Abstract/Summary

The emerging scientific field of public health economics, considering health-related behaviours such as physical activity and smoking, is establishing itself as an important component in assessing the impact of policy interventions on preventing disease. Epidemiological evidence points to links between diet, lifestyle and non-communicable diseases (NCDs). Policy decisions aimed at preventing or reducing the burden of NCDs need credible, reliable and evidence-based scientific information. In this context, facts are uncertain and values are contested, while decisions are often urgent and the stakes are high, a typical setting for post-normal science (PNS). Therefore, this work applies quality tools developed in the context of PNS to models used in nutrition and public health economics, using as a guide the seven-point checklist of sensitivity auditing. This analysis has identified scope for improvement in a number of areas, such as the definition of the modelling exercise scope, the justification of the choice of family of models adopted, comprehensively framing the issue by including the perspective of relevant stakeholders and the exertion of more care in justifying assumptions. Addressing these dimensions may even result in refraining from producing a quantitative assessment when the circumstances do not hold. This would conflict with the common imperative to quantify in regulatory policies - often requested by policy guidelines - and with the dynamics of the policy cycle. For this reason, we discuss the implied trade-offs, contradictions and way forward with an eye to achieving progress in the practice.