Key findings
1.3 Inequalities between countries
1.3.2 Inequalities within countries
Inequalities in service coverage also persist within countries, as different population sub-groups experience differential coverage of essential health services. Measuring and monitoring within- country inequalities is vital to identify populations that are left behind and inform equity-oriented interventions that can close existing gaps. However, a major challenge to monitoring inequalities in the UHC SCI is the limited availability of disaggregated data, which is data broken down by characteristics such as age, sex and economic status. While some of the indicators comprising the index cannot be disaggregated, such as International Health Regulations (IHR) or hospital bed density, for others where it is possible, data are not collected systematically or at all. Nevertheless, inequalities across population sub-groups can be examined for a subset of low-income countries (LICs) and lower-middle-income countries (LMICs) using a composite coverage index of RMNCH services derived from household survey data. As shown in Box 1.4, large inequalities persist, with higher service coverage observed among those living in richer households and urban areas, as well as those with more education.
6 DTP3, three doses of the combined diphtheria, tetanus toxoid and pertussis vaccine.
Monitoring Sustainable Development Goal 3.8.1: coverage of essential health services 13
Box 1.4. Inequalities in reproductive, maternal, newborn, and child service coverage
The RMNCH composite coverage index (14) is calculated as the weighted average of eight indicators in four stages along the continuum of care: reproductive health (demand for family planning satisfied with modern methods); maternal health (antenatal care coverage with at least one visit and skilled attendance at birth);
child immunization (BCG, measles and DTP3 immunization coverage); and management of childhood illnesses (oral rehydration therapy for diarrhoea and care seeking for suspected pneumonia) (15). This index derived from household survey data should not be compared with the RMNCH component of the UHC SCI as it summarizes the level of coverage across a larger spectrum of RMNCH interventions and is based on primary data from demographic and health surveys (DHS) or multiple indicator cluster surveys (MICS). Figure 1.11 below shows coverage by household economic status, education, and place of residence.
These results indicate large inequalities favouring those living in richer households (median coverage of 73% among the richest quintile compared to 58% among the poorest quintile across 88 countries), having more education (median coverage of 71% among those with secondary or higher education compared to 56% among those with no education across 78 countries), and living in urban areas (median coverage of 70% in urban areas compared to 63% in rural areas across 89 countries).
Fig. 1.11. RMNCH composite coverage index by multiple dimensions of inequality, 2011–2020
0 10 20 30 40 50 60 70 80 90 100
Coverage (%) 62.958.2
66.2 69.5 73.0
56.2
62.7
70.7
63.0
70.2 Quintile 1
(poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5
(richest) No education Primary
education Secondary Rural Urban or higher
education
Place of residence (89 countries) Education
(78 countries) Economic status
(88 countries)
Notes: Circles indicate countries – each country is represented by multiple circles (one for each subgroup). Horizontal black lines indicate the median value (middle point of estimates). This analysis used DHS, MICS, and reproductive health survey (RHS) data and was conducted by the WHO Collaborating Centre for Health Equity Monitoring (International Center for Equity in Health, Federal University of Pelotas.)
Source: WHO Health Inequality Data Repository (14).
The potential impact of eliminating economic-related inequalities on RMNCH service coverage is substantial. The most recent household survey data from DHS, MICS, and reproductive health surveys (RHS) between 2011 and 2020 for 88 LICs and LMICs were used to calculate the current national average of the RMNCH composite coverage index by household economic status (wealth quintiles) (see Fig. 1.12). The potential for improvement in each country was then determined by increasing the coverage in each wealth quintile to that of the highest wealth quintile. This yielded the potential national average that could be achieved if economic-related inequality were to be eliminated.
Monitoring Sustainable Development Goal 3.8.1: coverage of essential health services 14 Tracking universal health coverage 2023 global monitoring report
According to the most recent household survey data, only eight of 88 countries had RMNCH composite coverage index scores of 80% or more, while coverage was between 60% to 79% in 55 countries, between 40% and 59% in 23 countries, and below 40% in one country. After considering the potential improvement in national average by eliminating economic-related inequality, 14 additional countries would have coverage above 80%, 20 additional countries would have coverage between 60% and 79%, and two additional countries would have coverage between 40% and 59%. This accounts for the movement of 40% of countries (36 out of 88 countries) into the next highest category and demonstrates the importance of eliminating within-country inequality in service coverage to increase national coverage.
Within-country inequalities in UHC service coverage should be monitored across multiple dimensions of inequality, including household economic status, education and place of residence, as illustrated above. Sub-national analyses provide additional information regarding the progress on the pathway to UHC as well as insights for the design and implementation of health policies and programmes.
Advances in small area estimation (SAE) methods can be used with household survey data to produce estimates for smaller sub-groups by utilizing spatial correlation between data points. Figure 1.13 shows the results from an SAE analysis of average RMNCH service coverage7 (panel a) and antenatal care (4+ visits) (ANC4+) coverage (panel b) for sub-national administrative units from the most recent household surveys since 2010 in sub-Saharan Africa. Striking patterns of inequalities both within countries and across all administrative units were observed. There were substantial variations in RMNCH service coverage across all administrative units included in the analysis (range 10–79%), and a median of 59%. There were wide variations in coverage across all administrative units when only
7 RMNCH average coverage was derived using the most recent DHS household survey data (16), available for each country between 2010 and 2021. The average coverage was calculated as the geometric mean of estimated coverage for the four indicators related to RMNCH: ANC4+, DTP3, family planning needs satisfied with modern methods, and care-seeking for suspected acute respiratory infection ARI in children under five years of age)
Fig. 1.12. Potential improvement in national average by eliminating economic-related inequality in RMNCH composite coverage index
8 22
55
+14
+20
+2 23
2
61
5 Current distribution of
most recent survey- derived RMNCH coverage estimates (n of countries)
Potential improvements in distribution (n of countries)
Potential distribution of RMNCH coverage estimates (n of countries) Very high (>80%)
High (60–79%)
Medium (40%–59%)
Low (20%–39%)
Very high (>80%)
High (60–79%)
Medium (40%–59%) Low (20%–39%)
Note: This analysis used DHS, MICS, and RHS data and was conducted by the WHO Collaborating Centre for Health Equity Monitoring (International Center for Equity in Health, Federal University of Pelotas.)
Sources: WHO Health Inequality Data Repository (14).
Monitoring Sustainable Development Goal 3.8.1: coverage of essential health services 15
the ANC4+ indicator was considered, with prominent inequalities observed when administrative units were disaggregated by those containing capital cities and non-capital city units. The median ANC4+
coverage in capital city administrative units was 73% (range 48–93%), which was 20 percentage points higher than the median ANC4+ coverage in non-capital city administrative units at 53% (range 12–93%).
Fig. 1.13. Average RMNCH service coverage and ANC4+ coverage sub-national survey estimates, most recent household surveys available at two time periods, 2010–2015 and 2016–2020
a. RMNCH index sub-national survey estimates
b. ANC4+ sub-national survey estimates
Notes: These maps have been produced by WHO. The boundaries, colours or other designations or denominations used in the maps and the publication do not imply, on the part of the World Bank or WHO, any opinion or judgement on the legal status of any country, territory, city or area or of its authorities, or any endorsement or acceptance of such boundaries or frontiers.
Source: Analysis using most recent DHS concerning household survey data, 2010–2021 (16).
Monitoring Sustainable Development Goal 3.8.1: coverage of essential health services 16 Tracking universal health coverage 2023 global monitoring report