Change search
ReferencesLink to record
Permanent link

Direct link
Record-linkage comparison of verbal autopsy and routine civil registration death certification in rural north-east South Africa: 2006-09
Show others and affiliations
2014 (English)In: International Journal of Epidemiology, ISSN 0300-5771, E-ISSN 1464-3685, Vol. 43, no 6, 1945-1958 p.Article in journal (Refereed) Published
Abstract [en]

Background: South African civil registration (CR) provides a key data source for local health decision making, and informs the levels and causes of mortality in data-lacking sub-Saharan African countries. We linked mortality data from CR and the Agincourt Health and Socio-demographic Surveillance System (Agincourt HDSS) to examine the quality of rural CR data. Methods: Deterministic and probabilistic techniques were used to link death data from 2006 to 2009. Causes of death were aggregated into the WHO Mortality Tabulation List 1 and a locally relevant short list of 15 causes. The matching rate was compared with informant-reported death registration. Using the VA diagnoses as reference, misclassification patterns, sensitivity, positive predictive values and cause-specific mortality fractions (CSMFs) were calculated for the short list. Results: A matching rate of 61% [95% confidence interval (CI): 59.2 to 62.3] was attained, lower than the informant-reported registration rate of 85% (CI: 83.4 to 85.8). For the 2264 matched cases, cause agreement was 15% (kappa 0.1083, CI: 0.0995 to 0.1171) for the WHO list, and 23% (kappa 0.1631, CI: 0.1511 to 0.1751) for the short list. CSMFs were significantly different for all but four (tuberculosis, cerebrovascular disease, other heart disease, and ill-defined natural) of the 15 causes evaluated. Conclusion: Despite data limitations, it is feasible to link official CR and HDSS verbal autopsy data. Data linkage proved a promising method to provide empirical evidence about the quality and utility of rural CR mortality data. Agreement of individual causes of death was low but, at the population level, careful interpretation of the CR data can assist health prioritization and planning.

Place, publisher, year, edition, pages
Oxford University Press, 2014. Vol. 43, no 6, 1945-1958 p.
Keyword [en]
mortality, data quality, causes of death, vital statistics, verbal autopsy, data linkage, Agincourt Health and Demographic Surveillance System, Statistics South Africa, rural South Africa
National Category
Public Health, Global Health, Social Medicine and Epidemiology Environmental Health and Occupational Health
URN: urn:nbn:se:umu:diva-100302DOI: 10.1093/ije/dyu156ISI: 000348575500036PubMedID: 25146564OAI: diva2:792229
Available from: 2015-03-03 Created: 2015-02-27 Last updated: 2015-03-03Bibliographically approved

Open Access in DiVA

fulltext(1142 kB)75 downloads
File information
File name FULLTEXT01.pdfFile size 1142 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Kahn, KathleenMee, PaulTollman, Stephen M
By organisation
Epidemiology and Global Health
In the same journal
International Journal of Epidemiology
Public Health, Global Health, Social Medicine and EpidemiologyEnvironmental Health and Occupational Health

Search outside of DiVA

GoogleGoogle Scholar
Total: 75 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 54 hits
ReferencesLink to record
Permanent link

Direct link