Health Inequality Monitoring: A Practical Application of Population Health Monitoring

Hosseinpoor, Ahmad Reza; Bergen, Nicole

doi:10.1007/978-3-319-76562-4_8

Cited by 9 publications

(11 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our findings echo prior work on how national averages can mask health inequities,46 and how large inequities in child health outcomes and access can persist even in the context of increasing national coverage 43 47. Prior research has also demonstrated how absolute health inequities increase in the short term and how by the time coverage improves among the most deprived groups, coverage among the most privileged groups is already close to 100% 48.…”

Section: Discussionsupporting

confidence: 84%

“…Our findings make visible, and quantify, the large wealth and urban/rural inequities which most countries, even those that have improved birth registration, must tackle. These findings contribute to: critical scholarship on who is excluded from definitions and counts of a population59; the growing literature on the importance of studying changes in health inequities over time60–63 and to research arguing for the importance of public health data systems which allow health equity to be monitored to guide the development of equity-oriented policies, programme and practices 46 64–66. More specifically, our findings support current research and policy calling attention to the need to improve CRVS systems which remain underfunded, underprioritised and underdeveloped in many countries,3–5 have made modest progress,5 21 and continue to exclude marginalised populations 11.…”

Section: Discussionsupporting

confidence: 69%

See 1 more Smart Citation

Are inequities decreasing? Birth registration for children under five in low-income and middle-income countries, 1999–2016

et al. 2019

View full text Add to dashboard Cite

IntroductionAlthough global birth registration coverage has improved from 58% to 71% among children under five globally, inequities in birth registration coverage by wealth, urban/rural location, maternal education and access to a health facility persist. Few studies examine whether inequities in birth registration in low-income and middle-income countries have changed over time.MethodsWe combined information on caregiver reported birth registration of 1.6 million children in 173 publicly available, nationally representative Demographic Health Surveys and Multiple Indicator Cluster Surveys across 67 low-income and middle-income countries between 1999 and 2016. For each survey, we calculated point estimates and 95% CIs for the percentage of children under 5 years without birth registration on average and stratified by sex, urban/rural location and wealth. For each sociodemographic variable, we estimated absolute measures of inequality. We then examined changes in non-registration and inequities between surveys, and annually.Results14 out of 67 countries had achieved complete birth registration. Among the remaining 53 countries, 39 countries successfully decreased the percentage of children without birth registration. However, this reduction occurred alongside statistically significant increases in wealth inequities in 9 countries and statistically significant decreases in 10 countries. At the most recent survey, the percentage of children without birth registration was greater than 50% in 16 out of 67 countries.ConclusionAlthough birth registration improved on average, progress in reducing wealth inequities has been limited. Findings highlight the importance of monitoring changes in inequities to improve birth registration, to monitor Sustainable Development Goal 16.9 and to strengthen Civil Registration and Vital Statistics systems.

show abstract

Section: Discussionsupporting

confidence: 84%

Section: Discussionsupporting

confidence: 69%

Are inequities decreasing? Birth registration for children under five in low-income and middle-income countries, 1999–2016

et al. 2019

View full text Add to dashboard Cite

show abstract

“…First, to characterise economic inequality in nutrition outcomes, we included evidence using any study design that reported a CC or CIX. 3 CC and CIX were chosen based on an initial scoping search and dissertation by author (RA) 5 that determined these to be the most common metric to capture inequality across the full wealth distribution. As mentioned, CCs plot the cumulative proportion of a health outcome in a population against the cumulative proportion of the population ranked in ascending order of economic status.…”

Section: Methodsmentioning

confidence: 99%

“…A growing but disparate literature has sought to characterise economic inequalities in malnutrition in different countries, using metrics from economics: concentration curves (CCs) and concentration indices (CIXs). 3–5 CCs plot the cumulative proportion of a health outcome in a population against the cumulative proportion of the population ranked in ascending order of economic status, and CIX are twice the area between the CC and line of equality (the 45° line from the origin). Rather than simply compare the richest against the poorest, CC and CIX capture the inequality across the full study population, and CC also visualise where the biggest health burdens lie.…”

Section: Introductionmentioning

confidence: 99%

Economic inequality in malnutrition: a global systematic review and meta-analysis

et al. 2021

View full text Add to dashboard Cite

ObjectiveTo describe the evidence on global and regional economic inequality in malnutrition, and the associations between economic inequality and malnutrition.MethodsWe conducted a systematic review and meta-analysis. Between 1 November 2020 and 22 January 2021, we searched Medline, Embase, Global Health, Eldis, Web of Science and EBSCO Discovery Service. We contacted 39 experts and tracked citations. We included any study reporting a concentration index (CIX) relating economic status and nutritional status and any multilevel study reporting an association between economic inequality and nutritional status. Nutritional status was measured as stunting, wasting, anaemia, or overweight in children (<5 years), or underweight, overweight or obesity, or anaemia in adults (15–49 years). We had no study date or language restriction. Quality was assessed using the Appraisal Tool for Cross-Sectional Studies (AXIS tool). We mapped estimates and pooled them using multilevel random-effects meta-analyses.ResultsFrom 6185 results, 91 studies provided 426 CIX (>2.9 million people) and 47 associations (~3.9 million people). Stunting (CIX −0.15 (95% CI −0.19 to −0.11)) and wasting (−0.03 (95% CI −0.05 to −0.02)) are concentrated among poor households. Adult overweight and obesity is concentrated in wealthier households (0.08 (95% CI −0.00 to 0.17)), particularly in South Asia (0.26 (95% CI 0.19 to 0.34)), but not in Europe and Central Asia (−0.02 (95% CI −0.08 to 0.05)) or North America (−0.04 (95% CI −0.10 to 0.03)). We found no association between 0.1 increase in Gini coefficient and adult underweight (OR 1.03 (95% CI 0.94 to 1.12)) or overweight and obesity (0.92 (95% CI 0.80 to 1.05)).ConclusionsThere is good evidence that the prevalence of malnutrition varies by levels of absolute economic status. Undernutrition is concentrated in poor households, whereas concentration of overweight and obesity by economic status depends on region, and we lack information on economic inequalities in anaemia and child overweight. In contrast, links between malnutrition and relative economic status are less clear and should not be assumed; robust evidence on causal pathways is needed.PROSPERO registration numberCRD42020201572.

show abstract

“…7 National health inequality monitoring, an application of population health monitoring that tracks the performance of disadvantaged population subgroups over time with respect to a specified health indicator, is essential across all country contexts to measure the progressive realization of UHC and guide equity-oriented policy-making. 22,23 The broader convergence agenda of the SDGs, including promoting UHC in all countries, may one day create opportunities for developing cross-country best practices, especially as LMICs make variable progress towards UHC and some HICs risk backsliding. However, currently the specifics of monitoring – the selection of relevant health indicators, dimensions of inequality, data sources, and analysis and reporting approaches – are often different in HICs than LMICs.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Frameworks for Universal Health Coverage: What About High-Income Countries?

Bergen

Rückert

Labonté

2019

Int J Health Policy Manag

Self Cite

View full text Add to dashboard Cite

Implementing universal health coverage (UHC) is widely perceived to be central to achieving the Sustainable Development Goals (SDGs), and is a work program priority of the World Health Organization (WHO). Much has already been written about how low- and middle-income countries (LMICs) can monitor progress towards UHC, with various UHC monitoring frameworks available in the literature. However, we suggest that these frameworks are largely irrelevant in high-income contexts and that the international community still needs to develop UHC monitoring framework meaningful for high-income countries (HICs). As a first step, this short communication presents preliminary findings from a literature review and document analysis on how various countries monitor their own progress towards achieving UHC. It furthermore offers considerations to guide meaningful UHC monitoring and reflects on pertinent challenges and tensions to inform future research on UHC implementation in HIC settings.

show abstract

Health Inequality Monitoring: A Practical Application of Population Health Monitoring

Cited by 9 publications

References 15 publications

Are inequities decreasing? Birth registration for children under five in low-income and middle-income countries, 1999–2016

Are inequities decreasing? Birth registration for children under five in low-income and middle-income countries, 1999–2016

Economic inequality in malnutrition: a global systematic review and meta-analysis

Monitoring Frameworks for Universal Health Coverage: What About High-Income Countries?

Contact Info

Product

Resources

About