Fit to the task: using Canadian data for evidence-informed public health

Abstract

The challenge of data gaps in public health Evidence-informed decision-making (EIDM) is the practice of integrating scientific research evidence with the many other competing social and political considerations that inform policy (National Collaborating Centre for Methods and Tools, 2012). However, decision-makers and those who participate in policy development are often confounded in this effort by data that are patchy, weak, or missing altogether. We must often reach for the "next best thing, " typically data or studies from other demographically "comparable" nations, whom we assume to live, eat, work, and recreate in a manner closely similar to our Canadian population, under similar environmental conditions. This is problematic given that, within our own Canadian population, there is a wide disparity in factors influencing health, such as access to healthy foods, clean drinking water, and the presence of environmental contaminants. Also at issue is how we use data. Although it may be useful to know that a given intervention had a certain effect in some other population (i.e., a static study), having access to detailed health data collected repeatedly over time (i.e., surveillance data) allows us to not only make comparisons amongst populations and track changes in health status, but also predict the health impacts of specific interventions and evaluate them after implementation. The aim of this short commentary is to highlight two large, cross-sectional, representative Canadian data sets that have great potential to inform public health policy; one such example is the use of research around the built environment.