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ORIGINAL ARTICLE
Year : 2015  |  Volume : 19  |  Issue : 5  |  Page : 608-615

Bone mineral content has stronger association with lean mass than fat mass among Indian urban adolescents


1 Senior Consultant Endocrinology and Scientific Advisor (Projects), ILSI-India, New Delhi, India
2 Commandant and Consultant, Department of Medicine and Endocrinology, Military Hospital, Shillong, Meghalaya, India
3 Thyroid Research Centre, Institute of Nuclear Medicine and Allied Sciences, New Delhi, India
4 Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India

Date of Web Publication19-Aug-2015

Correspondence Address:
Raman K Marwaha
Flat No. 17, Gautam Apartments, Gautam Nagar, New Delhi - 110 049
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2230-8210.163174

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   Abstract 

Introduction: There are conflicting reports on the relationship of lean mass (LM) and fat mass (FM) with bone mineral content (BMC). Given the high prevalence of Vitamin D deficiency in India, we planned the study to evaluate the relationship between LM and FM with BMC in Indian children and adolescents. The objective of the study was to evaluate the relationship of BMC with LM and FM. Materials and Methods: Total and regional BMC, LM, and FM using dual energy X-ray absorptiometry and pubertal staging were assessed in 1403 children and adolescents (boys [B]: 826; girls [G]: 577). BMC index, BMC/LM and BMC/FM ratio, were calculated. Results: The age ranged from 5 to 18 years, with a mean age of 13.2 ± 2.7 years. BMC adjusted for height (BMC index and BMC/height ratio) was comparable in both genders. There was no difference in total BMC between genders in the prepubertal group but were higher in more advanced stages of pubertal maturation. The correlation of total as well as regional BMC was stronger for LM (B: Total BMC - 0.880, trunk - 0.715, leg - 0.894, arm - 0.891; G: Total BMC - 0.827, leg - 0.846, arm - 0.815 (all value indicate r2 , P < 0.0001 for all) when compared with FM (B: Total BMC - 0.776, trunk - 0.676, leg - 0.772, arm - 0.728; G: Total BMC - 0.781, leg - 0.741, arm - 0.689; all P < 0.0001) except at trunk BMC (LM - 0.682 vs. FM - 0.721; all P < 0.0001), even after controlling for age, height, pubertal stage, and biochemical parameters. Conclusions: BMC had a stronger positive correlation with LM than FM.

Keywords: Bone mineral content, children and adolescents, fat mass, lean mass


How to cite this article:
Marwaha RK, Garg M K, Bhadra K, Tandon N. Bone mineral content has stronger association with lean mass than fat mass among Indian urban adolescents. Indian J Endocr Metab 2015;19:608-15

How to cite this URL:
Marwaha RK, Garg M K, Bhadra K, Tandon N. Bone mineral content has stronger association with lean mass than fat mass among Indian urban adolescents. Indian J Endocr Metab [serial online] 2015 [cited 2020 Jul 13];19:608-15. Available from: http://www.ijem.in/text.asp?2015/19/5/608/163174


   Introduction Top


Bone mineral accrual during childhood and adolescence depends on genetic factors, hormonal status, growth, sexual maturation, nutritional status including body composition [1],[2] and ethnicity. [3],[4],[5] Several body composition studies have shown the bone mass to vary significantly among ethnic groups. [4],[5] Height has been correlated with bone mineral content (BMC). [1],[6] Since, Asians are shorter than Caucasians; [4] it was easy to explain the racial difference in BMC by the height difference. However, height adjusted BMC was reported to be lower in Asians. [4] The differences in BMC and bone mineral density (BMD) have been noted among genders, [7],[8],[9],[10],[11],[12] particularly during pubertal progression. [1],[2],[13],[14],[15]

There is growing evidence which suggests that tissues such as fat, muscle, and bone are intimately involved in regulation of each other. [16] The bone mass is affected by lean mass (LM) and fat mass (FM). Effect of FM is probably mediated through its weight-bearing effect and other pathways including adipokines, [3],[6] and lean body mass (LM) positively affect the bone accrual by the mechanical strains. [2] Though, bone mass has been found to be positively associated with FM [13],[14],[15],[16] and LM [10],[17],[18],[19],[20],[21],[22] in children and adolescents, but controversy exists in the relative contribution of each on bone mass. [23],[24],[25]

Among pediatric population for analysis of body composition, dual energy X-ray absorptiometry is most widely used as in addition to bone health, it gives precise information about the total and regional distribution of FM and LM. [26] There are few Indian studies which have assessed BMD [27] and BMC [8] but none have assessed the effect of FM and LM on bone health. In the present study, we have assessed the total and regional BMC among children and adolescents, evaluated the gender differences and its relation with pubertal status, and assessed relative contribution of FM and LM on bone health.


   Materials and Methods Top


This study was an extension of the analysis from our earlier study. [27],[28] Adolescents were recruited from different schools in the city of Delhi as a part of a project to generate normative data for BMD. There were 1829 apparently healthy children and adolescents who underwent health examination (clinical, biochemical, and densitometric) on a voluntary basis. The data on BMC, LM, and FM, and its distribution were available from 1403 children and adolescents, for the present study. Children and adolescents with clinically overt hepatic, renal, neoplastic, gastrointestinal, dermatological and endocrine and systemic infective disorders, steroid intake or alcoholism were excluded. Demographic, anthropometric and clinical data were ascertained, and a detailed physical examination conducted. The study was approved by the ethics committee of the Institute of Nuclear Medicine and Allied Sciences and all subjects gave written informed consent.

Pubertal staging was carried out by trained professionals of the same sex based on Tanner criteria. [29] Testicular volume was determined by comparative palpation with Prader orchidometer (Pharmacia and Upjohn, Uppsala, Sweden). Based on testicular volume, subjects were divided into four stages. Stage 1 (prepubertal) included subjects with testicular volume < 4 ml, Stage 2 (early puberty) - volume ≥ 4 but ≤ 8 ml, Stage 3 - volume > 8 ml but ≤ 10 ml, Stage 4 - volume > 10 ml but ≤ 15 and Stage 5 (fully mature) - testicular volume > 15 ml. A testicular volume of 4 ml or greater was considered as the onset of puberty. If there was a discrepancy in the testicular volumes of two sides, the larger one was taken as the final volume.

Fasting blood samples were drawn for the estimation of serum 25-hydroxy Vitamin D (25(OH) D), intact parathyroid hormone (iPTH), total and ionized calcium, inorganic phosphorus, and alkaline phosphatase (ALP). The normal range for different biochemical parameters are as follows: Serum total calcium - 2.2-2.55 mmol/L, ionized calcium 1.12-1.32 mmol/L, inorganic phosphorus 0.9-1.5 mmol/L, and ALP < 240 U/L. The serum concentrations of 25(OH) D (reference range: 22.5-94 nmol/L) and PTH (reference range: 10-65 ng/L) were measured by RIA (Diasorin, Stillwater, MN) and electrochemiluminescence assay (Roche Diagnostics, GmdH-Manheim, Germany), respectively.

BMC and regional distribution, FM and LM were measured using the Prodigy Oracle (GE Lunar Corp., Madison, WI) according to standard protocol. Quality control procedures were carried out in accordance with the manufacturer's recommendations. Instrument variation was determined regularly using a phantom supplied by the manufacturer and mean coefficient of variation was < 0.5%. For in vivo measurements, mean coefficients of variation for all sites were < 1%. BMC index was calculated by total bone weight in kg divided by square of height in meters. Total and regional BMC were adjusted for height, FM and LM by calculating BMC/Ht, BMC/fat, and BMC/lean ratio.

Statistical analysis was carried out using SPSS version 20.0 (Chicago, IL, USA). Data were presented as mean ± standard deviation or number (%) unless specified. Independent two variables (gender) were tested by Student's t-test. A one-way analysis of variance was used test differences between pubertal staging using P value for trend. Post-hoc analysis was used to compare the significance level between two groups within each parameter. Pearson's correlation coefficient was calculated to assess the strength of the relationship between total BMC and its distribution and various anthropometric, biochemical, and densitometric parameters. Multiple regression analysis was done to ascertain association between total and regional BMC as dependable variable and LM or FM, age, SMS, serum calcium, phosphates, serum alkaline phosphatase (SAP), 25(OH) D, and iPTH levels as independent variables.


   Results Top


Basic characteristics of 1403 children and adolescents (B - 826; G - 577) ranging from 5 to 18 years and a mean age of 13.2 ± 2.7 years (B - 13.0 ± 2.7; G - 13.4 ± 2.8 years) are as shown in [Table 1]. Boys were younger, taller and heavier than girls, but their BMI was lower than that of girls. Boys had higher serum 25(OH) D, calcium, phosphates, and ALP levels [Table 1].
Table 1: Comparison of anthropometric, hormonal, and densitometric (bone and total body) parameters between boys and girls

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BMC at all sites except trunk was higher in boys when compared with girls. When BMC was adjusted for height (BMC index, total BMC/Ht ratio), there was no difference between boys and girls. Similarly, total BMC adjusted for weight was also similar between the genders. BMC/FM was higher while BMC/LM was lower in boys than girls, probably reflecting the higher LM in boys compared to girls [Table 1].

Total and regional BMC were higher in more advanced stages of pubertal maturation, and the difference between early and late puberty persisted even after adjustment for age, except the comparison between pubertal Stages 4 and 5 in girls. Similarly, BMC index only increased significantly between pubertal Stage 3 and 4 in girls and Stage 4 and 5 in boys after controlling for age [Table 2]. The percentage increase in total BMC from pubertal Stage 1-5 was comparable between genders (B: 125% vs. G: 134%). A similar pattern of increase in BMC was observed at other regions [Supplementary [Table 1] [Additional file 1]]. Girls accumulated more BMC per unit of LM during pubertal maturation when compared to boys. However, BMC accumulation per unit of fat remained constant among girls during pubertal progression as compared to boys.
Table 2: BMC according to pubertal staging after adjusting for age

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Total and regional BMC were found to be positively correlated with age, height, BMI, total LM and FM, and 25(OH) D levels and negatively correlated with iPTH, ALP, calcium, and phosphorus in the study population and both genders independently [Table 3]. Importantly, correlation of BMC with height was stronger than that with BMI, and LM stronger than FM [Figure 1]. On multiple regression analysis, with adjustment for age, height, serum calcium, phosphates, ALP, 25(OH) D, iPTH, and SMS, the BMC was positively correlated with LM and FM at all sites. The relationship was stronger for total LM except at trunk in girls, where it was stronger for total FM [Table 4].
Figure 1: Correlation of total bone mineral content with lean and fat mass in study population

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Table 3: Correlation of BMC with anthropometric, hormonal, and densitometric (bone and total body composition) parameters

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Table 4: Correlation of BMC with lean and fat mass after adjusting for age, height, SMS, serum calcium, phosphates, ALP, 25(OH)D, and iPTH

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   Discussion Top


In the present study, we report higher total and regional BMC at all ages in boys when compared to girls except at trunk. Similar observations have been reported among UK, [10],[13] Polish, [14] Lebanese, [23] and Thai children and adolescents. [7] However, there was no significant difference in BMC index, which takes into account differences in height, between genders except in the prepubertal age group. This suggests that BMC is comparable in both genders, when adjusted for height. This was further supported by comparable BMC/Ht ratio and increment in BMC during puberty in both genders. In the present study, the difference in total BMC between genders became significant only after the age of 11 years. A similar observation was made in another Indian study [8] and in healthy Thai children and adolescents. [7] However, a study from Poland reported no difference in total BMC till the age of 16 years between genders. [30] Since BMC index is adjusted for height and does differ between genders, it can become a useful tool for assessing musculoskeletal health in children and adolescents.

As reported earlier, [8],[28] we also found that puberty is associated with an increase in total and regional BMC. The overall increase in total BMC during pubertal progression in present study was lower than that reported in another study from India (B: 125% vs. 184%; G: 134% vs. 177%), [8] but was similar to that reported in young Asian and Caucasian Americans (B: 119%; G: 140%). [4] Studies among Caucasians, Polish, and adolescents from Thailand reported higher bone mass accrual among boys compared to girls. [4],[7],[14] Total and regional BMC increases with age, which may also contribute to the increment in BMC observed during the evolution of puberty. After adjusting for age, there was no difference in total and regional BMC between pubertal Stages 1 and 2, suggesting that this is age related, whereas, the contribution of puberty to increase in BMC predominantly begins from pubertal Stage 3. A similar observation was made by Ashby et al., who reported no difference between genders in total BMC till pubertal Stage 3. [13] This may be due to the fact that bone accrual follows the peak height velocity.

Our results showed that total and regional BMC was positively related to total LM and FM, which persisted after adjusting for anthropometric and biochemical parameters. Previous studies have also reported a positive association between BMC and LM after controlling for various factors. [3],[5],[9],[10],[11],[17],[18],[20],[21],[22] As reported previously, [9],[11] BMC had a higher Pearson's correlation coefficient for LM in boys when compared to girls. The relation between BMC and FM has been inconsistent, with reports showing a positive, [3],[9],[17],[18],[19],[20],[21] negative correlation [18],[31] and absent correlation. [23] Similar to earlier literature, [3],[13],[32] we also report that the relation between LM and total and regional BMC was stronger than FM in both genders, except trunk BMC in girls. Other studies, including a longitudinal birth cohort study, showed a stronger correlation between total FM and BMC in girls as compared to boys. [6],[9],[23],[25],[33] On the contrary, a study from Italy found that the association between BMC and FM in boys and girls was comparable. [3] This heterogeneity in observations can be due to differential sensitivity of trabecular and cortical bone to mechanical loading and response to adipokines. [34] It has been reported that FM is a stronger stimulus for the accrual of cortical bone mass in girls with a greater tendency to stimulate periosteal growth and suppress endosteal expansion. [25]

The main limitation was the cross-sectional design of our study, which makes it difficult to assess the sequential changes in BMC with the progression of puberty. Correlation between various factors may differ between cross-sectional and longitudinal study. [5],[18],[22] In the present study, there is no information available on genetics, plasma hormones, nutritional status, physical activity, or growth and development in our subjects, which have been shown to have an impact on BMC. [1],[2],[35]


   Conclusion Top


Boys had higher BMC than girls, but height adjusted BMC was comparable in both genders. We demonstrated that LM was more strongly associated with BMC than FM.

 
   References Top

1.
Zemel B. Bone mineral accretion and its relationship to growth, sexual maturation and body composition during childhood and adolescence. World Rev Nutr Diet 2013;106:39-45.  Back to cited text no. 1
    
2.
Loomba-Albrecht LA, Styne DM. Effect of puberty on body composition. Curr Opin Endocrinol Diabetes Obes 2009;16:10-5.  Back to cited text no. 2
    
3.
Pietrobelli A, Faith MS, Wang J, Brambilla P, Chiumello G, Heymsfield SB. Association of lean tissue and fat mass with bone mineral content in children and adolescents. Obes Res 2002;10:56-60.  Back to cited text no. 3
    
4.
Bhudhikanok GS, Wang MC, Eckert K, Matkin C, Marcus R, Bachrach LK. Differences in bone mineral in young Asian and Caucasian Americans may reflect differences in bone size. J Bone Miner Res 1996;11:1545-56.  Back to cited text no. 4
    
5.
Burrows M, Baxter-Jones A, Mirwald R, Macdonald H, McKay H. Bone mineral accrual across growth in a mixed-ethnic group of children: are Asian children disadvantaged from an early age? Calcif Tissue Int 2009;84:366-78.  Back to cited text no. 5
    
6.
Zhu K, Briffa K, Smith A, Mountain J, Briggs AM, Lye S, et al. Gender differences in the relationships between lean body mass, fat mass and peak bone mass in young adults. Osteoporos Int 2014;25:1563-70.  Back to cited text no. 6
    
7.
Nakavachara P, Pooliam J, Weerakulwattana L, Kiattisakthavee P, Chaichanwattanakul K, Manorompatarasarn R, et al. A normal reference of bone mineral density (BMD) measured by dual energy X-ray absorptiometry in healthy Thai children and adolescents aged 5-18 years: a new reference for Southeast Asian Populations. PLoS One 2014;9:e97218.  Back to cited text no. 7
    
8.
Khadilkar AV, Sanwalka NJ, Chiplonkar SA, Khadilkar VV, Mughal MZ. Normative data and percentile curves for Dual Energy X-ray Absorptiometry in healthy Indian girls and boys aged 5-17 years. Bone 2011;48:810-9.  Back to cited text no. 8
    
9.
Ferretti JL, Capozza RF, Cointry GR, García SL, Plotkin H, Alvarez Filgueira ML, et al. Gender-related differences in the relationship between densitometric values of whole-body bone mineral content and lean body mass in humans between 2 and 87 years of age. Bone 1998;22:683-90.  Back to cited text no. 9
    
10.
Crabtree NJ, Kibirige MS, Fordham JN, Banks LM, Muntoni F, Chinn D, et al. The relationship between lean body mass and bone mineral content in paediatric health and disease. Bone 2004;35:965-72.  Back to cited text no. 10
    
11.
Goulding A, Taylor RW, Grant AM, Jones S, Taylor BJ, Williams SM. Relationships of appendicular LMI and total body LMI to bone mass and physical activity levels in a birth cohort of New Zealand five-year olds. Bone 2009;45:455-9.  Back to cited text no. 11
    
12.
Kriemler S, Zahner L, Puder JJ, Braun-Fahrländer C, Schindler C, Farpour-Lambert NJ, et al. Weight-bearing bones are more sensitive to physical exercise in boys than in girls during pre- and early puberty: a cross-sectional study. Osteoporos Int 2008;19:1749-58.  Back to cited text no. 12
    
13.
Ashby RL, Adams JE, Roberts SA, Mughal MZ, Ward KA. The muscle-bone unit of peripheral and central skeletal sites in children and young adults. Osteoporos Int 2011;22:121-32.  Back to cited text no. 13
    
14.
Boot AM, Bouquet J, de Ridder MA, Krenning EP, de Muinck Keizer-Schrama SM. Determinants of body composition measured by dual-energy X-ray absorptiometry in Dutch children and adolescents. Am J Clin Nutr 1997;66:232-8.  Back to cited text no. 14
    
15.
Kirchengast S. Gender differences in body composition from childhood to old age: An evolutionary point of view. J Life Sci 2010;2:1-10.  Back to cited text no. 15
    
16.
Ho-Pham LT, Nguyen UD, Nguyen TV. Association between lean mass, fat mass, and bone mineral density: a meta-analysis. J Clin Endocrinol Metab 2014;99:30-8.  Back to cited text no. 16
    
17.
Manzoni P, Brambilla P, Pietrobelli A, Beccaria L, Bianchessi A, Mora S, et al. Influence of body composition on bone mineral content in children and adolescents. Am J Clin Nutr 1996;64:603-7.  Back to cited text no. 17
    
18.
Wey HE, Binkley TL, Beare TM, Wey CL, Specker BL. Cross-sectional versus longitudinal associations of lean and fat mass with pQCT bone outcomes in children. J Clin Endocrinol Metab 2011;96:106-14.  Back to cited text no. 18
    
19.
Rocher E, Chappard C, Jaffre C, Benhamou CL, Courteix D. Bone mineral density in prepubertal obese and control children: relation to body weight, lean mass, and fat mass. J Bone Miner Metab 2008;26:73-8.  Back to cited text no. 19
    
20.
Dorsey KB, Thornton JC, Heymsfield SB, Gallagher D. Greater lean tissue and skeletal muscle mass are associated with higher bone mineral content in children. Nutr Metab (Lond) 2010;7:41.  Back to cited text no. 20
    
21.
Baptista F, Barrigas C, Vieira F, Santa-Clara H, Homens PM, Fragoso I, et al. The role of lean body mass and physical activity in bone health in children. J Bone Miner Metab 2012;30:100-8.  Back to cited text no. 21
    
22.
Rauch F, Bailey DA, Baxter-Jones A, Mirwald R, Faulkner R. The 'muscle-bone unit' during the pubertal growth spurt. Bone 2004;34:771-5.  Back to cited text no. 22
    
23.
El Hage RP, Courteix D, Benhamou CL, Jacob C, Jaffré C. Relative importance of lean and fat mass on bone mineral density in a group of adolescent girls and boys. Eur J Appl Physiol 2009;105:759-64.  Back to cited text no. 23
    
24.
Weiler HA, Janzen L, Green K, Grabowski J, Seshia MM, Yuen KC. Percent body fat and bone mass in healthy Canadian females 10 to 19 years of age. Bone 2000;27:203-7.  Back to cited text no. 24
    
25.
Sayers A, Tobias JH. Fat mass exerts a greater effect on cortical bone mass in girls than boys. J Clin Endocrinol Metab 2010;95:699-706.  Back to cited text no. 25
    
26.
Helba M, Binkovitz LA. Pediatric body composition analysis with dual-energy X-ray absorptiometry. Pediatr Radiol 2009;39:647-56.  Back to cited text no. 26
    
27.
Shivaprasad C, Marwaha RK, Tandon N, Kanwar R, Mani K, Narang A, et al. Correlation between bone mineral density measured by peripheral and central dual energy X-ray absorptiometry in healthy Indian children and adolescents aged 10-18 years. J Pediatr Endocrinol Metab 2013;26:695-702.  Back to cited text no. 27
    
28.
Marwaha RK, Tandon N, Reddy DR, Aggarwal R, Singh R, Sawhney RC, et al. Vitamin D and bone mineral density status of healthy schoolchildren in northern India. Am J Clin Nutr 2005;82:477-82.  Back to cited text no. 28
    
29.
Tanner JM. Growth at Adolescence: With a General Consideration of the Effects of Hereditary and Environmental Factors upon Growth and Maturation from Birth to Maturity. Oxford: Blackwell Scientific Publications; 1969.  Back to cited text no. 29
    
30.
Pludowski P, Matusik H, Olszaniecka M, Lebiedowski M, Lorenc RS. Reference values for the indicators of skeletal and muscular status of healthy Polish children. J Clin Densitom 2005;8:164-77.  Back to cited text no. 30
    
31.
Weiler HA, Janzen L, Green K, Grabowski J, Seshia MM, Yuen KC. Percent body fat and bone mass in healthy Canadian females 10 to 19 years of age. Bone 2000;27:203-7.  Back to cited text no. 31
    
32.
Courteix D, Lespessailles E, Loiseau-Peres S, Obert P, Ferry B, Benhamou CL. Lean tissue mass is a better predictor of bone mineral content and density than body weight in prepubertal girls. Rev Rheum 1998;65:328-36.  Back to cited text no. 32
    
33.
Qin MW, Yu W, Xu L, Tian JP, Xing XP, Meng XW, et al. Bone mineral and body composition analysis of whole body in 292 normal subjects assessed by dual X-ray absorptiometry. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 2003;25:66-9.  Back to cited text no. 33
    
34.
El Hage R, El Hage Z, Jacob C, Moussa E, Theunynck D, Baddoura R. Bone mineral content and density in overweight and control adolescent boys. J Clin Densitom 2011;14:122-8.  Back to cited text no. 34
    
35.
Ferretti JL, Cointry GR, Capozza RF, Frost HM. Bone mass, bone strength, muscle-bone interactions, osteopenias and osteoporoses. Mech Ageing Dev 2003;124:269-79.  Back to cited text no. 35
    


    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


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