title: A hierarchical Bayesian birth cohort analysis from incomplete registry data: evaluating the trends in the age of onset of insulin-dependent diabetes mellitus (T1DM).
abstract: Childhood diabetes is one of the major non-communicable diseases in children under 15 years of age. It requires a life-long insulin treatment and may lead to serious complications. Along with the worldwide increase in the incidence several countries have recently reported a decreasing trend in the age of onset of the disease. The aim of this study is to analyse long-term data on the incidence of the childhood diabetes in Finland from the birth cohorts perspective. The annual incidence data were available for the period 1965--1996 which translates into 1951--1996 birth cohorts. Hence the data consist of completely and partially observed cohorts. Bayesian modelling was employed in the analysis. Several different priors and cohort combinations were tried in order to determine the sensitivity of the results. The cumulative birth cohort incidence of diabetes was determined to have an increasing average annual trend of 2.5 per cent. Although the average birth cohort-specific age of onset was estimated to have decreased slightly over the years of observation, the trend could be a result of random variation.
authors.affiliation: Department of Epidemiology and Health Promotion, National Public Health Institute, Mannerheimintie 166, Helsinki 00300, Finland. moltchan@iiasa.ac.at
authors.forename: E
authors.initials: E
authors.lastname: Moltchanova
authors.forename: A
authors.initials: A
authors.lastname: Penttinen
authors.forename: M
authors.initials: M
authors.lastname: Karvonen
mesh_terms: D000293:Adolescent; D017668:Age of Onset; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D003922:Diabetes Mellitus, Type 1 / Q000453:epidemiology*; D005260:Female; D005387:Finland / Q000453:epidemiology; D006801:Humans; D008297:Male; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method