Characteristics of Locomotive Syndrome in Japanese Patients with Chronic Pain and Results of a Path Analysis Confirming the Relevance of a Vicious Cycle Involving Locomotive Syndrome, Musculoskeletal Pain, and Its Psychological Factors

Abstract

Introduction: The current aging population has a major impact on public health. Locomotive syndrome (LS) is a condition that carries a high risk for developing systemic musculoskeletal disability.

Methods: Participants were patients with chronic pain (n = 415) who were examined at the Japanese multidisciplinary pain centers of the research consortium. They completed the 25-question geriatric locomotive function scale (GLFS-25; LS screening tool), an 11-point numerical rating scale (NRS) of pain intensity and its psychological distresses, health-related quality of life (HRQOL) questionnaire, and a survey of exercise habits. A multifaceted analysis of the relevance of the pain, psychological distresses, and LS were conducted using SPSS and AMOS software.

Results: 337 patients (81.2%) were found to have LS. The final model of a multifaceted analysis demonstrated good fitness for the "vicious cycle" model among the results of LS, pain intensity, impairment of self-efficacy, and depression; these parameters independently impaired HRQOL. Anxiety related to falling (GLFS-25) and exercise habits affected the model.

Conclusions: These findings indicate LS, LS-related pain, and psychological distress create a vicious cycle, resulting in the impairment of HRQOL. Treatment strategies for LS should inclusively focus on musculoskeletal disorders, pain, and pain-related psychological factors.

Keywords: locomotive syndrome; musculoskeletal pain; psychological distress; vicious cycle.

Figure 1.

The final model of the relevance of a vicious cycle involving LS, musculoskeletal pain, and its psychological factors. Values on the single-headed arrows are partial standardized regression weights. Values on the double-headed arrows are correlation coefficients. A higher value indicates a stronger causal relationship. Numbers below the rectangles indicate a squared multiple correlation coefficient by the direct-connected upstream variables. For example, 23% of the self-efficacy is explained by pain and the locomotive syndrome (LS). CMIN is a Chi-square statistics comparing the test model and the independent model to the saturated model. CMIN/DF, the relative Chi-square, is an index of how much the fit of data to model has been reduced by dropping one or more paths. Additionally, the goodness of fit of the models was evaluated using the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA).