title: Global differences in dialysis modality mix: the role of patient characteristics, macroeconomics and renal service indicators.
abstract: BACKGROUND
  An increase in the dialysis programme expenditure is expected in most countries given the continued rise in the number of people with end-stage renal disease (ESRD) globally. Since chronic peritoneal dialysis (PD) therapy is relatively less expensive compared with haemodialysis (HD) and because there is no survival difference between PD and HD, identifying factors associated with PD use is important.
  
  
  METHODS
  Incidence counts for the years 2003-05 were available from 36 countries worldwide. We studied associations of population characteristics, macroeconomic factors and renal service indicators with the percentage of patients on PD at Day 91 after starting dialysis. With linear regression models, we obtained relative risks (RRs) with 95% confidence intervals (CIs).
  
  
  RESULTS
  The median percentage of incident patients on PD was 12% (interquartile range: 7-26%). Determinants independently associated with lower percentages of patients on PD were as follows: patients with diabetic kidney disease (per 5% increase) (RR 0.93; 95% CI 0.89-0.97), health expenditure as % gross domestic product (per 1% increase) (RR 0.93; 95% CI 0.87-0.98), private-for-profit share of HD facilities (per 1% increase) (RR 0.996; 95% CI 0.99-1.00; P = 0.04), costs of PD consumables relative to staffing (per 0.1 increase) (RR 0.97; 95% CI 0.95-0.99).
  
  
  CONCLUSIONS
  The factors associated with a lower percentage of patients on PD include higher diabetes prevalence, higher healthcare expenditures, larger share of private-for-profit centres and higher costs of PD consumables relative to staffing. Whether dialysis modality mix can be influenced by changing healthcare organization and funding requires additional studies.
authors.affiliation: ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. m.w.vandeluijtgaarden@amc.nl
authors.forename: Moniek W M
authors.initials: MW
authors.lastname: van de Luijtgaarden
authors.forename: Kitty J
authors.initials: KJ
authors.lastname: Jager
authors.forename: Vianda S
authors.initials: VS
authors.lastname: Stel
authors.forename: Anneke
authors.initials: A
authors.lastname: Kramer
authors.forename: Ana
authors.initials: A
authors.lastname: Cusumano
authors.forename: Robert F
authors.initials: RF
authors.lastname: Elliott
authors.forename: Claudia
authors.initials: C
authors.lastname: Geue
authors.forename: Alison M
authors.initials: AM
authors.lastname: MacLeod
authors.forename: Benedicte
authors.initials: B
authors.lastname: Stengel
authors.forename: Adrian
authors.initials: A
authors.lastname: Covic
authors.forename: Fergus J
authors.initials: FJ
authors.lastname: Caskey
mesh_terms: D000368:Aged; D003928:Diabetic Nephropathies / Q000191:economics*; D005500:Follow-Up Studies; D017048:Health Care Costs; D006801:Humans; D007676:Kidney Failure, Chronic / Q000191:economics* / Q000401:mortality / Q000628:therapy; D011379:Prognosis; D006435:Renal Dialysis / Q000191:economics*; D017582:Renal Replacement Therapy / Q000191:economics*; D012307:Risk Factors; D015996:Survival Rate
keywords: dialysis; epidemiology; health policy; macroeconomics