This study explored associations between perceived neighborhood walkability and neighborhood-based physical activity (NB-PA) and assessed possible moderation effects of the amount of time spent in the home neighborhood and individual characteristics (i.e., educational level and health-related problems). In 2016 to 2017, 509 Dutch adults, living in the South Limburg area, were included. Context-specific PA levels were measured using the Actigraph GT3X+ accelerometer and the Qstarz BTQ1000XT GPS-logger. Perceived neighborhood walkability, level of education, work status, and health-related quality of life were measured with validated self-report instruments. Results showed that individuals with a lower level of education or health-related problems spent more time in the home neighborhood. The perceived neighborhood walkability only affected NB-PA for individuals spending a relatively large amount of time in their home neighborhood. PA-facilitating features in the home neighborhood, for example, aesthetics, were only associated with more NB-PA for individuals without health-related problems or with a higher level of education.
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Background: The aim of the study was to test the 12-month effects of a multicomponent physical activity (PA) intervention at schoolyards on morning recess PA levels of sixth- and seventh-grade children in primary schools, using accelerometry and additional global positioning system data. Methods: A quasi-experimental study design was used with 20 paired intervention and control schools. Global positioning system confirmatory analyses were applied to validate attendance at schoolyards during recess. Accelerometer data from 376 children from 7 pairs of schools were included in the final analyses. Pooled intervention effectiveness was tested by multilevel linear regression analyses, whereas effectiveness of intervention components was tested by multivariate linear regression analyses. Results: Children exposed to the multicomponent intervention increased their time spent in light PA (+5.9%) during recess. No pooled effects on moderate to vigorous PA were found. In-depth analyses of intervention components showed that physical schoolyard interventions particularly predicted a decrease in time spent in sedentary behavior during recess at follow-up. Intervention intensity and the school’s commitment to the project strengthened this effect. Conclusions: The multicomponent schoolyard PA intervention was effective in making children spend a larger proportion of recess time in light PA, which was most likely the result of a shift from sedentary behavior to light PA.
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Background: The worldwide increase in the rates of childhood overweight and physical inactivity requires successful prevention and intervention programs for children. The aim of the Active Living project is to increase physical activity and decrease sedentary behavior of Dutch primary school children by developing and implementing tailored, multicomponent interventions at and around schools. Methods/design: In this project, school-centered interventions have been developed at 10 schools in the south of the Netherlands, using a combined top-down and bottom-up approach in which a research unit and a practice unit continuously interact. The interventions consist of a combination of physical and social interventions tailored to local needs of intervention schools. The process and short- and long-term effectiveness of the interventions will be evaluated using a quasi-experimental study design in which 10 intervention schools are matched with 10 control schools. Baseline and follow-up measurements (after 12 and 24 months) have been conducted in grades 6 and 7 and included accelerometry, GPS, and questionnaires. Primary outcome of the Active Living study is the change in physical activity levels, i.e. sedentary behavior (SB), light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and counts-per-minute (CPM). Multilevel regression analyses will be used to assess the effectiveness of isolated and combined physical and social interventions on children’s PA levels. Discussion: The current intervention study is unique in its combined approach of physical and social environmental PA interventions both at school(yard)s as well as in the local neighborhood around the schools. The strength of the study lies in the quasi-experimental design including objective measurement techniques, i.e. accelerometry and GPS, combined with more subjective techniques, i.e. questionnaires, implementation logbooks, and neighborhood observations. LinkedIn: https://www.linkedin.com/in/sanned/
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BACKGROUND: Although enhancing physical activity (PA) is important to improve physical and/or cognitive recovery, little is known about PA of patients admitted to an inpatient rehabilitation setting. Therefore, this study assessed the quantity, nature and context of inpatients PA admitted to a rehabilitation center. METHODOLOGY/PRINICIPAL FINDINGS: Prospective observational study using accelerometry & behavioral mapping. PA of patients admitted to inpatient rehabilitation was measured during one day between 7.00-22.00 by means of 3d-accelerometery (Activ8; percentage of sedentary/active time, number of sedentary/active bouts (continuous period of ≥1 minute), and active/sedentary bout lengths and behavioral mapping. Behavioral mapping consisted of observations (every 20 minutes) to assess: type of activity, body position, social context and physical location. Descriptive statistics were used to describe PA on group and individual level. At median the 15 patients spent 81% (IQR 74%-85%) being sedentary. Patients were most sedentary in the evening (maximum sedentary bout length minutes of 69 (IQR 54-95)). During 54% (IQR 50%-61%) of the observations patients were alone) and in their room (median 50% (IQR 45%-59%)), but individual patterns varied widely. CONCLUSION/SIGNIFICANCE: The results of this study enable a deeper understanding of the daily PA patterns of patients admitted for inpatient rehabilitation treatment. PA patterns of patients differ in both quantity, day structure, social and environmental contexts. This supports the need for individualized strategies to support PA behavior during inpatient rehabilitation treatment.
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BACKGROUND: Ambulatory children with Spina Bifida (SB) often show a decline in physical activity leading to deconditioning and functional decline. Therefore, assessment and promotion of physical activity is important. Because energy expenditure during activities is higher in these children, the use of existing pediatric equations to predict physical activity energy expenditure (PAEE) may not be valid. AIMS: (1) To evaluate criterion validity of existing predictions converting accelerocounts into PAEE in ambulatory children with SB and (2) to establish new disease-specific equations for PAEE. METHODS: Simultaneous measurements using the Actical, the Actiheart, and indirect calorimetry took place to determine PAEE in 26 ambulatory children with SB. DATA ANALYSIS: Paired T-tests, Intra-class correlations limits of agreement (LoA), and explained variance (R2) were used to analyze validity of the prediction equations using true PAEE as criterion. New equations were derived using regression techniques. RESULTS: While T-tests showed no significant differences for some models, the predictions developed in healthy children showed moderate ICC’s and large LoA with true PAEE. The best regression models to predict PAEE were: PAEE = 174.049 + 3.861 × HRAR – 60.285 × ambulatory status (R2 = 0.720) and PAEE = 220.484 + 0.67 × Actical counts – 60.717 × ambulatory status (R2 = 0.681). CONCLUSIONS: Existing equations to predict PAEE are not valid for use in children with SB for the individual evaluation of PAEE. The best regression model was based on HRAR in combination with ambulatory status, followed by a new model for the Actical monitor. A benefit of HRAR is that it does not require the use of expensive accelerometry equipment. Further cross-validation of these models is still needed.
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Movement behaviors, that is, both physical activity and sedentary behavior, are independently associated with health risks. Although both behaviors have been investigated separately in people after stroke, little is known about the combined movement behavior patterns, differences in these patterns between individuals, or the factors associated with these patterns. Therefore, the objectives of this study are (1) to identify movement behavior patterns in people with first-ever stroke discharged to the home setting and (2) to explore factors associated with the identified patterns.
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Purpose (1) To investigate the differences in the course of participation up to one year after stroke between distinct movement behavior patterns identified directly after discharge to the home setting, and (2) to investigate the longitudinal association between the development of movement behavior patterns over time and participation after stroke. Materials and methods 200 individuals with a first-ever stroke were assessed directly after discharge to the home setting, at six months and at one year. The Participation domain of the Stroke Impact Scale 3.0 was used to measure participation. Movement behavior was objectified using accelerometry for 14 days. Participants were categorized into three distinct movement behavior patterns: sedentary exercisers, sedentary movers and sedentary prolongers. Generalized estimating equations (GEE) were performed. Results People who were classified as sedentary prolongers directly after discharge was associated with a worse course of participation up to one year after stroke. The development of sedentary prolongers over time was also associated with worse participation compared to sedentary exercisers. Conclusions The course of participation after stroke differs across distinct movement behavior patterns after discharge to the home setting. Highly sedentary and inactive people with stroke are at risk for restrictions in participation over time. Implications for rehabilitation The course of participation in people with a first-ever stroke up to one year after discharge to the home setting differed based on three distinct movement behavior patterns, i.e., sedentary exercisers, sedentary movers and sedentary prolongers. Early identification of highly sedentary and inactive people with stroke after discharge to the home setting is important, as sedentary prolongers are at risk for restrictions in participation over time. Supporting people with stroke to adapt and maintain a healthy movement behavior after discharge to the home setting could prevent potential long-term restrictions in participation.
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Background/Objectives: Homecare staff often take over activities instead of “doing activities with” clients, thereby hampering clients from remaining active in daily life. Training and supporting staff to integrate reablement into their working practices may reduce clients' sedentary behavior and improve their independence. This study evaluated the effectiveness of the “Stay Active at Home” (SAaH) reablement training program for homecare staff on older homecare clients' sedentary behavior. Design: Cluster randomized controlled trial (c-RCT). Setting: Dutch homecare (10 nursing teams comprising a total of 313 staff members). Participants: 264 clients (aged ≥65 years). Intervention: SAaH seeks to equip staff with knowledge, attitude, and skills on reablement, and to provide social and organizational support to implement reablement in homecare practice. SAaH consists of program meetings, practical assignments, and weekly newsletters over a 9-month period. The control group received no additional training and delivered care as usual. Measurements: Sedentary behavior (primary outcome) was measured using tri-axial wrist-worn accelerometers. Secondary outcomes included daily functioning (GARS), physical functioning (SPPB), psychological functioning (PHQ-9), and falls. Data were collected at baseline and at 12 months; data on falls were also collected at 6 months. Intention-to-treat analyses using mixed-effects linear and logistic regression were performed. Results: We found no statistically significant differences between the study groups for sedentary time expressed as daily minutes (adjusted mean difference: β 18.5 (95% confidence interval [CI] 22.4, 59.3), p = 0.374) and as proportion of wake/wear time (β 0.6 [95% CI 1.5, 2.6], p = 0.589) or for most secondary outcomes. Conclusion: Our c-RCT showed no evidence for the effectiveness of SAaH for all client outcomes. Refining SAaH, by adding components that intervene directly on homecare clients, may optimize the program and require further research. Additional research should explore the effectiveness of SAaH on behavioral determinants of clients and staff and cost-effectiveness.
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The majority of studies investigating associations between physical activity and mental health in adolescents have been cross-sectional in design. Potential associations between physical activity and mental health may be better examined longitudinally as physical activity levels tend to decrease in adolescence. Few studies have investigated these associations longitudinally in adolescents and none by measuring physical activity objectively. A total of 158 Dutch adolescents (mean age 13.6 years, 38.6 % boys, grades 7 and 9 at baseline) participated in this longitudinal study. Physical activity, depressive symptoms and self-esteem were measured at baseline and at the 1-year follow-up. Physical activity was objectively measured with an ActivPAL3™ accelerometer during one full week. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale (CES-D) and self-esteem was assessed with the Rosenberg Self-Esteem Scale (RSE). Results were analysed using structural equation modelling.
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