This past year, I wrote a series of blogs on the muscle-to-bone ratio (MBR), which is a body composition metric that is gaining traction in the world of athletics and performance. Two of these blogs were from research conducted in my laboratory that focused on total-body as well as regional (i.e., arm, leg, trunk) MBRs in National League Football (NFL) players [Dengel et al., 2023]. One blog compared the NFL players to a group of healthy age-matched males. The second blog examined the MBR in NFL players by position. Recently, we published a similar research study in the Journal of Strength and Conditioning Research that examined total and regional MBR in NCAA Division I College Football Players (CFP). Like the NFL blogs on MBR, I have decided to split up the research from this scientific paper [Dengel et al., 2024] into two separate blogs.
In this blog, I will discuss total as well as regional measures of MBR in CFP (n=553) compared to a healthy age-matched control group (n=261). Since we used dual X-ray absorptiometry (DXA) to determine measures of MBR, we are also able to compare fat, lean and bone masses in CFP to the healthy age- and sex-matched control group. First, let’s discuss the fat, lean, and bone masses of the two groups. As expected, the CFP had more total, fat, lean, and bone masses than their age-matched counterparts (Figure 1). In addition, CFP had significantly greater bone mineral density (1.6+0.1 vs. 1.3+0.1 g/cm2, p<0.0001) than the controls. These results are like those we reported in NFL players [Dengel et al., 2023]. The greater amount of bone mass and higher bone mineral density in CFP compared to aged-match controls is not too surprising. We reported that NFL players also had greater bone mass and bone mineral density when compared to a healthy age-matched control group [Dengel et al., 2023]. Previous research has found that athletes in high-impact sports such as gymnastics, martial arts, and volleyball, or athletes in jumping or impact-loading sports like soccer or basketball, have higher bone mass compared to athletes participating in low-impact sports (e.g., swimming, water polo, cycling) [Tenforde & Fredericson, 2011]. Given the impacts and training that college football players are regularly exposed to, a greater amount of bone mass and bone mineral density would be expected.
Next, let us look at the MBR data from this study. Although the CFP had significantly greater amounts of both bone and lean masses compared to the healthy aged-matched controls, the two groups had similar total MBR (Figure 2). This is surprising since we found a lower total MBR in NFL players compared to a healthy age-matched control group. This might be explained by the fact that NFL players are older and have been consistently training at a high level for a greater number of years than the CFP. In addition, the NFL players are a select group of athletes in terms of body size compared to CFP. It could be that the bones of these top-level athletes are larger and stronger than the average CFP athlete. These large, strong bones would certainly shift the MBR to be lower despite their considerable amounts of lean mass.
When looking at regional MBR measures, only the trunk MBR was significantly different in the CFP compared to the healthy aged-matched controls. The CFP had a lower trunk MBR than the healthy age-matched controls. This is not too surprising given the amount of core exercises that CFP do compared to the normal population. When we compared NFL players to a healthy age-matched control group, we also found a significantly lower trunk MBR. We observed no difference in either arm MBR or leg MBR between CFP and controls. This result is a little different than what we saw when NFL players were compared to a healthy age-matched control group. In that comparison, the NFL players had a greater arm MBR than the healthy age-matched control group. Again, this difference may be due to the years and volume of strength training that NFL players are required to do as part of their sport. The differences in the arm MBR may be due to the fact that the arms are not involved in supporting the body mass as in the legs. This results in less loading of the bone and leads to the development of more lean mass than bone mass in the arms of NFL players. This might explain the difference between NFL players and the healthy age-matched control group.
What does it all mean?
First, the research used in this blog about CFP [Dengel et al., 2024] adds to our knowledge about MBR and athletics. It is possible that the MBR will give coaches and athletic trainers another matrix to monitor the effects of various training programs on muscle and bone, as well as the relationship between the two tissues.
Unlike anthropometric methods that utilize skinfolds, circumferences, length, and breaths to estimate muscle, fat, and bone masses, DXA provides a valid, accurate, high-resolution measurement of a three-component body composition model in a short amount of time. In addition, the DXA can provide both total and regional measures of MBR, which can be relevant and sport specific.
Finally, most of the regional MBR measures were similar between CFP and aged-matched healthy controls. We know from our research in NFL players that differences in total MBR will develop. These differences may be due to the years of target strength training that NFL players take part in. Our next blog will examine positional differences in total as well as regional MBR in CFP athletes.
REFERENCES
Dengel DR, Evanoff NG. Positional differences in muscle-to-bone ratio in National Football League Players. International Journal of Sports Medicine 44:720-727, 2023.
Dengel DR, Studee HR, Juckett WT, Bosch TA, Carbuhn AF, Stanforth PR, Evanoff NG: Muscle-to-bone ratio in NCAA division I collegiate football players by position. Journal of Strength and Conditioning Research 38(9): 1607-1612, 2024.
Tenforde AS, Fredericson M. Influence of sports participation on bone health in the young athlete: a review of the literature. PM&R 3:861–867, 2011.
About the Author
Donald Dengel, Ph.D., is a Professor in the School of Kinesiology at the University of Minnesota and is a co-founder of Dexalytics. He serves as the Director of the Laboratory of Integrative Human Physiology, which provides clinical vascular, metabolic, exercise and body composition testing for researchers across the University of Minnesota.