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Susan Paudel, Narayan Subedi, and Suresh Mehata

Background:

This study was carried out to assess physical activity level and identify associated factors among higher secondary school students in Banke district, Nepal.

Methods:

A school-based, cross-sectional descriptive study was conducted among 405 students studying in grades 11 and 12 in 7 higher secondary schools selected randomly. A self-administered questionnaire based on the International Physical Activity Questionnaire was used to measure physical activity level.

Results:

Only 5% of students were found to be inactive, and domestic and transport-related activities were major contributors to total physical activity score. No significant difference existed for total physical activity and domain-specific and activity-specific scores across different age groups when males and females were tested separately. Being male (P = .046), lower economic status (P = .026), living at a distance of less than 30 minutes (P = .007), walking/cycling to school (P < .001), and studying in government school (P < .001) were associated with increased physical activity scores on multivariate logistic regression analysis.

Conclusion:

Routine activities such as transport and household chores contributed greatly to total physical activity among students. This study highlights the need for physical activity promotion interventions at school addressing the associated factors and a need for greater focus on leisure-time physical activities.

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Andrea Stewart, Barbara Sternfeld, Brittney S. Lange-Maia, Kelly R. Ylitalo, Alicia Colvin, Carrie A. Karvonen-Gutierrez, Sheila A. Dugan, Robin R. Green, and Kelley Pettee Gabriel

(panels a–d). After adjusting for SWAN site, Black participants had statistically significantly lower active living, sports and exercise, and total physical activity scores than Whites. When compared to White women, Hispanic women had a statistically significantly lower sports and exercise score

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Loretta DiPietro, Teresa E. Seeman, Susan S. Merrill, and Lisa F. Berkman

To investigate the association between physical activity and cognitive ability, cross-sectional data from a representative cohort of 1,189 adults (70–79 years old) participating in the MacArthur Study of Successful Aging were examined. The frequency of current house/yardwork and recreational activities was assessed using five categories of responses. A total physical activity score was derived, and cognitive ability was assessed. The total physical activity score showed a modest yet significant bivariate correlation with the total cognitive ability score. In the multivariate analysis, physical activity showed a significant association with the total cognitive ability score, independent of gender, self-rated health, average peak expiratory flow rate, body mass index, number of current social relationships, and visual contacts in the past month. When education was added to the model, however, the effect of physical activity was substantially diminished. Higher levels of physical activity appear to be associated with some cognitive benefits among a population of healthy older adults, although this association is influenced strongly by their joint association with education.

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Lisiane Piazza Luza, Diego Rodrigues Pimentel da Silva, Elizandra Gonçalves Ferreira, Greicy Kelly Wosniak Pires, Paulo José Barbosa Gutierres Filho, and Rudney da Silva

compare the physical activity scores (leisure, domestic, occupational, and total) in people with lower limb amputation according to sex, use of prosthesis, and level and cause of amputation and to relate the total physical activity score to the age and time since the amputation. Methods This study was

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Chiaki Yokota, Sachiko Ohta, and Yasuyuki Fujimoto

METs for walking vigorously, 3.3 METs for walking moderately, 2.5 METs for walking slowly, and 1 MET for sitting, by frequency (in days per week) and duration (per minute). Each activity is summed to produce a total physical activity score from all reported activities per week. Total physical activity

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Madhura Phansikar and Sean P. Mullen

duration of each of the physical activities, the calculated total physical activity scores, and the scores on the cognitive variables were checked for univariate outliers and were winsorized if outliers were present. Except for animal fluency and delayed recall scores, the rest of the variables were

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Marlene Kritz, Cecilie Thøgersen-Ntoumani, Barbara Mullan, Afroditi Stathi, and Nikos Ntoumanis

( Washburn, Smith, Jette, & Janney, 1993 ). Sample items include: “Over the past seven days, how often did you take a walk outside your home or yard for any reason?” ( Washburn et al., 1993 ). A total physical activity score was determined by multiplying the time spent in each particular activity (hours per

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Minsuk Oh, David R. Jacobs Jr, Kelley Pettee Gabriel, Wei Bao, Gary L. Pierce, Lucas J. Carr, James G. Terry, Jingzhong Ding, John J. Carr, and Kara M. Whitaker

recreational sports, exercise, leisure, and occupational activities. 14 , 15 Total physical activity scores were calculated based on frequency (number of months), intensity score, and a weighting factor to represent the duration of each activity using a computer-based algorithm, as previously explained. 16

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Chantelle Zimmer and Meghan H. McDonough

activity required for their job or volunteer work (1 =  mainly sitting , 2 =  sitting and standing with some walking , 3 =  walking and light manual work , 4 =  walking and heavy manual work ). A total physical activity score was calculated for participants by multiplying their daily average time spent in