Evidence map›Paper›PMID 41365626›Full record

ArticleBMJ global health2025

Contribution and influence of social capital on corruption in the health sector: a view through the lens of service users.

Chinelo Esther Obi, Iheomimichineke Ojiakor, Chukwudi Nwokolo, Muktar Gadanya, Martin McKee, Blake Angell, Dina Balabanova, Obinna Onwujekwe

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Chinelo Esther ObiHealth Policy Research Group, University of Nigeria, Enugu, Nigeria chineloestherobi@gmail.com.ORCID 0000-0003-0186-8496
Iheomimichineke OjiakorHealth Policy Research Group, University of Nigeria, Enugu, Nigeria.
Chukwudi NwokoloHealth Policy Research Group, University of Nigeria, Enugu, Nigeria.
Muktar GadanyaDepartment of Community Medicine, Bayero University Kano, Kano, Nigeria.
Martin McKeeHealth Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-0121-9683
Blake AngellThe George Institute for Global Health, Newtown, New South Wales, Australia.ORCID 0000-0002-7188-7740
Dina BalabanovaGlobal Health and Development, LSHTM, London, UK.ORCID 0000-0001-7163-3428
Obinna OnwujekweHealth Policy Research Group, University of Nigeria, Enugu, Nigeria.

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundThe interplay between social capital and health system corruption in healthcare systems is underexplored, yet vital, a major barrier to advancing universal health coverage is underexplored. While social capital can support anticorruption by enabling collective action, it may also perpetuate corruption when networks are used to bypass procedures or access care unfairly. This study explores how social capital contributes to corrupt practices complex relationships play out in practice in Nigerian health facilities.

methodWe conducted a cross-sectional study across two Nigerian states, surveying 1659 households using a pretested interviewer-administered questionnaire. A composite measure of social capital was developed from key variables. We examined the relationship between social capital and engagement in corrupt practices, controlling for variables such as gender, age, education and group memberships. Data were analysed using univariate, bivariate and multivariate methods.

resultsAmong respondents, 60.3% were female, over 90% had formal education, and 75.6% lived with their spouse. Nearly half (49.6%) had experienced corruption when accessing healthcare. Of those who used connections to receive care, 11.8% did so specifically to secure treatment. Individuals relying on family and friends (69.7%) were more likely to engage in corruption, and those using political connections always did. Non-membership in professional associations and political parties significantly reduced the likelihood of corrupt behaviour by 57% and 36%, respectively (p<0.01). Active participation in religious organisations was linked to lower corruption, while involvement in political parties, governance structures and professional bodies increased the likelihood. Higher education was associated with a 90% increased chance of engaging in corrupt practices (p<0.01).

conclusionSocial capital has both enabling and constraining effects on corruption in Nigeria's healthcare system. Understanding its context-specific nature is crucial for designing effective anti-corruption strategies in health service delivery.

Indexed as

Delivery of Health CareHealth Care SectorSocial CapitalAdultCross-Sectional StudiesFemaleHealth Services AccessibilityHumansMaleMiddle AgedNigeriaSurveys and QuestionnairesHealth services researchHealth systems

Identifiers

PMID41365626
PMCPMC12699593

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.