Television watching and incident diabetes: Findings from the European Prospective Investigation into Cancer and Nutrition-Potsdam Study

J Diabetes. 2010 Mar;2(1):23-7. doi: 10.1111/j.1753-0407.2009.00047.x. Epub 2009 Jul 21.

Abstract

Background: The aim of the present study was to examine whether the amount of time spent watching television is a potential risk factor for incident diabetes and to what extent this association may be explained by obesity.

Methods: We used data for 23,855 men and women from the European Prospective Investigation into Cancer and Nutrition-Potsdam Study. During an average of 7.8 years of follow-up, 927 participants developed diabetes. Incident diabetes was identified on the basis of self-report and was verified by contacting the patient's attending physician. The amount of time spent watching television was self-reported.

Results: The mean time that the participants who developed diabetes watched television was 2.4 h/week, compared with 2.0 h/week for those who did not develop diabetes (P<0.001). After adjusting for age, sex, educational status, smoking status, alcohol use, occupational activity, physical activity, the intake of various foods, and systolic blood pressure, the adjusted hazard ratio for diabetes among participants who watched ≥4 h/day of television compared with those who watched <1 h/day was 1.63 [95% confidence interval (CI): 1.17-2.27]. After additional adjustment for waist circumference and body mass index, the hazard ratio was reduced to 1.14 (95% CI: 0.81-1.61).

Conclusions: In the present study, the amount of time spent watching television was an independent predictor of incident diabetes only in models that adjusted for sociodemographic characteristics, lifestyle behaviors, and systolic blood pressure. The attenuation of the association after adjusting for anthropometric measures may represent an explanatory mechanism for our findings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Diabetes Mellitus / epidemiology*
  • Diet
  • Educational Status
  • Female
  • Germany
  • Humans
  • Life Style*
  • Male
  • Middle Aged
  • Obesity / epidemiology*
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Systole / physiology
  • Television / statistics & numerical data*
  • Time Factors