Over 60% of female/woman/girl athlete injuries involve the lower-extremity (e.g., groin, hip, thigh, knee, calf, ankle, foot) (1). These injuries disrupt training and competition, increase recurrent injury risk, and can have long-term health consequences. To reduce these injuries, medical and performance teams are often encouraged to target ‘modifiable risk factors’ such as biomechanics, movement patterns, strength, or training load, but how strong is the evidence behind this advice? This blog summarises a recent systematic and meta-analysis that aimed to answer this question, and inform the International Olympic Committee Female woman and girl Athlete Injury pRevention (FAIR) Consensus (2).

Why was the review important?

Female/woman/girl athletes experience different injury patterns than male/man/boy athletes, yet most injury prevention practices are based on evidence from male/man/boy sport. Without a good understanding of risk factors for female/woman/girl athlete lower-extremity injuries, prevention strategies default to assumptions rather than evidence. This gap can lead and over-emphasis of factors with uncertain benefit, perpetuate myths (e.g., role of hormones, menstrual cycle, anatomical features), and divert attention from contextual factors that disadvantage female/woman/girl athletes such as limited resources, less training time and support (3, 4). A systematic review can address this problem by combining evidence across studies to clarify what is known and what is not.

What did we do?

We searched nine databases for studies that examined potential modifiable risk factors for female/woman/girl athlete lower-extremity injuries. Where possible, we pooled results across similar studies using meta-analyses. When this was not possible, we used semi-quantitative syntheses. We also graded the certainty of evidence for each risk factor.

What did we find?

We included 195 studies involving 1,525,662 participants, but only 2.4% were females/women/girls. Across the 59% of studies that reported female/woman/girl-specific data, 66 potential risk factors were investigated. There were enough studies to pool data for body mass and body mass index, weekly training distance, muscle strength, artificial turf, off-season plyometric training, readiness to return-to-sport, hop asymmetry, and vertical drop jump biomechanics, while an additional 26 factors were assessed with semiquantitative synthesis. Three key messages emerged

• Female/woman/girl athletes were under-represented. Fewer than 3% of participants were females/women/girls, and 40% of studies did not report female/woman/girl-specific data.
• The certainty of evidence is low to very low. Most potential ‘modifiable risk factors’ were studied in one study, and when we could pool data from several studies, the certainty of the conclusion was low or very low. As a result, the practical value of targeting factors like strength, flexibility, movement characteristics, or training load is unclear, not because they are not important, but because the evidence is not there.
• There is no single modifiable driver of injury. Female/woman/girl athlete lower-extremity risk is multifactorial and cannot be explained by one factor alone.

What are the key take home messages?

This review provides important guardrails for female/woman/girl injury prevention practice:

• Be cautious with simple explanations. Female/woman/girl athletes lower-extremity injuries are unlikely to be explained, or prevented by addressing a single modifiable factor.
• Avoid over-interpreting weak evidence. Some common screening or injury prevention strategies may lack strong female/woman/girl-specific support.
• Stick with best-practice principles. Progressive strength training, appropriate exposure to sport demands, and individualised load management remain reasonable injury prevention targets, even if their precise protective effects are uncertain.
• Advocate for better data. Female/woman/girl-specific data and adequately powered studies are essential to developing injury prevention strategies grounded in evidence rather than assumptions.

By highlighting what is known and unknown, this review provides a starting point for future research to understand modifiable risk factors to enhance female/woman/girl athlete lower-extremity injury prevention. Progress will depend on collaboration and a shared commitment to expanding female/woman/girl athletes’ participation and visibility in sport injury prevention research.

References

1. Whittaker JL, Raisanen AM, Martin C, et al. Modifiable risk factors for lower-extremity injury: a systematic review and meta-analysis for the Female, woman and/or girl Athlete Injury pRevention (FAIR) consensus. Br J Sports Med 2025;59(21):1499–513. doi: 10.1136/bjsports-2025-109902 [published Online First: 20251126]
2. Crossley KM, Whittaker JL, Patterson B, et al. Female, woman and/or girl Athlete Injury pRevention (FAIR) practical recommendations: International Olympic Committee (IOC) consensus meeting held in Lausanne, Switzerland, 2025. Br J Sports Med 2025;59(22):1546–59. doi: 10.1136/bjsports-2025-110889 [published Online First: 20251203]
3. Parsons JL, Coen SE, S B. Anterior cruciate ligament injury: towards a gendered environmental approach. Br J Sports Med 2020;Online First: 10 March 2021 doi: 10.1136/bjsports-2020-103173
4. Coen SE, Downie V, Follett L, et al. Gendered environmental pathways to sports injury: insights from retired athletes in the UK high-performance context. Br J Sports Med 2024 doi: 10.1136/bjsports-2024-108717 [published Online First: 20241203]

Authors:

Jackie L. Whittaker [1, 2, 3]

Garrett Bullock [3, 4]

Justin M. Losciale [5, 6]

Chelsea Martin [7]

Maitland Martin [3]

Carolyn A. Emery [3]

Affiliations:

1. Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
2. Arthritis Research Canada, Vancouver, Canada 
3. Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
4. Department of Orthopaedic Surgery & Rehabilitation, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
5. Informatics, Decision-Enhancement and Analytic Sciences Centre of Innovation, George E. Wahlen Veteran Affairs Medical Centre, Salt Lake City, USA
6. Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, USA
7. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, North Carolina, USA

Twitter/X:

@jwhittak_physio