Limitations of athlete-exposures as a construct for comparisons of injury rates by gender/sex

Key points

1. 01AEs are an aggregate group-level measure and do not reflect time individual athletes actually spend exercising or competing.
2. 02Women's teams often have lower training-to-match ratios than men's, meaning competition AEs (where injury risk is up to 10 times higher) are over-represented in women's cumulative AE counts.
3. 03Smaller roster sizes in women's sports inflate injury rates calculated per AE because each woman athlete covers a greater proportion of total playing time.
4. 04A 2014 validation substudy found retrospectively calculated aggregate AEs overestimated the team's actual exposure by 27% for both men and women.
5. 05Five recommendations are offered: disaggregate training and competition AEs, control for T:M ratio, use individual player-hours, collect richer qualitative data, and contextualise findings within gendered structural inequities.

How it was conducted

Design

Narrative review with theory-driven exploratory snowball literature searches

Databases

PubMed/MEDLINE and relevant scientific databases; builds on two prior systematic reviews as a foundational reference

Focus

Limitations of athlete-exposures for comparing ACL injury rates by gender/sex, with separate analytical streams on training-to-match ratio and team roster size

Scope

Sports injury epidemiology literature using AEs, combined with studies on gendered processes in sport

Framework

Gendered hypothesis framework (Parsons et al.) guiding critique of AE construct assumptions

What they found

• A 2014 validation substudy found retrospectively calculated aggregate AEs overestimated the team's exposure by 27% for both men and women.
• In a worked ice hockey example with the same one ACL injury per game, using game-participant AEs yields an injury rate of 5.3 per 100 AEs for men and 5.9 per 100 AEs for women; using full roster AEs yields 3.6 per 100 AEs for men and 4.0 per 100 AEs for women, despite identical minutes of gameplay.
• Women's T:M ratio among Swedish elite football players was 13% lower than men's teams in two different studies.
• An international meta-analysis found the proportion of injured athletes (percentage of athletes who were injured) was the same for women and men, despite women's injury rate per unit time being twice as high, suggesting men's lower rates may be partly driven by higher training volume.
• Finnish 15-year-old male athletes averaged 2.5 more hours of training per week than girls.
• NCAA ISS data showed women's basketball teams averaged 64 practices per season versus 71 for men; women's ice hockey averaged 60 versus 66 for men (most pronounced in Division III).
• Expenditures on collegiate Division I men's sports in the USA are double that of women's sports.
• ACL injury risk is up to 10-fold higher during matches compared with training sessions.

Limitations

• Narrative review methodology does not allow quantification of the actual magnitude of bias introduced by AE miscounting in published gender/sex disparity estimates.
• No studies directly quantifying the effect of T:M ratio differences on observed gender/sex ACL injury rate disparities were found in the literature at the time of writing.
• The review focuses on structural measurement issues and does not resolve the question of how much of the observed disparity is attributable to biological versus contextual factors.
• Evidence on gendered differences in training quality, facilities, and load is largely indirect and drawn from heterogeneous sources across sports and countries.

Why it matters

For patients

Women athletes and their families should know that published statistics suggesting women have 2 to 10 times the ACL injury risk of men may be partly a measurement artefact rather than a pure reflection of biological vulnerability.

For clinicians

Clinicians and researchers using AE-based injury rates to counsel athletes or design prevention programmes should treat crude cross-sex comparisons with caution and seek studies that disaggregate training and competition exposures and account for roster size.

For readers

The paper provides a methodological critique useful for epidemiologists, sports scientists, and policy makers interested in rigorous measurement of injury disparities and in addressing structural inequities in women's sport.