Department of Orthopaedic Surgery, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo, Kyoto, 606-8507, Japan.
Department of Health Informatics, Kyoto University Graduate School of Medicine, Konoe-cho, Yoshida, Kyoto, 606-8501, Japan.
Arthritis Res Ther. 2019 Apr 15;21(1):98. doi: 10.1186/s13075-019-1884-0.
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.
本研究旨在通过基于人群的纵向队列数据,探讨膝关节疼痛与包括下腰痛在内的各种危险因素之间的关系,并开发一种评分系统来预测老年人群中新发膝关节疼痛。
我们以系统的方式收集了社区≥50 岁居民的膝关节疼痛和人口统计学数据的问卷,分别在基线和 5 年后进行了两次调查。多变量逻辑回归分析用于调查膝关节疼痛与危险因素之间的关系,并建立一个预测模型,该模型可以计算出在 5 年内发生膝关节疼痛的风险。该模型以评分图表的形式呈现。
在完成第一次问卷调查的 9764 名队列居民中,共有 5932 名≥50 岁的居民被纳入第二次调查。排除后,对两次平均相隔 5.4 年的时间点进行了分析,共有 4638 名参与者纳入了配对数据分析。多变量分析显示,年龄较大、女性、较高的 BMI、体重增加、心理健康评分较低以及腰痛/残疾评分较高是膝关节疼痛的独立危险因素。预测评分由六个因素组成:年龄、性别、BMI、体重增加、心理健康和下腰痛/残疾。根据总分,发生膝关节疼痛的风险范围为 11.0%至 63.2%。
本研究表明膝关节疼痛与下腰痛/残疾以及其他危险因素之间存在显著关联。我们开发的评分系统可用于识别没有任何影像学检查的人群,这些人群患有膝关节疼痛的风险较高。