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Original Research

Maternal mortality in rural South Africa: the impact of case definition on levels and trends

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Pages 457-463 | Published online: 06 Aug 2013
 

Abstract

Background

Uncertainty in the levels of global maternal mortality reflects data deficiencies, as well as differences in methods and definitions. This study presents levels and trends in maternal mortality in Agincourt, a rural subdistrict of South Africa, under long-term health and sociodemographic surveillance.

Methods

All deaths of women aged 15 years–49 years occurring in the study area between 1992 and 2010 were investigated, and causes of death were assessed by verbal autopsy. Two case definitions were used: “obstetrical” (direct) causes, defined as deaths caused by conditions listed under O00–O95 in International Classification of Diseases-10; and “pregnancy-related deaths”, defined as any death occurring during the maternal risk period (pregnancy, delivery, 6 weeks postpartum), irrespective of cause.

Results

The case definition had a major impact on levels and trends in maternal mortality. The obstetric mortality ratio averaged 185 per 100,000 live births over the period (60 deaths), whereas the pregnancy-related mortality ratio averaged 423 per 100,000 live births (137 deaths). Results from both calculations increased over the period, with a peak around 2006, followed by a decline coincident with the national roll-out of Prevention of Mother-to-Child Transmission of HIV and antiretroviral treatment programs. Mortality increase from direct causes was mainly due to hypertension or sepsis. Mortality increase from other causes was primarily due to the rise in deaths from HIV/AIDS and pulmonary tuberculosis.

Conclusion

These trends underline the major fluctuations induced by emerging infectious diseases in South Africa, a country undergoing rapid and complex health transitions. Findings also pose questions about the most appropriate case definition for maternal mortality and emphasize the need for a consistent definition in order to better monitor and compare trends over time and across settings.

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Acknowledgments

The Agincourt health and sociodemographic surveillance system has been funded by The Wellcome Trust, UK (Grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z), with important contributions from The William and Flora Hewlett Foundation, National Institute on Aging of the NIH, and The Andrew W Mellon Foundation, USA. The School of Public Health and Faculty of Health Sciences, University of the Witwatersrand, and the Medical Research Council, South Africa, have provided vital support. We greatly value the involvement of community leaders, study participants, and district and provincial managers in health, education, and other government sectors.

Disclosure

The authors report no conflicts of interest in this work.