Seasonal Variation in Month of Diagnosis of Polish Children with Type 1 Diabetes - A Multicenter Study

Exp Clin Endocrinol Diabetes. 2019 May;127(5):331-335. doi: 10.1055/s-0043-125321. Epub 2018 Mar 5.


Aim: The seasonal variation of incidence of type 1 diabetes (T1D) theory supports the hypothesis that environmental factors play a role in the onset of the disease. The aim of this study is to assess seasonality of month of diagnosis in children with T1D in Poland.

Material and methods: the study group consisted of 2174 children from eastern and central Poland diagnosed with T1D between 2010 and 2014. Analysis was performed in different age groups, based on place of residence (rural/urban area) and depending on sex.

Results: We noted significant seasonality in the incidence of T1D with a peak in diagnosis of diabetes in January and the minimum rate in June. A total of 423 (19%) children were diagnosed in the warmest months (June to August with a mean temperature of 16.8°C) compared to 636 (29%) recognised in the coldest months (December to February with a mean temperature of -1.6°C), OR 0.57 95%CI [0.51-0.67], p<0.0001. We noted a more flat seasonal pattern in children 0-4 years of age compared with subjects 5-17 years old with a week correlation of trend comparison between both groups, r=0.69, p=0.001. Similar seasonal variation in the incidence of T1D was noted in children from urban and rural setting. For girls, seasonal pattern peaks were observed one month earlier as compared to boys.

Conclusions: Seasonal variation in incidence of T1D diagnosis of Polish children supports the role of different environmental factors in diabetes onset. The majority of children were diagnosed with diabetes in autumn and winter.

Publication types

  • Multicenter Study

MeSH terms

  • Adolescent
  • Child
  • Child, Preschool
  • Diabetes Mellitus, Type 1 / diagnosis*
  • Diabetes Mellitus, Type 1 / epidemiology*
  • Female
  • Humans
  • Incidence
  • Infant
  • Male
  • Poland / epidemiology
  • Rural Population / statistics & numerical data
  • Seasons*
  • Urban Population / statistics & numerical data