Season of birth and the risk of type 2 diabetes in adulthood: a prospective cohort study of 0.5 million Chinese adults

Diabetologia. 2017 May;60(5):836-842. doi: 10.1007/s00125-016-4200-4. Epub 2017 Jan 7.


Aims/hypothesis: Season of birth as a surrogate for potential environmental exposure during fetal development and early postnatal life has shown an inconsistent association with adult type 2 diabetes in white populations living in high-latitude regions. The present study aimed to examine the association between birth seasonality and risk of adult type 2 diabetes in Chinese individuals living across wide regions of low latitude and lower to middle latitude.

Methods: Participants from the China Kadoorie Biobank were enrolled during 2004-2008 and followed up until 31 December 2013. After excluding participants with cancer, heart disease, stroke and diabetes at baseline, the present study included 189,153 men and 272,058 women aged 30-79 years. We used multivariable Cox proportional hazards model to estimate the HR and 95% CI.

Results: During a median follow-up of 7.2 years (3.3 million person-years), we documented 8784 incident cases of type 2 diabetes. In the whole cohort, compared with summer-born participants, the adjusted HRs (95% CIs) were 1.09 (1.02, 1.16), 1.08 (1.02, 1.15) and 1.09 (1.02, 1.15) for those who were born in Spring, Autumn and Winter, respectively. The association was consistent in both men and women and across subgroups defined by residence and lifestyle factors later in life.

Conclusions/interpretation: In this large prospective study, participants born in summer had a lower risk of adult type 2 diabetes compared with other seasons of birth, suggesting exposures in early life with some degree of seasonal variation might influence the risk of adult diabetes.

Keywords: Fetal development; Seasons; Type 2 diabetes.

MeSH terms

  • Adult
  • Aged
  • Asian People
  • China / epidemiology
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Factors
  • Seasons*
  • Waist Circumference / physiology