Levels, timing, and etiology of stillbirths in Sylhet district of Bangladesh

Abstract

Background: Lack of data is a critical barrier to addressing the problem of stillbirth in countries with the highest stillbirth burden. Our study objective was to estimate the levels, types, and causes of stillbirth in rural Sylhet district of Bangladesh.

Methods: A complete pregnancy history was taken from all women (n=39 998) who had pregnancy outcomes during 2003-2005 in the study area. Verbal autopsy data were obtained for all identified stillbirths during the period. We used pre-defined case definitions and computer programs to assign causes of stillbirth for selected causes containing specific signs and symptoms. Both non-hierarchical and hierarchical approaches were used to assign causes of stillbirths.

Results: A total of 1748 stillbirths were recorded during 2003-2005 from 48,192 births (stillbirth rate: 36.3 per 1000 total births). About 60% and 40% of stillbirths were categorized as antepartum and intrapartum, respectively. Maternal conditions, including infections, hypertensive disorders, and anemia, contributed to about 29% of total antepartum stillbirths. About 50% of intrapartum stillbirths were attributed to obstetric complications. Maternal infections and hypertensive disorders contributed to another 11% of stillbirths. A cause could not be assigned in nearly half (49%) of stillbirths.

Conclusion: The stillbirth rate is high in rural Bangladesh. Based on algorithmic approaches using verbal autopsy data, a substantial portion of stillbirths is attributable to maternal conditions and obstetric complications. Programs need to deliver community-level interventions to prevent and manage maternal complications, and to develop strategies to improve access to emergency obstetric care. Improvements in care to avert stillbirth can be accomplished in the context of existing maternal and child health programs. Methodological improvements in the measurement of stillbirths, especially causes of stillbirths, are also needed to better define the burden of stillbirths in low-resource settings.

Figure 1

Classification of stillbirths by timing and hierarchical algorithm assigning primary causes