To learn more about EpiX Analytics' work, please visit our modeling applications, white papers, and training schedule.

Page tree

The following webinar was presented for a Norwegian and international audience. The goal was to provide a risk analyst's perspective on the methodology used to estimate and forecast the health impact of diets. 

Follow this link for the full webinar recording

The slides can be found here:

Webinar 1: How do they do it? A nutritionist-friendly explanation of the modeling methods used for the retrospective estimation of dietary burden of disease. 


Description: the estimation of the health impact of diets is conceptually simple, but its calculation and underlying assumptions can be math-heavy and sometimes intimidating to non-modelers. In this first of a two-webinar series, the presenters will provide a gentle introduction to the modeling methods used to estimate the health impact of diets. Topics will include how evidence on health impacts of dietary components is assessed and gathered, and how these estimates are translated into health metrics. Using the EAT-Lancet commission report as an example, the presenters will also discuss how implicit assumptions and the handling of statistical uncertainty can affect the conclusions of a dietary health impact study.   


Webinar 2: How will we do? Disentangling the methodology used to forecast health impacts of diets using burden of disease calculations. 


Description: the future does not always follow what has occurred in the past, and dietary interventions are no exception.  In this final webinar of a two series installment, the presenters will provide an intuitive explanation of the quantitative methodology used to forecast the future health impact of diets. As for the first webinar on estimation, the presenters will discuss the key assumptions used in such studies, and the correct methods to deal with uncertainty in health projections. Some of the examples used will include the Klimakur report recently published in Norway, and attempts to use the GBD as a forecasting tool for dietary changes.  

  • No labels