A cluster randomised controlled trial to investigate the effectiveness and cost effectiveness of the 'Girls Active' intervention: a study protocol

Background: Despite the health benefits of physical activity, data from the UK suggest that a large proportion of adolescents do not meet the recommended levels of moderate-to-vigorous physical activity (MVPA). This is particularly evident in girls, who are less active than boys across all ages and may display a faster rate of decline in physical activity throughout adolescence. The ‘Girls Active’ intervention has been designed by the Youth Sport Trust to target the lower participation rates observed in adolescent girls. ‘Girls Active’ uses peer leadership and marketing to empower girls to influence decision making in their school, develop as role models and promote physical activity to other girls. Schools are provided with training and resources to review their physical activity, sport and PE provision, culture and practices to ensure they are relevant and attractive to adolescent girls. Methods/Design: This study is a two-arm cluster randomised controlled trial (RCT) aiming to recruit 20 secondary schools. Clusters will be randomised at the school level (stratified by school size and proportion of Black and Minority Ethnic (BME) pupils) to receive either the ‘Girls Active’ intervention or carry on with usual practice (1:1). The 20 secondary schools will be recruited from state secondary schools within the Midlands area. We aim to recruit 80 girls aged 11 –14 years in each school. Data will be collected at three time points; baseline and seven and 14 months after baseline. Our primary aim is to investigate whether ‘Girls Active’ leads to higher objectively measured (GENEActiv) moderate-to-vigorous physical activity in adolescent girls at 14 months after baseline assessment compared to the control group. Secondary outcomes include other objectively measured physical activity variables, adiposity, physical activity-related psychological factors and the cost-effectiveness of the ‘Girls Active’ intervention. A thorough process evaluation will be conducted during the course of the intervention delivery. Discussion: The findings of this study will provide valuable information on whether this type of school-based approach to increasing physical activity in adolescent girls is both effective and cost-effective in the U

Objective assessment and modification of physical activity and health indices in adolescent females

The following literature review describes the benefits of being physically active in childhood and adulthood and also the dangers that accompany inactivity. The benefits of being physically activity as a young person can affect future health and future physical activity levels and this link will be considered as a rationale for promoting physical activity in adolescence. The negative consequences of obesity in childhood and adulthood are also considered. The relationship between childhood and adolescent body composition will be considered and it will be discussed how obesity tracks strongly from adolescence into adulthood meaning the current burden of obesity will affect future health. Like the tracking of physical activity, this link will be considered as a rationale for getting adolescents to be physically active. Irish and international data on physical activity and body composition will also be presented and critically appraised. Measurement of physical activity will also be discussed with a focus on accelerometry. Interventions that are school based will be discussed at the end of the chapter

Criterion and concurrent validity of the activPAL (TM) professional physical activity monitor in adolescent females

Background: The activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer.Methodologies: Thirty adolescent females (15 developmental; 15 cross-validation) aged 15-18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96,

Light-intensity physical activity is associated with adiposity in adolescent females

Introduction: Sedentary behavior (SB) research has relied on accelerometer thresholds to distinguish between sitting/lying time (SLT) and light-intensity physical activity (LIPA). Such methods may misclassify SLT, standing time (StT), and LIPA. This study examines the association between directly measured SB, physical activity (PA), and adiposity in an adolescent female sample. Methods: Female adolescents (n = 195; mean age, 15.7 yr (SD, 0.9)) had body mass index (BMI) (median, 21.7 kg.m(-2) (interquartile range, 5.2 kg.m(-2))) and four-site sum of skinfolds (median, 62.0 mm; interquartile range, 37.1 mm) measured and wore an activPAL (TM) activity monitor for 7 d. SLT, StT, breaks in SLT, and bouts of SLT = 30 min were determined from activPAL outputs. A threshold of 2997 counts per 15 s determined moderate-to-vigorous PA. All remaining time was quantified as LIPA. Mixed linear regression models examined associations between PA variables, SB variables, and adiposity. Results: Participants spent a mean of 65.3% (SD, 7.1) of the waking day in SLT, 23.0% (SD, 5.3) in StT, 5.6% (SD, 1.5) in LIPA, and 6.1% (SD, 2.4) in moderate-to-vigorous PA. Significant effects for the percentage of LIPA (which excluded StT) with both BMI (beta = -4.38, P = 0.0006) and sum of skinfolds (beta = -4.05, P = 0.006) were identified. Significant effects for breaks in SLT with BMI (beta = -0.30, P = 0.04) were also observed. No additional significant associations were found between activity measures and adiposity. Conclusions: Increased LIPA (excluding StT) and breaks in SLT were negatively associated with adiposity in this sample, independent of age. Interventional work should examine whether reducing SLT through breaks and increasing LIPA may prevent increases in adiposity in adolescent females

Beyond Cut-points: Accelerometer Metrics that Capture the Physical Activity Profile.

PURPOSE: Commonly used physical activity metrics tell us little about the intensity distribution across the activity profile. The purpose of this paper is to introduce a metric, the intensity gradient, which can be used in combination with average acceleration (overall activity level) to fully describe the activity profile. METHODS: 1669 adolescent girls (sample 1) and 295 adults with type 2 diabetes (sample 2) wore a GENEActiv accelerometer on their non-dominant wrist for up to 7-days. Body mass index and percent body fat were assessed in both samples and physical function (grip strength, Short Physical Performance Battery, sit-to-stand repetitions) in sample 2. Physical activity metrics were: average acceleration (AccelAV); the intensity gradient (IntensityGRAD from the log-log regression line: 25 mg intensity bins (x)/time accumulated in each bin (y)); total moderate-to-vigorous physical activity (MVPA); and bouted MVPA (sample 2 only). RESULTS: Correlations between AccelAV and the IntensityGRAD (r=0.39-0.51) were similar to correlations between AccelAV and bouted MVPA (r=0.48), and substantially lower than between AccelAV and total MVPA (r>0.93). The IntensityGRAD was negatively associated with body fatness in sample 1 (p<0.05) and positively associated with physical function in sample 2 (p<0.05); associations were independent of AccelAV and potential co-variates. In contrast, MVPA was not independently associated with body fatness or physical function. CONCLUSION: AccelAV and the IntensityGRAD provide a complementary description of a person's activity profile, each explaining unique variance, and independently associated with body fatness and/or physical function. Both metrics are appropriate for reporting as standardised measures and suitable for comparison across studies using raw acceleration accelerometers. Concurrent use will facilitate investigation of the relative importance of intensity and volume of activity for a given outcome

Cardiometabolic risk factor response to a lifestyle intervention: a randomized trial

BACKGROUND: Strategies to increase adherence to national dietary and physical activity (PA) guidelines to improve the health in regions such as the Lower Mississippi Delta (LMD) of the United States are needed. Here we explore the cardiometabolic responses to an education and behavior change intervention among overweight and obese adults that adapted the 2010 Dietary Guidelines (DG), with and without a PA component. METHODS: White and African American overweight and obese adults were randomized to a DG group (n=61) or a DG+PA group (n=60). Both groups received a 12-week dietary education and behavior change intervention, and the DG+PA group also received a PA education and behavior change intervention with a pedometer. Changes in individual risk factors (blood pressure, fasting glucose, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol) and a continuous cardiometabolic risk score were determined. General linear models compared mean changes between groups, adjusting for covariates. RESULTS: No main effect of intervention group was found in completers (n=99) and those who engaged with ≥80% of the intervention (n=83) for individual risk factors or the continuous risk score. Pooling both groups, those with higher baseline risk factor values realized greater improvements in individual risk factors. CONCLUSIONS: Adapting DG did not produce any cardiometabolic benefits, even with a PA component. Although the sample was ostensibly healthy, they were all overweight to mildly obese (body mass index of 25-34.9 kg/m[superscript: 2]) and participants with higher baseline risk factor values showed more improvements. Adherence to longer-term behavior change may elicit changes in risk profile, so this should be explored

Minimum wear duration for the activPAL professional activity monitor in adolescent females

Objectives: This study aims to determine the minimum number of days of monitoring required to reliably predict sitting/lying time, standing time, light intensity physical activity (LIPA), moderate-to-vigorous intensity physical activity (MVPA) and steps in adolescent females. Methods: 195 adolescent females (mean age = 15.7 years; SD = 0.9) participated in the study. Participants wore the activPAL activity monitor for a seven day protocol. The amount of time spent sitting/lying, standing, in LIPA and in MVPA and the number of steps per day were quantified. Spearman-Brown Prophecy formulae were used to predict the number of days of data required to achieve an intraclass correlation coefficient of both 0.7 and 0.8. Results: For the percentage of the waking day spent sitting/lying, standing, in LIPA and in MVPA, a minimum of 9 days of accelerometer recording is required to achieve a reliability of >= 0.7, while a minimum of 15 days is required to achieve a reliability of >= 0.8. For steps, a minimum of 12 days of recording is required to achieve a reliability of >= 0.7, with 21 days to achieve a reliability of >= 0.8. Conclusion: Future research in adolescent females should collect a minimum of 9 days of accelerometer data to reliably estimate sitting/lying time, standing time, LIPA and MVPA, while 12 days is required to reliably estimate steps

Uncovering physiological mechanisms for health disparities in type 2 diabetes

Type 2 diabetes (T2D) prevalence in the United States is significantly higher in African Americans vs Whites. Yet, the physiological mechanisms contributing to this health disparity have been poorly described. To design effective strategies to reduce this disparity, there is a need to determine whether racial differences in diabetes prevalence are attributable to modifiable or non-modifiable factors. This review synthesizes and critically evaluates the potential physiological and genetic mechanisms that may contribute to the higher susceptibility of African Americans to T2D. These mechanisms include: 1) obesity and fat distribution; 2) metabolic flexibility; 3) muscle physiology; 4) energy expenditure and fitness; and 5) genetics. We focus on the clinical significance of findings and limitations of the recent literature

Associations between anthropometric measurements and cardiometabolic risk factors in White European and South Asian adults in the UK

Objective To investigate the association of 4 anthropometric measurements with cardiometabolic risk factors in a UK biethnic sample of South Asians (SAs) and white Europeans (WEs). Patients and Methods Baseline data were collected from adults of WE and SA origin participating in the Leicester arm of the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care (ADDITION-Leicester) study between August 2004 and December 2007. Overall, 6268 WE and SA adults had measures of body mass index, waist circumference, waist-to-hip ratio, and waist-to-height ratio assessed between June 18, 2004, and December 4, 2007. Hypertension, dyslipidemia, and dysglycemia were established from venous blood samples using standard definitions. Crude and adjusted (covariates used were age, sex, ethnicity, smoking, and alcohol consumption) odds ratios were calculated using multivariate logistic regression. Receiver operating characteristic curves and the area under the curve were used to calculate optimal cut points for the whole cohort and for both ethnic groups. Results Increases in all anthropometric measurements resulted in a higher odds ratio for each of the risk factors in both the crude and adjusted models (P<.001). The adjusted odds ratios for dyslipidemia, hypertension, and dysglygemia ranged from 1.30 to 1.35, from 1.36 to 1.52, and from 1.62 to 1.75 (P<.001 for all), respectively, in WEs. The adjusted odds ratio for dyslipidemia, hypertension, and dysglygemia ranged from 1.50 to 1.65 (P<.01), from 1.40 to 1.60 (P<.01), and from 1.96 to 2.11 (P<.001 for all), respectively, in SAs. The areas under the receiver operating characteristic curves for all the anthropometric measurements had low accuracy (P<.70) for the whole cohort and when stratified by ethnicity and sex. Conclusion There is insufficient evidence to recommend replacing body mass index with another anthropometric measurement for the ethnically diverse population in the United Kingdom. Trial Registration clinicaltrials.gov Identifier: NCT00318032

Compliance of Adolescent Girls to Repeated Deployments of Wrist-worn Accelerometers

PURPOSE: To determine the cross-sectional and cumulative compliance of adolescent girls to accelerometer wear at three deployment points and to identify variables associated with compliance. METHODS: Girls from 20 secondary schools were recruited: 10 schools were participating in the 'Girls Active' intervention and 10 were control schools. Physical activity was measured using the GENEActiv accelerometer worn on the non-dominant wrist 24 hours/day for up to 7-days at baseline, 7-months and 14-months. Demographic and anthropometric characteristics were recorded. RESULTS: Seven valid days (≥16 hours) of accelerometer wear were obtained from 83%, 77% and 68% of girls at baseline (n = 1734), 7-months (n = 1381) and 14-months (n = 1326), respectively. 68% provided 7-valid days for both baseline and 7-months, 59% for baseline and 14-months and 52% for all three deployment points. Estimates of physical activity level from 3-days of measurement could be considered equivalent to a 7-day measure (i.e. they fell within a ±5% equivalence zone). Cross-sectionally, 3-valid days were obtained from at least 91% of girls; cumulatively, this was obtained from ≥88% of girls across any two deployment points and 84% of girls across all three deployment points. When controlling for clustering at school level and other potential predictors, physical activity level, being South Asian, being in the intervention group and prior compliance were positively associated with monitor wear. CONCLUSION: Compliance reduced across deployment points, with the reduction increasing as the deployment points got further apart. High prior compliance and high physical activity level were associated with the most additional wear-time