title: Multimorbidity patterns in HIV-infected patients: the role of obesity in chronic disease clustering.
abstract: BACKGROUND
  Increases in multimorbidity and obesity have been noted in HIV-infected populations in the current treatment era. Patterns of multimorbid disease clustering and the impact of obesity on multimorbidity are understudied in this population.
  
  
  METHODS
  We examined obesity and multimorbidity patterns among 1844 HIV-infected patients in the UAB 1917 Clinic. Exploratory factor analysis was used to identify the underlying factor structure responsible for clustering. Patterns among the resulting morbidity factors by body mass index (BMI) category were explored. Multivariable logistic regression models were fit to identify predictors of multimorbidity cluster patterns.
  
  
  RESULTS
  The prevalence of multimorbidity was 65% (1205/1844). Prevalence increased with progressive BMI categories from underweight (64%) to obese (79%). Three multimorbidity clusters were identified: "metabolic," including hypertension, gout, diabetes mellitus, and chronic kidney disease (range, 0.41-0.84; P < 0.001); "Behavioral," including mood disorders, dyslipidemia, chronic obstructive pulmonary disease, chronic ulcer disease, osteoarthritis, obstructive sleep apnea, and cardiac disorders (range, 0.32-0.57; P < 0.001); "Substance Use," including alcohol abuse, substance abuse, tobacco abuse, and hepatitis C (range, 0.53-0.89; P < 0.001). Obesity was associated with increased odds of multimorbidity (obese vs. normal BMI category: OR = 1.52, 95% CI: 1.15 to 2.00).
  
  
  CONCLUSIONS
  Three patterns of disease clustering were identified. Obesity was associated with a higher likelihood of multimorbidity. The management of multimorbidity and obesity will need to be addressed in future clinical practice guidelines to enhance long-term outcomes of HIV-infected patients in the current treatment era.
authors.affiliation: University of Alabama School of Medicine, Birmingham, AL 35294-2050, USA.
authors.forename: David J
authors.initials: DJ
authors.lastname: Kim
authors.forename: Andrew O
authors.initials: AO
authors.lastname: Westfall
authors.forename: Eric
authors.initials: E
authors.lastname: Chamot
authors.forename: Amanda L
authors.initials: AL
authors.lastname: Willig
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Mugavero
authors.forename: Christine
authors.initials: C
authors.lastname: Ritchie
authors.forename: Greer A
authors.initials: GA
authors.lastname: Burkholder
authors.forename: Heidi M
authors.initials: HM
authors.lastname: Crane
authors.forename: James L
authors.initials: JL
authors.lastname: Raper
authors.forename: Michael S
authors.initials: MS
authors.lastname: Saag
authors.forename: James H
authors.initials: JH
authors.lastname: Willig
mesh_terms: D000328:Adult; D000407:Alabama / Q000453:epidemiology; D015992:Body Mass Index; D002908:Chronic Disease; D016000:Cluster Analysis; D015897:Comorbidity; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000473:pathology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000473:pathology; D015995:Prevalence