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a Department of Community Based Medicine
b Clinical Science at South Bristol, University of Bristol, Bristol, United Kingdom
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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DESIGN. Potentially relevant articles were identified by searching electronic databases. Duplicates were removed, abstracts were inspected, and relevant articles were obtained. Studies were included in the systematic review if participants were <16.0 years old, were healthy, had extractable data on bone mass, and had fractures as the outcome.
RESULTS. Ten case-control studies were identified. No prospective studies were found. There was no evidence of heterogeneity between studies or of funnel-plot asymmetry. Eight of the studies were included in the meta-analysis, because they presented results as means and standard deviations of bone density in cases and controls. The pooled standardized mean difference for bone mass in children with and without fractures, from a fixed-effects model, was –0.32 (95% confidence interval: –0.43 to –0.21).
CONCLUSIONS. Evidence for an association between bone density and fractures in children is limited. The results from this meta-analysis suggest that there is an association between low bone density and fractures in children. Although there was no evidence of heterogeneity or publication bias, this meta-analysis is based on case-control studies that are prone to bias. Large, well-conducted prospective cohort studies are required to confirm the association between bone density and fractures in children.
Key Words: bone density • children • fractures • meta-analytic methods • systematic reviews
Abbreviations: DXA—dual-energy x-ray absorptiometry • BMC—bone mineral content • BA—bone area • BMD—bone mineral density • QCT—quantitative computed tomography • QUS—quantitative ultrasound • SMD—standardized mean difference • CI—confidence interval
Fractures in children are common; the reported incidence of fractures in the United Kingdom in children ranges from 1.6% per year1 to 3.6% per year.2 There is also evidence that the incidence of fractures in childhood is increasing over time.3 It is well recognized that bone mass in adults influences fracture risk, but the evidence for an association between bone mass and fractures in children is limited. Indirect evidence that bone mass may influence fracture risk in children can be found in several randomized, double-blind, intervention trials that examined the effects of calcium intake in children and adolescents.4–6 These studies demonstrated improvements in bone mass, and further study found that children who avoid drinking cow's milk are at an increased risk for prepubertal bone fractures.7
Bone densitometry is commonly used to measure bone mass in adults, particularly in postmenopausal women. The most commonly used technique is dual-energy x-ray absorptiometry (DXA), and it is being used increasingly in children.8 DXA machines produce values for bone mineral content (BMC) and bone area (BA) and then calculate "areal" bone mineral density (BMD) by dividing BMC by BA. This is not a true density but a 2-dimensional measurement that can be affected by the subject's size. Although the problem of size in bone densitometry is well appreciated, there is no consensus on the most appropriate way to correct results for size.9 Other techniques for measuring bone density in children include peripheral quantitative computed tomography (QCT), quantitative ultrasound (QUS), and metacarpal morphometry.
The incidence of fractures increases with age, and fractures in later life are associated with osteoporosis (lower bone mass).10 Fractures in children are generally thought to reflect the fact that falls and other injuries are common in childhood,11 but there is emerging evidence that fractures in childhood are related to underlying skeletal fragility. The purpose of this systematic review is to quantify this relationship. There have been no previous systematic reviews of this association
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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16.0 years of age. Children were excluded if they had a chronic illness that is likely to affect bone mass. All studies were required to have extractable data on bone mass measured by any method. The primary outcome measure was all fractures. A systematic strategy was used to search electronic databases of published articles using both Medical Subject Headings and text-words. The databases searched were Medline (1966–2005), Embase (1988–2005), Web of Science (1965–2005), the Cochrane Musculoskeletal Injuries Group, the Cochrane Controlled Trials Register, and Sigle for "gray" literature. Articles about bone mass were obtained by using the words "bone density," "bone mineral density," "bone mineral content," "bone mass," "bone mineral apparent density," or "calcification" and their abbreviations. Articles about fractures were obtained by using the words "fracture" or "fractures." Articles on children were obtained by either using Medical Subject Headings of "infant," "child," or "adolescent" or limiting the search. Reference lists of articles obtained were also searched.
We assessed the methodologic quality of the studies. If the article did not contain sufficient information on the methodology, the authors were contacted. The key components of study quality that were assessed were comparability of fracture and control group at entry; selection of control group; definition of inclusion and exclusion criteria; clearly defined outcome measure; the measure and control for potential confounders in either the recruitment or analysis stage; and use of multiple comparisons or subgroup analyses.
The methods and results of all studies that reported the association between bone density and fracture risk in children were tabulated. Data from the studies that reported means and SDs were combined. A test of heterogeneity was performed and a funnel plot was drawn to look for publication bias and heterogeneity.12 Analysis was performed by using Stata 8.0 (Stata Corp, College Station, TX) using the "metan" and "funnel" commands. The standardized mean difference (SMD) was calculated by the difference in means divided by the pooled SD of participants' outcomes across the whole trial.13
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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The studies by Schalamon et al22 and Goulding et al23 did not control for potential confounders during either recruitment or analysis, but Goulding et al23 showed no difference between fractures and controls in terms of age and body size at baseline. All other studies controlled for the potential confounding effects of age; 4 studies controlled for the potential confounding effects of body size (either weight14,21 or both height and weight18,20). Puberty was assessed by Tanner stage in 4 studies: 1 study20 limited entry to participants who were prepubertal or in early puberty (Tanner stage I or II); 2 studies21,23 noted that there was no difference in Tanner stage between children with fractures and those without; and 1 study18 matched cases and controls for Tanner stage. Two studies17,19 presented data on children who were assumed to be prepubertal because of their ages, but no formal testing of pubertal stage had been undertaken.
In all studies, the measure of bone density was taken after the fracture with the time delay ranging from 12 hours22 to >1 year.20 Multiple comparisons and subgroup analyses were conducted in 3 studies.17,20,21
Eight of the studies presented results as means and SDs of bone density in cases and controls.15–22 Landin and Nilsson14 presented bone density of cases as percentage difference (cases minus controls). The study by Goulding et al23 presented results as the percentage of children with volumetric bone density below 1 SD of the study population. Using these 8 studies,15–22 a funnel plot was drawn to assess publication bias and heterogeneity and showed no evidence of asymmetry. Formal testing of heterogeneity was conducted by using the 
2 test, which showed no evidence of heterogeneity (2 = 13.03, with 9 degrees of freedom; P = .161). These 8 studies were combined by using a fixed-effects meta-analysis. Because many of the studies presented multiple comparisons, estimates were chosen that included a measure of body size, which used BMC and a peripheral measure of bone mass (forearm or femur) where possible. One study17 presented data for 3 age groups of children, and results for these groups were included separately in the analysis.
The combined SMD in mean bone mass between children with fractures and controls was –0.32 (95% confidence interval [CI]: –0.43 to –0.21; P < .001). A forest plot is shown in Fig 1. The fixed-effects meta-analysis was repeated after excluding the largest study,21 and the results still showed an overall lower bone mass in children with fractures compared with controls (SMD: –0.26; 95% CI: –0.40 to –0.11; P < .001). Additional analysis was performed on the 3 studies that presented results for children with wrist and forearm fractures.17,18,21 This subgroup analysis showed a similar association to that observed in the main analysis with an SMD of –0.25 (95% CI: –0.40 to –0.10). When latitude of the study centers was assessed, the studies that were based further away from the equator were more likely to show an association between low bone mass and fractures in children.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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All the studies were case-control studies and therefore are prone to bias. In these studies, unclear verification of fractures may introduce bias because some "cases" may not have had a fracture. This is possible in 2 studies18,22 and would tend to move the observed association closer to the null. Thus, our observed difference in mean bone mass between children with fractures and controls of –0.32 may be an underestimate. Lack of representativeness of the control selection may lead to a biased estimate of the effect of bone mass on fracture risk. However, most of the studies included in this review used accepted methods of control selection.
Confounding, both measured and unmeasured, is a problem in case-control studies. In bone-mass estimates made by using DXA, adjusting for body size is important but difficult. If adjustment is not complete, it may lead to an inaccurate estimate of the effect of bone mass on fracture risk. There is no ideal technique, but all studies used at least 1 method to account for differences in body size, such as adjusting for height, weight, or both, during either the recruitment or analysis stage. Some studies noted that there was no difference in either height or weight between the children with fractures and the control group.15–17,22 Two studies19,23 used BMAD, which is BMD corrected for area and is less influenced by body size than either BMC or BMD. Other potential confounders that were considered by most studies were age and gender. Schalamon et al22 did not seem to adjust for gender, but direct communication with the lead author confirmed that there was no difference in gender between children with fractures and those in the control group.
All the studies measured bone mass in the children after the bone fracture had occurred, which means that a reduction in bone mass resulting from the previous fractures cannot be excluded. However, repeat bone-density measurements were taken on the children used in the study by Goulding et al17 4 years after the original fracture.25 This showed a sustained lower bone mass in the children with fractures compared with those without. It is possible that behavior is modified permanently by a fracture and results in a persistent low bone mass. However, the sustained low bone mass shown in the study by Goulding et al25 is more likely to represent long-term bone mass and reduces the likelihood of reverse causality.
Multiple comparisons and subgroup analyses such as those conducted by Goulding et al,17 Suuriniemi et al,20 and Ma and Jones21 increase the likelihood that a "significant" result will be seen by chance. Because the biggest weight in the fixed-effects meta-analysis was given to the study by Ma and Jones,21 this may mean that our results are biased. However, repeating the fixed-effects meta-analysis without this study showed a similar difference in bone mass in children with fractures compared with controls. No asymmetry was shown by the funnel plot, so publication bias is less likely; however, the studies were small and 6 of the 10 studies had positive results, so we cannot exclude publication bias as a possible explanation.
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CONCLUSIONS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address correspondence to E.M. Clark, MRCP, MSc, Department of Community Based Medicine, University of Bristol, 24 Tyndall Ave, Bristol BS8 1TQ, United Kingdom. E-mail: emma.clark{at}bristol.ac.uk
The authors have indicated they have no financial relationships relevant to this article to disclose.
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REFERENCES |
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This article has been cited by other articles:
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  S. A. Atkinson, G. P. McCabe, C. M. Weaver, S. A. Abrams, and K. O. O'Brien Are Current Calcium Recommendations for Adolescents Higher than Needed to Achieve Optimal Peak Bone Mass? The Controversy J. Nutr., June 1, 2008; 138(6): 1182 - 1186. [Full Text] [PDF]
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 C. LeBlanc and F. Reed Jr. Early development of 'bone health' can help prevent fractures, rickets, osteoporosis AAP News, March 1, 2008; 29(3): 18 - 18. [Full Text] [PDF]
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 T. Winzenberg and G. Jones Recommended Calcium Intakes in Children: Have We Set the Bar Too High? IBMS BoneKEy, February 1, 2008; 5(2): 59 - 68. [Abstract] [Full Text] [PDF]
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S. A. Abrams and G. J. Strewler Adolescence: How Do We Increase Intestinal Calcium Absorption to Allow for Bone Mineral Mass Accumulation? IBMS BoneKEy, May 1, 2007; 4(5): 147 - 157. [Abstract] [Full Text] [PDF]
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