Journal of Physical Activity and Health, 2015, 12, 982  -989 http://dx.doi.org/10.1123/jpah.2014-0151 © 2015 Human Kinetics, Inc.

ORIGINAL RESEARCH

Physical Activity Trajectories During Daily Middle School Physical Education Ryan D. Burns, Timothy A. Brusseau, and James C. Hannon Background: Optimal levels of moderate-to-vigorous physical activity (MVPA) have been shown to improve health and academic outcomes in youth. Limited research has examined MVPA trajectories throughout a daily middle school physical education (PE) curriculum. The purpose of this study was to examine MVPA trajectories over a daily PE curriculum and the modifying effects of sex, body composition, and cardiorespiratory endurance. Methods: One hundred 7th- and 8th-grade students participated in daily PE lessons. There were 66 lessons throughout the semester. MVPA was monitored during each lesson using NL-1000 piezoelectric pedometers. Students were classified into FITNESSGRAM Healthy Fitness Zones using estimated VO2 Max and Body Mass Index (BMI). A population averaged generalized estimating equation was employed to examine MVPA trajectories. Results: On average, students’ MVPA decreased over time (β = –0.35, P < .001). Poor student VO2max classification significantly modified the trajectories (β = –0.14, P < .001), however poor BMI classification did not have a modifying effect (β = 0.03, P = .158). Conclusions: MVPA decreased in daily PE over time and cardiorespiratory endurance significantly modified the trajectories. The results support that extra efforts have to be made by teachers and students to sustain MVPA behaviors over a semester. Keywords: adolescent, measurement, pedometry, physical fitness

Optimal levels of moderate-to-vigorous physical activity (MVPA) have numerous health and academic performance benefits that are established in the current literature. These benefits include improved clinical health measures such as blood pressure, triglycerides and cholesterol,1,2 as well as increases in fat-free mass and decreases in fat mass,3 improved self-efficacy and well being,4 and improved cognitive functioning leading to increased academic performance in school settings.5 Despite these benefits of elevated levels of daily MVPA, fewer than 12% of boys and 4% of girls of adolescent age, 12 to 15 years, achieve recommended daily amounts suggested by the U.S. Department of Health and Human Services (USDHHS), which recommends at least 60 minutes of MVPA per day.6,7 Indeed, it has been shown that during the developmental years, MVPA tends to decline, which may effect relative aerobic capacity (VO2max, expressed in terms of ml·kg-1·min-1).8–10 Less than optimal behaviors and traits can then track through adolescence and into adulthood where they may affect morbidity and mortality.11,12 The majority of adolescents in the U.S. spend a significant portion of weekday time in school settings. Although the majority of school time is sedentary, physical education (PE) class gives adolescents of developmental age opportunities to engage in MVPA to improve physical and cognitive health. Approximately 80% of states in the U.S mandate physical education in middle school,13 where a recommendation for these classes to achieve at least 50% of time engaged in MVPA has been set by Healthy People 2010.14 Students with opportunities for daily PE have a particular advantage to achieve the daily 60-minute MVPA guideline set by the USDHHS, but there has been limited research examining if daily PE classes actually sustains elevated MVPA behaviors over time. To determine the trajectories of MVPA behaviors, it is important

The authors are with the Dept of Exercise and Sport Science, University of Utah, Salt Lake City, UT. Burns ([email protected]) is corresponding author. 982

to employ objective measures that can be feasibly administered to adolescent youth during daily PE. Although there is an abundance of research examining MVPA, specifically in adolescents, measurements of these behaviors have often been cross-sectional in nature or have relied on self-report questionnaires or systematic observation where a low percentage of variance of true MVPA is actually explained.15,16 Studies employing more objective methods of measurement such as accelerometers yield accurate representation of MVPA, but data are often collected during relatively short 1- or 2-week intervals and do not monitor MVPA behaviors over longer, more continuous time periods.10 To get an accurate representation of true MVPA behavior in school PE settings, it is important to monitor MVPA in a feasible and sustainable manner while employing objective measurement on a daily basis. Pedometers have the benefit of being a reliable and valid measure of physical activity, in addition to their ease of administration and interpretation.17,18 Therefore, monitoring ambulatory physical activity behavior continuously over extensive time periods in physical education settings is very practical when using pedometers. Using pedometers, physical activity behaviors can be monitored on a daily basis with relative ease and with a high degree of criterion-related validity.19 To determine if a daily PE curriculum is taken full advantage of to achieve optimal levels of physical activity, understanding MVPA behavior trajectories over time is of critical importance. It is also of great importance to determine the influence of sex, body composition, and cardiorespiratory endurance on these trajectories. Much research has supported sex differences in physical activity behaviors in children and adolescents.6,9,11,12 Findings from these studies consistently show boys engaging in greater amounts of MVPA compared with girls, especially across the adolescent years. However, how a student’s sex may influence MVPA trajectories within the context of a daily PE curriculum is unknown. In addition, cross-sectional studies have shown both BMI and cardiorespiratory endurance, operationally defined by aerobic capacity or VO2max, have moderate relationships with MVPA behaviors.1,20–23

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One approach to examine these 2 domains of health-related fitness within a longitudinal model would be to use FITNESSGRAM’s 3 Healthy Fitness Zone scheme to classify students into the Healthy Fitness Zone (HFZ), Needs Improvement Zone-some risk (NIZsome risk), and Needs Improvement Zone-health risk (NIZ-health risk).24 Doing this will enable comparisons of MVPA trajectories for students with optimal and less than optimal body composition and cardiorespiratory endurance. Relating sex, body composition, and cardiorespiratory endurance to longitudinal MVPA behaviors will allow insights for the physical traits that may influence MVPA behavior over time in the context of a daily PE curriculum. Doing so will allow practitioners to develop teaching methods or interventions aimed at sustaining or improving MVPA behaviors in populations that tend to have to decreased levels over time. Therefore, the purpose of this study was to determine MVPA trajectories over an entire semester for a daily PE curriculum and to determine if sex, body composition, or cardiorespiratory endurance significantly modifies these trajectories in a sample of 7th and 8th grade students. It was initially hypothesized that MVPA behaviors would remain stable throughout the entire semester. In addition, it was initially hypothesized that sex, body composition, and cardiorespiratory endurance would modify MVPA trajectories by having girls and students classified into the NIZ subzones showing significant decreases in MVPA behavior compared with boys and students classified into the HFZ.

Methods Participants Data were collected on a convenience sample of 160 7th- and 8thgrade students recruited from a public middle school located in the southwestern US. Each student had the same certified physical education teacher throughout the entire semester and the curriculum was identical for all class periods across all age groups. Of these 160 students, 100 students (38 girls, 62 boys; mean age = 13.3 years, SD = 0.46 years) were used for analysis. Incomplete student data led to a decrease in the sample size. Written assent was obtained from the students and written consent was obtained from the parents before data collection. The University Institutional Review Board (IRB), participating school district, and principal from the participating school approved the protocols used in this study.

Instrumentation Each student’s physical activity was monitored using NL-1000 piezoelectric pedometers (New Lifestyles Inc., Lee’s Summit, MO, USA), which recorded total number of steps and time (in minutes) of MVPA for the entirety of the PE class. The NL-1000 uses a piezoelectric mechanism similar to accelerometers, therefore, in addition to counting steps, the NL-1000 also records time spent in MVPA. The NL-1000 MVPATM timer can be set to record intensities above any 1 of 9 discrete intensity levels. The NL-1000 model detects the maximum acceleration over a 4-second epoch, and each epoch is subsequently categorized into 1 of 11 activity intensity levels using the same internal processor as the Lifecorder EX (Suzuken Co. Ltd, Nagoya, Japan).19 A detailed description of this mechanism and physical activity intensity categorization schema were previously reported.25 The most common definition of MVPA is activity that is at or above an intensity of 3 metabolic equivalents (METs).26 Therefore, the NL-1000 MVPA timers in this study were set to record activity above

a threshold of 2.9 METs (Level 3). The manufacturers recommended setting to measure MVPA is at a Level 4, equivalent to a threshold of 3.6 METs. However, since MVPA is usually defined at intensities at or above 3 METs, the setting the NL-1000 at activity Level 3 (> 2.9 MET) was determined to be a more appropriate estimation of time spent in MVPA. McMinn et al27 found statistically significant correlations between the GT1M accelerometer and the NL-1000 across different activity modes with intraclass correlations (ICCs) ranging from ICC = 0.72 to 1.00, supporting acceptable relative validity. In addition, there was evidence for absolute validity as there were similar estimates found between the NL-1000 estimated and GT1Mestimated MVPA across most of the examined intensities and modes of physical activity. The NL-1000 therefore showed promising validity evidence as an inexpensive and convenient method of measuring MVPA in school settings,27 and was therefore determined appropriate to estimate MVPA in the current study.

Procedures All data collection took place over an entire Fall semester and involved a total of 66 physical education classes. Each class period was approximately 40 minutes in duration and was held 5 days a week (Monday through Friday). The curriculum involved a combination of team sports, individual games, and health-related fitness activities. Units were 2 to 3 weeks long with 1 day per week focused on fitness. Units were taught both indoors and outdoors depending on the activity (ie, basketball inside, football outside). Occasionally rain would require students to be inside. Lessons included skill development, small-sided games, and concluded with team or individual tournaments. Fitness activities included circuit training, aerobic exercise, and flexibility training. The units progressed in the following order throughout the semester: ultimate frisbee, soccer, volleyball, badminton, football, and basketball. Baseline measures included collecting height (to the nearest cm) via a portable stadiometer (Seca 213; Chino, CA, USA) and weight (to the nearest 0.1 kg) via a portable medical scale (Tanita HD-314; Arlington Heights, IL, USA) in addition to the Progressive Aerobic Cardiovascular Endurance Run (PACER). Body Mass Index (BMI) was calculated dividing each student’s weight (in kg) by the square of his or her height (in meters2). The 20-m PACER test was administered indoors on a marked gymnasium floor with background music and cadence given by an audio CD. No more than 10 students participated in the assessment at any given time. Students ran from one floor marker to another marker set 20-m apart while keeping pace with a prerecorded cadence. The test was terminated when a student twice failed to reach the opposite marker in the allotted time frame or when he/she voluntarily stopped. PACER scores were recorded as Laps.24 Students put on the NL-1000 pedometer immediately after changing for class. Each student had an identification number that matched the worn pedometer. Students wore his/her pedometer against their waist at the level of the superior boarder of the iliac crest on the right side above the right knee. Before each PE lesson, pedometer step count monitors were checked to ensure a reading of zero. Pedometers were also randomly calibrated using the “shake test” before the start of each class to ensure accurate measurement of step counts according to the recommended procedures given by Vincent and Sidman28 for validating digital pedometers. At the end of each class, pedometers were returned before changing. The senior author recorded all data once per week (as the monitor has a 7 day recall). The PE teacher marked any students that were absent or late/left early and that data were subsequently excluded.

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Statistical Analysis Data from the final sample were screened for outliers using box plots and normality was checked using k-density plots and Q-Q plots. Each student’s BMI was classified into 1 of the 3 FITNESSGRAM age and sex specific body composition Healthy Fitness Zones. Students’ PACER scores were converted to estimated VO2max using a validated prediction equation developed by Mahar et al29 and then classified into 1 of the 3 FITNESSGRAM age and sex specific aerobic capacity Healthy Fitness Zones. Preliminary analyses were conducted for descriptive purposes and to examine mean group differences in body composition, cardiorespiratory endurance, and physical activity. Differences between the sexes and between the grades on the anthropometric data, cardiorespiratory endurance data, total MVPA, and mean MVPA were analyzed using 2 × 2 Factorial ANOVA tests. In addition, 3 × 3 Factorial ANOVA tests were employed to examine differences among body composition and aerobic capacity Healthy Fitness Zone classification on total MVPA and mean MVPA. If statistically significant differences were found a Bonferroni post hoc analysis was employed with the alpha level adjusted appropriately using the Bonferroni method. Longitudinal physical activity data were entered into the statistical software package using a wide format, but was then converted to a long format, which is most appropriate for longitudinal analysis. MVPA data were determined to be Missing Completely at Random (MCAR) as no one variable was significantly related to the missing data for that variable. Therefore, the data were determined to be suitable for longitudinal analysis even though not all students had 66 days of physical activity measurement. A generalized estimating equation (GEE) was used to examine the population-averaged mean and longitudinal effects on physical education MVPA behavior over an entire semester. The GEE approach was determined to be more appropriate than a General Linear Mixed Model (GLMM) because of most interest were the population-averaged trajectories and not individual-specific trajectories, which may lead to biased inference if the unverifiable assumptions of GLMM are mis-specified.30 Mean effects included the effect of sex and body composition and aerobic capacity Healthy Fitness Zone classification on MVPA behavior across all time points. Boys and the HFZs for body composition and aerobic capacity were used as the reference groups for all comparisons. Longitudinal effects

included the effect of Time (in days) on MVPA behavior for the entire sample in addition to Sex × Time interactions and Fitness Zone × Time interactions to determine if students’ sex or classification into body composition or aerobic capacity Healthy Fitness Zones significantly modified MVPA behavior trajectories. Examination of the within-subject correlations between all time-points revealed an unstructured matrix, therefore an unstructured working correlation matrix was determined most appropriate for GEE analysis to account for within-subject dependence that is present in panel data. In addition, standard errors were calculated from GEE using the robust sandwich estimator to ensure precision of the parameter estimates even if the correlation structure was misspecified. The coefficients, robust standard error, statistical significance, and 95% Confidence Intervals were reported for all covariates from the GEE. Alpha level was set at P ≤ .05 and all analyses were carried out using STATA v12.0 statistical software package (College Station, TX, USA).

Results The mean anthropometric, cardiorespiratory endurance, and physical activity data are presented in Table 1. Boys in this sample were taller than girls (P < .001), but there were no statistically significant differences in weight or BMI between sexes. Regarding the cardiorespiratory endurance and physical activity data, boys had higher PACER scores, estimated VO2max, mean MVPA, and total MVPA across the entire semester (P < .001). There were no statistically significant differences among any of the aforementioned parameters between grade levels. Figure 1 and Figure 2 present the group differences in total MVPA and mean MVPA for students classified into FITNESSGRAM’s aerobic capacity Healthy Fitness Zones, respectively. There were no statistically significant differences among students classified into the body composition Healthy Fitness Zones in total MVPA (F(2, 95) = 0.52, P = .595) or mean MVPA (F(2, 95) = 0.32, P = .728). There were statistically significant differences found among students classified into the aerobic capacity Healthy Fitness Zones in both total MVPA (F(2, 95) = 3.25, P = .043) and mean MVPA (F(2, 95) = 3.72, P = .027). Bonferroni post hoc analyses revealed differences between the HFZ and NIZ-some risk for both total and mean MVPA (see Figure 1 and Figure 2). No interactions were found in the analysis.

Table 1  Descriptive Statistics for the Total Sample and Within Specific Sex Groups (Means and Standard Deviations) Total (N = 100) Mean

Girls (n = 38)

SD

Mean

Boys (n = 62) SD

Mean

SD

Height (m)

1.63

0.09

1.60

0.08

1.65*

0.09

Weight (kg)

55.06

15.70

54.48

17.21

55.42

14.83

BMI (kg·m-2)

20.38

4.26

20.82

4.73

20.11

3.96

PACER (laps)

46.82

21.87

39.02

17.96

51.71*

22.82

VO2max mL·kg-1·min-1

47.23

6.92

43.32

5.14

49.63*

6.80

Total steps

575.54

178.25

490.13

164.65

627.89*

166.70

Mean steps

11.22

3.12

9.73

3.18

12.12*

2.73

Abbreviations: BMI, Body Mass Index; PACER, Progressive Cardiovascular Endurance Run. * Statistically significant gender differences, P < .01. Note. Bold indicates statistical differences compared to girls. JPAH Vol. 12, No. 7, 2015

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Figure 1 — Total MVPA differences across aerobic capacity Healthy Fitness Zones (Means ± SD). * Statistically significant group differences compared with HFZ, P < .01.

Figure 2 — Mean MVPA differences across aerobic capacity Healthy Fitness Zones (Means ± SD). * Statistically significant group differences ­compared with HFZ, P < .01.

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Table 2 presents the results from GEE using an unstructured correlation matrix and the robust sandwich estimator. Students classified into NIZ-some risk and NIZ-health risk aerobic capacity Healthy Fitness Zones had on average lower MVPA across all times-points compared with students classified into the HFZ after accounting for the other covariates in the model (P < .05). There was no effect of sex or body composition Healthy Fitness Zone classification on mean MVPA across all time points. Regarding the longitudinal effects, Time had a statistically significant β-coefficient,

suggesting that as students progressed in their PE curriculum by 1 day, MVPA during PE decreased on average by 0.35 minutes (P < .001) after controlling for the other covariates in the model. The unadjusted averaged trajectory is depicted in Figure 3 using a spaghetti plot, which shows the individual and averaged MVPA predicted trajectories for all students as they progressed through the semester. In addition, there were statistically significant Fitness Zone × Time interactions for both NIZ-some risk and NIZ-health risk aerobic capacity subzones. These results suggest that when

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Table 2  Mean and Longitudinal Effects on MVPA From a Generalized Estimating Equation Using Robust Standard Errors and an Unstructured Correlation Matrix β Coefficient

Robust SE

Significance

95% CI

–1.51

1.09

.166

–3.65, 0.63

Mean Effects  Girls   BMI NIZ-some risk

0.23

0.90

.800

–1.54, 2.01

  BMI NIZ-health risk

–0.04

0.75

.960

–1.52, 1.44

 VO2max NIZ-some risk

–2.91

1.08

.004

–4.87, –0.95

 VO2max NIZ-health risk

–2.68

1.36

.050

–5.37, –0.01

–0.35

0.01

< .001

–0.38, –0.33

Longitudinal Effects   Time (days)   Girls × Time

0.03

0.02

.152

–0.01, 0.06

  BMI NIZ-some risk × Time

0.05

0.03

.146

–0.02, 0.11

  BMI NIZ-health risk × Time

0.03

0.02

.158

–0.01, 0.07

 VO2max NIZ-some risk × Time

–0.06

0.03

.020

–0.11, –0.01

 VO2max NIZ-health risk × Time

–0.14

0.03

< .001

–0.21, –0.07

Abbreviations: NIZ, Needs Improvement Zone; BMI, Body Mass Index; SE, Standard Error; 95% CI, 95% Confidence Interval.

Figure 3 — Spaghetti plot with an averaged trend line displaying individual and averaged MVPA trajectories during daily physical education over a semester (N = 100). JPAH Vol. 12, No. 7, 2015

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compared with students classified into the HFZ for aerobic capacity, students classified into the NIZ-some risk and NIZ-health risk subzones showed on average statistically significant greater decreases in MVPA in PE over time (P < .05). Interestingly, no statistically significant Sex × Time interaction or body composition Fitness Zone × Tiime interactions was found.

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Discussion The purpose of this study was to examine MVPA trajectories during daily PE over the course of a semester and the modifying effects of sex, body composition, and cardiorespiratory endurance in a sample of middle-school students. The results indicate that as the semester progressed, there was on average a decrease in MVPA behaviors in this sample of 7th- and 8th-grade students. In addition, students that were classified into any of the 2 aerobic capacity NIZ subzones showed statistically greater declines in MVPA behavior compared with students who were classified into the HFZ. Sex and body composition classification, estimated via BMI, did not modify MVPA trajectories. This study suggests that in adolescents, MVPA behaviors tend to decrease over time during a daily PE curriculum. The declines in MVPA seen in adolescents from larger longitudinal studies are supported by this research,9,10 with the declines in PE classes possibly marginally contributing to the overall declines in MVPA that were displayed in larger studies. In addition, it was also shown that cardiorespiratory endurance, measured by estimated aerobic capacity (VO2max), had a greater effect on MVPA behavior over time than a student’s sex or body composition, measured by BMI. This specific finding contrasts with previous research describing the longitudinal relationship between BMI and MVPA,9,10,31,32 but adds important insights regarding the importance of cardiorespiratory endurance. The physiological trait of having high levels of aerobic capacity (VO2max) may not only be a consequence of elevated MVPA throughout youth,33 but also a determinant of prospective daily PE MVPA behaviors over time. The average decrease in MVPA over time for the students participating in this study was not expected. An average decrease of 0.35 minutes of MVPA per day was seen after adjusting for other covariates in the model. This average daily decrease relates to a decrease of 1.75 minutes per week, which over the course of a semester, translates to a significant decrease in MVPA behavior. All students had the same PE teacher and participated in the same curriculum throughout the semester. Although PE unit subject area highly affects MVPA behavior, all lessons were designed to be similar in instruction time, practice time, and game time for each of the sport skill units. There are psychometric variables, such as intrinsic motivation and amotivation, which have shown to influence MVPA behaviors in school settings.34 Thus throughout a daily PE curriculum, there could be significant decreases in motivation to perform activities, which would therefore lead to reduced MVPA. Studies have reported a direct correlation between motivation and students’ physical activity levels in school and after school settings.35–37 Physical activity enjoyment, a subconstruct of motivation, specifically may have modified MVPA behaviors throughout daily PE since daily PE can manifest repetitive activities. However, these constructs were not examined in this study so no conclusions can be made. In addition, other factors may have influenced behaviors as well such as outdoor temperature, teacher motivation, and access to gym space and equipment. Regardless of the factors leading to reduced physical activity,

this research indicates that declines in the MVPA make it difficult for the child to achieve 60 min per day recommended by health agencies, even with the implementation of a daily PE curriculum. A student’s sex did not seem to influence MVPA behavior trajectories in this sample over the course of the semester. Preliminary analysis showed that boys displayed statistically greater total and mean MVPA compared with girls.6,10–12 This finding supports previous research concerning sex differences in MVPA behavior in school and after-school settings.6,10–12 However, after controlling for other covariates in the longitudinal model, the differences between the sexes became statistically insignificant. In addition, sex did not modify the trajectories of MVPA across the semester compared with boys. This specific finding suggests that both boys and girls, on average, had similar rates of decrease in MVPA behavior across the semester. Therefore, the factors that may have influenced the decrease in MVPA (motivation/enjoyment, weather, unit subject, etc.) affected boys and girls similarly. However, a consideration should be that there were an unequal number of boys and girls in the sample. This may have affected the results and must be considered before generalizations can be made. Previous research has shown highly conflicting results on the relationships between MVPA and VO2max.38 Factors contributing to these differences include how MVPA is measured (self-report vs. objective; cross-sectional vs. longitudinal) and also how VO2max is assessed and expressed (submaximal vs. maximal testing; per kg of body mass vs. per kg of fat-free mass). The current study had VO2max estimated from a validated prediction equation using the PACER test.29 It is unknown whether a direct VO2max measurement would have altered the results seen in this study. Despite this, the results suggest that students who are physically fit (high relative VO2max) will tend to have less of a decline in MVPA trajectories over time in PE compared with students that are not physically fit. It can be assumed from research that high physical activity during childhood may be a determinant of elevated VO2max.22,30 If VO2max is expressed as (mL·kg-1·min-1), then decreases in body weight resulting from chronically elevated MVPA28 will inherently increase the value of the expression of aerobic capacity, regardless of any increases in oxygen consumption capabilities. However, there is very limited research actually examining this phenomenon in the current literature using longitudinal studies. What this study does provide evidence for is that low fitness, as a physiological trait, negatively modifies MVPA behavior. Therefore, in addition to the concurrent health risk of having poor cardiorespiratory endurance, it seems that it may influence prospective healthy behaviors as well. Interestingly, BMI did not have any relationship with MVPA in this population of adolescents. Previous research has shown that elevated MVPA over time is associated with a decrease in BMI percentile rank.28,39 Cross-sectional studies have also shown that students in high BMI classification percentiles have significantly lower self-report and objective MVPA compared with children in lower BMI percentiles.15 Indeed, one of the primary reasons for promoting increased MVPA in youth is to attenuate the increases in body weight that may accrue for the developmental years.13 Therefore, BMI having no relationship with MVPA conflicts with these previous findings. There are 2 reasons why BMI may have not shown significant relationships with MVPA in this study. One is that the majority of adolescents in this sample (72%) were classified as in the HFZ using FITNESSGRAM’s age and sex specific standards. Therefore, the number of adolescents classified into the NIZ subzones may not have been large enough to see any meaningful relationship on longitudinal MVPA. Secondly, BMI does have inherent limitations

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as a body composition index. It fails to take into account the distribution of fat free mass and fat mass.40 Also, it does not specify where excess body weight is distributed, as fat deposited around the visceral abdominal region is shown to be more clinically relevant compared with subcutaneous deposits.41 Given the limitations of BMI, the current research supports that cardiorespiratory endurance may be just as important than body weight or BMI on influencing healthy behaviors that can affect long-term mortality.42,43 Indeed, high fitness has shown to have a protective effect on cardiovascular disease risk, even if an adolescent is overweight.44 Achieving a high fitness level may also yield favorable MVPA behaviors in adolescents as well, as supported by the current research. There were limitations to this study that may have affected the results. This study only included 1 school and 1 PE teacher, therefore MVPA behavior trajectories may have been different if more than 1 teacher and institution were examined. In addition, although pedometers are an objective method of MVPA measurement, accelerometers remain preferable as they can more accurately measure the intensity of ambulatory activity. All class periods involved in this study were coeducational, therefore results can only be generalized to middle school daily coeducational PE. Although the trends in MVPA clearly decreased in this sample, there are a number of factors that may have led to the reduction in MVPA behaviors including but not limited to weather, gym space, motivation, and sport unit. This study did not explore these potential factors relating to the decrease in behaviors but rather merely quantified the decrease over a semester. What this study does suggest is that MVPA behaviors may decrease over time in daily PE, thus attenuating the benefits of a daily PE curriculum in the context of optimizing healthy physical activity behaviors. Finally, body composition and cardiorespiratory endurance were both estimated using field measurements. It is unknown the influence of more direct measures of adiposity (% body fat) and aerobic capacity (Laboratory VO2 Max) have on MVPA trajectories in adolescents. In conclusion, MVPA behaviors tend to decrease over time during daily PE in middle school students. Cardiorespiratory endurance modified these trajectories while a student’s sex and BMI did not have a significant affect in this sample of adolescents. Practitioners, PE specialists, and PE teachers need to continue to develop effective curricula and teaching methods that attenuate decreases in MVPA behavior during daily PE in middle-school students. Examining the effects of health-related fitness programming such as SPARK compared with traditional (direct) instruction during daily PE may be worthwhile to determine if various PE curricula can sustain MVPA levels of time. Future research needs to further examine the factors that may influence decreases in MVPA behaviors over time and should also compare different pedagogical strategies on objective MVPA behavior over time for students participating in daily PE. Finally, future research also needs to examine the relationships between body composition, cardiorespiratory endurance, and MVPA using more accurate methods of measurement. This study provides unique insights on longitudinal MVPA behaviors in students who participate in a daily PE curriculum. If declines in MVPA behaviors in daily PE are supported in future research, PE teachers and specialists need to devise more effective strategies to sustain MVPA behaviors (less class management, less activity transition time, etc.) so that physical activity is optimized on a daily basis. Since the health and cognitive benefits of MVPA are numerous, it is well worth the effort to sustain elevated MVPA in adolescents throughout their youth to attenuate the health problems and academic under-achievement that may manifest due to excess sedentarism.

Acknowledgments The authors would also like to thank the parents, teachers, and students of Clayton Middle School. This work was partially funded for by a grant from the American Alliance for Health, Physical Education, Recreation, and Dance.

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