Evidence map›Paper›PMID 38954685›Full record

ArticlePLOS global public health2024

Missing the vulnerable-Inequalities in social protection in 13 sub-Saharan African countries: Analysis of population-based surveys.

David Chipanta, Silas Amo-Agyei, Lucas Hertzog, Ahmad Reza Hosseinpoor, Michael Smith, Caitlin Mahoney, Juan Gonzalo Jaramillo Meija, Olivia Keiser, Janne Estill

Abstract read
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Article in PLOS global public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

David ChipantaUnited Nations Joint Programme on HIV/AIDS (UNAIDS), Windhoek, Namibia.ORCID https://orcid.org/0000-0002-7909-6855
Silas Amo-AgyeiThe University of Manchester, Manchester, United Kingdom.ORCID https://orcid.org/0000-0001-9718-6363
Lucas HertzogFaculty of Health Sciences, WHO Collaborating Centre for Climate Change and Health Impact Assessment, School of Population Health, Curtin University, Perth, Australia.ORCID https://orcid.org/0000-0001-9881-3648
Ahmad Reza HosseinpoorDepartment of Data and Analytics, World Health Organization, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-7322-672X
Michael SmithNutrition Division, World Food Programme, Rome, Italy.
Caitlin MahoneySocial Protection Unit, World Food Programme, Rome, Italy.ORCID https://orcid.org/0009-0006-3449-5496
Juan Gonzalo Jaramillo MeijaSocial Protection Unit, World Food Programme, Rome, Italy.
Olivia KeiserInstitute of Global Health, University of Geneva, Geneva, Switzerland.
Janne EstillInstitute of Global Health, University of Geneva, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

We assessed socioeconomic inequalities in social protection coverage among the public, men and women living with the human immunodeficiency virus (MLHIV, WLHIV), and adolescent girls and young women (AGYW). We used population-based data from Cameroon, Côte d'Ivoire, Ethiopia, Eswatini, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe. We constructed concentration curves (CC) and computed concentration indices (CIX) for each country and population group. A CC represents the cumulative percentage of social protection coverage plotted on the y-axis against the cumulative proportion of the population-ranked by socioeconomic status from the poorest to the richest-on the x-axis. The CIX quantifies the concentration of social protection coverage among the poor or the rich. The sample size ranged from 10,197 in Eswatini to 29,577 in Tanzania. Social protection coverage among the public varied from 5.2% (95% Confidence Interval 4.5%-6.0%) in Ethiopia to 39.9% (37.0%-42.8%) in Eswatini. It ranged from 6.9% (5.7%-8.4%) MLHIV in Zambia to 45.0% (41.2-49.0) among WLHIV in Namibia. Among AGYW, it varied from 4.4% (3.6-5.3) in Ethiopia to 44.6% (40.8-48.5) in Eswatini. Socioeconomic inequalities in social protection coverage favored the poor in 11/13 countries surveyed. It favored the rich in Cameroon and was undefined in Côte d'Ivoire. The CIX in these 11 countries ranged from -0.080 (p = 0.002) among the public in Malawi to -0.372 (p< 0.001) among WLHIV in Zimbabwe. In 8 of these 11 countries, ≥15% of people from the poorest households reported receiving social protection. Only in countries with higher levels of social protection coverage did most people from the poorest households achieve high coverage. Social protection coverage was low and favored the poor. Pro-poor social protection is insufficient to reach the poor. Research is required to reach the poorest households with social protection in Africa.

Identifiers

PMID38954685
PMCPMC11218938

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.