Prevalence and patterns of multimorbidity in chronic diseases in Guangzhou, China: a data mining study in the residents’ health records system among 31 708 community-dwelling elderly people

Abstract

ObjectivesExamination of the prevalence, influence factors and patterns of multimorbidity among the elderly people in Guangzhou, China.DesignCross-sectional study.Participants31 708 community-dwelling elderly people aged 65 and over.Primary and secondary outcome measuresPrevalence, influence factors and patterns of multimorbidity in seven chronic conditions among the participants. A multistage, stratified random sampling was adopted for selection of health records in the residents’ health records system of Guangzhou. Data mining by association rule mining analysis was used to explore the correlations and multimorbidity patterns between seven chronic diseases.ResultsThe prevalence of morbidity was 55.0% (95% CI 40.1% to 60.1%) and the multimorbidity was 15.2% (95% CI 12.4% to 18.4%) among the participants. Elderly, women, higher education level, being single, living in urban areas and having medical insurance were more likely to have chronic diseases and multimorbidity. Data mining by association rule mining analysis reveals patterns of multimorbidity among the participants, including coexistence of hypertension and diabetes (support: 12.5%, confidence: 17.6%), hypertension and coronary heart disease (support: 4.4%, confidence: 5.7%), diabetes and coronary heart disease (support: 1.6%, confidence: 5.7%), diabetes, coronary heart disease and hypertension (support: 1.4%, confidence: 4.4%).ConclusionsA high prevalence of morbidity (especially on hypertension and diabetes) and a relatively low multimorbidity of chronic diseases exist in elderly people. Data mining of residents’ health records will help for strengthening the management of residents’ health records in community health service centres of Guangzhou, China.