title: How do childhood diagnoses of type 1 diabetes cluster in time?
abstract: BACKGROUND
  Previous studies have indicated that type 1 diabetes may have an infectious origin. The presence of temporal clustering-an irregular temporal distribution of cases--would provide additional evidence that occurrence may be linked with an agent that displays epidemicity. We tested for the presence and form of temporal clustering using population- based data from northeast England.
  
  
  METHODS
  The study analysed data on children aged 0-14 years diagnosed with type 1 diabetes during the period 1990-2007 and resident in a defined geographical region of northeast England (Northumberland, Newcastle upon Tyne, and North Tyneside). Tests for temporal clustering by time of diagnosis were applied using a modified version of the Potthoff-Whittinghill method.
  
  
  RESULTS
  The study analysed 468 cases of children diagnosed with type 1 diabetes. There was highly statistically significant evidence of temporal clustering over periods of a few months and over longer time intervals (p<0.001). The clustering within years did not show a consistent seasonal pattern.
  
  
  CONCLUSIONS
  The study adds to the growing body of literature that supports the involvement of infectious agents in the aetiology of type 1 diabetes in children. Specifically it suggests that the precipitating agent or agents involved might be an infection that occurs in "mini-epidemics".
authors.affiliation: Institute of Health and Society, Newcastle University, Newcastle upon Tyne, United Kingdom. Colin.Muirhead@Newcastle.ac.uk
authors.forename: Colin R
authors.initials: CR
authors.lastname: Muirhead
authors.forename: Timothy D
authors.initials: TD
authors.lastname: Cheetham
authors.forename: Simon
authors.initials: S
authors.lastname: Court
authors.forename: Michael
authors.initials: M
authors.lastname: Begon
authors.forename: Richard J Q
authors.initials: RJ
authors.lastname: McNally
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003922:Diabetes Mellitus, Type 1 / Q000175:diagnosis / Q000453:epidemiology*; D004739:England / Q000453:epidemiology; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D015233:Models, Statistical; D016012:Poisson Distribution; D013029:Space-Time Clustering