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

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 interventions towards decreasing that difference. OBJECTIVE: To quantify the wealth inequalities in health preventive measures...

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Detalles Bibliográficos
Autores principales: Daca, Chanvo S. L., Schumann, Barbara, Arnaldo, Carlos, San Sebastian, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928807/
https://www.ncbi.nlm.nih.gov/pubmed/35290171
http://dx.doi.org/10.1080/16549716.2022.2040150
Descripción
Sumario: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 interventions 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 contribution 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 conducted 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.