ArticleArchives of public health = Archives belges de sante publique2021
Socioeconomic, urban-rural and sex-based inequality in infant mortality rate: evidence from 2013 Yemen demographic and health survey.
Article in Archives of public health = Archives belges de sante publique, 2021. 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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Abstract
backgroundThe occurrence of Infant Mortality Rate (IMR) varied globally with most of the cases coming from developing countries including Yemen. The disparity in IMR in Yemen however, has not been well dealt and therefore we examined the IMR inequality based on the most reliable methodology in order to generate evidence-based information for some program initiatives in Yemen.
methodsBased on the World Health Organization (WHO) Health Equity Assessment Toolkit (HEAT) software, we analyzed the inequality across the different inequality dimensions in Yemen. The toolkit analyzes data stored in the WHO health equity monitor database. Simple and complex, and absolute and relative measures of inequality were calculated for the four dimensions of inequality (subpopulations) which included wealth, education, sex and residence. We computed a 95 % CI to assess statistical significance.
resultsThe analysis included 31, 743 infants. Absolute and relative wealth-driven, education, urban-rural and sex-based inequalities were found in IMR. Higher concentration of IMR was observed among infants from the poorest/poor households (ACI=-4.68, 95 % CI; -6.57, -2.79, R = 1.61, 95 % CI; 1.18, 2.03), rural residents (D = 15.07, 95 % CI; 8.04, 22.09, PAF=-23.57, 95 % CI; -25.47, -21.68), mothers who had no formal education (ACI=-2.16, 95 % CI; -3.79, -0.54) and had male infants (PAF= -3.66, 95 % CI; -4.86, -2.45).
conclusionsHigher concentration of IMR was observed among male infants from disadvantaged subpopulations such as poorest/poor, uneducated and rural residents. To eliminate the observed inequalities, interventions are needed to target the poorest/poor households, rural residents, mothers with no formal education and male infants.
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