There is no way literally to measure health, because health is multi-dimensional, and there is no metric whereby one person who is healthier than a second with respect to one dimension but less healthy with respect to another counts as healthier, less healthy or equally healthy overall. Health analysts instead measure how good or bad health states are in some regard. If these values are measures of health states, then identical health states must have identical values. But in different circumstances, (...) the same health state may have different values. It may be better or worse. Uniform values can nevertheless be assigned to kinds of health states, either as a weighted average of the values of their tokens or as the value of the performance in a standard environment of the capacity the health state constitutes. These uniform values are not well suited for some of the purposes for which summary measures of population health have been intended, and a set of non-evaluative indicators may be an attractive alternative. (shrink)

Reducing inequalities in health and the determinants of health is a widely acknowledged health policy goal, and methods for measuring inequalities and inequities in health are well developed. Yet, the evidence base is weak for how to achieve these goals. There is a lack of high-quality randomised controlled trials reporting impact on the distribution of health and non-health benefits and lack of methodological rigour in how to design, power, measure, analyse and interpret distributional impact in RCTs. Our overarching aim in (...) this paper is to contribute to the emerging effort to improve transparency and coherence in the theoretical and conceptual basis for RCTs on effective interventions to reduce health inequity. We endeavour to achieve this aim by pursuing two more specific objectives. First, we propose an overview of three broader health equity frameworks and clarify their implications for the measurement of health inequality in RCTs. Second, we seek to clarify the relationship between theory and translational challenges that researchers would need to attend to, in order to ensure that equity-relevant RCTs are coherently grounded in theory. (shrink)

The history of the documentation of health inequality is long. The way in which health inequality has customarily been documented is by comparing differences in the average health across groups, for example, by sex or gender, income, education, occupation, or geographic region. In the controversial World Health Report 2000, researchers at the World Health Organization criticized this traditional practice and proposed to measure health inequality across individuals irrespective of individuals’ group affiliation. They defended its proposal on the moral grounds without (...) clear explanation. In this paper I ask: is health inequality across individuals of moral concern, and, if so, why? Clarification of these questions is crucial for meaningful interpretation of health inequality measured across individuals. Only if there was something morally problematic in health inequality across individuals, its reduction would be good news. Specifically, in this paper I provide three arguments for the moral significance of health inequality across individuals: (a) health is special, (b) health equity plays an important and unique role in the general pursuit of justice, and (c) health inequality is an indicator of general injustice in society. I then discuss three key questions to examine the validity of these arguments: (i) how special is health?, (ii) how good is health as an indicator?, and (iii) what do we mean by injustice? I conclude that health inequality across individuals is of moral interest with the arguments (b) and (c). (shrink)

Health has an important role in the achievement of a good quality of life. Many public policies intended to enhance individual and population health. Amartya Sen’s Capability Approach (CA) offers a framework to assess well-being, as well as interventions seeking to increase it. There are, however, important practical challenges that must be faced before applying CA to concrete situations, such as health. One of these challenges is defining whether it is functioning or a capability that is the feature to be (...) assessed. Moreover, some aspects of freedom that are relevant for CA are frequently neglected, such as agency. These aspects must be considered when performing a health assessment using the CA as a framework. A health assessment using the CA as a framework should include indicators based on the achieved dimension (health functioning), resources and conversion factors (health capability), and freedom to achieve (agency). (shrink)