Low back pain precedes the development of new knee pain in the elderly population; a novel predictive score from a longitudinal cohort study.
Knee pain
Low back pain
Mental health
Predictive score
Risk factor
Journal
Arthritis research & therapy
ISSN: 1478-6362
Titre abrégé: Arthritis Res Ther
Pays: England
ID NLM: 101154438
Informations de publication
Date de publication:
15 04 2019
15 04 2019
Historique:
received:
02
10
2018
accepted:
01
04
2019
entrez:
17
4
2019
pubmed:
17
4
2019
medline:
14
5
2020
Statut:
epublish
Résumé
To investigate the association between knee pain and risk factors including low back pain and to develop a score to predict new knee pain in an older population, using population-based longitudinal cohort data. We collected a questionnaire on self-reported knee pain and demographic data in a systematic manner from community residents aged ≥ 50 years twice, at baseline, and after 5 years. Multivariate logistic regression analyses were performed to investigate the association between knee pain and risk factors and to build a predictive model that would enable calculation of the risk of the development of knee pain within 5 years. The model is presented in the form of score charts. A total of 5932 residents aged ≥ 50 years from the cohort of 9764 that completed the first questionnaire were enrolled in the second survey. After exclusions, paired data for the two time points an average of 5.4 years apart were analyzed for 4638 participants. Multivariate analyses showed older age, female sex, higher BMI, weight increase, lower mental health score, and higher back pain/disability score were independent risk factors for knee pain. The predictive score comprised six factors: age, sex, BMI, weight increase, mental health, and low back pain/disability. The risk of developing knee pain ranged from 11.0 to 63.2% depending on the total score. This study demonstrated a significant association between knee and low back pain/disability along with other risk factors. The score we developed can be used to identify a population without any imaging modality who are at high risk of developing knee pain.
Sections du résumé
BACKGROUND
To investigate the association between knee pain and risk factors including low back pain and to develop a score to predict new knee pain in an older population, using population-based longitudinal cohort data.
METHODS
We collected a questionnaire on self-reported knee pain and demographic data in a systematic manner from community residents aged ≥ 50 years twice, at baseline, and after 5 years. Multivariate logistic regression analyses were performed to investigate the association between knee pain and risk factors and to build a predictive model that would enable calculation of the risk of the development of knee pain within 5 years. The model is presented in the form of score charts.
RESULTS
A total of 5932 residents aged ≥ 50 years from the cohort of 9764 that completed the first questionnaire were enrolled in the second survey. After exclusions, paired data for the two time points an average of 5.4 years apart were analyzed for 4638 participants. Multivariate analyses showed older age, female sex, higher BMI, weight increase, lower mental health score, and higher back pain/disability score were independent risk factors for knee pain. The predictive score comprised six factors: age, sex, BMI, weight increase, mental health, and low back pain/disability. The risk of developing knee pain ranged from 11.0 to 63.2% depending on the total score.
CONCLUSION
This study demonstrated a significant association between knee and low back pain/disability along with other risk factors. The score we developed can be used to identify a population without any imaging modality who are at high risk of developing knee pain.
Identifiants
pubmed: 30987680
doi: 10.1186/s13075-019-1884-0
pii: 10.1186/s13075-019-1884-0
pmc: PMC6466785
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
98Subventions
Organisme : Japan Agency for Medical Research and Development
ID : H26-Choju-Ippan-001, 15dk0107007h0003, 16dk0110007h0003
Pays : International
Investigateurs
Yasuharu Tabara
(Y)
Takahisa Kawaguchi
(T)
Kazuya Setoh
(K)
Yoshimitsu Takahashi
(Y)
Shinji Kosugi
(S)
Takeo Nakayama
(T)
Fumihiko Matsuda
(F)
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