Measurement and analysis of inequality of opportunity in access of maternal and child health care in Togo

Abstract

BackgroundAccess to maternal and child health care in low- and middle-income countries such as Togo is characterized by significant inequalities. Most studies in the Togolese context have examined the total inequality of health and the determinants of individuals’ health. Few empirical studies in Togo have focused on inequalities of opportunity in maternal and child health. To fill this gap, we estimated changes in inequality of opportunity in access to maternal and child health services between 1998 and 2013 using data from Togo Demographic and Health Surveys (DHS).MethodWe computed the Human Opportunity Index (HOI)—a measure of how individual, household, and geographic characteristics like sex and place of residence can affect individuals’ access to services or goods that should be universal—using five indicators of access to healthcare and one composite indicator of access to adequate care for children. The five indicators of access were: birth in a public or private health facility; whether the child had received any vaccinations; access to prenatal care; prenatal care given by qualified staff; and having at least four antenatal visits. We then examined differences across the two years.ResultsBetween 1998 and 2013, inequality of opportunities decreased for four out of six indicators. However, inequalities increased in access to antenatal care provided by qualified staff (5.9% to 12.5%) and access to adequate care (27.7% to 28.6%).ConclusionsAlthough inequality of opportunities reduced between 1998 and 2013 for some of the key maternal and child health indicators, the average coverage and access rates underscore the need for sustained efforts to ensure equitable access to primary health care for mothers and children.

Inequalities in sub-Saharan African women’s and girls’ health opportunities and outcomes: evidence from the Demographic and Health Surveys

“…When analysing household survey data with multiple circumstances, and categories within, the formula in (3) cannot be applied directly because of limited number of observations within each circumstance group, with some of the circumstance groups even being a null set in some cases. Instead, an econometric procedure is used to obtain an estimate of D (and thus H ) [9,13]. Coverage rates in the formula (3) are substituted by probabilities.…”

“…More details on the estimation and properties of the HOI and the D-index are available elsewhere [6,7,13].…”

“…The current study aims to go one step further: to consider all such characteristics simultaneously to see the magnitude and sources of inequality for different indicators of access to health opportunities and outcomes, and thus identify which circumstances are associated with the highest inequalities in SSA. This method has only been used once with maternal and reproductive health indicators in a peer-reviewed publication [13]. The consistent method applied to the analysis in multiple countries, using similar sources of data, also allows for aggregation across countries.…”

Vaccine Equity in Low and Middle Income Countries: A Systematic Review and Meta-analysis

“…Negligible or contrasting differences between urban and rural settings were noted in Cambodia, Indonesia, and South Africa with general geographic heterogeneity suggested in Afghanistan, Mozambique, Nepal, and Togo [77, 41, 78, 79, 80, 81, 38, 82, 83, 84, 85, 86, 87, 88, 89]. Dropout of vaccination driven by transport costs and access was highlighted in South Africa and Uganda, despite mitigation through outreach activities [90, 91].…”

“…Parental education further contributed to socioeconomic heterogeneity in immunisation coverage globally, with increasing parental education contributing to improved coverage outcomes in Burkina Faso, Cambodia, China, Ethiopia, Gambia, Ghana, India, Indonesia, Kenya, Laos, Madagascar, Malawi, Namibia, Nepal, Nigeria, Pakistan, Tanzania, and Togo. While general trends for increasing vaccination coverage in children was observed with increased parental education attainment in Burkina Faso, Gambia, Kenya, Laos, Madagascar, Namibia, Pakistan, Tanzania, and Togo, [42, 28, 74, 75, 76, 105, 66, 82, 104, 89], some countries observed additional differences in coverage by vaccine. In Cambodia, differences in education level resulted in differences in DTP3 coverage, while in Ethiopia and Indonesia, uptake in measles immunisation varied by educational status [41, 55, 56, 54, 78, 79].…”