Analysis of Cardiometabolic Multimorbidity Patterns and Influencing Factors Based on Association Rules

Abstract OBJECTIVE To identify the patterns of cardiometabolic multimorbidity (CMM) and explore its influencing factors. METHOD A total of 1,467 subjects were collected from June 2019 to November 2021 at the Cardiovascular Department of The First Affiliated Hospital of Fujian Medical University, and Physical Examination Department of The Affiliated Union Hospital of Fujian Medical University. Using the method of frequency-matched case-control study, with sex and age as matching factors, 550 cases who had two or more cardiovascular metabolic diseases were included in the CMM group and 550 cases who had one or no cardiovascular metabolic diseases were included in the non-CMM group. Questionnaire survey was conducted to collect clinical data. Association rules were applied to uncover prevalent patterns of CMM, and multivariate conditional logistic regression analysis was utilized to explore the associated factors. RESULTS The most prevalent CMM patterns included hypertension and diabetes; hypertension and coronary heart disease (CHD); hypertension and hyperlipidemia; hypertension, CHD and diabetes; hypertension, CHD and hyperlipidemia; as well as hypertension, hyperlipidemia and diabetes. Logistic regression analysis revealed that family history of hypertension (Odds Ratio = 1.631, 95% Confidence Interval: 1.250–2.127), family history of diabetes (OR = 1.405, 95% CI: 1.005–1.965), obesity or overweight (OR = 1.589, 95% CI: 1.226–2.059), and alcohol consumption (OR = 1.426, 95% CI: 1.036–1.963) were significant risk factors for CMM. CONCLUSION Hypertension emerges as a pivotal node in CMM patterns. Family history of hypertension, family history of diabetes, obesity or overweight, and alcohol consumption are significant risk factors for CMM.