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Summary objectiveTo demonstrate the viability and value of comparing cause-specific mortality across four socioeconomically and culturally diverse settings using a completely standardised approach to VA interpretation.MethodsDeaths occurring between 1999 and 2004 in Butajira (Ethiopia), Agincourt (South Africa), FilaBavi (Vietnam) and Purworejo (Indonesia) health and socio-demographic surveillance sites were identified. VA interviews were successfully conducted with the caregivers of the deceased to elicit information on signs and symptoms preceding death. The information gathered was interpreted using the InterVA method to derive population cause-specific mortality fractions for each of the four settings.ResultsThe mortality profiles derived from 4784 deaths using InterVA illustrate the potential of the method to characterise sub-national profiles well. The derived mortality patterns illustrate four populations with plausible, markedly different disease profiles, apparently at different stages of health transition.ConclusionsGiven the standardised method of VA interpretation, the observed differences in mortality cannot be because of local differences in assigning cause of death. Standardised, fit-for-purpose methods are needed to measure population health and changes in mortality patterns so that appropriate health policy and programmes can be designed, implemented and evaluated over time and place. The InterVA approach overcomes several longstanding limitations of existing methods and represents a valuable tool for health planners and researchers in resource-poor settings.

Original publication

DOI

10.1111/j.1365-3156.2010.02601.x

Type

Journal

Tropical medicine & international health : TM & IH

Publication Date

10/2010

Volume

15

Pages

1256 - 1265

Addresses

Department of Public Health and Clinical Medicine, Division of Epidemiology & Global Health, Umeå Centre for Global Health Research, Umeå University, Umeå, Sweden. Edward.Fottrell@epiph.umu.se

Keywords

Humans, Population Surveillance, Mortality, Cause of Death, Models, Statistical, Caregivers, Ethiopia, South Africa, Indonesia, Vietnam, Global Health, Surveys and Questionnaires