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Relationships between Body Composition andFundamental Movement Skills among Children andAdolescentsAnthony D. Okely a , Michael L. Booth b & Tien Chey ca University of Wollongong, USAb School of Public Health, University of Sydney, USAc South Western Sydney Area Health Service, USAPublished online: 25 Feb 2013.

To cite this article: Anthony D. Okely , Michael L. Booth & Tien Chey (2004) Relationships between Body Composition andFundamental Movement Skills among Children and Adolescents, Research Quarterly for Exercise and Sport, 75:3, 238-247,DOI: 10.1080/02701367.2004.10609157

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Growth and Motor Development

Research Quarterly for Exercise and Sport©2004 by the American Alliance for Health,Physical Education, Recreation and DanceVol. 75, No.3, pp.238-247

Relationships Between Body Compositionand Fundamental Movement Skills AmongChildren and Adolescents

Anthony D. Okely, Michael L. Booth, and Tien Chey

Thepurpose of thisstudy was toexamineassociations offundamental movement skills(FMS)with measures ofbody compositionamong children and adolescents. Secondary analysesof cross-sectional data collectedfrom 4,363 children and adolescents inGrades 4, 6, 8, and 10 as part of the 1997New South Wales Schools Fitness and PhysicalActivity Survey were conducted. SixFMS (run, verticaljump, throw, catch, kick, and strike) were assessed byobservation. Height and weight(usedto calculate bodymass index; BMl) and waist circumference were directly measured. Results indicatedthat thechildren's and adolescents' abilitytoperform FMS wassignificantlyrelated toBMl and waist circumference. Specifically, BMI and waist circumference weresignificant predictorsfor FMS in six of theeightdemographic groups. Adjusted oddsratiosrevealed that overweight boys and girlsin allgrades were less likely topossess high levels ofFMS and more likely topossess lowleoels ofFMS than those whoweren't over­weight. lWum FMS were partitionedinto locomotor and object-eontrol skills, nonoverweight boys and girlsin eachgradewere twotothree times more likely topossess more advancedlocomotor skillsthan overweight boys and girls. However, for object-eontrol skills, theonlydemographic groupsin whichnonoverweight studentspossessed a greater numberof advancedskillsthan overweight studentswere boys in Grades 6 and 10. There appeartobesignificantand importantassociations between performance of locomotor skillsand weightstatus among children and adolescents. This would suggest that intervention strategies topreventunhealthy weightgain among children and youth might usefullyinclude increasingproficiency of locomotor skillsas a key component.

Key words: adiposity, body mass index, motor skills, waistcircumference

Body composition is considered a key component ofhealth-related fitness (Corbin & Lindsey, 1997)

The health consequences ofexcess adiposity have beenwell documented in children and youth and include agreater risk of psychosocial distress, orthopedic compli­cations, gastrointestinal disorders, features of the insu­lin resistance syndrome, hypertension, and abnormal

Submitted: September 30, 2002Accepted: December 7,2003

Anthony D. Dkely is with theFaculty of Education andMetabolicResearch Center at the University of Wollongong. Michael L.Booth is with the School of Public Health at the University ofSydney. lien Chey is with the Epidemiology Unitat the SouthWestern Sydney Area Health Service.

238

lipid profiles (Dietz, 1998). Because obese children andadolescents are more likely than their leaner peers tobecome obese adults and because adolescent obesity isrelated to adverse health outcomes during adulthoodindependent ofadult adiposity, obese children and ado­lescents have an increased risk ofmortality and morbidityas adults (Must, 1996). The prevalence of being over­weight or obese is increasing rapidly and is now one ofthe most significant public health challenges internation­ally (Ebbeling, Pawlak, & Ludwig, 2002; Styne, 2001).

It is important to understand influences on excessadi­posityto address obesityamong children. There are both bio­logicaland behavioral determinants to being overweightand obese, and, at present, the behavioral determinantsoffer the most fruitful possibilities for successful interven­tion (Baranowski et al., 2000). Fundamental movementskills (FMS) are critical to participation in most physicalactivities,because they represent the requisite behavioralcompetencies for participation. Previous studies among

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children and youth have shown a relationship betweenFMSproficiency and cardiorespiratoryendurance (Okely,Booth, & Patterson, 2001a) and participation in organizedphysical activity (Okely, Booth, & Patterson, 2001b). Itcould be argued, then, that the effects ofFMS proficiencyon being overweight or obese is mediated through car­diorespiratory endurance and physical activity participa­tion and that little can be gained by examining therelationship between FMS proficiency and adiposity.How­ever, it is not uncommon for determinants to have bothdirect and mediated relationships with health outcomes,and a more comprehensive understanding ofthe factorsinfluencing overweight can only improve our capacity tointervene effectively. In addition, because physical activ­ityisdifficult to measure in population studies ofchildrenand adolescents (Welk, Corbin, & Dale, 2000) and hassuch wide error, it may not be possible to detect ifassocia­tions between FMS proficiency and being overweight!obese are mediated by physical activity. Because FMSandbeing overweight/obese are easier to measure in childand adolescent populations, a plausible first step is to ex­plore the hypothesis that proficiency ofFMS is related tobeing overweight/obese among children and adolescents.

Several studies have examined the relationship ofbody composition to health-related fitness and motor abil­ity (e.g., speed, power, explosive strength) and reportedstrongcorrelations between body composition and health­related fitness components, such as cardiorespiratory fit­ness (Pissanos, Moore, & Reeve, 1983; Reeves, Broeder,Kennedy-Honeycutt, East, & Matney, 1999) and muscularendurance (Hensley, East, & Stillwell,1982), and weak tomodest correlations between body composition and mo­tor abilities (Hensley et aI., 1982; Malina et aI., 1995;Pissanos et al., 1983). However, it is known that geneticfactors (Maeset al., 1996) determine health-related fitnessand motor abilities during the prepubertal years and arenot easily modified by practice or training (Burton &Miller, 1998), thus, limiting the implications of these find­ings for practice. Fundamental movement skills (whichare directly observable, qualitative expressions of move­ment performance, unlike motor abilities, which are gen­eral traits or capacities not easilyobserved; Burton & Miller,1998) are different in that they are amenable to change,especiallyduring the prepubertal years, suggested as a sen­sitive learning period for mastering FMS (Gallahue,1996). If there is a direct association between FMS profi­ciency and adiposity among young people, programs in­tended to prevent or treat being overweight might usefullyinclude FMS training. Improved proficiency ofFMS alsohas the potential to improve perceived competence andself-esteem (Ulrich, 1987), twovariables known to be loweramong overweight and obese children and youth (Phillips& Hill, 1998; Southall, Okely, & Steele, 2004). Subse­quently, improved FMS proficiency has the potential toenhance motivation to be physically active through im-

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Oka/y, Booth, and Chay

proved self-esteem and enjoyment of physical activity, inaddition to improved skills.

As plausible as this may seem, studies examiningthe association between FMS proficiency and body com­position among children and adolescents are rare.Ellery (1991) found no relationship between skinfoldthickness and gross motor skill performance among 220preschool children. This differs from the results ofotherrecent studies. Malina et al. (1995) examined the asso­ciation between the sum offive skinfolds and five motorperformance items in over 9,000 girls ages &-18 yearsand found that as adiposity increased, balance, speed,power, and strength decreased. McKenzie et al. (2002)investigated the relationship of three movement skills(balance, catch, andjump) and the mean oftwoskin-foldsamong 400 children ages 4-6 years. Skinfolds were in­versely related to balance in boys and girls and the jumpand index ofthe three skillsin boys.These latter twostud­ies assessed only a small number ofFMS (between 1 and3) and used product-oriented assessments in contrastto recent trends to assess movement skills using process­oriented measures (Burton & Miller, 1998).

Examining the relationships between differentmeasures of body composition and multiple process­oriented measures ofFMS proficiency may now extendthe previous research. In addition, because FMS arepredominantly categorized into locomotor and object­control skills (Burton & Miller, 1998) it would be helpfulto know if this relationship was different between thesecategories. The purpose of this study was to describe thenature ofthe association between FMSproficiency and twofrequently used measures ofbody composition (BMIandwaist circumference). Specifically,we hypothesized that,among children and adolescents: (a) overall FMS profi­ciency would be inversely associated with body compo­sition, and (b) this inverse association would exist forboth locomotor and object-eontrol skills.

Method

Data were collected as part of the New South WalesSchools Fitness and Physical Activity Survey, 1997 (N=5,518; Booth et al., 1997). The methods ofthe surveyhavebeen reported in detail elsewhere (Booth, Macaskill,Phongsavan, McLellan, & Okely, 1998) and are onlybriefly described here.

$ample Selection

Proportional stratified random sampling ofall pri­mary and high schools in New South Wales (NSW) Aus­tralia was conducted. Special schools, schools withenrollments less than 180 students, and schools in re-

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Table 1. Components of the sprint run andoverhand throw

Note. From Fundamental Motor Skills: A Manual for ClassroomTeachers (Department of Education Victoria, 1996, pp. 20-241.

provide information about developmental trends in FMSproficiency (including the order in which youth acquiredevelopmental levels on the way to proficiency), for thepurpose of this study FMS proficiency was not measuredfrom a developmental perspective; rather, it wasmeasuredin comparison to an "expert" performer (i.e.,one who hasmastered all components of that skill). For each skill, ascore was calculated for each student based on the totalcomponents performed correctly. Process-oriented assess­ments ofFMS were used rather than product-oriented as­sessments, because they more accurately identify specifictopographical aspects of the movement (Ulrich, 2000).The test battery included skillsclosely related to activitiesand sports in which students were most likely to partici­pate. Field staff assessed skill components byscoring eachas present or absent on four offive trials (Department ofEducation Victoria, 1996). That is, if a student demon­strated the skill component on four offive trials he or shewasrecorded as possessing that skillcomponent Field staffwere required to reach a 90% interobserver agreementcriterion for all skills on pre-coded videotapes. The reli­abilityand validityof the skillsand their components werepreviouslyestablished (Department of Education Victoria,1996). Briefly,content validity was assessed by a panel of52 FMSexperts who reviewed and ranked the importanceof the skills and identified and reviewed each skill com­ponent. In addition, the instructor's manual reported amean test-retest reliability coefficient of 0.75 for the sixskills. An example of the components for two skills, thesprint run and overhand throw, are presented in Table 1.

Sprint run 1.2.

Description of the component

Eyes focused forward throughout the runKnees bend at right angles during recoveryphase

3. Arms bend at elbows and move in opposition tolegsContact ground with front part of footBody leans slightlyforwardEyes are focused onthe target throughout thethrow

2. Stand side-on to the target3. Throwing arm nearly straightened behind the

body4. Step toward the target with foot opposite

throwing arm during the throw5. Marked sequential hip-to-shoulder rotation

during the throw6. Throwing armfollows through down and across

the body

Skill

4.5.

Overhand 1.throw

Sixteen field staff (four teams offour staff, one teamper school), consisting of 14 teachers and two researchofficers, collected the data. All were trained to Levell ofthe International Society for the Advancement ofKinanthropometry accreditation and completed 3 days oftraining in assessing FMS proficiency during the 2 weeksof training and orientation prior to data collection. Datawere concurrently collected in schools from each educa­tion sector and geographic location, over a &week periodduring School Term 1 (summer) 1997. The University ofSydney Human Research Ethics Committee approved thestudy. Written consent from parents and caregivers wasrequired for students to participate in the study.

Body Composition Assessment. Body composition mea­surements included height, weight (used to calculateBMI), and waist circumference. These were collectedprior to the other tests to avoid fluid loss due to exertion.Height was assessed using portable stadiometers and thestretch stature method. Measurements were taken to thenearest 0.1 ern, Tanita 1597 (Mentone Educational Cen­ter, Victoria, Australia) bathroom scales were used to as­sess weight to the nearest 0.1 kg. Students wore lightclothing and removed their shoes prior to measurement.Nonextensible steel tapes were used to assess waist cir­cumference, which was measured at the narrowest pointbetween the lower costal border and the iliac crest.

FMSMeasurement. Six FMSwere assessed-run, verti­cal jump, catch, overhand throw, forehand strike, andkick-using process-oriented checklists comprising 5-7components for each skill. Methods for assessing theseskills are described in detail elsewhere (Department ofEducation Victoria, 1996) and only briefly mentionedhere. Each skill was composed of observable behavioralcomponents that together constituted a proficient perfor­mance. Although a main purpose of this measure was to

Data Collection

mote rural regions were excluded from the samplingframe. Despite these exclusions, the target populationcomprised 86% of the primary school population and97% of the high school population.

Forty-five primary and 44 high schools were selected,stratified by education sector (government, Catholic,and independent schools). The number of schools ineach stratum was proportional to the number of stu­dents enrolled in that education sector, and the likeli­hood of a school being selected in each stratum wasproportional to the size of the student enrollment.Within each selected school, one class in each ofGrades2,4, 6,8, and 10 was randomly chosen from mixed-abil­ity class lists. Grade 2 children were included for thepurpose of measuring body composition, while FMSproficiency was not assessed in this grade. Hence, theirdata are not used in the current analyses.

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Results of FMS assessments are conventionally re­ported as the proportion ofstudents who have masteredall components of the skill (Booth, Okely et aI., 1999;Walkley, Holland, Treloar, & Probyn-Smith, 1993). A limi­tation of this reporting method is that it is difficult tojudge what proportion of the students might be close toachieving mastery. As a result, we have created anotherreporting format (near mastery) in which the proportionof students who have mastered all but one ofthe compo­nents ofeach skillis reported. To compare nonoverweightand overweight students, those who displayed masteryor near mastery were combined into a single group andidentified as possessing "advanced" skills.

Sociodemographic Measures. Students were asked forinformation on their age (date of birth) , grade, sex, cul­tural background, suburb, and postcode of residence(equivalent to the U.S. zip code). Students were groupedinto quintiles ofsocioeconomic status (SES) based on theAustralian Bureau ofStatistics Index of Relative Socio­economic Disadvantage (Australian Bureau ofStatistics,1993) which gives a SES score for each postcode. Rural­itywas a dichotomous (urban/rural) variable based onthe school location. To determine cultural background,students were asked what language was spoken most athome and, from this, were grouped into English-, Euro­pean- (languages other than English), Middle Eastern,or Asian-speaking backgrounds.

Data Handling andAnalysis

Each FMSwasstandardized to a score of5, and scoresfor the six skills were added to create an overall indexofFMS proficiency (range: 0-30). Within gender andschool grade, students were ranked into quintiles by theFMS index scores, such that the number ofstudents ineach quintile was approximately equal. An ordinal scalevariable for FMS quintiles was constructed (1-5, with 1being the lowest). FMS was analyzed both as an ordinaland continuous scale variable.

Students were classified as overweight or obese(henceforward referred to as overweight) based on exactcalendar age-and gender-specific international cut-pointsfor BMI (Cole, Bellizzi,Flegal, & Dietz, 2000). FMS werealso grouped into locomotor (run and verticaljump) andobject-eontrol (catch, overarm throw, kick, and forehandstrike) skills. The number of advanced skills possessedwas classified as 0, 1,2 for locomotor skillsand 0, 1,2, orgreater than 2 for boys and 0, 1,or greater than 1 for girlsfor object-eontrol skills.Different object-eontrol classifica­tions for boys and girls were used, because few girls hadthree or more advanced skills and the groupings wouldnot have had adequate numbers for some of the grades.Analyses were carried out separately for boys and girls,stratified by school grade. Results were presented as per­centage distribution of the prevalence ofFMS measures

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Okely, Booth, and Chey

as quintiles and as number ofadvanced skillsby body com­position grouping. The significance ofany differences inpercentage prevalence was assessed by chi-square test ofassociation. Any linear trends between groups were as­

sessed byMantel-Haenszel chi-square test with one degreeoffreedom.

Age, SES, cultural background and rurality areknown to be associated with body composition amongchildren and adolescents (Booth et al., 1997). Two mod­elling approaches were used to investigate the relation­ships between FMS proficiency and body composition,adjusting for these covariates and design effects (schoolas a cluster). First, cumulative logistic regression mod­els were modelled, in which the probabilities of havinglower order values ofFMS proficiency in the overweightgroup, separately for boys and girls in each school grade.Second, multiple linear regression was used to modelthe standardized proficiency of FMS index score as afunction of body composition measure (BMI and waistcircumference) , adjusting for covariates and design ef­fects. Body composition variables were tested for normal­ity beforehand, and separate analyses were exploredusing log-transformed values for each variable. This didnot change the results, so, for ease ofinterpretation, log­transformed values are not presented. Analyses wereconducted using the statistical package SASV8.2 (SASInstitute Inc., Cary, NC, 1999-2001). All results wereadjusted for clustering design effects using the PROCGENMOD (Generalized Estimating Equation ap­proach) and PROC SURVEYREGprocedures for ordi­nal and continuous outcome variables.

Results

The range ofstandardized scores assigned to eachFMS proficiency quintile for boys and girls in each gradeare shown in Table 2. In each grade, the minimum andmaximum scores in every quintile were higher for boysthan girls except in Grade 4, where the maximum scorewas higher for girls than for boys in Quintile 5.

Table 3 shows the distribution (%) of students byFMSquintiles for nonoverweight and overweight groupsof boys and girls in Grades 4,6,8, and 10. The statisticsin Table 3 clearly show an inverse linear association be­tween FMS quintile among the overweight group andthat these students were approximately twice as likelyas nonoverweight students to be in the lowest FMSquintile. These strong relationships were consistentacross grades and between sexes. An illustration of thisrelationship for Grade 4 students appears in Figure 1.

Table 4 presents the distribution (%) of studentsby number of advanced locomotor skills possessed bynonoverweight and overweight groups for each grade

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and gender. Adjusted odds ratios from the cumulativelogistic regression models revealed that, in each grade,nonoverweight boys and girlswere two to four times morelikely to be advanced in both locomotor skills than over­weight boys and girls. An illustration of this relationshipfor Grade 6 students appears in Figure 2. The distribu­tion (%) ofstudents by number ofadvanced object-con­trol skills for nonoverweight and overweight groups ispresented in Table 5. Adjusted odds ratios indicated no

differences in number of advanced skills betweennonoverweight and overweightgirls in any grade. Amongboys, the significant chi-square statistics indicated anassociation between overweight and object-control skills,but the fact that the chi-square test for trend and the oddsratio were significant only for boys in Grades 6 and 10suggests the association is weak and inconsistent.

Multiple linear regression models that controlledfor exact age, SES, cultural background, and rurality

Table 2.The rangeof standardized scores assigned to each FMS quintilefor boys and girls in Grades 4,6,8,and10

Quintiles ofstandardizedFMS score

Grade 4Boys Girls

Grade 6Boys Girls

School yearGrade 8

Boys GirlsGrade 10

Boys Girls

1 (low)2345 (high)

5.42-14.7014.71-17.7917.83-20.4620.50-22.7722.81-28.58

3.00-12.0812.14-14.1514.19-16.2916.31-18.6518.69-29.17

3.00-17.53 3.00-13.70 4.00-18.62 2.00-15.3417.54-20.36 13.73-16.12 18.66-21.79 15.40-17.4120.38-22.62 16.14-18.17 21.81-23.82 17.42-19.8922.64-24.89 18.23-20.79 23.88-25.86 19.90-22.6224.90-30.00 20.83-27.74 25.90-30.00 22.64-28.46

7.73-19.9820.00-22.8922.90-24.9125.00-27.0027.02-30.00

0.83-16.1216.14-18.2918.35-20.7720.78-23.4823.52-30.00

Note. FMS = fundamental movement skills.

Table 3. Thedistribution (%)of students by FMS quintiles for nonoverweight andoverweight/obese groups

Quintiles of School yearstandardized Grade 4 Grade 6 Grade 8 Grade 10FMS score n Nonow% Owob% n Nonow% Owob% n Nonow% Owob% n Nonow% Owob%

Boys (n= 466) (n= 125) (n= 525) (n = 132) (n= 426) (n = 113) (n=413) (n= 96)1 (low) 118 16.6 32.8 131 16.4 33.8 106 17.7 27.2 101 17.5 28.92 119 19.6 22.4 128 18.3 24.1 107 17.0 30.7 103 18.5 26.83 114 19.1 20.0 134 21.9 14.3 107 21.9 12.3 104 21.1 16.54 120 22.8 11.2 132 21.1 15.8 109 20.3 20.2 100 20.1 16.55 (high) 119 21.9 13.6 133 22.3 12.0 109 23.1 9.7 106 22.8 11.3Test statistics: X2

14,· 23.32 (p < .001) 28.12 (p < .001) 24.87 (p < .001) 14.26 (p < .01)X2

111b 19.76 (p < .0011 23.46 (p < .001) 16.02 (p <.001) 12.99 (p <.001)

OR' 2.32 (1.66-3.23)** 2.29 (1.49-3.51 )** 2.08 (1.42-3.06)- 2.12 (1.34-3.36)**

Girls (n= 408) (n = 116) (n=413) (n = 124) (n = 409) (n = 92) (n = 332) (n = 79)1 (low) 103 16.0 32.8 107 18.4 25.0 98 16. 1 34.8 78 16.9 27.22 105 20.2 19.8 108 18.4 25.8 102 20.4 19.6 83 19.0 24.73 104 18.7 24.1 107 19.4 21.8 101 20.4 18.5 82 19.9 19.84 103 20.7 16.4 106 20.3 17.7 100 20.4 17.4 84 19.9 22.25 (high) 107 24.4 6.9 109 23.5 9.7 102 22.6 9.8 86 24.4 6.2Test statistics: X2

14,· 28.47 (p < .001) 14.25 (p < .01) 20.17 (p < .001) 15.27 (p < .01)

X2111

b 23.52 (p < .001) 12.24 (p < .001) 16.07 (p < .001) 11.91 (p < .001)OR' 2.48 (1.67-3.67)** 1.96 (1.42-2.71)** 2.03 (1.34-3.06)** 2.30 (1.42-3.71 )**

Note. FMS = fundamental movement skills; Nonow=nonoverweight; Owob =overweight/obese.·Chi-square test for independent factors.bMantel-Haenszel chi-square test for linear trend.'Adjusted odds ratios (estimate, 95% confidence intervals) for Owob derived from the cumulative logistic model, nonoverweight isthe referent group. Covariates adjusted were exact age (continuous), socioeconomic status(five categories), cultural background(four categories), and rurality (two categories).**p < .01.

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measured the strength of association between the stan­dardized sum ofall six FMS and the two measures ofbody

composition (BMI and waist circumference) are de­scribed in Table 6. These models confirmed that: (a)

o+--....--.---r-........--.r--........--.r--........-r--~--l

60

~00)

50GIqJ()

J::.

~ 40Q,I

.5 1VI I

\~ 30 • \Q,I

\

"~ ..Vi- 200~0'f0 10Q. • non-overweighte

CL.- - • - - overweight

0

0 2 0 2

Number of advanced locomotor skills

III

234 5

II\

non-overweight

I·\ .•

•\

•- - • - - overweight

234 5

35

•I

~ 30 \

~ I

'3 Io:::r \

J::. 25~Q,I

.5 20VI~Q,I

"~ 15Vi'0~ 100'f0Q.e 5

CL.

FMS Quintile

Figure 1. Proportion of overweight and nonoverweight boys andgirls in Grade 4 in each fundamental movement skill quintile(forfundamental movement skills quintile, 1 =low and 5 =high).

Figure 2. Proportion of overweight and nonoverweight boys andgirls in Grade 6 possessing advanced skills in 0, 1,or 2locomotor skills (thetwo locomotor skills assessed were thesprint run and vertical jump).

Table 4. Thedistribution (%)of students by number of advanced locomotor skills for nonoverweight andoverweight/obese groups

Number of School yearadvanced Grade 4 Grade 6 Grade 8 Grade 10locomotor skills n Nonow% Owob% n Nonow% Owob % n Nonow% Owob% n Nonow% Owob%

Boys (n=466) (n=125) (n=524) In =132) (n= 426) (n=113) (n=413) (n= 96)0 153 20.6 45.6 106 13.2 28.0 n 12.0 23.0 59 9.2 21.91 227 39.9 32.8 247 34.9 48.5 209 37.8 42.5 176 33.4 39.62 211 39.5 21.6 303 51.9 23.5 253 50.2 34.5 274 57.4 38.5Test statistics: X21218 33.92 (p < .001) 38.01 (p < .001) 12.82(p<.01) 16.79lp<.001)

X2111

b 29.85 (p < .001) 36.99 (p < .001) 12.62 (p < .001) 16.23 (p < .001)OR' 3.14 (2.09-4.73)** 2.93 (2.06-4.18)** 1.94 (1.41-2.67)** 2.20 11.38-3.52)**

Girls (n=408) (n= 116) (n=413) (n= 124) (n= 409) (n= 92) (n= 332) (n=19)0 159 25.5 47.4 106 16.2 31.5 107 16.6 42.4 82 17.2 31.71 214 40.0 44.0 236 43.1 46.8 198 40.3 35.9 147 33.7 44.32 151 34.6 8.6 195 40.7 21.8 196 43.0 21.7 182 49.1 24.0Test statistics: X21218 35.75 (p < .001) 20.88 (p < .001) 32.43 (p < .001) 17.74 (p < .0011

X2111b 34.92 (p < .001) 20.80 lp < .001) 28.96 (p < .001) 17.05 (p <.001)OR' 3.26 (2.22-4.79)** 2.65 (1.76-3.99)** 3.15 (1.95-5.09)** 3.14 (1.95-5.04)**

Note. Nonow = nonoverweight; Owob = overweight/obese.8Chi-Square test for independent factors.bMantel-Haenszel chi-square test for linear trend. .'Adjusted odds ratios (estimate. 95% confidence intervals) for Owob derived from the cumulative logistic model, nonoverweight isthe referent group. Covariates adjusted were exact age (continuous). socioeconomic status (five categories), cultural background(four categories). and rurality (two categories).**p < .01.

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BMI was a significant predictor for FMS proficiency forall demographic groups except Grade 10 boys; (b) waistcircumference was a significant predictor for FMS pro­ficiency for all groups except Grade 8 girls and Grade10 boys; and (c) FMS proficiency was inversely relatedto BMI and waist circumference, and the effects weregreater in the lower school grades (Grades 4 and 6).

Discussion

Two hypotheses were posited in this study. The re­sults of this study supported the first, that overall FMSproficiency is inversely associated with body composition.Specifically,for boys and girls in almost every grade, twiceas many overweight students are in the lowest FMS

Table 5. The distribution (%) of students bynumber of advanced object-control skills for nonoverweight and overweight/obese groups

Number of School yearadvanced Grade 4 Grade 6 Grade 8 Grade 10object-control skills n Nonow% Owob% n Nonow % Owob % n Nonow% Owob% n Nonow % Owob%

Boys (n = 466) (n = 125) (n = 525) (n= 132) (n= 425) (n= 113) (n = 417) (n= 97)0 198 31.3 41.6 89 12.8 16.7 71 12.9 14.2 39 5.3 17.51 181 30.9 29.6 178 24.8 36.4 114 18.6 31.0 78 15.4 14.42 125 23.4 12.8 193 29.9 27.3 152 31.1 17.7 127 23.7 28.93 or more 87 14.4 16.0 197 32.6 19.7 201 37.4 37.2 270 55.6 39.2Test statistics: X

2131•

8.56 (p < .05) 12.51 (p <.01) 12.20 (p < .01) 20.50 (p < .001)X2

111b 2.76 10.42 (p <.01) 1.83 13.52 (p < .001)

OR' 1.42 (0.99-2.03) 1.76 (1.24-2.49)** 1.25 (0.81-1.92) 2.15 (1.30-3.56)**

Girls (n= 407) (n= 116) (n=412) (n= 124) (n= 409) (n= 92) (n = 331) (n= 81)0 328 60.7 69.8 238 43.9 46.0 159 30.8 35.9 115 27.8 28.41 140 28.0 22.4 172 31.3 34.7 179 34.5 41.3 149 35.9 37.02 or more 55 11.3 7.8 126 24.8 19.3 163 34.7 22.8 148 36.3 34.6Test statistics: x2

m• 3.34 1.61 4.85 0.08X2

111b 3.15 0.83 3.35 0.05

OR' 1.44 (0.90-2.30) 1.14 (0.82-1.59) 1.28 (0.84-1.95) 1.12 (0.74-1.69)

Note. Nonow = nonoverweight; Owob = overweight/obese.·Chi-square test for independent factors.bMantel-Haenszel chi-square test for lineartrend.'Adjusted odds ratios (estimate, 95% confidence intervals) for Owob derived from the cumulative logistic model, nonoverweight isthe referent group. Covariates adjusted were exactage (continuous), socioeconomic status (5 categories), cultural background (4categories), and rurality (2 categories).**p< .01.

Teble 6. Results from multiple linear regressions with measures of body composition as predictor for standardized fundamentalmovement skills indexadjusted for age·, socioeconomic status, cultural background, and rurality

Predictorvariable

Effects of body composition (estimate, standard error)onstandardized FMS indexGrade 4 Grade 6 Grade 8 Grade 10

BoysBody mass indexWaist circumference

GirlsBody mass indexWaistcircumference

-0.290 (.07)**-0.126 (.03)**

-0.253 (.06)**-0.119 (.03)**

-0.326 (.07)**-0.137(.02)**

-0.168(.05)**-0.084 (.02)**

-0.142 (.05)**-0.076 (.02)**

-0.103 (.05)*-0.050 (.02)

-0.109 (.08)-0.055 (.03)

-0.219 (.07)**-0.097 (.03)**

Note. FMS = fundamental movement skills; Nonow = nonoverweight; Owob = overweight/obese.·Exact calendar agewhere available.*p < .05.**p < .01.

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quintile as compared to nonoverweight students, andtwo to four times as many nonoverweight students are inthe highest FMS quintile as compared to overweight stu­dents. These results agree with other studies in this areathat have used both process- (Southall et aI., 2004) andproduct-oriented (McKenzie et aI., 2002) assessmentsin smaller samples and across narrower age ranges. In­terestingly, the differences between overweight andnonoverweight students were strongest at the extremequintiles (that is, 1 and 5). Perhaps the variation inmaturation rate around puberty may confound this re­lationship in the middle three quintiles, because slightlyoverweight students and early maturers and normal andunderweight children and late maturers are in some ofthese groups.

Considering that FMS proficiency is associated withparticipation in organized physical activities (OkelyetaI., 2001b), this finding provides some explanation forthe lower physical activity levels reported among over­weight children (Trost, Kerr, Ward, & Pate, 2001). Itdemonstrates that overweight children are not develop­ing their FMS, or actual competence, to the same levelas nonoverweight children, potentially reducing theirenjoyment of (Okely & Booth, 2000) and participationin physical activity (Okely et aI., 2001b).

The results did not support the second hypothesis ofthis study. That is, body composition was found to be in­versely related to only locomotor skill proficiency; it wasvirtually unrelated to object-eontrol skill proficiency. Thisfinding supports the only other published study that hasexamined these differences. Southall et al. (2004) alsofound that, among Grade 6 students, overweight or obesestudents performed selected locomotor skillsmore poorlythat their leaner peers, but there was no difference inperformance on object-eontrol skills. The results fromSouthall and colleagues (performed with a much smallersample but broader range of skills) complement theseresults (larger sample but fewer skills and adjusted forSES,cultural background, and rurality).

There are several possible explanations for the sig­nificant findings for only locomotor skills. First, as loco­motor movements require greater overall movement ofbody mass than object-eontrol skills (which are morestatic in nature), they may be more difficult for over­weight children to perform. Ithas been shown that obesechildren find it more difficult to move their larger bodymass against gravity (Riddiford, 2000). In addition, over­weight children are more likely to have orthopedic com­plications, such as slipped capital femoral epiphyses(Loder, 1996), Blount's disease (Dietz, Gross, &Kirkpatrick, 1982), and flat feet (Riddiford-Harland,Steele, & Storlien, 2000), which may lead to greater painwhen performing physical activity and reduced partici­pation. However, because the data were drawn from across-sectional survey, we cannot infer causal direction.

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It is equally plausible that overweight children performless physical activity, which reduces the their opportu­nities to learn, practice, and develop FMS proficiency(being overweight causes low FMS proficiency) or thatchildren with poorer FMS proficiency have fewer oppor­tunities for and gain less enjoyment from participatingin physical activity (low FMS proficiency causes them tobe overweight). We offer the speculation that, in fact, bothof these alternatives are at least partially correct and thatFMSproficiency and overweight are reciprocally related.

The multiple linear regression analyses revealed thatBMI and waist circumference are significant predictorsfor FMS proficiency in all demographic groups exceptGrade 8 girls and Grade 10 boys. The relationships areconsistentfor both measures, and this consistencybetweentwo rather different measures strengthens the findings.We also found that the strength of the estimates betweenbeing overweight and FMSproficiencydecreases with age.Possible reasons for these differences between year groupsmay be the lower proportion ofGrade 4 and Grade 6 chil­dren who had advanced skills (mastery or near mastery)ofeach FMS (less ofa "ceiling" effect); that, as expected,BMI increased with age among this sample (Booth,Macaskill, Lazarus, & Baur, 1999); that overweight is lessamenable to change during adolescence (Styne, 2001);and that other factors, such as sedentary behaviors (forexample, homework and "hanging out" with friends), mayexert a greater influence on body composition during ado­lescence as students spend more time participating inthem (Kristjansdottir & Vilhjalmsson, 2001). It may alsobe a result of the interaction that occurs between physicalactivity and FMSproficiencywith respect to age. It isknownthat physical activityparticipation declines during adoles­cence, but that performance of FMS improves with ageduring this developmental period. An adolescent may beimproving FMS proficiency but at the same time decreas­ing participation in physical activity, therefore expendinglessenergy, which, assuming all else remains constant, willnot have as great an effect on body composition. This find­ing further highlights the importance offocusing on FMSinstruction during preschool and primary school yearswhen children are keen to develop skills, have less com­petingdistractions, and have, we hope, notyet developedbad habits, which maximizes their success and their moti­vation to be active,which, in tum, can influence adiposity.

These findings have particular relevance for thosewho work with overweight children and youth in devel­oping FMS proficiency (e.g., physical education teach­ers, coaches, parents, sports development officers). It isknown that these children suffer ridicule and teasingfrom their peers, especially in performing movementskills where they are often on public display (Puhl &Brownell, 2001). Consequently, overweight childrenoften opt out of these activities, thus reducing theiropportunities to develop actual competence and be

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Okely, Booth, and Chey

physically active. This was partly confirmed in some ad­ditional analyses we conducted on the students in thisdata set. We found that students who participated in theanthropometric measurements but who opted out of theFMS assessments had much higher BMIs and waist cir­cumferences compared with students in the nonmasteryFMSgroup.

This study is significant in that it is the first to usemore than one measure ofadiposity and a battery ofsixFMS. Its strengths include the use ofa large populationsample and the replication of results ofanalyses ofFMSproficiency and BMI, with another anthropometric mea­sure (waist circumference). It builds on previous stud­ies (Malina et al., 1995; McKenzie et aI., 2002) by usingdifferent body composition measures and a larger bat­tery ofFMS, assessed using process-oriented techniques.

In conclusion, our results indicate that BMI andwaist circumference are inversely associated with FMSproficiency among children and adolescents and thatthe association is strong for locomotor skills and weakfor object-control skills. These findings suggest thatmastery ofFMS may be an important factor in prevent­ing unhealthy weight gain among children and youth.This association is sufficiently robust to warrant investi­gation using both prospective cohort and experimen­tal methodologies.

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Authors' Notes

This study was supported by grants from the New SouthWales Department ofEducation and Training, the NewSouth Wales Department of Health, and the NationalProfessional Development Program. Please address allcorrespondence concerning this article to Anthony D.Okely, Faculty ofEducation, University ofWollongong,New South Wales, Australia, 2522.

E-mail: tokely@uow.edu.au

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