Physical inactivity, sedentary behaviour, and poor sleep are growing concerns among primary school children, contributing to poorer cognitive, physical, and psychosocial health. Happy Homework, previously a paper-based homework intervention, was adapted into a digital format to engage children in improving their 24-hour movement behaviours at home. This study outlines a participatory design procedure used to co-design the digital app with key stakeholders to ensure it was user-centred, age-appropriate, and scalable. Three rounds of iterative co-design workshops were conducted with children (n = 11), teachers (n = 8), and parents (n = 9) who reviewed paper-based prototypes, and in the final workshop, the Happy Homework app on smartphones. Iteratively, we thematically coded the qualitative data generated by stakeholders in the co-design workshops to directly inform subsequent app design specifications. The co-design approach resulted in numerous stakeholder recommendations for software enhancements which were unforeseen by the research team. These included eighteen distinct software enhancements that led to changes in the content, navigation, incentives, and appearance of the app. Stakeholder involvement was essential for identifying usability and design concerns, and for outlining solutions unforeseen by the research team. Concerns identified in initial co-design workshops did not reoccur after changes were made to the app. As such we deem the co-design process invaluable in guiding the development of the Happy Homework app ensuring its features are relevant and aligned with stakeholder input. The refined app will undergo formal pilot testing to evaluate user experience and feasibility. N/A.

Children’s 24-h movement behaviours—physical activity, sedentary behaviour, and sleep—are critical to health and wellbeing, yet many fail to meet recommended daily guidelines. School-based health interventions offer a scalable approach to improve movement behaviours, though their impact may be limited by competing academic demands. Homework presents an opportunity to extend the reach of school-based health interventions into the home environment. Happy Homework (HH 2.0) was developed as a digital intervention to integrate movement-based activities into home routines. This pilot study evaluated the feasibility, acceptability, and usability of HH 2.0 among primary school children. An 8-week pilot cluster randomised controlled trial was conducted across four primary schools in the West of Scotland, with classes randomly allocated to intervention or control. Feasibility, usability, and acceptability were assessed using basic app-usage analytics and questionnaires completed by children, parents and teachers. Secondary outcomes included physical activity, sedentary behaviour and sleep measured via activPAL devices, which provided multiple posture- and movement-based metrics. Self-report sleep questionnaires were included, with children’s motivation measured through basic psychological need satisfaction questionnaires. Linear mixed-effects models examined group by time interactions, accounting for clustering by school and repeated measures. A total of 82 children aged 8–12 years were recruited (60

Background: Body composition, blood pressure, estimated maximal oxygen uptake (VO2max), lung function, physical activity, muscle architecture, and endothelial function had not previously been examined in people with young onset dementia. Therefore, the study measured these variables in a young onset dementia group, compared them to age-matched controls. Methods: Estimated VO2max (via the Astrand-Rhyming test), body composition, blood pressure, lung function (via spirometry), muscle architecture (via ultrasonography), and endothelial function (via flow-mediated dilation) were assessed. Physical activity was measured using ActiGraph accelerometers for 7 days. Results: We recruited 33 participants (16 young onset dementia, 17 controls). The young onset dementia group had shorter fascicle lengths of the vastus lateralis, were sedentary for longer over a 7-day period, and completed less moderate-vigorous physical activity than controls (P = .028, d = 0.81; large effect, P = .029, d = 0.54; moderate effect, and P = .014, d = 0.97; large effect, respectively for pairwise comparisons). Pairwise comparisons suggest no differences at the P < .05 level between young onset dementia and controls for estimated VO2max (despite a moderate effect size [d = 0.66]), height, body mass, BMI, blood pressure, light physical activity, lung function, muscle thickness, pennation angle, or endothelial function. Conclusions: This study highlights differences between people with young onset dementia and controls, underscoring the need for multicomponent exercise interventions. Future interventions should target muscle architecture, increase moderate-vigorous physical activity, and reduce sedentariness, with the goal of improving quality of life and promoting functional independence. (c) 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license

We aimed to explore the feasibility, acceptability, and potential efficacy of Happy Homework (HH); an 8-week home-focussed intervention, with the purpose of encouraging children's positive dietary behaviours and engagement in positive physical activity (PA) and sleep behaviours. We randomised four Scottish schools (n = 71 participants; 5 classrooms) to either the HH intervention (n = 2) or usual curriculum control group (n = 2). HH consisted of movement and dietary-focused parent and child tasks. Primary outcome measures were intervention feasibility, acceptability, and potential efficacy. Secondary outcomes were objectively measured PA via ActiGraph GT3X+, sedentary behaviours (SBs) and sleep duration via activPAL4™ accelerometers and dietary behaviours, fruit and vegetable consumption and screen-time via questionnaires. After controlling for pre-test levels, post intervention stepping time and sleep duration were significantly greater for the HH group in comparison to the control group. The HH group reported eating more fruit and vegetables at post-test than the control group. Participants also reported the intervention to be enjoyable and motivating. These findings provide promising evidence that given a greater sample size, better retention and the prioritisation of health and wellbeing homework, HH could enhance children's health and wellbeing.

Introduction: Management of difficult-to-treat asthma is particularly challenging in people with elevated body mass index (BMI). Our randomised controlled trial of pulmonary rehabilitation (PR) showed improved outcomes at 8 weeks. Here we assess immediate and one-year effects of asthma-tailored PR in participants with difficult-to-treat asthma and BMI >= 25 kg/m(2), and identify response predictors. Methods: A prospective observational study of PR, tailored to asthma, comparing outcomes at baseline (V1), immediately after 8 weeks of PR (V2), and at 1 year (V3). Baseline characteristics were compared in responders/non-responders defined by achievement of minimum clinically important difference (MCID) for asthma control questionnaire (ACQ6) (0.5) at 8 weeks and 1 year. Results: Of 92 participants, 56 attended V2 and 45 attended V3. Mean age was 60 (SD 13) years, 60% were female, and median (IQR) BMI was 33.8 (29.5- 38.7) kg/m(2). At V1, V2, and V3, respectively, there were significant differences in ACQ6 (mean (95% CI): 2.5 (2.1- 2.9), 2.2 (1.8- 2.5), and 2.3 (1.9- 2.7), p< 0.003), Borg breathlessness score post-6-minute walk test (median (IQR): 2 (0.5- 3), 1 (0- 2), and 1 (0.5- 2), p< 0.035), and annualised exacerbations requiring prednisolone (median (IQR): 3 (2- 5), 0 (0- 4.7), and 1.5 (0- 4.2), p< 0.003). A total of 27/56 (48%) had improvements >MCID for ACQ6 at V2 and 16 (33%) at V3. Participants with higher ACQ6 scores at baseline (suggesting poorer asthma control) were more likely to achieve MCID. Baseline BMI, within the range studied, was not predictive. Conclusion: Pulmonary rehabilitation induced improvements in asthma-related outcomes including perception of breathlessness, asthma control, and exacerbation frequency at 1 year. Those with poorer baseline asthma control were more likely to benefit.

Step counts can be estimated from wrist-worn accelerometers through the Verisense Step Count Algorithm. No study has assessed agreement between stepping metrics from ActiGraph accelerometers during free-living. Thirty-four participants (age: 22.9 ± 3.4 years) provided 24 h accelerometer data (non-dominant wrist) and waist. Agreement of two Verisense Algorithms (Verisense 1 & 2) for estimating daily steps, moderate-to-vigorous physical activity (MVPA), peak 1-min and 30-min accumulated steps, against the waist and ActiLife step-count Algorithm was assessed. Mean bias ± 95% limits of agreement (LoA) for daily steps was +1255 ± 3780 steps/day (mean absolute percent error (MAPE): 21%) (Verisense 1) and +1357 ± 3434 steps/day (MAPE: 20%) (Verisense 2). For peak 1-min accumulated steps, mean bias and 95% LoA was -17 ± 23 steps/min (MAPE: 17%) (Verisense 1) and -6 ± 5 steps/min (MAPE: 9%) with Verisense 2. For peak 30-min accumulated steps, mean bias and 95% LoA was -12 ± 45 steps/min (MAPE: 25%) (Verisense 1) and -2 ± 38 steps/min (MAPE: 13%) (Verisense 2). For MVPA steps/day, mean bias and 95% LoA was -1450 ± 3194 steps/day (MAPE: 420%) (Verisense 1) and -844 ± 2571 steps/day (MAPE: 211%) (Verisense 2). For MVPA min/day, mean bias and 95% LoA was -13 ± 27 min/day (MAPE: 368%) (Verisense 1) and -8 ± 24 min/day (MAPE: 209%) (Verisense 2). The Verisense 2 algorithm enhanced agreement for stepping intensity metrics but further refinement is needed to enhance agreement for MVPA against the waist.

Introduction Poor sleep health is associated with increased asthma morbidity and mortality. Accelerometers have been validated to assess sleep parameters though studies using this method in patients with asthma are sparse and none have compared mild to difficult-to-treat asthma populations. Methods We performed a retrospective analysis from two recent in-house trials comparing sleep metrics between patients with mild and difficult-to-treat asthma. Participants wore accelerometers for 24-hours/day for seven days. Results Of 124 participants (44 mild, 80 difficult-to-treat), no between-group differences were observed in sleep-window, sleep-time, sleep efficiency or wake time. Sleep-onset time was ~ 40 min later in the difficult-to-treat group ( p = 0.019). Discussion Broadly, we observed no difference in accelerometer-derived sleep-metrics between mild and difficult-to-treat asthma. This is the largest analysis of accelerometer-derived sleep parameters in asthma and the first comparing groups by asthma severity. Sleep-onset initiation may be delayed in difficult-to-treat asthma but a dedicated study is needed to confirm.

Background : ActiGraph accelerometers can monitor sleep and physical activity (PA) during free-living, but there is a need to confirm agreement in outcomes between different models. Methods : Sleep and PA metrics from two ActiGraphs were compared after participants ( N = 30) wore a GT9X and wGT3X-BT on their nondominant wrist for 7 days during free-living. PA metrics including total steps, counts, average acceleration—Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation, intensity gradient, the minimum acceleration value of the most active 10 and 30 min (M10, M30), time spent in activity intensities from vector magnitude (VM) counts, and ENMO cut points and sleep metrics (sleep period time window, sleep duration, sleep onset, and waking time) were compared. Results : Excellent agreement was evident for average acceleration-Mean Amplitude Deviation, counts, total steps, M10, and light PA (VM counts) with good agreement evident from the remaining PA metrics apart from moderate–vigorous PA (VM counts) which demonstrated moderate agreement. Mean bias for all PA metrics were low, as were the limits of agreement for the intensity gradient, average acceleration-Mean Amplitude Deviation, and inactive time (ENMO and VM counts). The limits of agreement for all other PA metrics were >10%. Excellent agreement, low mean bias, and narrow limits of agreement were evident for all sleep metrics. All sleep and PA metrics demonstrated equivalence (equivalence zone of ≤10%) apart from moderate–vigorous PA (ENMO) which needed an equivalence zone of 16%. Conclusions : Equivalent estimates of almost all PA and sleep metrics are provided from the GT9X and wGT3X-BT worn on the nondominant wrist.

BACKGROUND: Obesity is often associated with uncontrolled, difficult-to-treat asthma and increased morbidity and mortality. Previous studies suggest that weight loss may improve asthma outcomes, but with heterogenous asthma populations studied and unclear consensus on the optimal method of weight management. The Counterweight-Plus Programme (CWP) for weight management is an evidence-based, dietitian-led total diet replacement (TDR) program.RESEARCH QUESTION: Can use of the CWP compared with usual care (UC) improve asthma control and quality of life in patients with difficult-to-treat asthma and obesity?STUDY DESIGN AND METHODS: We conducted a 1:1 (CWP to UC) randomized, controlled single-center trial in adults with difficult-to-treat asthma and BMI of = 30 kg/m(2). The CWP was a 12-week TDR phase (800 kcal/d low-energy formula) followed by stepwise food reintroduction and weight loss maintenance for up to 1 year. The primary outcome was the change in Asthma Control Questionnaire 6 (ACQ6) score over 16 weeks. The secondary outcome was change in Asthma Quality of Life Questionnaire (AQLQ) score.RESULTS: Thirty-five participants were randomized (36 screened) and 33 attended the 16-week follow-up (n = 17 in the CWP group, n = 16 in the UC group). Overall, mean ACQ6 score at baseline was 2.8 (95% CI, 2.4-3.1). Weight loss was greater in the CWP than UC group (mean difference, -12.1 kg; 95% CI, -16.9 to -7.4; P < .001). ACQ6 score improved more in the CWP than UC group (mean difference, -0.69; 95% CI, -1.37 to -0.01; P = .048). A larger proportion of participants achieved the minimal clinically important difference in ACQ6 score with CWP than with UC (53% vs 19%; P = .041; Number needed to treat, 3 [95% CI, 1.5-26.9]). AQLQ score improvement was greater in the CWP than UC group (mean difference, 0.76; 95% CI, 0.18-1.34; P = .013).INTERPRETATION: Using a structured weight management program results in clinically important improvements in asthma control and quality of life over 16 weeks compared with UC in adults with difficult-to-treat asthma and obesity. This generalizable program is easy to deliver for this challenging phenotype. Longer-term outcomes continue to be studied.

The purpose of this study was to develop sedentary cut-points for the activPAL and evaluate their performance against a criterion measure (i.e., activPAL processed by PALbatch). Part 1: Thirty-five adults (23.4 ± 3.6 years) completed 12 laboratory activities (6 sedentary and 6 non-sedentary activities). Receiver operator characteristic (ROC) curves proposed optimal Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) cut-points of 26.4 mg (ENMO) and 30.1 mg (MAD). Part 2: Thirty-eight adults (22.6 ± 4.1 years) wore an activPAL during free-living. Estimates from PALbatch and MAD revealed a mean percent error (MPE) of 2.2%, mean absolute percent error (MAPE) of 6.5%, limits of agreement (LoA) of 19% with absolute and relative equivalence zones of 5% and 0.3 SD. Estimates from PALbatch and ENMO revealed an MPE of −10.6%, MAPE of 14.4%, LoA of 31% and 16% and 1 SD equivalence zones. After standing was isolated from sedentary behaviours, ROC analysis proposed an optimal cut-off of 21.9 mg (herein ENMOs). Estimates from PALbatch and ENMOs revealed an MPE of 3.1%, MAPE of 7.5%, LoA of 25% and 9% and 0.5 SD equivalence zones. The MAD and ENMOs cut-points performed best in discriminating between sedentary and non-sedentary activity during free-living.

Background: People with Multiple Sclerosis (PwMS) find it more difficult to engage in physical activity (PA) than healthy controls. Accelerometers can be used to measure sedentary time and free-living physical activity, understanding the differences between PwMS and controls can help inform changes such as interventions to promote a more active lifestyle. This in turn will help prevent secondary conditions and reduce symptom progression. Objective: To conduct a systematic review and meta-analysis on accelerometer measured sedentary behavior and physical activity between PwMS and healthy controls. Methods: A systematic search of five databases (PubMed, Web of Science, Ovid, Science Direct and CINAHIL) from inception until 22nd November 2019. Inclusion criteria was (1) included a group of participants with a definite diagnosis of multiple sclerosis of any type; (2) have 3 or more days of PA monitoring using accelerometers during free living conditions; (3) include age matched healthy controls; (4) assess adults over the age of 18; (5) reported data had to have been reported in a manner suitable for quantitative pooling including: percent of time spent sedentary, minutes per day of sedentary, light, moderate, vigorous activity (moderate and vigorous totaled together), steps per day or counts per day. Results: Initial search produced 9021 papers, after applying inclusion criteria 21 eligible papers were included in the study. One paper was a longitudinal study from which only baseline data was included. One paper was a reliability and validity study, with data for PwMS versus controls in the validity section. All other papers are cross sectional, with one being a pilot study and another a random control study. One paper used two devices in unison, only one set of data is included in the statistics. Outcome data was available for 1098 participants, 579 PwMS and 519 healthy controls. Significant differences were seen in all categories tested: (1) sedentary time (min/day), standard mean difference -0.286, P = 0.044, n = 4 studies; (2) relative sedentary time (%/day), standard mean difference -0.646, P = 0.000, n = 5 studies; (3) LPA (min/day), standard mean difference 0.337, P = 0.039, n = 5 studies; (4) relative LPA (%/day), standard mean difference 0.211, P = 0.152, n = studies; (5) MVPA (min/day), standard mean difference 0.801, P = 0.000, n = 8 studies; (6) relative MVPA (%/day), mean difference 0.914, P = 0.000, n = 5 studies; (7) step count, standard mean difference 0.894, P = 0.000, n = 8 studies; (8) activity count, standard mean difference 0.693, P = 0.000, n = 13 studies. Conclusion: PwMS are more sedentary and engage in less LPA, MVPA, steps per day and accelerometer counts per day than healthy controls when measured using accelerometers during free-living conditions.

Identification of cardiometabolic risk (CMR) in U.S. younger population by assessing muscular strength via handgrip (HG) dynamometry may aid in prevention efforts. Currently, no nationally representative HG cut-points are available for identifying increased CMR in U.S. adolescents or young adults. In this study, we propose normalized grip strength (NGS) cut-points for U.S. younger population CMR identification. National Health and Nutrition Examination Survey 2011-2012 and 2013-2014 data sets were used for analysis. A total of 1,033 participants (female [F], n = 498; male [M], n = 535) aged 12-24 years without current infection were included in analyses. The identified age- and sex-specific NGS cut-points are: M = 0.39 and F = 0.34 (age = 12-17 years), M = 0.45 and F = 0.34 (age = 18-24 years). These cut-points may be used in U.S. public health screening routines such as school- or community-based health-related fitness surveillance programs. Future work should use these cut-points in various samples to test their predictive utility for increased CMR.

This study compared physical activity metrics from the activPAL (AP) worn on the thigh with the ActiGraph worn on the non-dominant wrist using open-source methods. Measures included average acceleration, intensity gradient (IG) and the minimum acceleration value of the most active X mins (MX). Fifty-two children (26 boys; age: 10.4 +/- 0.6 years) provided >= 1 day (24 h) of concurrent wear time from the activPAL and ActiGraph. Measures tended to be lower from the activPAL versus the ActiGraph. Poor agreement was evident for average acceleration but good for the IG. For the IG, the absolute and relative zones needed to reach equivalence was 4% and 0.4 SDs, respectively and for average acceleration were 10% and 1.2 SDs, respectively. Good agreement was evident for M60, M30, M20, M15 and M10 between devices. Regardless of the reference device used, equivalent estimates for the intensity gradient, M60, M30, M20, M15 and M10 were observed with relative and absolute equivalence zones being <= 4% and <= 0.5 SDs, respectively. The IG, M60, M30, M20, M15 and M10 appear good candidates for comparing activity data collected from the activPAL and ActiGraph. Future research can use the AP to report on sedentary behaviours as well as PA outcomes.

Purpose: Physical inactivity and overweight status has been linked to low socioeconomic status (SES) in youth. Parents are known to influence both their child's weight and physical activity (PA). The relationship between parent and child PA is of interest to many researchers; however, previous research typically relies on self-reported measures. The purpose of this study was to examine the relationship between parent and child moderate-to-vigorous PA (MVPA) and body mass index (BMI) in a sample of children (4-11 years old) using wrist-worn accelerometers and to explore mediating processes by which SES influences child MVPA and BMI through their parents MVPA and BMI. Methods: Parent and child dyads (n = 174) wore an ActiGraph GT3X+ accelerometer on their non-dominant wrist for 7 days. Mediation analyses were conducted to understand the indirect relationships between SES and child MVPA and BMI. Results: Weekend parent and child MVPA was significantly related (p .01). Parent and child BMIs were also significantly related (p < .001). There was a significant negative direct effect of SES on child BMI (p < .05). Additionally, we observed a significant negative indirect effect of SES on child BMI via their parents BMI (B = -.04, SE .02, 95% CI = -.07 to -.01). Conclusions: Whilst parent and child MVPA were significantly related during the weekend, there were no associations between SES and MVPA. Future interventions aiming to improve health outcomes in children should consider the influence SES can have as well as parental activity on children's weekend MVPA.

OBJECTIVES:Patients with asthma may feel limited in physical activity (PA). Reduced PA has been demonstrated in asthmatics versus healthy controls, and increasing PA associated with improved asthma outcomes. Obesity is commonly found with difficult-to-control asthma and worsens outcomes. We compared PA levels in participants with difficult-to-control asthma and elevated body mass index (BMI) (DOW group) and two mild-moderate asthma groups: one with BMI <25 kg/m2 (MHW) and one with BMI ≥25 (MOW). METHODS:This cross-sectional study used 7-day recordings from wrist-worn accelerometers to compare PA between groups. Inactive time, light (LPA), moderate-vigorous PA (MVPA) were measured, along with two novel metrics: intensity gradient (IG) reflecting PA intensity, and average acceleration (AA) reflecting PA volume. PA parameters were compared using ANOVA or Kruskall-Wallis testing. Correlation and linear regression analyses explored associations between PA parameters and asthma outcomes. As AA was the PA parameter correlated most closely with asthma-related outcomes, an exploratory analysis compared outcomes in highest and lowest AA quartiles. RESULTS:75 participants were recruited; 57 accelerometer readings were valid and included in analysis. Inactive time was significantly higher (p < 0.001), and LPA (p < 0.007), MVPA (p < 0.001), IG (p < 0.001) and AA (p < 0.001) all significantly lower in DOW versus MHW and MOW groups, even after adjusting for age and BMI. Quartiles based on AA had significantly different asthma profiles. CONCLUSIONS:Overweight/obese participants with difficult-to-control asthma performed less PA, and activity of reduced intensity and volume. Increased AA is associated with improvement in several asthma-related outcomes. Increased PA should be recommended to relevant patients.

Abstract Background Difficult-to-control asthma associated with elevated body mass index (BMI) is challenging with limited treatment options. The effects of pulmonary rehabilitation (PR) in this population are uncertain. Methods This is a randomised controlled trial of an eight-week asthma-tailored PR programme versus usual care (UC) in participants with difficult-to-control asthma and BMI ≥ 25 kg/m2. PR comprised two hours of education and supervised exercise per week, with encouragement for two individual exercise sessions. Primary outcome was difference in change in Asthma Quality of Life Questionnaire (AQLQ) in PR versus UC groups between visits. Secondary outcomes included difference in change in Asthma Control Questionnaire-6 (ACQ6), and a responder analysis comparing proportion reaching minimum clinically important difference for AQLQ and ACQ6. Results 95 participants were randomised 1:1 to PR or UC. Median age was 54 years, 60% were female and median BMI was 33.8 kg/m2. Mean (SD) AQLQ was 3.9 (+/-1.2) and median (IQR) ACQ6 2.8(1.8–3.6). 77 participants attended a second visit and had results analysed. Median (IQR) change in AQLQ was not significantly different: 0.3 (− 0.2 to 0.6) in PR and − 0.1 (− 0.5 to 0.4) in UC, p = 0.139. Mean change in ACQ6 was significantly different: − 0.4 (95% CI − 0.6 to − 0.2) in PR and 0 (− 0.3 to + 0.3) in UC, p = 0.015, but below minimum clinically important difference. In ACQ6 responder analysis, minimum clinically important difference was reached by 18 PR participants (54.5%) versus 10 UC (22.7%), p = 0.009. Dropout rate was 31% between visits in PR group, and time to completion was significantly prolonged in PR group at 94 (70–107) days versus 63 (56–73) in UC, p < 0.001. Conclusions PR improved asthma control and reduced perceived breathlessness in participants with difficult-to-control asthma and elevated BMI. However, this format appears to be suboptimal for this population with high drop-out rates and prolonged time to completion. Trial registration Clinicaltrials.gov. ID NCT03630432. Retrospectively registered, submitted May 26th 2017, posted August 14th 2018.

The activPAL accelerometer has been used extensively in research to assess sedentary behaviour (SB) and physical activity (PA) outcomes. The aim of this study was to assess the comparability of PA and SB outcomes from two automated algorithms (CREA and GHLA) applied to the activPAL accelerometer. One hundred and twenty participants aged 8–12 years wore an activPAL accelerometer on their right thigh continuously for seven days on two occasions, providing valid data from 1058 days. The PALbatch software downloaded the data after applying the CREA and GHLA (latest) algorithms. The comparability of the algorithms were assessed using the mean absolute percent error (MAPE), intra-class correlation coefficients (ICC), and equivalence testing. Comparisons for daily wear time, primary lying, sitting and standing time, sedentary and stepping time, upright time, total number of steps, sit–stand transitions and stepping time ≤ 1 min revealed mainly small MAPE (≤2%), excellent ICCs (lower bound 95% CI ≥ 0.97), and equivalent outcomes. Time spent in sitting bouts > 60 min and stepping bouts > 5 min were not equivalent with the absolute zone needed to reach equivalence (≥7%). Comparable outcomes were provided for wear time and postural outcomes using the CREA or GHLA algorithms, but not for time spent in sitting bouts > 60 min and stepping bouts > 5 min.

(1) Background: Scotland has one of the highest rates of obesity in the Western World, it is well established that poor weight profiles, and particularly abdominal obesity, is strongly associated with Type II diabetes and cardiovascular diseases. Whether these associations are apparent in ethnic population groups in Scotland is unclear. The purpose of this study was to examine the associations between different measures of fatness with clustered cardio metabolic risk factors between Scottish South Asian adolescents and Scottish Caucasian adolescents; (2) Methods: A sample of 208 Caucasian adolescents and 52 South Asian adolescents participated in this study. Stature, waist circumference, body mass index, blood pressure, physical activity, and cardiovascular disease (CVD) risk were measured; (3) Results: Significant, partial correlations in the South Asian cohort between body mass index (BMI) and individual risk factors were generally moderate. However, correlations between Waist circumference (WC) and individual risk factors were significant and strong. In the Caucasian cohort, a significant yet weak correlation between WC and total cholesterol (TG) was noted although no other associations were evident for either WC or BMI. Multiple regression analysis revealed that both BMI and WC were positively associated with CCR (p < 0.01) in the South Asian group and with the additional adjustment of either WC or BMI, the independent associations with clustered cardio-metabolic risk (CCR) remained significant (p < 0.005); (4) Conclusions: No positive relationships were found between BMI, WC, and CCR in the Caucasian group. Strong and significant associations between measures of fatness and metabolic risk were evident in Scottish South Asian adolescents.