The Role of Average Health Status - Health Inequalities Matrix for Assessing Impacts on Population Health in Health in All Policies

Introduction

There is increasing awareness that policies in all sectors have some impact on health. Health in All Policies approach aims to improve population health and health equity by taking into account these impacts when decisions are made (WHO, 2014). In order to be successful, apart from political will and resources, Health in All Policies needs appropriate tools for proper assessment of impacts on population health from different policy options. Such tools include: Social Impact Assessment which looks at social consequences from a policy and aims sustainable development (Becker, 1997); Health Impact Assessment (HIA) which explicitly looks for and examines impacts on population health (Lehto & Ritsatakis, 1999); Average Health Status – Health Inequalities Matrix (Panayotov 2006b; 2008a) which looks at the impacts on population health from different policy options in terms of changes in average health status and health inequalities; and Equity-Focussed Evaluation – an emerging concept with developing methodology, which is concerned with achieving equitable development (Bamberger & Segone, 2011).

Melkas (2013) suggests that “HIA is a key tool”. However, Panayotov (2010) points out that there are problems with HIA methodology, and policies can create and/or widen health inequalities, even if nobody is worse-off (see Examples, Case I). How to determine which is the best tool for successful Health in All Policies approach?

Population health has two major variables: average health status (AHS) and health inequalities (HI). During the last six decades decision-makers around the world were focused on improving AHS. HI are discussed since 1990 and Douglas & Scott-Samuel (2001) suggest that HIA should address HI, recognising that there is tension arising from the trade-offs between improving AHS and improving health of the most disadvantaged. What should decision-makers strive for in relation to population health: improving AHS, or reducing HI? While analysing the correlation between these two variables, Panayotov (2006a) points out that although that these two goals may look similar, they have different paths which lead to different ends. For example, AHS will improve, when the health of those who are better-off improves faster than rest of the population, but as result HI will increase. He points out that from an economics point of view creating and/or widening of HI represents inefficient and unsustainable allocation of limited public resources (Panayotov, 2006b). Showing that in relation to population health achieving equity is a premise for efficiency (maximizing population health with limited available resources), Panayotov (2006b) asserts that HI should be reduced not only on compassionate grounds. Therefore, he suggests that the goal for improving AHS should go hand-in-hand with the goal for reducing HI.