Seasonal variation and epidemiological parameters in children from Greece with type 1 diabetes mellitus (T1DM)

Pediatr Res. 2021 Feb;89(3):574-578. doi: 10.1038/s41390-020-0899-1. Epub 2020 Apr 23.


Background: A positive correlation between T1DM onset and winter has been suggested by several studies. We investigated the seasonal variation of T1DM diagnosis and epidemiological parameters in children from Western Greece with T1DM.

Methods: One hundred and five patients, 44 males, aged 1-16 years were studied. The month of the diagnosis, the order of birth, gestational age, birth weight, the mode of delivery, parental age and pubertal status were recorded from the patients' files.

Results: The mean age at diagnosis was 8.1 ± 4.0 years. The majority of the studied patients were diagnosed during the period of October-March. The majority were born at full term, 11.7% were preterm babies and 52.3% were first born. The mean birth weight was 3266 ± 596 g. 60% were born by vaginal delivery. The majority of the patients were prepubertal at diagnosis.

Conclusions: Our results are in agreement with the reported seasonal variation of T1DM onset in other regions of Greece and Europe. The positive correlation between T1DM presentation and colder temperatures may be explained by factors such as viral infections. This is the first report on epidemiological parameters that may be related to T1DM presentation in Western Greece. The study of such parameters extends the understanding on the disease as a whole.

Impact: A seasonality of the T1DM diagnosis is shown, with a predominance of the colder months of the year. This is in agreement with previous reports from other countries. Our findings confirm previously reported data and add to the existing knowledge on T1DM in general. Additionally, this is one of the few reports on the incidence and epidemiology of T1DM in Greece and the first in the region of Western Greece. Safer and more accurate conclusions can be drawn with regards to the possible causes and predisposing factors of T1DM by the assessment of statistical data from different populations throughout the world. This offers a better understanding of T1DM and may also contribute to the identification of factors that may reduce the incidence of the disease in the future.