This investigation is the first to compare bone phenotypes (TBMD, LBMD, LSBMD, T-score and Z-score) in high-level endurance runners with a non-athlete group, whilst also assess the impact of childhood sporting activity and menstrual status on BMD within high-level endurance runners.
Higher LBMD but not TBMD or LSBMD was shown in female runners compared to non-athletes. Specifically, LBMD was 0.050 g/cm2 higher in runners than non-athletes, highlighting the potential effects of site-specific mechanical loading on the lower extremity in endurance runners, which is congruent with some previous research (Brahm et al. 1997; Duncan et al. 2002; Nevill et al. 2003; Scofield and Hecht 2012). Mechanical loading initiates a response in molecular pathways mediating mechanical signalling in bone (e.g. nuclear factor k–b/nuclear factor k–b ligand/osteoprotegerin (RANK/RANKL/OPG), Wnt signalling and purinergic signalling pathways), influencing bone formation and resorption (Nakashima et al. 2011). Nevill et al. (2003) reported higher BMD in the legs of female endurance runners in comparison to upper body sites. They concluded that site-specific loading may enhance lower body BMD (via a positive osteogenic effect) at the expense of bone mass of the upper body sites, which may explain why we showed no difference in TBMD or LSBMD between female runners and non-athletes.
In one of the only other studies to investigate BMD in UK female endurance runners competing at a high-level, Pollock et al. (2010) demonstrated low TBMD (Z-score of − 1.0 to − 2.0) in two (4.9%) of the runners only but a median total-body Z-score of approximately 0.1 for their entire cohort. In the current study, the lowest observed total-body Z-score was − 0.9 in the female runners, with a median Z-score of 1.1 for the female runner group, suggesting higher TBMD in the runners we investigated. Sixty-six percent of the runners within this investigation had achieved the PB cutoff criteria for the marathon and at least one other running distance whilst differences in the mean age of the participants between the two studies existed (22 ± 6 vs 34 ± 12 years). Consequently, the impact of age as well as potential differences in the proportion of runners competing across the different running distances (> 800 m) between the two studies and the associated variation in body mass, running training volume and/or strength and resistance-based training practices could have contributed to the differences in findings.
Greater running distance per week has been negatively correlated with BMD (Burrows et al. 2003; Hind et al. 2006), but higher level runners (such as those participating in our investigation) are more likely to undertake resistance/strength training (Blagrove et al. 2017), which may apply greater amounts of high and multi-directional force to the bone, consequentially benefiting BMD (Nevill et al. 2003). Runners who complete higher volumes of resistance training have higher LSBMD that those who may complete lower volumes (Gordon and Nelson 2003), which may explain why we showed no difference in LSBMD between female runners and non-athletes.
Lower LSBMD but no differences in TBMD or LBMD were present in male runners. It is surprising to report no difference in LBMD between the male runners and non-athletes, given the differences observed in the female runners within this study. Previous investigation has also reported LBMD can be up to 14% higher in runners compared to non-athletes (Stewart and Hannan 2000; Kemmler et al. 2006). Kemmler et al. (2006), however, only investigated 20 high-level runners whilst Stewart and Hannan (2000) investigated bone phenotypes in runners with a range of ability, from club to international level, with specific racing distances not stated. Lower LSBMD in runners compared to non-athletes observed in our investigation is, however, comparable with other research. Lower vertebral (but not tibial or radial) BMD has been shown in male endurance runners completing 92.2 ± 6.3 km per week (Bilanin et al. 1989), whilst Hind et al. (2006) and Fredericson et al. (2007) reported low LSBMD in comparison to a reference population in male endurance runners. Endurance runners tend to have lower body mass than non-athletes (as shown in this study; Tables 2 and 3) and thus, if all else is equal, lower load will be exerted on these anatomical sites than in non-athletes. In addition, as the lumbar spine is considered a site of relatively less loading during endurance running (Pollock et al. 2010), less mechanical loading will occur here compared to the lower extremity, which might explain why BMD was lower at this site in runners compared to non-athletes, despite no difference in LBMD and TBMD (Cappozzo 1983; Pollock et al. 2010). However, other factors such as genetic predisposition, hormones and nutritional intake may also influence BMD in endurance runners.
Male runners may be at risk of relative energy deficiency in sport (RED-S), as highlighted in the recent IOC consensus statement (Mountjoy et al. 2018). Low energy availability induced by insufficient dietary intake and/or excessive energy expenditure may increase bone resorption and negatively impact bone metabolic markers, resulting in decreased bone formation, lower bone mass and altered structure (Papageorgiou et al. 2018). The benefits of mechanical loading on BMD, could, therefore, be lost, or reduced, by energy deficiency. Although difficult to assess directly from circulating bone (re)modelling markers, the balance of bone metabolism following repeated training in male endurance runners does not appear to be affected unless an energy deficiency is present, resulting in suppression of bone formation (Papageorgiou et al. 2018). A greater magnitude of loading at the lower extremity and the associated mechanical impact from running may protect against the potentially negative effect of reduced energy availability on BMD and consequently explain why lower LSBMD but similar TBMD and LBMD were shown compared to non-athletes. Energy availability was not measured in this investigation due to the difficulty in accurately measuring this complex phenomenon in such a large sample, so this surmised influence is based upon previous literature. The current methods available to assess energy availability are not without difficultly and consequently, it remains extremely problematic to identify “true” energy availability (Logue et al. 2020).
It is interesting that lower LSBMD was only evident in male, and not female, runners in comparison to their non-athlete counterparts. Higher oestrogen may preserve LSBMD in female runners. Indeed, studies reporting lower LSBMD in female endurance runners versus non-runners have primarily been in those who may have low energy availability and/or menstrual irregularities (Barrack et al. 2008; Scofield and Hecht 2012). However, we observed no difference in BMD at any site between amenorrheic and eumenorrheic runners (data appeared slightly lower in amenorrheic runners but did not approach statistical significance), suggesting that menstrual status did not affect BMD in our cohort. We assessed potential amenorrhoea and the number of sports completed in childhood via self-report questionnaire. Whilst measurement error exists (Small et al. 2007; Prince et al. 2008), questionnaires are inexpensive and easy to implement in larger cohorts, and widely used (Hoch et al. 2009; Farr et al. 2011; Martin et al. 2017). Other parameters that may influence bone phenotypes, such as smoking history and alcohol intake were not assessed as part of this investigation. Obtaining such information via self-report may not be particularly representative of the truth (Gorber et al. 2009), which in turn impacts the ability to assess or account for these parameters appropriately.
Physical activity during childhood is a key period for bone accretion (Weaver et al. 2016). Therefore, a limited range of physical activities during childhood could have negative implications for adult BMD. Herein, however, we identified no association between pBPAQ score (the type of sport and the number of sports completed in childhood) and any bone phenotype. Consequently, our findings suggest an appropriate volume of physical activity is completed (in childhood) to provide sufficient loading and associated mechanosensory benefit to elevate BMD in most runners.
Of note, we observed higher body-mass adjusted bone phenotypes for both male (TBMD and LBMD) and female (TBMD, LBMD, T-score and Z-score) runners in comparison to their non-athlete counterparts. Greater body mass has been shown to positively influence BMD, likely due to the increased load experienced by the bone (Felson et al. 1993). However, when body mass is accounted for, runners demonstrated higher relative BMD, possibly as a result of completing larger volumes of physical activity and benefitting from the associated mechanostransductive effect, than their non-athlete counterparts. The impact of body mass on BMD, however, is influenced by both muscle and fat tissue mass differently as well as the complex relationships between these body composition components and mechanical factors (Bierhals et al. 2019).
The large variance in TBMD, LBMD and LSBMD in both non-athletes and endurance runners is notable. This cannot be attributed solely to age- or physical activity-associated effects on BMD and indicates that other factors such as genetic variation also influence BMD. Heritability of BMD is estimated at 50–85% (Ralston and Uitterlinden 2010) and numerous genes may play a role (Hsu and Kiel 2012; Golchin et al. 2016).