Learning Through Chain Event Graphs: The Role of Maternal Factors in Childhood Type 1 Diabetes

Keeble, C., Thwaites, P. A., Baxter, P. D. , Barber, S., Parslow, R. C. and Law, G. R. (2017) Learning Through Chain Event Graphs: The Role of Maternal Factors in Childhood Type 1 Diabetes. American Journal of Epidemiology, 186 (10). pp. 1204-1208. ISSN 0002-9262

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Item Type:Article
Item Status:Live Archive


Chain event graphs (CEGs) are a graphical representation of a statistical model derived from event trees. They have previously been applied to cohort studies but not to case-control studies. In this paper, we apply the CEG framework to a Yorkshire, United Kingdom, case-control study of childhood type 1 diabetes (1993–1994) in order to examine 4 exposure variables associated with the mother, 3 of which are fully observed (her school-leaving-age, amniocenteses during pregnancy, and delivery type) and 1 with missing values (her rhesus factor), while incorporating previous type 1 diabetes knowledge. We conclude that the unknown rhesus factor values were likely to be missing not at random and were mainly rhesus-positive. The mother’s school-leaving-age and rhesus factor were not associated with the diabetes status of the child, whereas having at least 1 amniocentesis procedure and, to a lesser extent, birth by cesarean delivery were associated; the combination of both procedures further increased the probability of diabetes. This application of CEGs to case-control data allows for the inclusion of missing data and prior knowledge, while investigating associations in the data. Communication of the analysis with the clinical expert is more straightforward than with traditional modeling, and this approach can be applied retrospectively or when assumptions for traditional analyses are not held.

Keywords:Diabetes, bmjembargo
Subjects:B Subjects allied to Medicine > B990 Subjects Allied to Medicine not elsewhere classified
Divisions:College of Social Science > School of Health & Social Care
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ID Code:26599
Deposited On:09 Mar 2017 16:54

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