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Br J Sports Med. Author manuscript; available in PMC 2019 August 01.
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Published in final edited form as:

Br J Sports Med. 2019 August ; 53(16): 1003–1012. doi:10.1136/bjsports-2016-096274.

“What’s my risk of sustaining an ACL injury while playing

sports?” A systematic review with meta-analysis
Alicia M Montalvo1, Daniel K Schneider2,3, Laura Yut4, Kate E Webster5, Bruce Beynnon6,
Mininder S Kocher7, Gregory D Myer3,8,9,10
1Department of Athletic Training, Florida International University, Nicole Wertheim College of
Nursing and Health Sciences, Miami, Florida, USA
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2College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA

3Division of Sports Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
4Department of Biostatistics, Robert Stempel School of Public Health and Social Work, Florida
International University, Miami, Florida, USA
5Schoolof Allied Health, College of Science, Health and Engineering, La Trobe University,
Melbourne, Australia
6Department of Orthopedics and Rehabilitation, University of Vermont College of Medicine,
Burlington, Vermont, USA
7Department of Orthopedic Surgery, Harvard Medical School, Boston, Massachusetts, USA
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8Division of Sports Medicine, Boston Children’s Hospital, Boston, Massachusetts, USA

9Athletic
Training Division, School of Allied Medical Professions, The Ohio State University,
Columbus, Ohio, USA
10The Micheli Center for Sports Injury Prevention, Waltham, Massachusetts, USA

Abstract
Objective—To estimate the incidence proportion (IP) and incidence rate (IR) for ACL injury in
athletes.

Design—Systematic review with meta-analysis

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Correspondence to Dr Gregory D Myer, Division of Sports Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati OH
45229, USA; greg.myer@cchmc.org.
Contributors AMM, DKS, KEW, BB, MSK, and GDM worked on concept, writing, and approving the final draft. LY worked on
analysis, interpretation, writing, and approving the final draft.
Correction notice This article has been corrected since it was published Online First. The ‘Contributors’ section has been updated.
Collaborators Emir Veledar, PhD, Robert Stempel School of Public Health and Social Work, Florida International University, Miami,
Florida, USA
Competing interests None declared.
Patient consent Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement All data from this review are available from the journals in which they were published.
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Data sources—The PubMed, CINAHL and SpORTDiscus electronic databases were searched
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from inception to 20 January 2017.

Eligibility criteria for selecting studies—Studies were included if they reported total
number of participants/population by sex, total number of ACL injuries by sex and total person-
time by sex.

Results—Fifty-eight studies were included. The IP and IR of ACL injury in female athletes were
3.5% (1 out of every 29 athletes) and 1.5/10 000 athlete-exposures over a period of 1 season-25
years. The IP and IR of ACL injury in male athletes were 2.0% (1 out of every 50 athletes) and
0.9/10 000 athlete-exposures over a period of 1–25 years. Female athletes had a higher relative
risk (RR) for ACL injury compared with males (RR=1.5; 95% CI 1.2 to 1.9; P<0.01) and a higher
incidence rate ratio (IRR) of ACL injury compared with males over 1 season–25 years (IRR=1.7;
95% CI 1.4 to 2.2; P<0.010). When accounting for participation level, the disparity in the IR
between female and male athletes was highest for amateur athletes compared with intermediate
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and elite athletes (IRR=2.1; 95% CI 1.3 to 3.4; P<0.01; I2=82%). Amateur female athletes
remained at higher risk of ACL injury than did with amateur male athletes. In studies where
follow-up length was <1 year, female athletes had a higher IR of ACL injury than did to males
(IRR=1.7; 95% CI 1.3 to 2.2; P<0.01). Where follow-up was 1 year and beyond, there was no sex
difference in the IR of ACL injury (IRR=2.1; 95% CI 0.9 to 4.8; P=0.06; I2=65%).

Summary/conclusions—One in 29 female athletes and 1 in 50 male athletes ruptured their

ACL in a window that spanned from 1season to 25 years. The IR of ACL injury among female
athletes in a season was 1.7 times higher than the IR of ACL injury among male athletes and the
IP of ACL injury among female athletes was 1.5 times higher than the IP of ACL injury among
male athletes. The reported sex disparity in ACL injury rates is independent of participation level
and length of follow-up.
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Studies that control for athletic exposure and population size suggest that female athletes
may be at greater risk than male athletes for ACL injury.12 These findings have underscored
the substantial research focus on injury mechanisms and injury prevention approaches for
female athletes.3–7 ACL injuries present a significant healthcare burden. In addition to the
financial burden, ACL injury can have significant personal costs and may result in the loss of
a sport season, the loss of sport scholarships, reduced academic performance, long-term
disability and increased risk of developing knee osteoarthritis.89

Estimates for the increased risk of injury in females relative to males exist for certain sex-
comparable sports.12 This information is useful for those sports; however, the same
information is not available for all sports. To compare the rates of injury in male and female
athletes in a research study, the conditions for data collection must be identical. If the data
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collection methods of two studies investigating sex-comparable sports differ, it is not

possible to compare the risk of injury. Therefore, meta-analysis may be a useful tool for
estimating ACL injury rates. While previous meta-analyses comparing the rates on ACL
injury incidence in male and female athletes have been conducted, they were either specific
to one participation level (eg, high school only) or did not include all sports for which
information was available.1011 Therefore, the purpose of this systematic review was to

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estimate and compare the incidence proportions and incidence rates of ACL injury in male
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and female athletes.

METHOD
A systematic review was conducted using the Preferred Reporting Items for Systematic
Review and Meta-Analysis guidelines. We searched the PubMed and EBSCO host
(CINAHL, SPORT-Discus) electronic databases from database inception to 20 January 2017.
The following phrase was used in the search: anterior cruciate ligament AND (injury OR
tear OR rupture) AND (incidence OR prevalence OR epidemiology). We limited the search
to peer-reviewed articles published in English language. Experts in the field were contacted
for further study suggestions, and references from review papers were examined to identify
any further relevant articles for potential inclusion. Publication details from all studies
identified in the literature search were exported to bibliographic software (EndNote V.X7,
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Thomson Reuters, USA).

Selection criteria
One assessor screened articles for inclusion. Any grey areas of inclusion were brought to
discussion with a second assessor and any disagreements were arbitrated by a third assessor.
Articles were screened first by title, then by abstract and finally by full text according to the
inclusion and exclusion criteria (box 1). We defined organised sport as a school-based,
organised recreational or professional sport. Full texts were retrieved when the title or
abstract met the selection criteria, or when the status (include or exclude) could not be
determined from the title and/or abstract alone.

Data extraction and management

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The primary variables extracted were the number of ACL injuries, the person-time for each
sex, type of exposure, length of follow-up (<1 year, 1 year or >1 year), participation level
(amateur, intermediate and elite). Participation level was defined as follows: amateur
included recreational, high school and intramural athletes; intermediate included collegiate
and semi-professional athletes and elite included elite and professional athletes. One author
extracted data from all included articles (AMM) and another author independently reviewed
these data for accuracy and completeness (DKS). Studies used for incidence proportion and
incidence rate analyses are listed in online supplementary file 1.

The reported person-time unit was not uniform across studies. To establish a common
metric, we calculated athlete-exposures (AE). When the number of player-hours were
reported, AEs were estimated by multiplying the number of player-hours by 2. This was to
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estimate the average length of training sessions and games with warm-ups included.12–30
Player-days were treated as AEs as athletes typically participate in one practice or game per
day. This unit was only used in studies that investigated high school and college athletes.12
For studies that reported incidence rate by sex, the number of AEs and the reported
incidence rates were used to calculate the number of ACL injuries by sex (number ACL
injuries by sex=total AE by sex×rate numerator by sex/ rate denominator by sex).153132

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Whenever possible, the incidence proportion and incidence rate were calculated. The
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incidence proportion was calculated by dividing the number of new ACL injuries by the total
number of participants over the given time period specified in each study. The denominator
for incidence proportion ranged from 1 season to 25 years. The incidence rate was calculated
by dividing the total number of new ACL injuries by the total number of exposures. We
emailed the authors of studies where the number of ACL injuries by sex could not be
estimated. If the study authors did not have access to the information or did not respond to
our email, the study was excluded from the meta-analysis.33–40

Risk of bias assessment

Risk of bias was assessed by two authors independently (AMM, DKS) using the Quality
Assessment Tool for Observational Cohort and Cross-Sectional Studies.41 This tool
dichotomously assesses criteria including participation rate, whether exposure data were
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collected prospectively, whether the timeframe was sufficient to allow for the outcome to
occur, number of participants lost to follow-up after baseline, etc. If the criterion was
present, the item was given a ‘Y’. If the criterion was absent or was not reported, the item
was given an ‘N’. Any discrepancies in assessment were discussed. For discrepancies that
could not be resolved, a third author was consulted for arbitration (GDM). Studies where
interventions were administered were treated as cohort studies in our analyses, and assessed
using the same tool.

Statistical analysis
Injury data were analysed using R (V3.3.2, the R Foundation for Statistical Computing). We
used the packages meta and metafor with the functions metarate for incidence rate, metaprop
for incidence proportion single ratio, metainc for incidence rate ratio (IRR) and metabin for
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incidence proportion binary data ratio (weighted for individual study size). For calculating
incidence proportion and incidence rate for the total population, female athletes only and
male athletes only, all studies that presented data were included in the respective analyses.
When calculating the relative risks (RRs) and IRRs only studies that presented both females
and males in the same study were used. For example, studies that included only females
were used to calculate female incidence proportion and incidence rate, but were not used to
calculate RR or IRR.

Injury risk proportions for individual studies and pooled estimates were summarised in
forest plots for the following subgroups: female, male, combined. A pooled estimate for the
RR of ACL injury in females versus males was calculated and summarised a forest plot.
Raw injury incidence rates for individual studies and pooled estimates were summarised in
forest plots for the following groups and subgroups: female, male, combined. Pooled IRRs
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for females versus males were calculated and summarised in forest plots. Heterogeneity was
assessed using the I2 statistic,42 which estimates the variation resulting from heterogeneity
and not chance.42 I2 values over 75% were considered high.42 Publication bias was assessed
using funnel plots with SE as the measure of the study size on the y-axis and the ratio on the
x-axis. A P value of ≤0.05 was considered to be significant for all statistical analyses.

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Sensitivity analyses—To account for heterogeneity among studies, we used sensitivity

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analysis to assess the effect of each individual study on the overall rate of ACL injury. This
was done by removing one study, performing the analysis, investigating the effect of the
removal on heterogeneity, adding the study back to the analysis and repeating the procedure.
This was repeated for each individual analysis included.

To account for bias, we attempted to perform separate analyses on studies that met the
criteria for item 11 (reliability and validity of measurement of the dependent variable) and
item 14 (statistical adjustment for potential confounding variables). However, there were too
few studies that met the criteria. Therefore, we included all studies in the final analysis
(regardless of heterogeneity) because we expected that combining sports with varying risks
of ACL injury would result in high heterogeneity. Sources of heterogeneity will be further
explored in future analyses of the same data set.4344
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Subgroup analyses—To account for variations in length of follow-up, we compared

incidence rates from studies with follow-up lengths of up to 1 year and >1year. To account
for differences in participation levels, we compared incidence rates from amateur,
intermediate and elite athletes.

RESULTS
The final search yield was 3774 abstracts. After removal of duplicates, there were 1300
records for screening. After title and abstract screening, 1155 articles were excluded. The
remaining 145 articles were manually cross-referenced and experts were consulted to
identify additional relevant articles, resulting in inclusion of 17 additional articles. We
screened the full texts of 162 articles, and 58 studies were included (figure 1).12–3245–81
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Risk of bias assessment

Studies that fulfilled fewer than 50% of criteria were deemed to be of low quality. Three
studies fulfilled 75% or more of the criteria and 44 studies fulfilled 50% or more the criteria
(see online supplementary file 2). Fourteen studies fulfilled fewer than 50% of the criteria
and were deemed to be of low quality. Studies may have received low or moderate
assessment for lack of reporting information. The potentially unreported criteria include
total number of eligible individuals, how outcomes were measured and attrition.

The pooled ACL injury incidence proportion for all athletes was 2.8% (95% CI 2.4% to
3.3%; I2=99%) figure 2), which equates to 1 ACL injury in every 36 athletes. The pooled
ACL injury incidence proportion for female athletes was 3.5% (95% CI 2.6% to 4.5%; I2 =
98.0%; figure 3), which translates to 1 ACL injury in every 29 female athletes. The pooled
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ACL injury incidence proportion for male athletes was 2.0% (95% CI 1.6% to 2.5%;
I2=99%; figure 4), which translates to 1 ACL injury in every 50 male athletes. The RR for
ACL injury was 1.5 times higher in female athletes compared with male athletes (RR=1.5;
95% CI 1.2 to 1.9; P<0.01; P = 61%, figure 5). A list of included sports for each sex and the
studies used for each analysis are located in online supplementary file 1.

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ACL injury incidence among all athletes was 1.5 per 10 000 AEs (95% CI 1.2 to 2.0;
I2=99%; figure 6). Female injury incidence was 1.9 ACL injuries per 10 000 AEs (95% CI
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1.6 to 2.4; I2=94%; figure 7) and male injury incidence was 0.9 ACL injuries per 10 000
AEs (95% CI 0.7 to 1.1; I2=94%; figure 8). Females athletes had a 1.7-fold increase in
incidence rate of ACL injury relative to male athletes (95% CI 1.4 to 2.2; P<0.010; I2=87%;
figure 9).

The IRR) for amateur athletes was 2.1 (95% CI 1.3 to 3.4; P<0.01; I2=82%; figure 10). The
IRR was lower for elite athletes (IRR=1.7; 95% CI 1.1 to 2.8; P = 0.25; I2=25%) and for
intermediate athletes (IRR=1.3; 95% CI 0.9 to 1.7; P<0.01; I2=88%).

With regard to variations resulting from length of follow-up, the subanalyses indicated that
there were differences between sexes with regard to ACL injury incidence rate. The IRR for
a follow-up length of <1 year was 1.7 (95% CI 1.3 to 2.6; P<0.01; I2=89%; figure 11). The
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IRR for a follow-up length of 1 year or greater was 2.1 (95% CI 0.9 to 4.8; P = 0.06;
I2=65%). While female athletes were at great risk of ACL injury when follow-up was <1
year, this risk was not significant with longer follow-up length. Heterogeneity remained high
for studies with a follow-up length of <1 year, but was acceptable in studies with a follow-up
length of 1 year or greater.

Sensitivity analyses
Excluding single studies from each analysis did not alter the statistical heterogeneity (I2
statistic). Heterogeneity remained high (> 75 %) throughout the procedure. Excluding
studies that did not fulfil item 11 in the risk of bias assessment did not statistically alter the
pooled estimates for ACL injury incidence, and heterogeneity remained high. Excluding
studies that did not fulfil item 14 in the risk of bias assessment did not statistically alter the
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pooled estimates for total ACL incidence rate and female ACL injury incidence rate. There
were insufficient studies to conduct sensitivity analyses (excluding studies that did not fulfil
item 14) for the other ACL injury outcomes.

Publication bias
The funnel plot for RR indicated that almost all studies used for the analysis fell within the
expected parameters, most with low SE indicating that most studies were large (see online
supplementary file 3). A majority of studies showed females tend to have greater incidence
proportion, but to varying degrees. The funnel plot for IRR indicated that most studies fell
within the expected parameters (see online supplementary file 4). SE was relatively low,
indicating that studies were large, and a majority of studies showed that females were at
increased risk relative to males. The studies are not evenly distributed in the funnel, with
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studies missing from the lower left quadrant. Studies in the lower left quadrant would
represent smaller studies that show a greater incidence proportion or incidence rate of ACL
injuries in males relative to females. It is possible this quadrant is lacking studies due to
publication bias. Therefore, we deemed that the publication bias was low.

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DISCUSSION
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The incidence proportion and incidence rate of ACL injury in female athletes were 3.5% and
1.5/10 000 AEs, respectively. The incidence proportion and incidence rate of ACL injury in
male athletes were 2.0% and 0.9/10 000 AEs, respectively. Overall, female athletes had 1.5
times the incidence proportion and a 1.7-fold increase in the incidence rate of ACL injury
compared with males. When controlling for follow-up length (<1 year, or approximately one
season), females maintained about the same increased incidence of ACL injury. Female
athletes had a higher incidence of ACL injury in a season (independent of participation
level), compared with male athletes. There was no difference in injury incidence after 1 year
between male and female athletes.

We attempted to answer the following research questions: (1) What are the incidence
proportions and incidence rates of ACL injuries for all athletes, female athletes and male
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athletes? and (2) Are there sex differences in RR and IRR of ACL injuries? When pooling
data to answer our review questions, there was a trade-off between including more studies,
and producing spurious estimates when pooling statistically and clinically heterogeneous
data. We did not exclude studies based on either risk of bias or level of evidence, and we
judged the risk of bias in included studies as moderate because most included studies
(44/58) met 50% or more of the criteria. Moreover, many criteria that were not met were not
relevant to epidemiological study quality. However, the large number of included studies
enhances the generalisability of our results. Based on the Centre for Evidence Based
Medicine, these estimates would receive a Grade of Recommendation of C (level 4 evidence
included).82

Our findings support previous research suggesting that female athletes have a 1.5 times
increased risk for ACL injury compared with male athletes.10 One possible explanation for
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the disparity between sexes with regard to ACL injury risk may be differences in modifiable
and non-modifiable risk factors. Female athletes may have greater quadriceps activation
relative to hamstring activation (quadriceps dominance), greater reliance on stability from
ligaments than muscles (ligament dominance), increased strength and coordination in one
leg over the other (limb dominance) and altered neuromuscular control of the trunk (trunk
dominance) compared with male athletes.3683

There was a 1.7-fold increase in incidence of ACL injuries in females compared with males.
One explanation for this might be the increasing number of females participating in sport,
and female athletes spending more time participating in sport (ie, the exposure is greater).84
This is especially true in higher risk sports, such as soccer and rugby.85–87 Therefore,
continued implementation of rigorous injury surveillance programmes may be important to
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monitor injury incidence among female athletes. Sports medicine clinicians should be aware
of both the sex-specific increased risk of suffering ACL injury in order to prepare strategies
that are optimised for sexes. Specifically, efforts to enhance coaches’ understanding of sex-
specific risk factors for ACL injury indicate that training programmes are not one-size-fits-
all and programmes need to be specifically adjusted to suit the deficits of female athletes
(including specific injury prevention strategies). However, the focus on ACL injury

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prevention strategies should not be at the expense of male athletes— injury prevention and
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tailored training programmes are equally important for both sexes.

Methods issues
There are three issues related to systematic review methods that must be considered when
reading and using the results of our systematic review.

Risk of bias assessment—Poor internal validity (bias within studies) may have
contributed to statistical heterogeneity, and precision in effect estimates. Assessing the risk
of bias in epidemiological studies can be challenging because the tools available cover
methodological issues that do not necessarily contribute to bias in observational studies. For
example, existing tools assess whether or not subjects were randomised. However,
randomisation is not relevant when investigating whether or not a condition of interest is
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diagnosed in subjects. Items like this negatively impact risk of bias even though they are
irrelevant to the study design or research question. Despite the limitations regarding the
assessment of risk of bias, there was bias in included studies. Therefore, caution should be
exercised in generalising rates and risks.

Sources of variability—The high I2 statistics in our analyses indicate that the variability
in injury rates was due to heterogeneity rather than to chance. One explanation for the high
I2 in incidence proportion estimates and ACL injury incidence rate is that we pooled data
from studies of different types of sports, with differing risks for ACL injury. Our intention
was to provide general estimates of ACL injury, not sport-specific estimates. Subsequent
sport-specific analyses on the same dataset are forthcoming.44 We also intended to provide
relative estimates of ACL injury in female compared with male athletes. However,
conclusions regarding sex differences in ACL injury risk cannot be drawn about specific
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sports.

Exposure data varied among studies, and we estimated exposure in some studies. Conversion
may also have resulted in an underestimate of the true exposure, which would cause an over-
estimation of the incidence rates. Differences in participation level and length of follow-up
likely also contributed to statistical heterogeneity.

Sensitivity and subgroup analyses—We used sensitivity and subgroup analyses based
on participation level and length of follow-up to explore potential sources of heterogeneity.
However, statistical heterogeneity remained high in all sensitivity and subgroup analyses.
We were unable to determine the main sources of statistical heterogeneity, and this reduces
the robustness of the estimates in our systematic review.
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Limitations
Incidence proportions and rates may have been overestimated in some instances by the
inclusion of re-injuries; however, the inclusion of re-injuries is likely a small source of bias.
Some studies only included non-contact mechanisms of injury. Therefore, the estimates
provided here may be underestimates of the true rates, although it is difficult to be certain.
Incidence rates were based on estimated AE for 18 of 38 studies included for rate analyses.

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We employed broad inclusion criteria that captured a wide range of studies to enhance
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generalisability. This entailed including studies that investigated only males and only
females, which is another limitation. The lack of homogeneity negatively affects the
conclusions that may be drawn from the data.

With regard to the length of follow-up for the incidence proportion estimate, a large range of
follow-up periods that made it difficult to standardise. Incidence proportions require a unit
of time (eg, 1-year or 2-year incidence proportion). In this review, the length of follow-up in
included studies ranged from one season to 25 years. However, there were very few studies
with follow- up >1 year. We found that the sex-differences in incidence rate was maintained
when follow-up was <1 year. The sex-difference in ACL injury incidence was not significant
beyond 1 year.

We did not assess the influence of age on the injury estimates because many studies did not
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specify participant age or age range. Controlling for age would have substantially reduced
the number of studies eligible for inclusion. While the search was systematic and
comprehensive, we acknowledge the risk of publication and language bias associated with
the current report.

Future research
Whenever possible, future research should investigate injury epidemiology in male and
female athletes simultaneously to allow for sex comparisons in future meta-analysis. This is
especially true for sports that are not frequently investigated, such as gymnastics and skiing,
and for sports that are growing in popularity, such as rugby. This research should use the
most specific exposure units possible, such as player-hours, and should detail exact length of
follow-up in months or years. Because sport season lengths can vary by location, age and
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participation level, detailing follow-up length this way is particularly important for
standardising the period of time over which exposures are occurring.

Future research should also investigate sport-specific differences in incidence rates between
females and males. Making sport-specific distinctions will help to identify where the
greatest disparities between sexes lie and which populations could benefit the most from
preventive strategies such as neuromuscular training, which can reduce the rate of ACL
injury and improve performance.88–91 Addressing aspects of injury prevention, risk factor
assessment and athletic performance with a protocol targeted towards younger athletes at the
highest risk of ACL injury has important implications for helping to support injury-free
sport participation.9293
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CONCLUSION
Female athletes had 1.5 times greater risk of sustaining an ACL injury compared with male
athletes. One in 29 female athletes sustained an ACL injury, and 1 in 50 male athletes
sustained an ACL injury over 25 years. The reported sex disparity in ACL injury rates was
independent of participation level and length of follow-up.

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Supplementary Material
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Refer to Web version on PubMed Central for supplementary material.

Acknowledgements
The authors would like to acknowledge funding support from the National Institutes of Health/NIAMS Grant
U01AR067997.

Funding The authors have not declared a specific grant for this research from any funding agency in the public,
commercial or not-for-profit sectors.

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Box 1
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Inclusion and exclusion criteria

Inclusion criteria
► Research conducted in athletes playing organised sports

► Total number of ACL injuries and total number of individuals in the

population by sex reported

► Reported data such that the number of ACL injuries by sex could be
calculated

Exclusion criteria

► Further analyses on previously reported prospective studies

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► Studies published in languages other than English

► Review articles
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What is already known?

► Total and sex-specific estimates of ACL injury incidence proportions and

incidence rates have been reported in isolation, but the overall risk of ACL
injury including all sports is relatively unknown.
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What are the new findings?

► One in 29 female athletes and 1 in 50 male athletes ruptured their ACL in a

window that spanned between 1 season and 25 years.

► The incidence rate of ACL injury among female athletes in a season was 1.7
times higher than the incidence of ACL injury among male athletes.

► The incidence proportion of ACL injury among female athletes was 1.5 times
higher than the incidence proportion of ACL injury among male athletes.

► The sex differences in ACL injury rates were independent of participation

level.
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Figure 1.
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Flow chart summary of the article screening process.

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Figure 2.
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Forest plot for the incidence proportion and 95% CI of ACL injury in male and female
athletes.

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Figure 3.
Forest plot for incidence proportion and 95% CI of ACL injury for female athletes.
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Figure 4.
Forest plot for incidence proportion and 95% CI of ACL injury for male athletes.
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Figure 5.
Forest plot for relative risk (RR) and 95% CI of ACL injury in athletes—female vs male.
<1=reduced RR in females; >1=reduced RR in males.
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Figure 6.
Forest plot for total incidence rate and 95% CI of ACL injury in athletes for males and
females combined.
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Figure 7.
Forest plot for incidence rate and 95% CI of ACL injury for female athletes.
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Figure 8.
Forest plot for incidence rate and 95% CI of ACL injury for male athletes.
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Figure 9.
Forest plot for incidence rate and 95% CI of ACL injury for in athletes—female vs male.
<1=reduced relative risk in females; >1=reduced relative risk in males.
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 Montalvo et al. Page 27
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Figure 10.
Forest plot for incidence rate and 95% CI of ACL injury in athletes—female vs male by
participation level. <1=reduced relative risk in females; >1=reduced relative risk in males.
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Figure 11.
Forest plot for incidence rate and 95% CI of ACL injury for in athletes—female vs male by
length of follow-up. <1=reduced relative risk in females; >1=reduced relative risk in males.
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