International Journal of Epidemiology, Vol 28, 70-76, Copyright © 1999 by International Epidemiological Association
L Hoj, J Stensballe and P Aaby
BACKGROUND: In developing countries with scanty resources it is very
important to have reliable data to establish priorities for the health
sector; e.g. to reduce maternal mortality it is necessary to determine the
most important causes. The majority of deaths, however, occur without
previous contact with the health system and consequently conventional
analyses of death certificates are not feasible. Instead, studies have been
carried out in some developing countries with various forms of post-mortem
interviews, the so-called verbal autopsies (VA). METHODS: We developed a
structured interview with filter questions, which was applied to all deaths
of women of fertile age in a cohort of 10,000 women living in 100 clusters
in Guinea-Bissau and followed over a period of 6 years. The cause of death
was ascertained by means of a series of diagnostic algorithms for the most
common causes of maternal mortality, including postpartum haemorrhage,
antepartum haemorrhage, puerperal infection, obstructed labour, eclampsia,
abortion, and ectopic pregnancy. RESULTS: Of the 350 deaths of women of
fertile age, 32% were maternal and it seems unlikely that a significant
proportion of maternal deaths have not been classified correctly. Using the
diagnostic algorithm 70% could be given a specific diagnosis, the most
important causes being postpartum haemorrhage (42% [29/69]), obstructed
labour (19% [13/69]), and puerperal infection (16% [11/69]). We attempted
to identify the factors that are critical for obtaining sufficient
information to reach a diagnosis. In the univariate analyses, it was
important whether the respondent had been present during the last illness
(P = 0.04) and whether the death occurred more than one week after delivery
(P = 0.04). The husband was a better respondent than a co-wife (P = 0.08),
and men in general provided more specific information than women (P =
0.08). Furthermore, information appeared to be better if the woman had died
in the rainy season (P = 0.08). The length of the recall period, parity,
age of woman, place of death, rural/urban residence, and ethnic group were
not decisive. In the multivariate analysis sex and presence of respondent
and time after delivery were significantly associated with the risk of not
reaching a specific diagnosis. Women are less likely to provide adequate
information for a diagnosis than men (odds ratio [OR] 3.1; 95% confidence
interval [CI]: 1.2-8.1). Respondents that did not reside in the village
during the departed woman's illness/delivery carried equal risk of not
reaching a conclusion (OR 3.1; CI: 1.1-9.1). Deaths occurring more than one
week after delivery were also less likely to be classified (OR 6.1; CI:
1.7-22.0). CONCLUSION: The VA described in the present paper left 30% of
the maternal deaths unclassified without a specific diagnosis. Had all
interviews been with husbands, only 14% would have remained unclassified.
If we had only asked people who were present during the terminal phase of
the victim's illness the proportion of classified deaths would have risen
from 70% to 75%. It is likely that delayed maternal deaths have not been
adequately covered by the present algorithms, but they may also simply be
more difficult to describe due to the duration of the disease episode. In
contrast to methods by which cause of death is established by a panel of
medical experts, the present VA should be economically and technically
viable in areas where health workers have only minimal training.
ARTICLES
Maternal mortality in Guinea-Bissau: the use of verbal autopsy in a multi-ethnic population
Projecto de Saude de Bandim, Bissau, Guinea-Bissau.
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