Bone mineral density during puberty in Western Canadian children

Bone and Mineral. 19 (1992) 85-96 0169-6009/92/$05.00 0 1992 Elsevier Science Publishers B.V. All rights reserved.

85

BAM 00467

one mineral density during puberty in estern Canadian children

Susan K. Grimstona, Katherine Morrisonb, James A. Harderb and David A. HanleyC ‘Human Pqformance

Laboratory,

bAIberta Children’s Ilospital.

Faculty qf Physical Education,

University of Calgary, Alta., Canada

Calgary, Alta., Canada CDivisivrr of’ Endocrinology

and Metaboii,wn,

Faculty of Medicine, Foothills Hospital and University of Calgary, Calgary, Alla., Canada

(Received 16 September 1991) (Accepted 7 May 1992)

Sumssry To assess the influence of puberty 3vjdits associated changes in body weight and height on bone mineral density (BMD), 1Lmba: spine (L2- L4) and femoral neck BMD were measured in 74 healthy, active children (9-16 years) using dual-photon absorptiometry. Competitive swimmers were recruited to minimize the potential effect variabi;ity in mechanical loading regime may have on bone density of the lumbar spine. Tanner staging was used to ascess stage of puberty. Current dietary calcium intake was assessed by analysis of 6-day dietary records. Significant differences in spinal and femoral neck BMD occurred between early (Tanner 1 and 2) and late stages of puberty (Tanner 4 and 5), P ~0.05. A significant correlation was found between bone density and dietary calcium intake. However stepwise regression analyses demonstrated stage of puberty or body weight were the only factors which significantly affected spinal BMD, accounting for 77% and 68% of the variability respectively; while at the femoral neck, body weight accounted for 52% of the variability. These results demonstrate that when poten”ial interacliog factors arc controlled for through regression analyses, differences in BMD occur mainl) as a function of puberty and the associated gains in body weight.

Key words: Bone mineral density; Children; Puberty; Body weight; Calcium intake -

Introduction

One of the main risk factors identified for development of osteoporotic fracture is insufficient bone mass [l-8]. EXfortsto prevent osteoporotic fracture have thereCorrespondence to: David A. Hanley, M.D., FRCPC, Division Endocrinology and Metabolism, Faculty of Medicine, 3330 Hospital Drive N.W., Calgary, Alberta T2N 4N1, Canada.

86 fore focused on either maintaining existing bone mass in adults, minimizing bone mass loss in the elderly, or augmenting bone mass gains in the young [9-131. In general however, maximizing bone mass accretion during the years leading to skeletal maturity has been considered the best protection against osteoporosis and its related fractures [9,11,13]. A number of cross-sectional studies and the few longitudinal studies of bone mass in children have generally demonstrated an age-related increase in spinal and radial bone mass [W251. Some studies have shown gender-related differences [15-17,21-251 and most studies have shown associations between bone density, and body weight and/or height [14,17-261. Although the relationship between age and bone mass during childhood has been well documented, there is little information regarding the factors involved in augmenting bone mass and thus potential recommendations for increasing adult peak bone mass are not available. Hormonal changes during puberty and the nutritional status of children have been proposed as two important mechanisms for increasing bone mass during childhood [ 15,23,19,27,28]. Stage of puberty has been assessed using Tanner staging [ 17 19,20,26],testosterone concentration [18], and estimates of pubertal stage based on chronological age 1161.Results generally indicate pre-pubertal children to have significantly lower bone density than pubertal adolescents, but there remains considerable biological variability. Potential causes for the variability noted may include differences in physical activity levels and/or in the nutritional status of children studied. There have been few studies of children in which activity profiles have been extensively documented or controlled. Two recent studies used retrospective questionnaires to determine activity levels in children and found associations between BMD and both level of physical activity [29] and the time reported in weight-bearing activities [30]. Further detailed analyses of the role of physical activity during childhood would appear tm ; u Ln u- .,.xportant due to the known influence of mechanical load on the material properties of bone [31]. In addition there is a limited number of studies documenting the dietary calcium intake of the children measured for bone mineral density, and conclusions drawn by authors have been conflicting [14,17,32,33]. Some have reported a positive association between childhood dietary calcium intake and regional bone mass measurements [32,33], while others have found no such association [14,17]. Inconsistent consideration of interacting factors such as height and weight changes with calcium intake may provide some explanation for the conflicting results. A recent intervention stqdy has demonstrated a trend toward a positive influence of dietary calcium intake on bone mass accretion in adolescent females [12].This study was limited to ICyear-old females who had all reached menarche and by implication had advanced at least to the latter stages of pubertal development [27,34-361.Two years of dietary calcium intervention ranging from 270i 637 mgiday indicated a more pronounced increase in bone mass over time in the high calcium supplement group (1637 mg/day) compared to the low calcium

87

supplement group (270 mg/day). Although this paper demonstrated a positive influence of dietary calcium on bone mass in adolescent females, statistical significance to support the observed trend was not achieved. The possible influence of calcium on bone mass as children of both gender progress through the stages of puberty has yet to be adequately addressed. The purpose of the present study was to determine the relationship between bone mass accretion and stage of pubertal development in healthy children, participating in similar activity programs. The potential influence of calcium intake on bone mass acquisition in these children was also considered in the analysis of bone density changes during the formative years of childhood.

Subjects and Methods

Seventy-four healthy, physically active children (32 male and 42 female), aged bet;veen 9 and 16 years of age, participated in the study. Written consent was obt;ij.inedfrom children and their parents, in accordance with a protocol reviewed by t.he University of Calgary Conjoint Medical Ethics Committee. Sixty-seven of the children were recruited from a local swimming club and all had competed successfully on a regular basis at the provincial level. Coaches’ training recorded and childrens’ training logs indicated an average time spent in training of 15 h/ week. The remaining seven children were not involved in competitive swimming but did participate regularly in a variety of physical activities. Exclusion criteria included evidence of any medical problems known to affect bone health (e.g. malabsorptive gastrointestinal disease), chronic use of medications known to affect skeletal metabolism (e.g. glucocorticoid administration for asthma), and weight/height ratio below the 3rd or above the 97th percentile for North American children [37]. Puberty was assessed by Tanner staging during a complete medical examination. Assessment was made of pubic hair growth, breast (female) and genital (male) development as described previously [34-361. Basic anthropometric measurements of height and weight were included in the medical examination. Bone mineral density (BMD) was measured at the lumbar vertebrae (L2-L4) and femoral neck (FN) using dual-photon absorptiometry (BMC-LAB 22a, Novo Diagnostic Systems). Procedures for the measurement of lumbar and femoral neck BMD have been described previously [38]. The accuracy of repeated measures using this technique in our laboratory is 2-3%. Children and parents were given detailed instructions for completing a comprehensive dietary record. Subjects were asked to weigh, measure, de&be and record all ingested items (liquids and foods) over a specified 3-day period (one weekend and two week days). Parents and children returned the completed record to a registered dietitian, who reviewed it and then discussed it with the family for clarification and verification of estimated quantities and preparation of food A further 3 days of diet record keeping were then assigned and completed by each subject. The 6 days of diet records were then coded and analyzed using the

commercially available computer package, Nutritionist III (N-Squared Computing, Oregon). The data base provided had been expanded to include food items typical of the western Canadian diet. Dietary analyses included average daily energy intake (kcal/day), average daily calcium (Ca) intake (mg/day), and average daily intake of calcium derived from primary dairy products (DaCa; mg/day). Due to the potential for total dietary intakes to increase with increasing age and size of the children and the influence this may have on daily calcium intake, a calcium density was calculated for each child. Calcium density was computed and expressed as average daily Ca intake with respect to average daily caloric intake (mg Ca/kcal). Statistical analyses were carried out with the SPSS/PC program. Student’s Itests were used to compare swimmers and non-swimmers, and for comparison of males and females within each Tanner stage. One-way analysis of variance with Tukcy/b post hoc comparisons were conducted to compare variables with respect to Tanner staging uf puberty. Multiple regression analyses were run to establish the predictive power of measured variables for bone density, with consideration given to the effect of collinearity between variables. Statistical significance was concluded for probabilities of P co.05 Results

In our study there were no significant differences between swimmers and the seven non-swimmers for BMD or any other variable measured (data not presented). Since swimmers and non-swimmers were virtually identical for the Table 1

Comparisons between males and females for each stage of puberty (mean f SEM) TWWK~ stuye Gender

BMD L2-L,a (g HA/cm')

BMDFN

Ca density

(gHA/cm')

(mglkcal)

Height (cm)

Weight (kg)

38.3f 1.3 33.6f 2.2

I (~=13) (n=S)

M F

0.55* 0.02 OS8 t_0.05

0.68f 0.02 0.62f 0.02

0.53+ 0.05 0.612 0.05

148.0f 1.6 145.0f 4.2

2 (N= 3) (n--3)

M F

0.57f 0.03 0.641 0.04

0.72k 0.02 0.70* 0.03

0.46f 0.05 0.46f 0.11

148.3f 5.6 42.7f 1.6 147.7f 1.0 38.0f 0.4

3 (tt =3) (n= 8)

M F

0.62+ 0.02 0.63& 0.02

0.73f 0.03 0.65f 0.02

0.55f 0.05 0.60f 0.06

161.1rt 3.5 155.6+ 3.6

4 (~(-4) (n'8)

M F

0.74f 0.05 0.76+ 0.03

0.82a 0.06 0.78f 0.03

0.60_+0.05 0.58+ 0.04

174.8f 4.5' 60.1& 5.3" 158.9+ 2.1 48.4k 2.3

S (a=9)

M

0.83+_0.01

F

0.84f 0.01

0.87+_0.02 0.82a 0.02

0.58+ 0.04 0.57f 0.05

178.8+ I.4 69.24 2.6" 164.2+ 1.7 57.9* 1.4

(n=l8)

a P ~0.05 vs. females of the respective Tannerstage.

43.9f 3.1 40.84 1.7

89

measured variables, non-swim.mers were grouped with swimmers in further analyses. There were no significant differences between males and females for bone mineral density of the spine and femoral neck at any Tanner stage, however there was a trend for females to have greater spinal bone density and lower femoral neck bone density than males (Table 1). Small subject numbers for males in the later stages of puberty and for females in the early stages of puberty reduced the statistical power of these comparisons, which most likely accounted for the lack of statistical significance. However, since no significant differences were noted between males and females for the dependent variable of bone mineral density at any site at any stage of puberty, males and females were combined for comparisons of other variables as a function of puberty (Table 2). Although increasing the statistical power of our analyses, the combination of males and females within each Tanner stage does present a limitation and should be taken into consideration. Table 2 Physical and dietary characteristics of children according to stage of puberty (mean f SEM/[95% CL]) Tanner stage

Variable

1 (n = 18)

2

3

4

5

(n = 6)

(n = 11)

(n = 12)

(n = 27)

Age

(years)

10.6 f 0.2 [lO.l-11.11

11.0 + 0.8 [8.9-13.11

12.1 fr o.4b [I 1.L13.11

13.7 + 0.c [12.9-14.41

14.7 f 0.3” [14.2-15.31

Height

(cm)

146.9 + 1.6 [143.6-150.21

148.0 f 1.6 [143.8-152.21

157.1 f 2.gb [150.9-163.41

164.1 f 3.0’ [157.6-170.71

169.1 f 1.8” [165.4-172.81

Weight

(kg)

37.0 f 1.” [34.4-39.61

40.4 f 1.3 [37. I-43.61

41.6 + 1.5 [38.3-44.9]

52.3 f 2.8’ [46.2-58.31

61.8 f 1.7d [58.3-65.31

Energy (kcaljday)

2209 f 130 [ 1932-24871

2169 f 198 [I 539-27981

2440 f 219 [ 1935-29441

2332 + 120 [2069-25951

2559 + 177 [2 192-29261

Calcium (mg/day)

1228 f 117 [980-14771

1005 * 159 [499-15101

1433 &- 143 [I 105-17621

1350 f 83 [i i68-15321

1485 4 123 [1230-17401

Dairy (mg/day) calcium

910 f 125 [641-l 1791

1035 + 136

[156-8361

[721-13491

936 + 76 [768-l 1031

1077 * 100 [871-12841

Calcium(mg/kcal) density

0.55 f 0.04 [0.47-0.64]

0.46 f 0.05

0.59 f 0.05

[0.30-0.61]

[0.49-0.70]

0.58 f 0.03 [0.52-0.64]

0.58 f 0.03 (0.51-0.65]

’ P 60.05 vs Tanner

I, 2, 3.

b P
1.

’ P c 0.05 vs Tanner

1, 2.

d P co.05 vs Tanner

1, 2, 3, 4.

482 + 157

90 Calcium

I

-I, I

1 2

O-

I

Energy

8

,L

800

5

Tanner it age (PH)4 Fig. 1. Average daily energy (kcal/day) and calcium (mg/day) of 74 children as a function of stage of puberty. Mean values with SEM values shown.

Average daily energy intake of all children was considered adequate by Canadian standards, as was average daily calcium intake [39]. There was a progressive trend for increased calcium intake through puberty, that followed a similar trend evidenced for total daily energy intake (Fig. 1). There were no significant differences between males and females in calcium density at any stage of puberty (Table 1). There were significant increases in BMD of both the spine and femoral neck as a function of the stage of puberty (Table 3). Although a significant positive Table 3 Bone mineral density for lumbar spine (Lz-L4) and femoral neck (FN) according to stage of puberty (mean + SEM) Tanner stage

BMD Lz-L4 (8 HA/cm2)

95% CL

BMD FN (g f-Wm2)

95% CL

I (n = 18)

0.56 f 0.01

0.53-0.58

0.66& 0.02

0.62-0.7 ‘,

2 (n = 6)

0.61 f 0.03

0.54-0.68

0.71 f 0.02

0.66-0.75

3 (n = II)

0.63 f 0.02’

0.59-0.67

0.67 f 0.02

0.63-0.72

4 (n = 12)

0.75 f 0.03h

0.69-0.81

0.80 f 0.03d

0.74-0.86

5 (a = 27)

0.84 + O.OP

0.81-0.86

0.84 f O.Olh

0.8 l-n.87

a P -=o.os vs. 1, 2, 3.4. lJP
91

Multiple regression analysis of spinal BMD on anthropometry and stage of puberty: P* = 0.81 Variable

Regression coefficient

P value

Height Tanner stage (PH) Age Weight Constant

-0.002 0.042 0.002 0.006 0.613

0.176 O.i!GO 0.801 0.000 0.001

Table 5 Multiple regression analysis of femoral neck BMD on anthropometry and stage of puberty: r* = 0.55 Variable

Regression coefficient

P value

Height Tanner stage (PH) Age Weight Constant

- 0.0006 0.015 0.002 0.005 0.529

0.722 0.204 0.855 0.013 0.012

correlation existed between calcium intake and both BMD L2-L4 (1.= 0.25; P = 0.028) and BMD FN (r = 0.36; P = 0.002) this relationship was found through regression analyses to be a function of the relationships between calcium intake, body weight and stage of puberty (Tables 4 and 5). Stepwise regression analyses using spinal bone density as the dependent variable indicated stage of puberty to be the strongest predictor, accounting for 77% of the variability (Table 6). No other variable increased the predictive power. When stage of puberty was excluded from the analysis and body weight entered, body weight was found to account for 68% of the variability in spinal bone density (Table 6). Chronological age had the least predictive power at only 55% (Table 6). Fifty-two percent of variability in femoral neck bone density was determined by body weight, with only 47% and 41% determined by stage of puberty or chronological age respectively (Table 6). Dietary factors were not significant determinants of bone density at any site. Stage of puberty, chronoloTable 6 Stepwise regression equations for spinal and femoral neck BMD Regression equation BMD LrL4 = BMD L2-L.4 = BMD FN = BMD FN =

0.0709 (Tanner stage) -I- 0.469 0.0085 (Weight) + 0.254 0.046 (Tanner stage) + 0.601 0.0061 (Weight) + 0.453

r* r* r* 2

= = = =

0.77 0.68 047 0:52

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gical age and/or body weight were not entered in the same analyses due to the collinearity of these variables.

Discussion

In the present study we have focused on the effect of puberty on bone mineral density, Assessment of Tanner stage of puberty provides an index of the end organ response to hormonal changes responsible for growth and development in children. Our results demonstrated the known variability in age of onset and the rate of puberty in normal, healthy, active children. Although the expected increase in chronological age in association with advancing development was noted, there was a noticeable degree of overlap in ages within each Tanner stage (Table 2). Some of the variability noted in previous studies of bone density as a function of chronological age may thus be accounted for by the biological variability in the onset, progression, and ultimate completion of puberty in children [28,34-361. The tendency for a greater femoral neck BMD in males at each Tanner stage was consistent with previous results [40] and could be associated with greater body weight and height of males compared to females (Table 1). Bonjour and associates [40] reported these differences to be significant at Tanner stages 1 and 5, however the number of subjects in each group was not reported. No other study that we are aware of has divided subjects into male and female sub-groups when examining bone mineral density as a function of stage of puberty. In contrast, studies examining differences in bone density as a function of chronological age typically subdivide children on the basis of gender and have shown significant differences in bone density between males and females [ 17,21-26,291.Significant gender differences in bone density would be more likely to occur as a function of chronological age due to the known differences between males and females with respect to the age of onset and rate of progression of puberty [34-361.In order to understand the mechanisms underlying observed increases in bone density during childhood, reducing this known source of variability would appear to be important. When males and females within each Tanner stage were combined, significant differences in both spinal and femoral neck bone density as a function of puberty were found in this group of children (Table 3). In addition, it was noted that for both males and females there was little difference in bone density during the early stages of puberty, but that this was followed by an accelerated increase between Tanner stages 3 and 4 (16% increase) and between stages 4 and 5 (11% increase; Fig. 2). This result was similar to the recent findings of DeSchepper and associates [26] who studied 136 children from Belgium, of whom only 5 1 were assessed for stage of puberty. However, in that study the rate of increase in BMD between Tanner stages 4 and 5 decreased to approximately 4%. Interestingly, at all stages ofpuberty the Belgian children had greater BMD than’the children in the present study 1261.

93

1

2

8

4

5

TannerStage Fig 2. Male and female BMD L&L4 values, showing the average percent increase between Tanner stages 3 and 4 (16%). and between stages 4 and 5 (11%).

DeSchepper and associates [26] also observed a significant correlation between spinal BMD, height and weight but did not attempt to control for these influences on spinal BMD. In the present study we used multiple regression analyses to assess the significant factors associated with bone density accretion. Using this procedure both chronological age and body height were not significant predictors of spinal bone mineral density (Table 4). These results demonstrate the importance of puberty in understanding differences in bone density in children. The great biological variability in chronological age at each stage of puberty in normal, healthy children seen in cross-sectional analyses clearly indicates the limitations of studies of bone density accretion which only examine its variability with respect to age, In addition, weight and height gains in growing children are also a function of the physiological events associated with puberty and the collinearity between these variables should also be considered [28]. Stepwise regression analysis of our data indicated 77% of the variability in spinal BMD cauld be accounted for by stage of puberty, while 68% could be attributed to body weight in this sample of children whose primary physical exercise was swimming (Table 6). The predictive power of stage of puberty or body weight on BMD L2-L4 was high compared to results of previous investigators who have evaluated the predictive power of factors such as chronological age, body weight, and body height [22,24-261.For example Ponder and associates [22], using a second order polynomial function, derived a regression equation in which body weight was the most powerful predictor of spinal bone density accounting for 56% of the variability. Their analysis included white, black and hispanic children and no assessment of stage of puberty was made. The selection of swimmers in the present study was done to limit the potential variability in spinal bone density due to differences in mechanical loading regime Swimming results in large and frequent loads to the spinal column through muscular contraction, Although in excess of non-competitive swimmers, the average time spent swimming was only 2 h/day, resulting in a significant amount

94 of time available for a variety of other activities, including weight-bearing activities. The selection of swimmers may therefore be expected to minimize variability in spinal bone density, but could not be expected to minimize the variability in femoral neck bone density. In our subjects only 53% of the variability in femoral neck bone density in our subjects could be accounted for by body weight (Table 6). Another factor believed potentially responsible for bone density increments, and particularly bone density variability during childhood, has been dietary intake of calcium [14,17,32,33]. Differences in the method used to determine calcium intake may explain part of the variability in results [41-43]. In the majority of previous reports retrospective recall/questionnaire procedures were used to determine dietary intakes. This method, although used extensively, has the limitation of being dependent on t!re recall accuracy of the interviewees. Although 3- to e-day dietary records are not limited by the accuracy of memory of the subjects, they are limited by the honesty of reporting of dietary intakes by the subjects tested and their potential for inducing changes in eating behaviour [41-43]. In general however, daily dietary records are felt to provide one of the most accurate estimates of dietary intake and nutritional quality [43]. In our analysis of dietary calcium in developing children we found a positive correlation between calcium intake and bone density. However, when we controlled for its potential interaction with stage of puberty and body weight with regression analyses we did not find a significant influence of dietary calcium on bone density. This is an important finding in light of the fact that all children in the present study were considered to have an adequate dietary calcium intake, and in 82% of subjects, a dietary calcium intake in excess of the Canadian Recommended Nutrient Intake for children their age [39]. These results suggest that in healthy active children with more than adequate dietary calcium intake, such as seen in the children of the present study, the effect of calcium on bone density may not be appreciable. This possibility is supported in part by studies such as that of Dawson-Hughes and associates [44] who suggested the existence of a ‘threshold’ for dietary calcium, above which calcium intake effects on bone density may not be appreciable. Further studies might consider examining the effect of high versus moderate dietary calcium intakes on bone density in children. We conclude that increments in spinal bone density observed in children aged 9-16 years may be best characterized with respect to the developmental processes associated with puberty, in particular the associated weight gains, Chronological age and body height are not strong predictors of spinal bone density when these factors are controlled for. Minimizing the variability in the type of mechanical loading the spinal column may be exposed to, enhanced the predictive power of stage of puberty and body weight on spinal bone density. Femoral neck bone density was best predicted by body weight in the present study. It is possible however, that controlling for differences in mechanical loading of the femur in future study designs may provide further insight into other important stimuli for bone density accretion at this site.

Acknowledgments Supported by a grant from the Dairy Bureau of Canada. Dr. Grirnston is a Research Associate with the Alberta Centre for Well-Being.

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