Context: Selection of priority groups is important for health interventions. However, no quantitative method has been developed.
Objectives: To develop a quantitative method to support the process of selecting priority groups for public health interventions based on both high risk and population health burden.
Design: Secondary data analysis of the 2010 Canadian Community Health Survey.
Setting: Canadian population.
Participants: Survey respondents.
Methods: We identified priority groups for 3 diseases: heart disease, stroke, and chronic lower respiratory diseases. Three measures—prevalence, population counts, and adjusted odds ratios (OR)—were calculated for subpopulations (sociodemographic characteristics and other risk factors). A Priority Group Index (PGI) was calculated by summing the rank scores of these 3 measures.
Results: Of the 30 priority groups identified by the PGI (10 for each of the 3 disease outcomes), 7 were identified on the basis of high prevalence only, 5 based on population count only, 3 based on high OR only, and the remainder based on combinations of these. The identified priority groups were all in line with the literature as risk factors for the 3 diseases, such as elderly people for heart disease and stroke and those with low income for chronic lower respiratory diseases. The PGI was thus able to balance both high risk and population burden approaches in selecting priority groups, and thus it would address health inequities as well as disease burden in the overall population.
Conclusions: The PGI is a quantitative method to select priority groups for public health interventions; it has the potential to enhance the effective use of limited public resources.Author(s): Bo Zhang, Joanna Cohen, and Shawn O'Connor
Date: September 2014
Type of Publication: Journal Article