title: [Multimorbidity and comorbidity in the Dutch population--data from general practices].
abstract: OBJECTIVE
  To present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population.
  
  
  METHODS
  Data analysis.
  
  
  METHODS
  Data from the Netherlands Information Network of General Practice (LINH), a large representative network of general practices over a period of 7 years (2002-2008) were analysed. Multimorbidity was defined as a patient having been diagnosed with two or more of 29 chronic diseases in the general practitioner's electronic medical records system. The prevalence of chronic diseases and multimorbidity was calculated for the total population and subsequently by sex and age groups. For the 10 most prevalent diseases in the elderly, clustering and comorbidity of chronic diseases in patients 55 years and older were analysed.
  
  
  RESULTS
  Almost 13% of the total Dutch population and 37% of patients 55 years and older had 2 or more chronic diseases. More than 70% of the patients aged 55 years and older who had 1 of the 10 specific chronic diseases also had an additional chronic disease. Most disease pairs occurred more frequently than expected based on independency (clustering), particularly the combinations depression and anxiety disorder, coronary heart disease and heart failure, and COPD and heart failure. The five most common combinations of conditions associated with a certain disease concerned only a limited portion (30%) of all disease comorbidity. This means that 70% of patients with a chronic disease had 1 or more additional diseases not included in the 5 most frequently occurring diseases.
  
  
  CONCLUSIONS
  Multimorbidity was identified in over two-thirds of the elderly with frequently occurring chronic diseases. Comorbidity encompassed many different combinations of chronic diseases. In light of an ageing population, multimorbidity should increasingly be taken into account when delivering healthcare, in medical research and in defining healthcare policies.
authors.affiliation: Rijksinstituut voor Volksgezondheid en Milieu, Centrum voor Preventie en Zorg Onderzoek, Bilthoven, the Netherlands. sandra.van.oostrom@rivm.nl
authors.forename: Sandra H
authors.initials: SH
authors.lastname: van Oostrom
authors.forename: H Susan J
authors.initials: HS
authors.lastname: Picavet
authors.forename: Boukje M
authors.initials: BM
authors.lastname: van Gelder
authors.forename: Lidwien C
authors.initials: LC
authors.lastname: Lemmens
authors.forename: Nancy
authors.initials: N
authors.lastname: Hoeymans
authors.forename: Robert A
authors.initials: RA
authors.lastname: Verheij
authors.forename: François G
authors.initials: FG
authors.lastname: Schellevis
authors.forename: Caroline A
authors.initials: CA
authors.lastname: Baan
mesh_terms: D000367:Age Factors; D000368:Aged; D000375:Aging; D002908:Chronic Disease / Q000453:epidemiology* / Q000401:mortality; D016000:Cluster Analysis; D015897:Comorbidity; D005260:Female; D058006:General Practice / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends; D009426:Netherlands / Q000453:epidemiology; D015995:Prevalence; D012737:Sex Factors