 52 websites (11.5%) contained information specific to perimenopausal women, with one site citing evidence. For 26 women interviewed, the most common enabling factors were daily structure, positive feelings, and accountability; while common barriers were disruptions in daily structure, competing demands, and self - sacrifice. Conclusions: There is a lack of information regarding body weight changes for perimenopausal women. Perimenopausal women attribute their PA participation to psychosocial factors, and not the physiology of menopause.

Introduction: Metabolic syndrome (MetS) is a risk condition describing a clustering of traditional cardiovascular risk factors. A number of risk and protective factors have been associated with MetS, and individuals with MetS are at a higher risk for developing chronic diseases such as diabetes, cancer, and cardiovascular disease. Objective: To contribute to the understanding of MetS in Canada, and to describe how it is a risk state through which material, psychosocial, and behavioural factors associate with chronic diseases. This was examined through three objectives: (i) to describe the prevalence and distribution of MetS; (ii) to examine potential pathways linking income and education with MetS; and (iii) to examine the interplay between non-movement behaviours (NMBs, namely sleep, screen time, and sedentary behaviour) and MetS. Methods: The Canadian Health Measures Survey (2007-2009, 2009-2011, ages 18 and older) was used for all analyses, which include logistic regression, multinomial regression, and calculation of standardized logit coefficients. Results: MetS was prevalent among approximately 20% of Canadian adults. It was significantly associated with chronic diseases, such as diabetes (11.2% vs. 3.4% among those with MetS vs. the general population). A social gradient in MetS was identified, and the behavioural risk factors of alcohol use, smoking, physical inactivity, and screen time were suggested to be partial mediators of this pathway. Findings demonstrated that not adhering to physical activity guidelines (150 minutes or more of moderate-to-vigorous physical activity per week) was associated with increased odds of MetS. A stepwise moderating effect of guideline adherence on screen time and sleep behaviours was demonstrated. Conclusion: MetS is prevalent in Canadian adults, and a high proportion of individuals with MetS have chronic conditions. Addressing the modifiable determinants of physical inactivity, excess screen time, alcohol consumption, and smoking may reduce the social gradient in MetS. Furthermore, adhering to physical activity guidelines may mitigate the associations of NMBs with MetS. The current thesis suggests that healthy behaviours are associated with lower risk for MetS, and therefore, possibly for future chronic disease.

Background: In Canada, women aged 15-24 report the highest rate of depression, an age group which represents a significant proportion of undergraduate students (Hanlon, 2012). Although pharmacology remains the primary treatment for depression, it may not be the most sufficient (Stanton et al., 2014). Physical activity has been demonstrated to have a large and significant antidepressant effect in individuals with depression (Schuch et al., 2016), though what remains challenging is identifying the most effective way to activate this population. Physical Activity Counselling (PAC) has been shown in research to effectively increase levels of physical activity (Fortier et al., 2011). However, the effects of PAC have not been considered in a population of female students with depression specifically. Purpose: To investigate the effects of PAC on depressive symptoms, affect and physical activity in female undergraduate students with depression. Methods: Five female undergraduate students with depression received two months of PAC from a registered Kinesiologist. The study followed a multiple baseline, single-subject design in which measures were taken during four study phases: baseline, intervention, end point and follow-up. Data was collected, including daily objective measures of physical activity, using accelerometers, and self-reported measures of depressive symptoms, positive affect, negative affect and physical activity, using online surveys administered every second day. Results: Visual analyses revealed that depressive symptoms decreased and self-reported physical activity increased from baseline throughout subsequent study phases in all five participants, as hypothesized. Statistical analyses supported these results. Estimated effect sizes of grouped averages indicated that decreases in depressive symptoms from baseline throughout each study phase ranged from small to large, while increases in self-reported physical activity were in the medium to large range. Conclusions: Findings of this study provide initial support for Physical Activity Counselling as a potential strategy to increase physical activity levels and reduce depression among female undergraduate students with depression. Future research is recommended on this important topic.