Motor Competence between Children with and without Additional Learning Needs: A Cross-Sectional Population-Level Study

The aim of this study was to examine associations in motor competence between children with additional learning needs (ALN) and typically developing children. This cross-sectional study involved a nationally representative cohort of 4555 children (48.98% boys; 11.35 ± 0.65 years) from sixty-five schools across Wales (UK). Demographic data were collected from schools, and children were assessed using the Dragon Challenge assessment of motor competence, which consists of nine tasks completed in a timed circuit. A multi-nominal multi-level model with random intercept was fitted to explore the proficiency between children with ALN and those without. In all nine motor competence tasks, typically developing children demonstrated higher levels of proficiency than their peers with ALN, with these associations evident after accounting for age, sex, ethnicity, and socioeconomic status. This study highlights motor competence inequalities at a population level and emphasises the need for policymakers, practitioners, and researchers to prioritise motor competence development, particularly for children with ALN

Clustered Cardiometabolic Risk, Cardiorespiratory Fitness and Physical Activity in 10-11 Year-Old Children. The CHANGE! Project Baseline

Objectives: The primary objective of this cross sectional pilot study was to report clustered risk scores combining traditional invasive with non invasive cardiometabolic risk markers in 10-11 year old children participating in the CHANGE! project at baseline. A secondary objective was to determine the relationship between clustered risk score and objectively measured physical activity (PA) and cardiorespiratory fitness (CRF). Methods: Habitual PA was measured using accelerometry and CRF (VO2peak) was assessed using an individually calibrated treadmill based protocol. Twenty-nine participants had valid data for all components of the clustered risk score, calculated using total cholesterol: high density lipoprotein-cholesterol (TC:HDL-C), glucose, systolic blood pressure (BP), LV Mass Index (g/m2.7), and trunk fat mass (g). Participants with a clustered risk score greater than 1SD above the mean, were categorised as ‘higher’ risk (n=6); all others were categorised as ‘normal’ risk. \ud \ud Results: Clustered risk score, controlling for somatic maturity and gender, was negatively correlated with VPA (r= -0.51, p=0.01), MVPA (r= -0.44, p=0.03) and VO2peak (r= -0.57, p<0.01). ANCOVA, with somatic maturity and gender as covariates, revealed that those in the ‘normal’ risk group were more fit than those in the ‘higher’ risk group [f (1,24)=4.518, p=0.044]). There were no statistically significant differences between risk groups and PA however mean data suggest that those in the ‘normal’ risk group accrued 4 minutes more daily VPA than the ‘higher’ risk group which may be clinically important. \ud \ud Conclusions: This provides further evidence of the importance of promoting CRF and VPA in children, to reduce cardiometabolic risk especially for those that are ‘higher’ risk

A cross-sectional study on the deprivation and sex differences in health-related fitness measures in school children

This study aimed to investigate deprivation and sex differences in selected health-relatedfitness measures in 9-12-year-old children. Data were captured on 3,407 children (49.3% boys; aged 10.5 ± 0.6 years). Cardiorespiratory fitness(20 m multistage shuttle run test; 20 m MSRT), muscular strength (handgrip strength) and body mass index (BMI) were measured. Welsh Index of Multiple Deprivation (WIMD) scores were used to make quintile groups. A two-way Analysis of Variance examined differences in BMI z-score by sex and WIMD quintiles. Two-wayAnalysis of Covariances investigated the effect of sex and WIMD quintiles on grip strength and shuttles achieved in 20 m MSRT, adjusting for BMI z-score and maturation, repectively. Independent of sex, children in the middle quintile had a significantly higher mean BMI z-score (p = 0.029) than their least deprived counterparts. There was a significant increase in grip strength (p = 0.005) and20 m MSRT (boys p < 0.001; girls p = 0.028) between most and least deprived quintiles. Significant differences in 20 m MSRT score were more apparent with decreases in deprivation in boys.Overall, inequalities exist in health-related fitness by sex and deprivation. These results can be used to inform focused services to improve current and future health

Classification of accelerometer wear and non-wear events in seconds for monitoring free-living physical activity

_____________________________________________________________ This article is brought to you by Swansea University. Any person downloading material is agreeing to abide by the terms of the repository licence. Authors are personally responsible for adhering to publisher restrictions or conditions. When uploading content they are required to comply with their publisher agreement and the SHERPA RoMEO database to judge whether or not it is copyright safe to add this version of the paper to this repository. Design: A bi-moving-window-based approach was used to combine acceleration and skin temperature data to identify wear and non-wear time events in triaxial accelerometer data that monitor physical activity. Setting: Local residents in Swansea, Wales, UK. Participants: 50 participants aged under 16 years (n=23) and over 17 years (n=27) were recruited in two phases: phase 1: design of the wear/non-wear algorithm (n=20) and phase 2: validation of the algorithm (n=30). Methods: Participants wore a triaxial accelerometer (GeneActiv) against the skin surface on the wrist (adults) or ankle (children). Participants kept a diary to record the timings of wear and non-wear and were asked to ensure that events of wear/non-wear last for a minimum of 15 min. Results: The overall sensitivity of the proposed method was 0.94 (95% CI 0.90 to 0.98) and specificity 0.91 (95% CI 0.88 to 0.94). It performed equally well for children compared with adults, and females compared with males. Using surface skin temperature data in combination with acceleration data significantly improved the classification of wear/non-wear time when compared with methods that used acceleration data only ( p&lt;0.01). Conclusions: Using either accelerometer seismic information or temperature information alone is prone to considerable error. Combining both sources of data can give accurate estimates of non-wear periods thus giving better classification of sedentary behaviour. This method can be used in population studies of physical activity in free-living environments

Cardiorespiratory fitness predicts clustered cardiometabolic risk in 10-11.9 year olds

The aim of this study was to investigate levels of clustered cardiometabolic risk and the odds of being ‘at risk’ according to cardiorespiratory fitness status in children. Data from 88 10–11.9-year-old children (mean age 11.05 ± 0.51 years), who participated in either the REACH Year 6 or the Benefits of Fitness Circuits for Primary School Populations studies were combined. Waist circumference, systolic blood pressure, diastolic blood pressure, glucose, triglycerides, high-density lipoprotein cholesterol, adiponectin and C-reactive protein were assessed and used to estimate clustered cardiometabolic risk. Participants were classified as ‘fit’ or ‘unfit’ using recently published definitions (46.6 and 41.9 mL/kg/min for boys and girls, respectively), and continuous clustered risk scores between fitness groups were assessed. Participants were subsequently assigned to a ‘normal’ or ‘high’ clustered cardiometabolic risk group based on risk scores, and logistic regression analysis assessed the odds of belonging to the increased cardiometabolic risk group according to fitness. The unfit group exhibited significantly higher clustered cardiometabolic risk scores (p < 0.001) than the fit group. A clear association between fitness group and being at increased cardiometabolic risk (B = 2.509, p = 0.001) was also identified, and participants classed as being unfit were found to have odds of being classified as ‘at risk’ of 12.30 (95 % CI = 2.64–57.33).\ud \ud Conclusion Assessing cardiorespiratory fitness is a valid method of identifying children most at risk of cardiometabolic pathologies. The ROC thresholds could be used to identify populations of children most at risk and may therefore be used to effectively target a cardiometabolic risk-reducing public health intervention

Comparison of IFCC-calibrated HbA1c from laboratory and point of care testing systems

Objective: WHO, IDF and ADA recommend HbA1c ≥6.5% (48 mmol/mol) for diagnosis of diabetes with pre-diabetes 6.0% (42 mmol/mol) [WHO] or 5.7% (39 mmol/mol) [ADA] to 6.4% (47 mmol/mol). We have compared HbA1c from several methods for research relating glycaemic markers.Research design and methods: HbA1c was measured in EDTA blood from 128 patients with diabetes on IE HPLC analysers (Bio-Rad Variant II NU, Menarini HA8160 and Tosoh G8), point of care systems, POCT, (A1cNow+ disposable cartridges and DCA 2000®+ analyser), affinity chromatography (Primus Ultra2) and the IFCC secondary reference method (Menarini HA8160 calibrated using IFCC SRM protocol).Results: median (IQ range) on IFCC SRM was 7.5% (6.8–8.4) (58(51–68) mmol/mol) HbA1c with minimum 5.3%(34 mmol/mol)/maximum 11.9%(107 mmol/mol). There were positive offsets between IFCC SRM and Bio-Rad Variant II NU, mean difference (1SD), +0.33%(0.17) (+3.6(1.9) mmol/mol), r2 = 0.984, p &lt; 0.001 and Tosoh G8, +0.22%(0.20) (2.4(2.2) mmol/mol), r2 = 0.976, p &lt; 0.001 with a very small negative difference −0.04%(0.11) (−0.4(1.2) mmol/mol), r2 = 0.992, p &lt; 0.001 for Menarini HA8160. POCT methods were less precise with negative offsets for DCA 2000®+ analyser −0.13%(0.28) (−1.4(3.1) mmol/mol), r2 = 0.955, p &lt; 0.001 and A1cNow+ cartridges −0.70%(0.67) (−7.7(7.3) mmol/mol), r2 = 0.699, p &lt; 0.001 (n = 113). Positive biases for Tosoh and Bio-Rad (compared with IFCC SRM) have been eliminated by subsequent revision of calibration.Conclusions: small differences observed between IFCC-calibrated and NGSP certified methods across a wide HbA1c range were confirmed by quality control and external quality assurance. As these offsets affect estimates of diabetes prevalence, the analyser (and calibrator) employed should be considered when evaluating diagnostic data.</p

Associations with photoreceptor thickness measures in the UK Biobank.

Spectral-domain OCT (SD-OCT) provides high resolution images enabling identification of individual retinal layers. We included 32,923 participants aged 40-69 years old from UK Biobank. Questionnaires, physical examination, and eye examination including SD-OCT imaging were performed. SD OCT measured photoreceptor layer thickness includes photoreceptor layer thickness: inner nuclear layer-retinal pigment epithelium (INL-RPE) and the specific sublayers of the photoreceptor: inner nuclear layer-external limiting membrane (INL-ELM); external limiting membrane-inner segment outer segment (ELM-ISOS); and inner segment outer segment-retinal pigment epithelium (ISOS-RPE). In multivariate regression models, the total average INL-RPE was observed to be thinner in older aged, females, Black ethnicity, smokers, participants with higher systolic blood pressure, more negative refractive error, lower IOPcc and lower corneal hysteresis. The overall INL-ELM, ELM-ISOS and ISOS-RPE thickness was significantly associated with sex and race. Total average of INL-ELM thickness was additionally associated with age and refractive error, while ELM-ISOS was additionally associated with age, smoking status, SBP and refractive error; and ISOS-RPE was additionally associated with smoking status, IOPcc and corneal hysteresis. Hence, we found novel associations of ethnicity, smoking, systolic blood pressure, refraction, IOPcc and corneal hysteresis with photoreceptor thickness

Community led active schools programme (CLASP) exploring the implementation of health interventions in primary schools: headteachers’ perspectives

Background: Schools are repeatedly utilised as a key setting for health interventions. However, the translation of effective research findings to the school setting can be problematic. In order to improve effective translation of future interventions, it is imperative key challenges and facilitators of implementing health interventions be understood from a school's perspective. Methods: Nineteen semi-structured interviews were conducted in primary schools (headteachers n = 16, deputy headteacher n = 1, healthy school co-ordinator n = 2). Interviews were transcribed verbatim and analysed using thematic analysis. Results: The main challenges for schools in implementing health interventions were; government-led academic priorities, initiative overload, low autonomy for schools, lack of staff support, lack of facilities and resources, litigation risk and parental engagement. Recommendations to increase the application of interventions into the school setting included; better planning and organisation, greater collaboration with schools and external partners and elements addressing sustainability. Child-centred and cross-curricular approaches, inclusive whole school approaches and assurances to be supportive of the school ethos were also favoured for consideration. Conclusions: This work explores schools' perspectives regarding the implementation of health interventions and utilises these thoughts to create guidelines for developing future school-based interventions. Recommendations include the need to account for variability between school environments, staff and pupils. Interventions with an element of adaptability were preferred over the delivery of blanket fixed interventions. Involving schools in the developmental stage would add useful insights to ensure the interventions can be tailored to best suit each individual schools' needs and improve implementation.11 page(s

Compositional analysis of the associations between 24-h movement behaviours and cardio-metabolic risk factors in overweight and obese adults with pre-diabetes from the PREVIEW study: cross-sectional baseline analysis

Background: Physical activity, sedentary time and sleep have been shown to be associated with cardio-metabolic health. However, these associations are typically studied in isolation or without accounting for the effect of all movement behaviours and the constrained nature of data that comprise a finite whole such as a 24 h day. The aim of this study was to examine the associations between the composition of daily movement behaviours (including sleep, sedentary time (ST), light intensity physical activity (LIPA) and moderate-to-vigorous activity (MVPA)) and cardio-metabolic health, in a cross-sectional analysis of adults with pre-diabetes. Further, we quantified the predicted differences following reallocation of time between behaviours. Methods: Accelerometers were used to quantify daily movement behaviours in 1462 adults from eight countries with a body mass index (BMI) ≥25 kg·m− 2 , impaired fasting glucose (IFG; 5.6–6.9 mmol·l − 1 ) and/or impaired glucose tolerance (IGT; 7.8–11.0 mmol•l − 1 2 h following oral glucose tolerance test, OGTT). Compositional isotemporal substitution was used to estimate the association of reallocating time between behaviours. Results: Replacing MVPA with any other behaviour around the mean composition was associated with a poorer cardio-metabolic risk profile. Conversely, when MVPA was increased, the relationships with cardiometabolic risk markers was favourable but with smaller predicted changes than when MVPA was replaced. Further, substituting ST with LIPA predicted improvements in cardio-metabolic risk markers, most notably insulin and HOMA-IR. Conclusions: This is the first study to use compositional analysis of the 24 h movement composition in adults with overweight/obesity and pre-diabetes. These findings build on previous literature that suggest replacing ST with LIPA may produce metabolic benefits that contribute to the prevention and management of type 2 diabetes. Furthermore, the asymmetry in the predicted change in risk markers following the reallocation of time to/from MVPA highlights the importance of maintaining existing levels of MVPA. Trial registration: ClinicalTrials.gov (NCT01777893)