Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach
Abstract Background Patellofemoral pain (PFP) is among the most common injuries in runners. While multiple risk factors for patellofemoral pain have been investigated, the interactions of variables contributing to this condition have not been explored. This study aimed to classify runners with patel...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-01-01
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| Series: | Sports Medicine - Open |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40798-023-00671-8 |
| _version_ | 1827382207018172416 |
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| author | José Roberto de Souza Júnior Logan Walter Gaudette Caleb D. Johnson João Paulo Chieregato Matheus Thiago Vilela Lemos Irene S. Davis Adam S. Tenforde |
| author_facet | José Roberto de Souza Júnior Logan Walter Gaudette Caleb D. Johnson João Paulo Chieregato Matheus Thiago Vilela Lemos Irene S. Davis Adam S. Tenforde |
| author_sort | José Roberto de Souza Júnior |
| collection | DOAJ |
| description | Abstract Background Patellofemoral pain (PFP) is among the most common injuries in runners. While multiple risk factors for patellofemoral pain have been investigated, the interactions of variables contributing to this condition have not been explored. This study aimed to classify runners with patellofemoral pain using a combination of factors including biomechanical, anthropometric, and demographic factors through a Classification and Regression Tree analysis. Results Thirty-eight runners with PFP and 38 healthy controls (CON) were selected with mean (standard deviation) age 33 (16) years old and body mass index 22.3 (2.6) kg/m2. Each ran at self-selected speed, but no between-group difference was identified (PFP = 2.54 (0.2) m/s x CON = 2.55 (0.1) m/s, P = .660). Runners with patellofemoral pain had different patterns of interactions involving braking ground reaction force impulse, contact time, vertical average loading rate, and age. The classification and regression tree model classified 84.2% of runners with patellofemoral pain, and 78.9% of healthy controls. The prevalence ratios ranged from 0.06 (95% confidence interval: 0.02–0.23) to 9.86 (95% confidence interval: 1.16–83.34). The strongest model identified runners with patellofemoral pain as having higher braking ground reaction force impulse, lower contact times, higher vertical average loading rate, and older age. The receiver operating characteristic curve demonstrated high accuracy at 0.83 (95% confidence interval: 0.74–0.93; standard error: 0.04; P < .001). Conclusions The classification and regression tree model identified an influence of multiple factors associated with patellofemoral pain in runners. Future studies may clarify whether addressing modifiable biomechanical factors may address this form of injury. |
| first_indexed | 2024-03-08T14:16:13Z |
| format | Article |
| id | doaj.art-83f130fa0c3746fdbbed1256928bf06e |
| institution | Directory Open Access Journal |
| issn | 2198-9761 |
| language | English |
| last_indexed | 2024-03-08T14:16:13Z |
| publishDate | 2024-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Sports Medicine - Open |
| spelling | doaj.art-83f130fa0c3746fdbbed1256928bf06e2024-01-14T12:24:35ZengSpringerOpenSports Medicine - Open2198-97612024-01-011011910.1186/s40798-023-00671-8Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree ApproachJosé Roberto de Souza Júnior0Logan Walter Gaudette1Caleb D. Johnson2João Paulo Chieregato Matheus3Thiago Vilela Lemos4Irene S. Davis5Adam S. Tenforde6Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital/Harvard Medical SchoolDepartment of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital/Harvard Medical SchoolUnited States Army Research Institute for Environmental MedicineGraduate Program of Sciences and Technologies in Health, University of BrasíliaDepartment of Physical Therapy, State University of GoiásSchool of Physical Therapy and Rehabilitation Sciences, Morsani College of Medicine, University of South FloridaDepartment of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital/Harvard Medical SchoolAbstract Background Patellofemoral pain (PFP) is among the most common injuries in runners. While multiple risk factors for patellofemoral pain have been investigated, the interactions of variables contributing to this condition have not been explored. This study aimed to classify runners with patellofemoral pain using a combination of factors including biomechanical, anthropometric, and demographic factors through a Classification and Regression Tree analysis. Results Thirty-eight runners with PFP and 38 healthy controls (CON) were selected with mean (standard deviation) age 33 (16) years old and body mass index 22.3 (2.6) kg/m2. Each ran at self-selected speed, but no between-group difference was identified (PFP = 2.54 (0.2) m/s x CON = 2.55 (0.1) m/s, P = .660). Runners with patellofemoral pain had different patterns of interactions involving braking ground reaction force impulse, contact time, vertical average loading rate, and age. The classification and regression tree model classified 84.2% of runners with patellofemoral pain, and 78.9% of healthy controls. The prevalence ratios ranged from 0.06 (95% confidence interval: 0.02–0.23) to 9.86 (95% confidence interval: 1.16–83.34). The strongest model identified runners with patellofemoral pain as having higher braking ground reaction force impulse, lower contact times, higher vertical average loading rate, and older age. The receiver operating characteristic curve demonstrated high accuracy at 0.83 (95% confidence interval: 0.74–0.93; standard error: 0.04; P < .001). Conclusions The classification and regression tree model identified an influence of multiple factors associated with patellofemoral pain in runners. Future studies may clarify whether addressing modifiable biomechanical factors may address this form of injury.https://doi.org/10.1186/s40798-023-00671-8EtiologyBiomechanicsRunning injuriesStatistical approach |
| spellingShingle | José Roberto de Souza Júnior Logan Walter Gaudette Caleb D. Johnson João Paulo Chieregato Matheus Thiago Vilela Lemos Irene S. Davis Adam S. Tenforde Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach Sports Medicine - Open Etiology Biomechanics Running injuries Statistical approach |
| title | Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach |
| title_full | Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach |
| title_fullStr | Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach |
| title_full_unstemmed | Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach |
| title_short | Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach |
| title_sort | interaction of biomechanical anthropometric and demographic factors associated with patellofemoral pain in rearfoot strike runners a classification and regression tree approach |
| topic | Etiology Biomechanics Running injuries Statistical approach |
| url | https://doi.org/10.1186/s40798-023-00671-8 |
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