Association of developmental coordination disorder and low motor competence with impaired bone health : A systematic review

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY-NC-ND 4.0 https://creativecommons.org/licenses/by-nc-nd/4.0/ Association of developmental coordination disorder and low motor competence with impaired bone health : A systematic review © 2022 Elsevier Ltd. All rights reserved. Accepted version (Final draft) Tan, Jocelyn; Murphy, Myles; Hart, Nicolas H.; Rantalainen, Timo; Bhoyroo, Ranila; Chivers, Paola Tan, J., Murphy, M., Hart, N. H., Rantalainen, T., Bhoyroo, R., & Chivers, P. (2022). Association of developmental coordination disorder and low motor competence with impaired bone health : A systematic review. Research in Developmental Disabilities, 129, Article 104324. https://doi.org/10.1016/j.ridd.2022.104324 2022 Association of developmental coordination disorder and low motor competence with impaired bone health: a systematic review. Abstract Aims This systematic review explores the association between developmental coordination disorder (DCD) and low motor competence (LMC) with bone health. Methods and Procedures Studies were included with assessment of any bone health outcome in a DCD or LMC population. Studies were located by searching published and grey literature. Study bias was assessed using the JBI critical appraisal checklist with publication bias assessed by funnel plot asymmetry. Due to heterogeneity meta-analysis was not possible and narrative synthesis was performed with effect size and direction assessed via harvest plots. Outcomes and Results A total of 16 studies were included: 8 paediatric, 7 adolescent and one adult. Deficits were reported for the DCD/LMC group in most bone measures, most frequent in weight-bearing sites such as the tibia. Critical appraisal indicated very low confidence in the results, with issues relating to indirectness due to DCD/LMC identification and imprecision relating to comorbidities. Conclusions and Implications Individuals with DCD or LMC appear to be at increased risk of bone health deficits with potential increased risk of fracture. If substantiated, results imply a likely increased risk of osteoporosis in later life, which based on bone impairment location may be due to insufficient loading from physical activity. Keywords: developmental disabilities, fracture, movement, inactivity, falls, bone. What this paper adds This review provides the first synthesis of the evidence of the association between DCD or LMC and low bone health. It indicates that there is evidence of an association between DCD or LMC and poor bone health in paediatrics and adolescence, which may extend to an increase in fracture risk during adolescence. This synthesis provides evidence that these bone health detriments are related to lower levels of physical activity. Importantly, gaps in the literature are identified with guidance for future research to address methodological confidence and imprecision issues. 1. Introduction Developmental coordination disorder (DCD) is a neurodevelopmental condition typified by difficulty in the acquisition and performance of motor skills such that there is an impact upon everyday functioning (American Psychiatric Association, 2013). DCD is also referred to as low motor competence (LMC) when DCD diagnosis is not possible (Blank et al., 2019). Individuals with DCD have been suggested to be at risk of a variety of health conditions, including impaired bone health (Cantell, Crawford, & Doyle-Baker, 2008; Hands et al., 2015; Tsang, Guo, Fong, Mak, & Pang, 2012). Bone health indicates the vulnerability of the bone to fracture and is indicated by measures including density, architecture, and geometry (Hart et al., 2020; Hart et al., 2017). Bone health impairment may be considered present when bone measurements are more than one standard deviation below age-appropriate reference intervals (World Health Organization, 1994). However, no individual tool is currently able to assess all elements that make up bone health and hence completely assess fracture risk (Hart et al., 2020; Shalof, Dimitri, Shuweihdi, & Offiah, 2021). Bone health follows a lifelong trajectory with growth and development in childhood and adolescence followed by gradual decline in adulthood (World Health Organization, 1994). Therefore, bone health impairment identified at any age can be a predictor for osteoporosis, a term which indicates skeletal frailty and minimal trauma fractures at an earlier age than would otherwise be anticipated (Bishop et al., 2014). As such, impaired bone health in populations with DCD may indicate a group at increased risk of fracture. Individuals with DCD may be at increased risk of bone health impairment due to risk factors such as low birth weight (Blank, Smits‐Engelsman, Polatajko, & Wilson, 2012; Cooper et al., 2006) or medication use for co-occurrent conditions such as attention deficit disorder/attention deficit disorder with hyperactivity (ADD/ADHD)(Feuer, Thai, Demmer, & Vogiatzi, 2016; Landgren, Fernell, Gillberg, Landgren, & Johnson, 2021). Additionally, individuals with DCD have been reported to have physical activity patterns similar to that associated with impaired bone health in the general population (Faulkner, 2007; Foley, Quinn, & Jones, 2008; Hart et al., 2020), with sustained low levels of physical activity and high rates of sedentary behaviour (Rivilis et al., 2011). Physical activity creates mechanical strain which stimulates bone development in accordance with the type and degree of strain and the life stage in which it occurs (Kontulainen, 2007). The greatest benefits for bone development are observed from high levels of diverse physical activity during childhood and adolescence (Hart et al., 2017). As such, bone health impairments are anticipated in the DCD population with reported low levels of physical activity, particularly seen in childhood (Rivilis et al., 2011). In the context of bone health impairment, a DCD or LMC population may be at an even greater than expected increased risk of fracture due to a higher rate of falls compared to the general public (Scott-Roberts & Purcell, 2018) and comorbidity with ADD/ADHD (James et al., 2021), which is associated with increased injury risk (Chou, Lin, Sung, & Kao, 2014). Fractures have a substantial impact on quality of life (Fortington & Hart, 2021; Son et al., 2016), with osteoporotic fractures in particular having a high mortality rate (Cauley, 2013). Additionally, fractures have a substantial economic impact, with an estimated direct cost of more than 100 million dollars over a 10-year period for osteoporotic fractures alone in Western Australia (Briggs et al., 2015). Given the estimated population rate of DCD being between five to six percent (Blank et al., 2019), identification of bone health impairment in individuals with DCD is of public health interest. To ascertain if DCD or LMC population is at increased risk of bone health impairments, it is necessary to determine its prevalence and severity. Hence, this systematic review aims to examine the association between DCD and LMC with bone health measures across the lifespan. 2. Methods This systematic review was registered within PROSPERO (CRD42020167301). It was performed in accordance with PRISMA guidelines for the reporting of systematic reviews (Page et al., 2021) and the JBI manual for studies of etiology and risk (Moola et al., 2017). 2.1 Eligibility Criteria 2.1.1 Participants. Assessment of studies for inclusion was performed via two author assessment (JT and PC) of the DCD diagnostic criteria from the diagnostic and statistical manual, version five, (DSM- V)(American Psychiatric Association, 2013). The criteria are: A: Acquisition and performance of motor skills substantially below that expected given age and experience B: Motor skill deficit affects age-appropriate activities of daily living, productivity, and leisure C: Deficit present from early development D: Another condition does not better explain the motor skill deficit Studies were included as DCD if they met DSM-V criterion A, with studies not assessing the full criteria classified as LMC. Studies were excluded if participants had a movement limiting or bone affecting condition. 2.1.2 Study design. Cross sectional studies and longitudinal single or multi-arm studies (including case studies, case series and clinical trials) were included in this review, provided they assessed bone health in human DCD/LMC populations. Only baseline data was extracted from intervention studies as this review did not assess change over time. Review articles and other works such as book chapters were excluded while conference publications and thesis were included. There were no exclusions based on language or publication date. 2.1.3 Outcome of interest. Studies assessing bone health via any measure were included. Established measurement outcomes for bone health included dual-energy X-ray absorptiometry (DXA) for bone density measures (bone mineral density and content); peripheral quantitative computed tomography (pQCT) for macroscopic architecture, geometry, and bone density measurements (trabecular and cortical bone area, bone mineral content and density, periosteal and endosteal size, cortical thickness, bone mass, and bone strength indices)(Hart et al., 2020); quantitative ultrasound for overall bone health reflecting density and architecture (Binkley, Berry, & Specker, 2008); and skeletal age assessment for bone maturity. Reliability issues have been reported in paediatric use for tools due to bone size variation (DXA, quantitative ultrasound), movement (pQCT)(Shalof et al., 2021) and ethnicity (skeletal age)(Mansourvar et al., 2013). DXA measurements in adults are used diagnostically as a clinical measurement of bone health using established reference norms (Hart et al., 2020) and a meta-analysis has reported correlation for DXA of 0.57 with pQCT results and quantitative ultrasound (Shalof et al., 2021). Fracture rates were assessed as a secondary indicator of bone health. 2.2 Information Sources One study author (JT) performed a search (from inception to June 2020, updated in March 2021) of the following databases: PubMed, Cochrane Central Register of Controlled Trials, Informit Health Collection, and ScienceDirect. Grey literature was searched using OpenGrey, Trove, Digital Commons Network, Networked Digital Library of Theses and Dissertations, WorldCat (restricted to theses), DART-Europe E-these portal, EThOs, and Scopus. In addition, conference websites for the American Society for Bone and Mineral Research and International Conference on Children’s Bone Health were searched. International conferences for DCD (National Conference on Developmental Coordination Disorder, International Conference on Developmental Coordination Disorder) did not have comprehensive websites, however, the websites for each year’s conference were searched when they were available. Google Scholar, WorldWideScience, and reference lists of key studies (Cantell et al., 2008; Chivers et al., 2019; Hands et al., 2015; Tsang et al., 2012) were searched for additional studies. 2.3 Search Strategy The search strategy is provided in Table 1 and was amended to individual databases as needed (Appendix A). For database searches, the search strategy was validated by ability to identify key studies (Cantell et al., 2008; Chivers et al., 2019; Hands et al., 2015; Tsang et al., 2012) listed in the database. All records were exported into EndNote (Clarivate Analytics, 2018) where duplicate studies were automatically removed. Study author (JT) uploaded remaining studies to Rayyan (Ouzzani, Hammady, Fedorowicz, & Elmagarmid, 2016) for screening. Studies where a translated English version was not available were translated via online translator ("Google Translate," 2021), with translation crosschecked ("DeepL Translator,"). ENTER TABLE 1 HERE 2.4 Selection Process Studies were screened for inclusion by title and abstract, and then full text by two pairs of authors (RB and JT or PC and JT) with disagreements resolved via discussion. Study exclusion reasons are listed in Appendix B. 2.5 Data Collection Process JBI data extraction forms for systematic reviews of etiology and risk (https://tinyurl.com/2pxv2vmu), modified to include motor competence measures and mean and standard deviation (SD) for individual outcomes, were used for data extraction. Data extraction was performed using an Excel form completed by two authors (JT and PC) working independently and crosschecked by JT for accuracy. The following general study characteristics and demographic information were extracted to determine if studies were linked and the appropriateness of analysis: publication details; ethical approval details; date, duration and location of data collection; recruitment procedure; motor competence terminology and assessment tool; and data analysis method. Furthermore, the following information was extracted where available for both the LMC/DCD and comparator group: number of participants; age, sex and puberty characteristics; motor competence measures mean and SD; and presence and incidence of comorbidities. Where multiple studies represented a single cohort, all data was extracted and compared to determine the most representative study for sensitivity analysis. 2.5.1 Outcome data items. All reported measures presented in each study for bone health outcomes were extracted for the LMC/DCD and comparator group, including raw numbers, effect size, mean or median, SD, and 95% confidence interval (CI) and odds ratio (OR) for impairment or fracture rates. Data was extracted for all subgroups and models presented. Data representing the lowest 15th percentile was preferentially used for analysis in accordance with DCD recommendations (Smits-Engelsman, Schoemaker, Delabastita, Hoskens, & Geuze, 2015) as were models that controlled for confounding variables. 2.5.2 Dealing with missing data. Two studies did not report total group data. One study which reported gendered data only (Chivers et al., 2019), had complete data provided through PC, the corresponding author of the original work. One paper provided correlation data only (Gustafsson et al., 2010), the author of which was contacted and provided unpublished total group data. 2.6 Assessment of Study Quality Study quality was independently assessed for each study using the JBI critical appraisal checklist for each study design (https://jbi.global/critical-appraisal-tools) by two authors (JT and PC) with disagreement resolved by discussion. The checklist for cross-sectional studies includes items on subject selection, incomplete reporting, and confounders, while the checklist for case series includes items on criteria and completeness of inclusion, and demographic and clinical information reporting. A judgement of overall study quality was performed using a method similar to Hayden et al. (2013) based on number of missing measures and appropriateness to study design. For example, failure to describe inclusion for the sample in detail may not affect study quality if the tool was validated and cut off points known but would reduce the overall quality rating if the tool was not as well established. 2.6.1 Reporting biases. Publication bias was assessed visually using funnel plot asymmetry (Guyatt, Oxman, Montori, et al., 2011). Informal assessment of publication bias was performed by comparing harvest plots of unpublished results to that of published papers for effect size and direction. The influence of small study bias was addressed by the risk of bias criterion ‘study size’ based on the number of DCD/LMC participants. Under this criteria studies with fewer than 50 participants were at high risk of small sample bias, 50 to 200 participants moderate risk, and greater than 200 participants low risk (Dechartres, Trinquart, Boutron, & Ravaud, 2013). 2.6.2 Diversity and heterogeneity. Clinical diversity due to variation in age, gender, and degree of motor competence impairment was addressed by sub-group analyses. Other reasons for clinical diversity, such as comorbidities, were described narratively. For the intended meta-analysis, heterogeneity was assessed visually and via the X2 and I2 statistic. 3.3.1.3 Upper body. Studies in the upper body were limited to one adolescent cohort and a paediatric ultrasound study with significant deficits for the LMC group being reported for the entire upper body, radius, and ulna. Deficits included measures of density (Hands et al., 2015) and stress-strain index (Chivers et al., 2019; Hands et al., 2015; Jenkins et al., 2020). Findings on all measures are reported in Table 7. ENTER TABLE 7 HERE 3.3.2 Fracture rates. Out of the three studies reporting fracture rates, two reported increased fracture rates for the LMC population. Odds ratios for fracture occurrence for the whole body was between 3.1 (95% CI 1.2 to 7.9) (Hands et al., 2015) and 8.3 (95% CI 1.0 to 70.5) (Hellgren et al., 1993). The arm was reported to be the most common fracture site (57-90% of fractures respectively). Ma et al.(2004) study, however, was confined in the upper limb and reported no increased risk for LMC individuals with odds ratios between 1.16 (95% CI 0.16 to 4.01) in the upper arm and 1.25 (95% CI 0.56 to 2.81) in the hand. 3.4 Data Syntheses Study level comparisons using harvest plots found an overall detrimental impact of DCD/LMC upon bone health as indicated in Figure 3. Two paediatric studies reported no effect (Gustafsson et al., 2008; D. Ma et al., 2004). One adolescent study using pQCT (Jenkins et al., 2020) reported bone outcome benefits for the LMC group compared to the healthy comparator group, which was significantly younger, on 87% of measures, prior to statistical adjustment for age, sex and bone length. Similar findings were not reported in studies from the same cohort where a different comparator group was used. ENTER FIGURE 3 HERE Harvest plots for individual outcomes (Figure 4) showed variability between individual outcomes by bone area with bone health detriment for the DCD/LMC group being more likely for loading sites than non-loading sites. Findings from pQCT studies on bone architecture found more detriments for the LMC group in areas responsive to bone loading e.g., trabecular density. Where bone detriment was present measurements were between one and two standard deviations lower than the comparator group. ENTER FIGURE 4 HERE A sensitivity analysis to examine the effects of including studies from the same cohort, found that limiting the adolescent cohort (Chivers et al., 2019; Hands et al., 2015; Jenkins et al., 2020; Tan et al., 2020) to one representative paper produced more bone detriments overall for the LMC group, via the reduction of beneficial bone health outcomes (Figure 5). Limiting the paediatric cohort to one representative paper reduced the number of bone detriments for the DCD/LMC whole body measurements only. Sensitivity analyses on the effect of including studies that did not fulfill DSM-V criterion B found a reduction in negative outcomes for whole body measurements and no effect for upper and lower body outcomes. ENTER FIGURE 5 HERE 3.5 Heterogeneity of Studies Meta-analysis of bone health outcomes found a high level of heterogeneity (I2=94%). Separate sub-analyses found heterogeneity was higher for studies on adolescents (I2=97%), than in paediatrics (I2= 50%). Restricting paediatric analysis to skeletal age did not improve heterogeneity (I2 between 55 and 71%) nor did sensitivity analysis which removed linked cohorts. Examination of individual outcomes found that negative outcomes were not confined to a particular age group with no difference in overall rate of bone health detriments. Rather, variation between age group of outcomes was dependent on body part. Paediatric populations had a higher proportion of males (71.7% to 83.5%) than the adolescent population (40.4% to 75.5%). Only adolescent studies reported gender specific data, with gender significantly affecting bone outcomes, with the greatest detriments reported in males. Sub-analyses based on DCD versus LMC status, found an overall more negative outcome for DCD , with neutral and positive outcomes being confined to LMC studies (Cantell et al., 2008; Chivers et al., 2019; Filteau et al., 2016; Gustafsson et al., 2008; Hands et al., 2015; Hellgren et al., 1993; Ireland et al., 2016; Jenkins et al., 2020; D. Ma et al., 2004; Oettinger; Schlager et al.; Tan et al., 2020). DCD studies, however, were few, confined to a paediatric population, and reported fewer outcomes. The impact of other factors such as physical activity and comorbidities could not be assessed due to insufficient studies reporting on these outcomes. 3.6 Reporting Biases Publication bias was not considered to be present as the grey literature did not show a different rate of findings than published literature. Funnel plots did not show evidence of asymmetry for total outcomes, skeletal age, or fractures. Missing results were considered unlikely as studies reported outcomes anticipated for the tool and body area, excepting pQCT studies which reported different outcomes between studies. It was considered possible that fracture rates were underreported given the ease of acquiring this information. As an example, Hands et al. (2015) paper is part of the adolescent cohort, none of whom have reported on fracture rates. 3.7 Certainty of Evidence Assessment of the body of evidence using the GRADE system produced a very low rating for certainty of evidence, indicating the true effect may be substantially different from that presented. Summary of findings is presented in Table 8, with rationale for ratings in Appendix D. ENTER TABLE 8 HERE 4. Discussion 4.1 Interpretation Outcomes of this systematic review indicate that DCD and LMC are associated with deficits in bone health. These detriments were between one and two standard deviations below the comparator group mean which may indicate low bone health or osteopenia (World Health Organization, 1994). These findings indicate that individuals with DCD and LMC, while not having clinically important bone impairments at the time of study may be at increased risk of osteoporosis in later life. Findings regarding fracture risk were mixed, however, the potential for increased fracture is supported by bone health outcomes. In particular, the finding of decreased skeletal age and bone density which is known to be associated with increased paediatric fracture rate (Jones & Ma, 2005). Additionally bone microarchitecture changes reported (Chivers et al., 2019; Ireland et al., 2016; Tan et al., 2021) suggest increased fracture potential via decreased bone strength measurements, such as fracture load. The absence of clinically significant findings is not unexpected as studies were performed prior to when bone loss would occur and greater deficits could be anticipated in the future. Although effect size was unable to be determined due to heterogeneity in measurement site, bone impairment locations suggest a loading causality. Studies examining weight-bearing sites, particularly the tibia and the hip, reported more deficits for the DCD/LMC group than nonweight bearing sites such as the fibula (Jenkins et al., 2020) and ulna (Ireland et al., 2016). Measures of bone architecture found more deficits in areas responsive to loading such as cortical area (Chivers et al., 2019; Ireland et al., 2016; Tan et al., 2021) and trabecular density (Chivers et al., 2019). Combined, this indicates bone deficits in a DCD or LMC population may be due to bone loading variations. Further research is required to establish causation of bone differences in the DCD and LMC group, especially given that most research was in a paediatric population and effects of physical activity in determining optimal bone structure in children and adolescents is not established in the general population (Bland, Heatherington- Rauth, Howe, Going, & Bea, 2020). Bone deficits found in this review may be compensated in later life (Shalof et al., 2021) as all but one study was performed prior to peak bone mass attainment. Bone detriments, however, were consistent between paediatric and adolescent studies in keeping with longitudinal studies on bone development which showed bone impairments continued into at least late adolescence (Wren et al., 2014). Furthermore, habitual physical activity patterns established in childhood tend to continue into adulthood in individuals with DCD (Missiuna, Moll, King, Stewart, & Macdonald, 2008), which may indicate that bone deficits are unlikely to be regained over the period of adolescence and young adulthood. Therefore, it is anticipated that adults with DCD have bone impairments, with associated clinical implications. 4.2 Limitations of Evidence The evidence was limited by heterogeneity in bone health measurements and the appropriateness of the tools for the population. Quantitative ultrasound and DXA for paediatric populations tend to produce inconsistent results compared to other modalities due to confounding by bone size (Shalof et al., 2021). pQCT results may be impacted by motion artefact, which has previously been identified as an issue in adolescents with LMC (Rantalainen et al., 2018). Furthermore, methodological review indicated low certainty in the results. The majority of studies did not comment on comorbidities, particularly ADD/ADHD which may have impacted on bone health measures due to increased fracture risk (Chou et al., 2014; Zhang, Shen, & Yan, 2021) and bone affecting medication use (Feuer et al., 2016). As ADD/ADHD was not accounted for in most studies and is estimated to occur in 50% of individuals with DCD (Kaplan, Dewey, Crawford, & Wilson, 2001) bone impairments found in this review may reflect ADD/ADHD or other conditions rather than DCD or LMC. Furthermore inconsistency in how the DCD/LMC population was identified, although common (Smits-Engelsman et al., 2015), is of particular concern in assessing bone health measures. As such further work is required to differentiate bone impairments in a clinical DCD population rather than a LMC population. 4.3 Limitations of Review Process Search terms used were extensive to include all studies in this area but may have increased heterogeneity in the sample. The decision to deviate from protocol and include studies that did not assess criterion B of DSM-V may also have increased heterogeneity. Individual perception of motor competence, reflected by criterion B, rather than motor test performance has been reported to be the strongest influencer of physical activity (Utesch et al., 2021.) and so may impact bone health. Sensitivity analysis however did not show an impact of including studies that did not fulfil criterion B. This review did not include clinical trial registries, outside of the Cochrane Central Register, therefore some unpublished studies may not have been reported. 4.3 Implications and future research Identified detriments in bone health may have clinical implications, particularly regarding the increased risk of fracture. Due to fractures impact upon quality of life (Hough, Boyd, & Keating, 2010) this should be a particular area for further investigation. Findings suggested impaired bone health was linked to reduced physical activity and so may be responsive to intervention, such as physical activity programs. This provides further support for individuals with DCD to engage in these programs. Although findings of this review indicate a continuance into adulthood, there is an absence of research in this age group. Clinical implications of impaired bone health in later adulthood could be significant and further research is required in this age group. Longitudinal studies to determine bone change in this population would also be valuable. Findings of this review were limited by high heterogeneity between studies. This indicates the need for studies to use reliable tools, appropriate comparator populations, and report on comorbidities and DSM-V diagnostic criteria. Clarification is needed in future studies as to whether bone impairments are unique to DCD to shape research and treatment recommendations. 4.4 Conclusion DCD and LMC show an association with impaired bone health on multiple measures in childhood and adolescence. These detriments are such that they appear to be due to physical activity variations. There is currently insufficient evidence as to the continuation of bone health detriments into adulthood, with a complete absence of information in later adulthood. Further evidence is also required as to whether the presence of bone health impairment has clinical implications. 5. Other information 5.1 Registration and Protocol This systematic review was prospectively registered within PROSPERO (CRD42020167301). Protocol for this review is published and can be accessed at doi: 10.11124/JBIES-20-00112 5.2 Availability of Data, Code, and Other Materials Template data collection forms can be accessed via the protocol. 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H., Nimphius, S., Rantalainen, T., Ireland, A., Siafarikas, A., & Newton, R. U. (2017). Mechanical basis of bone strength: influence of bone material, bone structure and muscle action. Journal of Musculoskeletal & Neuronal Interactions, 17(3), 114-139. Linked cohort studies are grey, unique studies are black. Negative label indicates bone measures are lower for DCD/LMC group than comparator. Neutral indicates no or extremely small difference. Positive indicates bone measures ae higher for DCD/LMC group than comparator. Except in neutral category, height represents degree of difference 1< 1 SD, 2 = 1 to 2 SD, 3 >2 SD. Figure 5 Sensitivity Analysis of Lower and Upper Limb Outcomes for Adolescent Cohort Adolescent cohort study is grey, other studies are black bars. Negative label indicates bone measures are lower for DCD/LMC group than comparator. Neutral indicates no or extremely small difference. Positive indicates bone measures ae higher for DCD/LMC group than comparator. Except in neutral category, height represents degree of difference 1< 1 SD, 2 = 1 to 2 SD, 3 >2 SD. Tables Table 1 Systematic Review Search Strategy Number Combiners Terms 1 Problem of Interest Bone health OR bone density OR fractures OR osteoporosis OR skeletal age OR pQCT OR bone mineral content 2 Participants Developmental coordination disorder OR motor competence OR clumsiness OR apraxia OR dyspraxia OR motor difficulty OR physical awkwardness OR coordination impairment OR specific developmental disorder of motor function OR motorically awkward OR minimal cerebral dysfunction OR minimal brain dysfunction OR deficits in attention, motor control and perception 3 #1 AND #2 Limitations Human, study design as per inclusion criteria Table 2 List of Included Studies Authors (date) Title Study design Study population Motor assessment Bone assessment Notes N Mean age/age range (years) Paediatric studies Schlager et al. (1974) Bone age in children with minimal brain dysfunction Case series 54 8.5 Minimal brain dysfunction diagnosis (Clements criteria) Skeletal age (Greulich and Pyle) A. W. W. Ma et al. (2018) Adapted taekwondo training for prepubertal children with developmental coordination disorder: a randomized, controlled trial RCT 145 7.4/7.5 Bruininiks- Osteretsky Test of Motor Proficiency, or MABCa; DCD questionnaire Ultrasonic bone age Paediatric cohort Gustafsson et al. (2008) ADHD symptoms and maturity a study in primary school children Cross-sectional 208 8.4 (Md) Motor Skill Development as a Basis of Learning Skeletal age (Greulich and Pyle) Oettinger (1975) Letter: Bone age and minimal brain dysfunction Case series 105 Minimal brain dysfunction diagnosis Skeletal age (Greulich and Pyle) Letter to the editor Tsang et al. (2012) Activity participation intensity is associated with skeletal development in prepubertal children with developmental coordination disorder Cross-sectional 33 7.8 DCD diagnosis; MABC-2a Ultrasonic bone age; DXA Fong et al. (2018) Diversity of activity participation determines bone mineral content in the lower limbs of prepubertal children with developmental coordination disorder Cross-sectional 52 7.5 Bruininiks- Osteretsky Test of Motor Proficiency or MABC Ultrasonic bone age ; DXA Paediatric cohort Yam and Fong (2017) A comparison of bone mineral density and body composition between children with developmental coordination disorder and typical development: Dual-energy X-ray absorptiometry Cross-sectional 77 8.1 Physiotherapy assessment DXA Conference presentation. Paediatric cohort Filteau et al. (2016) Associations of vitamin D status, bone health and anthropometry, with gross motor development and performance of school-aged Indian Cross-sectional 560 5.0 Ages and Stages Questionnaire Quantiative ultrasound children who were born at term with low birth weight Adolescent studies Jenkins et al. (2020) Characterisation of peripheral bone mineral density in youth at risk of secondary osteoporosis – A preliminary insight Cross-sectional 51 14.3 MAND pQCT Adolescent cohort Hands et al. (2015) Peripheral quantitative computed tomography (pQCT) reveals low bone mineral density in adolescents with motor difficulties Cross-sectional 33 14.3 MANDb pQCT; Fracture rate Adolescent cohort Chivers et al. (2019) Suboptimal bone status for adolescents with low motor competence and developmental coordination disorder— It’s sex specific Cross-sectional 39 14.4 MANDb pQCT Adolescent cohort Tan et al. (2020) Impact of a multimodal exercise program on tibial bone health in adolescents with Development Coordination Disorder: an examination of feasibility and potential efficacy. Case series 28 14.1 MANDb pQCT Adolescent cohort Ireland et al. (2016) Motor competence in early childhood is positively associated with bone strength in late adolescence Cross-sectional 443 17.8 Gross motor score at 18 months old PQCT; DXA Hellgren et al. (1993) Children with deficits in attention, motor control and perception (DAMP) almost grown up: general health at 16 years Cross-sectional 59 16.5 Neurological and neuropsychological examinations Fracture rate D. Ma et al. (2004) Risk-taking, coordination and upper limb fractures in children: a population based case-control study Case-Control 642 12.0- 13.5 MABCa Fracture rate Adult studies Cantell et al. (2008) Physical fitness and health indices in children, adolescents, and adults with high or low motor competence Cross-sectional 66 28.1 MABCa(experimental); DCD questionnaire DXA A: Movement Assessment Battery for Children; b McCarron Assessment of Neuromuscular Development Table 3 Body Areas Scanned by Tool DXA pQCT QUSa Total (including skeletal age) Total body 3 0 0 8 Spine 1 0 0 1 Lower body 3 4 1 8 Hip 2 0 0 2 Tibia 0 4 1 4 Fibula 0 1 0 1 Upper body 1 3 1 5 Radius 0 3 1 4 Ulna 0 1 0 1 A: quantitative ultrasound Table 4 DCD Diagnostic Criteria Assessment Criterion A Criterion B Criterion C Criterion D Classification Paediatric Schlager et al. (1974) Yes No No Yes LMC Oettinger (1975) Yes Not reported Not reported Not reported LMC Gustafsson et al. (2008) Yes No No No LMC Tsang et al. (2012) Yes Yes Yes Yes DCD Filteau et al. (2016) Yes Partiala No No LMC Yam and Fong (2017) Yes No No No LMC Fong et al. (2018) Yes Yes Yes Yes DCD A. W. W. Ma et al. (2018) Yes Yes Yes Yes DCD Adolescent Hellgren et al. (1993) Yes No Yes Yes LMC D. Ma et al. (2004) Yes No No No LMC Hands et al. (2015) Yes Not exclusion No Yes LMC