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Objectives The aim of the study was to compare health problems as defined quantitatively by the Burden of Disease study to those defined by the community. The secondary aim was to explore the potential for using qualitative participatory methodologies as tools for planing and priority setting. Design Interviews and group discussions with a purposely sampled set of community members (n =51) and community leaders (n =6). The Nominal group technique, as well as in-depth interviews, were used to identify major health problems – as perceived by the community. Epidemiological data on the major health problems were derived from the national Burden of Disease study. Results Community perceived health problems were similar to those identified by the burden of disease study. Reasons given for the ranking included prevalence, fatality, social and cultural stigma. Social stigma and cultural values were not considered in the burden of disease studies. However, socially stigmatized diseases were considered to be more serious compared to non-stigmatised conditions, in spite of their low prevalence. Poverty and lack of knowledge were the perceived major causes of ill-health in the community. Conclusions Qualitative approaches like the nominal group technique may be useful in eliciting community values that could supplement quantitative information like that elicited by the Burden of Disease study. Such a mixed approach would capture both epidemiologicaly assessed and community felt needs in the priority setting process. [ABSTRACT FROM AUTHOR]

Introduction Measurement of health inequities is fundamental to all health equity initiatives. It is complex because it requires considerations of ethics, methods, and policy. Drawing upon the recent developments in related specialized fields, in this paper we incorporate alternative definitions of health inequity explicitly and transparently in its measurement. We propose a three-stage approach to measuring health inequities that assembles univariate health inequality, univariate health inequity, and bivariate health inequities in a systematic and comparative manner. Methods We illustrate the application of the three-stage approach using the Joint Canada/United States Survey of Health, measuring health by the Health Utilities Index (HUI). Univariate health inequality is the distribution of the observed HUI across individuals. Univariate health inequity is the distribution of unfair HUI -- components of HUI associated with ethically unacceptable factors -- across individuals. To estimate the unfair HUI, we apply two popular definitions of inequity: "equal opportunity for health" (health outcomes due to factors beyond individual control are unfair), and "policy amenability" (health outcomes due to factors amenable to policy interventions are unfair). We quantify univariate health inequality and inequity using the Gini coefficient. We assess bivariate inequities using a regression-based decomposition method. Results Our analysis reveals that, empirically, different definitions of health inequity do not yield statistically significant differences in the estimated amount of univariate inequity. This derives from the relatively small explanatory power common in regression models describing variations in health. As is typical, our model explains about 20% of the variation in the observed HUI. With regard to bivariate inequities, income and health care show strong associations with the unfair HUI. Conclusions The measurement of health inequities is an excitingly multidisciplinary endeavour. Its development requires interdisciplinary integration of advances from relevant disciplines. The proposed three- stage approach is one such effort and stimulates cross-disciplinary dialogues, specifically, about conceptual and empirical significance of definitions of health inequities. [ABSTRACT FROM AUTHOR]