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Assessment of Gastric Emptying in Non-obese Diabetic Mice Using a [13C]-octanoic Acid Breath Test
Published on: March 23, 2013
Cumulative effect of depressed mood and obesity on type II diabetes incidence: Findings from the MONICA/KORA cohort
S Atasoy1, H Johar2, X Y Fang3
1Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute of Medical Informatics, Biometry and Epidemiology (IBE), München, Germany.
Background:
Obesity and depression both individually contribute to the risk of Type II Diabetes (T2DM). The extent to which obesity can be set-off by depression is unknown.
Methods:
In a sample of 9340 participants followed for 15.4 years (79,372 person-years) from the prospective MONICA/KORA population-based cohort conducted in Southern Germany, we investigated the impact of obesity, defined as Body Mass Index (BMI) ≥ 30, and depression on the incidence of T2DM using Cox Proportional Hazards Regression.
Results:
The relative risk of T2DM was over 6 fold higher among obese participants in comparison to normal weight participants (HR 6.05; 95% CI 4.82 to 7.59; p < .0001). Nonetheless, among participants with obesity, comorbidity of depression was associated with an additional 2 fold risk T2DM (HR 8.05, 95% CI 5.90-10.98; p < .0001). This finding corresponded to an increase in the 15.4-year absolute risk of T2DM from 15.9 cases per 1000 person-years (py) in participants with obesity but not depression, to 21.4 cases per 1000 py for participants with obesity and depression. Further analysis of joint effects and Relative Excess Risk due to Interaction disclosed that depressed mood is associated with significantly higher risk of T2DM in participants with obesity, and to a lesser extent in overweight participants, however an association was not found in normal weight participants.
Conclusions:
The present investigation discloses that despite the overreaching importance of obesity as a risk factor for T2DM, there is room for depressed mood to add measurable risk prediction.
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