Investigation of multimorbidity and prevalent disease combinations in older Irish adults using network analysis and association rules

Abstract

Multimorbidity (the presence of multiple medical conditions) is well known to increase with age. People with multimorbidities often have higher physical and functional decline as well as increased mortality. Despite growing evidence that integrated and collaborative care improves many undesirable outcomes of multimorbidity, the majority of health systems are based around treating individual diseases. A pattern analysis of comorbidities using network graphs and a novel use of association rules was conducted to investigate disease associations on 6101 Irish adults aged 50+. The complex network of morbidities and differences in the prevalence and interactions of these morbidities by sex was also assessed. Gender specific differences in disease prevalence was found for 22/31 medical conditions included in this study. Females had a more complex network of disease associations than males with strong associations found between arthritis, osteoporosis and thyroid issues among others. To assess the strength of these associations we provide probabilities of being diagnosed with a comorbid condition given the presence of an index morbidity for 639 pairwise combinations. This information can be used to guide clinicians in deciding which comorbidities should be incorporated into comprehensive assessments in addition to anticipating likely future morbidities and thus developing prevention strategies.