Inproceedings: an article in a conference proceedings.
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Prevalence of measured and self-reported multimorbidity in the Swiss-CoLaus population-based study
Title of the conference
81. Jahrestagung der Schweizerischen Gesellschaft für Allgemeine Innere Medizin
Basel, Schweiz, 29-31 Mai, 2013
Introduction: The prevalence of multimorbidity (MM) in hospitalized patients is increasing and recognized as an important factor that may modify the strategies of treatment and increase the length of stay. Little is currently known about the prevalence of MM in the general population and if measured or self-reported diseases are different in the outpatient setting compared to hospitalized patients. The objective of the study was, therefore, to assess the prevalence of self-reported and measured MM in representative sample of the general population aged 35-75 years in Switzerland. Method: Data were obtained from the population based CoLaus Study: 3712 participants (1965 women, 50±9 years). MM was defined as presenting >=2 morbidities according to a list of 27 items (either measured or self-reported data, according to Barret et al.) or a Functional Comorbidity Index (FCI) (18 items, measured only). Results: The prevalence of MM according to these three definitions is summarized in the table 1. For all definitions prevalence of MM was higher in women, elderly participants, those with lower education levels, Swiss nationals, former smokers and obese participants. The prevalence of MM when measured data were used was significantly higher than according to self-reported (p<0.001). Multivariate analysis confirmed most of these associations, except that no difference was found for educational level and for overweight participants. Conclusion: The prevalence of MM is high in the general population, ranging from 13.8 and 50.3% even in the younger age group. The prevalence is higher in women, and increases with age and weight. The prevalence varies considerably according to the definition and is lower when using self-reported compared to measured data.
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