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Understanding lower limb location-specific running-related pain by males and females Elashi, Maha Essam 2016

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  UNDERSTANDING LOWER LIMB LOCATION-SPECIFIC RUNNING-RELATED PAIN BY MALES AND FEMALES  by   Maha Essam Elashi  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE   in   The Faculty of Graduate and Postdoctoral Studies  (Kinesiology)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  April 2016   © Maha Essam Elashi, 2016    ii Abstract  Running-related injuries (RRIs) have been attributed to a number of factors, but there is no consensus in the current literature as to whether sex is a risk factor for RRIs, or if risk factors for running-related pain differ by sex. It has been suggested that due to differences in anatomy and biomechanics, males and females have their own RRI risk profiles; several variables may need to be taken into consideration when assessing sex as a risk factor for RRIs and running-related pain.  Purpose: The proposed study represented the first two phases of a three-tiered epidemiological project. The purpose of Phase I was to determine whether there were significant differences in site-specific running-related injuries/pain between males and females training for a 10-km race; a statistical model was then created in the second phase to determine what explains running-related pain in the lower extremity by sex, for runners preparing for a 10-km race.  Methods: 114 recreational runners (46 males [37.9 ± 9.8 years; 75.46 ± 9.55 kg; 1.75 ± 0.08 m] and 68 females [32.60 ± 8.70 years; 63.47 ± 9.96 kg; 1.66 ± 0.06 m]) took part in a prospective cohort design of a gradual 12-week training program, and a comprehensive baseline assessment was recorded for each participant. Weekly online surveys were administered to monitor whether subjects experienced an RRI. The Visual Analogue Scale (VAS) was administered to record pain scores at 11 relevant anatomical locations in the lower limb and the whole body, at baseline and during Weeks 4, 8, and 12 of the program. Foot and Ankle Disability Index (FADI) pain scores were also measured at these time points.   Results: Sex was not a significant factor in the onset of location-specific, running-related pain in the VAS sites, but significant main effects of sex were found for the FADI. Males and females had different explanatory variables for each of the VAS and FADI sites.  Conclusions: The causes of running-related pain in the individual anatomical regions varied by sex, which suggests that running-related pain may be decreased by addressing sex-specific risk factors.     iii Preface   Collaborators and co-authors of this thesis study are as follows:  • Dr. Michael Koehle, MD, PhD, supervised this project, assisted with trouble-shooting as issues arose, provided insight into the practical application of research, as well as guidance during data analysis and writing. • Dr. Michael Ryan, MD, PhD, assisted with the development of the research design, completed the application for ethics approval, and assisted with the application for funding through the NIKE Global Research Foundation. • Dr. Jack Taunton, PhD, assisted in the development of the research design and the application for funding through the NIKE Global Research Foundation, offered a clinical diagnosis to all injured participants, and provided insight into the practical application of research.   • Dr. Tavinder K. Ark, PhD, assisted with data analysis and provided feedback during the writing process. • Sarah Koch, MSc, BSc, provided feedback during the writing process. • Ted Chang, Andrea Nikic, Madison McCarthy, and Jamie Hartwell assisted with baseline testing and data entry. • Beverley Larssen and Yuri Melnychuk supervised the training program track workouts. • Maha Elashi, BHK, assisted with the development of the research design and the application for funding through the NIKE Global Research Foundation, recruited subjects, performed baseline testing, managed data collection, supervised all group running sessions, coordinated final race event, managed and performed data entry, analyzed data, and wrote the final thesis document.  One manuscript resulting from the work presented in this thesis has been published to date. The abstract, attached in Appendix G, page 53 was accepted for a podium presentation at the Annual organized by Canadian Academy of Sport and Exercise Medicine in February 2015, in Ottawa, Canada.  This study involved human subjects and was granted full-board approval from the University of   iv British Columbia Clinical Research Ethics Board (H13-01582).      v   Table of Contents Abstract .......................................................................................................................................... ii!Preface ........................................................................................................................................... iii!Table of Contents .......................................................................................................................... v!List of Tables ............................................................................................................................... vii!List of Figures ............................................................................................................................. viii!List of Symbols and Abbreviations ............................................................................................ ix!Operational Definitions ................................................................................................................ x!Acknowledgements ...................................................................................................................... xi!Dedication .................................................................................................................................... xii!1 Introduction ................................................................................................................................ 1!1.1 Health benefits and concerns related to exercise ............................................................................... 1!1.2 Running-related injuries ..................................................................................................................... 1!1.3 Common running-related injuries ....................................................................................................... 1!1.4 Causes of running-related injuries ..................................................................................................... 2!1.5 Differences between sexes in running injury risk ............................................................................... 3!2 Understanding lower limb location-specific running-related pain by males and females .. 5!2.1 Purpose, objectives, and hypotheses ................................................................................................... 5!2.2 Methods ............................................................................................................................................... 6!2.2.1 Participant information ............................................................................................................... 6!2.2.2 Experimental design .................................................................................................................... 6!2.2.3 Training program ........................................................................................................................ 7!2.2.4 Outcome measures ....................................................................................................................... 8!2.2.5 Training and injury history assessment ....................................................................................... 9!2.2.6 Anthropometric measures and baseline variables .................................................................... 10!2.2.7 Biomechanical and strength variables ...................................................................................... 11!2.2.8 Survey administration ................................................................................................................ 12!2.2.9 Statistical analyses .................................................................................................................... 13!2.3 Results ............................................................................................................................................... 14!2.3.1 Descriptive demographics ......................................................................................................... 14!2.3.2 Phase I: Running-related injuries and running-related pain by males and females ................ 16!2.3.3 Phase II: Risk factors for running-related pain by males and females ..................................... 19!2.4 Discussion ......................................................................................................................................... 23!2.4.1 Discussion overview .................................................................................................................. 23!2.4.2 Dropped explanatory variables for males and females ............................................................. 24!2.4.3 Explanatory variables for the male model ................................................................................ 24!2.4.4 Explanatory variables for the female model ............................................................................. 27!2.4.5 Risk factors across sex ............................................................................................................... 30!3 Conclusion ................................................................................................................................ 32!3.1 Conclusions regarding thesis hypotheses ..................................................................................... 32!3.2 Limitations and future research directions .................................................................................. 32!References .................................................................................................................................... 36!  vi Appendices ................................................................................................................................... 45!A Consent form ....................................................................................................................................... 45!B Foot Posture Index (FPI) – foot type assignment ............................................................................... 49!C The Foot and Ankle Disability Index (FADI) Score and Sport Module .............................................. 50!D Visual Analogue Scale (VAS) .............................................................................................................. 51!E Injury history form ............................................................................................................................... 52!F Weekly survey ...................................................................................................................................... 53!G Manuscript .......................................................................................................................................... 53!H Training program ................................................................................................................................ 55!    vii List of Tables  Table 1: Objective and hypotheses for each project phase. ....................................................... 5 Table 2: Inclusion and exclusion criteria. .................................................................................. 6 Table 3: Example of a typical week of training taken from the training program. .................... 8 Table 4: Training and injury history variables. .......................................................................... 9 Table 5: Anthropometric and baseline variables. .................................................................... 10 Table 6: Biomechanical and strength variables. ...................................................................... 11 Table 7: Mean and standard deviation of participants' anthropometric variables by sex. ....... 14 Table 8: Mean and standard deviation of baseline explanatory variables by sex. ................... 14 Table 9: Frequency and percentage of baseline explanatory variables by sex. ....................... 15 Table 10: Mean and standard deviation of VAS and FADI scores for males over time. ........ 17 Table 11: Mean and standard deviation of VAS and FADI scores for females over time. ..... 17 Table 12: Significant baseline explanatory variables by pain site for males. .......................... 20 Table 13: Significant baseline explanatory variables by pain site for females. ....................... 22     viii List of Figures  Figure 1: Mean and standard deviation of hamstrings VAS pain scores by males and females over time, controlling for baseline scores. ..............................................................................18     ix List of Symbols and Abbreviations  °: degrees ADL: activities of daily living ANCOVA: analysis of covariance ASIS: anterior superior iliac spine BMI: body mass index cm: centimeters FADI: Foot and Ankle Disability Index HSD: honest significant difference IOC: International Olympic Committee ITB: iliotibial band ITBS: iliotibial band syndrome kg: kilograms L: left MTP: metatarsophalangeal MTSS: medial tibial stress syndrome PFPS: patellofemoral pain syndrome Q-angle: Quadriceps angle R: right RED-S CAT: relative energy deficiency in sport clinical assessment tool ROM: range of motion ROM: range of motion RRI: running-related injury     x Operational Definitions  Activities of Daily Living (ADL): self-care tasks or activities that are performed on a daily basis, usually without assistance.   Foot and Ankle Disability Index (FADI): The FADI is a standardized questionnaire with options from 0-4 (4 being “no difficulty,” and 0 being “unable to do”) that is specific to the foot and ankle and asks readers to rate the level of difficulty associated with performing a list of activities.  Running-related Injury (RRI): defined as running-related pain that resulted in a runner missing three consecutive scheduled workouts.  Visual Analogue Scale (VAS): The VAS is numbered from 0-10 (with 0 being no pain, to 10 being the worst pain imaginable), and includes all major muscle groups and joints in the lower extremity (i.e. the foot, ankle including the Achilles, shin, calf, knee, quadriceps, hamstrings, hip, groin, gluteal, and lower back), as well as the whole body.    xi Acknowledgements  This project would not have been possible without the financial support of the NIKE Global Research Foundation and the University of British Columbia, Faculty of Education.  I would not have been able to complete this thesis without the support of my supervisor, committee, lab mates, friends, and family. I would like to thank:  • My supervisor, Dr. Michael Koehle • My committee members, Dr. Jack Taunton and Dr. Michael Ryan • Dr. Tavinder K. Ark • Dr. Don McKenzie • Phil Moore and Evan Moore (Fit First) • Helen Luk and Nancy McLaren • My research team: Ted Chang, Jamie Hartwell, Andrea Nikic, and Madison McCarthy • Track coaches, Beverley Larssen, and Yuri Melnychuk • All of the athletes who participated in this study • Sarah Koch, Kristin MacLeod, and Margaux Chan • Sean Sinden, Elliott Boake, Dr. Martin MacInnis, and Dr. Keith Lohse • The Environmental Physiology Laboratory team • Dr. Bill Sheel and the Health and Integrative Physiology Laboratory team • The all-ladies sandwich team at the Deli • The Nike Global Research Foundation and the University of British Columbia, Faculty of Education • My friends, my family, and my parents for their unwavering support throughout this process     xii      To Mama and Baba, with love.    1 1 Introduction 1.1 Health benefits and concerns related to exercise The reasons for choosing to participate in running events around North America vary from fundraising initiatives, and competing in sport, to achieving personal goals, but most participants reap the benefits of positive health outcomes gained through their regular participation in physical activity. Regular exercise, and running in particular, has been shown to reduce the risk of disease development, and can positively affect cardiovascular, musculoskeletal, and respiratory function, as well as psychological well-being1-6. The benefits to running are numerous, however, 18.2% - 92.4% of runners appear to be affected by a musculoskeletal injury at some point during their training or in competition7-9. Therefore, it is possible that the cost of a musculoskeletal injury could interfere with the aforementioned health gains.  1.2 Running-related injuries Running-related injuries (RRIs) can be due to a variety of intrinsic (Q-angle and muscle strength) and extrinsic (training volume, training frequency, and environmental conditions) factors. Unfortunately, due to the heterogeneity of previous study designs, there is a lack of consensus as to which RRIs are the most common, and which training and injury factors, anthropometric measures, and biomechanical constituents, put runners at the greatest risk for an RRI11.  1.3 Common running-related injuries Much of the literature suggests that the majority of injuries sustained during training and competition affect the lower extremity. Lopes et al. (2012) conducted a review of the literature, which showed that prospective studies have reported medial tibial stress syndrome (MTSS), a condition characterized by pain on the medial edge of the tibia, as the most common musculoskeletal running injury10. Researchers have postulated potential running mechanisms which can lead to medial tibial stress syndrome; the first theory is stress caused by ground reaction forces as runners strike the ground with their foot during the landing phase of running, with the second possible mechanism being the constant contraction of muscles that plantarflex the foot (specifically tibialis posterior, flexor digitorum longus, and soleus)11. These actions   2 produce repeated stress on the tibia, which can result in an injury. Other possible risk factors for MTSS include interval training, a genu varus, as well as the frequency at which runners change their running shoes; however, direct relationships for these variables have not yet been determined8,11,12. Runners also commonly experience plantar fasciitis- a debilitating condition caused by the inflammation of the plantar fascia. The onset of heel pain presents either gradually or suddenly due to numerous possible causes, including a hard impact to the bottom of the foot, such as a ground reaction force during the heel strike phase of running, improper shoe type, aged shoes13, or repeated loads of stress (standing or running for long periods of time)11. Over time and with age, repeated stress can decrease fat pad thickness on the sole of the foot, as well as the ability of the plantar fascia to absorb ground reaction forces and to sustain loads applied to the body11. Another prevalent running injury is Achilles tendinopathy. The condition is characterized by inflammation, pain, or swelling of the Achilles tendon. Achilles tendinopathy symptoms can present in individuals who use improper footwear, increase training frequency and intensity, train on hard surfaces or surfaces of greater camber, as well as those who participate in activities that excessively load the Achilles tendon such as jumping, or running. Studies have shown that as runners use a forefoot-striking pattern, commonly adopted by those using minimalist footwear or short-distance runners, higher loads are applied to the gastrocnemius and soleus muscles, which are transmitted to the Achilles tendon and lead to overuse14,15. A common injury among females is patellofemoral pain syndrome (PFPS), which has been associated with hip strength deficits and PFPS in females16,17. It is important to note that many studies have used the term “runner’s knee” to report PFPS, often described as anterior knee pain or discomfort, as a common RRI, but there has been an inconsistency with the definition of the term; while some authors have referred to “runner’s knee” as PFPS, others have used it to report iliotibial band syndrome (ITBS). Unfortunately due to this heterogeneous definition, it is unclear whether PFPS is as prominent in the running population as the literature suggests.   1.4 Causes of running-related injuries Several studies have investigated various training regimens as risk factors for future injury. Positive correlations have been shown between weekly distance and the likelihood of   3 sustaining an RRI2,18-24; similarly, weekly running frequency was found to be predictive for running injuries13,18,21. Due to the repetitive loading that comes with an increase in frequency and distance in training per week, runners are put at a higher risk of developing an overuse injury20. Those who have had a previous musculoskeletal injury were also consistently found to re-injure the same area19,20,25-27. Age has been shown to have a positive correlation with sustaining an RRI7,13,28, as well. As expected, those who had more running experience18, previous participation in activities that involve axial loading27 (when force is applied in the direction of the long axis of the body), or regular participation in sports21, were found to be less at risk for an RRI compared to runners who lacked previous experience. Several studies have shown that static lower limb biomechanical and alignment measures are unrelated to the incidence of RRIs11,22,29-33, however others have found that anthropometric measures such as an individual’s quadriceps angle (Q-angle)25,34 a measure taken between the line of the quadriceps muscles and the patellar tendon; medial longitudinal arch height35,36, an arch on the medial side of the foot supported by various ligaments; Body Mass Index (BMI)13,27, a height to weight ratio; and navicular drop, an indication of the navicular tuberosity’s movement from neutral to relaxed while standing (marked by pronation)27, are significant factors of an RRI.  These differences in anthropometric and anatomical structures can change how forces are applied to the lower limb, as well as an individual’s gait37.  1.5 Differences between sexes in running injury risk Much of the running injury research that compares risk between females and males has focused on the differences in lower-limb structure and their contributions to injury by sex. For example, in studies investigating biomechanical differences in ground reaction forces during running between males and females38,39, females were found to exhibit greater vertical forces and moments than men. Several other anatomical factors that influence kinematics, such as greater genu valgum40, greater hip internal rotation41, larger hip femoral length ratio42, and increased Q-angle magnitude43 have also been studied in detail, and have been attributed greatly to RRIs in females more so than in males. Given the differences between males and females with regards to anatomical structures and biomechanics in the lower extremity, it stands to reason that each sex may have a different   4 running injury risk profile19,44. These sex differences are demonstrated in an extensive retrospective case-control analysis conducted by Taunton et al. (2002), which showed that females commonly experience stress fractures and PFPS, while males experience meniscal injuries and tendinopathy (Achilles and patellar)45. Currently, there is a lack of consensus as to whether a runner’s sex plays a role in their running injury risk; previous studies have found the female sex to be a risk factor for RRIs in secondary-school athletes, a protective factor against RRIs in recreational runners training for a short distance event, and unrelated in the incidence of an RRI for higher-level recreational runners training for a marathon18,25,46. The inconsistency in findings is likely due to a combination of inconclusive reporting from heterogeneous methodology, a lack of anthropometric and biomechanical measures included when considering injury, and retrospective designs, which is a weaker design that is prone to recall bias. The purpose of the proposed research was to provide an externally valid foundation for future research and investigation on RRIs and running-related pain between sexes. Data collection for the first phase of the project took place from September 2013 – August 2014; from this, we analysed and determined whether there were differences in the number of injuries between males and females and the specific variables that explained running-related pain for each sex. Using a prospective cohort study design, we examined anthropometric, biomechanical, and strength factors, in addition to clinical and training information, to shed light on which risk factors could explain injuries in male and female runners training for a 10-km race.     5 2 Understanding lower limb location-specific running-related pain by males and females 2.1 Purpose, objectives, and hypotheses The proposed study represents the first two phases of a three-tiered epidemiological project; the objective of this project was to investigate the variables that explain running-related pain in the lower extremity following the completion of a 12-week running program. During the first stage of the project, 46 males [37.9 ± 9.8 years; 75.46 ± 9.55 kg; 1.75 ± 0.08 m] and 68 females [32.60 ± 8.70 years; 63.47 ± 9.96 kg; 1.66 ± 0.06 m] trained for a 10-km race in order to determine whether sex was a risk factor for an RRI. Outcomes from the 12-week training program in the initial phase provided for Phase II, which involved the creation of a statistical model to determine the level of contribution of selected independent variables to lower-limb running-related pain in runners preparing for a 10-km race. The objectives and hypotheses for each phase are listed in Table 1.  Table 1: Objective and hypotheses for each project phase. Objective Hypotheses Phase I: to understand the effects of sex on RRIs by: i.   examining differences in incidence rates and relative risk for males and females. ii.   determining whether there are significant differences in site-specific running-related pain between males and females training for a 10-km event. Hypothesis 1: Female runners will have a higher number of reported injuries and higher levels of pain in their lower extremities compared to males, following a 12-week training period. Phase II: to create a statistical model to determine the variables explaining running-related pain/RRI by sex, for runners preparing for a 10-km event. Hypothesis 2: The variables explaining RRIs/pain in females will be different from males.  Hypothesis 3: The variables explaining RRIs/pain for females will be Q-angles in the highest quartile, and hip strength deficits.  Hypothesis 4: The variables explaining RRIs/pain for both males and females will be attributed to a history of injury, and a greater BMI.    6 Due to the small number of injured participants, we were unable to use RRIs as a dependent measure for the analyses, thus we used running-related pain as the outcome measure.  2.2 Methods 2.2.1 Participant information Ninety-one females and 71 male recreational runners were recruited through newspaper advertisements, flyers at running stores and race events, and by word-of-mouth via social media (i.e. Facebook and Twitter). Following the design of Ryan et al. (2014) which used a similar training program, the dropout rate was anticipated to be approximately 20%; only participants with a full data set were used for the final analysis (68 females and 46 males). The University of British Columbia Clinical Research Ethics Board gave ethical approval for this study design and methodology (H13-01582), and written informed consent was obtained from all participants prior to data collection. Subjects were presented with a NIKE Inc. technical shirt for their participation in the study. All inclusion and exclusion criteria are listed in Table 2.  Table 2: Inclusion and exclusion criteria.  2.2.2 Experimental design Prior to starting the training program, participants visited the Allan McGavin Exercise Physiology Laboratory (Allan McGavin Sports Medicine Centre - John Owen Pavilion in Vancouver, Canada) to provide informed written consent, and for the researchers to collect a detailed training and injury history (related and unrelated to running). At this time, a detailed Inclusion Criteria Exclusion Criteria ! Age 19-59 years ! Able to run continuously for 60 minutes ! Able to withstand 20-km – 40-km of training/week ! English-speaking ! Currently taking pain medication ! History of surgery to the lower extremity ! Significant musculoskeletal injury or running injury in the past six months ! Known degenerative conditions   7 biomechanical, and anthropometric assessment was performed. Details for the methodology for each of the variables collected during the baseline appointment are listed in Tables 4-6.  2.2.3 Training program All participants were provided with the same 12-week program, in preparation for an unofficial 10-km race held in Burnaby, British Columbia, in February, 2014. The structured training program was a slightly modified version of a 10-km program developed for and used by Ryan et al. (2014); it consisted of four runs per week, and participants were provided with a detailed description of each training session listing details such as goal, intensity, and duration. Subjects trained as a group during the weekly long run, and the mid-week interval workout, while the remaining two sessions were performed individually on allocated training days, as time-based workouts, at a self-selected pace. Experienced run leaders and track coaches supervised and facilitated the group running sessions, which accounted for 50% of the training program. When a participant experienced an RRI, defined as missing three consecutive training days due to running-related pain, a sports medicine physician was made available to the participant at their earliest convenience, and a clinical diagnosis was given. On days when environmental conditions interfered with outdoor training, participants were instructed to run on a treadmill, or to perform an equivalent workout by cross-training. The training program was designed to decrease the number of training sessions during weeks seven and eight of the program to two workouts each week, in order to maintain compliance over the December holiday season. An example of a typical week of training is listed below in Table 3; see Appendix G, page 53, for full training program.   8 Table 3: Example of a typical week of training taken from the training program. Week 6: Anaerobic Threshold Training December 15th – December 21st Date Workout Description Sunday 7 mile/11.2-km run Tour de Deer Lake Monday Rest day  Tuesday Interval workout  (50-min) Standard warm up (see instructions at the bottom of the program). Run 8 x 2-min repeats at 20 seconds per mile (or 1.6-km) faster than 5-km pace. Run at a fast, but controlled pace. Concentrate on maintaining proper form. Jog for 2-min between repeats. Cool down with 800m of jogging. Wednesday 30-min easy With 4 x acceleration strides as warm-up. Thursday Rest day  Friday 40-min easy  Saturday Rest day   2.2.4 Outcome measures Primary outcome measures include Foot and Ankle Disability Index (FADI; 0-4) scores and Visual Analogue Scale (VAS; 0-10) pain scores at selected anatomical locations of the lower extremity during Weeks 4, 8, and 1247,48, as well as a regression model showing the strength of explanatory variables for the FADI, each of the 11 VAS regions of the lower extremity (the foot, ankle including the Achilles, shin, calf, knee, quadriceps, hamstrings, hip, groin, gluteal, and lower back), and for the whole body, by males and females. In previous literature, regression models have been used to estimate the risk of anthropometric data; this strategy was employed on a minimal scale using only basic measures such as weight and height. The current study builds upon this work by including lower extremity hip muscle strength assessments, joint range of motion (ROM), and muscle flexibility tests for both right and left sides, in the regression model. The explanatory variables taken at baseline were broadly classified into three categories: training and injury history, anthropometric and baseline variables, and biomechanical and strength measures. A description of each variable is listed in Tables 4-6.   9 2.2.5 Training and injury history assessment Table 4: Training and injury history variables. Training and Injury History Units Description Visual Analogue Scale (VAS)  scores scale of 0-10 For a detailed description of each  survey, please see section 2.2.8 Survey administration. Foot and Ankle Disability    Index (FADI) scores  scale of 0-4 Running-related musculoskeletal injuries recorded month and  year, anatomical  region, and severity of injury Details of participants’ previous  musculoskeletal injuries (related  and unrelated to running) were  recorded; see Appendix E Injury history form, page 52 Non-running related musculoskeletal injuries Weekly running volume km/week Subjects were asked for their  average weekly running volume (for last 12 months) prior to the start of the program. Weekly running frequency number of runs/week Subjects were asked how frequently they would typically run in a week  (for the last 12 months) prior to the  start of the program.  Weekly running time hours Subjects were asked how much time they spent running in a week (for  the last 12 months) prior to the start of the program.   10 2.2.6 Anthropometric measures and baseline variables Table 5: Anthropometric and baseline variables. Anthropometry and Baseline Variables Units Description Height cm Height was recorded without shoes using a stadiometer. Weight kg Weight was taken via a Kistler Multicomponent Force Plate for Biomechanics Type 9286B (Winterthur, Switzerland) in N, and divided by constant gravity (9.81 m/s2). BMI kg/m2 BMI was calculated by dividing mass (kg) by height squared (m2). Leg length symmetry cm Leg length was considered equal if the difference was >5 mm. If leg length discrepancy was >2 cm, the difference was deemed marked. Q-angle ° Standing and supine Q-angle were taken by measuring the angle between the line that joins the anterior superior iliac spine (ASIS) to the center of the patella, and the line that joins the center of the patella to the center of the tibial tuberosity. Standing foot posture Foot Posture Index  (FPI); neutral,  pronated; supinated    foot The FPI has been used in several clinical investigations and is known to be a valid and reliable test to quantify foot posture (highly pronated, pronated, neutral, supinated, or highly supinated foot position). See Appendix B, page 49, for the FPI assessment. Standing leg  alignment cm Determined by asking participants to stand with their feet together, and measuring full leg length (ASIS to medial malleolus) and half-leg length (ASIS to lateral femoral epicondyle). Age  years  Sex F/M      11 2.2.7 Biomechanical and strength variables Table 6: Biomechanical and strength variables. Biomechanical and Strength Units/Trials/Test Description Ankle ROM Modified Lunge Test; cm Participants were asked to take a lunge stance with the most distal aspect of the phalanges on their forward foot against the wall. Participants were then asked to move away from the wall and lunge forward until their front knee could no longer make contact with the wall without lifting their heels off of the ground. The distance between the wall and the most distal aspect of their phalanges on their forward foot was recorded. ROM in first metatarsophalangeal (MTP) joint ° A non-weight bearing ROM in the first MTP joint was taken using a hand-held goniometer and measuring the angle between the line which joined the distal first phalanx to the centre of the first MTP joint, and the line that joined the center of the calcaneus to the center of the first MTP joint. Hip strength;  performed using  hand-held  dynamometry for  each leg, by a licensed physiotherapist.  Hip extension; kg Participants took a standing position with their hands on the plinth, a neutral trunk, and their hip in 10° of extension. Hip flexion; kg Participants lay supine with their hip and knee flexed to 90°. Hip abduction; kg Participants laid on their side with their hip in 10° of extension, and 10° of abduction. Hip adduction; kg Participants laid on their side with their bottom leg in 10° of adduction and their contralateral leg crossed over.     12 Biomechanical and Strength Units/Trials/Test Description Hip muscle flexibility; performed  using hand-held  dynamometry for each leg, by a licensed  physiotherapist Iliotibial band contracture (Ober’s Test) Participants kept their leg straight to the table. Hip flexion contracture (Thomas  Test); ° (if participant  tests positive) Participants kept 90° of hip flexion (minimum) on contralateral side. Rectus femoris  contracture (Kendall  Test); ° (if participant tests positive) Participants kept 90° of knee flexion (minimum). Hamstring contracture  (Hamstring Contracture  Test); ° (if participant tests positive) Participants kept 90° of hip flexion and were able to achieve a neutral knee. Hip abduction, adduction, flexion, and extension were measured three times for measurement reliability; the mean value was taken and used for all analyses.  2.2.8 Survey administration A weekly survey was administered online via SurveyMonkey at the end of each training week to monitor the injury status of participants, while a monthly survey was collected during the baseline appointment, and via SurveyMonkey at Weeks 4, 8, and 12. Investigators sent a weekly three-question survey to all participants to monitor injury rates and compliance to the training program. If a participant reported a running injury on the weekly survey, they were contacted immediately by the research manager, and offered an appointment with a sports medicine physician for a clinical diagnosis at their earliest convenience49. All injured participants saw the same physician. See Appendix F, page 53, for the weekly survey. The second survey consisting of the VAS and FADI was administered every four weeks. The VAS is numbered from 0-10 (0 being no pain, to 10 being the worst pain imaginable), and includes all major muscle groups and joints in the lower extremity (the foot, ankle including the Achilles, shin, calf, knee, quadriceps, hamstrings, hip, groin, gluteal, and lower back), as well as the whole body. The FADI is a standardized questionnaire with options ranging from 0-4 (4 being “no difficulty,” and 0 being “unable to do”) that are specific to the foot and ankle, and asks   13 readers to rate the level of difficulty associated with performing a list of activities47,48. See Appendices C and D, pages 50-51 for the monthly survey. Participants were asked to complete the monthly survey at baseline, and Weeks 4, 8, and 12; the weekly survey was completed at baseline, and Weeks 1-12.  2.2.9 Statistical analyses A repeated-measures ANCOVA was conducted on participants’ FADI and VAS pain scores from selected anatomical regions of the lower extremity as well as the whole body, with sex (males and females) as the between-subject factor, and time (Weeks 4, 8, 12) as the within-subject repeating factor. Each baseline FADI or VAS pain score was included as a covariate in its respective model. Tukey Honest Significant Difference (HSD) post-hoc analyses would have been conducted for significant main effects of time. Data collected from the initial phase of the project was used for Phase II. A series of linear multiple forward stepwise regression models were conducted using FADI and VAS scores (running-related pain) measured at Week 12. The following right and left variables were included as explanatory variables in each model: ankle ROM (Modified Lunge Test); first MTP joint ROM; hip muscle flexibility test outcomes (Ober’s Test, Kendall’s Test, Thomas Test, and Hamstring Contracture Test); hip strength assessments (flexion, extension, adduction, and abduction); and hip strength ratios (hip extension:flexion ratio and hip abduction:adduction ratio). FADI or VAS baseline scores were added as explanatory variables in each of their respective models19,25,27,46 along with the participants’ age, height, weight, BMI, presence or absence of a leg length discrepancy, standing leg alignment, and FPI scores. The model also included training history variables (running frequency, running experience, running volume, and running duration per week prior to the training program), as well as injury history variables (whether a runner incurred a previous musculoskeletal, or an RRI). Q-angle supine and Q-angle standing values were divided into quartiles according to Rauh’s (2007) findings and treated categorically50. The α level for all statistical tests performed in this study was set at 0.05. All statistical analyses were conducted using Statistical Package for Social Sciences (SPSS) Version 22 (IBM, Armonk, NY, USA).    14 2.3 Results 2.3.1 Descriptive demographics Sixty-eight females and 46 males volunteered to participate in this study. Participants’ descriptive statistics of anthropometric variables are presented in Table 7, mean baseline variables in Table 8, and categorical baseline variables in Table 9, by sex (males and females).  Table 7: Mean and standard deviation of participants' anthropometric variables by sex. Measurement Males Females N 46 68 Age (years)* 37.90 (9.80) 32.60 (8.70) Height (m)* 1.75 (0.08) 1.66 (0.06) Weight (kg)* 75.36 (9.55) 63.47 (9.96) BMI (kg/m2)* 24.74 (2.87) 22.93 (3.35) BMI, Body mass index; * denotes a significant difference between sexes.  Table 8: Mean and standard deviation of baseline explanatory variables by sex.  ROM, range of motion; MTP, metatarsophalangeal; * denotes a significant difference between sexes.   Measurement Male Female  Left Right Left Right Hip extension (kg)* 53.72 (11.50) 53.93 (11.33) 46.98 (9.25) 48.59 (10.56) Hip flexion (kg)* 47.72 (6.70) 47.48 (5.69) 38.50 (6.18) 39.07 (6.13) Hip abduction (kg)* 38.12 (7.81) 36.45 (6.93) 29.00 (5.53) 27.82 (5.70) Hip adduction (kg)* 39.54 (7.22) 38.01 (8.14) 27.44 (6.14) 27.43 (5.52) Modified lunge test (cm) 10.85 (3.73) 10.88 (3.85) 10.29 (3.47) 9.70 (3.33) ROM in first MTP joint (°)* 73.65 (11.25) 74.59 (10.37) 79.97 (10.45) 79.94 (10.67)   15 Table 9: Frequency and percentage of baseline explanatory variables by sex. Measurement Males Females  Frequency Percent Frequency Percent Right     Q-angle < 10°* 20 43.5 0 0.0 10° < Q-angle < 15° 17 37.0 29 42.6 15° < Q-angle < 20°  9 19.6 26 38.2 Q-angle > 20° 0 0.0 13 19.1 Left      Q-angle < 10°* 22 47.8 1 1.5 10° < Q-angle < 15° 16 34.8 25 36.8 15° < Q-angle < 20°  8 17.4 29 42.6 Q-angle > 20° 0 0.0 13 19.1 Standing right      Q-angle < 10°* 21 45.7 0 0.0 10° < Q-angle < 15° 17 37.0 29 42.6 15° < Q-angle < 20°  8 17.4 25 36.8 Q-angle > 20° 0 0.0 14 20.6 Standing left      Q-angle < 10°* 28 60.9 3 4.4 10° < Q-angle < 15° 13 28.3 28 41.2 15° < Q-angle < 20°  5 10.9 29 42.6 Q-angle > 20° 0 0.0 8 11.8 Foot type assignment      Neutral 19 41.3 31 45.6 Pronated 24 52.2 37 54.4 Highly pronated 3 6.5 0 0.0 Standing leg alignment*     Neutral 31 67.4 26 45.6 Varus 6 13.0 3 4.4 Valgus 9 19.6 39 57.4 Thomas Test*     Positive on one leg 4 8.7 0 0.0 Positive on both legs 6 13.0 2 2.9 Negative on both legs 36 78.3 66 97.1 Kendall Test     Positive on one leg 5 10.9 5 7.4 Positive on both legs 35 76.1 51 75.0 Negative on both legs 6 13.0 12 17.6 Ober’s Test     Positive on one leg 9 19.6 10 14.7 Positive on both legs 2 4.3 7 10.3   16 Measurement Males Females  Frequency Percent Frequency Percent Negative on both legs 35 76.1 51 75.0 Hamstring Contracture Test*     Positive on one leg 0 0.0 9 13.2 Positive on both legs 46 100.0 47 69.1 Negative on both legs 0 0.0 12 17.6 Previous running-related injury 22 47.8 37 54.4 Previous musculoskeletal injury 33 71.7 43 63.2 Injured during training program 4 8.7 6 8.8 Q-angle, quadriceps angle; * denotes a significant difference between sexes.  2.3.2 Phase I: Running-related injuries and running-related pain by males and females Ten participants (six females and four males) were injured over the course of the 12-week training program. Based on data from the weekly survey, male runners completed 1542 training sessions, and female runners completed 2272 training sessions. No significant differences were found between the normalized injury rates (RRIs/1000 training sessions) of 2.59 and 2.64 for males and females, respectively, with females having a relative risk of 0.99, 95% CI [0.59,1.69].  No significant difference in running-related pain was found at the end of the 12-week training period in the whole body or on any of the VAS anatomical sites, however significant main effects of sex were found in the FADI, with females reporting higher FADI scores. Given the low number of injured participants (n=10), we were underpowered to complete our a priori analyses using running-related injuries as the dependent measure for a linear forward multiple stepwise regression model; with n=10 injured participants and a female relative risk of 0.99, we instead chose to use running-related VAS and FADI pain scores as the dependent measures for our repeated measures ANCOVAs and regression models. The repeated measures ANCOVA is reported below. Violations of sphericity were accounted for using the Hyunh-Feldt Correction. A bonferroni correction would have been conducted to account for Type I errors when running multiple comparisons for time. See Table 10 for descriptive statistics of VAS and FADI scores for males, and Table 11 for females, over time.    17 Table 10: Mean and standard deviation of VAS and FADI scores for males over time. Outcome Location  Baseline Week 4 Week 8 Week 12 Whole body  1.13 (1.05) 1.35 (1.43) 1.51 (1.41) 1.83 (1.62) Lower back 0.74 (1.144) 0.50 (1.13) 0.67 (1.49) 0.78 (1.53) Hip 0.48 (0.86) 0.52 (1.05) 0.48 (1.26) 0.54 (1.22) Quadriceps 0.44 (0.81) 0.48 (0.86) 0.44 (1.09) 0.52 (1.05) Hamstrings 0.44 (0.72) 0.41 (1.24) 0.50 (1.17) 0.74 (1.27) Groin 0.13 (0.40) 0.17 (0.64) 0.26 (0.83) 0.35 (0.74) Gluteal 0.41 (0.96) 0.57 (1.20) 0.48 (1.05) 0.57 (1.07) Knee 0.91 (1.26) 0.85 (1.28) 0.91 (1.24) 0.91 (1.19) Shin  0.48 (0.78) 0.59 (1.18) 0.41 (0.96) 0.76 (1.33) Calf 0.67 (0.92) 0.91 (1.64) 0.72 (1.09) 1.00 (1.48) Ankle 0.63 (1.20) 0.26 (0.68) 0.41 (0.93) 0.63 (1.12) Foot  0.63 (1.16) 1.04 (1.53) 0.80 (1.15) 0.67 (1.28) FADI Scores 134.28 (2.10) 131.12 (9.07) 128.54 (20.88) 131.52 (7.15) VAS, Visual Analogue Scale; FADI, Foot and Ankle Disability Index.  Table 11: Mean and standard deviation of VAS and FADI scores for females over time. Outcome Location  Baseline Week 4 Week 8 Week 12 Whole body  1.09 (1.25) 1.75 (1.54) 1.34 (1.76) 1.46 (2.00) Lower back 0.44 (0.87) 0.49 (0.95) 0.57 (1.25) 0.60 (1.20) Hip 0.52 (0.94) 0.69 (1.26) 0.75 (1.64) 0.63 (1.53) Quadriceps 0.34 (0.89) 0.50 (1.11) 0.56 (1.23) 0.53 (1.35) Hamstrings 0.43 (0.94) 0.84 (1.36) 0.68 (1.42) 0.49 (1.18) Groin 0.16 (0.70) 0.15 (0.53) 0.22 (0.99) 0.37 (1.31) Gluteal 0.27 (0.64) 0.63 (1.16) 0.66 (1.44) 0.53 (1.37) Knee 0.96 (1.30) 1.19 (1.60) 1.00 (1.72) 1.16 (2.01) Shin  0.46 (0.92) 0.96 (1.68) 0.53 (1.45) 0.71 (1.59) Calf 0.53 (1.00) 1.02 (1.51) 0.60 (1.46) 0.82 (1.65) Ankle 0.46 (0.82) 0.41 (1.04) 0.32 (1.03) 0.53 (1.22) Foot  0.74 (1.59) 0.34 (0.81) 0.57 (1.35) 0.66 (1.59) FADI Scores 133.66 (3.87) 133.83 (5.00) 134.25 (6.19) 132.85 (8.02) VAS, Visual Analogue Scale; FADI, Foot and Ankle Disability Index.  A significant linear interaction effect was found between males and females at the hamstrings location over time F(2,222) = 3.152, p = 0.045; males appear to exhibit more   18 hamstrings pain than females over time, however this effect is borderline significant. See Figure 1.   A significant main effect of sex was found for the FADI, as females [133.72, (6.70)] reported higher FADI scores than males [130.28 (6.71)]. A significant interaction between baseline pain scores and time was found for the lower back F(1.933, 222) = 3.156, p = 0.046, the hamstrings F(2,222) = 3.213, p = 0.042, and the groin F(2,222) = 4.866, p = 0.009. Before we began the training program, females were found to have higher groin pain at baseline, and males were found to have higher pain in their lower back and hamstrings regions. Mauchly’s Test of Sphericity was violated for the lower back region [Mauchly’s Test of Sphericity = 0.929, !2(2) = 8.084, p = 0.018]; Hyunh-Feldt values were therefore used for this site. Independent samples t-tests were performed on all continuous explanatory variables, and chi squared tests were performed on all categorical explanatory variables to determine whether significant differences existed between both sexes; significant differences were also investigated for all baseline VAS regions and FADI baseline scores. Significant differences are marked with an asterisk in Tables 7-9. Although a significant main effect of sex was only found in the FADI, a differential impact was observed for pain explanatory variables between sex. As a result, a forward stepwise 4 8 12-10123WeeksRunning-Related Pain (VAS)HamstringsMalesFemalesFigure 1: Mean and standard deviation of hamstrings VAS pain scores by males and females over time, controlling for baseline scores. Error bars represent standard deviation.   19 multiple regression was conducted across the 11 anatomical locations, for the whole body, and for the FADI. The regression was performed separately for males and females.  2.3.3 Phase II: Risk factors for running-related pain by males and females Results are reported using adjusted R2 values, which is the percentage of variation in the dependent variable that is explained for by the explanatory variables, and standardized beta coefficients, which explain the amount of influence explanatory variables have on the dependent measures (VAS and FADI pains scores). A positive standardized beta coefficient indicates a directly proportional relationship, and a negative beta coefficient indicates an inversely proportional relationship. Please see Table 12 for all significant baseline variables by pain site for males, and Table 13 for significant variables by pain site for females.       20 Table 12: Significant baseline explanatory variables by pain site for males. Pain  Location Explanatory Variable Adjusted R2 Standardized ß 95% CI for ß p-value Whole body Left Hip abduction 0.065 0.950 0.084, 0.311 0.001  Right Hip abduction 0.189 -0.756 -0.306, -0.049 0.008 Lower back Left Hip abduction 0.280 0.440 0.037, 0.135 0.001  Lower back baseline 0.333 0.263 0.033, 0.673 0.032  ROM in the left MTP joint 0.380 -0.252 -0.068, -0.001 0.046 Hip Standing left Q-angle  (Q-angle < 10°) 0.095 -0.339 -1.550, -0.132 0.021 Quadriceps Standing right Q-angle (15° < Q-angle < 20°) 0.123 0.991 1.357, 4.065 >0.001  Left Q-angle  (15° < Q-angle < 20°) 0.203 -0.657 -3.134, -0.462 0.010  Right Hip extension 0.275 -0.298 -0.052, -0.003 0.027 Hamstrings None     Groin Standing right Q-angle (15° < Q-angle < 20°) 0.150 0.441 0.337, 1.361 0.002  Thomas Test  (Negatives) 0.223 -0.300 -1.001, -0.059 0.028 Gluteal Ober's Test (Negatives)  0.087 -0.330 -1.499, -0.133 0.020  Running experience 0.157 -0.296 -0.074, -0.003 0.036 Knee Knee baseline 0.161 0.424 0.141, 0.659 0.003 Shin Shin baseline 0.228 0.518 0.536, 1.237 >0.001  Left Hip extension 0.322 0.281 0.009, 0.057 0.090  BMI 0.411 0.386 0.083, 0.276 0.001  Standing right Q-angle (15° < Q-angle < 20°) 0.497 0.276 0.212, 1.710 0.013  Varus leg alignment  0.558 0.261 0.218, 1.833 0.014 Calf Calf baseline 0.122 0.380 0.210, 1.007 0.004  ROM in right first MTP joint 0.194 0.393 0.019, 0.092 0.004  BMI 0.318 0.378 0.063, 0.327 0.005 Ankle VAS Ankle baseline 0.176 0.176 0.209, 0.711 0.001  Standing left Q-angle (15° < Q-angle < 20°) 0.231 0.231 0.007, 1.921 0.048 Foot Foot baseline 0.113 0.440 0.193, 0.779 0.002  Standing left Q-angle (15° < Q-angle < 20°) 0.249 0.394 0.525, 2.690 0.005 FADI FADI Scores baseline 0.203 0.544 1.003, 2.691 >0.001 Scores Standing left Q-angle (15° < Q-angle < 20°) 0.341 -0.394 -14.604, -3.317 0.003   21 VAS, Visual Analogue Scale; ROM, range of motion; MTP, metatarsophalangeal; Q-angle, Quadriceps angle; FADI, Foot and Ankle Disability Index.    22 Table 13: Significant baseline explanatory variables by pain site for females. Pain Location Explanatory Variable Adjusted R2 Standardized ß 95% CI for ß p-value Whole body Left Q-angle  (Q-angle < 10°) 0.151 0.345 2.421, 8.984 0.001  Whole body baseline 0.220 0.308 0.175, 0.809 0.003  Standing left Q-angle  (Q-angle < 10°) 0.297 0.336 1.315, 5.188 0.001  Age 0.356 -0.265 -0.108, 0.015 0.011 Lower back Leg length symmetry 0.049 -0.252 -2.840, -0.084 0.038 Hip Running volume 0.104 -0.311 -0.072, -0.011 0.008  Hip baseline 0.147 0.237 0.016, 0.760 0.041 Quadriceps Standing left Q-angle  (Q-angle > 20°) 0.120 0.304 0.325, 2.214 0.009  Quadriceps baseline 0.182 0.277 0.076, 0.764 0.017 Hamstrings None ! ! ! ! Groin Groin baseline 0.271 0.485 0.533, 1.279 >0.001  Right Hip strength ratio (Extension:Flexion) 0.346 0.292 0.401, 2.150 0.005 Gluteal Gluteal baseline 0.149 0.371 0.343, 1.248 0.001  Right Hip strength ratio (Extension:Flexion) 0.207 0.306 0.417, 2.364 0.006  Weight 0.257 0.248 0.005, 0.063 0.024 Knee Knee baseline 0.375 0.538 0.564, 1.104 >0.001  Left Q-angle  (Q-angle < 10°) 0.461 0.309 2.249, 8.012 0.001  Weight 0.489 0.206 0.007, 0.076 0.019  Right Hip extension 0.514 0.180 0.002, 0.067 0.040 Shin Left Q-angle  (Q-angle > 20°) 0.110 0.350 0.484, 2.336 0.003 Calf Leg length symmetry 0.162 -0.408 -4.972, -1.530 >0.001  Weight 0.199 0.250 0.005, 0.077 0.025  Standing right Q-angle  (Q-angle > 20°) 0.237 0.222 0.024, 1.772 0.044 Ankle Previous running-related injury 0.067 -0.254 -1.177, -0.056 0.032  Hamstring Contracture Test (Negatives) 0.114 0.246 0.048, 1.512 0.037 Foot  Foot baseline 0.053 0.259 0.022, 0.497 0.033 FADI Running volume 0.072 0.293 0.041, 0.370 0.015 VAS, Visual Analogue Scale; Q-angle, quadriceps angle; FADI, Foot and Ankle Disability Index.   23 2.4 Discussion 2.4.1 Discussion overview The primary purpose of Phase I was to determine whether there were significant differences in running-related injuries and site-specific running-related pain between males and females training for a 10-km event. We hypothesized that female runners would have a higher number of reported injuries and higher levels of pain in their lower extremities compared to males, following a 12-week training period. Although females reported a higher number of injuries (n=6 compared to n=4 for males), we were unable to determine whether this difference was statistically significant due to the small number of injuries and small sample size. As previously stated, much of the literature suggests that running injuries are associated with training volume and intensity20,51. A possible explanation as to why we may not have had a large number of injuries is that our 12-week program was designed to be progressive and thus may have been protective against injury. For example, while we recognize the differences in training volume and duration, if we compare the percentage of runners injured in our study (8.8%) to Walter et al.’s (1989) study (50.4%), it is evident that our training program yielded far less injuries. The size of our sample may have also been a contributing factor to our small number of injuries. The goal of Phase II was to further understand the implications of running-related pain experienced by males and females, and whether anatomical structures or injury/training history variables had a differential impact on lower-limb pain. No significant differences in lower-limb, running-related pain were noted between males and females in any of the VAS pain sites however a significant main effect of sex was found in the FADI as females reported higher FADI scores. We also found that the risk factors associated with running-related pain in females were different from the risk factors that explained pain in males. Female injury risk was related to baseline pain scores at the hip region and locations distal to the hip area, high Q-angles, and training history variables. The pain in males was impacted by hip-related factors, high Q-angles, and baseline pain scores at the foot and locations proximal to the foot. At certain pain sites, demographic factors, such as BMI and weight had an effect on pain outcomes across sex.    24 2.4.2 Dropped explanatory variables for males and females Our second hypothesis stated that the variables that explained pain in females would be different from males. The demographics of males certainly differed from that of the female group, and there were instances in which categorical variables did not match the demographics of either sex. With regards to the male runners, no participant had a right or left supine/standing Q-angle of > 20° or a negative test score on the Hamstring Contracture Test for either leg; no female participant had a highly pronated foot type assignment, or a right supine/standing Q-angle of < 10°. Thus, these variables could not be used and were omitted from their respective models.  2.4.3 Explanatory variables for the male model Given that previous research had shown that approximately 20% of running injuries occurred proximal to the knee52, while the majority of the pain that runners experienced were due to injuries at45,53-56 or distal to the knee52, it stands to reason that the average male distance-running athlete would be relatively stronger in their quadriceps, hips, and lower back, but weaker or less flexible in their calves35 and ankles30. Our findings agree with this supposition, as the regressions for the proximal portion of the lower limb were composed of explanatory variables that were protective against running-related pain. This finding is also in agreement with the accepted clinical approach to these injuries, by improving stability through developing proximal and core strength in order to minimize distal movement patterns that could lead to injury57. There were noteworthy variables that explained running-related pain in the proximal portion of the lower limb, including hip-muscle strength imbalances and high Q-angles. While researchers had once assumed that measuring either the right or left Q-angle would yield the same angle value, studies have since reported asymmetry between individuals’ left and right Q-angles58-63. Larger Q-angle values of 15° < Q-angle < 20° are considered to be abnormal for men42,64,65, indicate a decrease in quadriceps strength66,67, and may cause muscle strength imbalances which contribute to pain. Much of the literature focuses on the relationship between Q-angle magnitude and knee pain. Smaller Q-angles are indicative of stronger hip flexors68 and have been shown to produce an efficient line of pull of the quadriceps muscles69; this results in a straighter leg alignment, and decreases the tendency for a lateral tracking patella that is associated with larger Q-angles. Based on the current literature, we anticipated that lower Q-angle values would be associated with less   25 pain at the knee; instead, we found that a standing left Q-angle of < 10° was protective against pain at the hip (ß = -0.339). A possible explanation may be that higher Q-angles put more stress on hip abductor muscles, however more research is required on the association between hip pain and Q-angle as it has not yet been described in the literature. Further to the relationship of Q-angle values and knee pain, we expected larger Q-angle values to be associated with more knee pain, but found that a larger Q-angle value, specifically a standing right Q-angle of 15° < Q-angle < 20°, explained running-related pain in the quadriceps muscles for males (ß = 0.991)25,70. It is important to note that our model shows discrepancies between right and left variables for the same Q-angle values, as well as right and left standing and supine Q-angles; this may be due to the position and the plane that a Q-angle is measured71. Although a standing right Q-angle of 15° < Q-angle < 20° increased the risk for pain in the quadriceps, a left supine and a standing left Q-angle of 15° < Q-angle < 20° was found to be protective against running-related pain at the quadriceps (ß = -0.657) and for the FADI (ß = -0.394), respectively. These differences in pain explanation between sides were unexpected and are challenging to reconcile as we may not have enough data to explain these findings, however the relationship between muscle strength and leg dominance may offer a possible explanation. Leg dominance, as noted by Jacobs et al. (2005), can result from side differences in hip abductor strength72,73, causing changes in recruitment patterns and ligament loads that may predispose a runner to injury74. Previous research has shown that strength differences in hip extensors75, and between knee extensors and flexors76 (with weaknesses commonly found in knee extensor muscles77,78), can differ between sides, play a role in asymmetry, and further contribute to leg dominance. Similar parallels regarding muscle weakness and asymmetry contibuting to leg dominance may be drawn from our findings as both males and females presented with weaker hip flexors than hip extensors. This may have lead runners to utilize their hip extensors for dynamic balance stability at the knee74. Unfortunately, we did not measure leg dominance in this study. Moreover, while we used adjusted R2 values to account for multiple explanatory variables in the model, these asymmetrical findings could be caused by Type I errors. Further to this concept of lower-limb asymmetries, we found that increased strength in the right hip abductors (ß = -0.756) was protective against pain, while increased strength in the left hip abductors positively explained whole body (ß = 0.950) and lower back (ß = 0.440) pain.   26 Again, this difference may represent hip asymmetry, such as leg length discrepancy which causes the hemipelvis on the shorter leg to be rotated anteriorly and the hemipelvis on the longer leg to be rotated posteriorly79,80, or an anterior pelvic tilt81 caused by tight hip flexors and gluteus muscles82-84. As leg length symmetry was incorporated into the model for male participants, but did not appear as a significant protective variable (likely due to our small sample size), these differences may be a result of muscle weakness and tilted pelves, but given that we did not assess hemipelvis alignment, we were unable to make definitive conclusions regarding the causes of this asymmetry. The latter explanation of muscle weakness is supported by differences in hip strength, as males presented with weak hip flexor muscles and hip abductor strength imbalances. These factors may have contributed to instability of the pelvis during midstance, which could be a possible explanation for pain in the lower back region85. All males tested positive for the Hamstring Contracture Test, indicating that hamstring inflexibility was characteristic among the male group. Chronic tight hamstrings would represent a possible mechanism for decreasing the anterior pelvic tilt. This increased tightness or decreased flexibility in the hip extensors may have also explained hamstrings pain; however, we had no male participants who tested negative on the Hamstring Contracture Test as a comparison group in our sample. Normal findings for both legs on the Thomas Test, a functional test indicative of tightness in hip flexor muscles17 (iliopsoas, rectus femoris, and the iliotibial band, also known as ITB), was protective against pain in the groin region (ß = -0.30). Likewise, males who had a normal finding for both legs on Ober’s Test, which indicates tightness in the ITB86, were protected against running-related pain in the gluteal region (ß = -0.33). These findings are consistent with the literature and with clinical approaches that encourage athletes to maintain hip flexor function and flexibility to protect against pain at the hip and groin. Baseline pain scores were significant variables which explained running-related pain at each of their respective anatomical sites below the knee; in fact, the FADI (ß = 0.544), shin (ß = 0.518), and knee (ß = 0.424) baseline variables explained a large amount of running-related pain in the male model. This is consistent with the notion that runners who experience pain prior to starting a training program, or have not yet fully recovered from a previous injury before training, will experience more pain with increases in training volume and intensity.    27 2.4.4 Explanatory variables for the female model As demonstrated by our results in Phase I, when comparing running-related pain scores at Week 12, a significant main effect of sex was found in the FADI, but no differences between males and females were found at any of the VAS sites. Although differences between sexes were only found in the FADI, our regression analyses indicated that the risk factors which explained running-related pain in males differed than those that explained pain for females. Our third hypothesis was that the variables explaining pain for the female model would be Q-angles in the highest quartile, and hip strength deficits. The literature has consistently shown that females have wider pelves and higher Q-angles compared to males due to a range of factors42,43,65,87,88 including pelvic width, hip strength deficits, and greater femoral neck anteversion65. These factors can result in changes to kinematics88, anatomical structure, the position of the patellae, and alignment in the lower extremity68,89 that force the proximal portion of females’ legs to angle inwardly; they may also explain the variation in Q-angle magnitude between sides, and subsequently the differences in the areas of pain explained by right and left Q-angles. We recognize that a previous study by Walter et al. (1980) disagrees with this notion22; researchers followed 1680 runners who trained for a shorter (either a 4-km or a 5.6-km) and a longer (16-km or a 22-km) race respectively over a 12-month period, and found no association between the aforementioned anthropometric variables and injury rates in males or females. It is difficult to compare our results to Walter et al.’s findings as no detail was given as to how they assessed the anthropometric and anatomical variables, and whether they included both right and left sides in the assessment; their study also had a larger sample size, higher training volume, and a different training program length. Many female runners with larger Q-angles also present with genu valgum40,45, a condition in which the portion of the extremity distal to the knee is angled outwards. This finding is consistent with our sample as we assessed supine and standing Q-angles, as well as standing leg alignment, and many of the female runners in our sample (n=39) presented with a valgus leg alignment and the majority of the female runners had a Q-angle magnitude of > 15°. A larger Q-angle and a valgus alignment may help explain why females tend to show greater hip adduction and knee abduction during the stance phase of running52,90 which can contribute to running-related pain at the knee45.   28 As hypothesized, Q-angles in the highest quartile, which are known to be abnormal ranges for females42,64,65, explained pain in females. A standing right Q-angle of > 20° explained pain in the calf (ß = 0.222), a standing left Q-angle of > 20° explained pain in the quadriceps (ß = 0.304), and a supine left Q-angle of > 20° explained pain in the shin (ß = 0.350)25,70,91. Standing and supine Q-angles in the lowest quartile also significantly explained pain as a left supine Q-angle < 10° explained pain at the knee (ß = 0.309) and in the whole body (ß = 0.345), and a standing left Q-angle > 10° explained whole body pain (ß = 0.336). It is important to note, however, that the number of participants in each of these lowest quartile angle groups were small (n=3 and n=1 for standing and supine, respectively); thus a higher number of participants with this Q-angle range would be needed to better understand the effect of female Q-angles that are   > 10°, at the population level. In general for the female model, left supine and standing Q-angles were more positively associated with running-related pain than the right side- again, possibly due to limb dominance, but this was not specifically assessed. This topic requires further research with a larger sample size in order to establish a more meaningful effect. We also hypothesized that hip strength deficits would explain running-related pain; an imbalance between hip extensors and hip flexors, with hip extensors being relatively stronger, explained pain at the groin (ß = 0.292) and gluteal (ß = 0.306) regions in females. Much of the literature on running injuries has focused on the effects of hip extensor, hip flexor relationships and their association with pain at the knee, rather than the groin or gluteal region. Research by Ireland et al. (2003) found that female participants with knee pain that presented as PFPS in one leg, had weaker hip flexors and hip abductors in their affected leg compared to their uninjured leg and females in the uninjured group16. Similarly, Kendall et al. (2007) investigated the relationships between lower-limb explanatory variables and PFPS; comparing runners with PFPS to an uninjured control group, they found that 90% of runners in the PFPS group showed decreased hip flexor and abductor strength92. Niemuth et al. (2005) also found RRIs to be associated with weak hip flexors when comparing muscle strength differences between runners’ injured and uninjured legs93. While these studies do not explain the association between muscle strength and groin/gluteal pain specifically, they offer insight on the relationships among hip muscle weakness, side-to-side strength imbalances, and running-related overuse injuries. Muscle strength deficits, such as a strength imbalance between the vastus lateralis and vastus medialis oblique muscles may also contribute to running-related pain caused by lateral   29 patellar tracking disorders94-97 such as PFPS98-101; a tight vastus lateralis muscle may pull the patella farther in the lateral direction- shearing the underside of the patella against the lateral femoral condyle. This condition often occurs in individuals with larger Q-angles, but we did not collect the muscle-specific strength measures to confirm this mechanism in our sample. While baseline explanatory variables appeared most frequently at anatomical sites below the knee in the male model, suggesting a “distal-to-proximal” pain mechanism, baseline variables appeared most frequently between the hip and the knee in the female model, suggesting a “proximal-to-distal” pain mechanism52,102. These variables were once again amongst the strongest variables that explained pain in the model, with baseline VAS scores explaining gluteal (ß = 0.371), groin (ß = 0.485), and knee (ß = 0.538) pain. As the cause of a running injury/running-related pain could be due to a myriad of training, strength, and biomechanical factors, these proposed sex-specific pain mechanisms can serve as prevention and treatment guides for clinicians. For example, as females exhibit greater hip internal rotation and adduction, as well as greater knee abduction while running than men103, clinicians could create a biomechanical injury prevention plan that focuses on strengthening the areas that contribute to this “proximal-to-distal” mechanism. Male runners could receive “distal-to-proximal” prevention plans that focus on curbing an increase in ankle rotation103, or the risk of Achilles tendinopathy104, and navicular stress fractures105. Comparing the two models, it was evident that females had fewer protective variables against running-related pain than males. Previous research had suggested that leg length symmetry was not a risk factor for overuse running injuries11,31, however it was found to be the most frequent and strongest protective variable for females against pain in the calf (ß = -0.408) and in the lower back (ß = - 0.252) regions45. Variables that protect against running-related pain in females are still elusive. As running research began by conducting studies using only male participants, it may be that the variables we chose to include are more appropriate for estimating male injury risk, while different tests and variables are needed in order to better understand running-related pain in females. Researchers have noted that sex-specific factors may determine how pain is experienced and perhaps differences in pain perception could account for sex differences in running-related pain106; for example, females who spend more time in painful footwear, or have given birth, have a higher pain threshold compared to males and females who have not had these experiences.   30 2.4.5 Risk factors across sex Our fourth hypothesis stated that risk factors across sex would be attributed to a previous history of injury, and increased BMI. While increased BMI was a significant explanatory variable for both the shin (ß = 0.386) and the calf (ß = 0.378) regions in the male model, it was not a significant variable in the female model; albeit, a heavier body weight was found to explain pain at the knee (ß = 0.206) and the calf (ß = 0.250) in the female model. The etiology of running injuries and pain in the distal portion of the lower limb has been attributed to a higher body weight45, and a greater BMI20 in some studies, but not in others18,22. On the contrary, according to the International Olympic Committee’s (IOC) Relative Energy Deficiency in Sport Clinical Assessment Tool (RED-S CAT), weight loss is a criterion to evaluate health status and risk of participation in sport107. It may be that both high and low BMI values are risk factors for running-related pain, particularly the latter in females45 and that an average BMI may be less associated with injury. The literature is inconsistent on the matter18,108 and more research is required to better understand whether an average BMI can indeed protect against running-related pain. With regards to our findings on pain, individuals who have a greater BMI and body weight need to push-off more as the force that calf muscles generate during the stance phase are directly proportional to body weight109, which also increases the likelihood of developing tendinopathy; in keeping with Cavanagh & Lafortune’s (1980) findings that approximately 75% of the most common running injuries (including tendinopathy, plantar fasciitis, shin splints, chondromalacia, and stress fractures) are caused by high forces at push-off, a higher BMI and weight would explain for more pain at the calf region110. Weight and BMI are also important factors when considering how the vertical ground reaction force (body weight) changes with kinematic components such as foot strike type (rear-foot, mid-foot, and fore-foot), or with shoe type (shod vs. minimalist)15. As for injury history, much of the literature suggests that a previous injury would be indicative of a future injury in the same area111. Our findings seem to counter this as a previous musculoskeletal injury was not a significant variable in either the male or female models, and a previous RRI was found to be protective of running-related pain in the ankle region for the female model (ß = 0.254). Behavioural changes may offer an explanation as to why a previous injury was protective of pain. Furthermore, previously injured runners112,113 are cognizant of the   31 biomechanical and training errors that had caused their past injuries and may have adjusted factors such as their running form in order to prevent these injury-causing movements in the future. Although our sample size was greater for the female group than the male group, the number of significant explanatory variables was higher for males compared to females; this could be due to a number of factors. Males may have been more competitive over the 12-week training program, (i.e. during the track workouts and weekly long runs, it was observed that males trained at a harder and higher intensity and pace than their female counterparts). Furthermore, more males were running additional mileage and participating in a higher number of sports in conjunction with the running program as noted by the activity journals they were asked to keep throughout the training program. If this were the case, throughout the 12-week training period, males would have had less opportunity properly recover114, which may have resulted in kinematic changes to compensate for fatigue or pain in certain areas.    32 3 Conclusion 3.1 Conclusions regarding thesis hypotheses Hypothesis 1: Although a higher number of females (n=6) reported an RRI compared to their male counterparts (n=4) following the conclusion of the training program, no significant differences were found between male and female running injury incidence rates per 1000 training sessions. With regards to the second portion of the hypothesis, for all VAS regions, we reject this hypothesis as no significant differences in running-related pain to the lower extremity were found between sex, however we accept this hypothesis for the FADI as a significant main effect of sex was found with females reporting higher FADI scores than males.  Hypothesis 2: We accept this hypothesis as our regression model shows different baseline explanatory variables for each of the VAS pain sites and the FADI.  Hypothesis 3: We accept this hypothesis as Q-angles in the highest quartile and hip strength deficits explained running-related pain.  Hypothesis 4: Our final hypothesis stated that the risk factors across sex would be a previous history of injury and BMI; we reject this hypothesis as a previous injury history was a protective variable for females, while BMI was only a risk factor for males.  3.2 Limitations and future research directions It is important to note that pain perception is an objective measure; as such, individuals may have indicated the same score on a VAS but experienced different levels of pain. As previously mentioned, this can be due to a number of factors including the amount of time spent in painful footwear, the time an individual spends on their feet or performing weight-bearing activities given their occupation, and whether a female had previously given birth. In order to standardize pain perception across participants, future researchers should consider the above variables, as well as possibly conducting pressure-pain threshold assessments. Although we did not consider the association of connective tissue with injury, studies have shown changes in ligament laxity115-117 or an increased risk of injury to the anterior cruciate ligament with the changes in hormone levels118 that accompany the menstrual cycle. Along with   33 hormonal changes, tendon and ligament injuries may also have an underlying genetic component119; for example, the TNC gene is responsible for a tissue’s response to mechanical load, while the COL5A1 gene regulates collagen assembly120. Unfortunately, we did not ask participants to keep records of their menstrual cycle, or record runners’ family injury history with regards to connective tissue injury; perhaps future studies could take note of these variables and their effects on running-related pain/RRIs. As participants ran during the winter, the weather played an important role with regards to safety and running surface choice. Environmental factors such as snow and ice may have impacted how participants ran as runners may have accommodated for potential risks that could have otherwise led to an RRI. For future studies, it is recommended to carry-out the training program during more weather-appropriate conditions. Participants were asked to adhere to the program as closely as possible, but compliance varied. To accommodate runners’ training schedules for upcoming running events, a running cap of 20-km in addition to the assigned training mileage for each week was imposed on all participants, but this variation in running mileage may have had an effect on the participants’ running pain scores. Future studies should control for the number of weight-bearing activities runners participate in concurrent to the training program. We recognize that there may have been a cumulative effect of stresses expressed during non-running activities that may have presented as running-related pain, but a larger sample size is needed to determine this by accounting for the variations in terrain (i.e. roads of greater or lesser camber, hill gradients, running surfaces, etc.) along with measurements of running gait, and other related parameters (i.e. leg dominance, stride characteristics, three-dimensional foot morphology, foot strike type, etc.). These are likely important factors for injury, but due to the practical issues related to including these variables in the analysis (the time, expense, and considerations for the multiple forward stepwise regression model), it was unfeasible to include all of these parameters in the study. While this study focused on differences between right and left sides, and including separate variables for each side into the model, future studies may consider determining  clinically significant side-to-side differences, and treating these variables as categorical; this would help lessen the amount of explanatory variables and mutliple comparisons used in the regression model.     34 Due to the small number of injured participants, we were unable to create a regression model to explain RRIs, thus we used a regression model to explain running-related pain. For future studies, a training program with a higher load, such as that of a half-marathon over a 12-week training period would increase the likelihood of reported RRIs and running-related pain. Financial constraints played a role in recruitment in terms of advertising, and limited our ability to expand the sample size beyond its current numbers. The sample size was restrictive with respect to the number of variables used for the multiple forward stepwise regression model in Phase II and assessing the strength of specific risk factors for running-related pain across males and females. Initially, we aimed to recruit 100 participants of each sex for the analysis; unfortunately, we fell short of our goal due to practical implications, which required the study to be completed on a fixed timeline. As such, few runners who satisfied the study inclusion criteria were available to participate in the running program during the winter months. As we were unable to determine statistically significant differences for the number of reported injuries between males and females, a larger sample size is needed to understand whether one sex has a higher number of reported injuries while training for a 10-km race. A larger sample size would also protect against Type I errors given the number of explanatory variables used for the regression models. Multiple regression models do not take measurement error into account as it is assumed that all variables are measured precisely. For future research, analyses such as structured equation modeling can be used that can take this error into account.  Our results show that different risk factors contributed to the running-related pain experienced by males and females in selected regions of the lower limb; this emphasizes the need for research on females, as well as different prevention and treatment plans for females. It is important to consider that the variables we chose for this study did not explain pain for females as well as they explained pain for males; variables investigating balance, limb dominance, psychosocial behaviours, pain threshold, differences in connective tissue due to hormonal changes and genetics, and gait analysis, may allow researchers to better understand running-related pain in females. This study serves as a foundation for future research that can implement interventions to investigate whether prevention strategies based on the findings of each regression model could mitigate running-related pain. For example, future studies can use control groups and   35 experimental groups that utilize stretching programs, as well as strategies to increase muscle strength, pelvic stability, and hip muscle flexibility to further investigate whether running-related pain can be decreased by addressing sex-specific risk factors.     36 References 1. Blair SN, Goodyear NN, Gibbons LW, et al. Physical Fitness and Incidence of Hypertension in Healthy Normotensive Men and Women. JAMA 1984; 252: 487–490. 2. Blair SN, Kohl HW, Paffenbarger RS, et al. Physical Fitness and All-Cause Mortality: A Prospective Study of Healthy Men and Women. JAMA 1989; 262: 2395–2401. 3. Powell KE, Thompson PD, Caspersen CJ, et al. Physical Activity and the Incidence of Coronary Heart Disease. http://dxdoiorg/101146/annurevpu08050187001345 2003; 8: 253–287. 4. Whaley M, Kampert J, Kohl 3rd H, et al. Physical fitness and clustering of risk factors associated with the metabolic syndrome. Med Sci Sports Exerc 1999; 31: 287–293. 5. Callaghan P. Exercise: a neglected intervention in mental health care? Journal of Psychiatric and Mental Health Nursing 2004; 11: 476–483. 6. Kalak N, Gerber M, Kirov R, et al. Daily Morning Running for 3 Weeks Improved Sleep and Psychological Functioning in Healthy Adolescents Compared With Controls. Journal of Adolescent Health 2012; 51: 615–622. 7. Satterthwaite P, Norton R, Larmer P, et al. Risk factors for injuries and other health problems sustained in a marathon. British Journal of Sports Medicine 1999; 33: 22–26. 8. van Gent BRN, Siem DD, van Middelkoop M, et al. Incidence and determinants of lower extremity running injuries in long distance runners: A systematic review. British Journal of Sports Medicine 2007; 41: 469–480. 9. van Middelkoop M, Kolkman J, Van Ochten J, et al. Prevalence and incidence of lower extremity injuries in male marathon runners. Scandinavian Journal of Medicine & Science in Sports 2008; 18: 140–144. 10. Lopes AD, Hespanhol MLC Jr, Yeung SS, et al. What are the Main Running-Related Musculoskeletal Injuries? Sports Med 2012; 42: 891–905. 11. Wen DY, Puffer JC, Schmalzried TP. Injuries in Runners: A Prospective Study of Alignment. Clinical Journal of Sport Medicine 1998; 8: 187. 12. Nielsen RO, Buist I. Training errors and running related injuries: a systematic review. International Journal of Sports Medicine 2012. 13. Taunton JE, Ryan MB, Clement DB, et al. A prospective study of running injuries: the Vancouver Sun Run ‘In Training’ clinics. British Journal of Sports Medicine 2003; 37: 239–244. 14. Arndt AN, Komi PV, Brüggemann GP, et al. Individual muscle contributions to the in vivo achilles tendon force. Clinical Biomechanics 1998; 13: 532–541.   37 15. Lieberman DE, Venkadesan M, Werbel WA, et al. Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature 2010; 463: 531–535. 16. Ireland ML, Willson JD, Ballantyne BT, et al. Hip Strength in Females With and Without Patellofemoral Pain. Journal of Orthopaedic & Sports Physical Therapy 2003; 33: 671–676. 17. Kendall FP, McCreary EK, Provance PG. Tests for length of hip flexor muscles. Baltimore, Md: Muscles: Testing and Function. 4th ed., 1993. 18. Macera CA, Pate RR, Powell KE, et al. Predicting Lower-Extremity Injuries Among Habitual Runners. Arch Intern Med 1989; 149: 2565–2568. 19. Hootman JM, Macera CA, Ainsworth BE, et al. Predictors of Lower Extremity Injury Among Recreationally Active Adults. Clinical Journal of Sport Medicine 2002; 12: 99. 20. Marti B, Vader JP, Minder CE, et al. On the epidemiology of running injuries The 1984 Bern Grand-Prix study. Am J Sports Med 1988; 16: 285–294. 21. Jacobs S, Berson BL. Injuries to runners: A study of entrants to a 10,000 meter race. Am J Sports Med 1986; 14: 151–155. 22. Walter SD. The Ontario Cohort Study of Running-Related Injuries. Arch Intern Med 1989; 149: 2561–2564. 23. Koplan JP, Powell KE, Sikes RK, et al. An Epidemiologic Study of the Benefits and Risks of Running. JAMA 1982; 248: 3118–3121. 24. Pollock M, Gettman L, Milesis C, et al. Effects of frequency and duration of training on attrition and incidence of injury. Med Sci Sports 1976; 9: 31–36. 25. Rauh MJ, Koepsell TD, Rivara FP, et al. Epidemiology of Musculoskeletal Injuries among High School Cross-Country Runners. Am J Epidemiol 2006; 163: 151–159. 26. Rauh MJ, Margherita AJ, Rice SG, et al. High School Cross Country Running Injuries: A Longitudinal Study. Clinical Journal of Sport Medicine 2000; 10: 110. 27. Buist I, Bredeweg SW, Lemmink KA, et al. Predictors of Running-Related Injuries in Novice Runners Enrolled in a Systematic Training Program A Prospective Cohort Study. Am J Sports Med 2010; 38: 273–280. 28. Neely FG. Intrinsic Risk Factors for Exercise-Related Lower Limb Injuries. Sports Med 1998; 26: 253–263. 29. Lun V, Meeuwisse WH, Stergiou P, et al. Relation between running injury and static lower limb alignment in recreational runners. British Journal of Sports Medicine 2004; 38: 576–580.   38 30. Montgomery L, Nelson F, Norton J, et al. Orthopedic history and examination in the etiology of overuse injuries. Med Sci Sports Exerc 1989; 21: 237–243. 31. Wen D, Puffer J, Schmalzried T. Lower extremity alignment and risk of overuse injuries in runners. Med Sci Sports Exerc 1997; 29: 1291–1298. 32. Warren B, Jones C. Predicting plantar fasciitis in runners. Med Sci Sports Exerc 1987; 19: 71–73. 33. Cowan DN, Jones BH, Robinson JR. Foot Morphologic Characteristics and Risk of Exercise-Related Injury. Archives of Family Medicine 1993; 2: 773. 34. Krivickas LS. Anatomical Factors Associated with Overuse Sports Injuries. Sports Med 1997; 24: 132–146. 35. Kvist M. Achilles Tendon Injuries in Athletes. Sports Med 1994; 18: 173–201. 36. Ogon M, Aleksiev AR, Pope MH, et al. Does Arch Height Affect Impact Loading at the Lower Back Level in Running? Foot Ankle Int 1999; 20: 263–266. 37. Nadler SF, Malanga GA, DePrince M, et al. The Relationship Between Lower Extremity Injury, Low Back Pain, and Hip Muscle Strength in Male and Female Collegiate Athletes. Clinical Journal of Sport Medicine 2000; 10: 89. 38. Li Y, Wang W, Crompton RH, et al. Free vertical moments and transverse forces in human walking and their role in relation to arm-swing. Journal of Experimental Biology 2001; 204: 47–58. 39. Chao EY, Laughman RK, Schneider E, et al. Normative data of knee joint motion and ground reaction forces in adult level walking. Journal of Biomechanics 1983; 16: 219–233. 40. Benas D. Special considerations in women’s rehabilitation programs. Rehabilitation of the Injured Knee 1984; 393–405. 41. Simoneau GG, Hoenig KJ, Lepley JE, et al. Influence of Hip Position and Gender on Active Hip Internal and External Rotation. Journal of Orthopaedic & Sports Physical Therapy 1998; 28: 158–164. 42. Horton MG, Hall TL. Quadriceps Femoris Muscle Angle: Normal Values and Relationships with Gender and Selected Skeletal Measures. Physical Therapy 1989; 69: 897–901. 43. Mizuno Y, Kumagai M, Mattessich SM, et al. Q‐angle influences tibiofemoral and patellofemoral kinematics. Journal of Orthopaedic Research 2001; 19: 834–840. 44. Phinyomark A, Hettinga BA, Osis ST, et al. Gender and Age-Related Differences in Bilateral Lower Extremity Mechanics during Treadmill Running. PLOS ONE 2014; 9:   39 e105246. 45. Taunton JE, Ryan MB, Clement DB, et al. A retrospective case-control analysis of 2002 running injuries. British Journal of Sports Medicine 2002; 36: 95–101. 46. Buist I, Bredeweg SW, Bessem B, et al. Incidence and risk factors of running-related injuries during preparation for a 4-mile recreational running event. British Journal of Sports Medicine 2010; 44: 598–604. 47. Tashjian RZ, Deloach J, Porucznik CA, et al. Minimal clinically important differences (MCID) and patient acceptable symptomatic state (PASS) for visual Analogue scales (VAS) measuring pain in patients treated for rotator cuff disease. Journal of Shoulder and Elbow Surgery 2009; 18: 927–932. 48. Ryan MB, Valiant GA, McDonald K, et al. The effect of three different levels of footwear stability on pain outcomes in women runners: a randomised control trial. British Journal of Sports Medicine 2011; 45: 715–721. 49. Ryan M, Elashi M, Newsham-West R, et al. Examining injury risk and pain perception in runners using minimalist footwear. British Journal of Sports Medicine 2013; 48: bjsports–2012–092061–1262. 50. Rauh MJ, Koepsell TD, Rivara FP, et al. Quadriceps Angle and Risk of Injury Among High School Cross-Country Runners. Journal of Orthopaedic & Sports Physical Therapy 2007; 37: 725–733. 51. Hulin BT, Gabbett TJ, Caputi P, et al. Low chronic workload and the acute:chronic workload ratio are more predictive of injury than between-match recovery time: a two-season prospective cohort study in elite rugby league players. British Journal of Sports Medicine 2016; bjsports–2015–095364. 52. Ferber R, Hreljac A, Kendall KD. Suspected Mechanisms in the Cause of Overuse Running Injuries: A Clinical Review. Sports Health: A Multidisciplinary Approach 2009; 1: 242–246. 53. Clement DB, Taunton JE, Smart GW, et al. Survey of overuse running injuries. Sports Health: A Multidisciplinary Approach 1981; 47–58. 54. Pinshaw R, Atlas V, Noakes TD. The nature and response to therapy of 196 consecutive injuries seen at a runners' clinic. S Afr Med J 1984; 291–298. 55. Rolf C. Overuse injuries of the lower extremity in runners. Scandinavian Journal of Medicine & Science in Sports 1995; 5: 181–190. 56. Macintyre JG, Taunton JE, Clement DB, et al. Running Injuries: A Clinical Study of 4,173 Cases. Clinical Journal of Sport Medicine 1991; 1: 81. 57. Kalia M. Build Better Knees: The Ultimate Program For Runners Who Want, Stronger   40 Pain-Free Knees Without Medications Or Surgery. 2015. 58. Shultz SJ, Nguyen A-D, Windley TC, et al. Intratester and Intertester Reliability of Clinical Measures of Lower Extremity Anatomic Characteristics: Implications for Multicenter Studies. Clinical Journal of Sport Medicine 2006; 16: 155. 59. Grubbs N, Nelson R, Bandy W. Predictive validity of an injury score among high school basketball players. Med Sci Sports Exerc 1997; 29: 1279–1285. 60. Livingston LA, Mandigo JL. Bilateral Q angle asymmetry and anterior knee pain syndrome. Clinical Biomechanics 1999; 14: 7–13. 61. Livingston L, Mandigo J. Bilateral within-subject Q angle asymmetry in young adult females and males. Biomed Sci Instrum 1996; 33: 112–117. 62. Shambaugh J, Klein A, Herbert J. Structural measures as predictors of injury basketball players. Med Sci Sports Exerc 1991; 23: 522–527. 63. Hahn T, Foldspang A. The Q angle and sport. Scandinavian Journal of Medicine & Science in Sports 1997; 7: 43–48. 64. Hvid I, Andersen LI, Schmidt H. Chondromalacia Patellae: The Relation to Abnormal Patellofemoral Joint Mechanics. Acta Orthopaedica Scandinavica 2009; 52: 661–666. 65. Woodland LH, Francis RS. Parameters and comparisons of the quadriceps angle of college-aged men and women in the supine and standing positions. Am J Sports Med 1992; 20: 208–211. 66. Sanchez HM, Sanchez EG de M, Baraúna MA, et al. Evaluation of Q angle in differents static postures. Acta Ortopédica Brasileira 2014; 22: 325–329. 67. Guerra JP, Arnold MJ, Gajdosik RL. Q Angle: Effects of Isometric Quadriceps Contraction and Body Position. Journal of Orthopaedic & Sports Physical Therapy 1994; 19: 200–204. 68. Bayraktar B, Yucesir I, Ozturk A, et al. Change of qaudriceps angle values with age and activity. Saudi Medical Journal 2004; 25: 756–760. 69. Byl T, Cole JA, Livingston LA. What determines the magnitude of the Q angle? A preliminary study of selected skeletal and muscular measures. Journal of Sport Rehabilitation 2000; 9: 26–34. 70. Messier S, Davis S, Curl W, et al. Etiologic factors associated with patellofemoral pain in runners. Med Sci Sports Exerc 1991; 23: 1008–1015. 71. Stensdotter A-K, Andersson P-I, Rydh A, et al. Q-angle variations in standing and supine positions and for different measurement methods in women with and without patellofemoral pain. Advances in Physiotherapy 2009; 11: 88–96.   41 72. Jacobs C, Uhl TL, Seeley M, et al. Strength and fatigability of the dominant and nondominant hip abductors. 2005. 73. Fredericson M, Cookingham CL, Chaudhari AM, et al. Hip Abductor Weakness in Distance Runners with Iliotibial Band Syndrome. Clinical Journal of Sport Medicine 2000; 10: 169. 74. Ford KR, Myer GD, Hewett TE. Valgus knee motion during landing in high school female and male basketball players. Medicine and Science in Sports and Exercise 2003. 75. Hewett TE, Stroupe AL, Nance TA, et al. Plyometric Training in Female Athletes Decreased Impact Forces and Increased Hamstring Torques. Am J Sports Med 1996; 24: 765–773. 76. Huston L, Wojtys EM. Neuromuscular Performance Characteristics in Elite Female Athletes. Am J Sports Med 1996; 24: 427–436. 77. Knapik J, Bauman CL, Jones BH, et al. Preseason strength and flexibility imbalances associated with athletic injuries in female collegiate athletes. Am J Sports Med 1991; 19: 76–81. 78. Burkett L. Causative factors in hamstring strains. Med Sci Sports 1969; 2: 39–42. 79. Cummings G, Scholz JP, Barnes K. The Effect of Imposed Leg Length Difference on Pelvic Bone Symmetry. Spine 1993; 18: 368. 80. Pitkin HC, Pheasant HC. Sacrarthrogenetic Telalgia. J Bone Joint Surg Am 1936; 18: 706–716. 81. Boyle KL. Managing a Female Patient with Left Low Back Pain and Sacroiliac Joint Pain with Therapeutic Exercise: A Case Report. Physiotherapy Canada 2011; 63: 154–163. 82. Neumann DA. Kinesiology of the Hip: A Focus on Muscular Actions. Journal of Orthopaedic & Sports Physical Therapy 2010; 40: 82–94. 83. Bodack MP, Monteiro M. Therapeutic Exercise in the Treatment of Patients With Lumbar Spinal Stenosis. Clinical Orthopaedics and Related Research 2001; 384: 144. 84. Seidenberg P, Bowen JD. The hip and pelvis in sports medicine and primary care. 2010. 85. Nadler SF, Malanga GA, Bartoli LA. Hip muscle imbalance and low back pain in athletes: influence of core strengthening. Medicine & Science In Sports & Exercise 2002. 86. Puniello MS. Iliotibial Band Tightness and Medial Patellar Glide in Patients with Patellofemoral Dysfunction. Journal of Orthopaedic & Sports Physical Therapy 1993; 17: 144–148.   42 87. Livingston LA. The Quadriceps Angle: A Review of the Literature. Journal of Orthopaedic & Sports Physical Therapy 1998; 28: 105–109. 88. Pettitt R, Dolski A. Corrective Neuromuscular Approach to the Treatment of Iliotibial Band Friction Syndrome: A Case Report. Journal of Athletic Training 2000; 35: 96. 89. Powell KE, Kohl H, Caspersen C, et al. An Epidemiological Perspective on the Cause of Running Injuries. Physician and Sportsmedicine 1986; 14: 100–114. 90. Malinzak RA, Colby SM, Kirkendall DT, et al. A comparison of knee joint motion patterns between men and women in selected athletic tasks. Clinical Biomechanics 2001; 16: 438–445. 91. Wiklander JLJ. Injuries in runners. Am J Sports Med 1987; 15: 168–171. 92. Kendall KD, Ferber R, Louro M. Proximal and distal clinical measures related to patellofemoral pain syndrome in runners. J Athl Train 2007; 42: S114. 93. Niemuth PE, Johnson RJ, Myers MJ, et al. Hip Muscle Weakness and Overuse Injuries in Recreational Runners. Clinical Journal of Sport Medicine 2005; 15: 14. 94. Thomeé R, Renström P, Karlsson J, et al. Patellofemoral pain syndrome in young women. Scandinavian Journal of Medicine & Science in Sports 1995; 5: 245–251. 95. Souza DR, Gross MT. Comparison of Vastus Medialis Obliquus:Vastus Lateralis Muscle Integrated Electromyographic Ratios Between Healthy Subjects and Patients with Patellofemoral Pain. Physical Therapy 1991; 71: 310–316. 96. Callaghan MJ, McCarthy CJ, Oldham JA. Electromyographic fatigue characteristics of the quadriceps in patellofemoral pain syndrome. Manual Therapy 2001; 6: 27–33. 97. Grabiner MD, Koh TI, Draganich LF. Neuromechanics of the patellofemoral joint. Med Sci Sports Exerc 1994. 98. Kettelkamp DB. Management of patellar malalignment. J Bone Joint Surg Am 1981; 63: 1344–1348. 99. Hughston JC, Walsh WM, Puddu G. Patellar subluxation and dislocation. 4 ed. 2004. 100. Insall J, Falvo KA, Wise DW. Chondromalacia Patellae. A prospective study. J Bone Joint Surg Am 1976; 58: 1–8. 101. Huberti HH, Hayes WC. Patellofemoral contact pressures. The influence of q-angle and tendofemoral contact. J Bone Joint Surg Am 1984; 66: 715–724. 102. Phinyomark A, Osis S, Hettinga BA, et al. Gender differences in gait kinematics in runners with iliotibial band syndrome. Scandinavian Journal of Medicine & Science in Sports 2015; 25: 744–753.   43 103. Ferber R, McClay Davis I, Williams DS III. Gender differences in lower extremity mechanics during running. Clinical Biomechanics 2003; 18: 350–357. 104. Zafar MS, Mahmood A, Maffulli N. Basic Science and Clinical Aspects of Achilles Tendinopathy. Sports Medicine and Arthroscopy Review 2009; 17: 190–197. 105. Harrast MA, Colonno D. Stress Fractures in Runners. Clinics in Sports Medicine 2010; 29: 399–416. 106. Bendelow G. Pain perceptions, emotions and gender. Sociology of Health & Illness 1993; 15: 273–294. 107. Mountjoy M, Sundgot-Borgen J, Burke L, et al. The IOC relative energy deficiency in sport clinical assessment tool (RED-S CAT). British Journal of Sports Medicine 2015; 49: bjsports–2015–094873–1354. 108. Östenberg A, Roos H. Injury risk factors in female European football. A prospective study of 123 players during one season. Scandinavian Journal of Medicine & Science in Sports 2000; 10: 279–285. 109. Burdett R. Forces predicted at the ankle during running. Med Sci Sports Exerc 1981; 14: 308–316. 110. Cavanagh PR, Lafortune MA. Ground reaction forces in distance running. Journal of Biomechanics 1980; 13: 397–406. 111. van Mechelen DW. Running Injuries. Sports Med 1992; 14: 320–335. 112. van Mechelen DW. Can Running Injuries Be Effectively Prevented? Sports Med 1995; 19: 161–165. 113. Bovens A, Janssen G, Vermeer H, et al. Occurrence of running injuries in adults following a supervised training program. International Journal of Sports Medicine 1989; 10 Suppl 3: S186–90. 114. Ryan MB, MacLean CL. A review of anthropometric, biomechanical, neuromuscular and training related factors associated with injury in runners. International SportMed Journal 2006. 115. Deie M, Sakamaki Y, Sumen Y, et al. Anterior knee laxity in young women varies with their menstrual cycle. International Orthopaedics (SICOT) 2002; 26: 154–156. 116. Wojtys EM, Huston LJ, Lindenfeld TN, et al. Association Between the Menstrual Cycle and Anterior Cruciate Ligament Injuries in Female Athletes. Am J Sports Med 1998; 26: 614–619. 117. Wojtys EM, Huston LJ, Boynton MD, et al. The Effect of the Menstrual Cycle on Anterior Cruciate Ligament Injuries in Women as Determined by Hormone Levels. Am J   44 Sports Med 2002; 30: 182–188. 118. Karageanes SJ, Blackburn K, Vangelos ZA. The Association of the Menstrual Cycle with the Laxity of the Anterior Cruciate Ligament in Adolescent Female Athletes. Clinical Journal of Sport Medicine 2000; 10: 162. 119. Smith HC, Vacek P, Johnson RJ, et al. Risk Factors for Anterior Cruciate Ligament Injury A Review of the Literature—Part 2: Hormonal, Genetic, Cognitive Function, Previous Injury, and Extrinsic Risk Factors. Sports Health: A Multidisciplinary Approach 2012; 4: 155–161. 120. September AV, Schwellnus MP, Collins M, et al. Tendon and ligament injuries: the genetic component. British Journal of Sports Medicine 2007; 41: 241–246.     45 Appendices A Consent form THE UNIVERSITY OF BRITISH COLUMBIA  Faculty of Medicine Department of Family Practice Allan McGavin Sports Medicine Centre 3055 Wesbrook Mall Vancouver, B.C. Canada V6Z 1T3   SUBJECT INFORMATION AND CONSENT FORM  THE EFFECT OF GENDER ON RUNNING INJURIES  Primary Investigator:    Jack E. Taunton, MD       Division of Sports Medicine        University of British Columbia  Co-Investigators:    Michael Koehle, MD, PhD Division of Sports Medicine, School of Kinesiology University of British Columbia  Michael Ryan, PhD   Allan McGavin Sports Medicine Centre  University of British Columbia    Maha Elashi, BHK  Human Kinetics  University of British Columbia   Contact Person IN EMERGENCIES available 24 hours:   Maha Elashi  PURPOSE The purpose of this study is to examine whether gender is risk factor for running injuries. You may decline to enter, or withdraw from, this experiment at any time without any consequences to your medical care.     Should you decline involvement in this study, you may contact Michael Ryan for information on alternative training programs for runners. You can withdraw from this study at any time. If you withdraw from the study any personal information you provide will be destroyed.   Funding for this research has been provided by Nike Inc.      46 RESEARCH PROCEDURES Participants who are interested in beginning a running clinic that will prepare you to complete a 10-kilometer event in 13 weeks will be invited to join the study. Subjects should be able to already run continuously for 60 minutes, tolerate 20-km - 40-km per week of running, and have not experienced a running-related injury requiring a stoppage of 2-weeks or more in the past 6 months. If you agree to participate in this study, you will take part in a 12-week run training program which will involve one or two group training sessions and two individual training sessions per week. A baseline testing session will take place prior to the start of the training program and will consist of an interview of your training and injury history, documentation of your lower body alignment, a 3-dimensional foot scan, assessment of the pressure distribution under your feet while you walk, and a test of how much postural sway (i.e. balance measurement) you have.    Participation in our study will also require you to keep weekly records of your participation in the training schedule and how many times you are unable to complete three scheduled running workout due to pain. You will also be asked to complete one additional questionnaire that will assess body-area specific pain, and foot and ankle disability at the baseline session then at the 6 and 13 week points. All questionnaires administered after the baseline session can be completed remotely and returned to study personnel via email. It is important to understand that you are not required to answer any questions within these questionnaires if you are not comfortable doing so.    If you have been diagnosed with systemic inflammatory disease, connective tissue disease, previous local trauma or you have any other injury, which may influence your physical ability, you may not be eligible to take part in this study.    TIME REQUIREMENTS You will be asked to come to the Fortius Multisport Centre of Excellence (3713 Kensington Ave. Burnaby, BC, V5B 0A7) for the initial baseline session which will take approximately 120 minutes, as well as once every Saturday for the group run session part of your program. There will be an optional 50-minute group track workout on every Wednesday starting in the third week of the program.      The running program will consist of between four run sessions per week varying in length from 15-min – 100-min, depending on your running speed. Every Saturday there will be a long run scheduled, and these runs will generally increase in distance (and duration) as you advance through the running program. In addition to the Saturday run, there will be three separate runs during the week that you will be encouraged to complete on your own time. One or two of these separate runs will be performed at a easy/recovery pace, while the remaining run will be used to improve your running speed, complete with specific instructions for completing the workout included in your running program.    Your involvement with the running program itself will require between two to three hours each week, depending on your running pace and which point in the program you are (there will be a greater time commitment later in the program as your weekly running volume increases).     47 RISKS & BENEFITS Participating in any running program brings with it a risk of experiencing a running injury. Previous research with runners training for the Vancouver Sun Run in a similar group format has reported that 29.5% of individuals self-reported experiencing an injury during a 12-week period. Most injuries (35.5%) in this study were classified as pain during a run, but not restricting distance or speed. Should you experience an injury in this study, you are encouraged to contact Maha Elashi for instructions on how to proceed with your run training. In the event of a severe injury, you will be provided with references to a sports medicine physician.  If at any time you have any questions or concerns, we would be happy to answer them for you. It is our goal that you feel fully informed before commencing as a subject in this study.  If at anytime we have to stop this study for whatever reason, we will contact you immediately by phone to explain to you the reasons for stopping the study.  CONFIDENTIALITY Data from pressure distribution, 3-dimensional foot scan, and postural sway (balance test) will be sent to Matthew Nurse at The Nike Sport Research Lab in Beaverton, OR, USA. Any study related data, sent outside of Canadian borders may increase the risk of disclosure of information because the laws in those countries [for example, the Patriot Act in the United States] dealing with protection of information may not be as strict as in Canada. However, all study related data that might be transferred outside of Canada will be coded (this means it will not contain your name or personal identifying information) before leaving the study site. By signing this consent form you are consenting to the transfer of your information to organizations located outside of Canada [The Nike Sport Research Lab in Beaverton, OR, USA].  A scientific paper may be submitted to an appropriate peer-reviewed journal following completion of this research. Your confidentiality will be respected. However, research records or other source records identifying you may be inspected in the presence of the Investigator or his or her designate by representatives of Nike Inc.  You will be assigned a unique study number as a subject in this study. Only this number will be used on any research-related information collected about you during the course of this study, so that your identity [i.e. your name or any other information that could identify you] as a subject in this study will be kept confidential. Information that contains your identity will remain only with the Principal Investigator and/or designate. The list that matches your name to the unique study number that is used on your research-related information will not be removed or released without your consent unless required by law. Your rights to privacy are legally protected by federal and provincial laws that require safeguards to insure that your privacy is respected and also give you the right of access to the information about you that has been provided to the sponsor and, if need be, an opportunity to correct any errors in this information. Further details about these laws are available on request to your study doctor.       48 WHAT IF SOMETHING GOES WRONG? Signing this consent form in no way limits your legal rights against the sponsor, investigators, or anyone else, and you do not release the study doctors or participating institutions from their legal and professional responsibilities.  WHO DO I CONTACT IF I HAVE ANY QUESTIONS OR CONCERNS ABOUT MY RIGHTS AS A SUBJECT? If you have any concerns or complaints about your rights as a research subject and/or your experiences while participating in this study, contact the Research Subject Information Line in the University of British Columbia Office of Research Services.  SIGNATURES My signature on this consent form means:  • I have read and understood the subject information and consent form. • I have had sufficient time to consider the information provided and to ask for advice if necessary. • I have had the opportunity to ask questions and have had satisfactory responses to my questions. • I understand that all of the information collected will be kept confidential. • I understand that my participation in this study is voluntary and that I am completely free to refuse to participate or to withdraw from this study at any time without changing in any way the quality of care that I receive. • I understand that I am not waiving any of my legal rights as a result of signing this consent form.      Signature of Subject   Printed Name     Date              Signature of Study Manager   Printed Name     Date   Maha Elashi    49 B Foot Posture Index (FPI) – foot type assignment 1. Talar Head Palpation -2 -1 0 1 2  Talar head palpable on lateral side/but not on medial side Talar head palpable on lateral side/slightly palpable on medical side Talar head palpable on lateral and medial side Talar head slightly palpable on lateral side/palpable on medial side Talar head not palpable on lateral side/but palpable on medial side 2. Supra and Infra Malleolar Curvature -2 -1 0 1 2  Curve below the malleolus either straight or convex Curve below the malleolus concave, but flatter/more shallow than the curve above the malleolus Both infra and supra malleolar curves roughly equal Curve below malleolus more concave than curve above malleolus Curve below malleolus markedly more concave than curve above malleolus 3. Calcaneal Frontal Plane Position -2 -1 0 1 2  More than estimated 5°  inverted (varus) Between vertical and an estimated 5°  inverted (varus) Vertical Between vertical and an estimated 5°  everted (valgus) More than an estimated 5°  everted (valgus) 4. Bulging in the Region of the TNJ -2 -1 0 1 2  Area of TNJ markedly concave Area of TNJ slightly, but definitely concave Area of TNJ flat Area of TNJ bulging slightly Area of TNJ bulging markedly 5. Height and Congruence of  the Medial Longitudinal Arch -2 -1 0 1 2  Arch high and acutely angled towards the posterior end of the medial arch Arch moderately high and slightly acute posteriorly Arch height normal and concentrically curved Arch lowered with some flattening in the central portion Arch very low with severe flattening in the central portion – arch making ground contact 6. Abduction/Adduction of the Forefoot on the Rearfoot -2 -1 0 1 2  More than an estimated 5°  inverted Between vertical and an estimated 5°  inverted Vertical Between vertical and an estimated 5°  everted More than an estimated 5°  everted FPI TOTAL f Neutral (0 to 5)  f Pronated (6 to 9)  f Highly Pronated (10+)  f Supinated (-1 to -4)   f Highly Supinated (-5 to -12) Foot Type  f Neutral                f Pronated                f Highly Pronated   50 C The Foot and Ankle Disability Index (FADI) Score and Sport Module Please answer every question with one response that most closely describes your condition within the past week by marking the appropriate number in the box. If the activity in question is limited by something other than your foot or ankle, mark N/A. Response Options 0 = Unable to do; 1 = Extremely difficult; 2 = Moderate difficulty; 3 = Slight difficulty; 4 = No difficulty  1. Standing  16. Walking up hills  2. Walking on even ground  17. Walking down hills  3. Walking on even ground without shoes  18. Going up stairs  4. Walking on uneven ground  19. Going down stairs  5. Stepping up and down curves  20. Squatting  6. Sleeping  21. Coming up to your toes  7. Walking initially  22. Walking 5 minutes or less  8. Walking approximately 10 minutes  23. Walking 15 minutes or greater  9. Home responsibilities  24. Activities of Daily Living  10. Personal Care  25. Light to moderate work (standing, walking)  11. Heavy work (push/pulling, climbing, carrying)  26. Recreational activities  12. Running   27. Jumping   13. Landing   28. Squatting and stopping quickly   14. Cutting, lateral movements   29. Low-impact activities   15. Ability to perform activity with your normal technique   30. Ability to participate in your desired sports as long as you would like   Pain related to the foot and ankle:  Response Options 0 Unbearable; 1 Severe Pain; 2 Moderate Pain; 3 Mild Pain; 4 No Pain   31. General level of pain   32. Pain at rest   33. Pain during your normal activity   34. Pain first thing in the morning   Office Use Only:  Score: ____________/136 points   51 D Visual Analogue Scale (VAS)      52 E Injury history form      53 F Weekly survey 1. Within the last 7 days, have you missed 3 or more consecutive running sessions due to running-related pain?  2. Please indicate the primary body area affected if you have missed 3 or more consecutive running sessions due to running-related pain.  3. How many run workouts did you complete this week?  G Manuscript Abstract Title: Males vs. Females: Is One Sex at a Greater Risk for Running Injuries? Author Names: 1Maha Elashi, BHK, 2Michael Ryan, PhD, 1Jack E. Taunton, MD, and 1Michael S. Koehle, MD, PhD. Affiliations: 1School of Kinesiology, University of British Columbia, Vancouver, BC, Canada, 2Centre for Musculoskeletal Research, Griffith University, Southport, Queensland, Australia. Objective: The proposed study represents the first of a three-tiered epidemiological project, in which the ultimate aim is to use a sex-targeted approach to reduce the incidence of running injuries. The initial and current study’s objective is to determine whether sex itself is a significant risk factor for injury in recreational runners. Study Design: Prospective cohort design. Subjects: 154 recreational runners (68 males [34 ± 1.2 years; 69 ± 1.5 kg; 170 ± 1.2 cm] and 86 females [34 ± 1.0 years; 68 ± 1.3 kg; 170 ± 1.0 cm]). Intervention: Runners took part in a 12-week organized run training program in preparation for an informal 10km running event. Outcome Measures: Outcome measures include number of running-related injuries (RRI) per 1000 training sessions, injury incidence via Kaplan-Meier Analysis, as well as Visual Analogue   54 Scale (VAS; 0-10), and Foot and Ankle Disability Index (FADI) pain scores at selected anatomical locations of the lower extremity, during weeks 0, 4, 8, and following the 10km running event (week 13). Results: Over the training period, significantly greater groin, gluteal, and whole body pain were reported for all participants; however, sex was not a significant factor in any location-specific outcome, or the whole body pain score. Conclusions: The primary finding from this study was that sex did not appear to be a significant factor for injury risk in runners. The relative risk of sustaining an RRI was not different across sexes (based on the 95% confidence interval of relative risk ratio), and the incidence of sustaining an injury was not different across sex (as shown in the Kaplan-Meier analysis). In addition, sex did not appear to be a factor in the onset of region-specific, running-related pain. Acknowledgements: NIKE Inc., UBC Environmental Physiology Laboratory, Allan McGavin Sports Medicine Centre, Fortius Institute, and Fit First. Disclosures: Maha Elashi and Michael Ryan received consulting payments for work to carry-out this research.     55 H Training program      56      57       58   

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