Angela Baschieri, MSc¹, Rob Stephenson, MSc, PhD², Steve Clements, PhD¹, Monique M Hennink, BA (Hons), PhD¹, and Nyovani Madise, PHD¹. (1) Southampton Statistical Science Research Institute, University of Southampton, Highfield, Southampton, SO17 1BJ, United Kingdom, (2) Johns Hopkins Bloomberg School of Public Health, Gates Institute for Population and Reproductive Health, 615 N. Wolfe Street, Baltimore, MD 21205, 410 955 2103, rstephen@jhsph.edu

In regard to mortality maternal, few studies have investigated the use of health facilities at delivery, despite the majority of maternal deaths happening during childbirth, and the importance of understanding behaviour behind health facility use. Furthermore, there has been limited evidence as to how community contextual factors may influence variation in the choice of place of delivery. This study looks at the areal variation of health facility use at delivery in East and West Africa and aims to advance the methodology used to explain areal variation in health facility use in developing countries through combining multilevel modelling and Geographical Information System Technique. Recent Demographic and Health Survey data (DHS) have collected a global positioning system (GPS) locator for the Primary Sampling Unit (PSU) in the survey. This allows for linking of other contextual data sources to DHS data. Individual demographic, socio-economic and community level factors are considered in explaining health facility use. The importance of these factors in accounting for areal variation in use will be also assessed. The findings will be compared between the study countries and the relative importance of individual/household and contextual factors discussed, along with their relevance to policy. Furthermore, detailed maps of the modelling results and contextual data can be plotted in order to better inform researchers and local policy makers, by highlighting those areas with unusually high or low levels of health facility use at delivery.

Learning Objectives:

• 1) To quantify the determinants of health facility use at delivery in East and West Africa countries.
• 2) To identify the relative importance of these determinants in accounting for the areal variation in the place of delivery.
• 3) To identify communities of unusually high or low use of health facilities after controlling for these determinants.

Keywords: Health Service, Geographic Information Systems

Related Web page: www.socstats.soton.ac.uk/choices/Opp&Choices%20Factsheet%208.pdf

Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.