Research in Developmental Disabilities 34 (2013) 4433–4438
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Research in Developmental Disabilities
Does relative body fat influence the Movement ABC-2 assessment in children with and without developmental coordination disorder? Brent E. Faught a,*, Stephen Demetriades a, John Hay a, John Cairney b,c a b c
Faculty of Applied Health Sciences, Brock University, St. Catharines, Ontario, Canada Department of Family Medicine, Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 July 2013 Accepted 10 September 2013 Available online 28 October 2013
Developmental coordination disorder (DCD) is a condition that results in an impairment of gross and/or fine motor coordination. Compromised motor coordination contributes to lower levels of physical activity, which is associated with elevated body fat. The impact of elevated body fat on motor coordination diagnostic assessments in children with DCD has not been established. The purpose of this study was to determine if relative body fat influences performance on the Movement Assessment Battery for Children, 2nd Edition (MABC-2) test items in children with and without DCD. A nested case–control, design was conducted within the Physical Health Activity Study Team longitudinal cohort study. The MABC-2 was used to assess motor coordination to categorize cases and matched controls. Relative body fat was assessed using whole body air displacement plethysmography. Relative body fat was negatively associated with the MABC-2 ‘‘balance’’ subcategory after adjusting for physical activity and DCD status. Relative body fat did not influence the subcategories of ‘‘manual dexterity’’ or ‘‘aiming and catching’’. Item analysis of the three balance tasks indicated that relative body fat significantly influences both ‘‘2-board balance’’ and ‘‘zig-zag hopping’’, but not ‘‘walking heel-toe backwards’’. Children with higher levels of relative body fat do not perform as well on the MABC-2, regardless of whether the have DCD or not. Dynamic balance test items are most negatively influenced by body fat. Health practitioners and researchers should be aware that body fat can influence results when interpreting MABC-2 test scores. Crown Copyright ß 2013 Published by Elsevier Ltd. All rights reserved.
Keywords: Relative body fat Movement Assessment Battery for Children 2nd ed. (MABC-2) Developmental coordination disorder
1. Introduction Developmental coordination disorder (DCD) is characterized by problems with gross and fine motor ability, resulting in a significant impairment in physical, social and academic functioning, but is not the result of another psychiatric, neurological, or other medical condition (American Psychiatric Association, 2000). Developmental coordination disorder results in impairment in gross and/or fine motor skills (Cermak & Larkin, 2002). Prevalence of DCD in school-aged children is approximately 5–6% (American Psychiatric Association, 2000; Kadesjo & Gillberg, 1998). However, motor coordination deficiencies in children are generally underestimated and can significantly influence the quality of life and development of
* Corresponding author at: Faculty of Applied Health Sciences, Brock University, St. Catharines, ON L2S 3A1, Canada. Tel.: +1 905 688 5550x3586; fax: +1 905 688 8954. E-mail addresses: [email protected], [email protected] (B.E. Faught). 0891-4222/$ – see front matter . Crown Copyright ß 2013 Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ridd.2013.09.016
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the child. Reasons for underreporting include a lack of awareness of DCD as well as the need for early screening tools (Faught et al., 2008; Hay, Hawes, & Faught, 2004). Nevertheless, if identified early, the physical, academic, and emotional challenges of affected children can be addressed (Polatajko, Fox, & Missiuna, 1995; Schoemaker et al., 2006). The potential for improved quality of life warrants efforts to screen for and identify children with DCD (Barnhart, Davenport, Epps, & Nordquist, 2003). Developmental coordination disorder covers a heterogeneous group of children and not all will demonstrate the same clinical picture (Hoare, 1994; Sugden & Keogh, 1990). Children’s coordination challenges can result from an arrangement of one or multiple impairments related to proprioception, motor programming, as well as timing, or sequencing of muscle activity (Barnhart et al., 2003). Developmental coordination disorder is not usually diagnosed until a child reaches school age when their lack of coordination becomes a problem resulting in failure to satisfy particular environmental demands (Cermak, Gubbay, & Larkin, 2002). Multiple criteria are required in identifying children who are suspected of DCD. Typically, initial screening for indicators of motor challenges is followed by a confirmatory assessment using standardized tools to substantiate both fine and gross movement in coordination (American Psychiatric Association, 2000). Two of the most recognized standardized tools include the Movement Assessment Battery for Children 2nd Edition (MABC-2) (Henderson, Sugden, & Barnett, 2007) or the Bruininks-Oseretsky test of Motor Proficiency (BOTMP) (Crawford, Wilson, & Dewey, 2001). Both MABC-2 and BOTMP integrate gross motor skill tasks, which are important to assess the impact of DCD on daily activities in children such as running, jumping and ball skills. Beyond the physical challenges of daily living, children with DCD regularly report lower levels of perceived self-competence, self-esteem and peer acceptance (Cairney, Hay, Faught, & Hawes, 2005; Cairney, Hay, Faught, Wade, et al., 2005; Losse et al., 1991). This sense of compromised motor competence and perceived self-adequacy contribute to children with DCD engaging in lower levels of participation in physical activity compared to their peers (Cairney, Hay, Faught, Flouris, & Klentrou, 2007; Faught, Hay, Cairney, & Flouris, 2005). Subsequently, reduced levels of physical activity can significantly increase the risk of factors contributing to coronary vascular disease, including elevated body fat, cardiac output, stroke volume, and left ventricular mass (Cairney, Hay, Veldhuizen, & Faught, 2011; Chirico et al., 2012; Faught et al., 2005; Tsiotra, Nevill, Lane, & Koutedakis, 2009). Further, the persistence or elevated body composition measures of BMI and waist circumference have been reported in longitudinal surveillance studies of children with DCD compared to their healthy peers (Cairney, Hay, Veldhuizen, & Faught, 2010). While DCD has repeated demonstrated to influence negative body composition, there is a suggestion that increased body composition could negatively influence DCD, particularly in the assessment of motor proficiency. Brady, Knight, and Berghage (1977) reported a negative influence of increased body fat on gross body coordination tests of pull-ups, cable jump and 1.5 mile run. Similarly, Goulding, Jones, Taylor, Piggot, and Taylor (2003) found BOTMP balance scores were negatively correlated with body weight, body mass index, relative body fat and total fat mass in boys suggesting that overweight adolescents possess poorer balance compared to their healthy weight peers. Finally, D’Hondt, Deforche, De Bourdeaudhuij, and Lenoir (2008) reported fine motor control deficit in overweight and obese boys and girls in the standing position compared to healthy weight peers. Furthermore, detrimental fine motor control continued to exist with obese boys and girls in a sitting position, but not in overweight and healthy weight children. While these studies suggest a negative relationship between adiposity and fine and gross motor coordination, none have specifically examined this relationship with respect to children with DCD. The purpose of this study was to determine if relative body fat influences MABC-2 scores in children with developmental coordination disorder. 2. Methods 2.1. Study sample Complete procedures regarding initial motor coordination using the short form of the Bruininks-Oseretsky test of motor proficiency and invitation to participate in this study have been previously reported (Cairney, Hay, Veldhuizen, & Faught, 2010; Cairney, Hay, Veldhuizen, Missiuna, et al., 2010). The Physical Health Activity Study Team (PHAST) incorporated a nested case–control design ancillary to the PHAST longitudinal cohort study. The study population consisted of 63 controls and 63 DCD cases matched based on gender, school location and age within 3 months. This study was approved by both research ethics boards for Brock University and the District School Board of Niagara. Each subject and a parent provided written consent to participate in this study upon arriving to the laboratory. 2.2. Measures 2.2.1. Motor coordination The PHAST prospective cohort design implemented the Bruininks-Oseretsky test of Motor Proficiency (BOTMP-SF) for baseline assessment of motor coordination of the main study cohort. This motor proficiency test measures reaction time, balance and coordination and was administered to every consenting child. A score below 38 was an indication of being at risk of DCD. A full explanation of the main PHAST study can be found in previous publications (Cairney, Hay, Veldhuizen, Missiuna, & Faught, 2009; Faught et al., 2008). From the main study group a selection of 126 participants were selected for further evaluation and testing. Sixty-three children who tested as DCD using the BOTMP-SF were selected and 63 matched controls were recruited. The Movement Assessment Battery for Children 2nd Edition (MABC-2) was administered, to assess motor coordination of both fine and gross motor skills (Henderson et al., 2007). MABC-2 examines children for manual
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dexterity, aiming and catching as well as tests for static and dynamic balance. An age adjusted score was gathered from each test item and converted to an overall standard score (Henderson et al., 2007). The MABC-2 test was administered by a trained and qualified paediatric occupational therapist. Children that scored at or below the 15th percentile were identified as having significant motor impairment and were classified as being probable DCD cases. Furthermore, subjects underwent a cognitive evaluation of their intellectual ability by the occupational therapist using the Kaufman Brief Intelligence Test, 2nd Edition to verify that motor coordination was not owing to cognitive ability (Sugden, 2006). However, a full assessment of all criteria to confirm a diagnosis of DCD was not possible (DSM-IV, 1994). We were not able to determine if the subject’s performance in daily activities that require motor coordination was substantially below that expected based on chronological age, assessed intelligence, significant interferes with academic achievement or activities of daily living. As a result, we have chosen to refer to our cases as probable DCD (p-DCD). Finally, to our knowledge, no subject had been previously diagnosed with developmental coordination disorder. 2.2.2. Body composition Measurements of height, weight and relative body fat were conducted in a private assessment room by a research assistant in the presence of a parent/guardian. Height was measured to the nearest 0.1 centimetre using a stadiometer (Ellard Instrumentation Ltd.) with the child standing upright and without shoes. Weight was measured to the nearest 0.1 kilogram using an electronic medical scale. Relative body fat was ascertained via whole body air displacement plethysmography using the Bod Pod (Life Measurement, Inc., Concord, CA). Percent body fat measurements using air displacement plethysmography and dual-energy x-ray absorptiometry are highly correlated in normal weight (Lockner, Heyward, Baumgartner, & Kenins, 2000) and overweight (Weyers et al., 2003) individuals. Subjects wore compression suits and swim caps to decrease weight as well as minimize the impact of air volume resulting from loose clothing and body hair (Fields, Hunter, & Goran, 2000). Prior to each assessment, the Bod Pod was calibrated using a 50.341 l cylinder. While sitting motionless in the Bod Pod, the average of two body volume measurements was taken for each subject (Cairney et al., 2011). Relative body fat was determined using Lohman’s (1989) equation and the subject’s average body volume. 2.2.3. Physical activity Subjects were fitted with an Actical activity-monitoring device (Actical, Version 2.0, Mini Mitter, Respironics). They each wore the device for a 7 day period during which parents completed a log outlining when the device was in use. Specifically, the log detailed the length of time that the accelerometer was worn as well as when it was removed for bathing/swimming, sleeping or for other reasons. Accelerometry worn for a 7 day period has been demonstrated to be an accurate estimate of habitual physical activity in children (Trost, 2001). The device measures movement in 3 dimensions and registers all movement of the child. The Actical registers the intensity and duration of the activity in 30 s epochs and measures activity in 2 ways; step count and energy expenditure based on the amount of activity it records. Physical activity measurements are converted into kilocalories so that average energy expenditure (AEE) can be calculated. The cases and controls were tested within 2 weeks of each other to minimize the effects of seasonal variation in activity levels. Data was excluded from the study if the accelerometer was worn; (1) 0.05). Table 2 outlines the effect of relative body fat on MABC-2 subcategory scores; manual dexterity, aiming/catching and balance. The effect of relative body fat was inversely and significantly associated with all subcategories (model 1). The addition of physical activity level in model 2 adjusting the subcategories whereby only manual dexterity (p < 0.05) and balance (p < 0.01) remained significant. Only balance remained significantly (p < 0.05) associated with relative body fat
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4436 Table 1 Sample characteristics (mean [SD]).
Total subjects Males Females Age (years) Mass (kg)* Height (cm) Body fat (%)y Physical activity (counts/day)*
Entire sample
p-DCD
Controls
126 74 52 12.4 [0.51] 54.9 [15.7] 157.7 [7.9] 24.4 [11.2] 194515.9 [69,603]
63 37 26 12.4 [0.52] 59.4 [11.5] 158.35 [7.8] 28.5 [11.2] 176865.3 [57,535]
63 37 26 12.3 [0.51] 50.3 [11.3] 156.9 [7.8] 20.3 [9.8] 210949.3 [76,068]
* p < 0.05 denotes significant difference between p-DCD and controls. p < 0.01 denotes significant difference between p-DCD and controls.
y
Table 2 Regression of MABC-2 test categories on relative body fat, physical activity and DCD status. Model 1
Relative body fat
Model 2
Model 3
MD
AC
BAL
MD
AC
BAL
MD
AC
BAL
0.0618* [0.0219]
0.0497* [0.0301]
0.1144* [0.0258]
0.0566* [0.0219] 6.1E6 [3.53E6]
0.0384 [0.0296] 1.2E5* [4.8E6]
0.111y [0.0263] 3.7E6 [4.2E6]
0.0097 [0.0186] 1.3E6 [1.3E6] 3.32y [0.425]
0.0165 [0.0267] 6.9E6 [4.17E6] 3.92y [0.611]
8.25 0.067
9.69 0.024
10.54 0.15
6.94 0.09
6.92 0.08
9.75 0.15
8.33 0.42
8.57 0.34
0.0539* [0.0218] 2.2E6 [3.4E6] 4.06y [0.498] 11.45 0.48
Physical activity DCD status Constant R-squared
MD = manual dexterity; AC = aiming/catching; BAL = balance. * Level of significance: p < 0.05. y Level of significance: p < 0.01.
Table 3 Regression of MABC-2 balance test items on relative body fat, physical activity and DCD status. Model 1
Model 2 WTH
2BB Relative body fat
*
0.0902 [0.0231]
0.0852 [0.0256]
10.39 0.121
10.29 0.092
ZZH *
*
WTH *
ZZH *
2BB *
0.152 [0.0322]
0.0896 [0.0235] 6.94E7 [3.79E6]
0.0866 [0.0259] 1.61E6* [4.18E6]
0.143 [0.0321] 1.03E5 [5.17E6]
11.57 0.169
10.24 0.121
10.64 0.093
9.34 0.199
Physical activity DCD status Constant R-squared
Model 3
2BB
*
0.045 [0.0211] 3.9E6 [3.3E6] 3.15y [0.481] 11.57 0.370
WTH
ZZH
0.0481 [0.0241] 6.22E6 [3.76E6] 3.16y [0.549] 11.97 0.306
0.0911* [0.0302] 4.96E6 [4.72E6] 3.7y [0.691] 10.89 0.370
2BB = 2-board balance; WTH = walking toe-heel; ZZH = zig-zag hopping. * Level of significance: p < 0.05. y Level of significance: p < 0.01.
following the addition of DCD status and accounted for nearly half (R2 = 48%) of the variance in the MABC-2 balance score (model 3). Table 3 demonstrates the influence of three individual test items (2-board balance, walking toe-heel, zig-zag hopping) that represent the MABC-2 balance subcategory. All three balance assessment items were significantly influenced (p < 0.05) by relative body fat (model 1) and after adjusting for physical activity level (model 2). However, only 2-board balance and zig-zag hopping were significant (p < 0.05) after adjusting for DCD status (model 3). 4. Discussion Our analysis indicates that a significant amount of variation in the balance subcategory of the MABC-2 test is influenced by relative body fat regardless of DCD status. The effect of high adiposity on balance is not well covered in the literature particularly the influence of relative body fat on the MABC-2. While our study demonstrated that relative body fat does not significantly impact manual dexterity, some research demonstrates that overweight and obese children do experience challenges from reduced levels of manual dexterity (D’Hondt, Deforche, De Bourdeaudhuij, & Lenoir, 2009). The lack of uniformity between studies could be due to the influence of body fat on fine motor coordination while in the seated position. D’Hondt et al. (2008) revealed that reductions in fine motor coordination were less severe when children were in the seated position as less effort is required to maintain proper
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posture. Other research on the effect of body fat on both static and dynamic balance using the BOTMP-SF outline that higher levels of body fat in males aged 10–21 years suffer from poorer balance than non-overweight males (Goulding et al., 2003). Zhu, Wu, and Cairney (2010) demonstrated that obese Taiwanese children have lower performance on balance test items for the original Movement ABC tool. Our study confirms the influence of body fat on balance test scores as well as demonstrates the degree that body fat has on MABC-2 test items. Our study confirms and builds on the results found by Zhu et al. (2010) as it assesses the impact of body fat on the MABC-2 tool. Further, our study demonstrates the impact of body fat on all MABC-2 test items. Relative body fat does not appear to significantly impact the test item walking toe-heel backwards. Conversely, 2board balance and zig-zag hopping, characterized by medial-lateral movement, are mostly affected by increased body fat. It appears that increased levels of body fat more negatively influence balance in medial-lateral movement rather than anteriorposterior movements. According to Wearing, Hennig, Byrne, Steele, and Hills (2006), medio-lateral movement is mainly stabilized by muscles in the hip and, to a lesser extent, in the foot. Muscle development in children with higher levels of body fat is generally less pronounced and this reduction can make more complex or unfamiliar medio-lateral movements more challenging (Wearing et al., 2006). Another factor could be the greater propensity of body fat to shift during movement. It has been proposed that the inertial properties of body fat are greater when medial-lateral movements are made versus anterior– posterior movements (McGraw, McClenaghan, Williams, Dickerson, & Ward, 2000). It seems probable that a combination of poor muscle development and increased inertial properties of body fat during 2-board balance and zig-zag hopping contribute to the decrease in dynamic balance MABC-2 scores. A strength of our study lies in the use of whole body air displacement plethysmography in assessing percent body fat rather than less accurate body composition assessment tools. A child’s body fat changes with maturity, making a specific cut point for obesity challenging (Lee, Lee, Kim, Kim, & Kim, 2007; Taylor, Jones, Williams, & Goulding, 2002). There was no need for stratification by obesity status in our study and as such, we have shown the impact of body fat independent of obesity status. Also, our study was effective in identifying precisely what MABC-2 test items were most influenced by relative body fat. Analyzing balance by MABC-2 test items allowed us to identify dynamic balance activities as more negatively affected by increased body fat in children with probable DCD. Future research should consider the influence of body fat on dynamic balance relative to gender. This would also serve as a source of valuable information for those administering the MABC-2 test. Practitioners must be aware of the influence that body fat can impart when interpreting motor coordination assessment scores and identifying patients with developmental coordination disorder. Conflict of interest The authors declare that there is no conflict of interest. Acknowledgements This work was supported by a grant from the Canadian Institutes of Health Research (Grant #: 66959). Access to subjects was facilitated with cooperation from the District School Board of Niagara. We acknowledge the efforts of Nadilein Mahlberg and Sally Baerg in coordinating the laboratory assessments as part of the PHAST longitudinal study. 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Contents lists available at ScienceDirect
Research in Developmental Disabilities
Does relative body fat influence the Movement ABC-2 assessment in children with and without developmental coordination disorder? Brent E. Faught a,*, Stephen Demetriades a, John Hay a, John Cairney b,c a b c
Faculty of Applied Health Sciences, Brock University, St. Catharines, Ontario, Canada Department of Family Medicine, Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 July 2013 Accepted 10 September 2013 Available online 28 October 2013
Developmental coordination disorder (DCD) is a condition that results in an impairment of gross and/or fine motor coordination. Compromised motor coordination contributes to lower levels of physical activity, which is associated with elevated body fat. The impact of elevated body fat on motor coordination diagnostic assessments in children with DCD has not been established. The purpose of this study was to determine if relative body fat influences performance on the Movement Assessment Battery for Children, 2nd Edition (MABC-2) test items in children with and without DCD. A nested case–control, design was conducted within the Physical Health Activity Study Team longitudinal cohort study. The MABC-2 was used to assess motor coordination to categorize cases and matched controls. Relative body fat was assessed using whole body air displacement plethysmography. Relative body fat was negatively associated with the MABC-2 ‘‘balance’’ subcategory after adjusting for physical activity and DCD status. Relative body fat did not influence the subcategories of ‘‘manual dexterity’’ or ‘‘aiming and catching’’. Item analysis of the three balance tasks indicated that relative body fat significantly influences both ‘‘2-board balance’’ and ‘‘zig-zag hopping’’, but not ‘‘walking heel-toe backwards’’. Children with higher levels of relative body fat do not perform as well on the MABC-2, regardless of whether the have DCD or not. Dynamic balance test items are most negatively influenced by body fat. Health practitioners and researchers should be aware that body fat can influence results when interpreting MABC-2 test scores. Crown Copyright ß 2013 Published by Elsevier Ltd. All rights reserved.
Keywords: Relative body fat Movement Assessment Battery for Children 2nd ed. (MABC-2) Developmental coordination disorder
1. Introduction Developmental coordination disorder (DCD) is characterized by problems with gross and fine motor ability, resulting in a significant impairment in physical, social and academic functioning, but is not the result of another psychiatric, neurological, or other medical condition (American Psychiatric Association, 2000). Developmental coordination disorder results in impairment in gross and/or fine motor skills (Cermak & Larkin, 2002). Prevalence of DCD in school-aged children is approximately 5–6% (American Psychiatric Association, 2000; Kadesjo & Gillberg, 1998). However, motor coordination deficiencies in children are generally underestimated and can significantly influence the quality of life and development of
* Corresponding author at: Faculty of Applied Health Sciences, Brock University, St. Catharines, ON L2S 3A1, Canada. Tel.: +1 905 688 5550x3586; fax: +1 905 688 8954. E-mail addresses: [email protected], [email protected] (B.E. Faught). 0891-4222/$ – see front matter . Crown Copyright ß 2013 Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ridd.2013.09.016
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the child. Reasons for underreporting include a lack of awareness of DCD as well as the need for early screening tools (Faught et al., 2008; Hay, Hawes, & Faught, 2004). Nevertheless, if identified early, the physical, academic, and emotional challenges of affected children can be addressed (Polatajko, Fox, & Missiuna, 1995; Schoemaker et al., 2006). The potential for improved quality of life warrants efforts to screen for and identify children with DCD (Barnhart, Davenport, Epps, & Nordquist, 2003). Developmental coordination disorder covers a heterogeneous group of children and not all will demonstrate the same clinical picture (Hoare, 1994; Sugden & Keogh, 1990). Children’s coordination challenges can result from an arrangement of one or multiple impairments related to proprioception, motor programming, as well as timing, or sequencing of muscle activity (Barnhart et al., 2003). Developmental coordination disorder is not usually diagnosed until a child reaches school age when their lack of coordination becomes a problem resulting in failure to satisfy particular environmental demands (Cermak, Gubbay, & Larkin, 2002). Multiple criteria are required in identifying children who are suspected of DCD. Typically, initial screening for indicators of motor challenges is followed by a confirmatory assessment using standardized tools to substantiate both fine and gross movement in coordination (American Psychiatric Association, 2000). Two of the most recognized standardized tools include the Movement Assessment Battery for Children 2nd Edition (MABC-2) (Henderson, Sugden, & Barnett, 2007) or the Bruininks-Oseretsky test of Motor Proficiency (BOTMP) (Crawford, Wilson, & Dewey, 2001). Both MABC-2 and BOTMP integrate gross motor skill tasks, which are important to assess the impact of DCD on daily activities in children such as running, jumping and ball skills. Beyond the physical challenges of daily living, children with DCD regularly report lower levels of perceived self-competence, self-esteem and peer acceptance (Cairney, Hay, Faught, & Hawes, 2005; Cairney, Hay, Faught, Wade, et al., 2005; Losse et al., 1991). This sense of compromised motor competence and perceived self-adequacy contribute to children with DCD engaging in lower levels of participation in physical activity compared to their peers (Cairney, Hay, Faught, Flouris, & Klentrou, 2007; Faught, Hay, Cairney, & Flouris, 2005). Subsequently, reduced levels of physical activity can significantly increase the risk of factors contributing to coronary vascular disease, including elevated body fat, cardiac output, stroke volume, and left ventricular mass (Cairney, Hay, Veldhuizen, & Faught, 2011; Chirico et al., 2012; Faught et al., 2005; Tsiotra, Nevill, Lane, & Koutedakis, 2009). Further, the persistence or elevated body composition measures of BMI and waist circumference have been reported in longitudinal surveillance studies of children with DCD compared to their healthy peers (Cairney, Hay, Veldhuizen, & Faught, 2010). While DCD has repeated demonstrated to influence negative body composition, there is a suggestion that increased body composition could negatively influence DCD, particularly in the assessment of motor proficiency. Brady, Knight, and Berghage (1977) reported a negative influence of increased body fat on gross body coordination tests of pull-ups, cable jump and 1.5 mile run. Similarly, Goulding, Jones, Taylor, Piggot, and Taylor (2003) found BOTMP balance scores were negatively correlated with body weight, body mass index, relative body fat and total fat mass in boys suggesting that overweight adolescents possess poorer balance compared to their healthy weight peers. Finally, D’Hondt, Deforche, De Bourdeaudhuij, and Lenoir (2008) reported fine motor control deficit in overweight and obese boys and girls in the standing position compared to healthy weight peers. Furthermore, detrimental fine motor control continued to exist with obese boys and girls in a sitting position, but not in overweight and healthy weight children. While these studies suggest a negative relationship between adiposity and fine and gross motor coordination, none have specifically examined this relationship with respect to children with DCD. The purpose of this study was to determine if relative body fat influences MABC-2 scores in children with developmental coordination disorder. 2. Methods 2.1. Study sample Complete procedures regarding initial motor coordination using the short form of the Bruininks-Oseretsky test of motor proficiency and invitation to participate in this study have been previously reported (Cairney, Hay, Veldhuizen, & Faught, 2010; Cairney, Hay, Veldhuizen, Missiuna, et al., 2010). The Physical Health Activity Study Team (PHAST) incorporated a nested case–control design ancillary to the PHAST longitudinal cohort study. The study population consisted of 63 controls and 63 DCD cases matched based on gender, school location and age within 3 months. This study was approved by both research ethics boards for Brock University and the District School Board of Niagara. Each subject and a parent provided written consent to participate in this study upon arriving to the laboratory. 2.2. Measures 2.2.1. Motor coordination The PHAST prospective cohort design implemented the Bruininks-Oseretsky test of Motor Proficiency (BOTMP-SF) for baseline assessment of motor coordination of the main study cohort. This motor proficiency test measures reaction time, balance and coordination and was administered to every consenting child. A score below 38 was an indication of being at risk of DCD. A full explanation of the main PHAST study can be found in previous publications (Cairney, Hay, Veldhuizen, Missiuna, & Faught, 2009; Faught et al., 2008). From the main study group a selection of 126 participants were selected for further evaluation and testing. Sixty-three children who tested as DCD using the BOTMP-SF were selected and 63 matched controls were recruited. The Movement Assessment Battery for Children 2nd Edition (MABC-2) was administered, to assess motor coordination of both fine and gross motor skills (Henderson et al., 2007). MABC-2 examines children for manual
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dexterity, aiming and catching as well as tests for static and dynamic balance. An age adjusted score was gathered from each test item and converted to an overall standard score (Henderson et al., 2007). The MABC-2 test was administered by a trained and qualified paediatric occupational therapist. Children that scored at or below the 15th percentile were identified as having significant motor impairment and were classified as being probable DCD cases. Furthermore, subjects underwent a cognitive evaluation of their intellectual ability by the occupational therapist using the Kaufman Brief Intelligence Test, 2nd Edition to verify that motor coordination was not owing to cognitive ability (Sugden, 2006). However, a full assessment of all criteria to confirm a diagnosis of DCD was not possible (DSM-IV, 1994). We were not able to determine if the subject’s performance in daily activities that require motor coordination was substantially below that expected based on chronological age, assessed intelligence, significant interferes with academic achievement or activities of daily living. As a result, we have chosen to refer to our cases as probable DCD (p-DCD). Finally, to our knowledge, no subject had been previously diagnosed with developmental coordination disorder. 2.2.2. Body composition Measurements of height, weight and relative body fat were conducted in a private assessment room by a research assistant in the presence of a parent/guardian. Height was measured to the nearest 0.1 centimetre using a stadiometer (Ellard Instrumentation Ltd.) with the child standing upright and without shoes. Weight was measured to the nearest 0.1 kilogram using an electronic medical scale. Relative body fat was ascertained via whole body air displacement plethysmography using the Bod Pod (Life Measurement, Inc., Concord, CA). Percent body fat measurements using air displacement plethysmography and dual-energy x-ray absorptiometry are highly correlated in normal weight (Lockner, Heyward, Baumgartner, & Kenins, 2000) and overweight (Weyers et al., 2003) individuals. Subjects wore compression suits and swim caps to decrease weight as well as minimize the impact of air volume resulting from loose clothing and body hair (Fields, Hunter, & Goran, 2000). Prior to each assessment, the Bod Pod was calibrated using a 50.341 l cylinder. While sitting motionless in the Bod Pod, the average of two body volume measurements was taken for each subject (Cairney et al., 2011). Relative body fat was determined using Lohman’s (1989) equation and the subject’s average body volume. 2.2.3. Physical activity Subjects were fitted with an Actical activity-monitoring device (Actical, Version 2.0, Mini Mitter, Respironics). They each wore the device for a 7 day period during which parents completed a log outlining when the device was in use. Specifically, the log detailed the length of time that the accelerometer was worn as well as when it was removed for bathing/swimming, sleeping or for other reasons. Accelerometry worn for a 7 day period has been demonstrated to be an accurate estimate of habitual physical activity in children (Trost, 2001). The device measures movement in 3 dimensions and registers all movement of the child. The Actical registers the intensity and duration of the activity in 30 s epochs and measures activity in 2 ways; step count and energy expenditure based on the amount of activity it records. Physical activity measurements are converted into kilocalories so that average energy expenditure (AEE) can be calculated. The cases and controls were tested within 2 weeks of each other to minimize the effects of seasonal variation in activity levels. Data was excluded from the study if the accelerometer was worn; (1) 0.05). Table 2 outlines the effect of relative body fat on MABC-2 subcategory scores; manual dexterity, aiming/catching and balance. The effect of relative body fat was inversely and significantly associated with all subcategories (model 1). The addition of physical activity level in model 2 adjusting the subcategories whereby only manual dexterity (p < 0.05) and balance (p < 0.01) remained significant. Only balance remained significantly (p < 0.05) associated with relative body fat
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4436 Table 1 Sample characteristics (mean [SD]).
Total subjects Males Females Age (years) Mass (kg)* Height (cm) Body fat (%)y Physical activity (counts/day)*
Entire sample
p-DCD
Controls
126 74 52 12.4 [0.51] 54.9 [15.7] 157.7 [7.9] 24.4 [11.2] 194515.9 [69,603]
63 37 26 12.4 [0.52] 59.4 [11.5] 158.35 [7.8] 28.5 [11.2] 176865.3 [57,535]
63 37 26 12.3 [0.51] 50.3 [11.3] 156.9 [7.8] 20.3 [9.8] 210949.3 [76,068]
* p < 0.05 denotes significant difference between p-DCD and controls. p < 0.01 denotes significant difference between p-DCD and controls.
y
Table 2 Regression of MABC-2 test categories on relative body fat, physical activity and DCD status. Model 1
Relative body fat
Model 2
Model 3
MD
AC
BAL
MD
AC
BAL
MD
AC
BAL
0.0618* [0.0219]
0.0497* [0.0301]
0.1144* [0.0258]
0.0566* [0.0219] 6.1E6 [3.53E6]
0.0384 [0.0296] 1.2E5* [4.8E6]
0.111y [0.0263] 3.7E6 [4.2E6]
0.0097 [0.0186] 1.3E6 [1.3E6] 3.32y [0.425]
0.0165 [0.0267] 6.9E6 [4.17E6] 3.92y [0.611]
8.25 0.067
9.69 0.024
10.54 0.15
6.94 0.09
6.92 0.08
9.75 0.15
8.33 0.42
8.57 0.34
0.0539* [0.0218] 2.2E6 [3.4E6] 4.06y [0.498] 11.45 0.48
Physical activity DCD status Constant R-squared
MD = manual dexterity; AC = aiming/catching; BAL = balance. * Level of significance: p < 0.05. y Level of significance: p < 0.01.
Table 3 Regression of MABC-2 balance test items on relative body fat, physical activity and DCD status. Model 1
Model 2 WTH
2BB Relative body fat
*
0.0902 [0.0231]
0.0852 [0.0256]
10.39 0.121
10.29 0.092
ZZH *
*
WTH *
ZZH *
2BB *
0.152 [0.0322]
0.0896 [0.0235] 6.94E7 [3.79E6]
0.0866 [0.0259] 1.61E6* [4.18E6]
0.143 [0.0321] 1.03E5 [5.17E6]
11.57 0.169
10.24 0.121
10.64 0.093
9.34 0.199
Physical activity DCD status Constant R-squared
Model 3
2BB
*
0.045 [0.0211] 3.9E6 [3.3E6] 3.15y [0.481] 11.57 0.370
WTH
ZZH
0.0481 [0.0241] 6.22E6 [3.76E6] 3.16y [0.549] 11.97 0.306
0.0911* [0.0302] 4.96E6 [4.72E6] 3.7y [0.691] 10.89 0.370
2BB = 2-board balance; WTH = walking toe-heel; ZZH = zig-zag hopping. * Level of significance: p < 0.05. y Level of significance: p < 0.01.
following the addition of DCD status and accounted for nearly half (R2 = 48%) of the variance in the MABC-2 balance score (model 3). Table 3 demonstrates the influence of three individual test items (2-board balance, walking toe-heel, zig-zag hopping) that represent the MABC-2 balance subcategory. All three balance assessment items were significantly influenced (p < 0.05) by relative body fat (model 1) and after adjusting for physical activity level (model 2). However, only 2-board balance and zig-zag hopping were significant (p < 0.05) after adjusting for DCD status (model 3). 4. Discussion Our analysis indicates that a significant amount of variation in the balance subcategory of the MABC-2 test is influenced by relative body fat regardless of DCD status. The effect of high adiposity on balance is not well covered in the literature particularly the influence of relative body fat on the MABC-2. While our study demonstrated that relative body fat does not significantly impact manual dexterity, some research demonstrates that overweight and obese children do experience challenges from reduced levels of manual dexterity (D’Hondt, Deforche, De Bourdeaudhuij, & Lenoir, 2009). The lack of uniformity between studies could be due to the influence of body fat on fine motor coordination while in the seated position. D’Hondt et al. (2008) revealed that reductions in fine motor coordination were less severe when children were in the seated position as less effort is required to maintain proper
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posture. Other research on the effect of body fat on both static and dynamic balance using the BOTMP-SF outline that higher levels of body fat in males aged 10–21 years suffer from poorer balance than non-overweight males (Goulding et al., 2003). Zhu, Wu, and Cairney (2010) demonstrated that obese Taiwanese children have lower performance on balance test items for the original Movement ABC tool. Our study confirms the influence of body fat on balance test scores as well as demonstrates the degree that body fat has on MABC-2 test items. Our study confirms and builds on the results found by Zhu et al. (2010) as it assesses the impact of body fat on the MABC-2 tool. Further, our study demonstrates the impact of body fat on all MABC-2 test items. Relative body fat does not appear to significantly impact the test item walking toe-heel backwards. Conversely, 2board balance and zig-zag hopping, characterized by medial-lateral movement, are mostly affected by increased body fat. It appears that increased levels of body fat more negatively influence balance in medial-lateral movement rather than anteriorposterior movements. According to Wearing, Hennig, Byrne, Steele, and Hills (2006), medio-lateral movement is mainly stabilized by muscles in the hip and, to a lesser extent, in the foot. Muscle development in children with higher levels of body fat is generally less pronounced and this reduction can make more complex or unfamiliar medio-lateral movements more challenging (Wearing et al., 2006). Another factor could be the greater propensity of body fat to shift during movement. It has been proposed that the inertial properties of body fat are greater when medial-lateral movements are made versus anterior– posterior movements (McGraw, McClenaghan, Williams, Dickerson, & Ward, 2000). It seems probable that a combination of poor muscle development and increased inertial properties of body fat during 2-board balance and zig-zag hopping contribute to the decrease in dynamic balance MABC-2 scores. A strength of our study lies in the use of whole body air displacement plethysmography in assessing percent body fat rather than less accurate body composition assessment tools. A child’s body fat changes with maturity, making a specific cut point for obesity challenging (Lee, Lee, Kim, Kim, & Kim, 2007; Taylor, Jones, Williams, & Goulding, 2002). There was no need for stratification by obesity status in our study and as such, we have shown the impact of body fat independent of obesity status. Also, our study was effective in identifying precisely what MABC-2 test items were most influenced by relative body fat. Analyzing balance by MABC-2 test items allowed us to identify dynamic balance activities as more negatively affected by increased body fat in children with probable DCD. Future research should consider the influence of body fat on dynamic balance relative to gender. This would also serve as a source of valuable information for those administering the MABC-2 test. Practitioners must be aware of the influence that body fat can impart when interpreting motor coordination assessment scores and identifying patients with developmental coordination disorder. Conflict of interest The authors declare that there is no conflict of interest. Acknowledgements This work was supported by a grant from the Canadian Institutes of Health Research (Grant #: 66959). Access to subjects was facilitated with cooperation from the District School Board of Niagara. We acknowledge the efforts of Nadilein Mahlberg and Sally Baerg in coordinating the laboratory assessments as part of the PHAST longitudinal study. 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