| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Original Studies |
Menzies Center for Population Health Research, Hobart, Tasmania 7000, Australia
Address all correspondence and requests for reprints to: Dr. Graeme Jones, Menzies Center for Population Health Research, GPO Box 252–23, Hobart, Tasmania 7000, Australia. E-mail: g.jones{at}utas.edu.au
 |
Abstract |
|---|
 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
|
Introduction |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
|
Subjects and Methods |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
The 696 subjects who agreed to the in-hospital interview were approached during 1996 to take part in a bone mass study. After 8 yr, we were able, through the use of school lists, to definitely identify 551 of these subjects (or 80%, which is in close agreement to the Australian Bureau of Statistics data on annual outward migration rates from Tasmania of 2.5%). Subjects who provided informed consent to take part underwent an extensive protocol involving measurement of bone mass, anthropometrics, physical activity and fitness, diet, and sunlight exposure. Ethical approval for this study was obtained from the University of Tasmania ethics committee (human experimentation).
Bone mass was assessed using the technique of dual energy x-ray absorptiometry at the total body, lumbar spine, and right femoral neck (Hologic QDR2000 densitometer, Waltham, MA). Bone mass was examined in two separate ways: bone mineral content (BMC) and bone mineral density (BMD). Precision estimates in vivo are not available in our subjects for ethical reasons. The longitudinal coefficient of variation for our machine during 1996 using daily measurements of a spine phantom was 0.54%. Body composition estimates were also available for these subjects.
Height was measured using a stadiometer with the subject in bare feet. Weight was measured using bathroom scales that were calibrated daily using known weights.
Physical activity measures included questionnaire items regarding
sports participation (defined as taking part in organized sport for at
least 3 months of the last 12), lunchtime activities (five-point
ordinal scale), and recess school activities (three-point ordinal
scale). Objective measures included measurement of muscle strength by
dynamometry at three sites: lower limb (involving both legs
simultaneously), upper limb push, and upper limb pull. The child was
instructed in each technique before testing, and each measurement was
performed twice. Repeatability estimates (Cronbach’s 
) were as
follows; lower limb, 0.91; upper limb pull, 0.89; and upper limb push,
0.83. The devices were calibrated by suspending known weights at
regular intervals. Physical work capacity was also assessed by a
bicycle ergometer (26). Subjects were asked to cycle at a constant 60
rpm for 3 min at each of three successively increasing, but submaximal,
workloads. Heart rate was recorded at 1-min intervals at each workload
using an electric heart rate monitor. Work capacity at 170 beats/minute
(PWC170) was then assessed by linear regression with extrapolation of
the line of best fit to a heart rate of 170 beats/min. The PWC170 was
not considered a technically adequate measure unless subjects had spent
a minimum of 2 minutes at each workload, and the pulse rate increased
by at least 5 beats/min with increasing workloads. We have previously
found this measure to correlate well (r = 0.8) with treadmill
assessment of maximal oxygen intake in Australian school
children, aged 9–15 yr (27). Repeatability was not assessed in our
subjects, but has previously been reported as 0.92 (26). The usual diet
in the last 12 months was assessed by food frequency questionnaire
completed by the parent/guardian under supervision by the research
assistant.
Sunlight exposure was assessed by questionnaire relating to the amount of daily exposure during school days, weekends, and on school holidays in both summer and winter. Categories were as follows: 1, less than 2 h; 2, 2–3 h; 3, 3–4 h; and 4, more than 4 h. We have previously validated this measure of exposure against actual exposure with polysulfone badges in teenage children and found them to correlate well in summer (r = 0.62) (28). Parents were also asked to record their child’s sleep duration (time of falling asleep and time of waking).
Statistics
Linear modelling techniques were used to examine the relationship between bone mass and study factors of causal interest. For BMC, the approach taken was initially univariate. Any factor was then adjusted for bone area at that site. Any factor with an area adjusted P < 0.15 was then placed in a multivariate model with height and weight. The exception to this approach was if a factor was associated with BMC at one site and not others; then the univariate coefficient and confidence limits at other sites are reported even if they include the null point. A similar approach was adopted for BMD, except that any univariate association was adjusted for height and weight in step 2 before further modelling. To determine whether associations were mediated by lean body mass, associations were then separately performed by the addition of lean body mass to the model. Physical activity and sunlight variables were examined separately in the modelling procedure. A statistically significant result was regarded as P < 0.05 (two-tailed) or a 95% confidence limit not including the null point. All statistical calculations were carried out using SPSS version 6.1 for Windows.
|
Results |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
documents
study factors and BMD broken down by sex. Males and females were very
similar in terms of age, weight, height, and calcium intake. However,
there were marked differences in other factors. Males had higher levels
of sports participation, sunlight exposure, muscle strength, PWC170,
and lean body mass but lower fat mass compared to females.
|
Associations between the various measures of physical activity and
fitness are reported in Table 2 and Fig. 1. In males, sports participation had the
strongest association with BMD, with those participating in organized
sport having a 4.2% higher BMD at the femoral neck and a 4.3% BMD
higher at the spine. Adjustment for bone free lean body mass negated
these associations, suggesting that they may be mediated by changes in
lean mass. Lower limb muscle strength was also important at the femoral
neck in males. This association, although decreased in magnitude,
persisted after adjustment for both body size and lean body mass,
suggesting a local loading mechanism. A boy in the highest quartile of
muscle strength had a size-adjusted BMD 5.1% higher than those in the
lowest quartile. This association was not present at the spine.
|
|
Lunchtime and playtime activities and hours of sleep were not associated with BMD at any site (data not shown).
Sunlight
Associations between winter sunlight exposure and BMD are
presented in Table 3 and Fig. 2. In males, winter sunlight exposure is
weakly associated with BMD. Compared to those in the lowest category of
sunlight exposure, males in the highest category had 0.001
g/cm2 higher BMD at the femoral neck [95% confidence
interval (CI), -0.039 to 0.041] and 0.020 g/cm2 higher
BMD at the lumbar spine (95% CI, -0.014 to 0.062). This equates to
0.9% at the femoral neck and 4.2% at the spine, respectively.
|
|
and Fig. 2) and when categorized. Compared to
those in the lowest category of sunlight exposure, females in the
highest category had 0.057 g/cm2 higher BMD at the femoral
neck (95% CI, 0.016–0.099) and 0.058 g/cm2 higher BMD at
the lumbar spine (95% CI, 0.014–0.102). This equates to 8.9% at the
femoral neck and 10.5% at the spine, respectively. These associations
persisted after adjustment for body size and composition (Table 3). The
associations were not altered by adjustment for PWC170 (data not
shown). Sunlight exposure during winter weekdays was more weakly associated with BMD in both sexes than weekend exposure. No category of sunlight exposure during the summer was associated with BMD (data not shown).
Body composition and bone mass
In multivariate analysis, BMD was strongly predicted by
bone free lean mass at both sites and weakly by fat mass at the spine
in boys. In contrast, in girls, BMD was strongly predicted by fat mass
at both sites and weakly by bone-free lean mass at the spine (Table 4).
|
Despite being similar in terms of body size, males had
significantly higher BMD at the femoral neck but not at the lumbar
spine (Table 1). The magnitude of the differences at the femoral neck
was reduced by adjustment for body size, composition, physical
activity, and sunlight exposure (adjusted difference, 9.6%; 95% CI,
6.9–14). However, at the lumbar spine, after the same adjustment,
girls had higher BMD than boys (adjusted difference, 3.2%; 95% CI,
0.8–5.6%).
The analysis for BMC was virtually identical to that for BMD, and the associations with total body BMD were very similar to those with femoral neck for physical activity, sunlight exposure, body composition, and gender differences, so the results of these analyses are not presented here.
|
Discussion |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
This study has a number of potential limitations. The children who took part in this study are not representative of Tasmanian children. They were originally selected on the basis of having a higher risk of sudden infant death syndrome (25). As a result, there was a higher proportion of males, premature babies, teenage mothers, and smoking during pregnancy. These findings suggest that this group is of a lower socio-economic status than the Tasmanian population as a whole. According to Mietinen (29), an analytical cohort study to be generalizable to other populations does not have to be representative of the community from which it was selected provided it meets the following key criteria with regard to definition of eligible participants, sample size, and a proper distribution of determinants, modifiers, and confounders. This study fulfills all three criteria. The study population was explicitly defined and is of adequate sample size; furthermore, it has considerable heterogeneity of exposure to factors of causal interest. Furthermore, there was no association between maternal education and household income levels and bone mass in these children, suggesting that this bias may not be of major concern. Overall, these observations would suggest that the exposure-bone mass associations reported in this sample may be generalizable to other prepubertal populations, particularly with regard to physical activity, but less so for sunlight exposure for other reasons (see below).
We found that a variety of physical activity measures were associated with bone mass, particularly at the femoral neck. In boys, sports participation was the most strongly associated at both sites and for lower limb muscle strength at the femoral neck. The association with sports participation appears to be mediated by increases in lean body mass, as adjustment for this negated the association. The association with muscle strength was only partially reduced by such adjustment and suggests an additional role for local biomechanical loading. In contrast, in girls, neither of these two was associated, but physical work capacity was, and this association also persisted after adjustment for body size and lean body mass. This suggest that physical fitness may have an effect on bone mass independent of these factors that may be due to common genetic factors or, alternatively, may be due to physical activity independently leading to both higher bone mass and higher fitness. However, it is widely recognized that the assessment of physical activity in children is difficult (13), and it may be that measurement of fitness is an indirect measure of physical activity in girls that has not been adequately captured by our other measurements. It is also possible that there is a threshold effect with physical activity, by which levels above a certain cut-off point may confer no further benefit. There are some data to support this in our sample, as males in the lowest quartile of PWC170 had BMD identical to females in the highest quartile of PWC170 at the femoral neck, but not at the spine. However, the gender differences between physical activity measures and bone mass that we report here in prepubertal children are both unexpected and largely unexplained at present. The types of sports played by both are similar, so this is not an adequate explanation. The magnitude of the increase in bone mass with physical activity is substantial, with increments ranging from 4–7% (size adjusted). These findings contrast with those of Bass et al. (6), who found differences in the order of 10–15% in gymnasts, but, as stated by the researchers, it is likely that these are close to the maximum attainable, and our reported figures are more likely to be representative of what is possible in normal children. The variations we report indicate the need for further research in prepubertal children and strongly suggest that more objective measures that accurately quantify actual and habitual physical activity, such as pedometers, need to be further developed and validated so that measurement error can be minimized.
A novel finding of this study was an association between the amount of sunlight exposure on winter weekends (but not summer) and bone mass at all sites. The sunlight association is most likely to be through photosynthesis of vitamin D as well as physical activity, as relatively little vitamin D comes from dietary sources in Australia, and dietary supplementation is not considered necessary due to the abundant sunlight. Ambient UV light in the environment depends on many factors, including latitude, elevation, stratospheric ozone, sunspot activity, and atmospheric pollution (30). Furthermore, vitamin D photosynthesis depends on the action of UV radiation on skin and thus can also be affected by subject activity during peak exposure periods, amount of clothing worn, sun angle on skin, skin color, humidity, temperature, wind speed, sunscreens, and sweating (30). Hobart has levels of UV exposure comparable to those of other regions within Australia during summer at 20 minimal erythermal doses. In winter, however, the levels drop markedly to 1.6 minimal erythermal doses (31). Although comparative data exist, it is difficult to directly compare Northern and Southern latitudes. In New Zealand, it has been estimated that UV levels are 13–50% higher than equivalent Northern latitudes due primarily to lower ozone levels (32). This may explain the observation that sunlight intensity in Boston (latitude 42°N) during the winter months is insufficient to lead to photosynthesis of vitamin D (10), whereas our data suggest that 4 h or more of sunlight each day on winter weekends is required in Hobart (latitude 42°S) to attain vitamin D stores that are optimal for bone health. This relationship appears plausible, in that our questionnaire assessment of sun exposure correlates well with actual sun exposure measured by polysulfone badges in teenagers (28). It is possible that this association may be confounded by physical activity as winter organized sport is generally played on the weekend in Tasmania. However, adjustment for lean body mass or PWC170 did not alter the strength of the association. Furthermore, the association was not present for summer exposure, which would also be expected to be confounded, suggesting that this is not the case. The association with sunlight was stronger in girls than in boys. A possible explanation for this is that overall boys had higher levels of sunlight exposure than girls with fewer in the lower exposure categories, suggesting that more boys achieved sufficient exposure for optimal bone mineralization, making it more difficult to show statistically significant results even with the higher number of boys compared to girls. Furthermore, anecdotal evidence would suggest that boys may expose more skin than girls in Tasmania and, thus, may synthesize more vitamin D for the same amount of exposure. We do not have measures of vitamin D stores for these children, but our results indicate the need to directly measure serum 25-hydroxyvitamin D3 in both sexes to validate this finding, as vitamin D supplementation, at least in winter, may be required to achieve optimal bone mineralization in Tasmanian children (and possibly those in higher latitudes in other areas of the world where routine supplementation is not practiced), as the amount of sunlight required closely parallels the average daily sunlight hours, which are 3.9 h in winter compared to 7.4 h in summer (M. Nunez, personal communication). An optimum level of vitamin D remains controversial, but recent studies have suggested that minimum levels of 50–80 nmol/L are required in both adults and children (33, 34), which is well above levels indicative of overt deficiency.
The area of gender differences in bone mass is controversial. Areal bone mass is a two-dimensional approximation of volumetric bone density that is strongly correlated with actual breaking strength of bone (35). It appears likely that a major explanation for the reported gender differences in bone density and fracture thresholds (2) are due to artifactual differences in areal bone mass related to bone size. Although a number of methods have been developed to deal with this bias, including bone mineral apparent density (16) or adjusting for body size in the analysis as we have done, none is free of problems. Although we did not have a direct measure of bone size for ethical reasons, male and female children were virtually identical in terms of height and weight, suggesting that this explanation is unlikely in this case. Recent American studies have reported racial, but not gender, differences in prepubertal children (20). However, this study did not report on hip BMD and found a trend for higher spinal BMD in females, as reported in the present sample. A possible explanation for the gender differences is the observation that male and female children in this study differed markedly in terms of physical activity measures, sunlight exposure, and body composition, all of which were associated with areal bone mass, suggesting that the gender differences documented are not size related, but are related to environmental and/or constitutional differences in the prepubertal years. Variations in physical activity and body composition would appear the most plausible explanations for our observation. The fact that multivariate analysis did not completely remove the gender difference is consistent with residual confounding introduced by measurement error (36) in the assessment of physical activity and sunlight exposure. Better assessment of these factors may negate apparent gender differences.
In conclusion, this study has suggested that physical activity and exposure to sunlight are important in the bone mineralization of prepubertal male and female children. The magnitude of both gender and environmental differences in bone mass in this age group is substantial and suggests that modification at this stage of life may influence peak bone mass and possibly fracture risk in later life. However, these findings need to be confirmed in further studies of a longitudinal nature with the development of more objective measures of exposure, particularly physical activity and vitamin D.
|
Acknowledgments |
|---|
|
Footnotes |
|---|
Received June 1, 1998.
Revised September 3, 1998.
Accepted September 14, 1998.
|
References |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
This article has been cited by other articles:
 |
|
 |
|
  T Dwyer, L Blizzard, B Patterson, A-L Ponsonby, K Martin, S Quinn, M M Sale, S M Richards, R Morley, S Rich, et al. Association between birth weight and adolescent systolic blood pressure in a caucasian birth cohort differs according to skin type, CRH promoter or 11{beta}-HSD2 genotype Arch. Dis. Child., September 1, 2008; 93(9): 760 - 767. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. S. Jones, S. C. Kaste, W. Liu, C. Cheng, W. Yang, K. G. Tantisira, C.-H. Pui, and M. V. Relling CRHR1 Polymorphisms Predict Bone Density in Survivors of Acute Lymphoblastic Leukemia J. Clin. Oncol., June 20, 2008; 26(18): 3031 - 3037. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. F. Holick Vitamin D Deficiency N. Engl. J. Med., July 19, 2007; 357(3): 266 - 281. [Full Text] [PDF]
|
|
|
|
 |
|
 K. Rajakumar, J. D. Fernstrom, J. E. Janosky, and S. L. Greenspan Vitamin D Insufficiency in Preadolescent African-American Children Clinical Pediatrics, October 1, 2005; 44(8): 683 - 692. [Abstract] [PDF]
|
|
|
|
 |
|
 V. Tangpricha, A. Turner, C. Spina, S. Decastro, T. C Chen, and M. F Holick Tanning is associated with optimal vitamin D status (serum 25-hydroxyvitamin D concentration) and higher bone mineral density Am. J. Clinical Nutrition, December 1, 2004; 80(6): 1645 - 1649. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. F Holick Sunlight and vitamin D for bone health and prevention of autoimmune diseases, cancers, and cardiovascular disease Am. J. Clinical Nutrition, December 1, 2004; 80(6): 1678S - 1688S. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Arabi, H. Tamim, M. Nabulsi, J. Maalouf, H. Khalife, M. Choucair, R. Vieth, and G. El-Hajj Fuleihan Sex differences in the effect of body-composition variables on bone mass in healthy children and adolescents Am. J. Clinical Nutrition, November 1, 2004; 80(5): 1428 - 1435. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. P Garnett, W. Hogler, B. Blades, L. A Baur, J. Peat, J. Lee, and C. T Cowell Relation between hormones and body composition, including bone, in prepubertal children Am. J. Clinical Nutrition, October 1, 2004; 80(4): 966 - 972. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Ding, F. Cicuttini, F. Scott, M. Glisson, and G. Jones Sex differences in knee cartilage volume in adults: role of body and bone size, age and physical activity Rheumatology, November 1, 2003; 42(11): 1317 - 1323. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G Jones, K Bennell, and F M Cicuttini Effect of physical activity on cartilage development in healthy kids Br. J. Sports Med., October 1, 2003; 37(5): 382 - 383. [Full Text] [PDF]
|
|
|
|
|
|
M. K. Lehtonen-Veromaa, T. T Mottonen, I. O Nuotio, K. M. Irjala, A. E Leino, and J. S. Viikari Vitamin D and attainment of peak bone mass among peripubertal Finnish girls: a 3-y prospective study Am. J. Clinical Nutrition, December 1, 2002; 76(6): 1446 - 1453. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W. Taha, D. Chin, A. I. Silverberg, L. Lashiker, N. Khateeb, and H. Anhalt Reduced Spinal Bone Mineral Density in Adolescents of an Ultra-Orthodox Jewish Community in Brooklyn Pediatrics, May 1, 2001; 107(5): 79e - 79. [Abstract] [Full Text]
|
|
|
|
|
|
G. Jones, M. D Riley, and S. Whiting Association between urinary potassium, urinary sodium, current diet, and bone density in prepubertal children Am. J. Clinical Nutrition, April 1, 2001; 73(4): 839 - 844. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. E.-H. Fuleihan, M. Nabulsi, M. Choucair, M. Salamoun, C. H. Shahine, A. Kizirian, and R. Tannous Hypovitaminosis D in Healthy Schoolchildren Pediatrics, April 1, 2001; 107(4): e53 - e53. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Endocrinology | Endocrine Reviews | J. Clin. End. & Metab. |
| Molecular Endocrinology | Recent Prog. Horm. Res. | All Endocrine Journals |
