Abstract
ning is associated with a higher risk of overuse injury than other forms of aerobic exercise such as walking, swimming and cycling. An accurate description of the proportion of running in- juries per anatomical location and where possible, per specific pa- thology, for both genders is required. The aim of this review was to determine the proportion of lower limb running injuries by an- atomical location and by specific pathology in male and female runners (≥800m - ≤ marathon). The preferred reporting items for systematic reviews and meta-analyses guidelines were followed for this review. A literature search was performed with no re- striction on publication year in Web of Science, Scopus, Sport- Discus, PubMed, and CINAHL up to July 2017. Retrospective, cross-sectional, prospective and randomised-controlled studies which surveyed injury data in runners were included. 36 studies were included to report the overall proportion of injury per ana- tomical location. The overall proportion of injury by specific pa- thology was reported from 11 studies. The knee (28%), ankle-foot (26%) and shank (16%) accounted for the highest proportion of injury in male and female runners, although the proportion of knee injury was greater in women (40% vs. 31%). Relative to women, men had a greater proportion of ankle-foot (26% vs. 19%) and shank (21% vs. 16%) injuries. Patellofemoral pain syn- drome (PFPS; 17%), Achilles tendinopathy (AT; 10%) and me- dial tibial stress syndrome (MTS; 8%) accounted for the highest proportion of specific
and female runners, although the proportion of knee injury was greater in women (40% vs. 31%). Relative to women, men had a greater proportion of ankle-foot (26% vs. 19%) and shank (21% vs. 16%) injuries. Patellofemoral pain syn- drome (PFPS; 17%), Achilles tendinopathy (AT; 10%) and me- dial tibial stress syndrome (MTS; 8%) accounted for the highest proportion of specific pathologies recorded overall. There was in- sufficient data to sub-divide specific pathology between genders. The predominate injury in female runners is to the knee. Male runners have a more even distribution of injury between the knee, shank and ankle-foot complex. There are several methodological issues, which limit the interpretation of epidemiological data in running injury. Key words: Running, injury, injury prevention, epidemiology Introduction Running is associated with a higher risk of overuse injury (Bertola et al., 2014; Hauret et al., 2015; Salmon et al., 2014) than other forms of aerobic exercise such as walking, swimming and cycling. To unlock the full potential of run- ning as a sport or a vehicle to improve health there is a need to understand the aetiology of injury. In any sport, this pro- cess begins by gaining an understanding of the most fre- quent injuries associated with that sport (Fitzharris et al., 2017). Preferably, injury epidemiology would be synthe- sized from high quality studies, using standardised defini- tions, by way of systematic review and meta-analysis. This poses a challenge to researchers due to the heterogeneity of studies in the literature, which are affected by differences in study populations, designs and injury or exposure defi- nitions. The most recent systematic reviews on running in- jury (Kluitenberg et al., 2015; Lopes et al., 2012; Nielsen et al., 2012; van der Worp et al., 2015; Videbaek et al., 2015) have highlighted issues such as a lack of standard- ised injury definitions, the classification of a runner, and the recording of exposure. To minimise the effect of study heterogeneity on the outcome variable of interest, authors of systematic reviews have used strict inclusion-exclusion criteria to answer specific questions about running injury epidemiology or injury epidemiology in specific types
al., 2015) have highlighted issues such as a lack of standard- ised injury definitions, the classification of a runner, and the recording of exposure. To minimise the effect of study heterogeneity on the outcome variable of interest, authors of systematic reviews have used strict inclusion-exclusion criteria to answer specific questions about running injury epidemiology or injury epidemiology in specific types of runners. This results in a smaller number of studies being included for review. Reviews that focus on injury inci- dence require accurate estimates of exposure (van der Worp et al., 2015; Videbaek et al., 2015). Reviews that fo- cus on the prevalence of specific injuries or injuries in a specific population of runners, are limited to those studies including a medical diagnosis or specific type of runner (Kluitenberg et al., 2015; Lopes et al., 2012). An alternative approach, albeit less sensitive and potentially subject to greater bias, is to use a broad inclu- sion criteria. This would allow inclusion of a larger popu- lation (i.e. recreational, amateur, elite, triathlon, orienteer- ing), and a broader classification of injury (i.e. hip, knee, ankle and foot). Subsequently, sub-group analyses can be performed from studies that clearly describe injury per gen- der or specific pathology. Gaining a broad understanding of the proportion of running injuries could provide a foun- dation for the investigation of risk factors associated with running injuries. Furthermore, knowledge of the anatomi- cal locations most commonly affected may assist with the development of standardised study procedures in relation to reporting injury prevalence and incidence. A number of running injury epidemiology studies have recently been published (Altman and Davis, 2016; Hespanhol Junior et al., 2016; Hespanhol Junior et al., 2017b; Kerr et al., 2016; Malisoux et al., 2016b; Smits et al., 2016; van der Worp et al., 2016), therefore the primary aim of this review was to determine the proportion of injuries in male and female runners by anatomical site. A secondary aim was to specify pathologies (self-reported or reported by a health care prac- titioner), where possible. Methods Data sources and search strategy Review article
2016; van der Worp et al., 2016), therefore the primary aim of this review was to determine the proportion of injuries in male and female runners by anatomical site. A secondary aim was to specify pathologies (self-reported or reported by a health care prac- titioner), where possible. Methods Data sources and search strategy Review article
Running injury in men and women 22 This review was prepared and conducted according to the preferred reporting items for systematic reviews and meta- analysis (PRISMA) guidelines (Moher et al., 2009). The aim of the search strategy was to find published retrospec- tive, cross-sectional, prospective and randomised-con- trolled studies that provided survey data. The following electronic databases were searched (from inception) with- out date restriction to July 2017; and included Web of Sci- ence (n = 194), Scopus (n = 215), SportDiscus (n = 72), PubMed (n = 691), SCIELO (n = 5) and CINAHL (n = 57). The last electronic search was conducted on 01/07/2018. Search terms included running* (Boolean Phrase); injury* (Boolean Phrase); prevalence* (Boolean Phrase). In addi- tion, manual searches of the reference lists of four recent running injury systematic reviews (Kluitenberg et al., 2015; Lopes et al., 2012; van der Worp et al., 2015; Videbaek et al., 2015) were undertaken by a single author (PF). All citations were imported to EndNote X7 (Thom- son Reuters, USA) and duplicates removed by PF. Articles were screened by title, abstract and finally full text, accord- ing to predetermined study criteria (Figure 1). Three au- thors (PF, CW and KS) independently reviewed all titles and abstracts, and selected those for inclusion. Disagree- ment was resolved via consensus and a third author (MIJ) was to be consulted if no agreement was reached. Full texts were reviewed by one author (PF) to determine which stud- ies met the inclusion criteria. No hand-search of specific sports medicine journals was performed. Figure 1. Flow chart of literature search. Inclusion and exclusion criteria The inclusion criteria were: (1) published peer-reviewed prospective cohort; retrospective cohort; cross-sectional; or randomised controlled studies, (2) reported running in- jury data in adult (mean age: ≥18 years) runners, (novice, recreational, amateur, elite runners, triathletes and orient- eers) competing in distances ≥800m - ≤ marathon), (3) pro- vided the anatomical location of lower limb running injury separate to other injuries/illness (e.g. upper body), (4) writ- ten in English, (5) interventions that did not alter the vol- ume of running undertaken, use strategies
in adult (mean age: ≥18 years) runners, (novice, recreational, amateur, elite runners, triathletes and orient- eers) competing in distances ≥800m - ≤ marathon), (3) pro- vided the anatomical location of lower limb running injury separate to other injuries/illness (e.g. upper body), (4) writ- ten in English, (5) interventions that did not alter the vol- ume of running undertaken, use strategies designed to di- rectly alter pain, and did not report a difference in running related injury (RRI) between intervention and control groups (e.g. the influence of footwear on running injury), (6) included shod injuries separate to barefoot injuries in studies investigating these conditions, (7) not duplicate
Francis et al. 23 publications or multiple studies on the same cohort, (8) did not include service personnel (e.g. police, fire service, mil- itary) (9) separated lower limb running injuries from other lower limb injuries (e.g. triathlon injuries divided into swim, bike and running), (10) did not recruit participants with a specific type of injury, (11) did not describe track and field competition injuries, (12) presented data as run- ning injury or any lower limb pain regardless of its inter- ference with running. Data extraction Data from included studies were extracted by a single au- thor (PF), and checked by MIJ. A standardised data extrac- tion sheet was developed by PF (available on request) where the following data related to study characteristics and injury were extracted: (1) author, year, (2) runner type, (3) gender, age, (4) injury definition, yes/no, (5) study de- sign, (6) time period for retrospective/prospective analysis (7) gender split of injuries, yes/no, (8) sampling method, (9) 6-month or 12-month follow up for prospective or ret- rospective studies respectively, yes/no, (10) the sample in- cluded versus analysed, (11) injury as self-reported, re- ported by a health professional or diagnosed by a medical doctor (12) injury proportion expressed as a total of all in- jury, yes/no, (13) consistent mode of data collection, yes/no, (14) all injuries reported, yes/no, (15) running inju- ries separate, yes/no, (16) anatomical location or specific injury identifiable, yes/no, (17) number of runners, number of injured runners, total injuries, (18) anatomical location of injury, (19) specific type of injury. The primary outcome variable was the proportion of lower limb running injury. Due to the heterogeneity of studies, studies were grouped according to anatomical location, and subsequent sub- group analyses were conducted on data pertaining to spe- cific pathologies. Injuries were categorized by the anatom- ical regions ‘hip’ (hip joint/pelvis/groin), ‘thigh’ (upper leg), ‘knee’, ‘shank’ (lower leg), ‘ankle-foot’ (including toes) and ‘other’ (not clear diagnosis/location/upper ex- tremity/illness)(Kluitenberg et al., 2015; van Gent et al., 2007). Overall injury prevalence was defined as the num- ber of injured runners divided by the total number of run- ners in the
cific pathologies. Injuries were categorized by the anatom- ical regions ‘hip’ (hip joint/pelvis/groin), ‘thigh’ (upper leg), ‘knee’, ‘shank’ (lower leg), ‘ankle-foot’ (including toes) and ‘other’ (not clear diagnosis/location/upper ex- tremity/illness)(Kluitenberg et al., 2015; van Gent et al., 2007). Overall injury prevalence was defined as the num- ber of injured runners divided by the total number of run- ners in the study. This was calculated from 26-studies where injured runners could be separated from the total number of runners and the total number of running injuries. Descriptive statistics for prevalence were calculated using SPSS. Injury proportions were defined as the total injury number per anatomical region or specific pathology di- vided by the total number of injuries reported from all sites or pathologies. Specific pathology refers to a pathology with a self-reported or confirmed medical diagnosis. Quality assessment Recent systematic reviews on running injury prevalence, incidence and risk factors have used different tools to as- sess the quality of studies (Lopes et al., 2012; Nielsen et al., 2012; van der Worp et al., 2015; Videbaek et al., 2015). Most tools that have been used can be traced back to epi- demiological or occupational studies on general musculo- skeletal pain (van der Worp et al., 2015). The tool is often modified to be more ‘running’ specific and subsequent run- ning reviews often modify it further (Nielsen et al., 2012; Videbaek et al., 2015) or propose their own criteria based on the aims of their review (Lopes et al., 2012). A score out of the total number of criteria or a percentage of positive responses (from yes-no answers) are used to express qual- ity (Kluitenberg et al., 2015; Nielsen et al., 2012; van der Worp et al., 2015). The main purpose of this study was to determine the proportion of injuries at different anatomical locations in runners and where possible specify the pathology respon- sible. The level of runner, cause, prevalence or incidence of injury were not of interest thus minimising the im- portance of methods for randomization for the quality of outcome. Therefore, we used the 10 yes/no criteria pro- posed by
study was to determine the proportion of injuries at different anatomical locations in runners and where possible specify the pathology respon- sible. The level of runner, cause, prevalence or incidence of injury were not of interest thus minimising the im- portance of methods for randomization for the quality of outcome. Therefore, we used the 10 yes/no criteria pro- posed by Lopes et al. (2012) as their review was mainly concerned with prevalence and also because the 10 criteria also encapsulated 7 of the 8 criteria recently used by Videbaek et al. (2015) to conduct a similar review. The only difference between our quality assessment and that re- ported by Lopes et al. (2012) is that where the authors used the words prevalence or incidence, we used the word pro- portion. Using yes/no criteria a positive score ≥50% is deemed a low risk of bias (Kluitenberg et al., 2015; van der Worp et al., 2015). The detailed criteria can be viewed within the supplementary material from the authors’ (Lopes et al. 2012) manuscript but briefly they are as fol- lows: 1) definition of injury reported, yes/no; 2) studies with prospective and cross-sectional designs that present proportion data, yes/no; 3) description of the population or type of runner e.g. 10km, marathon, yes/no; 4) random sampling used (i.e. not a convenience sample), yes/no; 5) data analysis performed on 80% of the participants, yes/no; 6) self-reported injury by the athlete or health care profes- sional, yes/no; 7) consistent mode of data collection, yes/no; 8) diagnosis by a medical doctor, yes/no; 9) a fol- low-up of 6 months for prospective trials or up to 12- months for retrospective trials, yes/no; 10) injury propor- tion expressed as a proportion of total injuries, yes/no. Results Characteristics of included studies The literature search yielded 1282 unique citations, of which 112 full texts were obtained and assessed for eligi- bility. Of the 112 full-text articles, 36 met the eligibility criteria and progressed to data extraction. The reasons for the exclusion of specific studies are displayed in the study flow chart (Figure 1). Of the 36 included studies, 18 were
included studies The literature search yielded 1282 unique citations, of which 112 full texts were obtained and assessed for eligi- bility. Of the 112 full-text articles, 36 met the eligibility criteria and progressed to data extraction. The reasons for the exclusion of specific studies are displayed in the study flow chart (Figure 1). Of the 36 included studies, 18 were prospective injury audits, 16 were retrospective injury au- dits, and two were a cross-sectional analyses of current in- juries. Quantitative analysis Injury proportions by anatomical location were calculated from 10,688 injuries reported from 18,195 runners in- cluded in the 36 studies. These proportions were further sub-categorised for females (n = 8 studies, 2,279 injuries) and males (n = 7 studies, 1,875 injuries). Overall injury proportions for specific pathologies were calculated from 3,580 injuries reported by 4,752 runners (n = 11 studies).
Running injury in men and women 24 There were insufficient data (n = 2 studies) to divide spe- cific pathologies by gender. The overall injury prevalence, calculated from 13,182 runners reporting 5,362 injuries (n = 26 studies), was 42.7% ± 19.8 (range 10 – 92%; 95% confidence interval 34.7% - 50.7%). Injury proportions by anatomical site Figure 2 displays the proportion of injuries by anatomical location. The knee (28%) and ankle-foot (26%) regions ac- counted for over half of all the injuries reported (n = 5,816/10,688). The third highest proportion of injury was at the shank (16%). These data indicate that 70% of all in- juries reported were at or below the knee. The hip and thigh regions accounted for 14% of injuries. The remaining inju- ries (other, 15%) were either of unclear location, from the upper extremity, or illness. The proportion of injury per anatomical location did not change when analysed by gender. Injuries to the knee and below accounted for the majority of injuries in men (78%) and women (75%). However, the proportions of the three most frequent injuries differ between genders (Figure 3 and 4). Figure 4 illustrates that knee injuries account for 40% of all injuries in women, followed by the ankle-foot (19%) and shank (16%). Injuries are more evenly weighted in men between knee (31%), ankle-foot (26%) and shank (21%) (Figure 3). The hip and thigh regions accounted for 15% and 18% of all injuries in men and women respectively. Inju- ries classified as ‘other’ accounted for 6% and 7% of all injuries in men and women respectively. Injury proportions by specific pathology From the 3,580 recorded injuries, 770 were classified as ‘other’. The top 10 running injuries recorded from the re- maining 2,810 injuries are displayed in Figure 5 and ex- pressed as a percentage of all injuries (n = 3,580). Discussion The purpose of this review, was to describe the proportion of running injuries by anatomical location and where pos- sible, specific pathology in men and women. There was sufficient literature to satisfy this aim in relation to anatom- ical location and specific
are displayed in Figure 5 and ex- pressed as a percentage of all injuries (n = 3,580). Discussion The purpose of this review, was to describe the proportion of running injuries by anatomical location and where pos- sible, specific pathology in men and women. There was sufficient literature to satisfy this aim in relation to anatom- ical location and specific pathology for both genders com- bined but only the anatomical location of injury could be divided by gender. The proportion of running injuries by anatomical site and specific pathology Unsurprisingly, and in agreement with previous reviews on the topic, the majority (~70%) of running injuries occur at or below the knee (Kluitenberg et al., 2015; Lopes et al., 2012). This finding is true for both men and women. Figure 2. Injury proportions by anatomical site (%). Figure 3. Male injury proportions by anatomical site (%).
Description
This systematic review analyzes lower limb running injuries by gender and anatomical location.