Skip to main content

Advertisement

SpringerLink
Log in

Comparison of Bone Quality Among Winter Endurance Athletes with and Without Risk Factors for Relative Energy Deficiency in Sport (REDs): A Cross-Sectional Study

  • Original Research
  • Published:
Calcified Tissue International Aims and scope Submit manuscript

Abstract

Relative Energy Deficiency in Sport (REDs) is a syndrome describing the relationship between prolonged and/or severe low energy availability and negative health and performance outcomes. The high energy expenditures incurred during training and competition put endurance athletes at risk of REDs. The objective of this study was to investigate differences in bone quality in winter endurance athletes classified as either low-risk versus at-risk for REDs. Forty-four participants were recruited (M = 18; F = 26). Bone quality was assessed at the distal radius and tibia using high resolution peripheral quantitative computed tomography (HR-pQCT), and at the hip and spine using dual X-ray absorptiometry (DXA). Finite element analysis was used to estimate bone strength. Participants were grouped using modified criteria from the REDs Clinical Assessment Tool Version 1. Fourteen participants (M = 3; F = 11), were classified as at-risk of REDs (≥ 3 risk factors). Measured with HR-pQCT, cortical bone area (radius) and bone strength (radius and tibia) were 6.8%, 13.1% and 10.3% lower (p = 0.025, p = 0.033, p = 0.027) respectively, in at-risk compared with low-risk participants. Using DXA, femoral neck areal bone density was 9.4% lower in at-risk compared with low-risk participants (p = 0.005). At-risk male participants had 21.9% lower femoral neck areal bone density (via DXA) than low-risk males (p = 0.020) with no significant differences in females. Overall, 33.3% of athletes were at-risk for REDs and had lower bone quality than those at low-risk.

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. Warden SJ, Edwards WB, Willy RW (2021) Preventing bone stress injuries in runners with optimal workload. Curr Osteoporos Rep 19:298–307. https://doi.org/10.1007/s11914-021-00666-y

    Article  PubMed  PubMed Central  Google Scholar 

  2. Schipilow JD, Macdonald HM, Liphardt AM et al (2013) Bone micro-architecture, estimated bone strength, and the muscle-bone interaction in elite athletes: an HR-pQCT study. Bone 56:281–289. https://doi.org/10.1016/j.bone.2013.06.014

    Article  CAS  PubMed  Google Scholar 

  3. Loucks AB, Kiens B, Wright HH (2011) Energy availability in athletes. J Sports Sci. https://doi.org/10.1080/02640414.2011.588958

    Article  PubMed  Google Scholar 

  4. Papageorgiou M, Dolan E, Elliott-Sale KJ, Sale C (2018) Reduced energy availability: implications for bone health in physically active populations. Eur J Nutr 57:847–859. https://doi.org/10.1007/s00394-017-1498-8

    Article  PubMed  Google Scholar 

  5. Joy E, De Souza MJ, Nattiv A et al (2014) Female athlete triad coalition consensus statement on treatment and return to play of the female athlete triad. Curr Sports Med Rep 13:219–231. https://doi.org/10.1249/jsr.0000000000000077

    Article  PubMed  Google Scholar 

  6. Loucks AB, Verdun M, Heath EM (1998) Low energy availability, not stress of exercise, alters LH pulsatility in exercising women. J Appl Physiol 84:37–46. https://doi.org/10.1152/jappl.1998.84.1.37

    Article  CAS  PubMed  Google Scholar 

  7. Stellingwerff T, Heikura IA, Meeusen R et al (2021) Overtraining syndrome (OTS) and relative energy deficiency in sport (RED-S): shared pathways, symptoms and complexities. Sport Med 51:2251–2280. https://doi.org/10.1007/s40279-021-01491-0

    Article  Google Scholar 

  8. McCormack WP, Shoepe TC, LaBrie J, Almstedt HC (2019) Bone mineral density, energy availability, and dietary restraint in collegiate cross-country runners and non-running controls. Eur J Appl Physiol 119:1747–1756. https://doi.org/10.1007/s00421-019-04164-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Cherian KS, Sainoji A, Nagalla B, Yagnambhatt VR (2018) Energy balance coexists with disproportionate macronutrient consumption across pretraining, during training, and posttraining among Indian junior soccer players. Pediatr Exerc Sci 30:506–515. https://doi.org/10.1123/pes.2017-0276

    Article  PubMed  Google Scholar 

  10. Silva MRG, Silva HH, Paiva T (2018) Sleep duration, body composition, dietary profile and eating behaviours among children and adolescents: a comparison between Portuguese acrobatic gymnasts. Eur J Pediatr 177:815–825. https://doi.org/10.1007/S00431-018-3124-Z

    Article  PubMed  Google Scholar 

  11. Heikura IA, Uusitalo ALT, Stellingwerff T et al (2018) Low energy availability is difficult to assess but outcomes have large impact on bone injury rates in elite distance athletes. Int J Sport Nutr Exerc Metab 28:403–411. https://doi.org/10.1123/ijsnem.2017-0313

    Article  CAS  PubMed  Google Scholar 

  12. Mountjoy M, Sundgot-Borgen J, Burke L et al (2014) The IOC consensus statement: beyond the female athlete triad-relative energy deficiency in sport (RED-S). Br J Sports Med 48:491–497. https://doi.org/10.1136/bjsports-2014-093502

    Article  PubMed  Google Scholar 

  13. Mountjoy M, Sundgot-Borgen J, Burke L et al (2015) The IOC relative energy deficiency in sport clinical assessment tool (RED-S CAT). Br J Sports Med 49:1354. https://doi.org/10.1136/bjsports-2015-094873

    Article  PubMed  Google Scholar 

  14. MacNeil JA, Boyd SK (2008) Bone strength at the distal radius can be estimated from high-resolution peripheral quantitative computed tomography and the finite element method. Bone 42:1203–1213. https://doi.org/10.1016/j.bone.2008.01.017

    Article  PubMed  Google Scholar 

  15. Schipilow JD, Macdonald HM, Zieger A et al (2015) Bone micro-architecture of elite alpine skiers is not reflected by bone mineral density. Osteoporos Int 26:2309–2317. https://doi.org/10.1007/s00198-015-3133-y

    Article  PubMed  Google Scholar 

  16. Ackerman KE, Nazem T, Chapko D et al (2011) Bone microarchitecture is impaired in adolescent amenorrheic athletes compared with eumenorrheic athletes and nonathletic controls. J Clin Endocrinol Metab 96:3123–3133. https://doi.org/10.1210/jc.2011-1614

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Gama EMF, Kasuki L, Paranhos-Neto FP et al (2021) Low energy availability interferes with exercise-associated bone effects in female long-distance triathletes as detected by HR-pQCT. J Clin Densitom. https://doi.org/10.1016/j.jocd.2021.01.013

    Article  PubMed  Google Scholar 

  18. Burt LA, Gabel L, Billington EO et al (2022) Response to high-dose vitamin D supplementation is specific to imaging modality and skeletal site. JBMR Plus 6:1–8. https://doi.org/10.1002/jbm4.10615

    Article  CAS  Google Scholar 

  19. Mckay AKA, Stellingwerff T, Smith ES et al (2022) Defining training and performance caliber: a participant classification framework. Int J Sports Physiol Perform 17:317–331

    Article  PubMed  Google Scholar 

  20. De Souza MJ, Nattiv A, Joy E et al (2014) Female athlete triad coalition consensus statement on treatment and return to play of the female athlete triad: 1st international conference held in San Francisco, California, May 2012 and 2nd International conference held in Indianapolis, Indiana. M Br J Sports Med 48:289. https://doi.org/10.1136/bjsports-2013-093218

    Article  Google Scholar 

  21. Whittier DE, Boyd SK, Burghardt AJ et al (2020) Guidelines for the assessment of bone density and microarchitecture in vivo using high-resolution peripheral quantitative computed tomography. Osteoporos Int 31:1607–1627. https://doi.org/10.1007/s00198-020-05438-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pauchard Y, Liphardt AM, Macdonald HM et al (2012) Quality control for bone quality parameters affected by subject motion in high-resolution peripheral quantitative computed tomography. Bone 50:1304–1310. https://doi.org/10.1016/j.bone.2012.03.003

    Article  PubMed  Google Scholar 

  23. Buie HR, Campbell GM, Klinck RJ et al (2007) Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis. Bone 41:505–515. https://doi.org/10.1016/j.bone.2007.07.007

    Article  PubMed  Google Scholar 

  24. Burghardt AJ, Buie HR, Laib A et al (2010) Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone 47:519–528. https://doi.org/10.1016/j.bone.2010.05.034

    Article  PubMed  PubMed Central  Google Scholar 

  25. Manske SL, Davison EM, Burt LA et al (2017) The estimation of second-generation HR-pQCT from first-generation HR-pQCT using in vivo cross-calibration. J Bone Miner Res 32:1514–1524. https://doi.org/10.1002/jbmr.3128

    Article  PubMed  Google Scholar 

  26. Whittier DE, Manske SL, Kiel DP et al (2018) Harmonizing finite element modelling for non-invasive strength estimation by high-resolution peripheral quantitative computed tomography. J Biomech 80:63–71

    Article  PubMed  PubMed Central  Google Scholar 

  27. Pistoia W, Van Rietbergen B, Lochmüller EM et al (2002) Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images. Bone 30:842–848. https://doi.org/10.1016/S8756-3282(02)00736-6

    Article  CAS  PubMed  Google Scholar 

  28. Whittier DE, Burt LA, Hanley DA, Boyd SK (2020) Sex- and site-specific reference data for bone microarchitecture in adults measured using second-generation HR-pQCT. J Bone Miner Res 35:2151–2158. https://doi.org/10.1002/jbmr.4114

    Article  CAS  PubMed  Google Scholar 

  29. Melin A, Tornberg ÅB, Skouby S et al (2014) The LEAF questionnaire: a screening tool for the identification of female athletes at risk for the female athlete triad. Br J Sports Med 48:540–545. https://doi.org/10.1136/bjsports-2013-093240

    Article  PubMed  Google Scholar 

  30. Koltun KJ, Strock NCA, Southmayd EA et al (2019) Comparison of female athlete triad coalition and RED-S risk assessment tools. J Sports Sci 37:2433–2442. https://doi.org/10.1080/02640414.2019.1640551

    Article  PubMed  Google Scholar 

  31. Rogers MA, Appaneal RN, Hughes D et al (2021) Prevalence of impaired physiological function consistent with relative energy deficiency in sport (RED-S): an Australian elite and pre-elite cohort. Br J Sports Med 55:38–45. https://doi.org/10.1136/bjsports-2019-101517

    Article  PubMed  Google Scholar 

  32. Ackerman KE, Holtzman B, Cooper KM et al (2019) Low energy availability surrogates correlate with health and performance consequences of relative energy deficiency in sport. Br J Sports Med 53:628–633. https://doi.org/10.1136/bjsports-2017-098958

    Article  PubMed  Google Scholar 

  33. Hoenig T, Ackerman KE, Beck BR et al (2022) Bone stress injuries. Nat Rev Dis Prim 81(8):1–20. https://doi.org/10.1038/s41572-022-00352-y

    Article  Google Scholar 

  34. Warden SJ, Sventeckis AM, Surowiec RK, Fuchs RK (2022) Enhanced bone size, microarchitecture, and strength in female runners with a history of playing multidirectional sports. Med Sci Sports Exerc 54:2020–2030. https://doi.org/10.1249/MSS.0000000000003016

    Article  PubMed  Google Scholar 

  35. Jonvik KL, Torstveit MK, Sundgot-Borgen J, Mathisen TF (2022) Do we need to change the guideline values for determining low bone mineral density in athletes? J Appl Physiol 132:1320–1322. https://doi.org/10.1152/japplphysiol.00851.2021

    Article  PubMed  PubMed Central  Google Scholar 

  36. Gabel L, Liphardt AM, Hulme PA et al (2022) Pre-flight exercise and bone metabolism predict unloading-induced bone loss due to spaceflight. Br J Sports Med 56:196–203. https://doi.org/10.1136/bjsports-2020-103602

    Article  PubMed  Google Scholar 

  37. Ihle R, Loucks AB (2004) Dose-response relationships between energy availability and bone turnover in young exercising women*. Am Soc Bone Miner Res 19:1231–1240. https://doi.org/10.1359/JBMR.040410

    Article  Google Scholar 

  38. De Souza MJ, Williams NI, Nattiv A et al (2014) Misunderstanding the female athlete triad: refuting the IOC consensus statement on relative energy deficiency in sport (RED-S). Br J Sports Med 48:1461–1465. https://doi.org/10.1136/bjsports-2014-093958

    Article  PubMed  Google Scholar 

  39. Williams NI, Koltun KJ, Strock NCA, De Souza MJ (2019) Female athlete triad and relative energy deficiency in sport: a focus on scientific rigor. Exerc Sport Sci Rev 47:197–205. https://doi.org/10.1249/JES.0000000000000200

    Article  PubMed  Google Scholar 

  40. Rogers MA, Drew MK, Appaneal R et al (2021) The utility of the low energy availability in females questionnaire to detect markers consistent with low energy availability-related conditions in a mixed-sport cohort. Int J Sport Nutr Exerc Metab 31:427–437. https://doi.org/10.1123/IJSNEM.2020-0233

    Article  PubMed  Google Scholar 

  41. Papageorgiou M, Elliott-Sale KJ, Parsons A et al (2017) Effects of reduced energy availability on bone metabolism in women and men. Bone 105:191–199. https://doi.org/10.1016/j.bone.2017.08.019

    Article  CAS  PubMed  Google Scholar 

  42. Lundy B, Torstveit MK, Stenqvist TB et al (2022) Screening for low energy availability in male athletes: attempted validation of LEAM-Q. Nutrients 14:1–19. https://doi.org/10.3390/nu14091873

    Article  CAS  Google Scholar 

  43. Tenforde AS, Barrack MT, Nattiv A, Fredericson M (2016) Parallels with the female athlete triad in male athletes. Sport Med 46:171–182. https://doi.org/10.1007/s40279-015-0411-y

    Article  Google Scholar 

  44. Kenkre JS, Bassett JHD (2018) The bone remodelling cycle. Ann Clin Biochem 55:308–327. https://doi.org/10.1177/0004563218759371

    Article  CAS  PubMed  Google Scholar 

  45. Varley I, Greeves JP, Sale C (2019) Seasonal difference in bone characteristics and body composition of elite speed skaters. Int J Sports Med 40:9–15. https://doi.org/10.1055/a-0767-6924

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the athletes who took time from their busy training schedules to participate in this work. They would also like to thank the staff at the McCaig Institute for Bone and Joint Health, University of Calgary including Anne Cook, Stephanie Kwong, Joanne Zhu, and Katrina Koger for their role in data scheduling and collection. They also wish to acknowledge the funding provided by Mitacs and cooperation of the Canadian Sport Institute Calgary and in making this work possible.

Funding

This work was supported by a funding provided by Mitacs (IT26169). The authors have no other financial interests or biases to disclose.

Author information

Authors and Affiliations

  1. McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada

    Paige M. Wyatt, Emma O. Billington, Steven K. Boyd & Lauren A. Burt

  2. Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada

    Steven K. Boyd & Lauren A. Burt

  3. Canadian Sport Institute Calgary, Calgary, AB, Canada

    Paige M. Wyatt, Kelly Drager & Erik M. Groves

  4. Canadian Sport Institute Pacific, Victoria, BC, Canada

    Trent Stellingwerff

  5. Department of Exercise Science, Physical and Health Education, University of Victoria, Victoria, BC, Canada

    Trent Stellingwerff

  6. Division of Endocrinology and Metabolism, Cumming School of Medicine, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada

    Emma O. Billington

Authors
  1. Paige M. Wyatt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kelly Drager
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erik M. Groves
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Trent Stellingwerff
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emma O. Billington
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Steven K. Boyd
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lauren A. Burt
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LB devised the study, assisted in data analysis and interpretation of results, and provided supervision throughout the study. They are the guarantor. PW contributed to athlete recruitment, data analysis, manuscript drafts, and creation of tables and figures. KD helped with athlete recruitment and provided insight for study design. EG helped to set up the study and provided insight for statistical analysis. TS and EB provided insights for study design and interpretation of results. SB assisted with data analysis and provided supervision throughout the study. All authors contributed to revision of this manuscript.

Corresponding author

Correspondence to Lauren A. Burt.

Ethics declarations

Conflict of interest

Paige Wyatt, Kelly Drager, Erik Groves, Emma Billington, Trent Stellingwerff, Steven Boyd and Lauren Burt have no conflicts of interest.

Human and Animal Rights and Informed Consent

All procedures performed in the study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Conjoint Health Research and Ethics Board (CHREB) at the University of Calgary (REB19-1078). No animals were involved in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 16 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wyatt, P.M., Drager, K., Groves, E.M. et al. Comparison of Bone Quality Among Winter Endurance Athletes with and Without Risk Factors for Relative Energy Deficiency in Sport (REDs): A Cross-Sectional Study. Calcif Tissue Int 113, 403–415 (2023). https://doi.org/10.1007/s00223-023-01120-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00223-023-01120-0

Keywords

Search

Navigation