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      Effect of corruption on perceived difficulties in healthcare access in sub-Saharan Africa

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          Abstract

          Background

          Achieving Universal Health Coverage (UHC) by improving financial protection and effective service coverage is target 3.8 of the Sustainable Development Goals. Little is known, however, about the extent to which paying bribes within healthcare acts as a financial barrier to access and, thus, UHC.

          Methods

          Using survey data in adults from 32 sub-Saharan African countries in 2014–2015, we constructed a multilevel model to evaluate the relationship between paying bribes and reported difficulties of obtaining medical care. We controlled for individual-, region-, and country-level variables.

          Results

          Having paid bribes for medical care significantly increased the odds of reporting difficulties in obtaining care by 4.11 (CI: 3.70–4.57) compared to those who never paid bribes, and more than doubled for those who paid bribes often (OR = 9.52; 95% CI: 7.77–11.67). Respondents with higher levels of education and more lived poverty also had increased odds. Those who lived in rural areas or within walking distance to a health clinic had reduced odds of reporting difficulties. Sex, age, living in a capital region, healthcare expenditures per capita, and country Corruption Perception Index were not significant predictors.

          Conclusions

          We found that bribery in healthcare is a significant barrier to healthcare access, negatively affecting the potential of African countries to make progress toward UHC. Future increases in health expenditures—which are needed in many countries to achieve UHC—should be accompanied by greater efforts to fight corruption in order to avoid wasting money. Measuring and tracking health sector-specific corruption is critical for progress toward UHC.

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          Most cited references20

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          Public trust in physicians--U.S. medicine in international perspective.

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            How's Your Government? International Evidence Linking Good Government and Well-Being

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              Inequalities in maternal health care utilization in Benin: a population based cross-sectional study

              Background Ensuring equitable access to maternal health care including antenatal, delivery, postnatal services and fertility control methods, is one of the most critical challenges for public health sector. There are significant disparities in maternal health care indicators across many geographical locations, maternal, economic, socio-demographic factors in many countries in sub-Sahara Africa. In this study, we comparatively explored the utilization level of maternal health care, and examined disparities in the determinants of major maternal health outcomes. Methods This paper used data from two rounds of Benin Demographic and Health Survey (BDHS) to examine the utilization and disparities in factors of maternal health care indicators using logistic regression models. Participants were 17,794 and 16,599 women aged between15–49 years in 2006 and 2012 respectively. Women’s characteristics were reported in percentage, mean and standard deviation. Results Mean (±SD) age of the participants was 29.0 (±9.0) in both surveys. The percentage of at least 4 ANC visits was approximately 61% without any change between the two rounds of surveys, facility based delivery was 93.5% in 2012, with 4.9% increase from 2006; postnatal care was currently 18.4% and contraceptive use was estimated below one-fifth. The results of multivariable logistic regression models showed disparities in maternal health care service utilization, including antenatal care, facility-based delivery, postnatal care and contraceptive use across selected maternal factors. The current BHDS showed age, region, religion were significantly associated with maternal health care services. Educated women, those from households of high wealth index and women currently working were more likely to utilize maternal health care services, compared to women with no formal education, from poorest households or not currently employed. Women who watch television (TV) were 1.31 (OR = 1.31; 95% CI = 1.13–1.52), 1.69 (OR = 1.69; 95% CI = 1.20–2.37) and 1.38 (OR = 1.38; 95% CI = 1.16–1.65) times as likely to utilize maternal health care services after adjusting for other covariates. Conclusion The findings would guide stakeholders to address inequalities in maternal health care services. More so, health care programmes and policies should be strengthened to enhance accessibility as well as improve the utilization of maternal care services, especially for the disadvantaged, uneducated and those who live in hard-to-reach rural areas in Benin. The Benin government needs to create strategies that cover both the supply and demand side factors at attain the universal health coverage.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                21 August 2019
                2019
                : 14
                : 8
                : e0220583
                Affiliations
                [001]Technische Universität Berlin, Department of Health Care Management, Berlin, Germany
                Syracuse University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-2295-0886
                Article
                PONE-D-19-09407
                10.1371/journal.pone.0220583
                6703670
                31433821
                41c700ce-11d3-4142-acc5-87df60c0c338
                © 2019 Hsiao et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 2 April 2019
                : 18 July 2019
                Page count
                Figures: 1, Tables: 2, Pages: 12
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Social Sciences
                Economics
                Health Economics
                Medicine and Health Sciences
                Health Care
                Health Economics
                Social Sciences
                Economics
                Finance
                Medicine and Health Sciences
                Health Care
                Socioeconomic Aspects of Health
                Medicine and Health Sciences
                Public and Occupational Health
                Socioeconomic Aspects of Health
                People and Places
                Geographical Locations
                Africa
                Social Sciences
                Sociology
                Education
                Schools
                Medicine and Health Sciences
                Public and Occupational Health
                Global Health
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Sciences
                Sociology
                Social Networks
                Earth Sciences
                Geography
                Geographic Areas
                Rural Areas
                Custom metadata
                All data files are available from the Afrobarometer database ( http://www.afrobarometer.org/data/merged-data).

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                Uncategorized

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