Association between Cardiometabolic Risk Factors and Future Multimorbidity Patterns: A K-means Clustering Analysis
Abstract Body: Introduction: Multimorbidity, the co-occurrence of multiple chronic diseases, is associated with increased mortality and reduced quality of life. While cardiometabolic risk factors (CMRs) are strongly linked with cardiovascular events, their relationship with disease patterns across diverse organ systems remains unexplored. We examined associations between baseline CMRs and longitudinal chronic disease clustering patterns. Hypothesis: Baseline CMRs are associated with distinct multimorbidity patterns involving multiple disease domains. Methods: This study was performed with Tsuruoka Metabolomics Cohort Study, which included 11,002 participants (men 46.5%) at baseline in 2012. Of these, 3,396 participants (men 43.3%) who completed three surveys over six years were analyzed. Eighteen self-reported chronic diseases over six years were categorized into seven groups: inflammatory/tumorous gastrointestinal, ulcerative gastrointestinal, metabolic/renal, respiratory, ophthalmic, psychiatric, and skeletal/immune diseases. K-means clustering was applied to classify participants based on their prevalences of seven groups across the three surveys. Baseline CMRs included hypertension, hyperglycemia, dyslipidemia and overweight as defined by clinical guidelines. Multinomial logistic regression was performed to estimate odds ratios (ORs) for cluster membership versus the healthiest cluster, adjusting for age, sex, alcohol, and smoking. Results: A total of seven clusters were identified: one healthy and six disease-dominant clusters, including two inflammatory/tumorous gastrointestinal clusters (persistent and newly developed), metabolic/renal, ophthalmic with skeletal/immune, ulcerative gastrointestinal, and complex multimorbidity patterns. Baseline dyslipidemia showed elevated ORs in three clusters: persistent inflammatory/tumorous gastrointestinal (OR 1.59), metabolic/renal (OR 2.61), and complex multimorbidity (OR 1.81). The metabolic/renal cluster uniquely demonstrated multiple CMR associations with elevated ORs for hypertension (OR 1.60), dyslipidemia (OR 2.61), and overweight (OR 1.76). Conclusions: Baseline CMRs, particularly dyslipidemia, are associated with distinct multimorbidity patterns across diverse organ systems. These findings demonstrate that the impact of CMRs extends beyond the cardiovascular system, underscoring their relevance to multimorbidity across multiple domains. Integrated preventive strategies targeting CMRs may reduce multimorbidity burden.
Omoto, Yuki
( Keio University School of Medicine
, Tokyo
, Japan
)
Miyagawa, Naoko
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Miyake, Atsuko
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Takebayashi, Toru
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Toki, Ryota
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Iba, Chisato
( Keio University School of Medicine
, Tokyo
, Japan
)
Iida, Miho
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Edagawa, Shun
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Shibuki, Takuma
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Harada, Sei
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Hirata, Aya
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)
Matsumoto, Minako
( Department of Preventive Medicine and Public Health, Keio University School of Medicine
, Tokyo
, Japan
)