The authors have no conflict of interest
Bone Mineral Response to a 7-Month Randomized Controlled, School-Based Jumping Intervention in 121 Prepubertal Boys: Associations With Ethnicity and Body Mass Index†
Article first published online: 1 MAY 2002
Copyright © 2002 ASBMR
Journal of Bone and Mineral Research
Volume 17, Issue 5, pages 834–844, May 2002
How to Cite
Mackelvie, K. J., Mckay, H. A., Petit, M. A., Moran, O. and Khan, K. M. (2002), Bone Mineral Response to a 7-Month Randomized Controlled, School-Based Jumping Intervention in 121 Prepubertal Boys: Associations With Ethnicity and Body Mass Index. J Bone Miner Res, 17: 834–844. doi: 10.1359/jbmr.2002.17.5.834
- Issue published online: 2 DEC 2009
- Article first published online: 1 MAY 2002
- Manuscript Accepted: 18 DEC 2001
- Manuscript Revised: 8 NOV 2001
- Manuscript Received: 16 JUL 2001
- bone mineral density;
- body mass index
We examined the effects of a 7-month jumping intervention (10 minutes, 3 times per week) on bone mineral gain in prepubertal Asian and white boys (10.3 ± 0.6 years, 36.0 ± 9.2 kg) at 14 schools randomized to control (n = 60) and intervention (n = 61) groups. Intervention and control groups had similar mean baseline and change in height, weight, lean mass and fat mass, baseline areal bone mineral density (aBMD; g/cm2), bone mineral content (BMC; g; dual-energy X-ray absorptiometry [DXA], QDR 4500W), and similar average physical activity and calcium intakes. Over 7 months, the intervention group gained more total body (TB) BMC (1.6%, p < 0.01) and proximal femur (PF) aBMD (1%, p < 0.05) than the control group after adjusting for age, baseline weight, change in height, and loaded physical activity. We also investigated the 41 Asian and 50 white boys (10.2 ± 0.6 years and 31.9 ± 4.4 kg) who were below the 75th percentile (19.4 kg/m2) of the cohort mean for baseline body mass index (BMI). Boys in the intervention group gained significantly more TB and lumbar spine (LS) BMC, PF aBMD, and trochanteric (TR) aBMD (+ ∼2%) than boys in the control group (adjusted for baseline weight, final Tanner stage, change in height, and loaded physical activity). Bone changes were similar between Asians and whites. Finally, we compared the boys in the control group (n = 16) and the boys in the intervention group (n = 14) whose baseline BMI fell in the highest quartile (10.5 ± 0.6 years and 49.1 ± 8.2 kg). Seven-month bone changes (adjusted as aforementioned) were similar in the control and intervention groups. In summary, jumping exercise augmented bone mineral accrual at several regions equally in prepubertal Asian and white boys of average or low BMI, and intervention effects on bone mineral were undetectable in high BMI prepubertal boys.
EXERCISE IN childhood promotes bone mineral accrual and, consequently, bone strength.(1,2) These factors are likely to reduce fracture risk in childhood(3) and, if maintained, also may reduce the risk of osteoporotic fracture in the elderly.(4)
Mechanically loading immature bone may influence its future strength profoundly.(5) Body mass provides a skeletal load during growth and is related to both absolute bone mass,(6–8) bone mass change in children,(8–10) and adult bone mass.(11) High-impact exercise augments skeletal loading; yet it is unclear to what extent body mass may interact with exercise to influence skeletal change in over- or average-weight children.
Exercises that are unusual, with ground reaction forces greater than those typically encountered in walking and running games, likely stimulate greater adaptations in young bones.(12,13) In young children, jumping activities that are performed easily, irrespective of the level of athletic skill, can provide ground reaction forces as high as nine times body weight.(14)
Several exercise interventions that incorporated jumping, weight training, and/or high-impact running games have successfully augmented bone mineral accrual at a range of skeletal sites in girls(15–17) and in combined groups of boys and girls.(14,18) However, to our knowledge, only one exercise intervention has examined the bone response to exercise in an independent group of young boys,(19) and all but one study(18) has been limited to white children.
Hip fracture rates are highest in whites, and worldwide rates in men are rising continuously.(20) Interestingly, Asian men sustain a greater number of hip fractures than do Asian women.(21) Asian children in North America may be at even greater risk for low bone mass in adulthood compared with their North American white counterparts.(22,23) Early intervention in children's activity habits may provide an important population-health initiative to reduce osteoporotic fractures in the future. Thus, it is critical to characterize the bone response to weight-bearing exercise in both boys and girls and in different ethnicities.
The primary purpose of this randomized controlled trial was to compare the changes in bone mineral content (BMC) and areal density (aBMD) between prepubertal boys participating in a 7-month, school-based, jumping intervention and their controls. During these primary analyses, we identified that body mass and ethnicity may have modified the intervention effects on bone mineral. Thus, we completed secondary analyses after categorizing boys as either having high body mass index (hiBMI) or average/low BMI (avBMI). Our secondary analyses in these two groups of boys investigated how the jumping intervention affected 7-month bone mineral change in Asian and white boys of avBMI and in boys with hiBMI.
MATERIALS AND METHODS
This randomized, school-based intervention included seven intervention and seven control elementary schools. Baseline measurements were made during the fall of the school year (September-October 1999). The intervention ran from late October to late May (7 months in duration) and final measurements were made at the end of the school year (June 2000). Each set of measurements was completed during a 4-week period. Schools were measured in random order at baseline, and this order was replicated at follow-up.
We recruited principals, teachers, and students from Richmond, a multiethnic school district outside of Vancouver, Canada, to participate in this study. The population of Richmond is 34% Hong Kong Chinese, 57% North American/European white, 5% East Indian, and 4% of other ethnic origin or mixed ethnicity. Of the 15 schools that initially expressed interest, 14 entered the study. Thirty-three teachers and 383 children (192 boys) from grades 4, 5, and 6 (8.8-11.7 years of age) consented to participate. This represented 50% of eligible children from the 14 schools.
To ensure equivalent ethnic distribution in control and intervention groups, schools were stratified by ethnic composition (<33% or >33% Asian) and number of student participants (<20 or >20). Schools then were randomized to either control or intervention groups. All boys and parents signed informed consent.
Each boy's health history questionnaire was completed by his parents. Each parent's birthplace was self-reported. All boys reported where they were born and what language was spoken at home. Boys were considered white if both parents were of North American or European origin. Ninety-two percent of white boys were born in Canada. Boys were classified as Asian if both parents or all 4 grandparents were born in Hong Kong (71%), Taiwan (18%), or the Philippines (11%). Of the Asian boys, 20% were born in Canada, 30% had immigrated 6-10 years before baseline measurement, and 50% had immigrated ≤5 years before baseline measurement. Boys from mixed ethnic backgrounds or of other ethnicities were excluded from this analysis.
Three boys were excluded from analysis because they had medical conditions that could affect normal physical activity or bone development (Down's syndrome, fractured tibia, or recent heart surgery). For generalizability of results and to ensure approximately equal variances by group, one other boy was excluded from this analysis because his bone mineral change across sites was consistently 3 SD above the mean. All other boys were healthy and none took medications known to influence bone metabolism. The institutional Research Ethics Board approved this study.
After excluding the 4 boys described previously, there were 133 prepubertal Asian and white boys at baseline. Line drawings of Tanner pubic hair ratings (1-5) were used to identify the maturity level of each boy.(24) Because this method has a high correlation with clinical examination(25) and is noninvasive, it is suitable for pediatric studies. At baseline, parents completed the assessment with their sons. The boys were either assisted by a member of the research team with the follow-up assessment or completed it with written instructions (in English or Chinese) under parental supervision at home. In this study, boys who were Tanner pubic hair stage 1 at baseline were classified as prepubertal. Boys who advanced two Tanner stages over the course of intervention were excluded from this analysis (n = 2, Asian; n = 6, white).
Bone mineral assessment
We assessed the following bone parameters: BMC (g) for the total body (TB) and BMC and aBMD (g/cm2) for the lumbar spine (LS) and proximal femur (PF) and its femoral neck (FN) and greater trochanter (TR) subregions using a Hologic QDR 4500W bone densitometer (dual-energy X-ray absorptiometry [DXA]; Hologic, Inc., Waltham, MA, USA). Measurements were made by one of two qualified technicians and all scans were analyzed by a single investigator using standardized procedures as outlined in the Hologic, Inc. Users Guide.(26) TB lean mass (g) and fat mass (g) were obtained from TB DXA scans. Because of a technical error in acquiring PF scans from 4 boys at baseline, these data were not available; all other boys had complete TB, LS, and PF data. We conducted a short-term precision study with our QDR 4500W and measured TB, LS, PF (and FN and TR) BMC, and aBMD three times within 1 h in 17 healthy young adults (K. J. MacKelvie, M. G. Donaldson, H. A. McKay, and M. A. Petit, unpublished data, 1999). The CVs for BMC and aBMD for the TB and LS were l < 0.7%. The CV for BMC at the PF, FN, and TR was 1.4, 2.6, and 3.5%, respectively. Similarly, the CV for aBMD was 0.5, 1.2, and 0.8%, respectively, at these sites. Precision studies in children on other DXA systems result in similar variation: between 0.8 and 2.3% CV for aBMD, depending on the site measured.(27) Spine and anthropomorphic phantoms were scanned daily for quality assurance.
Estimated volumetric BMD (vBMD) was calculated for the FN, assuming this region approximates a cylinder, by the equation vBMD = (4BMC ∗ [height of FN box])/π ∗ (FN area)2.(28) The height of the FN box was held constant at the manufacturer's default of 1.5 cm.(29) These assumptions provide a good approximation of true FN geometry.(28)
Height and weight
We measured standing height (stretch stature) to the nearest millimeter using a customized wall-mounted stadiometer. We assessed body weight with an electronic scale to the nearest 0.1 kg. For both height and weight, we used the mean of two measures for analysis.
All boys completed a food frequency questionnaire (FFQ) to estimate dietary intake of calcium.(22) The FFQ includes ethnic-specific, calcium-rich foods and was validated in Asian and white adolescents living in Vancouver, Canada.(30) A bilingual (Chinese-English) trained measurer assisted Chinese children. Questionnaires were analyzed by calculating daily calcium intake (mg) based on the calcium content of food items. The questionnaire was administered at baseline (fall), during the winter, and at final measurement (spring), and the average of three calcium intakes is reported.
General physical activity was determined by a modified version of the Physical Activity Questionnaire for Children (PAQ-C),(31) a researcher-administered measure of daily activity in the moderate to vigorous range over the previous 7 days. Final general physical activity scores were calculated as an average of the PAQ-C items in a continuous range between 1 (low activity) and 5 (high activity). This approach has been validated(32) and used in other pediatric studies.(1,18,22) The questionnaire was modified to include an estimate of time (h/week) spent in common sports and activities designated as loaded (impact > walking) physical activity. This questionnaire was administered at baseline, during the winter, and at final measurement. We report the mean of the three administrations.
School-based exercise intervention
The exercise program was designed to provide a brief (10-12 minutes), high-impact, weight-bearing exercise session during the twice-weekly scheduled physical education class and on one other occasion (supervised in the classroom or outside) during the week. For each session, teachers chose a circuit made up of five activities from a menu of nine different exercises and were encouraged to choose different activities from session to session. Students rotated through the five activity stations, taking approximately 1.5-2 minutes/station. All stations were comprised of jumping exercises (i.e., jumping jacks, lunge jumps, hopping, jumping over various obstacles, and drop jumps from a platform). The program generated progressively greater impact loading over the school year and the three levels (each 2.5 months long) were made increasingly difficult over time. For example, a simple jump using both feet was changed to a tuck jump and later to a plyometric jump. The height of the platform was increased progressively for drop jumps, from 10 (level 1) to 30 (level 2) to 50 cm (level 3). Within each level, the number of jumps at every station increased each week (starting with 10 to a maximum of 20 jumps). By this design, students jumped a minimum of 50 times each session at the beginning of a level and progressed to ∼100 jumps by the end of a level. Ground reaction forces for these activities typically were 3.5-5 times body weight.(33) After the circuit intervention, the regular physical education class continued normally.
The teachers who were to provide the intervention (n = 15) undertook a 4-h training session and this was supplemented by a 3-h inservice during the school year. Teachers were given a manual detailing all circuit activities and were provided with station posters to set up in the gym. Fourth-year Human Kinetics students from the University of British Columbia visited each intervention class once per month, to ensure that the program was implemented consistently. Teachers completed a log detailing the date, time spent, and circuit stations chosen each time their class performed the circuit.
Teachers at control schools (n = 18) were asked to implement a 10-minute stretching warm-up at the beginning of their physical education classes and a “stretch break” during class time on one other day during the week. We interviewed control school teachers to ensure that they had a similar time allowance (two 40-minute sessions) for physical education as the intervention schools. Teachers at control and intervention schools all used the standard school board instructional resource package for physical education.
Primary analyses—intervention effects
We used independent t-tests to compare baseline values for all variables (age, body size/composition, BMC, aBMD, and vBMD) and average yearly values for calcium and physical activity between control and intervention groups.
To compare change in BMC, aBMD, and vBMD, we used a 1-factor (intervention-control) analysis of covariance (ANCOVA), with baseline body mass (to control for initial size), change in height (to control for change in body size), physical activity loading time (to control for activity outside of the intervention), and age (to control for the range between boys in grades 4, 5, and 6) as covariates. We report main effects of the intervention on 7-month change in bone parameters (Table 1).
Baseline body mass and change in height and age were used as covariates based on the established relationships between these variables and change in bone mineral.(6,8,9,34,35) Furthermore, of the baseline body size variables (i.e., baseline height, baseline bone, and BMI), baseline body mass was the most highly correlated with change in bone parameters (r = 0.3-0.5; p < 0.001). We also used loaded physical activity as a covariate for two reasons: (1) mean yearly values were not equivalent between groups and (2) within this cohort, loaded physical activity was the most consistent predictor of bone mineral change across sites in stepwise linear regression. We report adjusted mean percent change in bone parameters.
Primary analyses showed a range in body mass (22.0-68.6 kg). We also identified an imbalance in the Asian/white ratio within BMI centiles: 3 of the 4 boys below the fifth percentile for baseline BMI were Asian, and 69% of boys above the 75th percentile for baseline BMI also were Asian. This range resulted in unequal variances in baseline body mass and BMI between Asian and white groups. Because change in bone mineral is predicted generally by baseline body size (larger children have larger unadjusted absolute gains in bone mineral than smaller children),(8–10) change in bone mineral had similar extreme variance, most notably in the Asian control group. However, bone mineral gains in boys in the highest quartile for baseline BMI were inconsistent, and these boys accrued some of the highest and lowest amounts of bone mineral over 7 months.
To evaluate the role of ethnicity and intervention on change in bone parameters, in groups with equal variance, we grouped boys according to baseline BMI. Boys who fell below the 75th percentile for baseline BMI (19.4 kg/m2) formed the avBMI group (n = 91, avBMI), and boys whose BMI was above the 75th percentile formed the hiBMI group (n = 30, hiBMI). We examined ethnic and intervention effects within the avBMI group and intervention effects only in the smaller hiBMI group. The number of Asian and white boys who were categorized as avBMI and hiBMI is shown in Tables 2 and 3.
Boys with avBMI—intervention and ethnicity effects
We used analysis of variance (ANOVA) to compare baseline values for all variables (age, body size/composition, BMC, aBMD, and vBMD) and average yearly values for calcium and physical activity between Asian-control, Asian-intervention, white-control, and white-intervention. To compare change in bone parameters, we used a 2 (Asian, white) × 2 (intervention, control) ANCOVA, with baseline weight, change in height, loaded physical activity, and final Tanner stage as covariates. We analyzed main and interaction effects of the intervention and ethnicity on bone mineral change.
Boys with hiBMI—intervention effects
We used independent t-tests to compare baseline values for all variables (age, body size/composition, BMC, aBMD, and vBMD) and average yearly values for calcium and physical activity between hiBMI-control and hiBMI-intervention groups. To evaluate a main effect for change in bone mineral between groups, we used a 1 factor (intervention and control) ANCOVA, with baseline weight, change in height, loaded physical activity, and final Tanner stage as covariates.
We report adjusted mean percent change in bone parameters. Data were analyzed using statistical software, Windows version 8.0 (SPSS, Inc., Chicago, IL, USA). Baseline data are presented as mean (SD), and change data are presented as (adjusted for bone parameters) mean (95% CI). Significance was set at p < 0.05 for all statistical analyses.
Subjects and compliance
Four boys moved during the school year (two control and two intervention). Thus, after excluding 8 boys who advanced 2 Tanner stages over the intervention, prospective data were available for 60 control and 61 intervention boys. Ninety-one boys were below the 75th percentile for baseline BMI (avBMI = 19 Asian control, 22 Asian intervention, 25 white control, and 25 white intervention) and 30 boys above the 75th percentile for BMI (16 hiBMI controls and 14 hiBMI intervention; total n = 121).
Classes at intervention schools performed the circuit intervention a mean of 57 (SD = 10) times. The maximum possible number of intervention sessions was 72. Thus, compliance averaged 80% across schools.
Primary analyses—intervention effects
The number of participants who advanced to Tanner stage 2 over the course of intervention was similar between control (n = 22, 37%,) and intervention (n = 25, 41%) groups. Baseline and change values for body size and anthropometric characteristics and average yearly values for physical activity and calcium intakes are reported (Table 1). There were no significant differences at baseline or in 7-month change between control and intervention groups for height, weight, lean mass, fat mass, physical activity, or calcium.
Table 1 summarizes baseline (mean [SD]) and adjusted change (mean [95% CI]) values for BMC, aBMD, and vBMD across sites. Baseline bone parameters were similar between intervention and control groups. There was a significant main effect for intervention for adjusted change in TB BMC (9.8% vs. 8.2%; p < 0.01) and PF aBMD (3.4% vs. 2.4%; p < 0.05). There was a trend for greater gain in LS BMC for the intervention group (10.6% vs. 9.2%; p = 0.10). Change at other skeletal sites and for other bone parameters did not differ significantly between intervention and control groups.
Secondary analyses: Boys with average/low BMI (avBMI)—intervention and ethnicity effects.
Within the avBMI group, the number of boys advancing to Tanner stage 2 in intervention (38%) and control (36%) groups was similar. More white (52%) than Asian (20%) boys advanced to Tanner stage 2. Baseline and change values for body size and anthropometric characteristics and average yearly values for physical activity and calcium intakes are reported (Table 2). There were no significant differences at baseline or in 7-month change between control and intervention groups within ethnicities for height, weight, lean mass, fat mass, physical activity, or calcium. White controls were taller than Asian controls at baseline (p < 0.05).
Table 2 summarizes baseline (mean [SD]) and adjusted change (mean [95% CI]) values for BMC, aBMD, and vBMD across sites. Baseline bone parameters did not differ between control and intervention groups within ethnicities. Asian controls had significantly lower baseline LS BMC than white controls and lower FN BMC as compared with both groups of white boys, (all p < 0.05).
There was a significant main effect of intervention for adjusted change in TB BMC (9.6% vs. 7.5%; p < 0.01), LS BMC (10.1% vs. 8.1%; p < 0.05), PF aBMD (3.2% vs. 2.1%; p < 0.05), and TR aBMD (3.4% vs. 1.8%; p < 0.05). Change at the FN was not significantly different between groups. Additionally, adjusting change in LS BMC and FN BMC for baseline BMC, as per baseline differences noted previously, did not alter the outcomes. Adjusted individual values for change in LS BMC and TR aBMD for intervention and control groups are shown (Figs. 1A and 1B)). There were no significant main effects for ethnicity and no significant ethnicity by intervention interaction effects on bone mineral change.
Secondary analyses: Boys with hiBMI—intervention effects.
The number of boys advancing to Tanner stage 2 in intervention and control groups was comparable. Control and intervention groups did not differ at baseline or in change in height, weight, lean mass, fat mass, physical activity, or calcium (Table 3). At baseline, all bone parameters were similar between groups. Adjusted 7-month bone change did not differ significantly between hiBMI control and hiBMI intervention at any site or for any bone parameter (Table 3). Further adjustment for change in fat mass to account for a trend toward greater gain in the control group did not alter this outcome.
This is the first prospective intervention study to show, in the primary analysis, a significant effect of a school-based jumping program on bone mineral change at the TB and PF in a large cohort of prepubertal Asian and white boys. Because of the unequal variances between Asian and white boys, we conducted an independent analysis of avBMI and hiBMI groups. This allowed us to examine our a priori question of an ethnic response to loading without violating statistical assumptions for ANCOVA. Secondary analyses revealed that Asian and white boys in the intervention group who were below the 75th percentile for BMI showed greater gains in TB and LS BMC and aBMD at the total PF and greater TR, compared with their same-ethnicity, control counterparts. However, boys in the intervention group above the 75th percentile for BMI in this cohort did not gain bone mineral relative to controls of similar BMI.
Primary analysis of intervention effects
The relatively small intervention effect we observed in the total sample (1-1.6% greater TB and PF bone mineral gain) was consistent with the only other exercise intervention in boys.(19) Our previous study that used a similar, but less structured and less intense exercise intervention,(18) also showed significant effects at the PF (TR subregion) in Asian and white boys and girls. Several factors, relevant to change in bone parameters in both the primary and the secondary analyses, will be discussed in the following sections.
Boys with avBMI: intervention effects on change in bone parameters
Our finding of a significant intervention effect (+2.1%) for change in TB BMC in avBMI boys is consistent with results of the single previous intervention in boys (n = 40), which reported a 1.2% greater increase in TB aBMD in the intervention group.(19) A seven-year prospective observational study also showed that peak absolute values and the magnitude and rate of TB bone mineral accrual were significantly greater in highly active children compared with low active children.(1) Change in TB bone mineral suggests a significant response to the intervention, not merely redistribution of bone mineral from a relatively unloaded site.
Although small, the change in TR aBMD in the intervention group was double that of controls and it was reflected in the significant increase at the total PF. Change at the FN was not different between intervention and control groups. Site specificity of the bone response to loading in this and previous studies(16–18) highlights the possibility of a combined influence of sex and maturity. Previous work by our group showed a significant 1.2% augmentation of bone mineral at the greater TR in younger prepubertal, Asian, and white boys and girls.(18) Recently, we showed a lack of response at the TR in prepubertal girls (10 years old, late Tanner stage 1)(17) involved in the same intervention as boys in the current study. Change at the PF and its regions was not reported in the previous study of prepubertal boys alone.(19)
We previously indicated that the physical maturity of subjects contributes substantially to bone mineral accrual as well as the skeletal response to exercise.(17) Early pubertal girls(17) following the same intervention as the boys in this study had significantly greater change at the FN (+3.1% for vBMD) than controls of similar maturity, and change at the TR was similar between groups. A jumping intervention in Finnish premenarcheal (mainly Tanner stages 2 and 3) girls augmented gains at the FN (+4% for BMC) but not the TR.(16) Taken together, these studies suggest that the PF and especially the FN may respond to a greater extent in early puberty as compared with prepuberty. However, further prospective studies of boys' responses to exercise at different maturational stages are needed.
Our intervention incorporated 2-foot and 1-foot jumps and multidirectional movements that required contraction of the gluteal and quadriceps muscles that attach to the greater TR. Therefore, we anticipated a change in bone mineral at this site. The incidence of TR fractures in older adults is increasing,(20) and there is a higher ratio of TR than FN fractures in both white(20) and Asian(21) men than in women. At the population level, aBMD is a good predictor of osteoporotic fracture in old age.(36) Whether site-specific gains in aBMD made in childhood persist into adulthood and old age and whether these gains reflect increased bone strength(37) are important areas for further investigation.
We also observed increased bone mineral at the LS in the intervention boys (+2% greater change in BMC). This result is consistent with investigations in similarly aged, prepubertal boys (+2.8%)(19) and younger prepubertal boys and girls (+3.1%).(14) However, exercise intervention did not affect change in LS bone mineral in our previous study of a younger, less mature, cohort of Asian and white boys and girls.(18) The “late Tanner stage 1” status of the boys in this study may have conferred a readiness for skeletal response to loading,(13) as compared with the less mature children in our previous study.(18) Furthermore, that study(18) used a moderate-impact exercise program that was less focused than either this study or other interventions that augmented bone mineral gain at the spine.(14,19) Thus, results from these studies suggest that a response at the LS may be elicited in prepubertal children who undertake a greater magnitude increase in impact loading activity.
Boys with avBMI: ethnicity effects on change in bone parameters
These are the first data comparing ethnic differences in bone mineral response to an intervention in boys alone. After adjusting for body size, maturity, and physical activity, there was no ethnic difference in the bone accrual response to exercise over 7 months at any measured site. In our previous intervention study in Asian and white boys and girls(18) after controlling for lean mass, fat mass, and sex in hierarchical regression, ethnicity did not significantly predict aBMD change with exercise.(18)
Ethnic differences in bone mineral may not appear until early puberty or later.(23,38) In a mixed longitudinal study that compared ethnic differences in bone mineral gain in 193 boys, Asians reached a lower peak spinal aBMD than white boys and tended to achieve this peak at an earlier age than boys from other ethnicities.(39) These data point to the need for studies in boys at different stages of maturity to better evaluate the role of ethnicity in bone mineral change.
Boys with hiBMI: intervention effects on change in bone parameters
There is a strong positive relationship between body weight and absolute values of bone mineral,(6–8) bone size,(35,40) and change in bone mineral(8–10) in children. The issue of body mass has received little attention in prospective studies of the bone response to exercise. The hiBMI boys in this study weighed, on average, 45% more than the mean for boys of the same age in Hong Kong (49.1 kg vs. 34 kg),(41) and 37% more than the mean for 10-year-old white Canadian boys (35.8 kg).(42) The 75th percentile for BMI in our cohort (19.4 kg/ m2) was slightly higher than that of 10.5-year-old boys in both the United States (18.5 kg/m2),(43) and China (18.2 kg/m2).(44) Thus, our cohort may have included a disproportionate number of overweight boys. Exercise intervention did not appear to further influence the already relatively large gains in bone mineral observed in boys who were above the 75th percentile for baseline BMI.
Body mass exerts stress on growing bone, leading to positive bone adaptations.(45) In obese children (defined as 20% above the expected weight for height), bone age maturation is accelerated.(46) It is possible that the skeletons of heavy boys may not respond to a loading exercise program when already under substantial adaptive stress because of the boys' weight. Overweight and obese children have greater absolute bone mineral than normal weight children; however, their bone mineral mass is lower than that predicted from their body mass.(47) In our cohort, boys in the highest quartile for BMI had a lower mean ratio of TB BMC/body mass (25.8 ± 3.4 g/kg body mass) than boys in the lower quartiles for BMI (32.2 ± 2.8 g/kg body mass). This imbalance between bone mass and TB mass may predispose heavy and obese children to childhood fractures.(3)
An alternative hypothesis is that the hiBMI boys in the intervention group were not motivated to perform the jumping exercises and may have found the type of intervention difficult to execute. Intervention teachers reported constant participation and effort on behalf of the overweight boys; however, we cannot be certain that their jumps were of high quality. Along these lines, previous studies suggest that adults who have higher percent body fat overestimate activity(48) and have a less accurate recollection of vigorous activity.(49) An approximate 50% exaggeration of self-report activity in overweight children has been reported.(50) We adjusted change in bone parameters by participation in extracurricular physical activity. An overestimation of physical activity likely would be equivalent between intervention and control groups and should not affect overall findings.
The possibility that the endocrine profile, and its effect on bone of overweight children differs from normal weight children should be noted. The complex relationships between hormones including growth hormone and insulin-like growth factor (IGF) 1, maturation, obesity, and exercise pose interesting possibilities for explaining the skeletal response to exercise in heavy children.(12,51–55) However, we did not evaluate hormone levels in this study. Further endocrinological research may be warranted to explore the mechanisms that control bone metabolism in overweight boys.
As a final point, the important influence of body composition on the accuracy (or inaccuracy) of DXA measures is noteworthy. Recent work using a simulation model showed that a sizable overestimation of BMC and aBMD can exist when percent body fat is high.(56) In light of this, comparisons of both baseline and change in DXA-measured bone mineral between normal (∼19% body fat in this study) and hiBMI children (∼33% body fat) must be interpreted with caution. Further investigations of the utility of DXA in the accurate assessment of bone mineral accrual in overweight children are warranted.
In summary, a 10-minute jumping intervention, implemented three times per week over 7 months, had a small but significant effect on TB and PF bone mineral accrual in a large cohort of Asian and white boys when data were analyzed without regard to boys' BMI. However, BMI at baseline was significantly related to bone mineral accrual and this may play a role in dampening the effect of a jumping intervention, because TB, LS, PF, and TR bone mineral changes were augmented by 1.1-2.1% in Asian and white boys of avBMI compared with their controls. In contrast, we observed no additional skeletal response to loading intervention in prepubertal boys with hiBMI. We conclude that a school-based exercise intervention can positively influence bone parameters in prepubertal boys and that this response appears to be independent of race. Further studies exploring the mechanisms whereby BMI influences bone accrual in this age group may be warranted.
We extend our sincere appreciation to 4-, 5-, and 6-grade students; teachers; and principals in the Richmond School District who volunteered their time and resources for this study. This project was supported by the British Columbia Health Research Foundation (2400-2 and 10898-2).
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