Background: Maternal mortality remains high in sub-Saharan African countries, including Guinea. Skilled birth attendance (SBA) is one of the crucial interventions to avert preventable obstetric complications and related maternal deaths. However, within-country inequalities prevent a large proportion of women from receiving skilled birth attendance. Scarcity of evidence related to this exists in Guinea. Hence, this study investigated the magnitude and trends in socioeconomic and geographic-related inequalities in SBA in Guinea from 1999 to 2016 and neonatal mortality rate (NMR) between 1999 and 2012.
Methods: We derived data from three Guinea Demographic and Health Surveys (1999, 2005 and 2012) and one Guinea Multiple Indicator Cluster Survey (2016). For analysis, we used the 2019 updated WHO Health Equity Assessment Toolkit (HEAT). We analyzed inequalities in SBA and NMR using Population Attributable Risk (PAR), Population Attributable Fraction (PAF), Difference (D) and Ratio (R). These summary measures were computed for four equity stratifiers: wealth, education, place of residence and subnational region. We computed 95% Uncertainty Intervals (UI) for each point estimate to show whether or not observed SBA inequalities and NMR are statistically significant and whether or not disparities changed significantly over time.
Results: A total of 14,402 for SBA and 39,348 participants for NMR were involved. Profound socioeconomic- and geographic-related inequalities in SBA were found favoring the rich (PAR = 33.27; 95% UI: 29.85-36.68), educated (PAR = 48.38; 95% UI: 46.49-50.28), urban residents (D = 47.03; 95% UI: 42.33-51.72) and regions such as Conakry (R = 3.16; 95% UI: 2.31-4.00). Moreover, wealth-driven (PAF = -21.4; 95% UI: -26.1, -16.7), education-related (PAR = -16.7; 95% UI: -19.2, -14.3), urban-rural (PAF = -11.3; 95% UI: -14.8, -7.9), subnational region (R = 2.0, 95% UI: 1.2, 2.9) and sex-based (D = 12.1, 95% UI; 3.2, 20.9) inequalities in NMR were observed between 1999 and 2012. Though the pattern of inequality in SBA varied based on summary measures, both socioeconomic and geographic-related inequalities decreased over time.
Conclusions: Disproportionate inequalities in SBA and NMR exist among disadvantaged women such as the poor, uneducated, rural residents, and women from regions like Mamou region. Hence, empowering women through education and economic resources, as well as prioritizing SBA for these disadvantaged groups could be key steps toward ensuring equitable SBA, reduction of NMR and advancing the health equity agenda of "no one left behind."
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http://dx.doi.org/10.1186/s12884-021-04370-8 | DOI Listing |
Int J Equity Health
May 2024
Center for Health Systems Research, National Institute of Public Health of Mexico, Universidad Av. 655, Cuernavaca, Morelos, Mexico.
Background: Despite the resources and personnel mobilized in Latin America and the Caribbean to reduce the maternal mortality ratio (MMR, maternal deaths per 100 000 live births) in women aged 10-54 years by 75% between 2000 and 2015, the region failed to meet the Millenium Development Goals (MDGs) due to persistent barriers to access quality reproductive, maternal, and neonatal health services.
Methods: Using 1990-2019 data from the Global Burden of Disease project, we carried out a two-stepwise analysis to (a) identify the differences in the MMR temporal patterns and (b) assess its relationship with selected indicators: government health expenditure (GHE), the GHE as percentage of gross domestic product (GDP), the availability of human resources for health (HRH), the coverage of effective interventions to reduce maternal mortality, and the level of economic development of each country.
Findings: In the descriptive analysis, we observed a heterogeneous overall reduction of MMR in the region between 1990 and 2019 and heterogeneous overall increases in the GHE, GHE/GDP, and HRH availability.
BMC Med
January 2024
Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.
Background: Aggregate trends can be useful for summarizing large amounts of information, but this can obscure important distributional aspects. Some population subgroups can be worse off even as averages climb, for example. Distributional information can identify health inequalities, which is essential to understanding their drivers and possible remedies.
View Article and Find Full Text PDFMidwifery
December 2023
Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b).
Introduction: Utilisation of maternal healthcare is low, and it consistently decreases across antenatal to postnatal period in Bangladesh. However, there is paucity of knowledge in Bangladesh to understand gaps and associated factors in seeking continuum of maternal healthcare along the pathway. Therefore, we aimed to assess the trend in socioeconomic and demographic factors and wealth inequity in maternal CoC using the Bangladesh Multiple Indicator Cluster Survey (MICS).
View Article and Find Full Text PDFBMC Health Serv Res
July 2023
School of Economics, College of Business and Management Sciences, Makerere University, Kampala, Uganda.
Background: Maternal and neonatal mortality in Uganda remain persistently high. While utilisation of maternal health services has been shown to reduce the risk of maternal death, little is known about the inequalities in utilisation of maternal health services in Uganda. This study examined the inequalities in utilisation of maternal health services between 2006 and 2016 to draw implications for achieving universal health coverage.
View Article and Find Full Text PDFPLOS Glob Public Health
June 2023
Department of Obstetrics and Gynecology, The University of Dodoma, Dodoma, Tanzania.
Limited scientific, evidence has so far described the interactions between socioeconomic factors and the gap of inequalities in maternal healthcare utilization. This study assessed the interaction between wealth status and education to identify women with greater disadvantage. This analysis used secondary data from the three most recent rounds (2004, 2010, and 2016) of the Tanzania Demographic Health Survey (TDHS).
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