Multi-morbidity is prevalent among the elderly, yet specific co-occurrence patterns remain unclear. While prior studies have predominantly focused on cardiometabolic disease clusters, this study aimed to explore the proportion of recorded diagnoses of common diseases and identify unconventional multi-morbidity patterns among older adults at primary healthcare settings using electronic health records. We conducted a cross-sectional study using data from regional health information platform in eastern China. Participants aged ≥ 65 years who underwent at least one health examination at primary healthcare setting in 2022 were included. Association rule mining integrated with the hypertext-induced topic search framework was employed to identify disease co-occurrence patterns, weighting participants and diseases based on network connectivity. Twelve common diseases were analyzed, stratified by sex and age. There were 39,172 individuals enrolled in this study. Significant sex and age differences were found in most diseases, with hypertension, hyperlipidemia, cataract and other diseases accounting for 56.48%, 36.02%, 21.33% and 13%-20% of the overall proportion of recorded diagnoses. A total of 58 association rules met the predefined thresholds among the whole population. Beyond cardiometabolic clusters (hypertension or hyperlipidemia co-occurrence), we identified strong associations within inflammatory diseases (osteoporosis and arthritis) and between gastrointestinal conditions and sleep disorders (chronic gastritis, constipation, and sleep disorder). Patterns were consistent across sex and age subgroups. Multi-morbidity patterns in Chinese older adults extend beyond traditional cardiovascular risks to include inflammatory and gut-sleep clusters. These findings suggest the potential value of considering cluster-based care pathways and may inform the integration of sleep screening into gastrointestinal management in primary healthcare settings.
Wu et al. (Thu,) studied this question.