title: Prevalence of CKD in northeastern Italy: results of the INCIPE study and comparison with NHANES.
abstract: OBJECTIVE
  Sufficiently powered studies to investigate the CKD prevalence are few and do not cover southern Europe.
  
  
  METHODS
  For the INCIPE study, 6200 Caucasian patients ≥40 years old were randomly selected in northeastern Italy in 2006. Laboratory determinations were centralized. The albumin to creatinine ratio in urine and estimated GFR from calibrated creatinine (SCr) were determined. A comparison with 2001 through 2006 NHANES surveys was performed.
  
  
  RESULTS
  Prevalence of CKD was 13.2% in northeastern (NE) Italy (age and gender standardized to the U.S. 2007 Caucasian population). Prevalence of CKD in U.S. Caucasians is higher (20.3%), the major difference being in CKD 3. Risk factors for CKD are more prevalent in the United States than in Italy. With use of CKD 3a and 3b stages, CKD prevalence decreased in NE Italy (8.5%) and in the United States (12.8%).
  
  
  CONCLUSIONS
  The prevalence of CKD is high in NE Italy, but lower than that in the United States. A large part of the difference in CKD prevalence in NE Italy versus that in the United States is due to the different prevalence of CKD 3. The higher prevalence of a number of renal risk factors in persons from the United States explains in part the different dimensions of the CKD problem in the two populations.
authors.affiliation: Department of Biomedical and Surgical Sciences, Ospedale Civile Maggiore, Azienda Ospedaliera-University of Verona, Verona, Italy. giovanni.gambaro@rm.unicatt.it
authors.forename: Giovanni
authors.initials: G
authors.lastname: Gambaro
authors.forename: Tewoldemedhn
authors.initials: T
authors.lastname: Yabarek
authors.forename: Maria Stella
authors.initials: MS
authors.lastname: Graziani
authors.forename: Alessandro
authors.initials: A
authors.lastname: Gemelli
authors.forename: Cataldo
authors.initials: C
authors.lastname: Abaterusso
authors.forename: Anna Chiara
authors.initials: AC
authors.lastname: Frigo
authors.forename: Nicola
authors.initials: N
authors.lastname: Marchionna
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Citron
authors.forename: Luciana
authors.initials: L
authors.lastname: Bonfante
authors.forename: Francesco
authors.initials: F
authors.lastname: Grigoletto
authors.forename: Salvatore
authors.initials: S
authors.lastname: Tata
authors.forename: Pietro Manuel
authors.initials: PM
authors.lastname: Ferraro
authors.forename: Angelo
authors.initials: A
authors.lastname: Legnaro
authors.forename: Gina
authors.initials: G
authors.lastname: Meneghel
authors.forename: Piero
authors.initials: P
authors.lastname: Conz
authors.forename: Paolo
authors.initials: P
authors.lastname: Rizzotti
authors.forename: Angela
authors.initials: A
authors.lastname: D'Angelo
authors.forename: Antonio
authors.initials: A
authors.lastname: Lupo
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000419:Albuminuria / Q000453:epidemiology; D015415:Biomarkers / Q000652:urine; D002908:Chronic Disease; D003404:Creatinine / Q000652:urine; D005260:Female; D005919:Glomerular Filtration Rate; D054624:Health Status Disparities; D006306:Health Surveys; D006801:Humans; D007558:Italy / Q000453:epidemiology; D007668:Kidney / Q000503:physiopathology; D007674:Kidney Diseases / Q000175:diagnosis / Q000453:epidemiology* / Q000208:ethnology / Q000503:physiopathology; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data
chemical_list: D015415:Biomarkers; D003404:Creatinine
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