The increasing prevalence of type 2 diabetes calls for effective population-based preventive strategies. Lifestyle modification, including dietary changes, among high-risk individuals has demonstrated efficacy in preventing and/or delaying diabetes. Furthermore, dietary approaches to lower postprandial glucose and insulin, potential risk factors for diabetes, have been linked to reduced risk.
Health impact model
Despite this evidence, quantitative estimates of the potential impact of different dietary approaches for diabetes risk do not exist. Health impact models can be used to predict the potential impact of dietary approaches or specific food components to reduce the population burden of disease. These models can also be used to estimate effects in certain subpopulations, such as people with impaired glucose tolerance, and to simulate the potential of changing specific diet behaviours. These are of value for underpinning, comparing and communicating the potential value of different foods and dietary approaches.
To validate the model, model-based predictions of the short-term impact of dietary interventions on diabetes incidence will be compared to direct estimates of the impact such as reported in studies. If necessary, model parameters will be tuned based on this comparison.
Quantitative health impact modeling, with explicit incorporation of the uncertainty associated with available data, is valuable in providing information to health policy makers. By the use of state-of-the-art mathematical and statistical techniques, health impact modeling can generate predictions of the potential size of health effects and associated uncertainty. The figure below is a schematic framework of the model being worked on during this project.