Syfte och frågeställningar: Syftet med studien var att beskriva skador och träningsvanor hos löpare som uppsöker sjukgymnast på stora träningscenter i Stockholmsområdet. Frågeställningarna var: Vilka löprelaterade skador förekommer? Hur ser träningsvanor hos dessa löpare ut? Hur många har haft tidigare löprelaterade skador? Hur ser skillnaden i löpmängd ut mellan kvinnor och män samt mellan knäskadade och icke-knäskadade? Metod: En enkät utformades och lämnades ut till 18 sjukgymnaster som arbetar på 12 träningscenter i Stockholmsområdet. Frågorna i enkäten baserades på en tidigare enkät och modifierades och anpassades efter tillgänglig litteratur och studiens syfte. Enkäten var indelad i 4 delar och innehöll frågor om demografi, löpning, andra träningsvanor och skador. Personer 18 år och äldre med smärta i benet som uppkommit i samband med löpning inkluderades i studien. Totalt samlades 40 enkäter in under perioden 2014-01-29 till och med 2014-06-27. Deskriptiv statistik användes i form av antal och procent samt medelvärde och standarddeviation för normalfördelad data och median och interkvartilt avstånd (IQR) för icke-normalfördelad data. Analytisk statistik i form av student t-test för normalfördelad data och Mann Whitney-U för icke-normalfördelad data användes för de jämförande analyserna. Resultat: Av 40 deltagare var 19 st kvinnor och 21 st män. Knäskada var den mest förekommande skadan, vilket totalt 52.5 % angav. Meniskskada var den vanligaste diagnosen vilket 20 % av deltagarna hade följt av löparknä/iliotibialt smärtsyndrom (17.5 %) och achillestendinos (12.5 %). Asfalt var det vanligaste underlaget att springa på. Långdistans var den mest frekventa löpträningen följt av intervall och backträning. De flesta deltagarna styrketränade (78 %). Av de 40 deltagarna hade 23 st (57.5 %) haft en tidigare löprelaterad skada och endast 12 st blev besvärsfria ifrån denna tidigare skada. Det fanns ingen signifikant skillnad i löpmängd mellan knäskadade och icke-knäskadade. Dock fanns en tendens till signifikant skillnad mellan knäskadade och icke-knäskadade gällande löphastighet (p = 0.05). Det fanns en signifikant skillnad mellan kvinnor och män gällande löphastighet (p = 0.02), men inte gällande antal sprungna kilometer per vecka, antal minuter löpning eller antal löptillfällen per vecka. Slutsats: Studien visar att knäskada är den vanligaste skadan och meniskskada den vanligaste diagnosen följt av löparknä/iliotibialt smärtsyndrom och achillestendinos hos löpare som uppsöker sjukgymnast på de utvalda träningscentrena i Stockholmsområdet. Mer än hälften av deltagarna har haft en tidigare löprelaterad skada.  Framtida studier med fler deltagare behövs för att kunna undersöka och dra generella slutsatser om samband mellan löpmängd och olika löprelaterade skador samt om träning såsom styrketräning kan användas i skadeförebyggande syfte. / Aim: The purpose of the study was to describe injuries and training characteristics in runners who consult a physical therapist at a large training center in the County of Stockholm. Research questions: What running related injuries (RRI) do they have? What are the training characteristics of these runners? How many have had earlier RRIs? How does running volume in this sample differ between men and women as well as between knee-injured and non-knee injured runners? Method: A questionnaire was designed and handed to 18 physical therapists who work at 12 different training centers in the County of Stockholm. The questions in the questionnaire were based on a previous questionnaire then modified based on previous studies and adjusted to fit the purpose of the study. The questionnaire was divided into 4 parts with questions about demographics, running, other forms of training and injuries. People, 18 years and older, with pain from the hip down, that started during running were included in the study. A total of 40 questionnaires were collected from 2014-01-29 to 2014-06-27. Descriptive statistics were used as number of observations and percent as well as mean and standard deviation for normally distributed data and median and inter quartile range (IQR) for non-normally distributed data. Statistical analysis was performed using student t-test for normally distributed data and Mann Whitney-U test for non-normally distributed data. Results: There were a total of 40 participants, 19 female and 21 male. Knee injury was the most common injury which 52.5 % of the participants stated. Meniscal injury was the most common diagnosis with 20 % of the participants followed by runner’s knee/iliotibial band syndrome (17.5 %) and achillestendinosis (12.5 %). Asphalt was the most commonly used running surface. Long distance running was the most common type of running followed by interval and hill training. Most of the participants were performing strength training (78 %). 23 (57.5 %) of the 40 participants have had a previous running related injury. There was not a significant difference in running volume between participants with knee injury and non-knee injury. There was a tendency towards a significant difference in running speed between runners with knee injury and non- knee injury (p = 0.05). There was a significant difference between women and men regarding running speed (p = 0.02) but not regarding number of kilometers, number of minutes or number of occasions of running per week.  Conclusions: The study demonstrates that knee injury is the most common running injury and that meniscal injury is the most common diagnosis followed by runner’s knee/iliotibial band syndrome and achillestendinosis in runners diagnosed by a physical therapist at the chosen training centers in the County of Stockholm. More than 50% have had a previous running related injury. Future studies with more participants are needed in order to draw conclusions on relationships between running volume and RRIs and if strength training can be used as prevention of RRIs. / <p>Presenterat vid OMT/FYIM Kongress/Årsmöte Täby Park hotell 20-21 mars 2015</p>

Foot strike type affects running mechanics and may influence overuse injury occurrence. Measuring the interaction between cumulative load and foot strike type may provide additional information that could eventually help with understanding injury mechanisms. The purpose of this study was to determine how foot strike type affects cumulative loading in runners, and to determine if individual metrics change throughout a 5-kilometer sub-maximal run. 30 participants ran on an instrumented treadmill for 5 km at 3.15 m/s with their preferred foot strike type (14 rearfoot strike, 16 non-rearfoot strike). Stride rate, foot strike angle, loading rate, per stride and per km (cumulative) vertical ground reaction force impulse, impact peak, absolute peak, knee negative work, and ankle negative work were calculated and compared across time and between groups. Per stride between-group main effects were seen for stance time (p=0.003), foot strike angle (p<0.001), and loading rate (p=0.040), all of which were greater for rearfoot strike runners. Per stride and cumulative ankle and knee negative work also showed significant differences, with ankle negative work being greater for non-rearfoot strike runners (p=<0.001 per stride, p=<0.001 cumulative) and knee negative work being greater for rearfoot strike runners (p=0.014 per stride, p=0.008 cumulative). Both loading rate and cumulative vertical ground reaction force impulse decreased significantly over time (p=0.035, p=<0.001 respectively). In summary, we found a few differences in per stride and cumulative metrics between foot strike groups, namely ankle and knee loading as previously observed. However, as a whole, individual variability in vertical ground reaction force loading patterns was more apparent than any group distinctions. We also found patterns in previous research suggesting that study design components, specifically self-selected speed and habituation, affect variables such as stride rate and peak vertical ground reaction force. The common perception that non-rearfoot strike runners have a higher stride rate was not supported in this study. Lastly, we determined that cumulative calculations can be different if taken at the beginning vs the end of a run. Quantifying injury risk is complicated and cumulative damage models should take into account individual load capacity and training session characteristics (e.g., warm-up time, length, intensity, and rest time).