Seasonality of birth in children and young adults (0–29 years) with type 1 diabetes in Ukraine View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2007-01

AUTHORS

A. M. Vaiserman, B. Carstensen, V. P. Voitenko, M. D. Tronko, V. I. Kravchenko, M. D. Khalangot, L. V. Mechova

ABSTRACT

AIMS/HYPOTHESIS: Numerous epidemiological studies have shown differences in seasonality of birth patterns between the general population and the group who develop type 1 diabetes mellitus. This finding indicates that environmental factors operating during pre- and/or postnatal development could be aetiologically important. We examined whether the pattern of month of birth for type 1 diabetes patients in Ukraine differs from that for total live births. METHODS: Data consist of prevalent cases of type 1 diabetes in Ukraine by the end of 2003. Cases are restricted to persons born after 1 January 1960, diagnosed with type 1 diabetes before the age of 30 years (n = 20,117). People born during the same time in the general population (n = 29,105,560) were the reference standard. Seasonal patterns were estimated using logistic regression with harmonic terms. RESULTS: We found a strongly significant seasonal pattern of type 1 diabetes incidence rates (p < 0.001), with the lowest rates in December and the highest in April. The rate ratio between the extremes was 1.32 (95% CI 1.27-1.39). Tests for seasonal patterns in subgroups defined by sex and age or by sex and date of birth were all significant with p values less than 0.02. We found no interactions with sex (p = 0.142) or age at diagnosis (p = 0.207), but found a strong interaction with period of birth (p < 0.0001). CONCLUSIONS/INTERPRETATION: The results obtained indicate that early-life factors linked to seasons may influence type 1 diabetes risk later in life. More... »

PAGES

32-35

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00125-006-0456-4

DOI

http://dx.doi.org/10.1007/s00125-006-0456-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039201400

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17093948


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