title: Age-period-cohort analysis of 1990-2003 incidence time trends of childhood diabetes in Italy: the RIDI study.
abstract: OBJECTIVE
  To investigate age-period-cohort effects on the temporal trend of type 1 diabetes in children age 0-14 years in Italian registries.
  
  
  METHODS
  This report is based on 5,180 incident cases in the period 1990-2003 from the Registry for Type 1 Diabetes Mellitus in Italy (RIDI). Multilevel (random intercept) Poisson regression models were used to model the effects of sex, age, calendar time, and birth cohorts on temporal trends, taking into account the registry-level variance component.
  
  
  RESULTS
  The incidence rate was 12.26 per 100,000 person-years and significantly higher in boys (13.13 [95% CI 12.66-13.62]) than in girls (11.35 [10.90-11.82]). Large geographical variations in incidence within Italy were evident; incidence was highest in Sardinia, intermediate in Central-Southern Italy, and high in Northern Italy, particularly in the Trento Province, where the incidence rate was 18.67 per 100,000 person-years. An increasing temporal trend was evident (2.94% per year [95% CI 2.22-3.67]). With respect to the calendar period 1990-1992, the incidence rates increased linearly by 15, 27, 35, and 40% in the following time periods (P for trend < 0.001). With respect to the 1987-1993 birth cohort, the incidence rate ratio increased approximately linearly from 0.63 (95% CI 0.54-0.73) in the 1975-1981 cohort to 1.38 (1.06-1.80) in the 1999-2003 cohort. The best model, however, included sex, age, and a linear time trend (drift).
  
  
  CONCLUSIONS
  Large geographical variations and an increasing temporal trend in diabetes incidence are evident among type 1 diabetic children in Italy. Age-period-cohort analysis shows that the variation over time has a linear component that cannot be ascribed to either the calendar period or the birth cohort.
authors.affiliation: Department of Internal Medicine, University of Turin, Turin, Italy. graziella.bruno@unito.it
authors.forename: Graziella
authors.initials: G
authors.lastname: Bruno
authors.forename: Milena
authors.initials: M
authors.lastname: Maule
authors.forename: Franco
authors.initials: F
authors.lastname: Merletti
authors.forename: Giulia
authors.initials: G
authors.lastname: Novelli
authors.forename: Alberto
authors.initials: A
authors.lastname: Falorni
authors.forename: Antonio
authors.initials: A
authors.lastname: Iannilli
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Iughetti
authors.forename: Emma
authors.initials: E
authors.lastname: Altobelli
authors.forename: Giuseppe
authors.initials: G
authors.lastname: d'Annunzio
authors.forename: Silvano
authors.initials: S
authors.lastname: Piffer
authors.forename: Paolo
authors.initials: P
authors.lastname: Pozzilli
authors.forename: Dario
authors.initials: D
authors.lastname: Iafusco
authors.forename: Marco
authors.initials: M
authors.lastname: Songini
authors.forename: Federico
authors.initials: F
authors.lastname: Roncarolo
authors.forename: Sonia
authors.initials: S
authors.lastname: Toni
authors.forename: Flavia
authors.initials: F
authors.lastname: Carle
authors.forename: Valentino
authors.initials: V
authors.lastname: Cherubini
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D003922:Diabetes Mellitus, Type 1 / Q000453:epidemiology*; D005260:Female; D005843:Geography; D006801:Humans; D015994:Incidence; D007223:Infant; D007558:Italy / Q000453:epidemiology; D016013:Likelihood Functions; D008297:Male; D016012:Poisson Distribution; D012042:Registries