Spatial and multilevel analysis of unskilled birth attendance in Chad

• Published in: BMC public health Vol. 22; no. 1; pp. 1 - 1561
• Main Authors: Acquah, Evelyn, Nyarko, Samuel H, Boateng, Ebenezer N. K, Dickson, Kwamena Sekyi, Addo, Isaac Yeboah, Adzrago, David
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 16-08-2022; BioMed Central; BMC
• Subjects: Attended births; Birth; Births; Chad; Childbirth; Cohabitation; Complications and side effects; Demographic and Health Surveys (DHS); Demographics; Demography; Education; Geographic information systems; Geospatial; Health surveys; Households; Infants; Literacy; Maternal & child health; Maternal mortality; Methods; Midwifery; Mothers; Multilevel analysis; Neonates; Patient outcomes; Pregnancy; Public health; Remote sensing; Secondary education; Sociodemographics; Socioeconomic factors; Socioeconomics; Spatial analysis; Spatial analysis (Statistics); Traditional birth attendance; Unskilled birth attendance; Variables; Volunteers; Womens health; Chad
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-022-13972-6

Background Unskilled birth attendance is a major public health concern in Sub-Saharan Africa (SSA). Existing studies are hardly focused on the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad (a country in SSA), although the country has consistently been identified as having one of the highest prevalence of maternal and neonatal deaths in the world. This study aimed to analyse the socio-demographic correlates and geospatial distribution of unskilled birth attendance in Chad. Methods The study is based on the latest Demographic and Health Survey (DHS) data for Chad. A total of 10,745 women aged between 15 and 49 years were included in this study. A multilevel analysis based on logistic regression was conducted to estimate associations of respondents' socio-demographic characteristics with unskilled birth attendance. Geographic Information System (GIS) mapping tools, including Getis-Ord Gi hotspot analysis tool and geographically weighted regression (GWR) tool, were used to explore areas in Chad with a high prevalence of unskilled birth attendance. Results The findings show that unskilled birth attendance was spatially clustered in four Chad departments: Mourtcha, Dar-Tama, Assoungha, and Kimiti, with educational level, occupation, birth desire, birth order, antenatal care, and community literacy identified as the spatial predictors of unskilled birth attendance. Higher educational attainment, higher wealth status, cohabitation, lowest birth order, access to media, not desiring more births, and higher antenatal care visits were associated with lower odds of unskilled birth attendance at the individual level. On the other hand, low community literacy level was associated with higher odds of unskilled birth attendance in Chad whereas the opposite was true for urban residency. Conclusions Unskilled birth attendance is spatially clustered in some parts of Chad, and it is associated with various disadvantaged individual and community level factors. When developing interventions for unskilled birth attendance in Chad, concerned international bodies, the Chad government, maternal health advocates, and private stakeholders should consider targeting the high-risk local areas identified in this study. Keywords: Geospatial, Unskilled birth attendance, Multilevel analysis, Chad, Traditional birth attendance, Demographic and Health Surveys (DHS), Social demography, Public health