Introduction: Increase in diabetes prevalence in the U.S. is likely due to demographic and dietary changes, but epidemiological studies do not show large enough changes in either to explain the magnitude of diabetes increase. We used a validated diabetes model to decompose the impact of diet on diabetes prevalence from 2001-2014, while considering demographics data and new diabetes diagnosis criteria.

Methods: We used a published model of diabetes that considers macronutrient intake, demographics and individual physiology to simulate a virtual population matched to U.S. demographics in 2001 and advanced it annually by updating demographic distribution (matched to U.S. Census) and diet (estimated by training the model to CDC-estimated diabetes prevalence from ‘01-’06). Prevalence was forecast for ‘07-’14 assuming the estimated diet trend continued linearly.

Results: Predicted prevalence was within 0.24% (absolute error) of CDC estimates between ‘07-‘14. Diabetes rates were largely explained by increase in carbohydrate (5%) and decrease in fat intake (11%) between ‘01-’14. The apparent plateau in diagnosed diabetes after 2010 (Figure) is inconsistent with model prediction unless both high HbA1c and glucose are used to diagnose diabetes, suggesting possible misuse of the ‘10 criteria in clinical practice.


S. Mohanty: None. C.M. Chelini: Employee; Self; Pwc. P. D'Alessandro: None. G. Dwivedi: None.

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