title: Multimorbidity patterns in primary care: interactions among chronic diseases using factor analysis.
abstract: OBJECTIVE
  The primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases.
  
  
  METHODS
  This observational, retrospective, multicentre study utilised information from the electronic medical records of 19 primary care centres from 2008. To identify multimorbidity patterns, an exploratory factor analysis was carried out based on the tetra-choric correlations between the diagnostic information of 275,682 patients who were over 14 years of age. The analysis was stratified by age group and sex.
  
  
  RESULTS
  Multimorbidity was found in all age groups, and its prevalence ranged from 13% in the 15 to 44 year age group to 67% in those 65 years of age or older. Goodness-of-fit indicators revealed sample values between 0.50 and 0.71. We identified five patterns of multimorbidity: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Some of these patterns were found to evolve with age, and there were differences between men and women.
  
  
  CONCLUSIONS
  Non-random associations between chronic diseases result in clinically consistent multimorbidity patterns affecting a significant proportion of the population. Underlying pathophysiological phenomena were observed upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective.
authors.affiliation: IIS Aragón, Aragón Health Sciences Institute, Miguel Servet University Hospital, University of Zaragoza, Zaragoza, Spain.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Prados-Torres
authors.forename: Beatriz
authors.initials: B
authors.lastname: Poblador-Plou
authors.forename: Amaia
authors.initials: A
authors.lastname: Calderón-Larrañaga
authors.forename: Luis Andrés
authors.initials: LA
authors.lastname: Gimeno-Feliu
authors.forename: Francisca
authors.initials: F
authors.lastname: González-Rubio
authors.forename: Antonio
authors.initials: A
authors.lastname: Poncel-Falcó
authors.forename: Antoni
authors.initials: A
authors.lastname: Sicras-Mainar
authors.forename: José Tomás
authors.initials: JT
authors.lastname: Alcalá-Nalvaiz
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002908:Chronic Disease; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D009017:Morbidity; D011320:Primary Health Care / Q000379:methods* / Q000458:organization & administration*; D012107:Research Design; D012189:Retrospective Studies; D012737:Sex Factors; D013030:Spain