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Approaches for measuring socioeconomic status in health studies in Sub-Saharan Africa: a scoping review

Yopa, D. S.; Kiki, G. M.; Ngangue, P.; Ngoufack, M. N.; Lekelem Dongmo, G. P.; Mbang Massom, D.; Amvella Priscillia, A.; Bongwong Tamfon, B.; Chichom-Mefire, A.; Juillard, C.; Hubbard, A.; Nguefack-Tsague, G.

2025-01-02 public and global health
10.1101/2025.01.01.25319868 medRxiv
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BackgroundSocioeconomic status (SES) is essential for determining a person or communitys position about certain social and economic characteristics. This is particularly important in sub-Saharan Africa, where health disparities are pronounced. We conducted a scoping review to explore approaches used in health studies to measure socio-economic status in the sub-Saharan region. MethodsA comprehensive literature search covering January 2012 to June 2024 was conducted in five databases: PubMed, EMBASE, CIHNAL, Web of Science, and African Index Medicus. All studies in sub-Saharan Africa focused on health-related socioeconomic status were included, regardless of study methodology. Three peer reviewers independently evaluated the selected articles according to inclusion and exclusion criteria. Discrepancies between reviewers were resolved through a consensus meeting. The review protocol was registered on the Open Science Framework (OSF, OSF.IO/7NGX3). ResultsThe initial search yielded 19,669 articles. At the end of the screening process, 65 articles were analysed. Cross-sectional studies have been widely used. South Africa (13.4%) and Kenya (11%) were the most represented countries. Maternal, neonatal, and infant/juvenile health was the most covered theme (31%). The review identified 12 categories of SES measurement methods, with the asset-based wealth index being the most widespread (61.9%). Principal component analysis (PCA) is the primary analytical method used to calculate this index (57.7%). ConclusionsThis scoping review identified the asset-based wealth index as the most frequently used and provided essential elements for pooling different SES calculation methodologies to reach a consensus. Using SES to improve interventions is important to limit African health disparities.

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