PT  - JOURNAL ARTICLE
AU  - Michelle T Barrack
AU  - Michael Fredericson
AU  - Adam S Tenforde
AU  - Aurelia Nattiv
TI  - Evidence of a cumulative effect for risk factors predicting low bone mass among male adolescent athletes
AID  - 10.1136/bjsports-2016-096698
DP  - 2017 Feb 01
TA  - British Journal of Sports Medicine
PG  - 200--205
VI  - 51
IP  - 3
4099  - http://bjsm.bmj.com/content/51/3/200.short
4100  - http://bjsm.bmj.com/content/51/3/200.full
SO  - Br J Sports Med2017 Feb 01; 51
AB  - Background Limited research has evaluated risk factors for low bone mineral density (BMD) in male adolescent athletes.Aims/objectives To evaluate predictors of low BMD (defined as BMD Z-score <−1.0) in a sample of male adolescent distance runner and non-runner athletes.Methods Male adolescent athletes completed a survey characterising sports participation, nutrition, stress fracture history, dual energy X-ray absorptiometry (DXA)-measured BMD and body composition. Independent t-tests and analysis of covariance (ANCOVA) evaluated group differences; logistic regression evaluated low BMD risk factors.Results Runners (n=51) exhibited a lower body weight (p=0.02), body mass index (BMI) (kg/m2) (p=0.02), per cent expected weight (p=0.02) and spine BMD Z-score (p=0.002) compared with non-runners (n=18). Single risk factors of low BMD included <85% expected weight (OR=5.6, 95% CI 1.4 to 22.5) and average weekly mileage >30 in the past year (OR=6.4, 95% CI 1.5 to 27.1). The strongest two-variable and three-variable risk factors included weekly mileage >30+ stress fracture history (OR=17.3, 95% CI 1.6 to 185.6) and weekly mileage >30+<85% expected weight + stress fracture history (OR=17.3, 95% CI 1.6 to 185.6), respectively. Risk factors were cumulative when predicting low BMD (including <85% expected weight, weekly mileage >30, stress fracture history and <1 serving of calcium-rich food/day): 0–1 risk factors (11.1%), 2 risk factors (42.9%), or 3–4 risk factors (80.0%), p<0.001).Conclusions Male adolescent runners exhibited lower body weight, BMI and spine BMD Z-score values. The risk of low BMD displayed a graded relationship with increasing risk factors, highlighting the importance of using methods to optimise bone mass in this population.