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Wealth inequalities in reproductive and child health preventive care in Mozambique: a decomposition analysis

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dc.contributor.author Daca, Chanvo S. L.
dc.contributor.author Schumann, Barbara
dc.contributor.author Arnaldo, Carlos
dc.contributor.author Sebastian, Miguel San
dc.date.accessioned 2024-05-16T07:07:46Z
dc.date.available 2024-05-16T07:07:46Z
dc.date.issued 2022
dc.identifier.citation Chanvo S. L. Daca, Barbara Schumann, Carlos Arnaldo & Miguel San Sebastian (2022) Wealth inequalities in reproductive and child health preventive care in Mozambique: a decomposition analysis, Global Health Action, 15:1, 2040150, DOI: 10.1080/16549716.2022.2040150 en_US
dc.identifier.other https://www.tandfonline.com/doi/pdf/10.1080/00036846.2023.2203457
dc.identifier.uri http://www.repositorio.uem.mz/handle258/940
dc.language.iso eng en_US
dc.publisher Taylor & Francis Group en_US
dc.relation.ispartofseries 15;2043
dc.rights openAcess en_US
dc.subject Socioeconomic inequality en_US
dc.subject Decomposition analysis en_US
dc.subject Health preventive care en_US
dc.subject Mozambique en_US
dc.title Wealth inequalities in reproductive and child health preventive care in Mozambique: a decomposition analysis en_US
dc.type article en_US
dc.description.resumo Background: Assessing the gap between rich and poor is important to monitor inequalities in health. Identifying the contribution to that gap can help policymakers to develop inter ventions towards decreasing that difference. Objective: To quantify the wealth inequalities in health preventive measures (bed net use, vaccination, and contraceptive use) to determine the demographic and socioeconomic con tribution factors to that inequality using a decomposition analysis. Methods: Data from the 2015 Immunisation, Malaria and AIDs Indicators Survey were used. The total sample included 6946 women aged 15–49 years. Outcomes were use of insecticide treated nets (ITN), child vaccination, and modern contraception use. Wealth Index was the exposure variable and age, marital status, place of residence, region, education, occupation, and household wealth index were the explanatory variables. Wealth inequalities were assessed using concentration indexes (Cindex). Wagstaff-decomposition analysis was con ducted to assess the determinants of the wealth inequality. Results: The Cindex was −0.081 for non-ITN, −0.189 for lack of vaccination coverage and −0.284 for non-contraceptive use, indicating a pro-poor inequality. The results revealed that 88.41% of wealth gap for ITN was explained by socioeconomic factors, with education and wealth playing the largest roles. Lack of full vaccination, socioeconomic factors made the largest contribution, through the wealth variable, whereas geographic factors came next. Finally, the lack of contraceptive use, socioeconomic factors were the main explanatory factors, but to a lesser degree than the other two outcomes, with wealth and education contributing most to explaining the gap. Conclusion: There was a pro-poor inequality in reproductive and child preventive measures in Mozambique. The greater part of this inequality could be attributed to wealth, education, and residence in rural areas. Resources should be channeled into poor and non-educated rural communities to tackle these persistent inequities in preventive care. en_US
dc.journal Global Health Action en_US


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