Despite our increasing knowledge of the positive impact of physical activity during childhood for long term health, children are becoming less active (Boreham and Riddoch, 2001; Tremblay et al., 2011a). Childhood sedentary behaviour is strongly associated with obesity (Must and Tybor, 2005; Pearson and Biddle, 2011) and is also known to predict overweight in adolescence and adulthood (Guo et al., 2002; Magarey et al., 2003). In addition, sedentary behaviour is related to other chronic metabolic diseases, such as osteoporosis, type 2 diabetes and ischaemic heart disease (Dunstan et al., 2010; Katzmarzyk et al., 2009; Tremblay et al., 2011a). Increasing physical activity participation in school is notionally a very practical method to improve the health of children at the population level (Boreham and Riddoch, 2001). An exercise regime that would effectively improve the health of multiple body systems, however, is yet to be described. For instance, it is well known that increasing the duration of physical activity is an effective strategy to enhance cardiovascular function (Haskell et al., 2007), but not the skeletal system. To stimulate the latter system, short duration, high intensity loading is required (Lanyon and Rubin, 1984).
Exercise prescriptions can be manipulated in terms of frequency (exercise bouts per week), intensity (metabolic and musculoskeletal load), duration (length of exercise bout), and exercise type (Must and Tybor, 2005). The current physical activity recommendation for children includes the accumulation of 60 minutes per day of moderate to vigorous exercise in addition to activities that strengthen bone and muscle on at least three days per week (Janssen, 2007; Strong et al., 2005; Tremblay et al., 2011b; Twisk, 2001). Measures of intensity traditionally focus on cardiovascular or metabolic load and are classified in terms of heart rate and estimates of energy expenditure (EE) (Haskell et al., 2007). Such measures, however, fail to capture characteristics of mechanical intensity that are vital to the musculoskeletal response. In order to identify childhood activities that are broadly beneficial to multiple systems, it is important to know the intensity of both cardiovascular/metabolic load and musculo-skeletal load. Furthermore, from a psychosocial standpoint, variety and enjoyment are critically important elements of an exercise program that contribute to uptake and ongoing engagement (Richard et al., 1997).
Accelerometry is a recognised technique to track physical activity in bone and metabolic research (Janz et al., 2003). Accelerometry-derived weight-bearing movements can predict bone mass and density in young children (Janz et al., 2001; Specker et al., 2001). Biomechanical characteristics of weight-bearing exercises are typically estimated by measuring ground reaction forces (GRF) (Prapavessis and McNair, 1999).
The CAPO Kids program was a recent brief and enjoyable in-school exercise intervention designed to improve the musculoskeletal and metabolic health of pre and peripubertal children (Nogueira et al., 2014; 2015). The goal of the program was to simultaneously apply a moderate to vigorous aerobic load and high intensity impact loading. Exercises were based on capoeira, a Brazilian sport that combines martial art, dance and music, presenting a new and interesting activity for the participants. Capoeira was supplemented with high impact activities including a variety of jumps and upper limb loading activities. The program improved bone health and metabolic factors such as waist circumference, resting heart rate and maximal oxygen uptake over a nine-month period (Nogueira et al., 2014; 2015).
The aim of the present study was to characterise the biomechanical and metabolic loads of the CAPO Kids exercise program, in boys and girls. Those data will allow others to make an informed judgement with regards to the potential of the program to produce metabolic and musculoskeletal benefit or other outcomes.
Study design and ethical approval
We conducted a cross-sectional descriptive study of metabolic and mechanical loads experienced by participants in the CAPO Kids trial. Ethical approval was obtained from the Griffith University Human Research Ethics Committee (PES/35/12/HReC), and all participants provided informed consent. Parents had the option to override and decline to consent.
A sample of the Year 5 and 6 primary school children (9.7-11.4 years of age) who were participating in the 9month CAPO Kids exercise intervention were recruited for the current study. Participants were included if they were healthy, ambulant, and enrolled in the exercise arm of the trial. Participants were excluded if they had a metabolic, endocrine or renal condition; were taking medications known to affect bone, muscle or fat metabolism; were recovering from a serious lower limb fracture or other immobilising injury in the past six months; or were affected by any condition not compatible with short bouts of physical activity. Specific details of school and participant recruitment are available in previous publications (Nogueira et al., 2014; 2015).
Participants were invited to wear a Sense Wear Armband (SWA, BodyMedia, Pittsburgh, PA, USA) for the entirety of one CAPO Kids exercise bout in order to have parameters of metabolic intensity measured. The same participants were also invited to attend a single session of testing at the Biomechanics Laboratory at Griffith University in order to have the ground reaction forces (GRF) associated with intervention activities measured on a force platform. Participation in the GRF session was optional. An a priori sample size estimate was not conducted.
Anthropometries: Anthropometric measures included standing and sitting height (portable stadiometer, HART Sport and Leisure, Australia and a 50 cm stool), and body weight (digital scale, Charder MS 3200, CE, Taichung City, Taiwan). Weight was measured in duplicate, while standing and sitting height were determined by a single measure. Body mass index (BMI) was determined from weight and height per the accepted method (BMI = weight-height-2, kg x m-2).
Maturity: Maturity was assessed by calculating years to age of peak height velocity (YAPHV), based on an algorithm that includes several anthropometric variables (Mirwald et al., 2002). The algorithm uses the following variables: date of birth, sex, weight, sitting and standing height; and predicts maturity offset as the number of years the participant is from their estimated age of peak height velocity (APHV). YAPHV is calculated by subtracting APHV from...