Multimorbidity Patterns in Older Adults: An Approach to the Complex Interrelationships Among Chronic Diseases.

BACKGROUND AND AIMS: There is a growing need for evidence based answers to multimorbidity, especially in primary care settings. The aim was estimate the prevalence and patterns of multimorbidity in a Mexican population of public health institution users ≥60 years old.

METHODS: Observational and multicenter study was carried out in four family medicine units in Mexico City; included older men and women who attended at least one consultation with their family doctor during 2013. The most common diseases were grouped into 11 domains. The observed and expected rates, as well as the prevalence ratios, were calculated for the pairs of the more common domains. Logistic regression models were developed to estimate the magnitude of the association. Cluster and principal components analyses were performed to identify multimorbidity patterns.

RESULTS: Half of all of the patients who were ≥60 years old and treated by a family doctor had multimorbidity. The most common disease domains were hypertensive and endocrine diseases. The highest prevalence of multimorbidity concerned the renal domain. The domain pairs with the strongest associations were endocrine + renal and hypertension + cardiac. The cluster and principal components analyses revealed five consistent patterns of multimorbidity.

CONCLUSIONS: The domains grouped into five patterns could establish the framework for developing treatment guides, deepen the knowledge of multimorbidity, develop strategies to prevent it, decrease its burden, and align health services to the care needs that doctors face in daily practice.