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. 2010 Oct;15(10):1256-65.
doi: 10.1111/j.1365-3156.2010.02601.x.

Mortality measurement in transition: proof of principle for standardised multi-country comparisons

Edward Fottrell  1 , Kathleen Kahn, Nawi Ng, Benn Sartorius, Dao Lan Huong, Hoang Van Minh, Mesganaw Fantahun, Peter Byass
Affiliations
Free PMC article

Mortality measurement in transition: proof of principle for standardised multi-country comparisons

Edward Fottrell et al. Trop Med Int Health. 2010 Oct.
Free PMC article

Abstract

Summary objective: To 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.

Methods: Deaths 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.

Results: The 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.

Conclusions: Given 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.

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Figures

Figure 1
Figure 1
Age distributions of all-cause mortality from the four health and demographic surveillance sites.
Figure 2
Figure 2
Broad groups cause classifications by country based on population cause-specific mortality fractions determined by InterVA for 4784 deaths from Butajira (Ethiopia), Agincourt (South Africa), FilaBavi (Vietnam) and Purworejo (Indonesia).
Figure 3
Figure 3
Breakdown of external causes of death in Agincourt (South Africa) and FilaBavi (Vietnam).
See this image and copyright information in PMC

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