The prevalence of osteoporosis has been increasing in recent years because of increases in life expectancy and in the proportion of older individuals in most countries(Reference Zhao, Wu and Liu1). An effective and economical approach to reducing the incidence of osteoporosis is to increase bone mass accrual during childhood and adolescence to achieve optimal peak bone mass. Childhood and adolescence are critical periods for bone mass accrual since more than 50 % of peak bone mass is accumulated during this period(Reference Nguyen, Maynard and Towne2). Low bone mass accrual during childhood and adolescence has been shown to increase not only the risk of osteoporosis in old age(Reference Bachrach3–Reference Ilich, Badenhop and Matkovic5) but also the incidence of fracture during childhood(Reference Goulding, Cannan and Williams6).
Although about 60–80 % of the variability of bone mass accrual during childhood and adolescence could be explained by heritable factors(Reference Heaney, Abrams and Dawson-Hughes7), the genetic potential is reached only if the modifiable environmental factors are optimal. Among environmental factors, suitable nutrient intakes, especially sufficient Ca intake, are the basis for maximum bone mass accrual. However, dietary Ca intakes in children are very low in some countries. For instance, in China, it was only 334 mg/d for urban girls aged 11–13 years according to the 2002 China National Nutrition and Health Survey(Reference Zhai and Yang8). This was much lower than the recommended adequate intake (1000 mg/d for this age group), suggested by the dietary recommended intakes of the Chinese Nutrition Society published in 2000(9). Although children with habitual low Ca intakes appear to increase absorption and decrease excretion of Ca during puberty(Reference Lee, Cheng and Jiang10), the data of Abrams et al. (Reference Abrams, Griffin and Hicks11) indicate that dietary Ca intakes less than 500 mg/d were far from enough for adequate Ca retention or optimal bone mass accrual. Whether habitual low Ca intake would influence the bone mass accrual in Chinese children needs further research.
The intake of other nutrients, such as protein, might also have an effect on bone mass accretion. Although dietary protein supplies the amino acid substrates for the protein of bone matrix, any quantitative relationship between protein intake and bone mass remains uncertain. Several studies have indicated a negative(Reference Abelow, Holford and Insogna13, Reference Sebastian, Harris and Ottaway14) or positive(Reference Hunt, Johnson and Roughead15, Reference Munger, Cerhan and Chiu16) influence of protein on Ca balance in postmenopausal women. However, understanding of how protein affects bone mass accrual in children and adolescents is limited to data for Western children on high Ca diets(Reference Alexy, Remer and Manz12, Reference Bounds, Skinner and Carruth17) with little information available about children with low Ca intakes. The purpose of the present study was to assess whether there was any relationship between dietary nutrient intakes, especially protein intake, and bone mass accrual in Chinese adolescent girls, who had low habitual Ca intakes.
Subjects and methods
Pre-pubertal girls (n 757) with a mean age of 10·1 years at baseline were recruited from nine primary schools in urban of Beijing, China, for a 2-year milk supplementation trial(Reference Du, Zhu and Trube18) and 3-year follow-up study(Reference Zhu, Zhang and Foo19). They were free from any disease that might influence their bone growth and development. During an intervention study in 1999–2001, they were randomly divided into three groups of comparable socio-economic status according to their school. Two groups were supplied with either 330 ml Ca-fortified milk (n 238) or milk fortified with Ca and vitamin D (n 260) on each school day for 24 months. The third group acted as controls and consumed their habitual diet without milk supplementation (n 259) during the same period. The milk supplement contained (g/l): Ca 1·7, protein 30, fat 30, sucrose 20 and lactose less than 50. After adjustment for weekends and holidays, each subject in the two supplemented groups consumed on average 144 ml/d supplementary milk, containing Ca 245 mg/d and protein 4·3 g/d with/without vitamin D 3·33 μg/d(Reference Du, Zhu and Trube18). In the follow-up study, 505 out of the 698 subjects who completed the 2-year supplementation trial were available at 36 months after supplement withdrawal, that is, 60 months from the baseline, in 2004. They were by then enrolled in twenty-six secondary schools, ranging from one to fifty-six subjects in each school(Reference Zhu, Zhang and Foo19).
The present study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Ethics Committees of the University of Sydney, and the Institute of Nutrition and Food Hygiene of the Chinese Academy of Preventive Medicine (now the National Institute for Nutrition and Food Safety, Chinese Centre for Disease Control and Prevention). Written informed consent was obtained from all subjects.
Bone mass was measured at 0, 12, 24, 48 and 60 months from the baseline with dual energy X-ray absorptiometry and analysed with software version 3.94 (Norland XR-36; Norland Medical Systems, Inc., Norland, Fort Atkinson, WI, USA) at the Department of Nuclear Medicine, 304 Hospital, Beijing. The densitometer had a variation in precision of < 1·0 % for the measured bone site at standard speed. A daily quality assurance test was performed over the study period with the use of a hydroxyapatite phantom (as supplied by the manufacturer), resulting in an accuracy error rate of < 1·0 %. Subjects wore T-shirts and shorts without any metal objects during the measurement process.
Bone mineral content (BMC), bone area (BA) and bone mineral density (BMD) were measured at the distal and proximal forearm of the non-dominant arm in all subjects, and at the whole body in half of the subjects selected at random. The starting point of the distal forearm measurement scan for each subject was determined by XR software using the minimum BMD value found during the first forearm scout scan. A numeric value of 33 % for the total length of the ulna (i.e. the distance from the ulnar end plate) was calculated by XR software and then determined as the starting point for the proximal forearm measurement scan.
Dietary intakes were assessed by a seven-consecutive-day food record at the baseline and a three-consecutive-day food record (including two weekdays and one weekend day) at 6, 12, 24, 48, 54 and 60 months from the baseline. Change from a 7-d food record to a 3-d food record was designed to improve the compliance of subjects. The correlation coefficient between the two methods was 0·784–0·883 as calculated for eighty-nine subjects selected at random from the nine schools during the baseline study(Reference Du, Zhu and Trube18).
Before each survey, instructions on how to complete the dietary record were given in detail, including illustrating the portions and sizes of each dish. Subjects recorded their own dietary intake with some help from their parents if needed. All the food records were verified by interviewing each subject about their diets. Chinese measurements of bowls, plates and spoons, being of standard size, were used to quantify food with the assistance of food-measuring models. Nutrient intakes were calculated from the Chinese food composition tables(20). The vitamin D content of food was estimated from the UK food composition tables(21) and adjusted downwards for vitamin D in eggs and in fortified fresh milk based upon local analyses of these foods(20–Reference He, Du and Greenfield22). Milk supplied for the two intervention groups during the first 2 years of intervention was included in calculating the dietary nutrient intakes.
Food sources of protein in each survey were categorised into thirteen groups, primarily as referred to in the 2002 China National Nutrition and Health Survey(Reference Zhai and Yang8), namely cereals, legumes, vegetables, fruits, nuts, candies, beverages, ice confections and condiments as plant sources, and meats, eggs, seafood, milk and milk products as animal sources. Nutrient intakes or protein sources at 0, 24 and 48 months since the baseline were related to bone mass measured at the same time. Dietary intakes at 6 and 12 months since baseline were averaged and related to bone mass measured at 12 months. Dietary intakes at 54 and 60 months since baseline were averaged and related to bone mass measured at 60 months. Milk supplied for the two intervention groups was treated as a covariate in multiple regression analyses and included when calculating dietary intakes. Three cooperating observers (Q. Z., K. Z. and X. D.) conducted the dietary surveys using the same methods.
The ratio of Ca to protein (Ca:protein, mg:g) in the diet was calculated at each dietary survey. Dietary acid load was estimated as potential renal acid load (PRAL) by using the following algorithm(Reference Alexy, Remer and Manz12):
Physical activity (PA) was determined from a 6-month PA questionnaire at 0, 12 and 24 months after baseline with regard to leisure activity PA and PA from training at sports clubs or teams. A 12-month PA questionnaire estimated PA at 48 and 60 months since baseline and extended the original questionnaire to cover leisure activities, school-organised activities and any training(Reference Liu, Ma and Zhang23). To control for differences in the questionnaires, total PA was expressed as PA metabolic equivalents (kJ/kg per week)(Reference Ainsworth, Haskell and Leon24, Reference Ainsworth, Haskell and Whitt25) and their percentage distribution at each survey.
Anthropometry and pubertal development were assessed at 0, 12, 24, 48 and 60 months from the baseline. Body weight was measured with an electronic digital scale (Thinner, Fairfield, WI, USA) while wearing light clothing and no shoes; height was measured with a body height measuring device (TG-III Type, No. 6; Machinery Plant, Beijing, China) in bare feet. Breast and pubic hair development were assessed in accordance with Tanner's definition of the five stages of puberty(Reference Tanner26); information about menstrual status and date of menarche was collected during each interview.
The second voiding morning urine samples were collected in 133 subjects at baseline and in 227 subjects at 12 months after baseline, randomly selected from all subjects. Urine samples were stored at − 20°C before being shipped in solid CO2 to Australia for analysis at the University of Sydney. The total Ca concentration in urine was determined using an arsenazo III spectrophotometric method (Cobas MIRA Roche Diagnostica, Basle, Switzerland). Urinary creatinine was measured by the Beckman Clinical Systems (Synchron CX5; Beckman Coulter, Inc., Fullerton, CA, USA) enzymatic method. Urine Ca and creatinine concentrations were expressed as Ca:creatinine ratio (mmol/mmol).
Data were entered using SPSS (version 12.0; SPSS Inc., Chicago, IL, USA) and Epi Info (version 6; WHO/CDC, Atlanta, GA, USA), and statistical analysis was conducted with Statistical Analysis Systems for Windows NT (version 8.00, 1999; SAS Institute, Inc., Cary, NC, USA). To describe information in each survey, means and standard deviations were applied for normal distribution data, while median, as well as 25th and 75th percentiles, was applied for non-normal distribution data, unless otherwise stated.
The effect of nutrient intakes on bone mass was analysed by linear mixed models (PROC MIXED in SAS program) for longitudinal analysis. In the model, the dependent variable was the bone mass at each survey point. The main independent variables included nutrient intakes at each survey, baseline bone mass and pubertal development, as well as age and PA level at each survey. Other independent variables included the school attended as a random effect for clustering design and the time of the repeated measurements for each subjects(Reference Kalkwarf, Khoury and Bean27). Groups supplied with milk or serving as controls during the first 2 years of intervention period, time and the interaction between group and time were entered into the model as covariates(Reference Kalkwarf, Khoury and Bean27).
Continuous variables were logarithm transformed to observe the proportional association and to correct a skewed distribution of continuous variables. The regression coefficient (β) of continuous variables, after being multiplied by 100, corresponded closely with the percentage change in the dependent variable associated with each 100 % change in the independent variable after adjustment for other confounders(Reference Cole28). Therefore, results of the regression analysis could be interpreted as, for example, doubling the Ca intake would theoretically result in a 0·82 % increment in BMC of the total body according to the model suggested by Cole(Reference Cole28).
All nutrient intakes were included in the initial model, followed by backward elimination with P ≤ 0·1 as the standard for retention. All subjects from all groups and subjects from the control groups (representing typical urban girls in China at puberty) were analysed separately to identify the influential components. In all of these analyses, results with P values less than 0·05 were considered as statistically significant, while a P value between 0·05 and 0·1 was considered as approaching significance or marginal significance. Similar methods were used to analyse the food source of protein on bone mass accrual after control for Ca intake and other potential confounders.
The mean age of the subjects was 10·1 (sd 0·4) year at baseline, and 15·0 (sd 0·4) year at the end of study. During the 5-year study, the average dietary intakes were only 454 (sd 182) mg/d for Ca and 55·9 (sd 16·4) mg/d for protein in the control group who represented typical urban girls in China at puberty. For the two intervention groups, their Ca and protein intake reached 774·8 (sd 183·1) mg/d and 61·0 (sd 16·3) g/d, respectively, during the supplementation period, and only 452·5 (sd 189·8) mg/d and 55·0 (sd 16·9) g/d, respectively, during the follow-up period. For all subjects, their average total body bone mass accretion was 958 (sd 154) g, rising from 1332 (sd 200) g at baseline to 2290 (sd 266) g 5 years later with an increase of 71·9 %. Other physical characteristics, nutrient intakes and PA level at each survey are presented in Table 1.
BMC, bone mineral content; BA, bone area; BMD, bone mineral density; PRAL, potential renal acid load.
* Median instead of mean, lowest quartile and highest quartile instead of sd.
† n instead of mean, % instead of sd.
‡ Including supplied milk for both intervention groups.
§ Including nutrients from supplied milk for both intervention groups.
After 2 years of milk supplementation, significant differences were observed between the two supplied groups and the control group for TB BMC(Reference Du, Zhu and Trube18). However, the difference between groups became non-significant 3 years after supplement withdrawal(Reference Zhu, Zhang and Foo19). These results have been published elsewhere(Reference Du, Zhu and Trube18, Reference Zhu, Zhang and Foo19).
Nutrient intakes and bone mass accrual
In order to shed light on the relationship between diet and bone mass accrual of Chinese pubertal girls, a linear mixed model with backward elimination regression was used to identify and quantify the influential components of longitudinal nutrient intakes of all subjects after adjusting for baseline bone mass and other potential confounders, including baseline pubertal development, age and PA percentage distribution at each survey, survey time, group, the interaction between time and group and clustering by schools (model 1 in Table 2).
BMC, bone mineral content; BMD, bone mineral density; BA, bone area.
* All continuous variables were transformed to natural logarithms and then multiplied by 100, so β represents the percentage change in the dependent variable associated with double intake of each nutrient after control for other confounders.
† Analysis with linear mixed model adjusted for baseline bone mass and pubertal development, age and physical activity percentage distribution at each survey, survey time, group, the interaction between time and group, and clustering by schools.
‡ All nutrient intakes were included in initial model and followed by backward elimination with P ≤ 0·1 as the standard for retention – excluded by the regression model.
As shown in Table 2, the total diet Ca intake positively influenced BMC accrual at TB (β = 0·92, P = 0·04), PF (β = 5·72, P < 0·01) and DF (β = 2·59, P < 0·01), BA accrual at PF (β = 6·57, P < 0·01) and DF (β = 1·36, P = 0·02), as well as BMD accrual at DF (β = 1·72, P < 0·01). However, negative associations were observed between diet protein intake and BMC accrual at TB (β = − 1·92, P = 0·02), PF (β = − 10·2, P = 0·01) and DF (β = − 4·82, P < 0·01), BA accrual at PF (β = − 9·11, P < 0·01), as well as BMD accrual at DF (β = − 3·18, P < 0·01). Similar trends were revealed when analyses were conducted separately in control group subjects who were representative of urban girls in China (data not shown). The association still existed after controlling for P intake in all subjects or in control group subjects only.
When similar analyses were carried out during the milk supplementation period over the first 2 years, protein intake had significantly negative effects on BMC accrual at TB, PF and DF, on BMD accrual at DF, and on BA accrual at PF and DF (β = − 4·80 to − 14·6, all P < 0·05); however, the effects of Ca intake were NS on bone mass accrual at all the sites measured during the supplementation period.
Animal protein v. plant protein
Dietary protein intake from animal sources and from plant sources was assessed. Protein intake from plant sources was 29·2 (sd 13·4) g/d on average in all subjects over 5 years, while protein intake from animal sources ranged between 29·4 (sd 13·4) and 34·4 (sd 13·3) g/d at different periods with or without supplied milk in both intervention groups, and 29·7 (sd 13·4) g/d in the control group (Table 3).
* Including protein from supplied milk for both intervention groups.
† Protein intakes from nuts, fruit, beverages, ice confections, candies or condiments were less than 1 g/d, separately, and were not listed in the table.
After controlling for Ca intake at each survey point, baseline bone mass and pubertal stage, PA level and age at each survey, as well as group, time, interaction between time and group, and clustering by school, dietary animal protein intake had a significant negative effect on BMC accrual at DF (β = − 1·36, P = 0·02) and PF (β = − 1·09, P = 0·02), and on BMD accrual at DF (β = − 0·86, P = 0·02). However, plant protein had no effect on bone mass at PF or DF (model 2 in Fig. 1) after adjustment. The effect of plant protein or animal protein intake on total body bone mass was NS. Moreover, given similar Ca intake and total protein intake, the percentage of total protein as animal protein had no effect on bone mass accrual at total body or forearm after similar adjustment (data not shown).
Protein from different food groups
As shown in Table 4 for model 3, food sources of protein were categorised into thirteen groups, namely cereals, legumes, vegetables, fruits, nuts, ice confections, candies, beverages and condiments for plant protein intake, as well as meats, eggs, seafood, milk and milk products for animal protein intake. After controlling for Ca intake at each survey and other potential confounders indicated as above, protein sources from thirteen food groups were assessed by backward elimination regression. Negative associations were observed between protein intake from meat and BMC accrual at TB (β = − 0·22, P = 0·09) and PF (β = − 0·63, P < 0·01), BMD accrual at DF (β = − 0·28, P = 0·08) and BA accrual at PF (β = − 0·69, P < 0·01). Similarly, the negative effects of protein from eggs were also observed significantly for BMC accrual (β = − 0·25, P < 0·01), BMD accrual (β = − 0·12, P = 0·04) and BA accrual (β = − 0·19, P = 0·01) at DF. Overall, no negative effects were observed from protein from milk and milk products.
BMC, bone mineral content; BMD, bone mineral density; BA, bone area.
* All continuous variables were transformed to natural logarithms and then multiplied by 100, β represents the percentage change in the dependent variable associated with double intake of each nutrient after control for other confounders.
† Analysis with linear mixed model adjusted for Ca intake, age and physical activity level at each survey, baseline bone mass and pubertal stage, time, group, the interaction between time and group, and clustering by schools.
‡ All nutrient intakes were included in initial model, and followed by backward elimination with P ≤ 0·1 as the standard for retention – excluded by the regression model.
The association between bone mass accretion and total body acid load, expressed as PRAL in the diet, was analysed separately in model 4 or model 5 indicated in Table 5 to further explain the effect of protein intake on bone mass accrual. Mean daily PRAL was as high as 24·1 (sd 8·3) to 27·5 (sd 9·0) mEq/d over the 5 years (Table 1). After controlling for potential confounders as indicated earlier, PRAL had a negative effect on BMD at DF (β = − 1·20, P = 0·01) but no effect on other indices or at other positions.
BMC, bone mineral content; BA, bone area; BMD, bone mineral density.
* Analysis with linear mixed model adjusted for Ca intake, physical activity level and age at each survey, bone mass and pubertal stage at baseline, group, time, interaction between time and group, and clustering by schools.
† All continuous variables were transformed to natural logarithms.
The average Ca:protein ratio (mg:g) was only 8·1 (sd 2·3) to 11·5 (sd 3·9) over the 5 years. The Ca:protein ratio was positively associated with BMD at DF (β = 1·51, P = 0·02) and with BA at PF (β = 2·14, P = 0·04), but not with TB bone mass indices after controlling for Ca intake, PA level and age at each survey, baseline bone mass and pubertal stage, as well as group, time, interaction between time and group and clustering by school.
The average urine Ca:creatinine ratio (mmol/mmol) was 0·135 (sd 0·156) at baseline and 0·100 (sd 0·168) at 12 months from baseline. After controlling for group, time, age, PA level and baseline pubertal stage, urine Ca:creatinine ratio was not associated with Ca intake or protein intake, and neither PRAL nor bone mass accrual at any site measured (data not shown).
In the present study of Chinese pubertal girls during the period from 10 to 15 years of age, bone mass accretion was considerable. BMC accrual was positively associated with longitudinal Ca intake, but negatively associated with protein intake at TB, DF or PF after controlling for potential confounders. Protein from animal foods had significantly negative effects on BMC accrual at DF or PF when protein intakes were categorised as from animal or plant food sources. Positive associations were observed between Ca:protein ratio and bone mass accrual at the forearm, but not for the total body.
Generally speaking, subjects in the present study were typical Chinese urban girls in this age group when compared with subjects in the 2002 China National Nutrition and Health Survey(Reference Wang29), having low Ca intakes and moderate protein intakes. For instance, Ca intake was about 454 mg/d on average in the control group who were typical urban girls from 10 to 15 years old in the present study. Although this was slightly higher than the average Ca level of Chinese urban girls aged 11–13 years (334 mg/d) in the 2002 China National Nutrition and Health Survey, it was still less than half the suggested 1000 mg/d for this age group(9). Their protein intakes (about 55·9 g/d) were approaching the adequate level according to the recommendation (65–80 g/d) for this age group in the Chinese dietary recommended intakes(Reference Zhai and Yang8), and only 10·4 % of the subjects consumed less than 50 % of the recommendation for protein intake. Their average protein intake per body weight was 1·36 (sd 0·53) g/kg per d.
As previously reported(Reference Du, Zhu and Trube18), the present longitudinal study showed that increased Ca intake had positive effects on bone mass accrual at total body, proximal forearm and distal forearm(Reference Du, Zhu and Trube18). Similar results were also reported by Bounds et al. (Reference Bounds, Skinner and Carruth17) in a longitudinal study of white American boys and girls from 2·3 to 8 years old with relatively high Ca intakes (857 mg/d). Moreover, most Ca supplementation trials in children and adolescents (although relatively short term, of 1–3 years except for one study over 7 years(Reference Matkovic, Badenhop-Stevens and Ha30)) also showed an overall positive effect of Ca on bone mass accrual of 1–6 % for the total body and 1–10 % at regional skeleton sites, compared with placebos.
During adolescence, the requirement of Ca for growth and bone mass accrual, as well as absorption of Ca, is higher than at any other time of life. Female adolescents tend to have higher Ca absorption efficiency for bone growth and lower urinary and faecal Ca excretion than adults(Reference O'Brien, Abrams and Liang31), especially 1 year before and after menarche(Reference Matkovic, Goel and Badenhop-Stevens32). However, during that period of rapid skeletal growth in children and adolescents, Ca intake is often inadequate, especially in Chinese adolescent girls. Although children with habitually low Ca intakes during puberty show increased absorption and decreased excretion of Ca(Reference Lee, Cheng and Jiang10), the data of Abrams et al. indicated that dietary Ca of less than 500 mg/d was insufficient to achieve maximum bone mass accrual. The average Ca intakes in the present study were far below that considered necessary for optimal bone mass accrual in Chinese pre-pubertal girls.
The effect of dietary protein intake on bone mass accrual is complex. On one hand, it has been suggested in a paired study with young women and postmenopausal women measured by dual stable isotopic methodology that moderate dietary protein intake might promote greater intestinal Ca absorption, compared with a low protein intake(Reference Hunt, Johnson and Roughead15, Reference Kerstetter, O'Brien and Caseria33). According to Cadogan(Reference Cadogan, Eastell and Jones34), an increase in dietary protein in healthy children and adolescents may also induce an increase in blood insulin-like growth factor-1 concentration, which might stimulate osteoblast activity and promote bone mineralisation. On the other hand, higher dietary protein intake, particularly animal protein, is associated with increased urinary Ca excretion by increasing the total acid load from protein metabolism(Reference Barzel and Massey35–Reference Remer37). The sulphur-containing amino acids in protein, the main part of the dietary acid load, could reduce the blood pH and result in an increase in bone resorption(Reference Remer37). For instance, a study by Kerstetter et al. (Reference Kerstetter, Mitnick and Gundberg38) in young Western women found that a high protein intake increased urinary excretion of Ca as well as N-telopeptides (bone resorption bio-marker), which suggests that there is increased bone resorption with higher protein intake.
In the present study, using Coles's model(Reference Cole28), it is predicted that a theoretical doubling of protein intake might decrease BMC accrual by 4·82 % at DF, by 10·2 % at PF or by 1·92 % for the TB, lower BMD accrual by 3·18 % at DF, or reduce BA accrual by 9·11 % at PF in Chinese pubertal girls from 10 to 15 years old. Furthermore, applying the same model(Reference Cole28), a hypothetical doubling of protein intake from animal food could potentially decrease BMC accrual over 5 years by 1·09 % at PF or by 1·36 % at DF, or lessen BMD accrual by 0·86 % at DF given similar Ca intake, PA level, age and baseline BMC and pubertal development.
In the present study, longitudinal PRAL reached 24·1 (sd 8·3) to 27·5 (sd 9·0) mEq/d, higher than that in the Dortmund nutritional and anthropometric longitudinally designed study of 720 German children aged 3–18 years (6–21 mEq/d) consuming protein at about 40·5–83·8 g/d(Reference Alexy, Kersting and Remer39). Although their earlier report for 229 healthy children and adolescents aged 6–18 years indicated that children with a higher dietary PRAL had significantly lower BMC at the proximal diaphyseal radius(Reference Alexy, Remer and Manz12), the present study did not observe any significant effect of PRAL on bone mass accrual of total body or proximal forearm, except for the negative effect on BMD at distal forearm. Moreover, we did not observe any association between PRAL or protein intake and urine Ca:creatinine. On the other hand, a positive effect of Ca:protein ratio on bone mass accrual was seen for BMD at DF and BA at PF. Heaney(Reference Heaney40–Reference Heaney42) have suggested that the dietary Ca:protein ratio required for positive Ca balance should be at least 20:1 (mg:g). In the present study, the ratio of Ca to protein in the habitual diet was only approximately 8·1–11·5 at different times. We speculate that the observed association between protein intake and bone mass might have been related to the overall low Ca intakes. Urinary Ca excretion might be increased by a higher protein intake in line with the suggestion by Weaver et al. that approximately 6 mg dietary Ca is required to compensate for the urinary Ca loss related to 1 g dietary protein intake(Reference Weaver, Proulx and Heaney43). In that case, it is predicted that on average 55 g/d protein intake during the age of 10–15 years as in the present study would be associated theoretically with a need for an extra 330 mg/d dietary Ca to compensate for this urinary Ca loss. With low Ca intakes, a relatively high protein intake could cause great pressure on Ca urinary loss, i.e. the higher the protein intake, the less Ca being retained for bone mass accretion.
The study of Bounds et al. (Reference Bounds, Skinner and Carruth17) with white American children aged 2·3–8 years and the study of Alexy et al. (Reference Alexy, Remer and Manz12) with German children and adolescents aged 6–18 years have shown that longitudinal protein intake was positively associated with BMC at total body or proximal forearm. The average protein intakes in those studies were similar to that in the present study. However, the average Ca intakes (667–1056 mg/d) were much higher than those in the present study. Compensation for urinary Ca loss related to protein intake might not cause much pressure on Ca retention for bone mass accrual with relatively higher Ca intakes, and protein intake may have been a benefit for bone mass accrual in Caucasian children with high Ca intake, but a disadvantage in Chinese children with low Ca intake. The results in the study of Vatanparast et al. (Reference Vatanparast, Bailey and Baxter-Jones44) with 133 Canadian Caucasian young adults aged 23 years would seem to support this assumption to certain extent: in the case of females at peri-adolescence or early adulthood with adequate Ca intake (average 1064 or 1247 mg/d) in that study, protein intake positively predicted BMC and BMD at total body; whereas at low Ca intake (average 659 and 766 mg/d), protein did not have any beneficial effect on bone.
In China, the average Ca intake has remained at low levels for a long time and, according to serial national nutrition surveys, has even decreased in recent years from 694·5 mg/d in 1982 to 405·4 mg/d in 1992 and to 388·8 mg/d in 2002. At the same time, although average protein intake remained stable at 66·7 g/d in 1982, 68·0 g/d in 1992 and 66·1 g/d in 2002, consumption of animal food products has increased greatly in recent years from 52·6 g/d in 1982 to 102·4 g/d in 1992 and to 131·9 g/d in 2002. Thus, protein intake of animal origin has increased, while protein from plant foods has decreased, corresponding to a decline in cereal consumption(Reference Zhai and Yang8). While these changes may be interpreted as a sign of improved protein nutrition status, their potential negative influence on bone mass accretion should be monitored during growth. For children in China with low Ca intakes, improvements in protein intake should include increased intakes of protein foods rich in Ca. This situation in China might also be a problem in other developing countries where milk intakes are low.
Strengths and limitations of the study
In the present study, linear mixed models were adopted to analyse the influence of longitudinal dietary intake. This statistical procedure provided a suitable mechanism for modelling the covariance structure associated with repeated measurements, such as bone mass over several years. It could also compensate for missing data points, thus avoiding the need to eliminate subjects with incomplete data records.
Dual-energy X-ray absorptiometry was used in the present research due to its high accuracy, precision and safety. However, BMD measured by X-ray absorptiometry estimates areal BMD, not volumetric BMD. So BA and BMC were used to evaluate bone mass accretion. Moreover, dietary intakes determined by questionnaires are less accurate than other parameters such as bone variables, which can be measured with comparatively high accuracy. Therefore, associations between diet and other variables must be viewed with caution. Finally, the decline in numbers of participants over time might have had a small limiting effect on the outcome of statistical analysis.
In conclusion, it was observed that higher background Ca intake appeared to have a positive effect on bone mass accrual, while higher protein intakes appeared to have a negative effect on bone mass accrual in Chinese pubertal girls, perhaps in association with their low Ca intakes. Further research is needed to confirm the effect of dietary protein intake, or the sources of protein, on bone mass accrual in children and adolescents of various ethnic groups and with varying Ca intakes.
We thank the staff of Beijing Xicheng Student Health Institute and the Department of School Nutrition for their help with organising the fieldwork, especially Dr X. Zhang, Dr L. Zhang and Dr Y. Tong. We also thank Dr J. Liu, Dr Q. Ouyang and Dr D. Z. Wen from Beijing No. 304 Army Hospital for their supports on bone densitometry; Dr T. A. Dobbins of the School of Public Health, University of Sydney for advice on the mixed-model analysis. We are grateful to the support of all the school principals and teachers involved, and the cooperation of all the participating students and their parents.
Q. Z. was involved in data collection and analysis, and drafted the manuscript. K. Z., L. H. F. and X. H. were involved in data collection. G. M. and X. D. were involved in the conception and design of the study. H. G. and D. R. F. were involved in conception, design and interpretation of the study. All authors contribute to the writing of the manuscript. All authors have declared that no conflicts of interest exist. The project was supported by the Australian Dairy Research and Development Corporation (now known as Dairy Australia), the Nestle Foundation and Danone Institute, China.