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Aim Motor skill impairment is a common negative outcome in children born preterm who do not develop cerebral palsy (CP). This study aimed to conduct a systematic review of current data to provide an accurate estimate of the prevalence of non-CP motor impairment in preterm children at school age.
Method We searched the Medline, PubMed, and PsycInfo databases and relevant journals to identify all studies published post-1990 that reported the prevalence of motor impairment in school-aged children born preterm (<37wks’ gestation) using standardised motor assessment batteries. We applied a range of exclusionary criteria, with 11 studies included in the final analyses. We identified two levels of motor impairment commonly reported – mild–moderate and moderate – and conducted a random effects meta-analysis to produce a prevalence estimate for each.
Results The pooled estimate for mild–moderate impairment in preterm children was 40.5/100. and for moderate motor impairment the estimate was 19.0/100. There was also a trend for lower motor impairment levels in samples born before 1990 compared with those born after 1990.
Interpretation Children born preterm are at increased risk of motor impairment, with prevalence three to four times greater than in the general population. This highlights the need for improved surveillance and intervention strategies in this group of children.
Motor skill impairment is a common negative outcome of preterm birth, with cerebral palsy (CP) the most severe form.1 However, many preterm children who do not develop CP still present with impaired motor skills, similar to that observed in developmental coordination disorder (DCD). Such impairment is known to have a significant negative impact reaching beyond the motor domain, with deficits commonly observed in educational, behavioural, and social domains among children with DCD.2–5 However, this type of impairment is often overshadowed in the preterm population by more severe physical and intellectual impairments. To inform surveillance and intervention services for preterm children, we need accurate estimates of the prevalence of motor impairment, an understanding of the nature of this impairment, and an appreciation of associated risk factors.
The prevalence of DCD in the general paediatric population is estimated to range between 5 and 1/10.6 In contrast, the prevalence of motor impairment in preterm cohorts without CP appears higher when reports are considered from individual studies. However, given the absence of a systematic review, we are without a reliable, overall estimate of prevalence. It is possible that motor impairment is the most common form of impairment in this population. If this is the case, appropriate resources should be assigned to detect and treat these difficulties. Therefore, the aim of this systematic review was to calculate an overall estimate of the prevalence of motor impairment (excluding CP) at school age in preterm children by pooling all of the available published data.
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Data extraction from the 15 studies resulted in nine estimates of prevalence at each impairment level. Table I provides details of each study, including the measure used, age at follow-up, and year of birth. Individual study sample sizes, prevalence levels, and 95% CIs for the proportion with mild–moderate and moderate impairment can be seen in Figures 1 and 2 respectively.
Figure 1. Prevalence of mild–moderate motor impairment by study with the pooled estimate from a random effects meta-analysis. Tinted line, pooled estimate of prevalence. Weight (%), the weight given to each study when calculating the pooled estimate.
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Figure 2. Prevalence of moderate motor impairment by study with the pooled estimate from a random effects meta-analysis. Tinted line, pooled estimate of prevalence. Weight (%), the weight given to each study when calculating the pooled estimate.
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Reported prevalence of mild–moderate motor impairment ranged from 22.2 to 72.2/100 (Fig. 1), with a pooled estimate of 40.5/100 (95% CI 32.1–48.9/100). [Correction added after publication 10 December 2009: in the preceding sentence the text ‘to 72.2’ was added.] Reported prevalence of moderate motor impairment ranged from 9.5 to 34.0/100 (Fig. 2), with a pooled estimate of 19.0/100 (95% CI 14.2–23.8/100). In both cases there was strong evidence of between-study heterogeneity (p<0.001), with estimates of the between-study SD of 12.0/100 for mild–moderate impairment estimate and 6.6/100 for the moderate impairment estimate (proportion of variability attributable to heterogeneity I2=91.3% and 85.9% respectively).
The two most commonly used motor assessment batteries in these studies were the Movement ABC and the BOTMP (Table I). Separate meta-analyses for the studies using each of these tests showed similar estimates of prevalence for each test (Table II).
Table II. Pooled estimates (% impaired) by variables of interest
| ||Moderate impairment||Mild–moderate impairment|
|Test norms used for impairment cut-off||7||18.5||12.7–24.3||7||36.3||27.7–45.0|
|Impairment cut-off based on reference sample||2||20.9||16.1–25.7||2||57.4||30.0–84.8|
|Born before 1990||3||23.1||16.7–29.6||3||42.6||34.1–51.0|
|Born after 1990||5||17.5||10.2–24.9||5||41.7||27.9–55.5|
Performing separate meta-analyses for the different types of impairment cut-off used suggested that studies using a local reference sample, rather than test norms, tend to identify a greater proportion of their sample as having motor skill impairment (Table II). This is particularly evident when the mild–moderate impairment cut-off was used. However, these findings should be viewed with caution owing to the small number of studies that included local reference samples.
Finally, Table II also shows the results of meta-analyses conducted separately on studies with children born before and after 1990. Note one study recruited their sample both before and after 199014 and was excluded from these calculations. These results suggest a small trend for higher prevalence levels of motor impairment in preterm children born before 1990 than those born after 1990; however, again, the small number of studies in each subgroup resulted in large and overlapping CIs.
Results of the pairwise correlation did not indicate a significant relation between age at follow-up and prevalence of motor impairment (r=−0.20 [n=9] for the mild–moderate cut-off and r=0.32 [n=9] for the moderate cut-off).
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This study aimed to provide an estimate of the prevalence of motor impairment in the preterm population excluding children with CP. Given that it is thought that the prevalence of DCD, a form of motor impairment very similar to that seen in children born preterm, is approximately 5–1/10 of the general population,6 our findings highlight the inflated level of motor impairment in preterm populations. This suggests that we need to do far more to develop an understanding of such impairment in these children so that appropriate intervention programmes can be developed. The cause of this apparent inflated rate of motor impairment remains unknown, though it is likely to be related to high rates of white-matter pathology15 and altered brain development16 observed in this population.
Interestingly, despite the elevated prevalence of motor impairment in preterm samples, there is little evidence on the functional impact of this impairment or its developmental course. Because of this, it is possible for this impairment to be viewed as transient in nature, reducing its clinical recognition. Such a view was often taken with DCD before the publication of longitudinal studies in the 1990s which demonstrated that though a portion of children with DCD appeared to overcome their motor skill problems with age, for many, problems continued into adolescence and beyond.3,4 More recent studies, such as those by Cantell et al.,17 have supported those initial findings. Since that time, the wide-ranging psychosocial implications of DCD have also been well recognized,2–5 indicating that it is important not to underestimate the impact of motor impairment on preterm children. We have demonstrated here the inflated level of motor impairment in preterm children compared with the general population, which we believe is the first step in gaining greater clinical recognition for children with these difficulties. Evidence for the functional impact on daily living skills would be the next step in improving clinical services, followed by longitudinal studies, which continue into adolescence rather than stopping in late childhood, and which map the developmental course of these difficulties and provide evidence about their lasting nature.
To obtain the prevalence estimates of motor impairment, studies that were heterogeneous in terms of study design, outcomes, birthweight, and years of birth were included in this meta-analysis. We will discuss the effects of some of these factors, though our findings need to be interpreted cautiously owing to the small number of studies available.
Motor assessment battery
Most studies presented here used the Movement ABC or BOTMP. The results of separate meta-analyses conducted for these two assessment batteries found similar prevalence levels. Other motor assessments may not yield similar findings. For example, some studies excluded from this review reported on motor impairment using only the Test of Visual Motor Integration.18 This test does not assess motor development across a range of skill types and yields greatly different results to those of an assessment battery. For example, Jongmans et al.19 reported an impairment level of 30.7/100 using the Movement ABC, but according to Test of Visual Motor Integration only 3.8/100 of the same sample was impaired. This highlights the importance of using standardised motor assessment batteries to define motor impairment.
A further issue about assessment batteries is the relevance of test norms. We reported on studies here that used the BOTMP at a time when the test norms were quite dated; in one instance, the test norms were more than 20 years old.20 Although we did not find a large difference in reported prevalence between the Movement ABC and the BOTMP, outdated norms could over- or underestimate prevalence levels, and assessment batteries should be chosen with this in mind. Importantly, both the Movement ABC and the BOTMP have recently been revised and both provide revised normative data. It is recommended that the revised versions of both tools be used in future studies to ensure prevalence estimates remain accurate.
Impairment cut-off used
Our review highlights the importance of the cut-off used to classify children as motor impaired. First, Figures 1 and 2 demonstrate the large difference, which is to be expected, between prevalence when a moderate impairment cut-off is used compared with a mild–moderate cut-off. We would suggest that, for ease of comparison, future studies report impairment rates using both levels of impairment.
Further, if a reference sample is to be used to create local norms, we would recommend reporting impairment rates according to both the local and test norms. Our results, though limited by the small number of studies, indicate that reference samples might result in higher levels of impairment than test norms. Although using a reference sample to create local norms allows researchers to control, to a limited extent, environmental factors that might play a role in children’s development, they do not allow results to be replicated easily or compared with other studies. A brief inclusion of results according to test norms would assist in this respect.
Year of birth
The era in which the infant was born and treated might also influence the prevalence of motor impairment. Our meta-analysis, although again limited by the small number of studies, indicated slightly lower prevalence in children born after 1990 than in those born before. Survival rates increased significantly after 1990 owing to the introduction of surfactant and antenatal steroids,21 but reductions in mortality have not been matched by reductions in morbidity.22 Given that there are now more ‘high-risk’ infants (e.g. infants born <26wks) surviving in the post-1990 era than previously, the slight decrease in motor impairment in more contemporary cohorts is a positive finding that we hope is replicated as more cohorts are followed up.
Birthweight and gestational age
The risk of negative long-term outcomes of preterm birth is likely to increase with decreases in birthweight and gestational age. As such, it would be expected that motor impairment would be more prevalent as birthweight and gestational age decrease. Unfortunately, a few studies that directly compared across birthweights were excluded because they either reported only on estimates using the 10th centile23 or included children with mild CP in their sample.24,25 Unsurprisingly, though, these studies did provide support for the higher prevalence of motor impairment in lower birthweight groups.23–25 None of the studies included in this meta-analysis examined prevalence across gestational age categories. If future samples have sufficient numbers of participants to allow it, estimating rates of impairment in gestational age and birthweight subgroups is recommended.
Age at follow-up
We found no correlation between age of the sample at follow-up and prevalence levels. However, Marlow and et al.26 have previously demonstrated that there was improvement in the TOMI scores of a sample of children who were born with low birthweight between 6 and 8 years of age. These improvements were maintained at age 12 years,8 indicating there might be a period of ‘catch-up’ for some preterm or low birthweight children during childhood. This indicates that age at follow-up could impact upon reported prevalence: the lack of a significant relation here could be the result of the lack of a representative spread of ages in the studies included in this review.
The variability among published studies presented the biggest limitation to our systematic review, with many of these factors discussed above. The variability in approaches also resulted in several studies either not meeting our inclusion criteria or being excluded from analyses. This included, for example, studies that reported mean scores on assessment batteries but did not provide prevalence levels.
The variability among the modest number of studies available for inclusion in our analysis also led to limitations in the depth of our analyses and our ability to determine how the factors of variability might interact. For example, did the effect of the impairment cut-off used (test norms vs control sample) differ depending on the test battery used?
Finally, we were unable to explore the impact of birthweight and gestational age on prevalence of motor impairment. The likely impacts of these factors were discussed above and it is hoped that future research will report levels of impairment in a way that allows such analysis.