This study used a network analysis to combine results from factor analysis and observed/expected ratios of disease combinations in order to create a pattern-specific disease network.
We investigated the degree of comparability of the prevalence of chronic diseases and disease combinations in the elderly in two databases comparable with regard to diseases included, sex and age of the patients (65 85 years), and cutoff score for case definition.
For that reason, it seams important to discover the underlying structure in the distribution of disease combinations, i.e. which pathways may lead through the labyrinth of multimorbidity.
In accordance with the systemic nature of the disease, combinations are common and in reality, most organs are involved also when not giving symptoms.
Finally, the presence of co-morbidity complicates the question how a specific condition is related to outcome variables such as affect or QOL, and our co-morbidity analyses were performed on a simple count of illnesses rather than on specific disease combinations.
Multimorbidity is the presence of multiple chronic conditions that can include any type of disease combinations.
Most of the disease combinations were identified as the most prevalent conditions in table 1.
Over time, additional chemicals and health end point or disease combinations will be developed.
Several researchers investigated the joint effects that specific disease combinations have on quality of life.
For disease combinations costs in primary care were studied in another English study [ 33].
