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Nutrient Physiology, Metabolism, and Nutrient-Nutrient Interactions

The Effects of Dietary Protein on Bone Mineral Mass in Young Adults May Be Modulated by Adolescent Calcium Intake^1,2

³ College of Pharmacy and Nutrition and ⁴ College of Kinesiology, University of Saskatchewan, Saskatoon, Canada S7N 5C9; and ⁵ School of Human Movement Studies, University of Queensland, Brisbane, Australia 4000

^* To whom correspondence should be addressed. E-mail: vatan.h{at}usask.ca.

	ABSTRACT

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
The effect of dietary protein on bone mass measures at different life stages is controversial. We investigated the influence of protein intake on bone mass measures in young adults, considering the influence of calcium intake through adolescence. Subjects were 133 young adults (59 males, 74 females) who were participating in the Saskatchewan Pediatric Bone Mineral Accrual Study (1991–1997, 2003–2006). At adulthood, their mean age was 23 y. We assessed dietary intake via serial 24-h recalls carried out at least once yearly. Total body (TB) bone mineral content (BMC) and TB bone mineral density (BMD) were assessed annually using Dual energy X-ray absorptiometry. We determined TB-BMC net gain from the age of peak height velocity (PHV) to early adulthood. We analyzed data from all subjects and subsets based on sex and calcium intake using multiple regression. TB-BMC significantly increased from age at PHV to early adulthood by 41% in males and 37% in females. Height, weight, physical activity, and sex were significant predictors of TB-BMC, TB-BMC net gain, and TB-BMD among all subjects. Protein intake predicted TB-BMC net gain in all subjects (ß = 0.11; P = 0.015). In females at peri-adolescence or early adulthood with adequate calcium intake (>1000 mg/d), protein intake positively predicted TB-BMC, TB-BMC net gain, and TB-BMD (P < 0.05). Our results indicate that when calcium intake is adequate, protein intake has a beneficial effect on the bone mass of young adult females. Protein, in the absence of sufficient calcium, does not confer as much benefit to bone.

	Introduction

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

Only a few studies in children, adolescents, and young adults have examined the relationship between high protein intake and bone (16,26–28,30–32). Theintz et al. (27) observed a positive relationship between protein intake and bone mineral content (BMC)⁶ and bone mineral density (BMD) in lumbar and femoral bone sites in healthy adolescents aged 9–19 y. Chevalley et al. (28) reported that in healthy prepubertal boys, the positive response to calcium supplementation was influenced by habitual protein intake. A recent cross-sectional study (26) reported that in children and adolescents aged 6–18 y, dietary protein had a beneficial effect on diaphyseal bone strength during growth. These authors caution, however, that the anabolic effect of dietary protein only occurs with an adequate intake of alkali equivalents, such as potassium and magnesium found in fruits and vegetables. Calcium, protein, phosphorus, and the calcium:protein or calcium:phosphorus ratios together had significant effects on the spine and total body (TB) BMD and TB-BMC in females aged 18–31 y measured cross-sectionally (30). In a longitudinal prospective study among young adult females, Recker et al. (31) reported that the rate of bone gain in spine BMD had a positive correlation with the calcium:protein ratio. Recently, Ballard et al. (16) reported no effect of protein supplementation on areal and volumetric BMD during a 6-mo exercise program in females aged 18–25 y; however, protein favorably affected bone formation biomarkers (32).

One of the mechanisms of the effect of dietary protein on calcium retention in bone is its effect on urinary calcium excretion and dietary calcium absorption (33). Despite the long-term assumption that high protein intake increases calcium loss, recent studies suggest that not only does protein not present that effect, but it also increases intestinal absorption of calcium (34). Meyer et al. (35) found an elevated risk of hip fracture in perimenopausal females who had high dietary protein accompanied by a low calcium intake. In contrast, epidemiologic studies among perimenopausal females reported that adequate dietary calcium intake minimized the hypercalciuric effect of excess dietary protein, limiting its adverse effect on bone (36,37). Milk is an example of food that is a source of calcium and protein. Hence, calcium in milk can compensate for the urinary calcium loss due to milk protein (38). A calcium intake of at least 20 mg for every 1 g protein has been suggested to protect bone (39). Because most studies have been conducted in perimenopausal women, less is known about the effect of dietary protein in relation to calcium intake on bone parameters during the critical years of peak bone mass achievement, adolescence to early adulthood.

The University of Saskatchewan Pediatric Bone Mineral Accrual Study (PBMAS) has measured diet, physical activity, and body and bone parameters since childhood to early adulthood. This has allowed the evaluation of cumulative exposure to foods and nutrients of interest (40). The primary purpose of this study was to examine the association of selected dietary factors, specifically protein, calcium, and fruit and vegetable, on bone mineral mass parameters of young adult males and females who have reached peak bone mass.

	Materials and Methods

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
    Study participants and design. Subjects were participants in PBMAS, which used a mixed-longitudinal study design incorporating 8 entry age cohorts (aged 8–15 y at study entry). The initial phase of the study was conducted from 1991–1997 and during this time, the age cohort clustering remained the same. Therefore, due to overlapping of age groups, a developmental age range of 8–21 y was assessed. A total of 251 subjects enrolled in the original study. The majority of subjects were Caucasian, selected as a population-based sample of children in Saskatoon (41). From 2003 to 2006, the PBMAS subjects were reassessed (aged 17–29 y). Subjects provided written informed consent. We obtained ethical approval from the University of Saskatchewan and Royal University Hospital Advisory Committee on Ethics in Human Experimentation.

    Dietary analysis. In the original PBMAS study (1991–1997), intake was assessed via serial 24-h recalls (2–4 recalls per year) conducted at the participating schools and in the hospital at the time of the bone scans. All days of the week, except Friday and Saturday, were included (42,43). At reassessment of dietary intake between 2003–2004 and 2005–2006, we obtained yearly 24-h recalls (in-person or by telephone) over the 3-y period. Dietary data were analyzed using Food Processor (version 8.0 and its revisions, ESHA Research) that contained foods from the 2000 Canadian Nutrient File. Recalls were considered valid when energy intake was more than the basal metabolic rate and <16,744 kJ/d. Intakes from at least 3 valid recalls were averaged to determine usual intake of subjects. Nutrient intake data included supplements that were reported on the days recalled.

    Bone measurements. TB bone parameters were obtained by annual Dual energy X-ray absorptiometry (DXA) scans (QDR 2000; Hologic). Array mode was used for bone mineral acquisition and enhanced global software (version 7.10) was used for analysis. To minimize operator-related variability, the same person analyzed all TB scans using software version 5.67 A. Short-term precision in vivo for TB-BMC, expressed as CV (%), was 0.60 (43). In young adulthood (2003–2006), TB-BMC and TB-BMD data during the 3 y of follow-up were averaged to represent bone measures of young adults. The mean TB-BMC values of young adults were used in this study.

    Anthropometric, physical activity, and maturity assessments. Between 1991 and 1997, height and weight were measured every 6 mo (44). The age of attainment of peak height velocity (PHV), a measure of somatic maturity, was considered as a biological maturity age (43). In brief, using a cubic spline procedure, we fitted a curve to each individual's velocity data (cm/y) and extrapolated the age at the peak value from the curve. Biological maturity was calculated as measurement age minus age at PHV, with biological maturity at age of PHV equal to 0. Biological maturity age prior to age of PHV is measured in negative years and after PHV in positive years (43). Between 2003 and 2006, height and weight were measured annually by trained study personnel using the same scale and stadiometer used in the initial study period. Subjects wore t-shirts and shorts, with no shoes or jewelry, during measurement. Height and weight were measured twice and recorded to the nearest 0.1 cm and 0.1 kg, respectively. The means of the 3 measurements of height and weight during early adulthood were used in this study.

Physical activity was assessed using the physical activity questionnaire (PAQ) for children, adolescents (44), and adults (44). These 7-d recall questionnaires rate individuals' physical activity level during their spare time and strenuous occupational activity during the previous 7 d, resulting in a rating from 1 to 5, where a higher score reflected a higher level of physical activity (45). Between 2003 and 2006, we averaged the total physical activity questionnaire for adolescents score at each measurement occasion to define the physical activity pattern of our young adult cohort.

The 2 time points of interest were 1) near the age of PHV; and 2) early adulthood, which was close to the time of peak bone mass achievement. To characterize dietary and physical activity patterns of peri-adolescent subjects, the dietary and physical activity data from 4 y surrounding age of PHV were averaged. To calculate net gain in TB-BMC, height and weight from age of PHV to early adulthood, bone and body measures at age of PHV (–0.5 y to +0.5 y) were subtracted from their equivalents at early adulthood. The closest bone and body measures to the age of PHV were used in some subjects (n = 12) with no data in the 1 y around the age of PHV. The sample comprised 133 subjects (59 males and 74 females) (Table 1 provides descriptive information).

We developed a multiple regression model (Eq. 1) to investigate the effect of intake of calcium and protein on bone mass measures in the presence of other potential factors:

(Eq. 1)

where y is TB-BMC or TB-BMD at early adulthood, or TB-BMC net gain from peri-adolescence to early adulthood, ß₀ is the coefficient for the intercept, ß₁ is the coefficient for the variable X₁, and e_i is the residual. We used forward stepwise procedures to add potential covariates, including sex, current height and weight, physical activity level, calcium or protein intake, vegetable and fruit intake, and peri-adolescent intakes of vegetables, fruit, calcium, or protein, and physical activity, into the model. When TB-BMC net gain was considered as the outcome variable, current height and weight were replaced by their respective net gain from age at PHV to early adulthood.

The adequate intake value of calcium for young adult males and females >18 y is 1000 mg/d. Using PBMAS longitudinal data, Whiting et al. (46) estimated calcium requirements of 1000 mg/d for girls and 1200 mg/d for boys during the whole age range of adolescence (9–18 y). Therefore, we chose a calcium intake of 1000 mg/d as an appropriate cutoff value. Subjects were classified into 2 groups: those with adequate (A) calcium intake (1000 mg/d) and individuals with low (L) calcium intake (<1000 mg/d) (Table 2). We assigned a 2-letter descriptor of calcium intake. The first letter categorizes calcium intake status of peri-adolescents and the second letter describes calcium intake of young adults (e.g. LA means low calcium intake at peri-adolescence and adequate calcium intake in early adulthood). Sex-specific analyses were conducted to investigate any possible differences in the relationship between dietary factors and bone measures, considering other possible covariates. As a final analysis, differences in predictors of TB-BMC net gain were determined in females alone, as there was an adequate number of female, but not male, subjects who had low (LL) compared with adequate (AA, AL, LA) calcium intake (Table 2). In all analyses, the significance levels for entry and removal from the model were 0.05 and 0.10, respectively.

	Results

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

Separate models were conducted in multiple regression analysis because of the colinearity of calcium and protein intakes. When all subjects were included (Table 3) in models with protein, height, weight, and sex were significant predictors of all 3 bone measures (TB-BMC, TB-BMD, and TB-BMC net gain). Although peri-adolescent physical activity significantly predicted TB-BMC and TB-BMC net gain, current physical activity was a significant predictor of only TB-BMD. Protein intake in early adulthood was a significant positive predictor of TB-BMC net gain (P = 0.006). Calcium was not a significant predictor of bone measures. When the calcium:protein ratio was added into this model, there were no significant association with the bone measures (P > 0.05).

The distribution of females according to their calcium intake allowed us to examine the influence of adequate calcium intake on the effects of protein on bone. There were not enough subjects for this analysis in males (Table 2). We compared females with consistently low calcium intake (LL, n = 30) to all other females who had adequate calcium intake in one or both of the peri-adolescence and young adulthood (AA, LA, and AL, n = 44). Current and peri-adolescent mean calcium intakes in the LL group were 659 mg/d and 766 mg/d, respectively. In the group with adequate calcium intake (AA, LA, and AL), the mean intakes of calcium were 1064 mg/d and 1247 mg/d in early adulthood and peri-adolescence, respectively. Milk product and vegetable and fruit consumption at peri-adolescence and early adulthood and current protein intake were lower (P < 0.05) in LL females compared with all other females. In the multiple regression model, height and weight net gains were significant predictors of TB-BMC net gain for all females, whereas protein intake predicted TB-BMC, TB-BMC net gain, and TB-BMD only in females who had adequate calcium intake at 1 of the time points assessed (Table 4). When the calcium:protein ratio was added into these models, there were no significant associations with the bone measures.

	Discussion

TOP ABSTRACT Introduction Materials and Methods Results Discussion LITERATURE CITED

 
In this longitudinal data set among nutrients and food groups that are considered bone protective, only protein was a significant predictor of net gain in TB-BMC from the age of PHV to early adulthood, the most likely time of peak bone mass achievement (47). TB-BMC provides a more accurate measurement of bone mineral mass than TB-BMD during the time of bone mass development (48,49). Further, the net gain of TB-BMC from age of PHV to early adulthood excludes the amount of bone mineral mass accumulated before the age of PHV and hence provides an appropriate and specific outcome variable in our analysis. As demonstrated in our subanalysis in which female subjects were classified according to their calcium intake, the extent of the association of protein intake and bone measures was influenced by calcium intake.

The anabolic effect of protein on bone is due to provision of amino acids for bone matrix formation as well as production of insulin-like growth hormone I, which is responsible for bone mass development (2). Dietary protein may influence bone indirectly through its effect on muscle mass and strength (50). Further, dietary protein increases intestinal calcium absorption (34). These mechanisms may explain the positive association between bone measures and protein intake in men and women (17–30,32,34,50,51). Other studies found that a high protein diet induces metabolic acidosis followed by urinary calcium excretion, presumably through bone mineral dissolution (13,33,52,53). If protein intake is accompanied by a low rather than high potential renal acid load (PRAL), the effect on bone is anabolic rather than catabolic (10,26,37). Sources of alkali in the diet that reduce PRAL include fruit and vegetables (13,54). Because a lack of alkali promotes calcium losses (54), providing additional calcium is another way to overcome acid-induced losses.

Milk products are the main source of dietary calcium. We previously showed that the intake of milk product in our cohort is higher than in subjects of similar age in other studies among North Americans (43,55). Further, milk products were the 2nd main food source of protein, after meat, and accounted for 15% of protein in the Canadian diet (56). In addition to containing calcium, milk contains potassium and phosphorus, which result in a nearly neutral PRAL (0.3 mEq/100 g) compared with a highly positive (thus acidogenic) value for meat (26 mEq/100 g) (36). Hence, the distribution of subjects based on daily calcium intake, primarily from milk products, at peri-adolescence and early adulthood allowed us to investigate the effect of calcium intake, as well as the possible effects of other factors on bone measures.

In sex-specific analysis other than height and weight, protein intake was the only consistent significant predictor of bone measures among all nutrients of interest in females. Only 3% of male subjects had less than age- and weight-matched recommended dietary allowance for protein intake (0.8 g/kg), providing a homogenous sample regarding protein intake, whereas 24% of females did not meet the recommended dietary allowance for protein, which may be the reason why the effect of protein was more demonstrable in females. In addition, only 8.5% of males had consistent low calcium intake at peri-adolescence and early adulthood, whereas 40.6% of females fell into this category (Table 2). Hence, despite the homogenous sample of males in terms of protein and calcium intakes, the distribution of females was appropriate for statistical analyses. This provided a unique opportunity to examine the effect of protein on bone measures of young adult females in relation to calcium intake.

Although a high calcium:protein ratio has been reported to be a significant predictor of bone mass (30), it did not explain the changes in bone measures of our cohort. From peri-adolescence to early adulthood, the intake of protein increased in both males and females (P < 0.05), whereas the intake of calcium decreased in females and was unchanged in males (Table 2), resulting in a descending trend in the calcium:protein ratio. The calcium:protein ratio was not a predictor on bone measures in our cohort. Instead, our data suggest that an adequate intake of calcium is more important than its intake relative to that of protein.

Our data do not contradict the finding of Alexy et al. (26), who reported that intake of alkalizing minerals through vegetables and fruit modulates the anabolic effect of dietary protein on bone. Vegetables and fruit provide organic salts of potassium and magnesium. Higher intakes of this food group produce more net base, which is reflected as a negative PRAL that in turn enhances calcium retention (48). Many subjects in our cohort already had an adequate calcium intake, which facilitated the anabolic effect of protein on bone. We previously found vegetable and fruit intake to be a significant predictor of TB-BMC in males aged 8–20 y (43); however, this effect was not maintained to early adulthood in this analysis, possibly due to the homogeneity of distribution of vegetable and fruit intake by young adults.

There are limitations in our study. The sample size was small in the subanalyses and there were not enough male subjects with low calcium intake for comparison. Dietary intakes were self-reported, which can lead to underestimation due to underreporting. We have previously shown, using data from y 1 of our study, that underreporting was greater in girls than in boys and older girls underreported more than younger girls (57). As adolescent females age, they tend to report energy intake less accurately (58), and this phenomenon may partially explain the difference in intakes of calcium and protein among males and females. Physical activity was also self-reported and was measured as frequency of various activities. One strong point of our study is its longitudinal nature. Data from the same subjects were analyzed at 2 important time points: age of PHV and early adulthood as the time of peak bone mass achievement.

Peri-adolescence and early adulthood are 2 important time points in bone mineral mass development. Peak BMC velocity occurs around the first time point (59) and peak bone mass is achieved in early adulthood (47). In our cohort of healthy young adults, longitudinal data from childhood indicates that along with height and weight, current protein intake was a significant predictor of TB-BMC net gain from age of PHV to young adulthood in females who had adequate calcium intake mainly from milk products. Among young adult females who had long-term low calcium intake at peri-adolescence and early adulthood, no effect of protein on TB-BMC net gain was observed. The results of this study suggest that protein intake has a beneficial anabolic affect on bone during the critical years of bone mineral mass development in females and that an appropriate intake of calcium is necessary for this effect. Further investigation is needed to examine this effect in young adult males.

	FOOTNOTES

 
¹ Supported by the Canadian Institutes of Health Research.

² Author disclosures: H. Vatanparast, D. A. Bailey, A. D. G. Baxter-Jones, no conflicts of interest; S. Whiting has been a paid speaker for the California Dairy Council and the Dairy Farmers of Canada.

⁶ Abbreviations used: AA, adequate calcium intake at 2 time points: peri-adolescence and early adulthood; AL, adequate calcium intake at peri-adolescence and low calcium intake at early adulthood; BMC, bone mineral content; BMD, bone mineral density; LA, low calcium intake at peri-adolescence and adequate calcium intake at early adulthood; LL, low calcium intake at 2 time points: peri-adolescence and early adulthood; PBMAS, Pediatric Bone Mineral Accrual Study; PHV, peak height velocity; PRAL, potential renal acid load; TB, total body.

Manuscript received 1 June 2007. Initial review completed 2 July 2007. Revision accepted 2 October 2007.

	LITERATURE CITED

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