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4.3 Neglected conditions in vulnerable groupsChair: Prof. Alan Fenwick, UK
O4-3.1 Distance and quality of care strongly influence choice of delivery place in rural Zambia: a study linking national data in a geographic information system
  1. S Gabrysch1,
  2. S Cousens2,
  3. J Cox2,
  4. O Campbell2
  1. 1Ruprecht-Karls-Universität, Heidelberg, Germany
  2. 2London School of Hygiene & Tropical Medicine, London, UK

Abstract

Introduction Maternal and perinatal mortality could be reduced if all women delivered in settings where skilled attendants can provide Emergency Obstetric Care (EmOC) if complications arise. Epidemiological research on determinants of skilled attendance at delivery has focused on household and individual factors, neglecting the influence of distance and quality of care, in part due to a lack of suitable data.

Methods Using a Geographic Information System (GIS), we linked national household data from the Zambian Demographic and Health Survey 2007 with national facility data from the Zambian Health Facility Census 2005 and calculated straight-line distances. Health facilities were classified by whether they provided Comprehensive EmOC, Basic EmOC, limited or substandard services. Multi-variable multilevel logistic regression analyses were performed to investigate the influence of distance to care and quality of care on place of delivery for 3682 rural births.

Results Only a third of rural Zambian births occurred at a health facility, and half were to mothers living further than 25 km from a facility of Basic EmOC standard or better. As distance to the closest health facility doubled, the odds of facility delivery decreased by 29% (95% CI 14% to 40%). Independently, each step increase in quality of care led to 26% higher odds of facility delivery (95% CI 7% to 48%).

Conclusion Lack of geographic access to quality EmOC is a key factor explaining why most rural deliveries in Zambia still occur at home without skilled care; this needs to be addressed to lower maternal and perinatal mortality. Linking datasets using Geographic Information System has great potential for future research.

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