1. ¹School of Nursing and Department of Global Health, University of Washington, Seattle, WA, USA
2. ²University of Cincinnati College of Nursing, Cincinnatti, Ohio, USA
3. ³Department of Mathematics and Statistics, University of Montreal, Montreal, Québec, Canada

Correspondence: Sue Thomas Hegyvary, School of Nursing, University of Washington, 1959 Pacific Street, Box 357266, Seattle, WA 98195, USA. E-mail: hegyvary@u.washington.edu

Abstract

Clustering countries based on health outcomes is a useful technique for assessing global health disparities. However, data on country-specific indicators of health outcomes are inconsistent across databases from different sources, such as World Bank, WHO, and UNICEF. The new database on under-five child mortality from the Institute for Health Metrics and Evaluation advances information about child mortality by showing both country-level estimates and confidence intervals. We used the new database for child mortality and WHO data for HALE from 160 countries to identify country clusters through model-based clustering techniques. The four clusters in 2000 and six in 2003, within levels of uncertainty, showed nonlinear distributions of health outcomes globally, indicating that no single trajectory for progression is evident. We propose the use of country clusters in further study of societal conditions that contribute to health outcomes and changes over time.