The development of scientific evidence for health policies for obesity: why and how?

Abstract

Potential obesity-related policy approaches have recently been receiving more attention. While some have been implemented and others only proposed, few have been formally evaluated. We discuss the relevance, and in some cases irrelevance, of some of the types of evidence that are often brought to bear in considering obesity-related policy decisions. We discuss major methods used to generate such evidence, emphasizing study design and the varying quality of the evidence obtained. Third, we consider what the standards of evidence should be in various contexts, who ought to set those standards, as well as the inherent subjectivity involved in making policy decisions. Finally, we suggest greater transparency from both academics and policymakers in the acknowledgment of subjectivities so they can distinguish and communicate the roles played by empirical evidence and subjective values in the formulation of policy.

Socioeconomic inequalities in obesity: modelling future trends in Australia

“…People generally accrue BMI during their life course11 and, as a result, there has been great interest in identifying BMI trajectories through longitudinal studies or modelling BMI growth trajectories12 to understand the epidemiology of disease and to identify at-risk populations. Beyond their value in epidemiological studies, models are regarded as powerful tools for informing policy decisions,13 yet current models of obesity rarely take account of socioeconomic position (SEP), thus overlooking a key policy-relevant determinant of obesity. There are currently few analytical tools to evaluate which interventions are most effective in reducing inequalities 14.…”

Simulation modeling to assist with childhood obesity control: perceptions of Baltimore City policymakers

“…There are numerous examples of well-intentioned obesity-related policies and programs that have led to undesired consequences [32]. Further, the quality of data in obesity research ranges widely [33]. As a result, computational simulation models should be carefully validated prior to use in obesity prevention.…”

Unpalatable food for thought: Let marketing research guide effective public obesity interventions

“…The specific contributions of each are recognized in the call for more openness to observational and emerging hybrid research designs for investigating public prevention efforts in obesity 4,59,74 and public health more broadly 73,80 . Other hybrid research designs that might be considered include pragmatic clinical trials, 85 quasi‐experimental designs, natural experiments and field experiments 4,19,86–88 . In quasi‐experimental designs for instance, researchers may sacrifice full random assignment but can nevertheless examine the success of interventions in situ.…”

“…Outcomes further from the ultimate outcomes become less valid suggesting a clear hierarchy of preferred effects: energy intake should be preferenced over food quantity consumed, consumption over purchase and behaviours over cognitions. However, the ideal is to focus on ultimate outcomes rather than rely on measures of ‘presumed mediating variables’ 19 …”

“…Public health and policymakers are actively searching for guidance from relevant research. However, research where ‘the effects of a policy remain speculative’ 19 is not particularly helpful. We propose that public health and policymakers will be better served by more applied marketing research which (1) focuses on the ultimate outcomes that interventions seek to change, (2) focuses on research designs that test interventions in real‐world settings over time and (3) focuses on analyses of effect sizes (rather than statistical significance).…”