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首页医源资料库在线期刊美国临床营养学杂志2003年77卷第2期

Diet in midpuberty and sedentary activity in prepuberty predict peak bone mass

来源:《美国临床营养学杂志》
摘要:Objective:Weassessedwhetherthereisastageofpubertywhendietarycalciumismorestronglyrelatedtopeakbonemass,asindicatedbyyoungadultbonemass(YABM)。Dietarycalciumandsedentaryactivitydata,gatheredthrough3-dfoodrecordsandself-reportsoftelevision-videoviewingat......

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May-Choo Wang, Patricia B Crawford, Mark Hudes, Marta Van Loan, Kirstin Siemering and Laura K Bachrach

1 From the Department of Nutritional Sciences (M-CW, PBC, MH, and KS) and the School of Public Health (M-CW), University of California, Berkeley; the Western Human Nutrition Research Center, US Department of Agriculture, Davis, CA (MVL); and the Department of Pediatrics, Stanford University School of Medicine, CA (LKB).

2 Presented in part at the 17th International Congress of Nutrition, Vienna, August 27–31, 2001.

3 Supported by NIH (National Institute of Child Health and Human Devlopment) grant R01-HD36590. Longitudinal data were from work supported by grants NO-HC 55023–26 and UO1-HL48941–44 from the National Heart, Lung, and Blood Institute of the NIH.

4 Address reprint requests to M-C Wang, University of California, Berkeley, School of Public Health,140 Warren Hall, Berkeley, CA 94720-7360. E-mail: maywang{at}uclink.berkeley.edu.


ABSTRACT  
Background: An average daily calcium intake of 1300 mg is recommended for North American adolescents aged 9–18 y. However, questions remain about these recommendations.

Objective: We assessed whether there is a stage of puberty when dietary calcium is more strongly related to peak bone mass, as indicated by young adult bone mass (YABM); whether dietary calcium intake > 1000 mg/d in adolescence is associated with higher YABM; and whether race affects any of these associations between dietary calcium and YABM. Secondarily, we evaluated relations between sedentariness and YABM.

Design: In a retrospective cohort study, we recruited 693 black and white women aged 21–24 y who had participated in the 10-y National Heart, Lung, and Blood Institute Growth and Health Study and measured YABM with the use of dual-energy X-ray absorptiometry. Dietary calcium and sedentary activity data, gathered through 3-d food records and self-reports of television-video viewing at 8 annual examinations, were averaged over 3 pubertal stages. Complete data were available from 161 black and 180 white females. Multiple regression, controlling for race, weight, and height, was applied to assess diet and activity relations with YABM.

Results: Dietary calcium was most strongly associated with YABM in midpuberty. Calcium intake > 1000 mg/d was associated with higher YABM, but this association was not significant at all skeletal sites. Race did not affect the observed relations between calcium and YABM. Sedentary activity in prepuberty was inversely associated with YABM.

Conclusions: Interventions should focus on ensuring adequate calcium intake in midpuberty and on minimizing sedentariness in prepuberty.

Key Words: Diet • calcium • physical activity • television viewing • puberty • peak bone mass • adolescents


INTRODUCTION  
Peak bone mass, which is attained by the third decade of life (1, 2), is an important determinant of osteoporosis risk. Approximately 60–80% of the variance in peak bone mass is attributable to genetics (3–5), leaving modifiable factors such as diet and physical activity to influence attainment of one’s genetically programmed peak bone mass. In particular, several experimental studies showed that calcium supplementation increases bone density in children and adolescents (6–14). However, questions remain about calcium requirements for the pediatric population. For example, racial differences in bone density have been documented (3), but it is not clear if race affects relations between calcium and bone mass. Physiologically, bone mineral increases rapidly through puberty (15–17), but it is plausible that there is an optimal window of time during puberty when the skeleton is especially responsive to the effects of calcium. Calcium supplementation was shown to have beneficial effects in both prepubertal (7–11) and pubertal (13, 14) children, but none of these studies followed the subjects to young adulthood. The dietary recommendation for calcium was recently raised from 1000 to 1300 mg for children and adolescents aged 9–13 and 14–18 y (18), but recent reports failed to provide evidence that calcium intakes > 1000 mg are associated with increased peak bone mass (19, 20). Furthermore, many of the studies that showed positive linear associations between calcium intake and bone density (21–25) have been criticized for including a considerable proportion of subjects with relatively low intakes of calcium (18). It is likely that calcium has a threshold effect on bone density (26–29).

The primary aim of the present study was to examine the relation of adolescent diet to bone mass measured in the third decade of life in a cohort of young adult black and white women who had been followed from age 9–10 y in the National Heart, Lung, and Blood Institute Growth and Health Study (NGHS; 30). The following hypotheses were evaluated: 1) dietary calcium in midpuberty is more strongly associated with peak bone mass, as indicated by young adult bone mass (YABM), than is dietary calcium in postpuberty; 2) dietary calcium > 1000 mg/d is associated with higher peak bone mass; and 3) race does not affect any of these associations between dietary calcium and peak bone mass.

Because protein intake may influence bone metabolism (31, 32) and exercise was shown to increase bone density in young women (33, 34), a secondary aim was to examine the roles of protein and physical (including sedentary) activity in mediating the relation between calcium and peak bone mass at various stages of puberty. Another secondary aim was to examine the associations of the dietary and activity variables of interest, with ultrasound bone measurements, which may reflect not only bone mass but also bone microarchitecture (35, 36).


SUBJECTS AND METHODS  
Subjects
The Berkeley Bone Health Study (BBHS) is a retrospective cohort study that was initiated in 1997 to examine the relations of genes and adolescent behavior with peak bone mass, indicated by bone mass measured in young adulthood. The researchers recruited 693 black and white women, aged 21–24 y, who had participated in the NGHS, a 10-y prospective investigation of cardiovascular disease risk factors (30). The NGHS examined a total of 2379 girls at 3 research centers, one of which was the University of California, Berkeley. The Berkeley center recruited 887 girls from West Contra Costa County, CA, in 1987–1988 with census-sampling methods. Of these 887 girls, 816 were contacted, 724 were found eligible for the BBHS, and 693 agreed to participate, giving a response rate of 95% (693/724). Subjects were excluded if they had 1) systemic or metabolic disorders or medications known to affect bone metabolism, 2) experienced surgical menopause, 3) experienced pregnancy or lactation 6 mo of examination, or 4) experienced a first-trimester pregnancy termination 3 mo of examination.

NGHS data
NGHS subjects were examined annually for 10 y, beginning at age 9–10 y, providing a wealth of anthropometric, dietary, physical activity, and eating behavior information (30). NGHS data used in the BBHS included nutrient intake assessed by 3-d food diaries (available for years 1–5, 7, 8, and 10); sedentary activity assessed by self-reports of weekly hours of televsion-video viewing (years 1, 3, and 5–10); physical activity level assessed by self-reported habitual activities, with scores derived by using metabolic equivalent values and time estimates (years 1, 3, and 5–10); height and weight measurements (yearly); pubertal stage (yearly) according to Tanner principles (37)—prepuberty, midpuberty, and postpuberty. The validity of several of these measures, including the dietary and physical activity assessments, was evaluated and reported (38–40).

NGHS data were not always available for every subject even when the subjects came for annual visits for several reasons: 1) maintenance of dietary and activity records can be burdensome, and they were therefore not collected at every visit; 2) subjects did not always allow themselves to be examined for pubertal stage; and 3) even when subjects allowed themselves to be examined for pubertal stage, they may already have been past pre- or midpuberty at the first examination (in 1987–1988), or they may have developed so quickly that annual visits were not adequate for capturing midpuberty. For example, calcium and sedentary activity data for prepuberty were available for 560 and 531 BBHS subjects, respectively, and for midpuberty, for 452 and 336 subjects. In comparison, calcium and sedentary activity data for postpuberty were available for more subjects: 673 and 671, respectively. The number of subjects with complete NGHS data for the analyses described below ranged from 315 to 341, depending on the outcome variable used.

New data collection
BBHS subjects aged 21–24 y made a 2-h visit to the bone densitometry laboratory at the University of California, Berkeley, where the following information was gathered: height, weight, bone mass, and reproductive history. Height and weight were measured with the use of a standard protocol (30).

Bone mass was measured by dual-energy X-ray absorptiometry (DXA; DPX-IQ, Lunar Corp, Madison, WI). DXA scans were performed on the spine (L2–L4), left proximal femur, and whole body for all subjects who weighed < 136 kg (300 lb). In addition, subjects with large body sizes that compromised the accuracy of readings from whole-body scans received only spine and proximal femur scans. Bone mineral content (BMC; in grams), and areal bone mineral density (BMD; in g/cm2) were measured from each DXA scan. Because both of these measurements fail to consider the volume of the bone (and therefore fail to adjust for bone size), estimates of volumetric bone mineral density were derived from BMC and bone area for the spine and femoral neck. These derived estimates are referred to as bone mineral apparent density (BMAD; in g/cm3) (41).

Measurements of the bone were also made by quantitative ultrasound at the calcaneus (Achilles; Lunar Corp). These measurements were made on the nondominant heel (except when the nondominant heel had suffered a fracture) and expressed as broadband ultrasound attenuation (BUA; in db/Mz), speed of sound (SOS; in m/s), and stiffness index. The CVs for measurements made in our bone densitometry laboratory are < 1% for all DXA measurements and 1.7% and 0.5% for BUA and SOS measurements, respectively. A detailed description of the methodology for bone mass measurements is given in another article (42). Reproductive history data were collected by a self-administered questionnaire (43).

The protocol for the BBHS was approved by the Committee for the Protection of Human Subjects at the University of California, Berkeley, and the Institutional Review Board at Stanford University.

Data management
To derive behavioral variables that corresponded to pubertal stages, we averaged the relevant variables over the 3 predefined pubertal stages. For example, daily calcium intake was calculated by averaging calcium estimates from all 3-d food records gathered during each pubertal stage:


RESULTS  
The means and SDs of the independent and outcome variables of interest are shown in Table 1 only for those subjects who contributed to the data used in the final regression analysis; a comprehensive description of the bone mass status of the entire BBHS sample was reported previously (42).


View this table:
TABLE 1 . Summary description of variables of interest1  
Although the NGHS has published data suggesting that the mean menarcheal age is lower for blacks than for whites (38), the mean menarcheal age of the subjects in this study was not significantly different by race. Mean calcium intake fell throughout puberty, from 848 mg/d (prepuberty) to 789 mg/d (postpuberty). In prepuberty, 40% of whites and 60% of blacks had calcium intakes < 800 mg/d; in comparison, 35% of whites and 20% of blacks had calcium intakes > 1000 mg (data not shown). Sedentary activity, as indicated by mean weekly hours of televsion-video viewing, was higher in midpuberty (40.8 h/wk) than in prepuberty (31.8 h/wk) and postpuberty (30.7 h/wk).

At all pubertal stages, racial differences in calcium intake, sedentary activity, and DXA and calcaneal ultrasound measures of YABM were apparent. On average, whites had a higher mean calcium intake and watched less televsion-video than did blacks. Blacks had higher mean DXA and calcaneal ultrasound measurements and were heavier. At some but not all pubertal stages, racial differences in protein intake and physical activity were observed.

Pearson’s correlations coefficients between diet and activity at different pubertal stages and DXA bone measurements showed calcium in midpuberty, calcium in postpuberty, sedentary activity in prepuberty, and physical activity in postpuberty to be the only variables associated with at least one DXA measurement. When these variables and potential confounders (weight, height, and race) were analyzed simultaneously with multiple linear regression techniques, the regression coefficients for calcium and physical activity in postpuberty, menarcheal age, and the interaction term between race and calcium intake were consistently nonsignificant and were eliminated from further analyses. In the final regression equations, the independent variables were race, weight, height, calcium in midpuberty, and sedentary activity in prepuberty.

The results of these multiple regression analyses are shown in Table 2. Calcium intake in midpuberty was a positive predictor of bone density at every skeletal site measured by DXA, and sedentary activity in prepuberty was a negative predictor of femoral neck BMD and BMAD. There was also evidence of an association between sedentary activity (in prepuberty) and YABM for the spine (BMAD) and whole body (BMD), but these associations were not statistically significant. Calcium intake in midpuberty was also positively associated with all ultrasound measurements. Sedentary activity in prepuberty was associated only with SOS, but not significantly.


View this table:
TABLE 2 . Multiple linear regression with dual-energy X-ray absorptiometry (DXA) and calcaneal ultrasound measurements as outcome variables1  
To test our first hypothesis—that calcium intake in midpuberty is more strongly associated with YABM than is calcium in postpuberty—differences between the regression coefficients for calcium intake at each pubertal stage were evaluated with the use of a t test (Table 3). Calcium intake in midpuberty was more strongly associated with YABM for the spine and whole body than was calcium intake in pre- and postpuberty.


View this table:
TABLE 3 . Comparison of regression coefficient for dietary calcium in midpuberty (bmid) with those for dietary calcium in prepuberty (bpre) and dietary calcium in postpuberty (bpost)1  
When calcium intake in midpuberty was treated as a 3-category variable (< 800 mg, 800–1000 mg, and > 1000 mg), both DXA and ultrasound bone mass measurements tended to increase with calcium intake after adjusting for race, height, weight, and sedentary activity (Figure 1). However, only differences in whole-body BMD, SOS, and stiffness index by calcium intake were statistically significant (P < 0.05). Linear (P < 0.05) but not quadratic trends were noted.


View larger version (43K):
FIGURE 1. . Mean (± SE) dual-energy X-ray absorptiometry and calcaneal ultrasound measurements by midpubertal calcium intake (adjusted for race, height, weight, and sedentary activity in prepuberty). n = 341 for spine and femoral neck measurements, 323 for whole-body measurements, and 315 for calcaneal ultrasound measurements. BMD, bone mineral density; BMAD, bone mineral apparent density; BMC, bone mineral content. Differences in means were evaluated by using ANOVA and linear and quadratic trend tests. A linear trend test was significant at P < 0.05 for whole-body BMD and speed of sound.

 
In the above analyses that examined relations of calcium intake, first as a continuous variable and then as a 3-category variable, with YABM, there was no evidence to support an interaction between race and calcium intake, indicating that race did not influence the observed relations between calcium intake in midpuberty and YABM.


DISCUSSION  
Puberty is a period of rapid bone mineral gain (15–17). From longitudinal data, Bailey et al (49) estimated that at peak height velocity (corresponding to peak BMC velocity), girls accrue calcium at a mean rate of 284 ± 58 mg/d and concluded that 26% of adult calcium is laid down during the period of peak skeletal growth. Thus, it seems biologically plausible that the skeleton is most responsive to dietary calcium during puberty, when bone mineral is being accrued most rapidly. The benefits of calcium supplementation were shown in prepubertal subjects (7–11) and postpubertal subjects (12–14). However, few studies have examined subjects at different stages of puberty. In a 2-y double-blinded, placebo-controlled calcium supplementation trial involving 112 white girls with a mean calcium intake of 983 mg/d and a mean age of 11.9 ± 0.5 y at entry, Lloyd et al (13) reported that benefits in bone gain were observed only among those with Tanner scores greater than the median. None of these supplementation studies followed subjects to adulthood to determine whether dietary calcium consumption early in life translated into gains in peak bone mass.

Prospective epidemiologic studies of a cohort followed throughout puberty would help to determine whether there is a particular developmental stage when the effects of dietary calcium on bone density are stronger. In the 15-y longitudinal Amsterdam Growth and Health Study, 182 Dutch children were followed from age 13 y. Calcium intake estimated over 3 progressively wider age intervals (13–17, 13–21, and 13–27 y) was not related to bone density measured at age 27 y (50). In another prospective study, involving 264 Finns aged 9–18 y at entry, again no relation between calcium and bone density, measured 11 y after entry, was observed (51). Recently, Lloyd et al (20) reported that calcium intake during adolescence was not associated with bone mineral gains at the hip nor with hip bone density measured at age 18 y among 81 white females followed from age 12–18 y. Only exercise during ages 12–18 y was observed to be significantly associated with hip bone density measured at age 18 y. An even more recent report on the same group of women confirmed that calcium intake, averaged from food records collected between ages 12 and 20 y, was not associated with bone mass nor with bone structure measured at age 20 y (52).

Contrary to these findings, our data indicate that calcium intake in midpuberty is related to YABM. When our subjects were in midpuberty, their mean age was 12.0 y for whites and 11.7 y for blacks. These ages approximate the mean age of peak calcium accretion for girls estimated by Bailey et al (16) (12.5 ± 0.9 y).

With regard to our second hypothesis—that calcium intake > 1000 mg/d is associated with higher YABM—we observed higher bone density among those with midpubertal calcium intakes > 1000 mg than among those with intakes < 800 mg and 800–1000 mg, but the differences were statistically significant only for whole-body BMD. Furthermore, we did not find evidence of a threshold effect of calcium on bone mass at 800–1000 mg/d. Some (9–14) but not all (19, 20) calcium supplementation studies have shown that calcium intake > 1000 mg/d increases bone mass in adolescent females. However, many metabolic studies suggest that the relation between calcium and bone mass plateaus with increasing calcium intakes (28, 29). Existing evidence indicates that such a threshold effect exists at calcium intakes of 1000–1500 mg/d (26–29). In an analysis of data from 124 balance studies involving children and young adults, Matkovic and Heaney (28) reported that the threshold calcium intake for 9–17-y-olds is 1480 mg. Determination of such an effect in the present study was precluded because few subjects had calcium intakes that averaged 1500 mg/d .

Our secondary efforts to examine associations of physical activity and sedentary activity with bone measurements yielded interesting observations. First, our analyses showed more consistent associations with sedentary activity than with physical activity. Second, the associations with sedentary activity were significant only during prepuberty. The first observation is likely to reflect either 1) differences in the magnitude of measurement error between sedentary activity and physical activity; 2) the limitation of the physical activity assessment tool, which was not designed to specifically measure weight-bearing activity; or 3) physiologic differences in the effect of sedentary activity and physical activity on bone mass. It is conceivable that associations with physical activity are likely to be observed only when there is great variation (in the level of physical activity) among subjects.

Our observation that it is in prepuberty when relations with sedentary activity are apparent is supported by recent literature. In 1995, Kannus et al (53) reported that female tennis and squash players who started playing at or before menarche had higher bone mass than did those who started playing after menarche. Subsequently, Bass et al (54) postulated that intense exercise during puberty and after puberty (when there may be interference with sex hormone cyclicity) may be associated with amenorrhea and therefore lower peak bone mass but that exercise during prepuberty, when growth is relatively independent of sex hormones, may contribute to the attainment of optimal peak bone mass. Indeed, their study of prepubertal (Tanner breast stage 1) female gymnasts showed that the prepubertal years are an "opportune time for exercise to increase bone density." To our knowledge, the present study is among the first to show that sedentary activity, as indicated by televsion-video viewing, may compromise bone health in females and that its effects are observed in prepuberty. It should be noted that physical activity may affect bone mass differently in males. At least one study has found peripubertal exercise to increase bone mass in boys but not in girls (55).

Another secondary aim was to examine the relation between protein intake and bone mass. No such relation was observed. The role of protein in calcium metabolism appears to be related not just to total protein intake but also to the source of protein (animal or plant; 56). Data for conducting the analysis by source of protein were not available.

We also examined associations of midpubertal calcium intake and prepubertal sedentary activity with calcaneal measurements and found positive associations. Associations between sedentary activity and calcaneal measurements were not statistically significant. There are few reports of the influences of diet and activity on bone ultrasound measurements in young people. A few cross-sectional studies of adult women have observed that dietary calcium and physical activity are positively associated with BUA, SOS, or both (57, 58). In a study of peripubertal Finnish girls aged 11–17 y, Lehtonen-Veromaa et al (59) observed higher BUA and SOS among gymnasts and runners but noted that SOS declined among runners who had ceased training. In Japanese children, Sasaki et al (60) reported that an index derived from bone ultrasound measurements was positively associated with past and current milk consumption as well as physical activity. Our research group, in a preliminary study involving a subsample (n = 63) of the NGHS cohort, also reported a positive association between calcium measured over ages 9–11 y and BUA measured at age 18–19 y (61).

To our knowledge, this is the largest study of bone health in a biracial cohort of young women that used prospective dietary, activity, and pubertal-stage data to examine relations with bone mass measured in the third decade of life. Most investigations of the influences of calcium and physical activity on bone mass have been cross-sectional studies or intervention trials of short duration involving small numbers of subjects or only whites. Many have inferred that early adolescent lifestyle has important effects on bone health. Our findings are consistent with and further refine this inference. With regard to calcium, we observed that it is during midpuberty when the skeleton is most responsive. We also noted that race does not influence the relation between midpubertal calcium intake and bone mass. With regard to activity, we found that among our study subjects, sedentary activity is a better predictor of YABM than is physical activity. Furthermore, it is in prepuberty when the adverse effects of sedentary activity on skeletal health are observed. Because calcium intakes begin to decline in early adolescence (62), physical activity levels are low among US children (63), and racial differences in calcium intake and physical activity patterns exist, these findings have important policy implications.


ACKNOWLEDGMENTS  
LK B, PBC, MVL, and M-CW designed the study. PBC was the principal investigator of the BBHS. MH provided statistical consultation and assisted M-CW with the data analyses. M-CW wrote the manuscript collaboratively with all coauthors. KS coordinated the data collection. MVL provided technical consultation on the operations of the bone densitometry laboratory. None of the authors has any financial or personal interest in the organization that funded this study. We are grateful to the subjects of the NGHS for their continued support. Finally, we thank Zak Sabry, associate dean of the School of Public Health, University of California, Berkeley, who was the chair of the National Steering Committee and the principal investigator of the Berkeley center of the NGHS and who provided invaluable support from the initial planning stages of the BBHS to the review of this article.


REFERENCES  

  1. Recker RR, Davies KM, Hinders SM, Heaney RP, Stegman MR, Kimmel DB. Bone gain in young adult women. JAMA 1992;268:2403–8.
  2. Heaney RP, Abrams S, Dawson-Hughes B, et al. Peak bone mass. Osteoporos Int 2000;11:985–1009.
  3. Pollitzer WS, Anderson JJB. Ethnic and genetic differences in bone mass: a review with a hereditary vs environmental perspective. Am J Clin Nutr 1989;50:1244–59.
  4. Smith DM, Nance WE, Kang KW, Christian JC, Johnston CC Jr. Genetic factors in determining bone mass. J Clin Invest 1973;52:2800–8.
  5. Slemenda CW, Christian JC, Williams CJ, Norton JA, Johnston CC Jr. Genetic determinants of bone mass in adult women; a reevaluation of the twin model and the potential importance of gene interaction on heritability estimates. J Bone Min Res 1991;6:561–7.
  6. Dibba B, Prentice A, Ceesay M, Stirling DM, Cole TJ, Poskitt EM. Effect of calcium supplementation on bone mineral accretion in Gambian children accustomed to a low-calcium diet. Am J Clin Nutr 2000;71:544–9.
  7. Carter LM, Whiting SJ. Effect of calcium supplementation is greater in prepubertal girls with low calcium intake. Nutr Rev 1997;55:371–3.
  8. Lee WT, Leung SS, Leung DM, Tsang HS, Lau J, Cheng JC. A randomized double-blind controlled calcium supplementation trial, and bone and height acquisition in children. Br J Nutr 1995;74:125–39.
  9. Johnston CC Jr, Miller JZ, Slemenda CW, et al. Calcium supplementation and increases in bone mineral density in children. N Engl J Med 1992;327:82–7.
  10. Bonjour JP, Carrie AL, Ferrari S, et al. Calcium-enriched foods and bone mass growth in prepubertal girls: a randomized, double-blind, placebo-controlled trial. J Clin Invest 1997;99:1287–94.
  11. Bonjour JP, Chevalley T, Ammann P, Slosman D, Rizzoli R. Gain in bone mineral mass in prepubertal girls 3.5 years after discontinuation of calcium supplementation: a follow-up study. Lancet 2001;358:1208–12.
  12. Lloyd T, Andon MB, Rollings N, et al. Calcium supplementation and bone mineral density in adolescent girls. JAMA 1993;270:841–4.
  13. Lloyd T, Martel JK, Rollings N, et al. The effect of calcium supplementation and Tanner stage on bone density, content and area in teenage women. Osteoporos Int 1996;6:276–83.
  14. Merrilees MJ, Smart EJ, Gilchrist NL, et al. Effects of dairy food supplements on bone mineral density in teenage girls. Eur J Nutr 2000;39:256–62.
  15. Bachrach LK. Acquisition of optimal bone mass in childhood and adolescence. Trends Endocrinol Metab 2001;12:22–8.
  16. Bailey DA, Martin AD, McKay HA, Whiting S, Mirwald R. Calcium accretion in girls and boys during puberty: a longitudinal analysis. J Bone Miner Res 2000;15:2245–50.
  17. Martin AD, Bailey DA, McKay HA, Whiting S. Bone mineral and calcium accretion during puberty. Am J Clin Nutr 1997;66:611–5.
  18. Standing Committee on the Scientific Evaluation of Dietary Reference Intakes. Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D and fluoride. Washington, DC: National Academy Press, 1997.
  19. Fehily AM, Coles RJ, Evans WD, Elwood PC. Factors affecting bone density in young adults. Am J Clin Nutr 1992;56:576–86.
  20. Lloyd T, Chinchilli VM, Johnson-Rollings N, Kieselhorst K, Eggli DF, Marcus R. Adult female hip bone density reflects teenage sports-exercise patterns but not teenage calcium intake. Pediatrics. 2000;106:40–4.
  21. Sentipal JM, Wardlaw GM, Mahan J, Matkovic V. Influence of calcium intake and growth indexes on vertebral bone mineral density in young females. Am J Clin Nutr 1991;54:425–8.
  22. Ruiz JC, Mandel C, Garabedian M. Influence of spontaneous calcium intake and physical exercise on the vertebral and femoral bone mineral density of children and adolescents. J Bone Miner Res 1995;10:675–82.
  23. Gunnes M, Lehmann EH. Physical activity and dietary constituents as predictors of forearm cortical and trabecular bone gain in healthy children and adolescents: a prospective study. Acta Paediatr 1996;85:19–25.
  24. Kardinaal AF, Hoorneman G, Vaananen K, et al. Determinants of bone mass and bone geometry in adolescent and young adult women. Calcif Tissue Int 2000;66:81–9.
  25. Lee WT, Leung SS, Ng MY, et al. Bone mineral content of two populations of Chinese children with different calcium intakes. Bone Miner 1993;23:195–206.
  26. Matkovic V, Ilich JZ, Andon MB, et al. Urinary calcium, sodium, and bone mass of young females. Am J Clin Nutr 1995;62:417–25
  27. Kristinsson JO, Valdimarsson O, Steingrimsdottir L, Sigurdsson G. Relation between calcium intake, grip strength and bone mineral density in the forearms of girls aged 13 and 15. J Intern Med 1994;236:385–90.
  28. Matkovic V, Heaney RP. Calcium balance during human growth: evidence for threshold behavior. Am J Clin Nutr 1992;55:992–6.
  29. Matkovic V. Calcium metabolism and calcium requirements during skeletal modeling and consolidation of bone mass. Am J Clin Nutr 1991;54(suppl):245S–60S.
  30. The National Heart, Lung and Blood Institute Growth and Health Study. Obesity and cardiovascular disease risk factors in Black and White girls: the NHLBI Growth and Health Study. Am J Public Health 1992;82:1613–20.
  31. Lutz J. Calcium balance and acid-base status of women as affected by increased protein intake and by sodium bicarbonate ingestion. Am J Clin Nutr 1984;39:281–8.
  32. Heaney RP. Protein intake and the calcium economy. J Am Diet Assoc 1993;93:1259–60.
  33. Slemenda CW, Reister T, Hui SL, Miller JZ, Christian JC, Johnston CC Jr. Influences on skeletal mineralization in children and adolescents: evidence for varying effects of sexual pubertal and physical activity. J Pediatr 1994;125:201–7.
  34. Snow CM, Shaw JM, Matkin CC. Physical activity and risk for osteoporosis. In: Marcus R, Feldman D, Kelsey JL, eds. Osteoporosis. New York: Academic Press, 1996:511–28.
  35. Bouxsein ML, Radloff SE. Quantitative ultrasound of the calcaneus reflects the mechanical properties of calcaneus trabecular bone. J Bone Miner Res 1997;12:839–46.
  36. Hans D, Arlot M, Schott A, Roux J, Kotzki P, Meunier P. Do ultrasound measurements on the os calcis reflect more the bone micro-architecture than the bone mass? A two-dimensional histomorphometric study. Bone 1995;16:295–300.
  37. Tanner JM. Growth at adolescence. 2nd ed. Oxford, United Kingdom: Blackwell Scientific Publications, 1992.
  38. Wu Y, Schreiber GB, Klementowicz V, Biro F, Wright D. Racial differences in accuracy of self-assessment of sexual pubertal among young Black and White girls. J Adolesc Health 2001;28:197–203.
  39. Crawford PB, Obarzanek E, Morrison J, Sabry ZI. Comparative advantage of 3-day food records over 24-hour recall and 5-day food frequency validated by observation of 9- and 10-year-old girls. J Am Diet Assoc 1994;94:626–30.
  40. Kimm SYS, Glynn NW, Kriska A, et al. Longitudinal assessment of physical activity from childhood through adolescence. Med Sci Sports Exerc. 2000;32:1445–54.
  41. Katzman DK, Bachrach LK, Carter DR, Marcus R. Clinical and anthropometric correlates of bone mineral acquisition in healthy adolescent girls. J Clin Endocrinol Metab 1991;73:1332–9.
  42. Fielding KT, Bachrach LK, Hudes ML, Crawford PB, Wang MC. Ethnic differences in bone mass of young women vary with method of assessment. J Clin Densitometry 2002;5:229–38.
  43. Bachrach LK, Wang M-C, Van Loan M, Crawford PB. Peak bone mass and hormonal contraceptive use during adolescence. J Bone Miner Res 2000;14(supp):S538 (abstr).
  44. Khosla S, Atkinson EJ, Riggs BL, Melton LJ III. Relationship between body composition and bone mass in women. J Bone Miner Res 1996;11:857–63.
  45. Moyer-Mileur L, Xie B, Ball S, Bainbridge C, Stadler D, Jee WS. Predictors of bone mass by peripheral quantitative computed tomography in early adolescent girls. J Clin Densitom 2001;4:313–23.
  46. McKay HA, Bailey DA, Mirwald RL, Davison KS, Faulkner RA. Peak bone mineral accrual and age at menarche in adolescent girls: a 6-year longitudinal study. J Pediatr 1998;133:682–7.
  47. Galuska DA, Sowers MR. Menstrual history and bone density in young women. J Womens Health Gend Based Med 1999;8:647–56.
  48. Abrams SA, O’Brien KO, Liang LK, Stuff JE. Differences in calcium absorption and kinetics between Black and White girls aged 5–16 years. J Bone Miner Res 1995;10:829–33.
  49. Bailey DA, McKay HA, Mirwald RL, Crocker PR, 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;4:1672–9.
  50. Welten DC, Kemper HC, Post GB, et al. Weight-bearing activity during youth is a more important factor for peak bone mass than calcium intake. J Bone Miner Res 1994;9:1089–96.
  51. Valimaki MJ, Karkkainen M, Lamberg-Allardt C, et al. Exercise, smoking, and calcium intake during adolescence and early adulthood as determinants of peak bone mass. Cardiovascular Risk in Young Finns Study Group. BMJ 1994;309:230–5.
  52. Lloyd T, Beck TJ, Lin HM, et al. Modifiable determinants of bone status in young women. Bone 2002;30:416–21.
  53. Kannus P, Haapasalo H, Sankelo M, 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.
  54. Bass S, Pearce G, Bradney M, et al. Exercise before puberty may confer residual benefits in bone density in adulthood: studies in active prepubertal and retired female gymnasts. J Bone Miner Res 1998;13:500–7.
  55. Sundberg M, Gardsell P, Johnell O, et al. Peripubertal moderate exercise increases bone mass in boys but not in girls: a population-based intervention study. Osteoporos Int 2001;12:230–8.
  56. Buclin T, Cosma M, Appenzeller M, et al. Diet acids and alkalis influence calcium retention in bone. Osteoporos Int 2001;12:493–9
  57. Gregg EW, Kriska AM, Salamone LM, et al. Correlates of quantitative ultrasound in the Women’s Healthy Lifestyle Project. Osteoporos Int 1999;10:416–24
  58. Cheng S, Fan B, Wang L, et al. Factors affecting broadband ultrasound attenuation results of the calcaneus using a gel-coupled quantitative ultrasound scanning system. Osteoporos Int 1999;10:495–504.
  59. Lehtonen-Veromaa M, Mottonen T, Nuotio I, Heinonen OJ, Viikari J. Influence of physical activity on ultrasound and dual-energy X-ray absorptiometry bone measurements in peripubertal girls: a cross-sectional study. Calcif Tissue Int 2000;66:248–54.
  60. Sasaki M, Harata S, Kumazawa Y, Mita R, Kida K, Tsuge M. Bone mineral density and osteo sono assessment index in adolescents. J Orthop Sci 2000;5:185–91.
  61. Wang MC, Moore EC, Crawford PB, et al. Influence of pre-adolescent diet on quantitative ultrasound measurements of the calcaneus in young adult women. Osteoporos Int 1999;9:532–5.
  62. Alaimo K, McDowell MA, Briefel RR, et al. Dietary intake of vitamins, minerals, and fiber of persons ages 2 months and over in the United States: third National Health and Nutrition Examination Survey, phase 1, 1988–91. Adv Data 1994;258:1–28.
  63. Physical activity trends—United States, 1990–1998. MMWR Morb Mortal Wkly Rep 2001;50:166–9.
Received for publication January 22, 2002. Accepted for publication May 7, 2002.


作者: May-Choo Wang
医学百科App—中西医基础知识学习工具
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