ArticleAnnals of medicine2026
Network analysis of multisite chronic pain in middle-aged and older adults in Western China.
Article in Annals of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
backgroundMultisite chronic pain (MCP) is a growing public health concern among aging populations worldwide, disproportionately affecting underdeveloped regions of low- and middle-income countries where pain awareness and management capacity remain limited. This study aimed to investigate MCP prevalence and co-occurrence patterns, identify key sites, and explore subgroup heterogeneity among middle-aged and older adults in Yunnan Province, western China. MATERIALS AND
methodsA cross-sectional study was conducted using multi-stage stratified random cluster sampling to recruit 5,346 participants aged 45 years and older, and demographic characteristics and pain status across 30 body sites were collected using structured questionnaires. The Ising model was applied to eatimate pairwise associations between pain sites, and Network Comparison Test (NCT) was performed to evaluate pain pattern differences.
resultsThe prevalence of MCP was 29.83%. Co-occurrence patterns were dominated by bilateral symmetry (e.g. left-right knee, weight = 4.93), followed by adjacent-region pain (e.g. right upper arm-right elbow, weight = 4.26). Conversely, contralateral adjacent sites showed negative association (e.g.,left calf-right knee, weight = -3.24). The left calf, right thigh, right knee, right calf, and left knee were identified as core pain sites, whereas the left hip, left thigh, neck, left buttock, and chest served as bridge nodes. Notably, no statistically significant differences in MCP networks were detected across gender, age, and ethnic subgroups.
conclusionsMCP remains disproportionately prevalent and exhibits structured pain patterns. The identified network characteristics provide new insights into pain co-occurrence and may inform future research and pain management strategies in resource-limited settings.
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