Background: The 25-question Geriatric Locomotive Function Scale (GLFS-25) is widely used in daily clinical practice in evaluating locomotive syndrome (LS). The questionnaire contains 25 questions aiming to describe 6 aspects, including body pain, movement-related difficulty, usual care, social activities, cognitive status, and daily activities. However, its potential underlying latent factor structure of the questionnaire has not been fully examined so far. Methods: Five hundred participants who were 60 years or older and were able to walk independently with or without a cane but had complaints of musculoskeletal disorders were recruited face to face at the out-patient ward of Aichi Medical University Hospital between April 2018 and June 2019. All participants completed the GLFS-25. Confirmatory factor analysis (CFA) models (single-factor model, 6-factor model as designed by the developers of the GLFS-25) were fitted and compared using Mplus 8.3 with a maximum likelihood minimization function. Modification indices, standardized expected parameter change were used, a standard strategy for scale development was followed in the search for an alternative and simpler model that could well fit the collected data. Cronbach's α and its 95% confidence interval (CI) were also calculated. Results: Mean (standard deviation) participants age was 72.6 (7.4) years old; 63.6% of them were women. Under the current criteria, 132 (26.4%) and 262 (52.4%) of the study subjects would be classified as LS stage 1 and stage 2, respectively. Overall, the Cronbach's α (95% CI) for GLFS-25 evaluated using these data was 0.959 (0.953, 0.964). The single- and 6-factor models were rejected due to poor fit. The alternative models with either full 25 questions or a shortened GLFS-16 were found to fit the data better. These alternative models included three latent factors (body pain, movement-related difficulty, and psycho-social complication) and allowed for cross-loading and residual correlations. Discussion: The findings of the CFA models provided evidence that the factor structure of the GLFS-25 might be simpler than the 6-factor model as suggested by the designers. The complex relationships between the latent factors and the observed items may also indicate that individual sub-scale use or simply combining the raw scores for evaluation is likely to be inadequate or unsatisfactory. Thus, future revisions of the scoring algorithm or questions of the GLFS-25 may be required.