Microsimulation Modeling in Food Policy: A Scoping Review of Methodological Aspects

Abstract

Food policies for the prevention and management of diet-related noncommunicable diseases (NCDs) have been increasingly relying on microsimulation models (MSMs) to assess effectiveness. Given the increased uptake of MSMs, this review aims to provide an overview of the characteristics of MSMs that link diets with NCDs. A comprehensive review was conducted in PubMed and Web of Knowledge. Inclusion criteria were: 1) findings from an MSM; 2) diets, foods, or nutrients as the main exposure of interest; and 3) NCDs, such as overweight/obesity, type 2 diabetes, coronary heart disease, stroke, or cancer, as the disease outcome for impact assessment. This review included information from 33 studies using MSM in analyzing diet and diverse food policies on NCDs. Hereby, most models employed stochastic, discrete-time, dynamic microsimulation techniques to calculate anticipated (cost-)effectiveness of strategies based on food pricing, food reformulation, or dietary (lifestyle) interventions. Currently available models differ in the methodology used for quantifying the effect of the dietary changes on disease, and in the method for modeling the disease incidence and mortality. However, all studies provided evidence that the models were sufficiently capturing the close-to-reality situation by justifying their choice of model parameters and validating externally their modeled disease incidence and mortality with observed or predicted event data. With the increasing use of various MSMs, between-model comparisons, facilitated by open access models and good reporting practices, would be important for judging a model's accuracy, leading to continued improvement in the methodologies for developing and applying MSMs and, subsequently, a better understanding of the results by policymakers.

Keywords: chronic diseases; food policies; health decision-making; microsimulation modeling; public health.