Title

Can Physical Characteristics and Sports Bra Use Predict Exercise-Induced Breast Pain in Elite Female Athletes?

Publication Name

Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine

Abstract

OBJECTIVE: To evaluate whether a simple 4-factor model using self-reported data could be used to predict exercise-induced breast pain in elite female athletes. DESIGN: Survey study. SETTING: Online or hard-copy surveys completed at sporting competitions and training facilities around Australia. PARTICIPANTS: Four hundred ninety female athletes competing nationally or internationally across 49 sports. INDEPENDENT VARIABLES: A binomial logistic regression analysis was used to evaluate the strength of a predictive model that included 2 continuous independent variables (age and body mass index) and 2 binary independent variables (breast size and sports bra use). Odds ratios were also calculated to determine the likelihood of an athlete reporting exercise-induced breast pain in association with each of the 4 variables. MAIN OUTCOME MEASURES: Exercise-induced breast pain was the binary dependent variable. RESULTS: The model incorporating athlete age, breast size, body mass index, and sports bra use was found to be statistically significant, but weak, in its ability to predict exercise-induced breast pain in elite female athletes (correctly identified 66% of athletes). For every 1-year increase in age, a significant 2.6% increase in the likelihood of experiencing exercise-induced breast pain was observed. Athletes with medium-to-hypertrophic sized breasts were 5.5 times more likely to experience exercise-induced breast pain than athletes with small breasts. CONCLUSIONS: Although the current model was not sensitive enough for use by clinicians and coaches, age and breast size were both identified as critical variables in the prediction of exercise-induced breast pain. Future research is encouraged to investigate whether incorporating additional variables such body fat percentage, bra fit, and other relevant factors can add strength to the model.

Open Access Status

This publication is not available as open access

Volume

31

Issue

6

First Page

e380

Last Page

e384

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Link to publisher version (DOI)

http://dx.doi.org/10.1097/JSM.0000000000000831