title: Body mass index, dialysis modality, and survival: analysis of the United States Renal Data System Dialysis Morbidity and Mortality Wave II Study.
abstract: BACKGROUND
  The impact of obesity on survival in end-stage renal disease (ESRD) patients as related to dialysis modality (i.e., a direct comparison of hemodialysis with peritoneal dialysis) has not been assessed adjusting for differences in medication use, follow-up > or =2 years, or accounting for changes in dialysis modality.
  
  
  METHODS
  We performed a retrospective cohort study of the United States Renal Data System (USRDS) Dialysis Morbidity and Mortality Wave II Study (DMMS) patients who started dialysis in 1996, and were followed until October 31 2001. Cox regression analysis was used to model adjusted hazard ratios (AHR) for mortality for categories of body mass index (BMI), both as quartiles and as > or =30 kg/m2 vs. lower. Because such a large proportion of peritoneal dialysis patients changed to hemodialysis during the study period (45.5%), a sensitivity analysis was performed calculating survival time both censoring and not censoring on the date of change from peritoneal dialysis to hemodialysis.
  
  
  RESULTS
  There were 1675 hemodialysis and 1662 peritoneal dialysis patients. Among hemodialysis patients, 5-year survival for patients with BMI > or =30 kg/m2 was 39.8% vs. 32.3% for lower BMI (P < 0.01 by log-rank test). Among peritoneal dialysis patients, 5-year survival for patients with BMI >/=30 kg/m2 was 38.7% vs. 40.4% for lower BMI (P > 0.05 by log-rank test). In adjusted analysis, BMI > or = 30 kg/m2 was associated with improved survival in hemodialysis patients (AHR 0.89; 95% CI 0.81, 0.99; P= 0.042) but not peritoneal dialysis patients (AHR = 0.99; 95% CI, 0.86, 1.15; P= 0.89). Results were not different on censoring of change from peritoneal dialysis to hemodialysis.
  
  
  CONCLUSIONS
  We conclude that any survival advantage associated with obesity among chronic dialysis patients is significantly less likely for peritoneal dialysis patients, compared to hemodialysis patients.
authors.affiliation: Nephrology Service, Walter Reed Army Medical Center, Washington, DC 20037, USA. kevin.abbott@na.amedd.army.mil
authors.forename: Kevin C
authors.initials: KC
authors.lastname: Abbott
authors.forename: Christopher W
authors.initials: CW
authors.lastname: Glanton
authors.forename: Fernando C
authors.initials: FC
authors.lastname: Trespalacios
authors.forename: David K
authors.initials: DK
authors.lastname: Oliver
authors.forename: Maria I
authors.initials: MI
authors.lastname: Ortiz
authors.forename: Lawrence Y
authors.initials: LY
authors.lastname: Agodoa
authors.forename: David F
authors.initials: DF
authors.lastname: Cruess
authors.forename: Paul L
authors.initials: PL
authors.lastname: Kimmel
mesh_terms: D000328:Adult; D000368:Aged; D015992:Body Mass Index; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000401:mortality; D010530:Peritoneal Dialysis / Q000401:mortality*; D016016:Proportional Hazards Models; D006435:Renal Dialysis / Q000401:mortality*; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology