Skip to main content

Advertisement

SpringerLink
Log in

Gender differences in the relationships between lean body mass, fat mass and peak bone mass in young adults

  • Original Article
  • Published:
Osteoporosis International Aims and scope Submit manuscript

Abstract

Summary

The relationships between fat mass and bone mass in young adults are unclear. In 1,183 young Australians, lean body mass had a strong positive relationship with total body bone mass in both genders. Fat mass was a positive predictor of total body bone mass in females, with weaker association in males.

Introduction

Body weight and lean body mass are established as major determinants of bone mass, but the relationships between fat mass (including visceral fat) and peak bone mass in young adults are unclear. The aim of this study was to evaluate the associations between bone mass in young adults and three body composition measurements: lean body mass, fat mass and trunk-to-limb fat mass ratio (a surrogate measure of visceral fat).

Methods

Study participants were 574 women and 609 men aged 19–22 years from the Raine study. Body composition, total body bone mineral content (TBBMC), bone area and areal bone mineral density (TBBMD) were measured using DXA.

Results

In multivariate linear regression models with height, lean body mass, fat mass and trunk-to-limb fat mass ratio as predictor variables, lean mass was uniquely associated with the largest proportion of variance of TBBMC and TBBMD in males (semi-partial R 2 0.275 and 0.345, respectively) and TBBMC in females (semi-partial R 2 0.183). Fat mass was a more important predictor of TBBMC and TBBMD in females (semi-partial R 2 0.126 and 0.039, respectively) than males (semi-partial R 2 0.006 and 0.018, respectively). Trunk-to-limb fat mass ratio had a weak, negative association with TBBMC and bone area in both genders (semi-partial R 2 0.004 to 0.034).

Conclusions

Lean body mass has strong positive relationship with total body bone mass in both genders. Fat mass may play a positive role in peak bone mass attainment in women but the association was weaker in men; different fat compartments may have different effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Khosla S, Atkinson EJ, Riggs BL, Melton LJ 3rd (1996) Relationship between body composition and bone mass in women. J Bone Miner Res 11:857–863

    Article  CAS  PubMed  Google Scholar 

  2. Bogl LH, Latvala A, Kaprio J, Sovijarvi O, Rissanen A, Pietilainen KH (2011) An investigation into the relationship between soft tissue body composition and bone mineral density in a young adult twin sample. J Bone Miner Res 26:79–87

    Article  PubMed Central  PubMed  Google Scholar 

  3. Wang MC, Bachrach LK, Van Loan M, Hudes M, Flegal KM, Crawford PB (2005) The relative contributions of lean tissue mass and fat mass to bone density in young women. Bone 37:474–481

    Article  CAS  PubMed  Google Scholar 

  4. Sayers A, Tobias JH (2010) Fat mass exerts a greater effect on cortical bone mass in girls than boys. J Clin Endocrinol Metab 95:699–706

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Janicka A, Wren TA, Sanchez MM, Dorey F, Kim PS, Mittelman SD, Gilsanz V (2007) Fat mass is not beneficial to bone in adolescents and young adults. J Clin Endocrinol Metab 92:143–147

    Article  CAS  PubMed  Google Scholar 

  6. Baxter-Jones AD, Eisenmann JC, Mirwald RL, Faulkner RA, Bailey DA (2008) The influence of physical activity on lean mass accrual during adolescence: a longitudinal analysis. J Appl Physiol 105:734–741

    Article  PubMed  Google Scholar 

  7. Lu H, Fu X, Ma X, Wu Z, He W, Wang Z, Allison DB, Heymsfield SB, Zhu S (2011) Relationships of percent body fat and percent trunk fat with bone mineral density among Chinese, black, and white subjects. Osteoporos Int 22:3029–3035

    Article  CAS  PubMed  Google Scholar 

  8. Taes YE, Lapauw B, Vanbillemont G, Bogaert V, De Bacquer D, Zmierczak H, Goemaere S, Kaufman JM (2009) Fat mass is negatively associated with cortical bone size in young healthy male siblings. J Clin Endocrinol Metab 94:2325–2331

    Article  CAS  PubMed  Google Scholar 

  9. Baker JF, Davis M, Alexander R, Zemel BS, Mostoufi-Moab S, Shults J, Sulik M, Schiferl DJ, Leonard MB (2013) Associations between body composition and bone density and structure in men and women across the adult age spectrum. Bone 53:34–41

    Article  PubMed Central  PubMed  Google Scholar 

  10. Hamrick MW, Ferrari SL (2008) Leptin and the sympathetic connection of fat to bone. Osteoporos Int 19:905–912

    Article  CAS  PubMed  Google Scholar 

  11. Reid IR (2010) Fat and bone. Arch Biochem Biophys 503:20–27

    Article  CAS  PubMed  Google Scholar 

  12. Braun T, Schett G (2012) Pathways for bone loss in inflammatory disease. Curr Osteoporos Rep 10:101–108

    Article  PubMed  Google Scholar 

  13. Heaney RP, Abrams S, Dawson-Hughes B, Looker A, Marcus R, Matkovic V, Weaver C (2000) Peak bone mass. Osteoporos Int 11:985–1009

    Article  CAS  PubMed  Google Scholar 

  14. WHO (March 2011) Obesity and overweight. Fact sheet N°311. World Health Organization

  15. Zagarins SE, Ronnenberg AG, Gehlbach SH, Lin R, Bertone-Johnson ER (2010) The association of lean mass and fat mass with peak bone mass in young premenopausal women. J Clin Densitom 13:392–398

    Article  PubMed  Google Scholar 

  16. Kirchengast S (2010) Gender differences in body composition from childhood to old age: an evolutionary point of view. Journal of Life Science 2:1–10

    Google Scholar 

  17. Makovey J, Naganathan V, Sambrook P (2005) Gender differences in relationships between body composition components, their distribution and bone mineral density: a cross-sectional opposite sex twin study. Osteoporos Int 16:1495–1505

    Article  PubMed  Google Scholar 

  18. Reid IR, Plank LD, Evans MC (1992) Fat mass is an important determinant of whole body bone density in premenopausal women but not in men. J Clin Endocrinol Metab 75:779–782

    CAS  PubMed  Google Scholar 

  19. Russell M, Mendes N, Miller KK, Rosen CJ, Lee H, Klibanski A, Misra M (2010) Visceral fat is a negative predictor of bone density measures in obese adolescent girls. J Clin Endocrinol Metab 95:1247–1255

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Ackerman KE, Davis B, Jacoby L, Misra M (2011) DXA surrogates for visceral fat are inversely associated with bone density measures in adolescent athletes with menstrual dysfunction. J Pediatr Endocrinol Metab 24:497–504

    Article  PubMed Central  PubMed  Google Scholar 

  21. Gilsanz V, Chalfant J, Mo AO, Lee DC, Dorey FJ, Mittelman SD (2009) Reciprocal relations of subcutaneous and visceral fat to bone structure and strength. J Clin Endocrinol Metab 94:3387–3393

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Baxter-Jones AD, Faulkner RA, Forwood MR, Mirwald RL, Bailey DA (2011) Bone mineral accrual from 8 to 30 years of age: an estimation of peak bone mass. J Bone Miner Res 26:1729–1739

    Article  PubMed  Google Scholar 

  23. Newnham JP, Evans SF, Michael CA, Stanley FJ, Landau LI (1993) Effects of frequent ultrasound during pregnancy: a randomised controlled trial. Lancet 342:887–891

    Article  CAS  PubMed  Google Scholar 

  24. Robinson M, Oddy WH, McLean NJ, Jacoby P, Pennell CE, de Klerk NH, Zubrick SR, Stanley FJ, Newnham JP (2010) Low-moderate prenatal alcohol exposure and risk to child behavioural development: a prospective cohort study. BJOG 117:1139–1150

    Article  CAS  PubMed  Google Scholar 

  25. Savgan-Gurol E, Bredella M, Russell M, Mendes N, Klibanski A, Misra M (2010) Waist to hip ratio and trunk to extremity fat (DXA) are better surrogates for IMCL and for visceral fat respectively than for subcutaneous fat in adolescent girls. Nutr Metab (Lond) 7:86

    Article  Google Scholar 

  26. Kleinbaum DG, Kupper LL, Muller KE, Nizam A (1998) Applied regression analysis and other multivariable methods. Duxbury Press, Pacific Grove

    Google Scholar 

  27. De Laet C, Kanis JA, Oden A et al (2005) Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int 16:1330–1338

    Article  PubMed  Google Scholar 

  28. Choi HS, Kim KJ, Kim KM, Hur NW, Rhee Y, Han DS, Lee EJ, Lim SK (2010) Relationship between visceral adiposity and bone mineral density in Korean adults. Calcif Tissue Int 87:218–225

    Article  CAS  PubMed  Google Scholar 

  29. Bouxsein M (2011) Biomechanics of age-related fractures. In: Marcus R, Feldman D, Kelsey J (eds) Osteoporosis, 2nd edn. Academic, San Diego, pp 509–534

    Google Scholar 

  30. Pou KM, Massaro JM, Hoffmann U et al (2007) Visceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and oxidative stress: the Framingham heart study. Circulation 116:1234–1241

    Article  CAS  PubMed  Google Scholar 

  31. Cartier A, Lemieux I, Almeras N, Tremblay A, Bergeron J, Despres JP (2008) Visceral obesity and plasma glucose-insulin homeostasis: contributions of interleukin-6 and tumor necrosis factor-alpha in men. J Clin Endocrinol Metab 93:1931–1938

    Article  CAS  PubMed  Google Scholar 

  32. Hsu YH, Venners SA, Terwedow HA et al (2006) Relation of body composition, fat mass, and serum lipids to osteoporotic fractures and bone mineral density in Chinese men and women. Am J Clin Nutr 83:146–154

    CAS  PubMed  Google Scholar 

  33. Dimitri P, Bishop N, Walsh JS, Eastell R (2012) Obesity is a risk factor for fracture in children but is protective against fracture in adults: a paradox. Bone 50:457–466

    Article  CAS  PubMed  Google Scholar 

  34. Schott AM, Cormier C, Hans D et al (1998) How hip and whole-body bone mineral density predict hip fracture in elderly women: the EPIDOS prospective study. Osteoporos Int 8:247–254

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We acknowledge with thanks the Raine Study participants and families for being part of the study, the Raine Study Team for cohort management and data collection and the Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital for providing the DXA machine. The 20 year cohort follow-up assessment was funded by project grants from the Australian National Health and Medical Research Council and funding from the Lions Eye Institute in WA. The Canadian Institutes of Health Research funded the DXA data collection. Core funding for the Raine Study is provided by the University of Western Australia, The Raine Medical Research Foundation, Telethon Institute for Childhood Health Research, Women and Infants Research Foundation, Curtin University. None of the funding agencies had any role in the conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.

Conflicts of interest

None.

Author information

Authors and Affiliations

  1. Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, 6009, Australia

    K. Zhu & J. P. Walsh

  2. School of Medicine and Pharmacology, University of Western Australia, Crawley, Australia

    K. Zhu & J. P. Walsh

  3. School of Physiotherapy, Curtin University, Perth, Australia

    K. Briffa, A. Smith & L. Straker

  4. Telethon Institute for Child Health Research, Centre for Child Health Research, University of Western Australia, Perth, Australia

    J. Mountain

  5. Curtin Health Innovation Research Institute, Curtin University, Perth, Australia

    A. M. Briggs

  6. Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada

    S. Lye

  7. School of Women’s and Infants’ Health, University of Western Australia, Crawley, Australia

    C. Pennell

Authors
  1. K. Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Briffa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Mountain
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A. M. Briggs
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. S. Lye
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. Pennell
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. L. Straker
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. J. P. Walsh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Zhu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhu, K., Briffa, K., Smith, A. et al. Gender differences in the relationships between lean body mass, fat mass and peak bone mass in young adults. Osteoporos Int 25, 1563–1570 (2014). https://doi.org/10.1007/s00198-014-2665-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-014-2665-x

Keywords

Search

Navigation