ArticleEnvironmental health : a global access science source2009
Space-time clustering analyses of type 1 diabetes in children from north-east England: support for an infectious aetiology?
Article in Environmental health : a global access science source, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Geospatial clustering of type 1 diabetes in Sweden: a cohort study based on all residential locations from birth to diagnosis.Diabetologia · 2026Article
- Clustering patterns in Finnish type 1 diabetes patients: a nationwide register-based study.BMJ open diabetes research & care · 2025Article
- A Scoping Review of GIS Mapping of Type 1 Diabetes in Children: Identifying Current Gaps and Future Research Directions Using PRISMA-ScR.Current diabetes reviews · 2025Article
- Analysis of Apoptotic, Clinical, and Laboratory Parameters in Type 1 Diabetes and Early Diabetic Nephropathy: Clustering and Potential Groups Evaluation for Additional Therapeutic InterventionsJournal of clinical research in pediatric endocrinology · 2022Article
- Article
- A synopsis of the Joint Environment and Human Health Programme in the UK.Environmental health : a global access science source · 2009Article
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Abstract
backgroundThe aetiology of type 1 diabetes in children is uncertain. A number of recent studies have suggested an infectious aetiology. It has been postulated that an infectious agent may be involved. Support for this hypothesis may be provided by a finding of space-time clustering. The aims of this study were: (i) to determine whether there was space-time clustering in cases of childhood diabetes from north-east England; and to test for differences in space-time clustering: (ii) due to age at diagnosis; (iii) between the sexes and (iv) between levels of residential population density.
methodsWe studied incidence of type 1 diabetes diagnosed in children aged 0-14 years and diagnosed during the period 1990-2007. All cases were resident in a defined geographical region of north-east England (Northumberland, Newcastle upon Tyne and North Tyneside). We applied a second-order procedure based on K-functions to test for global clustering. Locations were residential addresses at time of diagnosis. Tests were repeated using nearest neighbour thresholds to allow for variable population density, providing the primary result for each analysis. Differences between sexes and between levels of population density were assessed.
resultsWe analysed 457 cases of type 1 diabetes. Overall, there was marginally significant evidence of global space-time clustering (P = 0.089). There was statistically significant clustering amongst pairs of cases that contained at least one female (P = 0.017), but not amongst pairs of cases that contained at least one male (P = 0.190). Furthermore, there was significant clustering amongst pairs of cases that contained at least one from a more densely populated area (P = 0.044), but not amongst pairs of cases that contained at least one from a less densely populated area (P = 0.226).
conclusionAlthough the analyses have only found marginally significant evidence of global space-time clustering for cases of type 1 diabetes diagnosed in north-east England, there were two notable findings. First, there was evidence of clustering amongst females and secondly clustering was confined to cases from more densely populated areas. These findings are consistent with a possible aetiological involvement of an infectious agent.
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