Patterns of Pain in Middle-Aged and Older Adults in China: A Latent Class Analysis

Chronic pain is a leading global cause of disability in aging populations, yet pain distribution patterns among middle-aged and older adults in China remain uncharacterized. Using latent class analysis (LCA), this study identified distinct pain location patterns and their associations with cognitive impairment, depressive symptoms, and functional limitations.

A cross-sectional analysis of 9544 participants from the CHARLS 2020 database was conducted. LCA categorized pain patterns, and multivariate logistic regression examined influencing factors and associations with cognitive impairment, depressive symptoms, and activities of daily living (ADL) impairment. Model fit was optimized via AIC/BIC and entropy/posterior probabilities (> 0.8).

Four distinct categories were identified: the broad pain group (n = 935, 9.8%), the shoulder-low back pain group (n = 2426, 25.4%), the lower limb pain group (n = 2568, 26.9%), and the head-neck-stomach pain group (n = 3615, 37.9%). The analysis revealed significant associations between pain location patterns and variables such as sex, income, and the presence of multiple comorbidities, including dyslipidemia, stomach disease, cancer, asthma, chronic lung disease, stroke, kidney disease, arthritis, mood disorders, Parkinson's disease, and memory-related diseases. In addition, the broad pain group showed stronger associations with cognitive impairment, depressive symptoms, and ADL difficulties (including BADL difficulties and IADL difficulties), and the lower limb pain group was associated with a significantly higher likelihood of ADL impairment than the head-neck-stomach pain group.

Pain patterns in Chinese adults ≥ 45 years reflect distinct phenotypes with differential health risks. The broad pain group warrants comprehensive intervention targeting pain, cognition, mood, and function. Lower limb pain requires prioritized mobility preservation strategies. Findings support phenotype-specific pain management to reduce disability burden.