Our project builds upon the recent advancements in methodology for causal inference to conduct comparative effectiveness research in the field of nutritional epidemiology. We will use the target trail conceptual framework and causal analytical methods, the parametric g-formula to evaluate the effectiveness of hypothetical dietary interventions on the risk of different chronic conditions by using data from the Swedish Mammography Cohort and the Cohort of Swedish Men. Nutritional epidemiology uses observational data extensively, as randomized controlled experiments are expensive and often difficult to conduct. However, previous research has been struggling with methodological shortcomings, often as the consequences of ill-defined interventions, i.e., limiting the research question of examining the associations between different levels of a nutrient or different dietary patterns and the risk of CVD and other chronic diseases, but not explicitly formulating the causal question. Furthermore, conventional methods and measurement of dietary information one point at a time, assuming that the given dietary pattern are stable over time and that there is no treatment-confounder feedback between diet and other risk factors. Evaluating the effectiveness of sustained interventions requires both repeated longitudinal measures and causal analytical methods which can handle the feedback loop between the examined dietary factors and other risk factors. In this proposal we aim to quantify the effect of dietary intervention on the intake of specific foods both with and without substitution on the risk of different chronic diseases. We will use the parametric g-formula to quantify the effect of the different hypothetical dietary interventions on the risk of the different chronic diseases.