This study has two purposes: (1) to observe the step-count patterns of adult women who participated in an eight-month healthy lifestyle-based book club intervention and (2) to describe step-count patterns across seasons and body mass index (BMI) categories. Sixty-two participants (mean age ± SD = 53 ± 9, 92% Caucasians) had complete pedometer data, which was used for data analysis. After weekly, hour-long, discussion-based meetings during months one through four, and bi-monthly meetings during months five through eight, women increased their step counts by 26%. Significant step-count differences were observed among seasons (p < .05), and from pre- to post-intervention (p < .05), with the lowest steps being reported in the fall and the highest in the spring. Women in the obese category continued to increase steps during the winter, while the healthy-weight group decreased steps. There was a significant correlation between the average steps taken during the intervention and changes in BMI from pre- to post-intervention (r = −.26, p < .05). Overall, positive step-count pattern observations were found among adult women participating in a healthy lifestyle-based intervention.
Cara L. Sidman, Jennifer L. Huberty and Yong Gao
Jennifer L. Huberty, Diane Ehlers, Jason Coleman, Yong Gao and Steriani Elavsky
Ideal approaches to increasing long-term physical activity (PA) adherence in women remain unclear. This study used a longitudinal mixed-methods approach to 1) determine the effectiveness of an 8-month book club intervention for increasing PA participation and self-worth, and reducing barriers at 1-year follow-up; and 2) identify reasons why completers and noncompleters did or did not maintain PA.
One year after the cessation of Women Bound to be Active (WBA), completers (participated in posttesting; n = 30) and noncompleters (did not participate in posttesting; n = 22) responded to questionnaires and interviews assessing their body mass index (BMI), current PA participation, barriers, and global self-worth.
Compared with noncompleters, completers reported decreases in BMI, higher motivation for PA, higher ratio of benefits to barriers, and more consistent PA. Both groups still reported barriers to PA, especially time; however, completers more often reported strategies for overcoming these barriers. Completers more directly discussed the impact of their improved self-worth on their PA participation.
In the future, a greater focus on time management and self-regulation strategies should be emphasized in PA interventions, specifically those that focus on women. This may help to prevent program and long-term PA attrition.
Yong Gao, Haichun Sun, Jie Zhuang, Jian Zhang, Lynda Ransdell, Zheng Zhu and Siya Wang
This study determined the metabolic equivalents (METs) of several activities typically performed by Chinese youth.
Thirty youth (12 years) performed 7 activities that reflected their daily activities while Energy Expenditure (EE) was measured in a metabolic chamber.
METs were calculated as activity EE divided by participant’s measured resting metabolic rate. A MET value ranging from 0.8 to 1.2 was obtained for sleeping, watching TV, playing computer games, reading and doing homework. Performing radio gymnastics had a MET value of 2.9. Jumping rope at low effort required 3.1 METs. Except for watching TV, METs for other activities in this study were lower than Youth Compendium values.
The results provide empirical evidence for more accurately assessing EE of activities commonly performed by Chinese youth. This is the first study to determine METs for radio gymnastics and jump rope in Chinese youth.
Weimo Zhu, Zorica Nedovic-Budic, Robert B. Olshansky, Jed Marti, Yong Gao, Youngsik Park, Edward McAuley and Wojciech Chodzko-Zajko
To introduce Agent-Based Model (ABM) to physical activity (PA) research and, using data from a study of neighborhood walkability and walking behavior, to illustrate parameters for an ABM of walking behavior.
The concept, brief history, mechanism, major components, key steps, advantages, and limitations of ABM were first introduced. For illustration, 10 participants (age in years: mean = 68, SD = 8) were recruited from a walkable and a nonwalkable neighborhood. They wore AMP 331 triaxial accelerometers and GeoLogger GPA tracking devices for 21 days. Data were analyzed using conventional statistics and highresolution geographic image analysis, which focused on a) path length, b) path duration, c) number of GPS reporting points, and d) interaction between distances and time.
Average steps by subjects ranged from 1810−10,453 steps per day (mean = 6899, SD = 3823). No statistical difference in walking behavior was found between neighborhoods (Walkable = 6710 ± 2781, Nonwalkable = 7096 ± 4674). Three environment parameters (ie, sidewalk, crosswalk, and path) were identified for future ABM simulation.
ABM should provide a better understanding of PA behavior’s interaction with the environment, as illustrated using a real-life example. PA field should take advantage of ABM in future research.