No abstract

Wearable technologies represent a novel approach in the prevention of obesity and overweight that encourages users to engage in physical activities aided by technological assistance. This is the first meta-analysis to investigate the effects of wearable technologies as physical activity interventions on weight control. Various electronic databases were searched to select eligible articles, including EBSCO, ScienceDirect, and PubMed, from the first available date to January 9, 2019. All analyses were performed using a random-effects model. Moderator analyses were conducted to investigate differences in the effect size. This meta-analysis of 19 randomized controlled trials indicated that wearable technologies as a physical activity intervention achieved a moderate and significant effect size on body weight and waist circumference and large and significant effect sizes on the body mass index. A subgroup analysis confirmed that wearable technologies were more efficient for weight control in individuals with obesity and chronic diseases. A duration of using wearable technologies for a total of more than or equal to 12 weeks was more effective. Meta-regressions have also revealed that the body weight of individuals who received an additional week of treatment could be reduced by more than 0.37%. Wearable technologies offer innovative platforms of physical activity interventions and an efficient method for weight control.

Background/objectiveProductive engagement can be a strategy to reduce stress and chaos. Physical activity, a basic type of productive activity, could benefit older adults. Therefore, the purpose of this study was to explore how productive engagement in physical activity may influence older adults in maintaining their health-related quality of life when they live in a long-term care facility.MethodsWe used purposive sampling to recruit 163 participants from 14 long-term care facilities in Taiwan. Data were collected through individual interviews with a structured questionnaire. Descriptive statistics and independent t-test were used.ResultsThe result demonstrated that the preferred type of physical activities for the older adults was similar after the relocation. Older adults with increasing productive engagement in physical activity reported better scores of Mental Component Summary, social and emotional role functioning than those with decreasing productive engagement in physical activity.ConclusionOlder adults can have a positive perceived health-related quality of life by consistently or increasingly engaging in productive physical activity, especially when encountering a life event.

No abstract

Maintaining physical activity is necessary to promote health in our daily lives. The Ecological Model of Active Living was proposed to examine whether individuals participate in active living. The purpose of this study was to understand the determinants of physical activity and create a predictive path model of the intrapersonal, perceived environment, behavior settings, and policy environment domains. Data were obtained from open government data and questionnaires, including the International Physical Activity Questionnaire, Health Belief Model Inventory, Physical Activity Neighborhood Environment Survey, and Accessibility of Open Spaces. Participants comprised 1085 healthy adults who completed a self-reported internet survey. An analysis of the intrapersonal domain revealed that the variables of female, an older age, and a low educational level, and individuals with obesity or cardiometabolic diseases presented lower odds ratios for active living. We found significant statistical support for our path model (The Ecological Model of Active Living), with a predictive power of 23.1%. The predictive path model is a good approach to quantitatively measure the impacts of various determinants on active living that suggests further lines of research in approaches for modeling relationships.