Girls Physical Activity During High School Physical Education: Influences of Body Composition and Cardiorespiratory Fitness

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1 382 JOURNAL OF TEACHING IN PHYSICAL EDUCATION, 2003, 22, HUMAN KINETICS PUBLISHERS, INC. Fairclough Girls Physical Activity During High School Physical Education: Influences of Body Composition and Cardiorespiratory Fitness Stuart J. Fairclough REACH Group and Liverpool John Moores University This study assessed the physical activity levels of 20 high school girls (age 13 years, SD = 1.1) during physical education classes, over an 8-month period. Physical activity was measured by heart rate telemetry and accelerometry. Skinfold measurements were used to estimate percent body fat, and peak VO 2 was assessed by maximal treadmill running. Girls engaged in moderate-tovigorous intensity physical activity (MVPA) for 38.5% of class time and produced vector magnitude (Vmag) counts min 1. Body fat was inversely correlated with Vmag counts min 1 (r =.65, p <.01) and peak VO 2 (r =.65, p <.01). Girls MVPA in physical education did not meet the Healthy People % of class time criterion. Body fat significantly predicted 42% of the variance in Vmag counts min 1. Cardiorespiratory fitness appeared not to influence physical activity during physical education, regardless of measurement method. Girls physical activity in physical education may be improved if schools advocate planned lesson outcomes that aim to maximize opportunities for physical activity. Key Words: body fat, peak VO 2, heart rate monitoring, accelerometry, adolescence It is well established that physical activity is associated with health benefits in adults (Shephard, 1995). Although the primary morbidities that affect humans occur mainly in middle and old age (Riddoch, 1998), evidence suggests that cardiovascular disease (CVD) risk factors, such as obesity, hypertension, and hypercholesterolaemia, can develop during childhood (Gutin et al., 1994). Of these risk factors, overfatness and obesity are recognized as major public health problems, with 61% of American adults classified as overweight or obese (Centers for Disease Control [CDC], 2001), and 18% of men and 24% of women in the UK projected to be obese by 2005 (Department of Health, 1995). Moreover, this trend is mirrored in children and adolescents, with 13% of 6- to 11-year-olds, and 14% of 12- to 19-year-olds in the US being overweight (CDC, 2002, 1). Research indicates that low levels of physical activity are associated with increased body fatness in young people (DeLany, 1998). Thus, physical activity participation among S.J. Fairclough is with the REACH (Research into Exercise, Activity and Children s Health) Group and Liverpool John Moores University, Liverpool, UK L17 6BD. 382

2 Girls Physical Activity During Physical Education 383 children and adolescents may positively affect body composition, as well as other health indicators, and consequently delay the development of CVD risk factors (Tremblay, Inman, & Willms, 1999). In recognition of the health benefits associated with physical activity, recommendations for children and youth have been produced in the UK (Biddle, Sallis, & Cavill, 1998) and US (Corbin & Pangrazi, 1998), advocating the accumulation of one hour s daily physical activity. School physical education has been highlighted as a significant contributor to help young people achieve their daily volume of physical activity (Biddle et al., 1998; Corbin & Pangrazi, 1998). The vast majority of young people are exposed to physical education, while the facilities and personnel provide a purpose made infrastructure for quality physical activity education and participation. Furthermore, the physical education experience can promote knowledge of, and positive attitudes towards physical activity, which may influence young people s participation after compulsory education and through the lifespan (Sallis & McKenzie, 1991). To more clearly focus physical education on physical activity and health goals, Healthy People 2010 includes three physical education-related objectives. These are (a) to increase the number of schools timetabling daily physical education classes, (b) increase the proportion of students who participate in daily physical education, and (c) improve the number of students who are physically active for at least 50% of lesson time (US Department of Health and Human Services [USDHHS], 2000). The inclusion of these objectives serves to emphasize the important role physical education has in promoting health-enhancing physical activity in children and youth. Girls habitual physical activity participation is generally less frequent and of a lower intensity than that of boys (Sallis, 1993; Welsman & Armstrong, 1997). This distinction has also been noted during physical education classes when physical activity has been assessed using heart rate monitoring (Stratton, 1996), accelerometry (LeMura, Andreacci, Carlonas, Klebez, & Chelland, 2000), and direct observation (McKenzie, Marshall, Sallis, & Conway, 2000). Moreover, although both sexes reduce their physical activity as they mature (Sallis, 1993), this reduction is more apparent in girls and is steeper during adolescence (Armstrong & Welsman, 1997). The physiological changes to body composition during the growth spurt, as well as psychosocial influences, make adolescence a particularly high risk period for girls to adopt sedentary habits. An inactive lifestyle during this period can result in augmented body fat and decreased cardiorespiratory fitness (Rowland, 1999). Furthermore, adolescence is a key period for changes in certain health risk factors relating to CVD and bone mineral density, which, along with physical activity habits, are likely to track into the adult years (Rowland, 1999). Such tracking trends are confirmed by the fact that more US adult females than males take part in no leisure time physical activity (USDHHS, 2000). Moreover, as heart disease is the leading cause of death among US women (CDC, 2001), the potential public health implications of low physical activity levels among girls could be serious. For this reason, physical education should be the obvious medium through which girls physical activity is optimally enhanced and promoted. Therefore, the purpose of this study was to objectively measure the physical activity of high school girls during physical education classes, using accelerometry and heart rate monitoring. The Healthy People 2010 objective relates to students being physically active for 50% of class time (USDHHS, 2000). This recommendation is considered as an ambitious, yet feasible, target (USDHHS,

3 384 Fairclough 2000) and is based on a consensus of expert opinion (Sallis & Patrick, 1994). For these reasons it was chosen as the criterion measure against which heart rate activity levels were compared. Because two objective measures of physical activity were used, an assessment of the relationship between the heart rate monitoring and accelerometry was made. The study also aimed to examine the association between girls body composition and cardiorespiratory fitness, with their physical activity during physical education. Method Subjects and Settings Twenty female students from a state high school in the Merseyside region of England volunteered to participate in this study, which was part of a larger project assessing baseline physical activity during physical education. Nine girls were in a Year 7 class (11 12 years), three in a Year 8 class (12 13 years), and eight in a Year 9 class (13 14 years), and all regularly participated in physical education lessons. Students were informed about the study by their physical education teachers. Those who were interested received written informed consent, which was completed by students and their parents or guardians, and returned to school prior to the study commencing. The school taught the statutory programs of study detailed in the English National Curriculum for Physical Education (Department for Education and Employment/Qualifications and Curriculum Authority, 1999). The National Curriculum is organized into six distinct areas of activity (i.e., athletic activities, dance, games, gymnastic activities, outdoor activities, and swimming). When designing their curricula, schools have the flexibility to select differing combinations of activities from these six areas. Games typically dominate English physical education curricula, with the other areas of activity taking up the remainder of available time. Most activities are traditionally taught on a seasonal basis (e.g., soccer, netball in winter and autumn; athletics, softball in summer). The girls attended physical education classes twice each week in single sex groups and were taught by specialist female physical educators. Instruments and Procedures The investigation received ethics committee approval in May 2001 from the Liverpool John Moores Research Degrees Ethics Committee. It involved monitoring the girls physical activity during physical education classes using short wave, radio heart rate telemetry systems (Vantage XL; Polar Electro Oy, Kempele, Finland). Such systems measure the physiological load on the participants cardiorespiratory systems, and allow analysis of the quality of physical activity in terms of current recommendations (USDHHS, 2000). Through their involvement in a larger physical activity study, the 20 girls involved had previous experience of wearing the telemeters. For this reason it was assumed that they were accustomed to the equipment to such a degree that it did not directly influence their activity levels. Physical activity was also assessed using tri-axial accelerometers (Tritrac-R3D; Hemokinetics Inc., Madison, WI). These instruments are about the size of a pocket calculator and measure acceleration in the horizontal, vertical, and lateral planes. They also integrate acceleration to yield one composite value of movement. The theoretical basis underlying the use of this equipment is that acceleration is directly

4 Girls Physical Activity During Physical Education 385 proportional to muscular forces exerted during activity and, therefore, is related to energy expenditure (Melanson & Freedson, 1996). Participants were monitored over the course of 33 lessons, which covered a variety of team games, movement activities (i.e., gymnastics and dance), and track and field athletics. The girls were fitted with the equipment while changing into their physical education uniforms. Heart rate monitors were attached by fitting a lightweight chest strap (transmitter) and wristwatch (receiver). Heart rate was recorded once every 5 s for the duration of the lessons. Total lesson activity time was the equivalent of the total recorded time on the receiver. Students were instructed to ignore the equipment and wore wristbands over the receivers to deter them from tampering with the buttons or looking at the displays. Prior to the lessons the accelerometers were programmed to record physical activity on a minute-by-minute basis. They were placed in sealed pouches that were attached to adjustable fabric belts. Each subject wore the belt with the pouch positioned on their right hip, secured inside the waistband of their shorts or tracksuit pants. In order for the output to be stabilized, girls wore the monitors for at least 5 min prior to the official lesson start times. During this period they took part in regular prelesson processes such as registration, receiving instructions and organization of groups and equipment. To accurately assess the relationship between the heart rate monitors and accelerometers, it was important to establish a precise temporal association between the two instruments. Prior to the lessons, the heart rate monitors and accelerometers internal clocks were synchronized with that of the computer system to which they would be interfaced for data analysis. Heart rate monitors were set to record data at the beginning of the first new minute after the teacher officially began the lesson. Recording was stopped after the last minute of the lesson. The exact start and end times of heart rate recording were noted for the purposes of temporally matching heart rate and accelerometer data. Because the accelerometer began recording activity immediately after being initialized, once the data had been downloaded, all movement counts recorded prior to the lesson start time and after the lesson finish time were deleted. At the end of the lessons both instruments were removed from each child and returned to the laboratory, where they were interfaced with a PC and data were downloaded for analyses (Tritrac-R3D; Hemokinetics Inc., Madison, WI; Polar Precision Performance 2.0; Polar Electro Oy, Kempele, Finland). The accelerometer outcome measure of interest was activity counts, which were measured in units that are independent of body size. Separate movement count values were produced for movement in the horizontal, vertical, and lateral planes, along with a composite vector magnitude representation of these counts. In this study mean vector magnitude counts, corrected for variability in activity durations (Vmag counts min -1 ), were used as the output measure. Resting heart rates were measured once on days when the students were not timetabled for physical education. After sitting in morning lessons students reported to the gymnasium in groups of three. All were in a postprandial state for at least 2 hours. They were fitted with the heart rate monitors that were set to record at 5-s intervals and remained in a supine position for a period of 10 min. Telemeters were subsequently removed from the students and returned to the laboratory where they were interfaced and downloaded for analysis. It has been reported that resting heart rates tend to exceed basal heart rates recorded during sleep (Anderson, McCartney, Shinebourne, & Tynan, 1987). However, the logistical difficulties

5 386 Fairclough of obtaining sleeping heart rates were such that this alternative best-fit method was devised, while acknowledging that the resting heart rates may have been elevated above basal values. To ascertain the most accurate and representative resting heart rate values possible, the lowest 12 consecutive heart rate readings (i.e., the equivalent of 1 min), which on initial inspection represented values within a similar range, were identified. If the variance between these 12 values was < 5%, this was deemed an acceptable level of error, and the mean of the 12 values was recorded as the resting heart rate. If the variance exceeded 5%, then an alternative 12 consecutive values were selected. By employing this approach, each student had a mean resting heart rate value, with an acceptable level of error calculated over the course of 1 min. Using the resting values and the maximum heart rate values attained from the peak VO 2 test, heart rate reserve (HRR) at the 50% threshold was calculated for each student. This threshold represents moderate physical activity (Stratton, 1996). Percentage of lesson time spent in health enhancing moderate-to-vigorous physical activity (MVPA) was calculated by summing HRR threshold values 50%. Each student made one visit to the laboratory over the course of the data collection period. Stature was measured using a stadiometer (Avery, 3306ABV; Birmingham, England) and recorded to the nearest 0.1 cm. Balance beam scales (Avery, 3306ABV; Birmingham, England) were used to measure body mass to the nearest 0.1 kg. Tricep and calf skinfold sites were assessed by an experienced female technician using calibrated Harpenden calipers (British indicators, London). Triplicate measures of both sites were taken to the nearest 0.1 mm, using the methods described by Lohman, Roche, & Martorell (1988). The means of the three skinfold measures were summed to yield a total skinfold score. From this value percentage body fat was calculated using the equation developed by Slaughter et al. (1988). Students underwent a modified version of the Balke maximal treadmill test (Rowland, 1993) to assess cardiorespiratory fitness. After receiving safety instructions and an explanation of the rating of perceived exertion (RPE) scale, the students underwent a 1-min familiarization walk at a speed of 4 km h 1 (0% gradient). Following this period the treadmill speed increased and the test commenced. The speed was predetermined prior to the familiarization and remained constant throughout the test. The test speeds had successfully been used in our laboratory on previous occasions and ranged between 6.5, 8.0, and 9.5 km h 1. They were selected after consultation with each student and their teacher, based on the student s age, level of ability and experience of treadmill running. The gradient increased by 2.5% every 2 min. Heart rate and RPE were recorded at the end of each workload. Students terminated the test of their own volition by placing their feet to the sides of the moving belt. Gas collection and analysis were performed automatically throughout each test via an on-line gas analysis system (Schiller-AG, CS-100; Baar, Switzerland). The highest volume of oxygen consumed was described as peak VO 2, providing the students could no longer continue at the required speed, had respiratory exchange ratio (RER) values > 0.99, and heart rates in excess of 200 beats min 1 (Rowland, 1996). Design and Analysis So as to cause only minimal disruption to the physical education classes, monitoring took place during one of the two weekly lessons. On each occasion

6 Girls Physical Activity During Physical Education 387 data were obtained from a maximum of three girls from a preselected class of The 33 lessons spanned an 8 month period, which allowed the monitoring of the girls during a representative seasonal range of physical education activities. The physical education teachers were instructed to teach their lessons as they usually would. They were asked not to place any special emphasis on activities that would increase heart rates more than usual (e.g., fitness work or circuit training), unless this was what the lesson would normally have focused upon. Means and standard deviations (±) were calculated for all dependent variables. Pearson product moment correlation coefficients assessed the level of association between variables. Two linear regression analyses established whether body composition (i.e., body fat) and cardiorespiratory fitness (i.e., peak VO 2 ) were predictive of physical activity measured by heart rate monitoring and accelerometry. All data were analyzed using SPSS v.10 (SPSS Inc; Chicago, IL) and significance was set at p <.05. Results Descriptive characteristics of the students are presented in Table 1. Each student was monitored during 2.6 ± 0.9 physical education lessons. Some girls were monitored on more occasions than others because of absence from school. Analysis of heart rate data revealed that the girls were engaged in MVPA for 38.5% ± 23.5 of physical education lesson time. Physical activity measured by accelerometry indicated that their movement produced Vmag counts min 1 ± Mean activity duration per lesson was 48.8 min ± Shapiro-Wilk tests of normality confirmed that the principle dependent variables were normally distributed (Vmag counts min 1, Shapiro-Wilk (20) = 0.9, p >.05; MVPA, Shapiro-Wilk (20) = 0.91, p >.05; body fat, Shapiro-Wilk (20) = 0.91, p >.05; peak VO 2, Shapiro-Wilk (20) = 0.98, p >.05). As the assumption of normality had been met, statistical analyses were performed using parametric procedures. Table 2 describes the correlation coefficients for the dependent variables Table 1 Descriptive Characteristics of Students N = 20 M SD Age (yr) Stature (cm) Mass (kg) Body fat (%) Peak VO 2 (ml kg 1 min 1 ) Resting heart rate (beats min 1 ) Resting heart rate variance (%) Peak heart rate (beats min 1 ) RER

7 388 Fairclough analyzed. Physical activity during physical education, measured by both heart rate and accelerometry was inversely related to body fat. Significant negative associations were also observed between this measure of adiposity and cardiorespiratory fitness. Furthermore, peak VO 2 was weakly associated with both measures of physical activity. Multiple linear regression analyses were used to determine whether body composition and cardiorespiratory fitness might predict physical activity during physical education. Body fat, then peak VO 2 were entered into the regression equations according to the strength of their relationship with habitual physical activity. The first regression model produced a significant relationship with Vmag counts min 1, F(2, 17) = 6.26, p <.01. When the predictor variables were applied to a second regression analysis with MVPA as the outcome variable, no significant relationships were noted, F(2, 17) = 1.46, p = Table 3 presents increments of R 2 for both predictor variables in each analysis. For physical activity assessed by accelerometry, body fat accounted for 42% of the variance in girls Vmag counts min 1, with peak VO 2 not contributing. The second regression model predicted 15% of the variance in percent of lesson time the girls engaged in MVPA. Most of this was explained by body fat (10%), with peak VO 2 contributing the remaining 5%. Table 2 Pearson Product Moment Correlation Matrix of Dependent Variables Vmag Body fat min 1 MVPA Peak VO 2 Body fat.65*.32.65* Vmag min MVPA.37 *p <.01. Table 3 Increments of R 2 for Multiple Regression of Physical Activity in PE, on Body Composition and Cardiorespiratory Fitness Incremental R 2 Incremental R 2 Order of entry Vmag counts min 1 MVPA Body fat.42*.1 Peak VO R 2 =.42* R 2 =.15 *p <.01.

8 Girls Physical Activity During Physical Education 389 Discussion This study assessed the physical activity levels of high school girls during physical education lessons. The girls engaged in moderate-to-vigorous intensity physical activity (MVPA) for 38.5% of class time, which is below the USDHHS (2000) 50% criterion. This shortfall has been noted in previous physical education studies employing systematic observation (McKenzie et al., 2000) and heart rate telemetry (Stratton, 1997). While the exact reasons for the deficit are unclear, it does highlight the varied goals implicit within physical education curricula (e.g., cognitive, social, motor, and moral development; Sallis & McKenzie, 1991). Although physical activity is what makes physical education unique from other subjects, its other diverse goals could conflict with the attainment of recommended physical activity targets. The large standard deviations of MVPA and Vmag counts min 1 represented 61.1% and 56.6% of the respective mean values, which illustrates the variability of physical activity within physical education. Differences in motivation, ability levels, and differentiation of content can influence physical activity levels within the same lesson. Moreover, the type of activity can have a significant bearing on the levels of MVPA achieved between different lessons. It may be significant that 14 of the 33 lessons monitored in the present study focused on the invasion games of soccer, hockey, and netball, while the remainder comprised of gymnastics, dance, trampolining, and athletics. It is possible that these invasion game lessons could have positively influenced the mean percentage of time that the girls engaged in MVPA. This contention is supported by Stratton (1997), who noted that children were more active during physical education when involved in invasion games lessons, in comparison to other activities. A further illustration of invasion games potential to effectively promote activity was presented by Yelling, Lockwood, & Swaine (1998). They measured the heart rates of girls grouped by differing levels of body fatness during netball lessons. Each group of girls was engaged in MVPA for more than 50% of lesson time, regardless of body fatness (Yelling et al., 1998). Although the present study did not assess maturity, the mean body fat of 23% is comparable to previously reported data for similarly aged girls (Malina & Bouchard, 1991). Moreover, it is consistent with the increase in body fat to approximately 25%, which occurs during the female adolescent growth spurt (Armstrong & Welsman, 1997). Body fat accounted for 42% of the variance in physical activity measured in Vmag counts min 1. This R 2 value is substantially greater than that reported in LeMura et al. s (2000) study of elementary physical education, which correlated body fat with physical activity using a Caltrac accelerometer (R 2 = 14%). The significant inverse relationship noted between body fat and Vmag counts min 1 (r =.65) suggests that girls with more subcutaneous body fat are less active in physical education than their leaner peers. Similar findings were also reported by LeMura et al. (2000), although Yelling et al. (1998) observed no significant differences in MVPA between British girls of differing body fatness. However, the general trend is for body fat and physical activity to be negatively correlated, which is consistent in studies measuring habitual physical activity of overweight and obese young people (Bar-Or & Baranowski, 1994). When percent of class time engaged in MVPA was used as the measure of physical activity, the magnitude of the correlation with body fat was smaller (r =.32). Similar nonsignificant correlation coefficients have been noted when heart

9 390 Fairclough rate monitoring was used to assess children s free-living physical activity (Armstrong, Williams, Balding, Gentle, & Kirby, 1991a). The regression analysis in the present study revealed that body fat predicted only 10% of MVPA variance in the physical education context. This suggests that body fat may not be a key determinant of girls physical activity levels during physical education, when measured by heart rate telemetry. These findings concur with Welsman & Armstrong s (2000) research, where body fat explained 12% of the variance in girls MVPA in a free-living context. A possible explanation as to why the association between body fat and MVPA was weaker than when physical activity was expressed as movement counts may be that the energy cost of movement for girls with excess body fat is greater than for their leaner counterparts. The augmented energy demand would result in increased heart rate response, which could inflate the amount of MVPA measured by heart rate monitoring, relative to the amount of activity in which the students engaged in (Armstrong & Welsman, 1997). The mean peak VO 2 value of 43.4 ml kg 1 min 1 is similar to those previously reported in 13-year-old girls (Armstrong & Van Mechelen, 1998; Armstrong, Williams, Balding, Gentle, & Kirby, 1991b; Mirwald & Bailey, 1986). Moreover, this value is well above the 35 ml kg 1 min 1 level that has been suggested as a minimal threshold below which a health risk may be represented (Bell, Macek, Rutenfranz, & Saris, 1986). On this basis the girls cardiorespiratory fitness levels were satisfactory and certainly did not compromise their health status. A significant negative association was observed when peak VO 2 was correlated with body fat (r =.65). This suggests that girls with a greater proportion of body fat have lower cardiorespiratory fitness levels than their peers. Moreover, these data are supported by Armstrong et al. (1991), who reported a moderate association (r =.57) between sum of skinfolds and peak VO 2 in 13.1-year-old English girls. As Rowland (1999) concluded, increased adiposity may compound the health risks to adolescent girls compared to leaner peers, as their increased size makes them less likely to engage in health-enhancing physical activity. Peak VO 2 and physical activity in physical education, expressed as MVPA and Vmag counts min 1, were weakly associated. This suggests that cardiorespiratory fitness and physical activity in girls physical education bear little relationship to each other. Confirmation of this was provided by the negligible contribution of peak VO 2 to the variance of physical activity in physical education, measured by both instruments. These results are substantiated by existing habitual physical activity literature, which generally reports weak correlation coefficients (r.2) between peak VO 2 and various physical activity indexes (Morrow & Freedson, 1994). The likely explanation is that most young people do not experience physical activity of sufficient intensity and duration to increase peak VO 2 and that structured training programs appear to be necessary to improve cardiorespiratory fitness (Armstrong & Welsman, 1997). It is acknowledged that the study was limited by the small sample size, variety of physical education lesson content, and contextual factors that are particular to field research in the physical education setting (e.g., teaching styles, environment, group dynamics, etc.). Moreover, absence from school on monitoring days meant that some girls had their activity levels measured on fewer occasions than others. This may have provided some inconsistencies in individual data sets, which could have affected the validity of the analyses. Because of these limitations, the data should be interpreted cautiously with regard to generalizing to other populations.

10 Girls Physical Activity During Physical Education 391 Discrepancies in the strength of correlations between different physical activity measures highlight the advantage of combining instruments when assessing young people s physical activity. In this study the accelerometers measured physical movement, while the heart rate monitors assessed the physiological response to that movement. The correlation between them of r =.26 suggests that each instrument measured a different dimension of physical activity. As well as measuring the body s physiological response to movement, heart rate monitors are also sensitive to fluctuations caused by emotional and climatic changes, which can occur when little or no physical activity is taking place. Weak correlation coefficients create doubt as to the effectiveness of matching heart rate to movement in activities that are intermittent in nature and variable in duration and intensity. It is likely that continuous physical activity of steady intensity produces fewer errors when matching heart rate and movement data (Stratton & Mota, 2000). The resultant effect is more likely to be stronger correlation coefficients than those found in this study. However, the multidimensional nature of children s physical activity in the physical education setting is characterized by variations in intensity and duration (Stratton, 1996), which often preclude children from reaching a physiological steady state. This perhaps offers the best explanation of the weak correlation coefficients between MVPA and Vmag min 1 and concurs with the view of Stratton and Mota (2000) that intermittent activity behaviors are extremely difficult to match with heart rate. The sample of high school girls in this study failed to meet the USDHHS (2000) criterion of being physically active for 50% of lesson time. However, they were involved in MVPA for an average of 19 min per lesson. On the two occasions per week when they attended physical education, these students could have achieved approximately one third of the recommended daily volume of an hour s physical activity. This is a significant amount that could be augmented during other times of the day through lifestyle activities, play, or more structured extracurricular sport or recreation programs. Teaching interventions employing planned physical activity outcomes are needed to improve girls physical activity levels in all physical education lessons, regardless of content. Body fat negatively influenced the amount of activity that took place, but other unidentified factors accounted for the majority of the movement count and MVPA variance. Cardiorespiratory fitness appeared not to have had an influence on girls physical activity during physical education. It is important that this message is made very clear to teachers as well as children. The principal message underpinning curriculum design should be to use physical education as a vehicle to improve the amount of daily physical activity, not enhance fitness levels. Girls who aim for the latter goal could be setting unrealistic goals, which for many would inevitably lead to failure. The negative psychological consequences of this would most likely undermine other efforts to promote physical activity. Recommendations for Programming Physical education lessons that aim to engage girls in MVPA for 50% of class time by targeting optimal physical activity levels as planned outcomes, may have significant benefits for adolescent girls. Previous research illustrates the marked decline in the proportion of adolescent girls who are active on a daily basis (Welsman & Armstrong, 2000). Furthermore, for many girls physical education is their only

11 392 Fairclough source of regular physical activity (Riddoch, Savage, Murphy, Cran, & Boreham,1991). As well as maximizing class time spent in physical activity, physical educators can indirectly influence girls physical activity levels. Teaching methods that enhance physical and social skills, and enjoyment for physical activity, may lead to participation in activity outside of school (Sallis & McKenzie, 1991). Moreover, by setting up girl-only recreational extracurricular clubs, informing students of available opportunities in the local community, and teaching about planning for activity and the benefits of an active lifestyle, teachers can have a significant impact on girls future physical activity participation. The Trois Rivieres study, which focused on a daily physical education intervention, illustrated the powerful influence that physical education can have on female physical activity behavior. More than 20 years after participating in the program, significantly more women from the intervention groups were regularly involved in physical activity, compared to those from control groups (Shephard & Trudeau, 2000). In order to achieve optimal participation, it is possible that girls and boys may benefit from different pedagogic approaches. McKenzie et al. s (2000) observational analysis of physical activity during middle school physical education revealed that girls were most active during structured fitness activities, compared to free play and game play. Conversely, boys expended as much energy during free play as they did in the fitness activities. These data suggest that girls may need structure and teacher direction to initiate and maintain physically active behavior. McKenzie et al. (2000) point out that, variations in motivation, peer expectations, and skill level may inhibit many girls from engaging in MVPA when teacher direction is not available. Thus, appropriately planned physical education may be extremely significant in providing girls with a structured environment for physical activity. Future Research Future work evaluating children s physical activity may be enhanced by employing a combination of measurement methods. This would allow a more accurate assessment of all dimensions of the physical activity spectrum (Saris, 1986). Wherever practicable and possible, studies should consider the measurement of the physiological load (heart rate monitoring), quantity of movement (accelerometry or pedometry), and the quality of movement (systematic observation) within lessons. The quality of information produced from such a combination of methods would allow more effective design of lesson-based interventions to improve activity levels. Such interventions are important as physical education can make a significant contribution to girls volume of daily physical activity. It is clear from this study and previous work that the type of physical education activity that children participate in influences their potential to be physically active. Invasion games appear to consistently provide more scope than other activities for accumulating MVPA. To provide more opportunities for appropriate amounts of physical activity across the curriculum, future work should focus on maximizing MVPA in activities where activity levels are generally lower. Interventions directed at perceived girl-friendly activities, such as dance and individual games, would provide significant opportunities for girls to accumulate more daily MVPA through physical education.

12 Girls Physical Activity During Physical Education 393 Although body fat predicted a significant amount of physical activity variance, the unexplained 58% may be attributed to a multitude of psychological, social, pedagogical, and environmental factors. Multidisciplinary approaches may have greater efficacy in providing insights into girls participation in physical education. By utilizing such methods, teaching interventions can be designed that are underpinned and informed by contemporary physical activity correlates. Thus, enabling factors can be identified and promoted with the specific aim of targeting adolescent girls participation in physical education. Such interventions may require shifts in curriculum content, improved resources, different teaching approaches, and enhanced teacher expertise. Only when physical education departments are willing to embrace and invest in such changes can physical activity interventions be sustainable and achieve their long-term potential. References Anderson, R.H., McCartney, F.J., Shinebourne, E.A., & Tynan, M. (1987). Paediatric Cardiology (Vol. 1). Edinburgh, Scotland: Churchill Livingstone. Armstrong, N., & Van Mechelen, W. (1998). Are young people fit and active? In S. Biddle, J. F. Sallis, & N. Cavill (Eds.), Young and active? Young people and health-enhancing physical activity. Evidence and implications (pp ). London: Health Education Authority. Armstrong, N., & Welsman, J.R. (1997). Young people and physical activity. Oxford, England: Oxford University Press. Armstrong, N., Williams, J., Balding, J., Gentle, P., & Kirby, B. (1991a). Cardiopulmonary fitness, physical activity patterns, and selected coronary risk factor variables in 11 to 16 year olds. Pediatric Exercise Science, 3, Armstrong, N., Williams, J., Balding, J., Gentle, P., & Kirby, B. (1991b). The peak oxygen uptake of British children with reference to age, sex and sexual maturity. European Journal of Applied Physiology, 62, Bar-Or, O., & Baranowski, T. (1994). Physical activity, adiposity and obesity among adolescents. Pediatric Exercise Science, 6, Bell, R.D., Macek, M., Rutenfranz, J., & Saris, W.H. (1986). Health indicators and risk factors of cardiovascular diseases during childhood. In J. Rutenfranz, R. Mocellin, & F. Klimt (Eds.), Children and exercise XII (pp ). Champaign, IL: Human Kinetics. Biddle, S., Sallis, J.F., & Cavill, N. (Eds.). (1998). Young and active? Young people and health-enhancing physical activity. Evidence and implications. London: Health Education Authority. Centers for Disease Control. (2001). Deaths: Leading causes for National Vital Statistics Reports, 49(11), Centers for Disease Control. (2002, June 18). Prevalence of overweight among children and adolescents: United States Retrieved July 5, 2002 from nchs/products/pubs/pubd/hestats/overwght99.htm Corbin, C.B., & Pangrazi, R.P. (1998). Physical activity for children: A statement of guidelines. Reston, VA: NASPE Publications. DeLany, J.P. (1998). Role of energy expenditure in the development of pediatric obesity. American Journal of Clinical Nutrition, 68, 950S-955S. Department for Education and Employment / Qualifications and Curriculum Authority. (1999). Physical education. The national curriculum for England. London: DFEE/QCA.

13 394 Fairclough Department of Health. (1995). Health of the nation: Obesity, reversing the increasing problem of obesity in England. London: Department of Health. Gutin, B., Islam, S., Manos, T., Cucuzzo, N., Smith, C., & Stachura, M.E. (1994). Relation of body fat and maximal aerobic capacity to risk factors for atherosclerosis and diabetes in black and white seven-to-eleven year old children. Journal of Pediatrics, 125, LeMura, L.M., Andreacci, J., Carlonas, R., Klebez, J.M., & Chelland, S. (2000). Evaluation of physical activity measured via accelerometry in rural fourth grade children. Perceptual and Motor Skills, 90, Lohman, T.G., Roche, A.F., & Martorell, R. (1988). Anthropometric standardization reference manual. Champaign, IL: Human Kinetics. Malina, R.M., & Bouchard, C. (1991). Growth, maturation and physical activity. Champaign, IL: Human Kinetics. McKenzie, T.L., Marshall, S.J., Sallis, J.F., & Conway, T.L. (2000). Student activity levels, lesson context, and teacher behavior during middle school physical education. Research Quarterly for Exercise and Sport, 71, Melanson, E.L., & Freedson, P.S. (1996). Physical activity assessment: A review of methods. Critical Reviews in Food Science and Nutrition, 36, Mirwald, R.L., & Bailey, D.A. (1986). Maximal aerobic power. London: Sports Dynamics. Morrow, J., & Freedson, P. (1994). Relationship between habitual physical activity and aerobic fitness in adolescents. Pediatric Exercise Science, 6, Riddoch, C. (1998). Relationships between physical activity and health in young people. In S. Biddle, J.F. Sallis, & N. Cavill (Eds.), Young and active? Young people and healthenhancing physical activity. Evidence and implications. (pp ). London: Health Education Authority. Riddoch, C., Savage, J.M., Murphy, N., Cran, G.W., & Boreham, C. (1991). Long term health implications of fitness and physical activity patterns. Archives of Disease in Childhood, 66, Rowland, T.W. (1993). Pediatric laboratory exercise testing. Champaign, IL: Human Kinetics. Rowland, T.W. (1996). Developmental exercise physiology. Champaign, IL: Human Kinetics. Rowland, T.W. (1999). Adolescence: A risk factor for physical inactivity. President s Council on Physical Fitness and Sports Research Digest, 3(6), 1-8. Sallis, J.F. (1993). Epidemiology of physical activity and fitness in children and adolescents. Critical Reviews in Food Science and Nutrition, 33, Sallis, J.F., & McKenzie, T.L. (1991). Physical education s role in public health. Research Quarterly for Exercise and Sport, 62, Sallis, J.F., & Patrick, K. (1994). Physical activity guidelines for adolescents: Consensus statement. Pediatric Exercise Science, 6, Saris, W. (1986). Habitual physical activity in children: Methodology and findings in health and disease. Medicine and Science in Sports and Exercise, 18, Shephard, R.J. (1995). Physical activity, fitness and health: The current consensus. Quest, 47(3), Shephard, R.J., & Trudeau, F. (2000). The legacy of physical education: Influences on adult lifestyle. Pediatric Exercise Science, 12, Slaughter, M.H., Lohman, T.G., Boileau, R.A., Horswill, C.A., Stillman, R.J., Van Loan, M.D., & Bemben, D.A. (1988). Skinfold equations for estimation of body fatness in children and youth. Human Biology, 56,

14 Girls Physical Activity During Physical Education 395 Stratton, G. (1996). Children s heart rates during physical education lessons: A review. Pediatric Exercise Science, 8, Stratton, G. (1997). Children s heart rates during British physical education lessons. Journal of Teaching in Physical Education, 16, Stratton, G., & Mota, J. (2000). Girls physical activity during primary school playtime: A validation study using systematic observation and heart rate telemetry. Journal of Human Movement Studies, 38, Tremblay, M.S., Inman, J.W., & Willms, J.D. (1999). Relationships between physical activity, self-esteem and academic achievement in 10 and 11 year old children. Pediatric Exercise Science, 11, 255. United States Department of Health and Human Services. (2000). Healthy People 2010: Understanding and improving health. Washington, DC: DHHS. Welsman, J., & Armstrong, N. (1997). Physical activity patterns of 5-11 year old children. In N. Armstrong, B.J. Kirby, & J. Welsman (Eds.), Children and exercise XIX (pp ). London: E & F Spon. Welsman, J., & Armstrong, N. (2000). Physical activity patterns in secondary school children. European Journal of Physical Education, 5, Yelling, M., Lockwood, A., & Swaine, I. (1998). A comparison of relative heart rate responses in girls of differing body fatness within the same physical education lesson. In R. Fisher, C. Laws, & J. Moses (Eds.), Active living through quality physical education. ICHPER SD 8th European Congress (pp ). Leeds, England: PEA UK. Acknowledgments The data described in this paper contribute to a doctoral study examining physical activity during high school physical education lessons. The author would like to thank the school staff and students who participated in this study, as well as the reviewers for their helpful and insightful comments.

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