Abstract
OBJECTIVE: In this scoping review, we aim to consolidate the evidence on inequalities in service coverage in Africa using a comprehensive set of stratifiers. These stratifiers include place of residence, race/ethnicity/culture/language, occupation, gender/sex, religion, education, socioeconomic status and social capital. Our approach provides a more holistic understanding of the different dimensions of inequality in the context of universal health coverage (UHC). DESIGN: We conducted a scoping review following the Joanna Briggs Institute Manual for Evidence Synthesis. DATA SOURCES: We searched MEDLINE, Embase, Web of Science, CINAHL, PyscINFO, Cochrane Library, Google Scholar and Global Index Medicus for articles published between 1 January 2005 and 29 August 2022 examining inequalities in utilisation of health services for reproductive, maternal, newborn and child health (RMNCH), infectious or non-communicable diseases in Africa. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We included any empirical research that assessed inequalities in relation to services for RMNCH (eg, family planning), infectious diseases (eg, tuberculosis treatment) and non-communicable diseases (eg, cervical cancer screening) in Africa. DATA EXTRACTION AND SYNTHESIS: The data abstraction process followed a stepwise approach. A pilot-tested form capturing study setting, inequality assessment and service coverage indicators was developed and finalised. Data were extracted by one reviewer and cross-checked by another, with discrepancies resolved through consensus meetings. If a consensus was not reached, senior reviewers made the final decision. We used a narrative approach to describe the study characteristics and mapped findings against PROGRESS-Plus stratifiers and health service indicators. Quantitative findings were categorised as 'proequity', 'antiequity' or 'equal' based on service utilisation across social groups. RESULTS: We included 178 studies in our review, most studies published within the last 5 years (61.1%). Most studies assessed inequality using socioeconomic status (70.6%), followed by age (62.4%), education (60.7%) and place of residence (59.0%). Few studies focused on disability, social capital and ethnicity/race and intersectionality of stratifiers. Most studies were on RMNCH services (53.4%) and infectious disease services (43.3%). Few studies were qualitative or behavioural analyses. Results highlight significant inequalities across different equity stratifiers and services with inconsistent trends of inequalities over time after the implementation of strategies to increase demand of services and strengthen health systems. CONCLUSION: There is a need to examine equity in service coverage for a variety of health conditions among various populations beyond the traditional classification of social groups. This also requires using diverse research methods identifying disparities in service use and various barriers to care. By addressing these knowledge gaps, future research and health system reforms can support countries in moving closer to achievement of UHC targets.