Does Weight Status Influence Associations Between ...

Hume,Development Okely, Bagley, Telford, Booth, Crawford, and Salmon Motor Research Quarterly for Exercise and Sport ©2008 by the American Alliance for Health, Physical Education, Recreation and Dance Vol. 79, No. 2, pp. 158–165

Does Weight Status Influence Associations Between Children’s Fundamental Movement Skills and Physical Activity? Clare Hume, Anthony Okely, Sarah Bagley, Amanda Telford, Michael Booth, David Crawford, and Jo Salmon

This study sought to determine whether weight status influences the association among children’s fundamental movement skills (FMS) and physical activity (PA). Two hundred forty-eight children ages 9–12 years participated. Proficiency in three object-control skills and two locomotor skills were examined. Accelerometers objectively assessed physical activity. Body mass index was calculated to determine weight status. Correlations between physical activity and FMS proficiency were evident among boys and girls. No significant interaction was apparent when examining FMS proficiency scores, PA variables, and weight status. Future studies should examine a broader range of skills and types of activities to better characterize this relationship and to inform the promotion of movement skill proficiency and PA.

Key words: motor competence, motor skills, overweight, pediatric

T

he proportion of overweight and obese children has increased substantially both in Australia (Booth et al., 2003), and internationally (Wing et al., 2001). In developed countries, obesity is now a leading modifiable risk factor for a number of chronic conditions including Type 2 diabetes and hypertension (Wing et al., 2001). Participation in physical activity is an important element of weight gain prevention among children (Williamson et al., 1993). Evidence of declining cardiorespiratory

Submitted: April 11, 2006 Accepted: March 20, 2007 Clare Hume, Sarah Bagley, David Crawford, and Jo Salmon are with the Center for Physical Activity and Nutrition Research at Deakin University. Anthony Okely is with the Child Obesity Research Center at the University of Wollongong. Amanda Telford is with the Division of Exercise Sciences, School of Medical Sciences at RMIT University. Michael Booth is with the Center for Research into Adolescents’ Health at the University of Sydney.

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fitness levels support concerns of inadequate energy expenditure among a substantial proportion of children (Tomkinson, Leger, Olds, & Cazorla, 2003) and declines in some types of physical activity, specifically active transport (Salmon, Timperio, Cleland, & Venn, 2005). Fundamental movement skills (FMS) are an integral part of a primary school’s curriculum for personal development, health, and physical education. Their position is based on the importance of motor development to children’s physical, cognitive, and social growth and development (Payne & Isaacs, 1995) and that FMS are the foundations of a physically active lifestyle (Gallahue & Ozmun, 2002). These skills also seem to be related young people’s health. For example, children and adolescents with greater fundamental movement skill proficiency tend to be more physically active (Okely & Booth, 2000; Saakslahti et al., 1999; Ulrich, 1987), have higher levels of aerobic fitness (Okely, Booth, & Patterson, 2001a) and self-esteem (Ulrich, 1987), and are less likely to be overweight (Okely, Booth, & Chey, 2004). Because of their educational and health benefits, FMS development is one of the best investments for turning children on to physical activity and preventing and treating child obesity by giving children the actual

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Hume, Okely, Bagley, Telford, Booth, Crawford, and Salmon

and perceived physical competence to be physically active (NSW Department of Health, 2003). Several experimental studies have shown that teachers find these skills easy to integrate into their teaching programs, which are well delivered and re-ceived through appropriate professional development programs (McKenzie, Alcaraz, Sallis, & Faucette, 1998; Okely, Booth, Wright, Hearne, & Konza, 2003; Wright, Hearne, Konza, & Okely, in press [Still in press?]). Several studies have described the levels of FMS mastery among Australian children (Booth et al., 1997; Booth et al., 1999; van Beurden, Zask, Barnett, & Dietrich, 2002; Walkley, Holland, Treloar, & Probyn-Smith, 1993) and adolescents (Booth et al., 1999; Okely & Booth, 2004; Walkley et al., 1993), indicating substantial room for improvement in FMS proficiency, particularly among girls. In a study of 5–8-year-old children (n = 1438 ; 52% boys), Okely and Booth (2000) reported a positive association between proficiency at six FMS and enjoyment of physical activity (p = .0004). Okely, Booth, and Patterson (Okely et al., 2001a) found that among 982 adolescents (53% boys), mastery of six FMS explained a significant proportion of the variance in time that grade 8 and 10 students (ages 13 and 15 years) participated in organized physical activity (self-reported). The latter study also reported that this association differed by gender, as the association was considerably stronger among girls compared to boys. Interestingly, a recent study involving 4,363 children, from grades 2 to 10 (approximately 7–16 years of age) found both boys’ and girls’ FMS proficiency was inversely associated with their adiposity level (measured by body mass index and waist circumference; Okely et al., 2004). However, it is unknown whether this reduced proficiency in FMS among children with higher adiposity is associated with lower levels of physical activity and whether this association differs between boys and girls. The current study aimed to describe the relationship (a) among FMS proficiency, objectively measured physical activity, and weight status, and (b)among FMS proficiency, physical, activity and gender.

Method Overview Data for the current study were obtained from the baseline phase of the Switch-Play intervention. This was a group-randomized controlled trial that evaluated the impact of a FMS and behavior modification program on adiposity and enjoyment of and time spent in sedentary behaviors andphysical activity among 9–12-year-old children. The intervention methods have been reported

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elsewhere (Salmon, Ball, et al., 2005). Data collected prior to the intervention (the baseline phase) included objective measures of children’s height and weight, physical activity, and FMS proficiency. These data were used to describe the relationship among children’s FMS proficiency, physical activity, and weight status. The Deakin University Human Research Ethics Committee and Department of Education and Training, Victoria, Australia, provided ethics approval for this study. Recruitment Children attending three government primary schools participated in the study. All eligible schools in areas of low socioeconomic status (SES) based on the socioeconomic index for areas (SEIFA) scores (Australian Bureau of Statistics, 1998) in metropolitan Melbourne, Australia, were approached. Low SES areas were specifically targeted due to the increased likelihood of physical inactivity and related conditions that occur in individuals of low SES (U.S. Department of Health and Human Services, 1996). Of those agreeing to participate, the three largest schools were selected. The eligibility criteria were for the school to have a minimum enrolment of 500 students and at least three grade 5 classes. These students were specifically targeted to ensure long-term follow-up of the intervention while the children were still attending the same school. All grade 5 students ages 9–12 years (n = 397) in the selected schools were invited to participate in the study, and the children’s parents provided informed consent for their participation. Measures Fundamental Movement Skills. Six FMS, including three object-control skills (overhand throw, two-handed strike, kick) and three locomotor skills (sprint run, dodge, and vertical jump) were assessed. Where possible, test conditions were identical between schools. The test setting varied according to the facilities available. Testing at two schools was conducted in an indoor facility, while at the third school it was done outside on asphalt. Each test used the same equipment at each site (e.g., tennis balls for the overhand throw, child-size plastic baseball bat and sponge balls for the two-handed strike, and a youth-size soccer ball for the kick). The children were encouraged to throw, hit, and kick for force rather than accuracy, to run (over 25 m) and dodge (through a series of cones on the ground over 20 m) as fast as they could, and jump as high as they could. Children were put into groups of up to six and rotated through the six skill assessment stations. Video cameras were used to tape each child’s performance in each skill. Each child had five attempts at each skill. Four trained evaluators later assessed the children’s

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mastery of each skill from the videotape recording. An expert external evaluator performed a quality control check of each evaluator’s assessment, and interobserver agreement was greater than 85%. Each skill comprised between five and eight components; the methods for assessing proficiency in each skill have been described in detail previously (Department of Education Victoria, 1996). Examples of mastery criteria for two of the six skills are shown in Table 1. Children received a score of 1 if they performed a component correctly and 0 if not performed correctly on four of five trials for the object-control skills and consistently for the locomotor skills. If children displayed correct performance on all or all but one skill component, they were classified as having achieved mastery or near mastery, respectively, for that skill (Booth et al., 1999). In addition to dichotomous outcomes, the number of components performed correctly for each skill was summed to create a total score, with a higher score indicating greater proficiency in that skill. When assessing the dodge skill, inconsistent testing conditions at one school rendered the children unable to demonstrate mastery/near mastery; therefore, the dodge was eliminated from all analyses. Thus, the skills examined consisted of three object-control skills (overhand throw, two-handed strike, kick) and two locomotor skills (sprint run, vertical jump). Because the number of components varied among the skills, the total score for each was standardized to 6 so that overall FMS proficiency could be created by summing the standardized score for the individual skills. This procedure has been used before in similar studies and was performed here to ensure that proficiency in one skill (with a high number of mastery criteria) did not carry greater weight than a skill with a low mastery criteria in an overall proficiency score (Okely, Booth, & Patterson, 2001b). In addition to the overall FMS proficiency score, the values of the three object-control skills and two locomotor skills were summed separately to create an object-control proficiency score and a locomotor proficiency score. Physical Activity. Physical activity was objectively assessed using uniaxial accelerometers (Manufacturing Technology Inc [MTI], Actigraph Model, AM7164-2.2C [AQ: Incl. mfg’s city & state.], formerly Computer Science and Applications). The MTI accelerometer measures bodily movement in the vertical plane and has been validated as an objective measure of children’s physical activity (Trost et al., 1998). The children wore the accelerometer for 8 days during waking hours except during bathing and aquatic activities. They wore accelerometer on their right hip, and minute-by-minute results were downloaded using a reader interface unit connected to an IBM-compatible personal computer. The first and last days of recorded data were discarded, as they were incomplete due to accelerometer fitting

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and collection. Only children with at least 3 complete days of accelerometer data, including one weekend day were included in the analyses (Janz, Witt, & Mahoney, 1995). A complete day was defined as at least 10 hr of data and greater than 10,000 step counts, because it was unlikely participants wore the accelerometer for most of the day if the count was lower than 10,000 (Telford, Salmon, Jolley, & Crawford, 2004). Days on which total accelerometer counts exceeded 20,000 were also excluded from analysis, as this indicated a possible malfunction of the accelerometer (Telford et al., 2004). Physical activity data from accelerometers were recorded as the number of movement counts per minute. Average daily movement counts were calculated by summing total movement counts per day and dividing this value by the number of days each child wore the accelerometer. The average minutes/day spent in moderateand vigorous-intensity physical activity were calculated by applying movement count thresholds to the data using a QBASIC data reduction program. Movement count thresholds were based on Freedson’s child energy prediction equation: METs (metabolic equivalent units) = 2.757 + (0.0015·counts·min-1)-(0.08957·age[yr]) - (0.000038·counts·min-1·age[yr]), cited in previous studies (Trost et al., 2002). The intensities were defined in METs (Welk, 2002) as: moderate-intensity physical activity (MPA) = 3.0–5.9 METs, and vigorous-intensity physical activity (VPA) = ≥ 6.0 METs (Pate et al., 1995). Minutes/day spent in moderate- to vigorous-intensity

Table 1. Components of the vertical jump and the twohanded strike Components of the vertical jump

Components of the two-handed strike

1. Eyes focused forward or 1. Eyes focused on the ball upward throughout the jump throughout the strike 2. Crouch with knees bent 2. Preferred hand grips and arms behind the body above nonpreferred hand 3. Forceful upward thrust 3. Stand side-on to the of arms as legs straighten target to take off 4. Legs straighten in the air 4. Bat held behind shoulder prior to the strike 5. Contact ground with front 5. Step toward target with part of feet and bend knees foot opposite preferred to absorb force of landing hand during the strike 6. Balanced landing with 6. Marked sequential hip to no more than one step shoulder rotation during in any direction the strike 7. Ball contact made opposite front foot with arms straight 8. Follow through with bat around body

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physical activity (MVPA) was derived by summing the time spent at these intensities each day. As both the MVPA and VPA variables were positively skewed, these data were log transformed prior to analysis. All analyses were performed using the log transformed variables. Weight Status. A portable stadiometer and digital scales were used to measure height (cm) and weight (kg) without shoes. The same person took the measurements using standardized procedures. From the raw height and weight data, body mass index (BMI; kg/m2) was calculated. BMI scores were standardized into z scores to adjust for age and gender variations in growth patterns. Due to the small number of children classified as obese, individuals were grouped into two categories; nonoverweight, and overweight or obese. These groupings were performed using internationally accepted age- and sexspecific cut-points (ranging between 19.10–21.56 kg/m2 for 9–12-year-old boys, and 22.97–26.43 kg/m2 for 9–12year-old girls), defined by the International Obesity Task Force (Cole, Bellizzi, Flegal, & Dietz, 2000). Statistical Analysis Data were analysed using SPSS-W version 12.0.1. Descriptive statistics and frequencies for the demographic, physical characteristic, physical activity, and FMS variables were calculated. Differences between boys and girls for these variables were examined using chi-square (for categorical variables; weight category) or independent t tests (for continuous variables: age, BMI, physical activity). Differences between nonoverweight and overweight/obese children for mastery/near

mastery of individual movement skills were also examined using Chi-square tests. Pearson product-moment correlation tests examined correlations among FMS proficiency scores (total, object-control, and locomotor scores) and physical activity variables (MPA, VPA, and MVPA), FMS proficiency and BMI z scores, and physical activity variables and BMI z scores. Analyses examining the interactions (using generalized linear modelling) among FMS proficiency scores and BMI z scores, according to physical activity, and interactions among FMS proficiency scores and gender, according to physical activity, were performed in Stata version 8.0. The recruitment unit for this study was the child’s class at school, so analyses were adjusted for clustering by class to account for the possibility that children in one class may have better motor skill proficiency or higher physical activity levels than those in another class (Goldstein, 2003). A significance level of .05 was applied to all analyses.

Results Only children with active parental consent (n = 311) were eligible to participate in the assessment component of the study (74% response rate). Data from those who had completed all assessment components were used; therefore, the final sample consisted of 248 children. The demographic characteristics of the sample, the mean time spent participating in MPA and VPA, the mean BMI z scores, and BMI categories of boys and girls are presented in Table 2. The sample (50% boys) was

Table 2. Descriptive data for the physical characteristics and physical activity (PA) of boys and girls Variable Boys (n = 123) Girls (n = 125) M SD M SD .44 10.0 0.28 Age (years) 10.1 Min/day moderate PA 132.6 34.97 113.6 34.26 Min/day vigorous PA 24.9 23.13 14.5 9.20 Min/day MVPA 157.5 49.18 128.1 40.12 Height (cm) 142.0 6.86 142.9 7.01 Range 125.0–158.6 127.5–158.4 Weight (kg) 41.4 9.82 40.9 9.81 Range 24.0–68.6 23.2–72.2 BMI (kg/m2) 20.4 3.62 19.9 3.65 Range 14.38–31.15 13.46–29.86 % overweight/ obese (BMI kg/m2)a 39.3 35.2

t

p

1.93 4.31 4.67 5.16 -.99

.06 .0001 .0001 .0001 .32

.41

.68

1.03

.30

χ2

p

.45

.51

Note. M = mean; SD = standard deviation; PA = physical activity; MVPA = moderate to vigorous physical activity; BMI = body mass index. a Differences between boys and girls examined using Chi-square tests; differences in all other variables examined using independent t tests.

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approximately 10 years of age, with 39% of boys and 33% of girls classified as overweight or obese (not a significant gender difference). As shown in Table 2, boys participated in significantly more MPA (approximately 133 vs. 114 min) and VPA (approximately 25 vs. 15 min) per day compared to girls. Table 3 shows boys’ and girls’ mastery/near mastery of the five movement skills. Mastery/near mastery of the three object-control skills was lower among girls, with a significantly greater proportion of boys achieving mastery/near mastery in each skill (kick χ2 = 31.14, p = .0001; overhand throw χ2 = 43.17, p = .0001; two-handed strike χ2 = 62.20, p = .0001). There were no differences between boys and girls in either of the locomotor skills. Boys displayed higher total FMS and mean object-control proficiency scores than girls, but there was no difference in the mean total locomotor skill score. Mastery/near mastery of the individual skills was also examined according to weight status (see Table 4). Compared with overweight or obese children, a higher proportion of children classified as nonoverweight achieved mastery/near mastery in the run (χ2 = 10.90, p = .001). There were no differences in the proportion of children achieving mastery/near mastery in the other skills according to weight status or in the total FMS, object-control, or locomotor proficiency scores. Correlations Table 5 shows the correlations among FMS proficiency, physical activity, and weight by gender. Among

boys, MPA, VPA, and MVPA showed weak but significant positive correlations with the total FMS proficiency score (range: r = .21–.25). MPA and MVPA showed weak but significant positive correlations with the object-control proficiency score (r = .24 for both), but only VPA was significantly (although weakly) correlated with the locomotor proficiency score (r = .22). Boys’ BMI z scores were not significantly correlated with any FMS or physical activity variables. Among girls, VPA was weakly but significantly correlated with both the total FMS proficiency score (r = .21) and the locomotor proficiency score (r = .29), but there were no other correlations among FMS and physical activity variables. There were no significant correlations among any of the FMS or physical activity variables and BMI z scores among girls. Interactions After adjusting for clustering, no significant interaction was apparent among the FMS proficiency scores, physical activity variables, and weight, or the FMS proficiency scores, physical activity variables and gender.

Discussion This study aimed to examine children’s proficiency in FMS and time spent in physical activity to determine whether the relationship between these variables could be explained by interactions with weight status.

Table 3. Mastery/near mastery of individual movement skillsa and scores indicating fundamental movement skills proficiencyb of boys and girls Achieving mastery/ near mastery Boys Girls χ2 Object-control skills (%) Kick 76.4 44.0 27.17 Overhand throw 34.1 5.6 31.87 Two-handed strike 62.6 18.4 50.34 Locomotor skills (%) Run 20.3 16.8 .51 Vertical jump 20.3 24.0 .49 FMS proficiency scores Total FMS proficiency score (observed range 0–26) Object-control proficiency score (observed range 0–15) Locomotor proficiency score (observed range 0–12)

t

p .0001 .0001 .0001 .51 .54

M

SD

M

SD

p

18.8

3.87

14.4

4.32

8.41

.0001

12.2

2.74

8.0

2.86

11.79

.0001

6.6

2.37

6.4

2.32

.62

.53

Note. FMS = fundamental movement skills; M = mean; SD = standard deviation. a Differences between boys and girls in FMS mastery/near mastery of individual skills examined using chi-square tests. b Differences between boys and girls in FMS proficiency scores examined using independent t tests.

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A secondary aim was to examine whether FMS mastery varied between boys and girls. Consistent with previous studies (Okely & Booth, 2004; van Beurden et al., 2002), there were substantial differences between the sexes, with more boys achieving mastery/near mastery in object-control skills compared with girls. In this study, girls’ mastery/near mastery of object-control skills was low (ranging between 5–42% of girls achieving mastery/near mastery for the object-control skills), which is consistent with mastery levels shown in other studies (Booth et al., 1999; Okely & Booth, 2004; van Beurden et al., 2002; Walkley et al., 1993). Interestingly, fewer boys in the current study displayed mastery/near mastery of both locomotor skills than in the study reported by Booth and colleagues (1999), although a higher proportion of boys in the current study achieved mastery/near mastery in the object-control skills. These gender differences may be explained by the amount of reinforcement children of this age receive to participate in sports and activities using these skills. That is, the differences are likely to be environmental rather than biological, and there is a good chance these gender differences could be reduced if girls have the same opportunities for instruction, practice, feedback, and encouragement as boys (Thomas, 2000; Thomas & French, 1985). Due to the cross-sectional design of this study, a causeand-effect relationship between FMS and physical activity

Table 4. Mastery/near mastery of individual movement skillsa for nonoverweight and overweight/obese children Variable Nonoverweight Achieving mastery/ near mastery Object-control skills (%) Kick Overhand throw Two-handed strike Locomotor skills (%) Run Vertical jump

60.0 18.1 43.9 23.9* 23.2

Overweight/ obese Table 5. Pearson coefficients for correlations among fundamental movement skills, physical activity, and body mass index z scores 60.9 22.8 34.8

SD

M

SD

4.62

16.4

4.72

3.49

10.0

3.55

2.45

6.4

2.17

Variable Proficiency scores Total FMS Object-control Locomotor Boys Min/day MPA .21* .24** .08 Min/day VPA .25** .16 .22* Min/day MVPA .24** .24** .11 -.10 -.08 -.08 BMI z scores Girls Mins/day MPA .10 .08 .09 Mins/day VPA .21* .09 .29** Mins/day MVPA .13 .08 .14 BMI z scores .02 .03 -.01

Note. FMS = fundamental movement skills; M = mean; SD = standard deviation a Differences between nonoverweight and overweight/obese children in mastery/near mastery of individual movement skills examined using chi-square tests.

Note. FMS = fundamental movement skills; MPA = moderate physical activity; VPA = vigorous physical activity; BMI = body mass index. *p ≤ .05. **p ≤ .01.

FMS proficiency scores

M

Total FMS proficiency score (observed range 0–26) 16.7 Object-control proficiency score (observed range 0–15) 10.2 Locomotor proficiency score (observed range 0–12) 6.6

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cannot be determined. It is not clear whether a higher proficiency in movement skills increases a child’s physical activity or whether greater participation in physical activity improves movement skill proficiency. One study examined this relationship over a 6-year period and found that childresn’s movement skill performances at the age of 4 years did not predict physical activity participation at age 12 (McKenzie et al., 2002). The authors of that study posited various reasons for this finding but suggested it was because children’s movement skills were assessed prior to school enrolment, where they received formal FMS education. Further longitudinal studies are required to determine the direction of this relationship. Further research is also required to examine associations among FMS proficiency, physical activity, and weight. Previous research has suggested that BMI is inversely related to locomotor FMS proficiency and physical activity (Okely et al., 2004; Trost, Kerr, Ward, & Pate, 2001); however, when the interaction among FMS mastery/near mastery and weight status was examined in the current study, these variables did not interact with physical activity. Additional research is also required to examine different types of physical activity and whether there is a relationship between FMS proficiency and participation in certain activities. It is plausible that proficiency in throwing, for example, may be more important if a child participates in the type of activity requiring that skill. As objective physical activity monitoring does not assess participation in specific types of physical activity, it may be that overweight or obese children in the current study participated in activities that did not involve the five movement skills examined. Future stud-

9.8 20.7

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ies should examine children’s previous physical activity experiences, a broader range of movement skills, and types of activities in which children participate to better understand and characterize this relationship. The use of objective physical activity monitoring was a unique component of this study; only one other study (among young children) has examined the association between FMS and physical activity using this method (Fisher et al., 2005). A further strength of the current study was the inclusion of five FMS commonly used in children’s games, sports, and physical activities. As discussed previously, the cross-sectional design of this study meant the directions of the associations could not be determined. A larger sample size would also have enhanced the study, and it is possible the small numbers may have accounted for the lack of significant findings in the interaction analyses. Additionally, it is possible that not enough days of objectively measured physical activity were included in the analyses to provide a true representation of children’s usual physical activity patterns. Differences in physical activity according to FMS proficiency, gender, or weight status may have been detected if more days of monitoring had been included. In conclusion, findings from the current study suggest that more boys displayed FMS mastery/near mastery than girls and that children in this sample with higher FMS proficiency tended to be more active; however, this relationship did not interact with the children’s weight. This suggests that regardless of weight, improving movement skill proficiency among all children is a potential avenue for promoting increased physical activity.

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Department of Education Victoria. (1996). Fundamental motor skills: A manual for classroom teachers. Melbourne, Australia: Department of Education. Fisher, A., Reilly, J. J., Kelly, L. A., Montgomery, C., Williamson, A., Paton, J. Y., et al. (2005). Fundamental movement skills and habitual physical activity in young children. Medicine & Science in Sports & Exercise, 37, 684–688. Gallahue, D., & Ozmun, J. (2002). Understanding motor development: Infants, children, adolescents, adults (5th ed.). New York: McGraw-Hill. Goldstein, H. (2003). Multilevel statistical models (3rd ed.). London: Edward Arnold. Janz, K. F., Witt, J., & Mahoney, L. T. (1995). The stability of children’s physical activity as measured by accelerometry and self-report. Medicine & Science in Sports & Exercise, 27, 1326–1332. McKenzie, T., Alcaraz, J., Sallis, J., & Faucette, N. (1998). Effects of a physical education program on children’s manipulative skills. Journal of Teaching in Physical Education, 17, 327–341. McKenzie, T. L., Sallis, J. F., Broyles, S. L., Zive, M. M., Nader, P. R., Berry, C. C., et al. (2002). Childhood movement skills: Predictors of physical activity in Anglo American and Mexican American adolescents? Research Quarterly for Exercise and Sport, 73, 238–244. New South Wales Department of Health. (2003). NSW child obesity summit: Government response 2003. Sydney, Australia: New South Wales Department of Health. Okely, A. D., & Booth, M. (2000). Relationship of enjoyment of physical activity and preferred activities to fundamental movement skill proficiency in young children. International Journal of Behavioral Medicine, 7(Suppl. 1), 151. Okely, A. D., & Booth, M. L. (2004). Mastery of fundamental movement skills among children in New South Wales: prevalence and sociodemographic distribution. Journal of Science and Medicine in Sport, 7, 358–372. Okely, A. D., Booth, M. L., & Chey, T. (2004). Relationships between body composition and fundamental movement skills among children and adolescents. Research Quarterly for Exercise and Sport, 75(3), 238–247. Okely, A., Booth, M., & Patterson, J. (2001a). Relationship of cardiorespiratory endurance to fundamental movement skill proficiency among adolescents. Pediatric Exercise Science, 13, 380–391. Okely, A. D., Booth, M. L., & Patterson, J. W. (2001b). Relationship of physical activity to fundamental movement skills among adolescents. Medicine & Science in Sports & Exercise, 33, 1899–1904. Okely, A., Booth, M., Wright, J., Hearne, D., & Konza, D. (2003). Evaluation of the Gold Medal Fitness Program. Sydney, Australia: New South Wales Dept. of Education & Training. Pate, R. R., Pratt, M., Blair, S. N., Haskell, W. L., Macera, C. A., Bouchard, C., et al. (1995). Physical activity and public health. A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. Journal of the American Medical Association, 273, 402–407. Payne, V. G., & Isaacs, L. D. (1995). Human motor development: A lifespan approach (3rd ed.). Mountain View, CA: Mayfield.

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Author’s Notes This study was funded by the Victorian Health Promotion Foundation. Michael Booth is funded by the National Health and Medical Research Council, David Crawford is funded by the National Heart Foundation of Australia and the National Health and Medical Research Council, and Jo Salmon is funded by the Victorian Health Promotion Foundation. This study is part of the baseline measures taken as part of an intervention study; however, none of these findings have been reported elsewhere. Please address all correspondence concerning this article to Clare Hume, Center for Physical Activity and Nutrition Research, Deakin University, Victoria Australia, 3125. E-mail: [email protected]

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