Physical Activity Measures

2016 ◽  
pp. 77-82 ◽  
Author(s):  
David R. Bassett ◽  
Kenneth M. Bielak
Keyword(s):  
Physical Activity ◽  
Activity Measures

scholarly journals Responsiveness of Physical Activity Measures Following Exercise Programs after Total Knee Arthroplasty

2017 ◽  
Vol 4 (3) ◽  
pp. 1-8 ◽  
Author(s):  
Gustavo J Almeida ◽  
Lauren Terhorst ◽  
James J ◽  
Irrgan g ◽  
G. Kelley Fitzgerald ◽  
...  
Keyword(s):  
Physical Activity ◽  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Exercise Programs ◽  
Activity Measures ◽  
Total Knee

Motivators and Barriers to Healthy Eating and Physical Activity Measures

2017 ◽  
Author(s):  
Lee M. Ashton ◽  
Melinda J. Hutchesson ◽  
Megan E. Rollo ◽  
Philip J. Morgan ◽  
Clare E. Collins
Keyword(s):  
Physical Activity ◽  
Healthy Eating ◽  
Activity Measures

scholarly journals P234 Physical activity measures in cystic fibrosis: could we use new electronic devices?

2019 ◽  
Vol 18 ◽  
pp. S123
Author(s):  
D. Savi ◽  
L. Graziano ◽  
S. Schiavetto ◽  
N.J. Simmonds ◽  
B. Giordani ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cystic Fibrosis ◽  
Electronic Devices ◽  
Activity Measures

scholarly journals Association between early life factors and accelerometry-based physical activity measures in children aged 5-7 years old

2020 ◽  
Vol 31 (1) ◽  
Author(s):  
Maria Laura Siqueira de Souza Andrade ◽  
Carla Menêses Hardman ◽  
Mauro Virgílio Gomes de Barros
Keyword(s):  
Physical Activity ◽  
Birth Order ◽  
Early Life ◽  
Cross Sectional Study ◽  
Physical Activities ◽  
Moderate Intensity ◽  
Cross Sectional ◽  
Activity Measures ◽  
Early Life Factors ◽  
Daily Time

The present study aims to verify if there is an association between early life factors (birth weight, exclusive breastfeeding, birth order and preterm birth) and accelerometry-based physical activity measures in children aged 5 to 7 years old. It is a cross-sectional study carried out with children from public and private schools in Recife, Brazil. A questionnaire was applied to the children's parents. Of the 784 children participating in the study, 491 had at least three days of valid monitoring. It was possible to identify that the children classified as the fourth ones, as to birth order, or over, were 83% less likely to have a low percentage of daily time spent on moderate-intensity physical activities compared to firstborns (OR = 0.17; 0.03-0.80). Only birth order was negatively associated with low percentage of daily time spent on moderate physical activities, even after adjustment for confounding factors.

Classification and Processing of 24-Hour Wrist Accelerometer Data

2018 ◽  
Vol 1 (2) ◽  
pp. 51-59 ◽  
Author(s):  
Anna Pulakka ◽  
Eric J. Shiroma ◽  
Tamara B. Harris ◽  
Jaana Pentti ◽  
Jussi Vahtera ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Time ◽  
Total Activity ◽  
Sleep Time ◽  
Accelerometer Data ◽  
Classification Methods ◽  
Wake Time ◽  
Wear Time ◽  
Aging Study ◽  
Activity Measures

Background: An important step in accelerometer data analysis is the classification of continuous, 24-hour data into sleep, wake, and non-wear time. We compared classification times and physical activity metrics across different data processing and classification methods.Methods: Participants (n = 576) from the Finnish Retirement and Aging Study (FIREA) wore an accelerometer on their non-dominant wrist for seven days and nights and filled in daily logs with sleep and waking times. Accelerometer data were first classified as sleep or wake time by log, and Tudor-Locke, Tracy, and ActiGraph algorithms. Then, wake periods were classified as wear or non-wear by log, Choi algorithm, and wear sensor. We compared time classification (sleep, wake, and wake wear time) as well as physical activity measures (total activity volume and sedentary time) across these classification methods.Results:M(SD) nightly sleep time was 467 (49) minutes by log and 419 (88), 522 (86), and 453 (74) minutes by Tudor-Locke, Tracy, and ActiGraph algorithms, respectively. Wake wear time did not differ substantially when comparing Choi algorithm and the log. The wear sensor did not work properly in about 29% of the participants. Daily sedentary time varied by 8–81 minutes after excluding sleep by different methods and by 1–18 minutes after excluding non-wear time by different methods. Total activity volume did not substantially differ across the methods.Conclusion: The differences in wear and sedentary time were larger than differences in total activity volume. Methods for defining sleep periods had larger impact on outcomes than methods for defining wear time.

scholarly journals Dog ownership and adults’ objectively-assessed sedentary behaviour and physical activity

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mohammad Javad Koohsari ◽  
Ai Shibata ◽  
Kaori Ishii ◽  
Sayaka Kurosawa ◽  
Akitomo Yasunaga ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Linear Regression Models ◽  
Sedentary Behaviours ◽  
Dog Ownership ◽  
Intensity Physical Activity ◽  
Activity Measures ◽  
Sedentary Breaks ◽  
Dog Owners ◽  
Sedentary Bouts

Abstract Evidence suggests a positive effect of dog ownership on physical activity. However, most previous studies used self-reported physical activity measures. Additionally, it is unknown whether owning a dog is associated with adults’ sedentary behaviour, an emerging health risk factor. In this study, physical activity and sedentary behaviour were objectively collected between 2013 and 2015 from 693 residents (aged 40–64 years) living in Japan using accelerometer devices. Multivariable linear regression models were used, adjusted for several covariates. The means of total sedentary time and the number of long (≥ 30 min) sedentary bouts were 26.29 min/day (95% CI − 47.85, − 4.72) and 0.41 times/day (95% CI − 0.72, − 0.10) lower for those who owned a dog compared to those not owning a dog, respectively. Compared with non-owners, dog-owners had significantly higher means of the number of sedentary breaks (95% CI 0.14, 1.22), and light-intensity physical activity (95% CI 1.31, 37.51). No significant differences in duration of long (≥ 30 min) sedentary bouts, moderate, vigorous, and moderate-to-vigorous-intensity physical activity were observed between dog-owners and non-owners. A novel finding of this study is that owning a dog was associated with several types of adults’ sedentary behaviours but not medium-to-high-intensity physical activities. These findings provide new insights for dog-based behavioural health interventions on the benefits of dog ownership for reducing sedentary behaviour.

Validity of physical activity measures in ambulatory individuals with multiple sclerosis

2006 ◽  
Vol 28 (18) ◽  
pp. 1151-1156 ◽  
Author(s):  
Robert W. Motl ◽  
Edward McAuley ◽  
Erin M. Snook ◽  
Jennifer A. Scott
Keyword(s):  
Physical Activity ◽  
Multiple Sclerosis ◽  
Activity Measures
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