Low back pain precedes the development of new knee pain in the elderly population; a novel predictive score from a longitudinal cohort study

• Published in: Arthritis research & therapy Vol. 21; no. 1; pp. 98 - 9
• Main Authors: Ito, Hiromu, Tominari, Shinjiro, Tabara, Yasuharu, Nakayama, Takeo, Furu, Moritoshi, Kawata, Tomotoshi, Azukizawa, Masayuki, Setoh, Kazuya, Kawaguchi, Takahisa, Matsuda, Fumihiko, Matsuda, Shuichi
• Format: Journal Article
• Language: English
• Published: London BioMed Central 15.04.2019; BioMed Central Ltd; BMC
• Subjects: Age; Aged; Arthralgia - diagnosis; Arthralgia - etiology; Arthritis; Back pain; Body mass index; Cardiovascular disease; Cohort analysis; Cohort Studies; Complications and side effects; Demographic aspects; Development and progression; Disability; Disease prevention; Elderly; Female; Follow-Up Studies; Humans; Knee; Knee Joint - pathology; Knee pain; Longitudinal Studies; Low back pain; Low Back Pain - complications; Low Back Pain - diagnosis; Male; Medical examination; Medicine; Medicine & Public Health; Mental health; Meta-analysis; Middle Aged; Multivariate Analysis; Older people; Orthopedics; Pain Measurement - methods; Pain Measurement - standards; Population; Population Surveillance - methods; Predictive score; Predictive Value of Tests; Prospective Studies; Research Article; Rheumatology; Risk factor; Risk factors; Smoking; Systematic review; X-rays; Japan; Knee pain; Low back pain; Risk factor; Mental health; Predictive score
• ISSN: 1478-6362; 1478-6354; 1478-6362
• DOI: 10.1186/s13075-019-1884-0

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.