Patellofemoral kinematics in patellofemoral pain syndrome: The influence of demographic factors.
BMI
Covariates
Kinematics
Knee joint
Sex
Journal
Journal of biomechanics
ISSN: 1873-2380
Titre abrégé: J Biomech
Pays: United States
ID NLM: 0157375
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
received:
22
06
2021
revised:
20
09
2021
accepted:
12
10
2021
pubmed:
9
11
2021
medline:
19
2
2022
entrez:
8
11
2021
Statut:
ppublish
Résumé
Due to the multifactorial nature of patellofemoral pain, it is often difficult to identify an individual patient's exact cause of pain. Understanding how demographic variability influences these various factors will support improved consensus in regards to the etiology of PF pain. Thus, in this retrospective study, we tested the hypothesis that sex, height, weight, body mass index (BMI), and age influence the determination of between-groups differences in PF kinematics. We included 41 skeletally mature patients with patellofemoral pain and 79 healthy controls. Three-dimensional patellofemoral kinematics were quantified from dynamic magnet resonance images. We ran multiple regression analyses to determine the influence of demographic covariates (age, sex, height, weight, and BMI) on patellofemoral kinematics. Patellar shift was significantly influenced by weight (p = 0.009) and BMI (p = 0.009). Patellar flexion was influenced by height (p = 0.020) and weight (p = 0.040). Patellar tilt and superior displacement were not influence by demographic variables. Age and sex did not influence kinematics. This study supports the hypothesis that demographic parameters influence PF kinematics. The fact that weight, a modifiable measure, influences both patellar shift and flexion has strong implications for future research and clinical interventions. Clinically, weight loss may have a dual benefit of reducing joint stress and maltracking in patients who are overweight and experiencing patellofemoral pain. The influence of key demographics on patellofemoral kinematics, reinforces the clear need to control for population characteristics in future studies. As such, going forward, improved demographic matching between control and patient cohorts or more advanced statistical techniques that compensate for confounding variables are necessary.
Identifiants
pubmed: 34749164
pii: S0021-9290(21)00579-0
doi: 10.1016/j.jbiomech.2021.110819
pmc: PMC10311921
mid: NIHMS1908517
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
110819Subventions
Organisme : Intramural NIH HHS
ID : Z01 CL060062
Pays : United States
Organisme : Intramural NIH HHS
ID : Z99 CL999999
Pays : United States
Informations de copyright
Copyright © 2021. Published by Elsevier Ltd.
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