ArticleInternational journal of preventive medicine2014
Application of Capture-Recapture for Fine-tuning Uncertainties About National Maternal Mortality Estimates.
Article in International journal of preventive medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMaternal mortality ratio (MMR) is one of the main indicators of the millennium development goals and its accurate estimation is very important for the countries concerned. The objective of this study is to evaluate the applicability of capture-recapture (CRC) as an analytical method to estimate MMR in countries.
methodsWe used the CRC method to estimate MMR in Iran for 2004 and 2005, using two data sources: The maternal mortality surveillance system and the National Death Registry (NDR). Because the data registry contains errors, we defined three levels of matching criteria to enable matching of cases between the two systems. Increasing the matching level makes the matching criteria less conservative. Because NDR data were missing or incomplete for some provinces, we calculated estimates for two conditions: With and without missing/incomplete data.
resultsAccording to the CRC method, MMR in 2004 and 2005 were 33 and 25 in the best-case scenarios respectively and 86 and 59 in the worst-case scenarios respectively. These estimates are closer to the ones reported by United Nations Agencies published in 2010, 38 and Hogan's study, 30 in 100,000 live births in 2005.
conclusionsThe MMR estimation by CRC method is slightly different from the international studies. CRC can be considered as a cost-effective method, in comparison with cross-sectional studies or improvement of vital registration systems, which are both costly and difficult. However, to achieve accurate estimates of MMR with CRC method and decrease the uncertainty we need to have valid databases and the absence of such capacities will limit the applicability of this method in developing countries with poor quality health databases.
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