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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

Previous studies on the relation between moderate physical activity and bone mass have observed conflicting results. Many of these studies have not dissociated the role of physical activity by age groups and in relation to the period of peak bone mass formation. Our cross-sectional analysis of the baseline data of a longitudinal study of 273 women aged 21–40 attempted to evaluate the role of moderate physical activity on bone mass around the period of peak bone mass attainment. The analyses were carried out separately for the two age groups—21–30 and 31–40—and had also taken into account the effects of age, dietary calcium intake, and lean body mass on bone mineral density (BMD). The total metabolic equivalent values (MET) of leisure time physical activity was based on the MET values for each activity and the reported time spent on each activity in the past year. The results indicated that among the younger group of women, high level of leisure time physical activity was associated with higher bone mass at both the spine and the hip. Additive effects of physical activity and dietary calcium intake on the spine and the hip BMD were observed. Together with age and lean body mass, physical activity and dietary calcium intake accounted for 19% of the variances of bone mineral at the spine and 9–11% at the hip. Among women aged 31–40, presumably after the peak bone mass formation, lean body mass as well as fat mass have independent strong association with BMD. Physical activity was not associated with bone mass in this age group.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

Peak bone mass (PBM), defined as the amount of bony tissue present at the end of the skeletal maturation, is an important predictor of osteoporotic fracture risk in later life.1 Because one standard deviation increase in bone mass may reduce fracture risk by 100%,2 a small increase in PBM may produce quite large changes in subsequent fracture risks. Although genetic factors may determine as much as 80% of PBM attainment, environmental factors such as dietary calcium (Ca) intake and physical activity (PA) during the critical period of PBM formation may be important in the optimization of PBM to its genetic potential.3–5

Studies have generally shown the beneficial effect of dietary Ca intake on bone mass,6,7 but the association between PA and bone mineral density (BMD) has been less clear. Investigators have reported that exercise imposition may increase, decrease, maintain, or have no effect on bone mass.3,8–11 Although vigorous and varied weight-bearing regimens seemed to be more successful in increasing BMD,9 few studies have attempted to investigate the type, duration, and intensity of exercise that are beneficial for bone. The relation between moderate activity levels and bone status is even less clear. Individuals with a history of habitual exercises have greater bone mass than sedentary subjects but little data are available on the effectiveness of mild general exercise in preventing postmenopausal bone loss or enhancing bone density in younger age periods.10,12–14

The aims of this paper are first to describe the pattern of leisure time physical activity in a study population of Chinese women aged 21–40; and second, to relate the overall and types of PA to bone mass. The findings presented are based on the baseline data of a longitudinal study of the determinants of PBM in young Chinese women.7,15

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

Study subjects

Two hundred and ninety-seven healthy Chinese female subjects, aged between 21 and 40 years were included in a longitudinal study of determinants of PBM. The sampling method, exclusion criteria, respondent, and nonrespondent characteristics have been discussed in previous papers reporting the relation between anthropometry measurements as well as dietary calcium intake and bone mass.7,15 Briefly, 565 women aged 21–40 registered with the University Family Medicine Clinic were invited to join the study and 54% agreed to participate. All were premenopausal. Among them, 13 subjects were excluded because of the presence of health conditions which may affect bone mass.

Estimation of physical activity

Leisure-time PA was measured using a modification of the Minnesota Leisure time PA Questionnaire and that used in the study by Nieves et al.16 The reference period used was the previous 12 months. The metabolic equivalents (MET) expended performing each activity were calculated based on the published and adapted values from McArdle et al.17,18 MET is defined as the multiples of resting oxygen consumption and is the recently more preferred estimation of PA than energy expenditure. One MET represents the energy expended in 1 minute by a person seated at rest and is roughly equal to 1 kcal/minute or 1 kcal/kg of body weight/h. The total MET was based on the reported time spent on each activity and the MET values for each activity. A summary measure of the total MET values expended on leisure-time PA per day was also calculated by combining these data for all activities.

Leisure-time PA were classified as either weight-bearing or non–weight-bearing in order to assess the impact of each activity on specific skeletal sites. Weight bearing activities included PA that subjects had to perform on their feet. Activities were further classified into muscle contraction forces on the hip or spine, and striking or load-bearing force on each of the two bone sites according to the classification used by Nieves et al.16 The hip muscle force included PA that involved walking, moving legs against resistance, flexing or extending legs, and pushing off with legs. The striking force measures for the hip and spine included activities that involve striking the foot to the ground with more force than when walking. The muscle contraction measure for the spine included activities that involved muscular rotation of the trunk, stretching or reaching, and twisting motions.

Covariates

Dietary calcium intake

The estimation of dietary Ca intake was based on a quantitative food frequency questionnaire on 73 food items and details have been reported in a previous paper.7 The questionnaire was based on a 1-month intake with the previous 1 year as the frame of reference. Ca density, which is the amount of Ca intake per 100 kcal of energy consumption, was used for adjustment in the age group 31–40 as previous analysis shows a stronger association with BMD than that of Ca intake and BMD.7

Lean body mass, fat mass, and total body weight

Other recent studies have indicated that lean body mass (LBM) is a strong predictor of BMD, especially for the hip, for relatively sedentary and premenopausal women.19–22 In this study, LBM, fat mass, and total body weight were controlled for in the multivariate analysis. LBM was estimated based on the equation specific for women by Boddy et al.23 Fat mass was estimated from the sum of the four skin fold thicknesses using the equation suggested by Durnin and Womersley.24 The correlation between the estimation and direct dual-energy X-ray absorptiometry (DEXA) measurements for fat mass based on 47 subjects was 0.85 (p = 0.000) for LBM and 0.9512 (p = 0.000) for fat mass. Gutin26 in a recent comparison of body composition measurements by different methods also found a strong correlation of fat mass derived from DEXA and skin-fold thickness measurements (r = 0.937).

Outcome variable—Bone mineral density

Bone mass measurements were performed by means of the dual-energy X-ray densitometry (Norland XR 26, Norland Corp., Fort Atkinson, WI, U.S.A.) at two sites: lumbar vertebrae L2–L4, and left hip. Estimation of BMD was made on each lumbar vertebral body, together with the average from L2 to L4. At the femoral site, BMD was calculated on the neck of femur, trochanteric area, and Ward's triangle. A daily calibration of the densitometer was performed before each session, and four to eight women were usually measured in one session. The coefficient of variation ranged from 1% (spine) to 2.5% (neck of femur).

Statistical analysis

As baseline data15 have indicated that PBM seemed to be achieved in the early 30s, analyses were performed separately for subjects aged 21–30 and 31–40 years. The student's t-test was used to test for differences in the characteristics of study subjects and in the BMD between the two broad age groups: 21–30 and 31–40. The Chi-square test or Fisher's exact test was used to compare the differences in percentage distribution of MET values from the various types of PA between the two age groups.

The Mann-Whitney test was used to test for difference in BMD between subjects belonging to the high tertile and the other two tertiles of PA (MET/day) combined. Further comparisons were made between BMD values for subjects belonging to the different combinations of high or low PA/Ca intake categories. Linear multiple regression analysis was used to test for the associations between PA and BMD taking into account the presence of the other covariates (age, LBM, and Ca). The stepwise method was also used with the criteria of entry based on a probability of F-to-enter of 0.05 and a probability of F-to-remove of 0.10. SPSS for Windows statistical software (Release 6.0.1, SPSS Inc., Chicago, IL, U.S.A.) was used in the analyses.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

Table 1 shows the characteristics of the study subjects by the two broad age groups: 21–30 (mean age, 25.6; standard deviation, 2.84) and 31–40 (mean age, 35.3; standard deviation, 2.71). The older women were shorter and slightly heavier with a higher mean body mass index. They also had a higher percentage of body fat and lower LBM values. The older women had a slightly later age of menarche and a higher mean number of pregnancies and live births. There were 34% ever oral contraceptive users in the younger women and 68% in the older women. The mean spine and trochanter BMD values of the older women were significantly higher than that of women aged 21–30. The mean values of Ca intake and PA (MET) were similar among women in both age groups.

Table Table 1. Characteristics of Study Subjects by Two Age Groups
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Table 2 shows the percentage distribution of different types of leisure time PA. All forms of walking accounted for about 80% of PA in both age groups. Younger women had more activities in ball games while older women practiced more of the Chinese traditional form of exercises like Taichi.

Table Table 2. Percentage Distribution of MET Values from the Various Types of PA
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Subjects were categorized into high and low levels of PA with those belonging to the middle and low tertiles grouped into the “low” PA category. There were no significant differences in the reproductive factors between subjects belonging to the high and low levels of PA in both age groups. Figure 1 shows the percentage difference in BMD values between subjects of the two levels of PA (actual mean BMD values shown in Appendix A). Significant differences in BMD values between the two groups of subjects were only observed in the young women. Among them, there were significant or near significant associations between total activities and BMD at all bone sites. A stronger association between weight-bearing activities and BMD than that between non–weight-bearing activities and BMD was observed. A high level of hip muscle PA was also observed to be associated with higher BMD. Although subjects with a higher level of hip force impact activities had higher hip BMDs, the association was statistically nonsignificant, perhaps due to the relatively low proportion of PA related to hip force impact. In older women aged 31–40 years, all sites show a small but negative relationship between BMDs and PA.

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Figure FIG. 1. Percentage difference of BMD comparing subjects belonging to high tertile of PA with those in the other tertiles.

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Figure 2 shows the combined effects of Ca and PA on BMD. Among the younger women, a combination of high Ca and high PA seemed to have an additive effect on the spine as well as the hip BMDs. The difference between the high/high and low/low categories were 9% for the spine and 14.8–17.8% for the hip. In women aged 31–40, those with high level of Ca density had a higher mean value of BMD. PA was not associated with BMDs at both the spine and the hip.

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Figure FIG. 2. Percentage difference in BMD by comparing the different categories of PA (MET/day) and dietary CA (mg/day) with the low PA and low CA intake category. (A) H, high level of PA; L, low level of PA; h, high level of CA intake; l, low level of CA intake. (B) H, high level of PA; L, low level of PA; h, high level of CA density; l, low level of CA density.

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Tables 3a and 3b show the effect of PA (MET) on BMD at various sites after adjusting simultaneously for age, LBM (ln), and Ca intake. For the age group 21–30, age, LBM, and PA were significantly and independently associated with the spine BMD. Age was positively associated with the spine BMD. The four variables accounted for about 19% of the BMD variance. Both Ca and PA were noted to have effects on the BMD at the hip site. The four variables accounted for 9–11% of the BMD variances. However, for the age group 31–40, LBM was the most important independent variable that is strongly associated with the BMDs. Ca density also had a significant association with the spine BMD. Age was observed to have a negative association with BMDs for this age group but the association was only significant at the Ward's triangle.

Table Table 3a. Table 3a. Multiple Linear Regression Model on Simultaneous Effects of Age, Lean Body Mass, Ca,and PA on BMD in Women Age 21–30
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Table Table 3b. Table 3b. Multiple Linear Regression Model on Simultaneous Effects of Age, Lean Body Mass, Ca Density,and PA on BMD in Women Age 31–40
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The inclusion of fat mass (ln) or total body weight (ln) instead of LBM (ln) did not change the associations of PA or Ca/Ca density with BMD in the age group 21–30. Besides the spine BMD, fat mass (ln) was not observed to have a significant association with BMD at other sites. In women aged 31–40, the replacement of LBM (ln) by fat mass (ln) rendered a significant negative association between age and BMD at all sites. The associations of BMD with PA and Ca density remain similar. The use of weight in the model gave essentially similar results observed in Tables 3a and 3b. Similar results were produced with the use of stepwise regression analyses.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

Our study, attempting to investigate the role of PA on BMD in young women, has specifically used the measurement of MET values so as to take into account the differences in body dimensions and the confounding effects of body weight. The analyses were also carried out separately for the two age groups—21–30 and 31–40—since our baseline analysis seemed to indicate that the early 30s is when PBM is achieved in this population.15 We have also taken into account separately the effects of LBM and fat mass.

Our cross-sectional results have indicated differences in association between PA and BMD in the two age groups. Among the younger women, high level of PA was associated with higher BMD values at both the spine and the hip. Other studies of exercise trials in different age groups also seemed to suggest a more positive effect of exercise in women in their 20s26 than in women in their 30s or 40s.27,28 It is possible that there is a stronger response of bone remodeling to mechanical stimuli during the period when bone consolidation is still taking place. Such observations have also been reported by some other investigators.29,30

In our population of women aged 21–30, there also seemed to be a stronger association between PA and BMD at the lumbar spine than at the hip. It has been suggested that the greater surface area of trabecular bone has the potential for greater remodeling activity and may therefore be more sensitive to increased loading than cortical bone.31 A study by Snow-Harter et al.26 has shown that exercise intervention in college women (with a mean age of 20 years) resulted in a significant increase in BMD at the lumbar spine but not at the proximal femur. Kanders et al.32 observed a positive correlation between energy expenditure and lumbar spine BMD in young women. However, a follow-up study of 254 Finn adolescents in the age range of 20–29 years found that exercise over the past 10 years had a significant association with the femoral BMD in women and with both spine and femoral BMD in men.27 The variations in types and intensity of PA may partly explain the differences in the observed associations of PA with BMD at the different sites.

There have been recent attempts to categorize PA into types of activities. In a 15-year longitudinal study among youths in Amsterdam, Welten et al.3 found that weight-bearing activities, which accounted for almost 85% of the total MET values of PA, was an independent factor in the influence of PBM. In our study, weight-bearing activities accounted for over 90% of the total leisure time MET values. Our results indicated that in the younger women, both weight-bearing and hip muscle activities were related to increased spine and hip BMDs. Hip force and spine muscle activities were only modestly related to the hip BMD, perhaps due to their relatively low contribution to total PA. Nieves et al.16 reported high levels of hip muscle, and hip force activities were related to an increase in BMD at the hip. Snow-Harter et al. also reported the relation between muscle strength of the back and BMDs at the spine and femoral neck.26 Thus, both mechanical stimuli through muscle activities and impact loading could have stimulated response in bone formation.

The lack of association between PA and BMD in the older women may be related to the differences in types of activities as well as their post-PBM status. Among the younger women, a significantly higher proportion of the weight-bearing activities was derived from ball games. Such activities would involve a higher loading impact than that from walking and more stationary types of activities. Whelan et al.34 proposed that loading experience, as characterized by a load magnitude and number of cycles, determines the bone density at a bone region. Some recent studies seemed to indicate that a high-load regimen exerts more beneficial effects on BMD than a high repetition low-load regimen.35 Bassey et al.31 observed the better effectiveness of high impact force in increasing BMD than low impact exercises. Robinson et al.23 also found that female gymnasts had higher BMD values compared with the runners. These studies suggested that mechanical forces generated from high impact loading and muscular contraction have more osteogenic effects than low impact but repetitious movements. There have also been suggestions that higher intensity activity may be necessary to result in an increase in BMD after an equilibrium state of stimuli and bone formation has been achieved.9 The moderate level of PA and the mainly low impact but repetitious types of PA in the older women after the cessation of bone accretion may not exert adequate stimuli to result in observed differences in BMD. The decline of LBM and muscle strength and increased body fat with age may also contribute to the nonsignificant role of moderate PA on BMD in the older women.

Many studies have shown the strong association between body weight and BMD.13,36 Both body fat and LBM are related to body weight, but Sowers et al. suggested that high adiposity related to high BMD only when muscle mass was also high.37 Khlosa et al.22 concluded that both LBM and fat mass have important effects on bone mass. The association of fat mass and BMD could be mediated through the increase in the biologically available estrogen from the conversion of adrenal androstenedione to estrone.38 Some recent studies have strongly indicated the positive role of lean mass and muscle strength on bone mass.26 Because LBM partly reflects the history of PA and muscle strength, the strong association between LBM and BMD in the older women could be due to the effect of past history of PA. The disappearance of the negative association of BMD with age when LBM was controlled for could also be due to the decline of LBM with age in the older women. Further studies are required to investigate such a hypothesis.

Few studies on the determinants of bone mass in young women have considered the relative importance of Ca intake and PA. The study by Kanders et al.30 found that bone density was highest in those young women who had a high level of both PA and Ca intake. A recent study by Welton et al. suggested that weight-bearing activities in youth have stronger effects than Ca on PBM in both sexes.3 Multiple linear regression analysis in a recent study showed that body weight and sports activity during adolescence were stronger determinants than diet on female BMD.13 Our study has observed that, among younger women, PA had a stronger association with the spine BMD while Ca seemed to play a stronger role in the hip BMD. A recent meta analysis of studies in postmenopausal women by Specker39 suggested that PA exerts a positive effect on BMD only at Ca intake greater than 1000 mg/day. In our population with habitually low dietary Ca intake,7 only 2.4% (or seven subjects) had Ca intake at that level. Nonetheless, in women aged 21–30, a combination of high Ca as well as high PA showed an additive effect on the spine and on the hip BMDs.

Previous studies on the relation between PA and BMD have observed conflicting results. Many of these studies have not dissociated the analyses by age groups and in relation to the status of PBM formation. Our study attempted to evaluate the role of PA among young women before and after PBM has been achieved and have also attempted to take into account age, dietary Ca intake, and LBM. In the cross-sectional analysis, we have shown that before age 30, PA, probably high impact PA, and dietary Ca intake are associated with higher attainment of PBM. Age also has a significant effect after adjusting for LBM, PA, and dietary Ca in spine BMD formation. However, among women aged 30 and above, presumably after the PBM formation, LBM, probably the results of the cumulative effect of long-term PA, plays a major role in influencing PBM. Although our cross-sectional analysis does not permit interpretation of cause-and-effect association, and women who were more active could already have greater bone density, our study demonstrated independent association between PA and BMD in young women before age 30. LBM and fat mass are strong predictors of BMD in women beyond age 30. Prospective data from this study could provide more valid evidence on the positive effect of PA in maximizing PBM. Moreover, further research into the types, intensity, and duration of PA, taking into account age, nutritional, and body composition factors, are needed to formulate recommendations for PA for the maximization of BMD.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX

This work was supported by grants from the University and Polytechnic Grant Committee, and Sandoz Foundation for Gerontological Research. Special thanks to Dr. Jennifer Kelsey, Chief, Division of Epidemiology, Department of Health Research & Policy of Stanford University School of Medicine, for her valuable comments on the paper. The authors also thank Miss Yuen Kay Fan for her dedication in carrying out the study and Mrs. Angela Fong for preparation of the manuscript.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX
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APPENDIX

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
  9. APPENDIX
Table Appendix A. Mean BMD Values in Groups with High and Low levels of PA (MET/Day)
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