Social determinants and surveillance in the new Millennium

Abstract

Surveillance has been a common practice in Public Health (Teutsch and Churchill 2000; Lee et al. 2010; Croft et al. 2009), although, until recent decades, it has been applied mainly to the infectious diseases. Now, that Non communicable diseases (NCD’s) are the major cause of morbidity and mortality globally, much attention has been paid to NCD surveillance and, more specifically, to the surveillance of NCD related risk factors. This is often called Behavioral Risk Factor Surveillance (BRFS, McQueen and Puska 2003; Campostrini and McQueen, 2005) to emphasize the importance of risk factors, although, in the practice, BRFS practice covers a wide range of public health related matters (e.g., from vaccination to service access to demographic data). The major challenge Public Health is facing globally at the beginning of this new millennium is that of ‘‘closing the gap’’ (CSDH 2008), working for reducing health disparities within and between countries. Particularly national and local public health systems face the challenge of adopting suitable interventions and policies to reduce inequalities caused by Social Determinants (SD; Marmot 2009). If health outcomes are derived mainly by the agency of key behavioral risk factors, and SD the ‘‘causes of the causes’’ of such risk factors (Marmot 2005), it is dramatically important for decision makers charged with reducing health inequalities to have information both on the causes (risk factors) and the causes of the causes (SD). In search for what is termed ‘‘evidence-based public health’’ (McQueen 2001), quite often public-health professionals and more specifically health-promotion practitioners have struggled to find suitable information for evaluating the effectiveness of their work. Surveillance data and particularly BRFS data are an important source (Campostrini and McQueen 2005; Campostrini 2007; Minardi et al., this issue) for evidence that can be used to plan, monitor, and evaluate interventions or policies aimed to reduce the effect of SD on health disparities. The discussion about how to best measure the SD is still open, and much research is needed to agree on how to effectively measure SD to better understand the mechanisms by which generally (but not always) the ‘‘poorer’’ are the more unhealthy. With guidance from the papers published in this issue, we would like to note briefly some particular issues that show why the BRFS approach is a unique source for information on SD and health. As we see in the work of Pfoertner et al. (this issue), there is always something that we can know better about the relationship between poverty and health that is quite often shadowed by conventional measurements. The need to consider a wide range of aspects, not only economical, but also social and cultural (Abel 2008) is quite globally acknowledged, still the ‘‘how to (measure)’’ is under discussion. S. Campostrini and T. Abel edited the special issue ‘‘Monitoring social determinants of health’’.