Feasibility of a Virtual Health-Promoting Intervention (Choose to Move) for Older Adults: A Rapid Adaptation in Response to COVID-19.

To support older adults during the first wave of COVID-19, we rapidly adapted our effective health-promoting intervention (Choose to Move [CTM]) for virtual delivery in British Columbia, Canada. The intervention was delivered (April-October 2020) to 33 groups of older adults ("programs") who were a convenience sample (had previously completed CTM in person; n = 153; 86% female; 73 [6] years). We compared implementation outcomes (recruitment, dose received, retention, and completion of virtual data collection) to predetermined feasibility targets. We assessed mobility, physical activity, and social health outcomes pre- and postintervention (3 months) with validated surveys. We met most (dose received, retention, and virtual data collection), but not all (recruitment), feasibility targets. Approximately two thirds of older adults maintained or improved mobility, physical activity, and social health outcomes at 3 months. It was feasible to implement and evaluate CTM virtually. In future, virtual CTM could help us reach homebound older adults and/or serve as support during public health emergencies.

What is the 'voltage drop' when an effective health promoting intervention for older adults-Choose to Move (Phase 3)-Is implemented at broad scale?

BACKGROUND: Choose to Move (CTM), an effective health-promoting intervention for older adults, was scaled-up across British Columbia, Canada. Adaptations that enable implementation at scale may lead to 'voltage drop'-diminished positive effects of the intervention. For CTM Phase 3 we assessed: i. implementation; ii. impact on physical activity, mobility, social isolation, loneliness and health-related quality of life (impact outcomes); iii. whether intervention effects were maintained; iv) voltage drop, compared with previous CTM phases. METHODS: We conducted a type 2 hybrid effectiveness-implementation pre-post study of CTM; older adult participants (n = 1012; mean age 72.9, SD = 6.3 years; 80.6% female) were recruited by community delivery partners. We assessed CTM implementation indicators and impact outcomes via survey at 0 (baseline), 3 (mid-intervention), 6 (end-intervention) and 18 (12-month follow-up) months. We fitted mixed-effects models to describe change in impact outcomes in younger (60-74 years) and older (≥ 75 years) participants. We quantified voltage drop as percent of effect size (change from baseline to 3- and 6-months) retained in Phase 3 compared with Phases 1-2. RESULTS: Adaptation did not compromise fidelity of CTM Phase 3 as program components were delivered as intended. PA increased during the first 3 months in younger (+1 days/week) and older (+0.9 days/week) participants (p<0.001), and was maintained at 6- and 18-months. In all participants, social isolation and loneliness decreased during the intervention, but increased during follow-up. Mobility improved during the intervention in younger participants only. Health-related quality of life according to EQ-5D-5L score did not change significantly in younger or older participants. However, EQ-5D-5L visual analog scale score increased during the intervention in younger participants (p<0.001), and this increase was maintained during follow-up. Across all outcomes, the median difference in effect size, or voltage drop, between Phase 3 and Phases 1-2 was 52.6%. However, declines in social isolation were almost two times greater in Phase 3, compared with Phases 1-2. CONCLUSION: Benefits of health-promoting interventions-like CTM-can be retained when implemented at broad scale. Diminished social isolation in Phase 3 reflects how CTM was adapted to enhance opportunities for older adults to socially connect. Thus, although intervention effects may be reduced at scale-up, voltage drop is not inevitable.

'We just don't have this in us ': Understanding factors behind low levels of physical activity in South Asian immigrants in Metro-Vancouver, Canada.

BACKGROUND: South Asian immigrants in western countries are at a high risk for metabolic syndrome and associated chronic disease. While a physically active lifestyle is crucial in decreasing this risk, physical activity (PA) levels among this group remain low. The objectives of this study were to explore social and cultural factors that influence PA behavior, investigate how immigration process intersects with PA behaviors to influence PA levels and to engage community in a discussion about what can be done to increase PA in the South Asian community. METHODS: For this qualitative study, we conducted four Focus Group Discussions (FGDs) among a subset of participants who were part of a larger study. FGD data was coded and analysed using directed content analysis to identify key categories. RESULTS: Participants expressed a range of opinions, attitudes and beliefs about PA. Most believed they were sufficiently active. Women talked about restrictive social and cultural norms that discouraged uptake of exercise. Post-immigration levels of PA were low due to change in type of work and added responsibilities. CONCLUSION: Health promoters need to consider social, cultural, and structural contexts when exploring possible behavior change interventions for South Asian immigrants.

Device-worn measures of sedentary time and physical activity in South Asian adults at high risk for type 2 diabetes in Metro-Vancouver, Canada.

BACKGROUND: South Asians have high incidence of chronic disease. Physical activity (PA) and sedentary time are modifiable risk factors for chronic disease but their assessment in South Asians has been primarily based on self-report. This study presents directly-measured PA and sedentary time in South Asian adults in Canada. METHODS: A subset of 100 South Asian participants from a larger study who were identified at being at a higher risk for type 2 diabetes wore Actical accelerometers for 7 days. Anthropometric measures were taken and socio-demographic factors including age, income, education level, years since immigration, presence of children under the age of 12 years in the household and employment status were self-reported. RESULTS: Ninety-one participants (mean age 65.6 years) provided valid accelerometer data. Participants accumulated mean 673.5 (95% CI: 656.6, 691.0) min/day sedentary time, 130.5 (95% CI: 117.3, 145.3) min/day light PA (LPA) and 2.3 (95% CI: 1.3, 4.2) min/day moderate-to-vigorous PA (MVPA). For sedentary time and LPA, sex and BMI explained 51% of variability. For MVPA, BMI, season of assessment and employment status explained 23% variability with those who were employed accumulating significantly higher mean min/day of MVPA compared to those who were unemployed; (5.8, 95% CI: 1.5, 21.7) vs (1.5, 95% CI: 5.3, 20.0) respectively. CONCLUSION: High sedentary time, and low MVPA indicates the need to focus health promotion efforts on shifting sedentary time into LPA while trying to increase MVPA. Future studies need to be based on larger, representative samples of South Asians.

Pragmatic Evaluation of Older Adults' Physical Activity in Scale-Up Studies: Is the Single-Item Measure a Reasonable Option?

Convergent validity and responsiveness to change of the single-item physical activity measure were assessed in adults aged 60 years and older, at baseline (n = 205) and 6 months (n = 177) of a health promotion program, Choose to Move. Spearman correlations were used to examine associations between physical activity as measured by the single-item measure and the Community Health Activities Model Program for Seniors (CHAMPS) questionnaire at baseline and for 6-month change in all participants and for sex and age (60-74 years, and ≥75 years) subgroups. Effect size assessed responsiveness to change in physical activity for both tools. Baseline physical activity by the single-item measure correlated moderately with physical activity by the CHAMPS questionnaire in all participants and subgroups. Correlations were weaker for change in physical activity. Effect size for physical activity change was larger for the single-item measure than for the CHAMPS questionnaire. The single-item measure is a valid, pragmatic tool for use in intervention and scale-up studies with older adults.

Status Quo or Drop-Off: Do Older Adults Maintain Benefits From Choose to Move-A Scaled-Up Physical Activity Program-12 Months After Withdrawing the Intervention?

BACKGROUND: Choose to Move is one of few scaled-up health-promoting interventions for older adults. The authors evaluated whether Choose to Move participants maintained their intervention-related gains in physical activity (PA), mobility, and social connectedness 12 months after the intervention ended. METHODS: The authors assessed PA, mobility, loneliness, social isolation, and muscle strength via questionnaire and objective measures in 235 older adults at 0 months (baseline), 6 months (end of intervention), and 18 months (12-months postintervention). The authors fitted linear mixed models to examine the change in each outcome from 6 to 18 months (primary objective) and 0 to 18 months (secondary objective) and reported by age group (60-74 and ≥75 y). RESULTS: In younger participants, PA decreased between 6 and 18 months, but remained significantly higher than at baseline. Intervention-related benefits in loneliness, social isolation, mobility, and muscle strength were maintained between 6 and 18 months in the younger participants. Older participants maintained their intervention benefits in loneliness, mobility, and muscle strength. When compared with baseline values, PA levels in older participants were unchanged, whereas social isolation increased. CONCLUSIONS: Older adults maintained some, but not all, health benefits of Choose to Move 12 months after the intervention ended. Long-term commitments are needed to deliver effective health-promoting interventions for older adults if benefits are to be maintained.

Scaling up Action Schools! BC: How Does Voltage Drop at Scale Affect Student Level Outcomes? A Cluster Randomized Controlled Trial.

Action Schools! BC (AS! BC) was scaled-up from an efficacy trial to province-wide delivery across 11 years (2004-2015). In this study we: (1) describe strategies that supported implementation and scale-up; (2) evaluate implementation (teachers' physical activity (PA) delivery) and student's PA and cardiorespiratory fitness (CRF) within a cluster randomized controlled trial during years 2 and 3 of scale-up; and (3) assess relationships between teacher-level implementation and student-level outcomes. We classified implementation strategies as process, capacity-building or scale-up strategies. Elementary schools (n = 30) were randomized to intervention (INT; 16 schools; 747 students) or usual practice (UP; 14 schools; 782 students). We measured teachers' PA delivery (n = 179) using weekly logs; students' PA by questionnaire (n = 30 schools) and accelerometry (n = 9 schools); and students' CRF by 20-m shuttle run (n = 25 schools). INT teachers delivered more PA than UP teachers in year 1 (+33.8 min/week, 95% CI 12.7, 54.9) but not year 2 (+18.8 min/week, 95% CI -0.8, 38.3). Unadjusted change in CRF was 36% and 27% higher in INT girls and boys, respectively, compared with their UP peers (year 1; effect size 0.28-0.48). Total PA delivered was associated with change in children's self-reported MVPA (year 1; r = 0.17, p = 0.02). Despite the 'voltage drop', scaling-up school-based PA models is feasible and may enhance children's health. Stakeholders must conceive of new ways to effectively sustain scaled-up health promoting interventions if we are to improve the health of students at a population level. Clinical Trials registration: NCT01412203.

"It makes me feel not so alone": features of the Choose to Move physical activity intervention that reduce loneliness in older adults.

BACKGROUND: Despite the well-known health benefits of physical activity (PA), older adults are the least active citizens. Older adults are also at risk for loneliness. Given that lonely individuals are at risk for accelerated loss of physical functioning and health with age, PA interventions that aim to enhance social connectedness may decrease loneliness and increase long-term PA participation. The objectives of this mixed-method study are to: (1) evaluate whether an evidence-based PA intervention (Choose to Move; CTM) influenced PA and loneliness differently among self-identified 'lonely' versus 'not lonely' older adults and (2) to describe factors within CTM components most likely to promote social connectedness/reduce loneliness. METHODS: CTM is a flexible, scalable, community-based health promoting physical activity intervention for older adults. Two community delivery partner organizations delivered 56 CTM programs in 26 urban locations across British Columbia. We collected survey data from participants (n = 458 at baseline) at 0 (baseline), 3 (mid-intervention) and 6 (post-intervention) months. We conducted in depth interviews with a subset of older adults to understand how CTM facilitated or impeded their PA and social connectedness. RESULTS: PA increased significantly from baseline to 3 months in lonely and not lonely participants. PA decreased significantly from 3 to 6 months in lonely participants; however, PA at 6 months remained significantly above baseline levels in both groups. Loneliness decreased significantly from baseline to 3 and 6 months in participants identifying as lonely at baseline. Factors within CTM components that promote social connectedness/reduce loneliness include: Activity coach characteristics/personality traits and approaches; opportunity to share information and experiences and learn from others; engagement with others who share similar/familiar experiences; increased opportunity for meaningful interaction; and accountability. CONCLUSION: Health promoting interventions that focus on PA and social connectedness through group-based activities can effectively reduce social isolation and loneliness of older adults. Given the 'epidemic of loneliness' that plagues many countries currently, these kinds of interventions are timely and important. Research that further delineates mechanisms (e.g., sharing experiences vs. lectures), that modify the effect of an intervention on social connectedness outcomes for older adults engaged in community-based PA programs would be a welcome addition to the literature.

Physical activity is good for older adults-but is programme implementation being overlooked? A systematic review of intervention studies that reported frameworks or measures of implementation.

OBJECTIVE: To examine older adult physical activity (PA) intervention studies that evaluated implementation and/or scale-up. Research question 1: What implementation and/or scale-up indicators (specific, observable and measurable characteristics that show the progress of implementation) were reported? Research question 2: What implementation and/or scale-up frameworks were reported? Research question 3: Did studies evaluate the relationship between implementation or scale-up of the intervention and individual level health/behaviour outcomes? If yes, how? DESIGN: Systematic review. DATA SOURCES: Publications from electronic databases and hand searches (2000 to December 2019). ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Any PA intervention studies with community-dwelling older adult participants (mean age ≥60 years). Required indicators: (a) Must report amount of PA as an outcome, with validated self-report or objective measures, and (b) Must have reported at least one implementation or scale-up framework and/or one implementation or scale-up indicator. RESULTS: 137 studies were included for research question 1, 11 for question 2 and 22 for question 3. 137 studies reported an implementation indicator: 14 unique indicators. None were specified as indicators for scale-up evaluation. 11 studies were guided by an implementation or scale-up framework. 22 studies described a relationship between an implementation indicator and an individual-level health outcome. CONCLUSION: There is need for implementation research that extends beyond analysis at the individual level, includes clearly defined indicators and provides a guiding framework to support PA initiatives in older adults. Such implementation studies should evaluate factors in the broader context (eg,political, environmental) that influence scale-up. PROSPERO REGISTRATION: CRD42018091839.

Factors that influence implementation at scale of a community-based health promotion intervention for older adults.

BACKGROUND: Despite the many known benefits of physical activity (PA), relatively few older adults are active on a regular basis. Older adult PA interventions delivered in controlled settings showed promising results. However, to achieve population level health impact, programs must be effectively scaled-up, and few interventions have achieved this. To effectively scale-up it is essential to identify contextual factors that facilitate or impede implementation at scale. Our aim is to describe factors that influence implementation at scale of a health promotion intervention for older adults (Choose to Move). This implementation evaluation complements our previously published study that assessed the impact of Choose to Move on older adult health indicators. METHODS: To describe factors that influenced implementation our evaluation targeted five distinct levels across a socioecological continuum. Four members of our project team conducted semi-structured interviews by telephone with 1) leaders of delivery partner organizations (n = 13) 2) recreation managers (n = 6), recreation coordinators (n = 27), activity coaches (n = 36) and participants (n = 42) [August 2015 - April 2017]. Interviews were audio-recorded and professionally transcribed and data were analyzed using framework analysis. RESULTS: Partners agreed on the timeliness and need for scaled-up evidence-based health promotion programs for older adults. Choose to Move aligned with organizational priorities, visions and strategic directions and was deemed easy to deliver, flexible and adaptable. Partners also noted the critical role played by our project team as the support unit. However, partners noted availability of financial resources as a potential barrier to sustainability. CONCLUSIONS: Even relatively simple evidence-based interventions can be challenging to scale-up and sustain. To ensure successful implementation it is essential to align with multilevel socioecological perspectives and assess the vast array of contextual factors that are at the core of better understanding successful implementation.

Implementation and scale-up of physical activity and behavioural nutrition interventions: an evaluation roadmap.

BACKGROUND: Interventions that work must be effectively delivered at scale to achieve population level benefits. Researchers must choose among a vast array of implementation frameworks (> 60) that guide design and evaluation of implementation and scale-up processes. Therefore, we sought to recommend conceptual frameworks that can be used to design, inform, and evaluate implementation of physical activity (PA) and nutrition interventions at different stages of the program life cycle. We also sought to recommend a minimum data set of implementation outcome and determinant variables (indicators) as well as measures and tools deemed most relevant for PA and nutrition researchers. METHODS: We adopted a five-round modified Delphi methodology. For rounds 1, 2, and 3 we administered online surveys to PA and nutrition implementation scientists to generate a rank order list of most commonly used; i) implementation and scale-up frameworks, ii) implementation indicators, and iii) implementation and scale-up measures and tools. Measures and tools were excluded after round 2 as input from participants was very limited. For rounds 4 and 5, we conducted two in-person meetings with an expert group to create a shortlist of implementation and scale-up frameworks, identify a minimum data set of indicators and to discuss application and relevance of frameworks and indicators to the field of PA and nutrition. RESULTS: The two most commonly referenced implementation frameworks were the Framework for Effective Implementation and the Consolidated Framework for Implementation Research. We provide the 25 most highly ranked implementation indicators reported by those who participated in rounds 1-3 of the survey. From these, the expert group created a recommended minimum data set of implementation determinants (n = 10) and implementation outcomes (n = 5) and reconciled differences in commonly used terms and definitions. CONCLUSIONS: Researchers are confronted with myriad options when conducting implementation and scale-up evaluations. Thus, we identified and prioritized a list of frameworks and a minimum data set of indicators that have potential to improve the quality and consistency of evaluating implementation and scale-up of PA and nutrition interventions. Advancing our science is predicated upon increased efforts to develop a common 'language' and adaptable measures and tools.

Estimation of Peak Muscle Power From a Countermovement Vertical Jump in Children and Adolescents.

Gomez-Bruton, A, Gabel, L, Nettlefold, L, Macdonald, H, Race, D, and McKay, H. Estimation of peak muscle power from a countermovement vertical jump in children and adolescents. J Strength Cond Res 33(2): 390-398, 2019-Several equations to predict muscle power (MP) from vertical jump height (VJH) have been developed in adults. However, few have been derived in children. We therefore aimed to: (a) evaluate the validity of existing MP estimation equations from a vertical countermovement jump (CMJ) in children and adolescents and (b) develop and validate a new MP estimation equation for use in children and adolescents. We measured peak MP (in watts) and VJH (in centimeters) during a CMJ using a force platform in 249 children and adolescents (9-17 years; 119 boys and 130 girls). We compared actual (force platform) with predicted (12 existing prediction equations) MP using repeated-measures analysis of variance and estimated bias using modified Bland-Altman plots. We developed a new prediction equation using stepwise linear regression, assessed predictive error using leave-one-out and 10-fold cross-validation, and externally validated the equation in an independent sample (n = 100). All existing prediction equations demonstrated some degree of bias, either systematic bias (mean differences ranging 178-1,377 W; 8-64%) or bias at the extremes or interactions with sex. Our new prediction equation estimates MP from VJH and body mass: Power (W) = 54.2 × VJH (cm) + 34.4 × body mass (kg) - 1,520.4. With this new equation, there was no difference between actual and predicted MP (0%) and negligible differences (0.2-0.9%) in R and root mean square error between our observed and cross-validated sets. Actual and predicted MP were not different in our external validation (p = 0.12). The new equation demonstrates excellent validity and can be used to predict MP from a CMJ in children and adolescents.

Implementation of a co-designed physical activity program for older adults: positive impact when delivered at scale.

BACKGROUND: Despite known health benefits of physical activity (PA), older adults remain among the least physically active age group globally with 30-60% not meeting guidelines. In Canada, 87% do not meet recommended guidelines. To influence population health, interventions that are effective in small trials must be disseminated at scale. Despite evidence for efficacy, few PA interventions are scaled up to reach the wider community. In 2015, British Columbia (BC) Ministry of Health released a PA strategy where older adults were identified as a priority. In partnership with the Ministry, the Active Aging Research Team co-created a health promotion program called Choose to Move (CTM). CTM will be implemented in three phases at increasingly greater scale across BC. The objective of this study is to evaluate the effectiveness of CTM during Phase I (pilot) and Phase II (initial scale up) on PA, mobility, and social connectedness among older adults in BC, Canada. METHODS: We used a type 2 hybrid effectiveness-implementation study design, and herein focus on effectiveness. The implementation evaluation will be published as a companion paper elsewhere. Two community delivery partner organizations delivered 56 CTM programs in 26 large and small urban locations across BC. Outcome measurement occurred at 0 (baseline), 3 (mid-intervention) and 6 (post-intervention) months. We collected survey data from all participants (n = 458; province-wide) and also conducted a subset evaluation (n = 209). RESULTS: PA increased significantly during the active intervention phase (baseline-3 months) in younger (60-74 yrs.; + 1.6 days/week; p < 0.001) and older (≥75 yrs.; + 1.0 days/week; p < 0.001) participants. The increase was sustained at 6 months in younger participants only, who remained significantly more active than at baseline (+ 1.4 days/week; p < 0.001). Social exclusion indicators declined significantly in the younger group. Mobility and strength improved significantly at 3 months in the younger group, and in both groups at 6 months. CONCLUSIONS: CTM adopted central tenets of implementation science that consider the complicated systems where interventions are delivered to improve public health. In this iteration of CTM we demonstrate that a partner-based health promotion intervention can be effectively implemented across settings to enhance PA, mobility and social connectedness in older adults.

Sex-, Ethnic-, and Age-Specific Centile Curves for pQCT- and HR-pQCT-Derived Measures of Bone Structure and Strength in Adolescents and Young Adults.

There are presently no adolescent centile curves for bone parameters at the tibial midshaft using peripheral quantitative computed tomography (pQCT) or at the distal radius and tibia using high-resolution pQCT (HR-pQCT). Thus, we aimed to develop sex-, ethnic-, site-, and age-specific centile curves for pQCT and HR-pQCT-derived bone outcomes for youth and young adults aged 10 to 21 years. We acquired pQCT scans (XCT3000 or XCT2000) at the tibial midshaft (50% site) and HR-pQCT scans (XtremeCT) at the distal radius (7% site) and tibia (8% site) in a convenience sample of participants in the mixed-longitudinal University of British Columbia Healthy Bones III Study. We scanned 778 10- to 21-year-olds annually for a maximum of 11 years using pQCT (413 girls, 56% Asian; 365 boys, 54% Asian; n = 3160 observations) and 349 10- to 21-year-olds annually for a maximum of 4 years using HR-pQCT (189 girls, 51% Asian; 165 boys, 50% Asian; n = 1090 observations). For pQCT, we report cortical bone mineral density (BMD), total bone cross-sectional area, and polar strength-strain index. For HR-pQCT, we report standard measures (total BMD, trabecular number, thickness, and bone volume fraction) and automated segmentation measures (total bone cross-sectional area, cortical BMD, porosity, and thickness). We applied finite element analysis to estimate failure load. We applied the lamda, mu, sigma (LMS) method using LMS ChartMaker Light (version 2.5, The Institute of Child Health, London, UK) to construct LMS tables and centile plots. We report sex- and age-specific centiles (3rd, 10th, 25th, 50th, 75th, and 97th) for whites and Asians for pQCT bone parameters at the tibial midshaft and HR-pQCT bone parameters at the distal radius and tibia. These centile curves might be used by clinicians and scientists to interpret values or better understand trajectories of bone parameters in clinical populations, those from different geographic regions or of different ethnic origins. © 2018 American Society for Bone and Mineral Research.

Bouts of Vigorous Physical Activity and Bone Strength Accrual During Adolescence.

PURPOSE: We examined the influence of vigorous physical activity (VPA) bout frequency on bone strength accrual across adolescence, independent of total volume of VPA. METHODS: We measured VPA (6 metabolic equivalents; total volume and bout frequency <5 min in duration) annually using waist-worn accelerometers (ActiGraph GT1M) in 309 adolescents (9-20 y at baseline: 99, <13 y; 126, 13-18 y; 84, >18 y) over a maximum of 4 years. We applied finite element analysis to high-resolution peripheral quantitative computed tomography scans of the distal tibia (8% site) to estimate bone strength (failure load; F.Load, Newtons). We fit a mixed effects model with maturity offset (years from age at peak height velocity) as a random effect and sex, ethnicity, tibia length, lean body mass, and VPA (volume and bout frequency) as fixed effects. RESULTS: VPA volume and bout frequency were positively associated with F.Load across adolescence; however, VPA volume did not predict F.Load once VPA bout frequency was included in the model. Participants in the upper quartile of VPA bout frequency (∼33 bouts per day) had 10% (500 N) greater F.Load across adolescence compared with participants in the lowest quartile (∼9 bouts per day; P = .012). Each additional daily bout of VPA was associated with 21 N greater F.Load, independent of total volume of VPA. CONCLUSION: Frequent VPA should be promoted for optimal bone strength accrual.

Physical Activity, Sedentary Time, and Bone Strength From Childhood to Early Adulthood: A Mixed Longitudinal HR-pQCT study.

Bone strength is influenced by bone geometry, density, and bone microarchitecture, which adapt to increased mechanical loads during growth. Physical activity (PA) is essential for optimal bone strength accrual; however, less is known about how sedentary time influences bone strength and its determinants. Thus, our aim was to investigate the prospective associations between PA, sedentary time, and bone strength and its determinants during adolescence. We used HR-pQCT at distal tibia (8% site) and radius (7% site) in 173 girls and 136 boys (aged 9 to 20 years at baseline). We conducted a maximum of four annual measurements at the tibia (n = 785 observations) and radius (n = 582 observations). We assessed moderate-to-vigorous PA (MVPA) and sedentary time with accelerometers (ActiGraph GT1M). We aligned participants on maturity (years from age at peak height velocity) and fit a mixed-effects model adjusting for maturity, sex, ethnicity, leg muscle power, lean mass, limb length, dietary calcium, and MVPA in sedentary time models. MVPA was a positive independent predictor of bone strength (failure load [F.Load]) and bone volume fraction (BV/TV) at the tibia and radius, total area (Tt.Ar) and cortical porosity (Ct.Po) at the tibia, and negative predictor of load-to-strength ratio at the radius. Sedentary time was a negative independent predictor of Tt.Ar at both sites and Ct.Po at the tibia and a positive predictor of cortical thickness (Ct.Th), trabecular thickness (Tb.Th), and cortical bone mineral density (Ct.BMD) at the tibia. Bone parameters demonstrated maturity-specific associations with MVPA and sedentary time, whereby associations were strongest during early and mid-puberty. Our findings support the importance of PA for bone strength accrual and its determinants across adolescent growth and provide new evidence of a detrimental association of sedentary time with bone geometry but positive associations with microarchitecture. This study highlights maturity-specific relationships of bone strength and its determinants with loading and unloading. Future studies should evaluate the dose-response relationship and whether associations persist into adulthood. © 2017 American Society for Bone and Mineral Research.

The Influence of Epoch Length on Physical Activity Patterns Varies by Child's Activity Level.

PURPOSE: Patterns of physical activity (PA) and sedentary time, including volume of bouted activity, are important health indicators. However, the effect of accelerometer epoch length on measurement of these patterns and associations with health outcomes in children remain unknown. METHOD: We measured activity patterns in 308 children (52% girls, age range = 8-11 years) using ActiGraph GT1M accelerometers with 15-s epochs and reintegrated to 60-s epochs. We calculated the volume (minutes per day) of moderate-to-vigorous PA (MVPA), sedentary time, light, moderate, and vigorous PA, as well as bouted MVPA and sedentary time (0-5 min, 5-10 min, 10-20 min, and > 20 min). RESULTS: The difference between 15-s and 60-s epochs was statistically significant for all outcomes; however, effect sizes were small or negligible in 30% of comparisons. Bias ranged from 1.9 min/day (total MVPA) to 102.7 min/day (0-5 min sedentary bouts). Regression-based estimates of bias and 95% limits of agreement illustrated that the magnitude, and in some cases, the direction, of between-epoch differences varied with activity level. Correlations with body mass index and cardiovascular fitness were similar for 15-s (r = -.19 to .20) and 60-s (r = -.16 to .29) epochs. Estimated 15-s data (predicted from 60-s) were similar to measured data and had similar relationships with health outcomes. CONCLUSION: Epoch length influences measurement of PA and sedentary patterns and the effect is modified by activity level. However, associations with health outcomes were similar and epoch differences can be adjusted. Future research should clarify the accuracy of different epoch lengths for measuring bouted activity and evaluate whether epoch length alters relationships with additional health outcomes.

Reexamining the Surfaces of Bone in Boys and Girls During Adolescent Growth: A 12-Year Mixed Longitudinal pQCT Study.

We revisit Stanley Garn's theory related to sex differences in endocortical and periosteal apposition during adolescence using a 12-year mixed longitudinal study design. We used peripheral quantitative computed tomography to examine bone parameters in 230 participants (110 boys, 120 girls; aged 11.0 years at baseline). We assessed total (Tt.Ar, mm(2)), cortical (Ct.Ar, mm(2)), and medullary canal area (Me.Ar, mm(2)), Ct.Ar/Tt.Ar, cortical bone mineral density (Ct.BMD, mg/cm(3)), and polar strength-strain index (SSIp , mm(3)) at the tibial midshaft (50% site). We used annual measures of height and chronological age to identify age at peak height velocity (APHV) for each participant. We compared annual accrual rates of bone parameters between boys and girls, aligned on APHV using a linear mixed effects model. At APHV, boys demonstrated greater Tt.Ar (ratio = 1.27; 95% confidence interval [CI] 1.21, 1.32), Ct.Ar (1.24 [1.18, 1.30]), Me.Ar (1.31 [1.22, 1.40]), and SSIp (1.36 [1.28, 1.45]) and less Ct.Ar/Tt.Ar (0.98 [0.96, 1.00]) and Ct.BMD (0.97 [0.96, 0.97]) compared with girls. Boys and girls demonstrated periosteal bone formation and net bone loss at the endocortical surface. Compared with girls, boys demonstrated greater annual accrual rates pre-APHV for Tt.Ar (1.18 [1.02, 1.34]) and Me.Ar (1.34 [1.11, 1.57]), lower annual accrual rates pre-APHV for Ct.Ar/Tt.Ar (0.56 [0.29, 0.83]) and Ct.BMD (-0.07 [-0.17, 0.04]), and similar annual accrual rates pre-APHV for Ct.Ar (1.10 [0.94, 1.26]) and SSIp (1.14 [0.98, 1.30]). Post-APHV, boys demonstrated similar annual accrual rates for Ct.Ar/Tt.Ar (1.01 [0.71, 1.31]) and greater annual accrual rates for all other bone parameters compared with girls (ratio = 1.23 to 2.63; 95% CI 1.11 to 3.45). Our findings support those of Garn and others of accelerated periosteal apposition during adolescence, more evident in boys than girls. However, our findings challenge the notion of greater endocortical apposition in girls, suggesting instead that girls experience diminished endocortical resorption compared with boys.

Implementation of school based physical activity interventions: a systematic review.

OBJECTIVE: Implementation science is an emerging area in physical activity (PA) research. We sought to establish the current state of the evidence related to implementation of school-based PA models to explore 1) the relationship between implementation and health outcomes, and 2) factors that influence implementation. METHODS: We searched 7 electronic databases (1995-2014) and included controlled studies of school-based PA programmes for healthy youth (6-18 y) measuring at least one physical health-related outcome. For objective 1, studies linked implementation level to student-level health outcome(s). For objective 2, studies reported factors associated with implementation. RESULTS: There was substantial variability in how health outcomes and implementation were assessed. Few studies linked implementation and health outcomes (n=15 interventions). Most (11/15) reported a positive relationship between implementation and at least one health outcome. Implementation factors were reported in 29 interventions. Of 22 unique categories, time was the most prevalent influencing factor followed by resource availability/quality and supportive school climate. CONCLUSIONS: Implementation evaluation supports scale-up of effective school-based PA interventions and thus population-level change. Our review serves as a call to action to 1) address the link between implementation and outcome within the school-based PA literature and 2) improve and standardize definitions and measurement of implementation.