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Physical activity augments bone mineral accrual in young children: The Iowa Bone Development Study
PHYSICAL ACTIVITY AUGMENTS BONE MINERAL ACCRUAL IN YOUNG CHILDREN: THE IOWA BONE DEVELOPMENT STUDY KATHLEEN F. JANZ, EDD, JULIE M. GILMORE, PHD, TRUDY L. BURNS, PHD, STEVEN M. LEVY, DDS, MPH, JAMES C. TORNER, PHD, MARCIA C. WILLING, MD, AND TERESA A. MARSHALL, PHD
Objectives This 3-year follow-up study examined associations between physical activity and bone mineral content (BMC) and whether physical activity augments BMC accrual.
Study design Participants were 370 children (mean age baseline 5.3 years, follow-up 8.6 years). Physical activity was measured using 4-day accelerometry. BMC was measured using dual energy x-ray absorptiometry.
Results After adjustment for baseline BMC, age, and body size, mean physical activity predicted follow-up BMC at the hip, trochanter, spine, and whole body in boys and at the trochanter and whole body in girls. The variability in BMC explained by physical activity was modest (1% to 2%). However, based on a general linear model with adjustment for baseline BMC and body size, children who maintained high levels of physical activity accrued, on average, 14% more trochanteric BMC and 5% more whole-body BMC relative to peers maintaining low levels of physical activity. Conclusions This study suggests that maintaining high levels of everyday physical activity contributes to increases in BMC in young children, particularly at the trochanter. (J Pediatr 2006;148:793-9)
he greatest adaptive response of bone to physical activity appears to occur during childhood and adolescence.1,2 However, much of the evidence for the osteogenic effect of physical activity on bone development comes from observational studies of athletes or from targeted intervention studies.3-6 This is problematic because studies of athletes may be confounded by selection biases and reflect activity levels that would be unrealistic for many children. Musculoskeletal characteristics of athletic children, which also reflect the influence of genetic factors, are likely to be different from peers, even before training.6 Targeted intervention studies, although critical for determining cause and effect relations, are of limited value for understanding the natural history effects of physical activity on bone development including the time order of important relationships and sequencing of events. Therefore, in addition to research on athletes and intervention studies, longitudinal observational studies of normal, healthy children are needed to describe the cumulative effect of physical activity on bone acquisition and whether it is possible to increase bone or improve bone strength through higher levels of habitual physical activity.7 From a 6-year follow-up of 103 boys and girls (baseline age ranging from 8 to 15 years), Bailey et al1 observed that physically active boys achieved, on average, 9% more whole-body peak bone mineral content (BMC) than inactive boys while physically active girls had 17% more whole-body peak BMC than inactive girls. Other longitudinal studies of physical activity and bone accrual have also shown a positive influence of physical activity on bone during childhood and adolescence.8,9 However, controversy exists concerning the influence of sex on response of bone to physical activity and when the skeleton is most adaptable to the From the Departments of Health and Sport effects of physical activity.10-12 Studies, Preventive and Community DenWe have previously reported baseline associations between physical activity and tistry, Public Health Genetics, Epidemiology, and Pediatrics, The University of Iowa, BMC in a cohort of Midwestern children (179 boys and 189 girls, age ranging from 4 to Iowa City, Iowa. 13 6 years). We now report the 3-year follow-up associations specifically; we examine the Supported by grants from the National Inhypothesis that habitual levels of physical activity during middle childhood are predictive stitutes of Health RO1-DE12101, R01DE09551 and MO1-RR00059. of augmented BMC accrual. BMC reflects the absolute amount of mineral as hydroxySubmitted for publication Oct 2, 2005; last apatite within the selected bone. When adjusted for body size, BMC provides an revision received Nov 29, 2005; accepted important marker of skeletal mineralization and, unlike, areal bone mineral density Jan 30, 2006. Reprint requests: Kathleen F. Janz, EdD, De(aBMD) measures, it is not artificially inflated by bone size.14
T
aBMD Active minutes BMC
Areal bone mineral density (g/cm2) Daily frequency of accelerometry movement counts per minute ⱖ3000 Bone mineral content (g)
Total physical activity
Sum of total movement counts per day divided by total time of measurement (min) per day
partment of Health and Sport Studies, 102 FH, University of Iowa, Iowa City, IA 52242. E-mail: [email protected]. 0022-3476/$ - see front matter Copyright © 2006 Elsevier Inc. All rights reserved. 10.1016/j.jpeds.2006.01.045
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METHODS Study population Children were volunteers participating in the Iowa Bone Development Study, a longitudinal study of a cohort recruited immediately postpartum from 8 Iowa hospitals between 1992 and 1995. Of the 470 children in the original Iowa Bone Development Study cohort, 370 children completed baseline and follow-up physical activity and bone assessments (171 boys and 199 girls, mean age 5.3 years at baseline and 8.6 years at follow-up). Almost all (93%) of the cohort were non-Hispanic white. The study was approved by The University of Iowa Institutional Review Board (Human Subjects). Written informed consent was provided by the parents of the children. Skeletal bone measures Using a Hologic 2000 dual-energy x-ray bone absorptiometer (Hologic, Waltham, Mass), whole body, lumbar spine, and left hip scans were conducted in the University of Iowa General Clinical Research Center with software version 7.20. BMC (g) derived from these scans was the primary outcome variable. The pencil beam mode was used to scan the hip and the greater trochanteric sub region of the hip. (Because of concerns about reproducibility, we did not analyze the femoral neck sub region of the hip.) The whole body and anteroposterior view of the lumbar spine were scanned by use of fan-beam geometry with a multi-detector system. Previous research suggests that skull size confounds whole body bone data in young children. Therefore all whole body results presented in this study represent BMC excluding the skull.15 To minimize operator-related variability, all measurements were conducted on the same machine by 1 of 2 experienced, certified technicians. Quality control scans were performed daily using the Hologic phantom with the coefficient of variation for BMC measurements ⬍1%. Accelerometry-determined measures of physical activity Physical activity was assessed at baseline and follow-up using the Actigraph accelerometer (model 7164, Fort Walton Beach, Fla). Validation studies examining this accelerometer and the construction of summary variables for various characteristics of physical activity indicate that the Actigraph accelerometer is valid and reliable for monitoring activity in children in field settings.16-19 The accelerometer was set at 1-minute epochs and positioned to directly measure the acceleration of the displacement of the hip, making it particularly sensitive to monitoring weight-bearing movement. Children were asked to wear the accelerometers all daytime hours during 1 of the autumn months for 4 consecutive days. To be included in the data analysis, children had to wear the accelerometer at least 8 hours per day and at least 3 days. With the exception of 8 children, all participants wore the monitor at least 1 weekend day. 794
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From the accelerometry output we constructed 2 summary variables total physical activity and active minutes. These summary variables were calculated for each day and then averaged across days. Total physical activity was calculated by summing the total movement counts per day (raw data output) and dividing by total time of measurement (min) per day. Active minutes represents the daily frequency of accelerometry movement count per minute ⱖ 3000. During steady-state ambulation (brisk walking), this 3000 movement counts per minute cut-point is approximately equivalent to ground reaction forces of 1.6 times body weight in young children.20 It is also the approximate cut-point for vigorous activity (6 metabolic equivalent or METs) using the equation of Freedson et al.21
Body size measures At baseline and follow-up, trained General Clinical Research Center nurses measured the children’s weight (kg) and height (cm) using a Harpenden stadiometer (Holtain, United Kingdom) and a Healthometer physician’s scale (Continental, Bridgeview, Ill). Children were measured while wearing indoor clothes, but without shoes. Statistical analysis Sex-specific analyses were conducted to examine the distributional properties of the variables. Age, height, weight, BMC, and physical activity differences between boys and girls were tested with a 1-factor analysis of variance model, and sex-specific differences between baseline and follow-up values were tested using a 1-factor repeated measures analysis of variance model. The associations between baseline and follow-up measures were examined using Spearman rank-order correlation coefficients. Cross-sectional multiple linear regression models were constructed with follow-up BMC measures used as the dependent variables and total physical activity and active minutes as primary predictors. Covariates (age, weight, and height) were entered in a stepwise fashion. To examine longitudinal relationships, the models were refit for follow-up BMC with the additional covariates baseline BMC, change in height per year of age, follow-up height, and follow-up weight. Mean total physical activity and active minutes (average of baseline and follow-up) served as the primary predictor variables. Possible outlier observations were identified and their influence on fitted model parameters was assessed using regression diagnostic approaches. Final multiple regression models included all variables with associated P ⬍ .05. A general linear model was fit to compare mean differences in BMC accrual among 4 physical activity groups, adjusted for baseline BMC, change in height per year of age, follow-up height, and follow-up weight. Pairwise comparisons among the 4 least squares BMC means were made using the Bonferroni correction with an overall significance level of P ⬍ 0.05. Group 1 included those children ⬍ 50th percentile (least active for total physical activity) at baseline and followup. Group 2 consisted of those children who were ⱖ 50th The Journal of Pediatrics • June 2006
Table. Description of subjects and associations between baseline and follow-up measures (n ⴝ 171 boys and 199 girls) Baseline Age (yr) Boys Girls Height (cm) Boys Girls Weight (kg) Boys Girls Hip BMC (g) Boys Girls Trochanter BMC (g) Boys Girls Spine BMC (g) Boys Girls Whole Body BMC (g) Boys Girls Total Activity (ct/min) Boys Girls Active Minutes (min) Boys Girls
Mean (SD) 5.21 (0.42)* 5.30 (0.42) 111.76 (5.68) 111.22 (5.60) 20.36 (3.58) 20.11 (3.88) 7.27 (1.62) 6.96 (1.53) 1.27 (0.41)* 1.38 (0.46) 14.56 (2.50) 14.06 (2.64) 248.68 (76.57) 250.54 (80.95) 783.58 (162.88)* 714.79 (159.48) 31.50 (15.94)* 24.13 (12.80)
Follow-up Age (yr) Boys Girls Height (cm) Boys Girls Weight (kg) Boys Girls Hip BMC (g) Boys Girls Trochanter BMC (g) Boys Girls Spine BMC (g) Boys Girls Whole Body BMC (g) Boys Girls Total Activity (ct/min) Boys Girls Active Minutes (min) Boys Girls
Mean (SD)
r
8.62 (0.57) 8.66 (0.57)
0.29 0.30
133.90 (7.16)* 132.42 (6.80)
0.80 0.78
32.65 (9.72) 31.79 (8.72)
0.81 0.70
13.52 (3.32)* 12.81 (2.99)
0.71 0.77
2.72 (0.83) 2.71 (0.85)
0.68 0.57
22.73 (4.31) 21.87 (4.39)
0.81 0.57
582.58 (183.08) 562.18 (167.36)
0.82 0.82
733.92 (196.21)* 622.82 (164.15)
0.33 0.36
39.70 (21.81)* 24.83 (13.24)
0.40 0.40
Due to missing data: n ⫽ 169 boys baseline whole body BMC, 167 boys follow-up whole body BMC, 170 boys follow-up hip, 170 boys follow-up trochanter and 198 girls follow-up whole body BMC. Total Activity, Accelerometry-determined number of movement counts/day divided by the number of monitored minutes per day; r, Spearman correlation coefficients. *Boys significantly different than girls (P ⬍ .05). Baseline significantly different than follow-up (p ⬍ 0.05) for all measures except active minutes in girls (P ⬎ .05).
RESULTS
presented in the Table. The highest tracking correlation coefficients were for height and whole body BMC (r ⫽ 0.78 to 0.82). Tracking correlation coefficients were moderate to high for site-specific BMC (hip, trochanter, spine), with some divergence between boys and girls for spine BMC (r ⫽ 0.81 boys and 0.57 girls). physical activity was moderately stable between baseline and follow-up (r ⫽ 0.33 to 0.40).
Descriptive analyses At baseline, boys were more physically active, slightly younger, and had less trochanteric BMC than girls (Table). At follow-up, boys had significantly greater hip BMC, were taller, and were more active than girls. Between baseline and follow-up, height, weight, and all BMC measures increased in boys and girls. Total activity decreased in boys and girls while active minutes increased in boys but not girls. The mean time between baseline and follow-up scans was 3.4 (SD 0.6) years. The contribution of skull BMC to whole body BMC in our cohort decreased from a mean of 51% at baseline to 35% at follow-up with an approximate decrease of 4.4% per year (range 1.7 to 7.8%) (data not shown). Spearman rank-order correlation coefficients representing the stability of measures across the 3-year time period are
Multiple linear regression analysis Results from the follow-up cross-sectional stepwise multiple linear regression analyses are presented in Figure 1. Follow-up age, height, weight, and physical activity were considered for inclusion in each model but only those variables that were statistically significant (P ⬍ .05) were retained in the final models. As expected, height and weight explained much of the variability in follow-up BMC, whereas age was generally insignificant. At follow-up in boys, physical activity entered the models for hip BMC (active minutes) and trochanteric BMC (total activity), explaining 3% of the variability. In girls, physical activity entered the model explaining 1% of the variability for the trochanter (Figure 1). Results from the longitudinal stepwise multiple linear regression analyses
percentile (most active for total physical activity) at baseline but ⬍ 50th percentile at follow-up. Group 3 included those children ⬍ 50th percentile at baseline but ⱖ 50th percentile at follow-up. Group 4 included those children ⱖ 50th percentile at baseline and follow-up.
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Figure 1. Follow-up BMC, g from stepwise linear regression. Black bars ⫽ active minutes (min); striped bars ⫽ total activity (ct/min); gray bars ⫽ height (cm); stippled bars ⫽ weight (kg); crossed-hatch bars ⫽ age (yr). Note: % ⫽ R2. Only variables p ⬍ 0.05 retained in final models.
are presented in Figure 2. In these models, the dependent variables were hip, trochanter, spine, and whole-body BMC at follow-up. Covariates were baseline BMC, percent change in height per year, follow-up height, and follow-up weight. With 1 exception (girl’s trochanter), baseline BMC and follow-up weight explained much of the variability in follow-up BMC. Mean physical activity entered as significant in all models except follow-up hip and spine in girls. Its effect was small, explaining only 1% to 2% of the variability in follow-up BMC.1.
Physical activity group analysis Figure 3 presents results from a general linear model fitted to compare mean differences in BMC accrual among the 4 physical activity groups, adjusted for baseline BMC, change in height per year of age, follow-up height, and follow-up weight. The 4 physical activity groups were constructed to characterize the accumulation and pattern of physical activity levels during the 3-year study interval. Using a sex-specific median split of total physical activity at baseline and follow-up, group 1 included those children ⬍50th percentile (least active for total physical activity) at baseline and follow-up, group 2 were children ⱖ50th percentile (most active for total physical activity) at baseline but ⬍50th percentile at follow-up, group 3 were children ⬍50th percentile at baseline but ⱖ50th percentile at follow-up and group 4 were children ⱖ50th percentile at baseline and follow-up. Cell sizes for the physical activity groups were as follows: 47 boys and 59 girls (group 1), 38 boys and 40 girls (group 2), 38 boys and 40 girls (group 3), and 48 boys and 60 girls (group 4). The median split for total physical activity for boys was 761 ct/min at baseline and 722 ct/min at follow-up. For girls, the median split was 703 ct/min at baseline and 605 ct/min at follow-up. Sixty percent of the boys and 56% of the girls 796
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Figure 2. Follow-up BMC, g from stepwise linear regression with adjustment for baseline BMC. Black bars ⫽ mean active minutes (min); striped bars ⫽ mean total activity (ct/min); light gray bars ⫽ follow-up height (cm); dark gray bars ⫽ follow-up weight; white bars ⫽ percent change height/yr age (cm/yr); stippled white bars ⫽ baseline BMC (g). Note: % ⫽ R2. Only variables p ⬍ 0.05 retained in final models.
maintained their median split grouping at both baseline and follow-up. Statistically significant (P ⬍ .05) differences in adjusted follow-up BMC were found between group 4 (high activity baseline and follow-up) and group 1 (low activity baseline and follow-up) for the trochanter and whole body in both boys and girls and for the hip in boys. Pairwise comparisons indicated a 14.3% (boys) and 12.8% (girls) greater mean trochanteric BMC for group 4 when compared with group 1. Adjusted mean whole body BMC for group 4 was 5.2% (boys) and 4.1% (girls) greater than group 1. For boys, adjusted mean hip BMC for group 4 was 11% greater when compared with group 1. Results were similar when the active minutes physical activity measure was used to construct the comparison groups (data not shown).
DISCUSSION Longitudinal studies have the potential to define growth-related changes in BMC and may provide insight to important contributors of BMC accrual, as well as the prediction of future bone health. This longitudinal study used objective monitoring to examine the effects of habitual physical activity on bone accretion in young, non-athletic children because children under the age of 11 are generally incapable of accurately reporting their physical activity patterns and parents are poor proxy reporters, particularly of their children’s physical activity intensity.22 In this study, using accelerometry-determined physical activity, we have shown that physical activity contributes to increases in BMC for both boys and girls. This finding is consistent with previous longitudinal studies of older children and adolescents using survey methods1,7,9 and our cross-sectional study of 5 year-old children using accelerometry.13 Our findings suggest that the everyday The Journal of Pediatrics • June 2006
14.6
3.0
14.3
2.9
Trochanter (Girls) 2.8
Adjusted BMC (g)
Adjusted BMC (g)
14.0
Hip (Boys) 13.7
13.4
2.7
*
* 2.6
Trochanter (Boys)
*
13.1
*
2.5
*
*
12.8
2.4
Hip (Girls)
1
2
3
4
12.5 1
2
3
4
610.0
23.8
600.0
23.4
590.0
Adjusted BMC (g)
Adjusted BMC (g)
23.0
22.6
Spine (Boys) 22.2
Whole Body (Boys)
580.0
* 570.0
Whole Body (Girls)
* 560.0
21.8
*
550.0
Spine (Girls) 21.4 1
2
3
4 540.0 1
2
3
4
Figure 3. Sex-specific least squares means for adjusted follow-up BMC for hip, trochanter, spine and whole body by total physical activity group. Followup BMC adjusted for Baseline BMC, Follow-up Weight, Follow-up Height, and Percent Height Change per Year of Age. Key: 1 ⫽ low baseline and low follow-up physical total activity groups, 2 ⫽ high baseline and low follow-up, 3 ⫽ low baseline and high follow-up, 4 ⫽ high baseline and high follow-up. * P ⬎ .05 difference from group 4.
levels of activity provide osteogenic advantages to young children. Laboratory and epidemiologic studies have clearly shown that physical activity has a site-specific influence on bone.23-25 In our study, the influence of habitual physical activity on bone accretion appeared greatest at the trochanter sub-region of the hip. We observed a 13% difference in mean adjusted trochanteric BMC between children maintaining higher levels of total physical activity during the 3-year study interval when compared to those maintaining lower levels of physical activity. The magnitude of difference was not seen at other skeletal sites. This finding suggests that higher levels of physical activity have an important remodeling effect at the direct location of muscle attachment26 since muscles used for dynamic physical activity, such as jumping and running, are attached at the trochanter. These muscles work to counter the bending moments produced at the femoral neck during loading. In addition, the trochanter contains approximately 50% Physical Activity Augments Bone Mineral Accrual In Young Children: The Iowa Bone Development Study
trabecular and 50% cortical bone making it the least dense, but most metabolically active, site of the hip and therefore responsive to loading effects.27 In an 8-month intervention study of 7- to 10-year-old boys and girls, McKay et al26 showed that targeted exercise increases trochanteric aBMD but not the femoral neck, (total) hip, spine, or whole body aBMD. In the study of McKay et al,26 the absolute percent change in trochanteric aBMD was 4.4% for the exercise intervention group. In a 9-month intervention study of adolescent girls (mean age 14 years), Witzke and Snow28 reported greater trochanteric BMC for the intervention group when compared with control subjects but no significant differences for the femoral neck, femoral shaft, spine, or whole body BMC. The absolute percent increase in trochanteric BMC was 3.9%. In contrast, in a 20-month intervention study of 8to 12-year-old boys, MacKelvie et al29 reported significant differences for femoral neck BMC when compared with control subjects but not trochanter, spine, or whole body BMC. 797
We are not sure why maintaining higher levels of physical activity was predictive of higher levels of adjusted hip BMC in boys but not girls. The answer may be as simple as throughout the study period, the boys in our study were more active than the girls. It might also be that during middle childhood, physical activity yields more skeletal benefits for boys than girls or that the large amount of variability in adjusted hip BMC explained by weight in girls obscured the effects of physical activity. The literature suggests that that other lifestyle factors, particularly diet, modify the impact of physical activity to BMC during childhood; therefore, we view our lack of dietary information as a study weakness. For example, using a cross-sectional design, Rowlands et al30 have shown an interactive effect of physical activity and calcium intake in prepubertal children (ages 8-11 years). In this study, whole body BMC was highest in boys and girls when physical activity and calcium were (both) high; however, the simple effects of physical activity on whole body, hip, and femoral neck BMC were seen only in boys.30 The boys were more active than girls and there was a trend for higher levels of calcium intake in boys when compared to girls.30 In addition, pediatric randomized controlled studies by Specker and Binkley31 and Iuliano-Burns et al32 have shown that exercise results in site-specific BMC increases when calcium intake is supplemented. Our finding of higher levels of whole body BMC accrual in children maintaining higher levels of physical activity (when compared with peers who maintained lower levels of physical activity) is encouraging. It suggests an overall benefit of physical activity on children’s skeletal mineralization. This effect may be due to the diverse activity patterns encountered when monitoring habitual physical activity in observational studies. The diversity in movement inherent to children’s everyday activity patterns would result in different loading patterns not expected in targeted loading intervention studies that generally use jumping strategies. For example, in a 27year follow-up study of males (baseline age 13 years), Delvaux et al8 showed that habitual physical activity during adolescence and young adulthood explain 9% of the variability in whole body BMC at adulthood. In the 6-year Saskatchewan Bone Mineral Accrual Study, Bailey et al1 reported that the most active boys and girls accrued approximately 30% more whole body BMC in the 2 years around their growth spurt than less active peers. In contrast, most intervention studies do not show increases in whole body.10,26,28 Limitations of our study include the fact that it is a rural Midwestern convenience sample with minimal representation of minority children. In addition, we did not control for the effects of calcium intake. However, a subset of our cohort (n ⫽ 240) was evaluated for calcium intake at 6 months, 12 months, 3 years, and 5 years using 3-day food and beverage diaries. Mean calcium intake at each of these time points exceeded the recommended adequate intake,33 although intake was not analyzed by sex. Because of limitations of our accelerometry method, it was not possible to determine the exact amount or type of 798
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physical activity needed to significantly increase BMC. For example, total physical activity and active minutes were highly correlated (r ⫽ 0.88); therefore we are unsure which is more important for BMC accrual. The use of a 1-minute epoch to calculate active minutes is an additional weakness because a 1-minute sampling interval would be expected to miss shorter bouts of movement.34 Finally, the accelerometry cut-point method that we used to determine active minutes was calibrated in a laboratory.20,21 Associations between accelerometry movement counts and intensity during free-living activity would be expected to have greater variability; therefore our classification of active minutes on the basis of accelerometry movement count thresholds should be interpreted as indicating a relatively high intensity of movement rather than precise metabolic or mechanical loads. Our findings support the timeliness and critical need for current public health strategies aimed at reducing significant age-related declines in physical activity during late childhood. We thank Ms Barbara Broffitt, Ms Deanna Frei, Ms Joan Welsh-Grabin, Ms Elena Letuchy, Mr Mike Mueller, Ms Heather Pallister, Ms Barbara Simon, Ms Katherine Thomsen, and Ms Marta Tullis for their organizational and data management efforts. Special thanks to the study cohort for their sustained membership.
REFERENCES 1. Bailey DA, McKay HA, Mirwald RL, Crocker PRE, Faulkner RA. A six-year longitudinal study of the relationship of physical activity to bone mineral accrual in growing children: The University of Saskatchewan Bone Mineral Accrual Study. J Bone Miner Res 1999;14:1672-9. 2. Kannus P, Haapaslo H, Sankelo M, Sievanen H, Pasanen M, Heinonen A, et al. Effect of starting age of physical activity on bone mass in the dominant arm of tennis and squash players. Ann Intern Med 1995;123: 27-31. 3. Gustavsson A, Thorsen K, Nordstrom P. A 3-year longitudinal study of the effect of physical activity on the accrual of bone mineral density in healthy adolescent males. Calcified Tissue International 2003;73:108-14. 4. Nurmi-Lawton JA, Baxter-Jones AD, Mirwald RL, Bishop JA, Taylor P, Cooper C, et al. Evidence of sustained skeletal benefits from impactloading exercise in young females: a 3-year longitudinal study. J Bone Miner Res 2004;19:314-22. 5. Khan K, McKay HA, Haapasalo H, Bennell KL, Forwood MR, Kannus P, et al. Does childhood and adolescence provide a unique opportunity for exercise to strengthen the skeleton? J Science Med Sport 2000:3:150-64. 6. Marcus R. Role of exercise in preventing and treating osteoporosis. Rheum Dis Clin North AM 2001;27:131-41. 7. Kemper HC. Skeletal development during childhood and adolescence and the effects of physical activity. Pediatr Exerc Sci 2000;12:198-216. 8. Delvaux K, Lefevre J, Philippaerts R, Dequeker J, Thomis M, Vanreusel B, et al. Bone mass and lifetime physical activity in Flemish males: a 27-year follow-up study. Med Sci Sports Exerc 2001;33:1868-75. 9. Slemenda CW, Miller JZ, Hui SL, Reister TK, Johnston CC Jr. Role of physical activity in the development of skeletal mass in children. J Bone Miner Res 1991;6:1227-33. 10. MacKelvie KJ, McKay HA, Khan K, Crocker PR. A school-based exercise intervention augments bone mineral accrual in early pubertal girls. J Pediatr 2001;139:501-8. 11. Sundberg M, Gardsell P, Johnell O, Karlsson MK, Ornstein E, Sandstedt B, Sernbo I. Peripubertal moderate exercise increase bone mass in boys but not girls: a population-based intervention study. Osteoporosis Int 2001;12:230-8.
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12. Wu X, Yang Y, Zhang H, Yuan L, Luo X, Cao X, Liso E. Gender differences in bone density at different skeletal sites of acquisition with age in Chinese children and adolescents. J Bone Miner Metab 2005;23:253-60. 13. Janz KF, Burns TL, Torner JC, Levy SM, Paulos R, Wiling MC, Warren JJ. Physical activity and bone measures in young children: The Iowa Bone Development Study. Pediatrics 2001;107:1387-93. 14. Specker BL, Schoenau E. Quantitative bone analysis in children: Current methods and recommendations. J Pediatr 2005;146;726-31. 15. Taylor A, Konrad PT, Norman ME, Harcke HT. Total body bone mineral density in young children: influence of head bone mineral density. J Bone Miner Res 1997;12:652-5. 16. Ekelund U, Sjostrom M, Yngve A, Poortvliet E, Nilsson A, Froberg K, et al. Physical activity assessed by activity monitor and doubly labeled water in children. Med Sci Sports Exerc 2001;33:275-81. 17. Fairweather SC, Reilly JJ, Grant S, Whittaker A, Paton JY. Using the Computer Science and Applications (CSA) activity monitor in preschool children. Ped Exerc Sci 1999;11:413-20. 18. Janz KF, Witt JD, Mahoney LT. The stability of children’s physical activity as measured by accelerometry and self-report. Med Sci Sports Exerc 1995;27:1326-32. 19. Janz KF. Validation of the CSA accelerometer for assessing children’s physical activity. Med Sci Sports Exerc 1994;26:369-75. 20. Janz KF, Rao S, Baumann HJ, Schultz JL. Measuring children’s vertical ground reaction forces with accelerometry during walking, running, and jumping: The Iowa Bone Development Study. Pediatr Exerc Sci 2003;15:34-43. 21. Freedson PS, Sirard J, Debold E, Pate R, Dowda M, Trost S, Sallis J. Calibration of the Computer Science and Applications, Inc. (CSA) accelerometer. Med Sci Sports Exerc 1997;29:S45 [abstract]. 22. Kohl HW, Fulton JE, Caspersen C. Assessment of physical activity among children and adolescents: a review and synthesis. Prevent Med 2000;31:S54-S77. 23. Petit, MA., McKay HA, MacKelvie KJ, Heinonen A, Khan KM, Beck TJ. A randomized school-based jumping intervention confers site and ma-
Physical Activity Augments Bone Mineral Accrual In Young Children: The Iowa Bone Development Study
turity-specific benefits on bone structural properties in girls: a hip structural analysis study. J Bone Miner Res 2002;17:363-72. 24. Haapasalo, H., H. Sievanen, P. Kannus, A. Heinonen, P. Oja, I. Vuori. Dimensions and estimated mechanical characteristics of the humerus after long-term tennis loading. J Bone Minera Res 1996:11:864-72. 25. Umemura Y, Ishiko T, Yamauchi T, Kurono M, Mashiko S. Five jumps per day increase bone mass and breaking force in rats. J Bone Miner Res 1997;12:9:1480-5. 26. McKay HA, Petit MA, Schultz RW, Prior JC, Barr SI, Khan KM. Augmented trochanteric bone mineral density after modified physical education classes: a randomized school-based exercise intervention study in prepubescent and early pubescent children. J Peds 2000;136:156-62. 27. Khan, KM, McKay HA, Kannus P, Bailey D, Wark J, Bennell K. Physical activity and bone health. Champaign, Ill: Human Kinetics, 2001. 28. Witzke KA, Snow CM. Effects of plyometric jump training on bone mass in adolescent girls. Med Sci Sports Exerc 2000;32:1051-7. 29. MacKelvie KJ, Petit MA, Khan KM, Beck TJ, McKay HA. Bone mass and structure are enhanced following a 2-year randomized controlled trial of exercise in prepubertal boys. Bone 2004;34:755-64. 30. Rowlands AV, Ingledew DK, Powell SM, Eston R. Interactive effects of habitual physical activity and calcium intake on bone density in boys and girls. J Appl Physiol 2004;97:1203-8. 31. Specker B, Binkley T. Randomized trial of physical activity and calcium supplementation on bone mineral content in 3- to 5-year-old children. J Bone Miner Res 2003;18:885-92. 32. Iuliano-Burns S, Saxon L, Naughton G, Gibbons K, Bass SL. Regional specificity of exercise and calcium during skeletal growth in girls: a randomized controlled trial. J Bone Miner Res 2003;18:152-62. 33. Marshall TA, Eichenberger Gilmore JM, Broffitt B, Levy SM, Stumbo PJ. Relative validation of a beverage frequency questionnaire in children ages 6 months through 5 years using 3-day food and beverage diaries. J Am Diet Assoc 2003;103:714-20. 34. Welk GJ, Corbin CB, Dale D. Measurement issues in the assessment of physical activity in children. Research Quarterly for Exercise and Sport 2000;71:59-73.
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Objectives This 3-year follow-up study examined associations between physical activity and bone mineral content (BMC) and whether physical activity augments BMC accrual.
Study design Participants were 370 children (mean age baseline 5.3 years, follow-up 8.6 years). Physical activity was measured using 4-day accelerometry. BMC was measured using dual energy x-ray absorptiometry.
Results After adjustment for baseline BMC, age, and body size, mean physical activity predicted follow-up BMC at the hip, trochanter, spine, and whole body in boys and at the trochanter and whole body in girls. The variability in BMC explained by physical activity was modest (1% to 2%). However, based on a general linear model with adjustment for baseline BMC and body size, children who maintained high levels of physical activity accrued, on average, 14% more trochanteric BMC and 5% more whole-body BMC relative to peers maintaining low levels of physical activity. Conclusions This study suggests that maintaining high levels of everyday physical activity contributes to increases in BMC in young children, particularly at the trochanter. (J Pediatr 2006;148:793-9)
he greatest adaptive response of bone to physical activity appears to occur during childhood and adolescence.1,2 However, much of the evidence for the osteogenic effect of physical activity on bone development comes from observational studies of athletes or from targeted intervention studies.3-6 This is problematic because studies of athletes may be confounded by selection biases and reflect activity levels that would be unrealistic for many children. Musculoskeletal characteristics of athletic children, which also reflect the influence of genetic factors, are likely to be different from peers, even before training.6 Targeted intervention studies, although critical for determining cause and effect relations, are of limited value for understanding the natural history effects of physical activity on bone development including the time order of important relationships and sequencing of events. Therefore, in addition to research on athletes and intervention studies, longitudinal observational studies of normal, healthy children are needed to describe the cumulative effect of physical activity on bone acquisition and whether it is possible to increase bone or improve bone strength through higher levels of habitual physical activity.7 From a 6-year follow-up of 103 boys and girls (baseline age ranging from 8 to 15 years), Bailey et al1 observed that physically active boys achieved, on average, 9% more whole-body peak bone mineral content (BMC) than inactive boys while physically active girls had 17% more whole-body peak BMC than inactive girls. Other longitudinal studies of physical activity and bone accrual have also shown a positive influence of physical activity on bone during childhood and adolescence.8,9 However, controversy exists concerning the influence of sex on response of bone to physical activity and when the skeleton is most adaptable to the From the Departments of Health and Sport effects of physical activity.10-12 Studies, Preventive and Community DenWe have previously reported baseline associations between physical activity and tistry, Public Health Genetics, Epidemiology, and Pediatrics, The University of Iowa, BMC in a cohort of Midwestern children (179 boys and 189 girls, age ranging from 4 to Iowa City, Iowa. 13 6 years). We now report the 3-year follow-up associations specifically; we examine the Supported by grants from the National Inhypothesis that habitual levels of physical activity during middle childhood are predictive stitutes of Health RO1-DE12101, R01DE09551 and MO1-RR00059. of augmented BMC accrual. BMC reflects the absolute amount of mineral as hydroxySubmitted for publication Oct 2, 2005; last apatite within the selected bone. When adjusted for body size, BMC provides an revision received Nov 29, 2005; accepted important marker of skeletal mineralization and, unlike, areal bone mineral density Jan 30, 2006. Reprint requests: Kathleen F. Janz, EdD, De(aBMD) measures, it is not artificially inflated by bone size.14
T
aBMD Active minutes BMC
Areal bone mineral density (g/cm2) Daily frequency of accelerometry movement counts per minute ⱖ3000 Bone mineral content (g)
Total physical activity
Sum of total movement counts per day divided by total time of measurement (min) per day
partment of Health and Sport Studies, 102 FH, University of Iowa, Iowa City, IA 52242. E-mail: [email protected]. 0022-3476/$ - see front matter Copyright © 2006 Elsevier Inc. All rights reserved. 10.1016/j.jpeds.2006.01.045
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METHODS Study population Children were volunteers participating in the Iowa Bone Development Study, a longitudinal study of a cohort recruited immediately postpartum from 8 Iowa hospitals between 1992 and 1995. Of the 470 children in the original Iowa Bone Development Study cohort, 370 children completed baseline and follow-up physical activity and bone assessments (171 boys and 199 girls, mean age 5.3 years at baseline and 8.6 years at follow-up). Almost all (93%) of the cohort were non-Hispanic white. The study was approved by The University of Iowa Institutional Review Board (Human Subjects). Written informed consent was provided by the parents of the children. Skeletal bone measures Using a Hologic 2000 dual-energy x-ray bone absorptiometer (Hologic, Waltham, Mass), whole body, lumbar spine, and left hip scans were conducted in the University of Iowa General Clinical Research Center with software version 7.20. BMC (g) derived from these scans was the primary outcome variable. The pencil beam mode was used to scan the hip and the greater trochanteric sub region of the hip. (Because of concerns about reproducibility, we did not analyze the femoral neck sub region of the hip.) The whole body and anteroposterior view of the lumbar spine were scanned by use of fan-beam geometry with a multi-detector system. Previous research suggests that skull size confounds whole body bone data in young children. Therefore all whole body results presented in this study represent BMC excluding the skull.15 To minimize operator-related variability, all measurements were conducted on the same machine by 1 of 2 experienced, certified technicians. Quality control scans were performed daily using the Hologic phantom with the coefficient of variation for BMC measurements ⬍1%. Accelerometry-determined measures of physical activity Physical activity was assessed at baseline and follow-up using the Actigraph accelerometer (model 7164, Fort Walton Beach, Fla). Validation studies examining this accelerometer and the construction of summary variables for various characteristics of physical activity indicate that the Actigraph accelerometer is valid and reliable for monitoring activity in children in field settings.16-19 The accelerometer was set at 1-minute epochs and positioned to directly measure the acceleration of the displacement of the hip, making it particularly sensitive to monitoring weight-bearing movement. Children were asked to wear the accelerometers all daytime hours during 1 of the autumn months for 4 consecutive days. To be included in the data analysis, children had to wear the accelerometer at least 8 hours per day and at least 3 days. With the exception of 8 children, all participants wore the monitor at least 1 weekend day. 794
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From the accelerometry output we constructed 2 summary variables total physical activity and active minutes. These summary variables were calculated for each day and then averaged across days. Total physical activity was calculated by summing the total movement counts per day (raw data output) and dividing by total time of measurement (min) per day. Active minutes represents the daily frequency of accelerometry movement count per minute ⱖ 3000. During steady-state ambulation (brisk walking), this 3000 movement counts per minute cut-point is approximately equivalent to ground reaction forces of 1.6 times body weight in young children.20 It is also the approximate cut-point for vigorous activity (6 metabolic equivalent or METs) using the equation of Freedson et al.21
Body size measures At baseline and follow-up, trained General Clinical Research Center nurses measured the children’s weight (kg) and height (cm) using a Harpenden stadiometer (Holtain, United Kingdom) and a Healthometer physician’s scale (Continental, Bridgeview, Ill). Children were measured while wearing indoor clothes, but without shoes. Statistical analysis Sex-specific analyses were conducted to examine the distributional properties of the variables. Age, height, weight, BMC, and physical activity differences between boys and girls were tested with a 1-factor analysis of variance model, and sex-specific differences between baseline and follow-up values were tested using a 1-factor repeated measures analysis of variance model. The associations between baseline and follow-up measures were examined using Spearman rank-order correlation coefficients. Cross-sectional multiple linear regression models were constructed with follow-up BMC measures used as the dependent variables and total physical activity and active minutes as primary predictors. Covariates (age, weight, and height) were entered in a stepwise fashion. To examine longitudinal relationships, the models were refit for follow-up BMC with the additional covariates baseline BMC, change in height per year of age, follow-up height, and follow-up weight. Mean total physical activity and active minutes (average of baseline and follow-up) served as the primary predictor variables. Possible outlier observations were identified and their influence on fitted model parameters was assessed using regression diagnostic approaches. Final multiple regression models included all variables with associated P ⬍ .05. A general linear model was fit to compare mean differences in BMC accrual among 4 physical activity groups, adjusted for baseline BMC, change in height per year of age, follow-up height, and follow-up weight. Pairwise comparisons among the 4 least squares BMC means were made using the Bonferroni correction with an overall significance level of P ⬍ 0.05. Group 1 included those children ⬍ 50th percentile (least active for total physical activity) at baseline and followup. Group 2 consisted of those children who were ⱖ 50th The Journal of Pediatrics • June 2006
Table. Description of subjects and associations between baseline and follow-up measures (n ⴝ 171 boys and 199 girls) Baseline Age (yr) Boys Girls Height (cm) Boys Girls Weight (kg) Boys Girls Hip BMC (g) Boys Girls Trochanter BMC (g) Boys Girls Spine BMC (g) Boys Girls Whole Body BMC (g) Boys Girls Total Activity (ct/min) Boys Girls Active Minutes (min) Boys Girls
Mean (SD) 5.21 (0.42)* 5.30 (0.42) 111.76 (5.68) 111.22 (5.60) 20.36 (3.58) 20.11 (3.88) 7.27 (1.62) 6.96 (1.53) 1.27 (0.41)* 1.38 (0.46) 14.56 (2.50) 14.06 (2.64) 248.68 (76.57) 250.54 (80.95) 783.58 (162.88)* 714.79 (159.48) 31.50 (15.94)* 24.13 (12.80)
Follow-up Age (yr) Boys Girls Height (cm) Boys Girls Weight (kg) Boys Girls Hip BMC (g) Boys Girls Trochanter BMC (g) Boys Girls Spine BMC (g) Boys Girls Whole Body BMC (g) Boys Girls Total Activity (ct/min) Boys Girls Active Minutes (min) Boys Girls
Mean (SD)
r
8.62 (0.57) 8.66 (0.57)
0.29 0.30
133.90 (7.16)* 132.42 (6.80)
0.80 0.78
32.65 (9.72) 31.79 (8.72)
0.81 0.70
13.52 (3.32)* 12.81 (2.99)
0.71 0.77
2.72 (0.83) 2.71 (0.85)
0.68 0.57
22.73 (4.31) 21.87 (4.39)
0.81 0.57
582.58 (183.08) 562.18 (167.36)
0.82 0.82
733.92 (196.21)* 622.82 (164.15)
0.33 0.36
39.70 (21.81)* 24.83 (13.24)
0.40 0.40
Due to missing data: n ⫽ 169 boys baseline whole body BMC, 167 boys follow-up whole body BMC, 170 boys follow-up hip, 170 boys follow-up trochanter and 198 girls follow-up whole body BMC. Total Activity, Accelerometry-determined number of movement counts/day divided by the number of monitored minutes per day; r, Spearman correlation coefficients. *Boys significantly different than girls (P ⬍ .05). Baseline significantly different than follow-up (p ⬍ 0.05) for all measures except active minutes in girls (P ⬎ .05).
RESULTS
presented in the Table. The highest tracking correlation coefficients were for height and whole body BMC (r ⫽ 0.78 to 0.82). Tracking correlation coefficients were moderate to high for site-specific BMC (hip, trochanter, spine), with some divergence between boys and girls for spine BMC (r ⫽ 0.81 boys and 0.57 girls). physical activity was moderately stable between baseline and follow-up (r ⫽ 0.33 to 0.40).
Descriptive analyses At baseline, boys were more physically active, slightly younger, and had less trochanteric BMC than girls (Table). At follow-up, boys had significantly greater hip BMC, were taller, and were more active than girls. Between baseline and follow-up, height, weight, and all BMC measures increased in boys and girls. Total activity decreased in boys and girls while active minutes increased in boys but not girls. The mean time between baseline and follow-up scans was 3.4 (SD 0.6) years. The contribution of skull BMC to whole body BMC in our cohort decreased from a mean of 51% at baseline to 35% at follow-up with an approximate decrease of 4.4% per year (range 1.7 to 7.8%) (data not shown). Spearman rank-order correlation coefficients representing the stability of measures across the 3-year time period are
Multiple linear regression analysis Results from the follow-up cross-sectional stepwise multiple linear regression analyses are presented in Figure 1. Follow-up age, height, weight, and physical activity were considered for inclusion in each model but only those variables that were statistically significant (P ⬍ .05) were retained in the final models. As expected, height and weight explained much of the variability in follow-up BMC, whereas age was generally insignificant. At follow-up in boys, physical activity entered the models for hip BMC (active minutes) and trochanteric BMC (total activity), explaining 3% of the variability. In girls, physical activity entered the model explaining 1% of the variability for the trochanter (Figure 1). Results from the longitudinal stepwise multiple linear regression analyses
percentile (most active for total physical activity) at baseline but ⬍ 50th percentile at follow-up. Group 3 included those children ⬍ 50th percentile at baseline but ⱖ 50th percentile at follow-up. Group 4 included those children ⱖ 50th percentile at baseline and follow-up.
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Figure 1. Follow-up BMC, g from stepwise linear regression. Black bars ⫽ active minutes (min); striped bars ⫽ total activity (ct/min); gray bars ⫽ height (cm); stippled bars ⫽ weight (kg); crossed-hatch bars ⫽ age (yr). Note: % ⫽ R2. Only variables p ⬍ 0.05 retained in final models.
are presented in Figure 2. In these models, the dependent variables were hip, trochanter, spine, and whole-body BMC at follow-up. Covariates were baseline BMC, percent change in height per year, follow-up height, and follow-up weight. With 1 exception (girl’s trochanter), baseline BMC and follow-up weight explained much of the variability in follow-up BMC. Mean physical activity entered as significant in all models except follow-up hip and spine in girls. Its effect was small, explaining only 1% to 2% of the variability in follow-up BMC.1.
Physical activity group analysis Figure 3 presents results from a general linear model fitted to compare mean differences in BMC accrual among the 4 physical activity groups, adjusted for baseline BMC, change in height per year of age, follow-up height, and follow-up weight. The 4 physical activity groups were constructed to characterize the accumulation and pattern of physical activity levels during the 3-year study interval. Using a sex-specific median split of total physical activity at baseline and follow-up, group 1 included those children ⬍50th percentile (least active for total physical activity) at baseline and follow-up, group 2 were children ⱖ50th percentile (most active for total physical activity) at baseline but ⬍50th percentile at follow-up, group 3 were children ⬍50th percentile at baseline but ⱖ50th percentile at follow-up and group 4 were children ⱖ50th percentile at baseline and follow-up. Cell sizes for the physical activity groups were as follows: 47 boys and 59 girls (group 1), 38 boys and 40 girls (group 2), 38 boys and 40 girls (group 3), and 48 boys and 60 girls (group 4). The median split for total physical activity for boys was 761 ct/min at baseline and 722 ct/min at follow-up. For girls, the median split was 703 ct/min at baseline and 605 ct/min at follow-up. Sixty percent of the boys and 56% of the girls 796
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Figure 2. Follow-up BMC, g from stepwise linear regression with adjustment for baseline BMC. Black bars ⫽ mean active minutes (min); striped bars ⫽ mean total activity (ct/min); light gray bars ⫽ follow-up height (cm); dark gray bars ⫽ follow-up weight; white bars ⫽ percent change height/yr age (cm/yr); stippled white bars ⫽ baseline BMC (g). Note: % ⫽ R2. Only variables p ⬍ 0.05 retained in final models.
maintained their median split grouping at both baseline and follow-up. Statistically significant (P ⬍ .05) differences in adjusted follow-up BMC were found between group 4 (high activity baseline and follow-up) and group 1 (low activity baseline and follow-up) for the trochanter and whole body in both boys and girls and for the hip in boys. Pairwise comparisons indicated a 14.3% (boys) and 12.8% (girls) greater mean trochanteric BMC for group 4 when compared with group 1. Adjusted mean whole body BMC for group 4 was 5.2% (boys) and 4.1% (girls) greater than group 1. For boys, adjusted mean hip BMC for group 4 was 11% greater when compared with group 1. Results were similar when the active minutes physical activity measure was used to construct the comparison groups (data not shown).
DISCUSSION Longitudinal studies have the potential to define growth-related changes in BMC and may provide insight to important contributors of BMC accrual, as well as the prediction of future bone health. This longitudinal study used objective monitoring to examine the effects of habitual physical activity on bone accretion in young, non-athletic children because children under the age of 11 are generally incapable of accurately reporting their physical activity patterns and parents are poor proxy reporters, particularly of their children’s physical activity intensity.22 In this study, using accelerometry-determined physical activity, we have shown that physical activity contributes to increases in BMC for both boys and girls. This finding is consistent with previous longitudinal studies of older children and adolescents using survey methods1,7,9 and our cross-sectional study of 5 year-old children using accelerometry.13 Our findings suggest that the everyday The Journal of Pediatrics • June 2006
14.6
3.0
14.3
2.9
Trochanter (Girls) 2.8
Adjusted BMC (g)
Adjusted BMC (g)
14.0
Hip (Boys) 13.7
13.4
2.7
*
* 2.6
Trochanter (Boys)
*
13.1
*
2.5
*
*
12.8
2.4
Hip (Girls)
1
2
3
4
12.5 1
2
3
4
610.0
23.8
600.0
23.4
590.0
Adjusted BMC (g)
Adjusted BMC (g)
23.0
22.6
Spine (Boys) 22.2
Whole Body (Boys)
580.0
* 570.0
Whole Body (Girls)
* 560.0
21.8
*
550.0
Spine (Girls) 21.4 1
2
3
4 540.0 1
2
3
4
Figure 3. Sex-specific least squares means for adjusted follow-up BMC for hip, trochanter, spine and whole body by total physical activity group. Followup BMC adjusted for Baseline BMC, Follow-up Weight, Follow-up Height, and Percent Height Change per Year of Age. Key: 1 ⫽ low baseline and low follow-up physical total activity groups, 2 ⫽ high baseline and low follow-up, 3 ⫽ low baseline and high follow-up, 4 ⫽ high baseline and high follow-up. * P ⬎ .05 difference from group 4.
levels of activity provide osteogenic advantages to young children. Laboratory and epidemiologic studies have clearly shown that physical activity has a site-specific influence on bone.23-25 In our study, the influence of habitual physical activity on bone accretion appeared greatest at the trochanter sub-region of the hip. We observed a 13% difference in mean adjusted trochanteric BMC between children maintaining higher levels of total physical activity during the 3-year study interval when compared to those maintaining lower levels of physical activity. The magnitude of difference was not seen at other skeletal sites. This finding suggests that higher levels of physical activity have an important remodeling effect at the direct location of muscle attachment26 since muscles used for dynamic physical activity, such as jumping and running, are attached at the trochanter. These muscles work to counter the bending moments produced at the femoral neck during loading. In addition, the trochanter contains approximately 50% Physical Activity Augments Bone Mineral Accrual In Young Children: The Iowa Bone Development Study
trabecular and 50% cortical bone making it the least dense, but most metabolically active, site of the hip and therefore responsive to loading effects.27 In an 8-month intervention study of 7- to 10-year-old boys and girls, McKay et al26 showed that targeted exercise increases trochanteric aBMD but not the femoral neck, (total) hip, spine, or whole body aBMD. In the study of McKay et al,26 the absolute percent change in trochanteric aBMD was 4.4% for the exercise intervention group. In a 9-month intervention study of adolescent girls (mean age 14 years), Witzke and Snow28 reported greater trochanteric BMC for the intervention group when compared with control subjects but no significant differences for the femoral neck, femoral shaft, spine, or whole body BMC. The absolute percent increase in trochanteric BMC was 3.9%. In contrast, in a 20-month intervention study of 8to 12-year-old boys, MacKelvie et al29 reported significant differences for femoral neck BMC when compared with control subjects but not trochanter, spine, or whole body BMC. 797
We are not sure why maintaining higher levels of physical activity was predictive of higher levels of adjusted hip BMC in boys but not girls. The answer may be as simple as throughout the study period, the boys in our study were more active than the girls. It might also be that during middle childhood, physical activity yields more skeletal benefits for boys than girls or that the large amount of variability in adjusted hip BMC explained by weight in girls obscured the effects of physical activity. The literature suggests that that other lifestyle factors, particularly diet, modify the impact of physical activity to BMC during childhood; therefore, we view our lack of dietary information as a study weakness. For example, using a cross-sectional design, Rowlands et al30 have shown an interactive effect of physical activity and calcium intake in prepubertal children (ages 8-11 years). In this study, whole body BMC was highest in boys and girls when physical activity and calcium were (both) high; however, the simple effects of physical activity on whole body, hip, and femoral neck BMC were seen only in boys.30 The boys were more active than girls and there was a trend for higher levels of calcium intake in boys when compared to girls.30 In addition, pediatric randomized controlled studies by Specker and Binkley31 and Iuliano-Burns et al32 have shown that exercise results in site-specific BMC increases when calcium intake is supplemented. Our finding of higher levels of whole body BMC accrual in children maintaining higher levels of physical activity (when compared with peers who maintained lower levels of physical activity) is encouraging. It suggests an overall benefit of physical activity on children’s skeletal mineralization. This effect may be due to the diverse activity patterns encountered when monitoring habitual physical activity in observational studies. The diversity in movement inherent to children’s everyday activity patterns would result in different loading patterns not expected in targeted loading intervention studies that generally use jumping strategies. For example, in a 27year follow-up study of males (baseline age 13 years), Delvaux et al8 showed that habitual physical activity during adolescence and young adulthood explain 9% of the variability in whole body BMC at adulthood. In the 6-year Saskatchewan Bone Mineral Accrual Study, Bailey et al1 reported that the most active boys and girls accrued approximately 30% more whole body BMC in the 2 years around their growth spurt than less active peers. In contrast, most intervention studies do not show increases in whole body.10,26,28 Limitations of our study include the fact that it is a rural Midwestern convenience sample with minimal representation of minority children. In addition, we did not control for the effects of calcium intake. However, a subset of our cohort (n ⫽ 240) was evaluated for calcium intake at 6 months, 12 months, 3 years, and 5 years using 3-day food and beverage diaries. Mean calcium intake at each of these time points exceeded the recommended adequate intake,33 although intake was not analyzed by sex. Because of limitations of our accelerometry method, it was not possible to determine the exact amount or type of 798
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physical activity needed to significantly increase BMC. For example, total physical activity and active minutes were highly correlated (r ⫽ 0.88); therefore we are unsure which is more important for BMC accrual. The use of a 1-minute epoch to calculate active minutes is an additional weakness because a 1-minute sampling interval would be expected to miss shorter bouts of movement.34 Finally, the accelerometry cut-point method that we used to determine active minutes was calibrated in a laboratory.20,21 Associations between accelerometry movement counts and intensity during free-living activity would be expected to have greater variability; therefore our classification of active minutes on the basis of accelerometry movement count thresholds should be interpreted as indicating a relatively high intensity of movement rather than precise metabolic or mechanical loads. Our findings support the timeliness and critical need for current public health strategies aimed at reducing significant age-related declines in physical activity during late childhood. We thank Ms Barbara Broffitt, Ms Deanna Frei, Ms Joan Welsh-Grabin, Ms Elena Letuchy, Mr Mike Mueller, Ms Heather Pallister, Ms Barbara Simon, Ms Katherine Thomsen, and Ms Marta Tullis for their organizational and data management efforts. Special thanks to the study cohort for their sustained membership.
REFERENCES 1. Bailey DA, McKay HA, Mirwald RL, Crocker PRE, Faulkner RA. A six-year longitudinal study of the relationship of physical activity to bone mineral accrual in growing children: The University of Saskatchewan Bone Mineral Accrual Study. J Bone Miner Res 1999;14:1672-9. 2. Kannus P, Haapaslo H, Sankelo M, Sievanen H, Pasanen M, Heinonen A, et al. Effect of starting age of physical activity on bone mass in the dominant arm of tennis and squash players. Ann Intern Med 1995;123: 27-31. 3. Gustavsson A, Thorsen K, Nordstrom P. A 3-year longitudinal study of the effect of physical activity on the accrual of bone mineral density in healthy adolescent males. Calcified Tissue International 2003;73:108-14. 4. Nurmi-Lawton JA, Baxter-Jones AD, Mirwald RL, Bishop JA, Taylor P, Cooper C, et al. Evidence of sustained skeletal benefits from impactloading exercise in young females: a 3-year longitudinal study. J Bone Miner Res 2004;19:314-22. 5. Khan K, McKay HA, Haapasalo H, Bennell KL, Forwood MR, Kannus P, et al. Does childhood and adolescence provide a unique opportunity for exercise to strengthen the skeleton? J Science Med Sport 2000:3:150-64. 6. Marcus R. Role of exercise in preventing and treating osteoporosis. Rheum Dis Clin North AM 2001;27:131-41. 7. Kemper HC. Skeletal development during childhood and adolescence and the effects of physical activity. Pediatr Exerc Sci 2000;12:198-216. 8. Delvaux K, Lefevre J, Philippaerts R, Dequeker J, Thomis M, Vanreusel B, et al. Bone mass and lifetime physical activity in Flemish males: a 27-year follow-up study. Med Sci Sports Exerc 2001;33:1868-75. 9. Slemenda CW, Miller JZ, Hui SL, Reister TK, Johnston CC Jr. Role of physical activity in the development of skeletal mass in children. J Bone Miner Res 1991;6:1227-33. 10. MacKelvie KJ, McKay HA, Khan K, Crocker PR. A school-based exercise intervention augments bone mineral accrual in early pubertal girls. J Pediatr 2001;139:501-8. 11. Sundberg M, Gardsell P, Johnell O, Karlsson MK, Ornstein E, Sandstedt B, Sernbo I. Peripubertal moderate exercise increase bone mass in boys but not girls: a population-based intervention study. Osteoporosis Int 2001;12:230-8.
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12. Wu X, Yang Y, Zhang H, Yuan L, Luo X, Cao X, Liso E. Gender differences in bone density at different skeletal sites of acquisition with age in Chinese children and adolescents. J Bone Miner Metab 2005;23:253-60. 13. Janz KF, Burns TL, Torner JC, Levy SM, Paulos R, Wiling MC, Warren JJ. Physical activity and bone measures in young children: The Iowa Bone Development Study. Pediatrics 2001;107:1387-93. 14. Specker BL, Schoenau E. Quantitative bone analysis in children: Current methods and recommendations. J Pediatr 2005;146;726-31. 15. Taylor A, Konrad PT, Norman ME, Harcke HT. Total body bone mineral density in young children: influence of head bone mineral density. J Bone Miner Res 1997;12:652-5. 16. Ekelund U, Sjostrom M, Yngve A, Poortvliet E, Nilsson A, Froberg K, et al. Physical activity assessed by activity monitor and doubly labeled water in children. Med Sci Sports Exerc 2001;33:275-81. 17. Fairweather SC, Reilly JJ, Grant S, Whittaker A, Paton JY. Using the Computer Science and Applications (CSA) activity monitor in preschool children. Ped Exerc Sci 1999;11:413-20. 18. Janz KF, Witt JD, Mahoney LT. The stability of children’s physical activity as measured by accelerometry and self-report. Med Sci Sports Exerc 1995;27:1326-32. 19. Janz KF. Validation of the CSA accelerometer for assessing children’s physical activity. Med Sci Sports Exerc 1994;26:369-75. 20. Janz KF, Rao S, Baumann HJ, Schultz JL. Measuring children’s vertical ground reaction forces with accelerometry during walking, running, and jumping: The Iowa Bone Development Study. Pediatr Exerc Sci 2003;15:34-43. 21. Freedson PS, Sirard J, Debold E, Pate R, Dowda M, Trost S, Sallis J. Calibration of the Computer Science and Applications, Inc. (CSA) accelerometer. Med Sci Sports Exerc 1997;29:S45 [abstract]. 22. Kohl HW, Fulton JE, Caspersen C. Assessment of physical activity among children and adolescents: a review and synthesis. Prevent Med 2000;31:S54-S77. 23. Petit, MA., McKay HA, MacKelvie KJ, Heinonen A, Khan KM, Beck TJ. A randomized school-based jumping intervention confers site and ma-
Physical Activity Augments Bone Mineral Accrual In Young Children: The Iowa Bone Development Study
turity-specific benefits on bone structural properties in girls: a hip structural analysis study. J Bone Miner Res 2002;17:363-72. 24. Haapasalo, H., H. Sievanen, P. Kannus, A. Heinonen, P. Oja, I. Vuori. Dimensions and estimated mechanical characteristics of the humerus after long-term tennis loading. J Bone Minera Res 1996:11:864-72. 25. Umemura Y, Ishiko T, Yamauchi T, Kurono M, Mashiko S. Five jumps per day increase bone mass and breaking force in rats. J Bone Miner Res 1997;12:9:1480-5. 26. McKay HA, Petit MA, Schultz RW, Prior JC, Barr SI, Khan KM. Augmented trochanteric bone mineral density after modified physical education classes: a randomized school-based exercise intervention study in prepubescent and early pubescent children. J Peds 2000;136:156-62. 27. Khan, KM, McKay HA, Kannus P, Bailey D, Wark J, Bennell K. Physical activity and bone health. Champaign, Ill: Human Kinetics, 2001. 28. Witzke KA, Snow CM. Effects of plyometric jump training on bone mass in adolescent girls. Med Sci Sports Exerc 2000;32:1051-7. 29. MacKelvie KJ, Petit MA, Khan KM, Beck TJ, McKay HA. Bone mass and structure are enhanced following a 2-year randomized controlled trial of exercise in prepubertal boys. Bone 2004;34:755-64. 30. Rowlands AV, Ingledew DK, Powell SM, Eston R. Interactive effects of habitual physical activity and calcium intake on bone density in boys and girls. J Appl Physiol 2004;97:1203-8. 31. Specker B, Binkley T. Randomized trial of physical activity and calcium supplementation on bone mineral content in 3- to 5-year-old children. J Bone Miner Res 2003;18:885-92. 32. Iuliano-Burns S, Saxon L, Naughton G, Gibbons K, Bass SL. Regional specificity of exercise and calcium during skeletal growth in girls: a randomized controlled trial. J Bone Miner Res 2003;18:152-62. 33. Marshall TA, Eichenberger Gilmore JM, Broffitt B, Levy SM, Stumbo PJ. Relative validation of a beverage frequency questionnaire in children ages 6 months through 5 years using 3-day food and beverage diaries. J Am Diet Assoc 2003;103:714-20. 34. Welk GJ, Corbin CB, Dale D. Measurement issues in the assessment of physical activity in children. Research Quarterly for Exercise and Sport 2000;71:59-73.
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