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

Bhatia, Amiya; Krieger, Nancy; Beckfield, Jason; Barros, Aluísio J D; Victora, Cesar G

doi:10.1136/bmjgh-2019-001926

Cited by 21 publications

(28 citation statements)

References 44 publications

(60 reference statements)

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“…21 Birth registration was also classified in this group because it requires access to vital record facilities, often with costs incurred. 22 Community-based interventions had the least pro-rich inequalities. In many countries, these interventions are delivered by community health workers at little or no cost to families, including immunisations, case management for common diseases (malaria, diarrhoea, and pneumonia), and insecticide-treated bednets or household spraying with insecticides.…”

Section: Discussionmentioning

confidence: 99%

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Delivery channels and socioeconomic inequalities in coverage of reproductive, maternal, newborn, and child health interventions: analysis of 36 cross-sectional surveys in low-income and middle-income countries

Leventhal

Crochemore‐Silva

Vidaletti

et al. 2021

The Lancet Global Health

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Background Global reports have described inequalities in coverage of reproductive, maternal, newborn, and child health (RMNCH) interventions, but little is known about how socioeconomic inequality in intervention coverage varies across multiple low-income and middle-income countries (LMICs). We aimed to assess the association between wealth-related inequalities in coverage of RMNCH interventions. MethodsIn this cross-sectional study, we identified publicly available Demographic Health Surveys and Multiple Indicator Cluster Surveys from LMICs containing information on household characteristics, reproductive health, women's and children's health, nutrition, and mortality. We identified the most recent survey from the period 2010-19 for 36 countries that contained data for our preselected set of 18 RMNCH interventions. 21 countries also had information on two common malaria interventions. We classified interventions into four groups according to their predominant delivery channels: health facility based, community based, environmental, and culturally driven (including breastfeeding practices). Within each country, we derived wealth quintiles from information on household asset indices. We studied two summary measures of within-country wealth-related inequality: absolute inequalities (akin to coverage differences among children from wealthy and poor households) using the slope index of inequality (SII), and relative inequalities (akin to the ratio of coverage levels for wealthy and poor children) using the concentration index (CIX). Propoor inequalities are present when intervention coverage decreased with increasing household wealth, and pro-rich inequalities are present when intervention coverage increased as household wealth increased. FindingsAcross the 36 LMICs included in our analyses, coverage of most interventions had pro-rich patterns in most countries, except for two breastfeeding indicators that mostly had higher coverage among poor women, children and households than wealthy women, children, and households. Environmental interventions were the most unequal, particularly use of clean fuels, which had median levels of SII of 48•8 (8•6-85•7) and CIX of 67•0 (45•0-85•8). Interventions primarily delivered in health facilities-namely institutional childbirth (median SII 46•7 [23•1-63•3] and CIX 11•4 [4•5-23•4]) and antenatal care (median SII 26•7 [17•0-47•2] and CIX 10•0 [4•2-17•1])-also usually had pro-rich patterns. By comparison, primarily community-based interventions, including those against malaria, were more equitably distributed-eg, oral rehydration therapy (median SII 9•4 [2•9-19•0] and CIX 3•4 [1•3-25•0]) and polio immunisation (SII 12•1 [2•3-25•0] and CIX 3•1 [0•5-7•1]). Differences across the four types of delivery channels in terms of both inequality indices were significant (SII p=0•0052; CIX p=0•0048). Interpretation Interventions that are often delivered at community level are usually more equitably distributed than those primarily delivered in fixed facilities or those that require changes in t...

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Section: Discussionmentioning

confidence: 99%

“… 21 Birth registration was also classified in this group because it requires access to vital record facilities, often with costs incurred. 22 …”

Section: Discussionmentioning

confidence: 99%

Delivery channels and socioeconomic inequalities in coverage of reproductive, maternal, newborn, and child health interventions: analysis of 36 cross-sectional surveys in low-income and middle-income countries

Leventhal

Crochemore‐Silva

Vidaletti

et al. 2021

The Lancet Global Health

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“…The self-reported birth registration completeness data collected by DHS and MICS and used by UNICEF have met a number of policy needs in the over 100 countries where they have been collected, in particular to track progress towards Sustainable Development Goal 16.9 and to demonstrate socio-economic differences in registration completeness using a wealth index or other variables not readily available in published CRVS data [24][25][26]. However there are many advantages of using CRVS data; these data can measure birth registration completeness at the small area level more accurately than sample surveys and can be used to track progress and better target interventions to increase completeness in an era where efforts, such as the Bloomberg Philanthropies Data for Health Initiative, are being made to improve registration of vital events.…”

Section: Discussionmentioning

confidence: 99%

How reliable are self-reported estimates of birth registration completeness? Comparison with vital statistics systems

Adair

Lopez

2021

PLoS ONE

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Background The widely-used estimates of completeness of birth registration collected by Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) and published by UNICEF primarily rely on registration status of children as reported by respondents. However, these self-reported estimates may be inaccurate when compared with completeness as assessed from nationally-reported official birth registration statistics, for several reasons, including over-reporting of registration due to concern about penalties for non-registration. This study assesses the concordance of self-reported birth registration and certification completeness with completeness calculated from civil registration and vital statistics (CRVS) systems data for 57 countries. Methods Self-reported estimates of birth registration and certification completeness, at ages less than five years and 12–23 months, were compiled and calculated from the UNICEF birth registration database, DHS and MICS. CRVS birth registration completeness was calculated as birth registrations reported by a national authority divided by estimates of live births published in the United Nations (UN) World Population Prospects or the Global Burden of Disease (GBD) Study. Summary measures of concordance were used to compare completeness estimates. Findings Birth registration completeness (based on ages less than five years) calculated from self-reported data is higher than that estimated from CRVS data in most of the 57 countries (31 countries according to UN estimated births, average six percentage points (p.p.) higher; 43 countries according to GBD, average eight p.p. higher). For countries with CRVS completeness less than 95%, self-reported completeness was higher in 26 of 28 countries, an average 13 p.p. and median 9–10 p.p. higher. Self-reported completeness is at least 30 p.p. higher than CRVS completeness in three countries. Self-reported birth certification completeness exhibits closer concordance with CRVS completeness. Similar results are found for self-reported completeness at 12–23 months. Conclusions These findings suggest that self-reported completeness figures over-estimate completeness when compared with CRVS data, especially at lower levels of completeness, partly due to over-reporting of registration by respondents. Estimates published by UNICEF should be viewed cautiously, especially given their wide usage.

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“…It should be emphasized that the height for age z-score, in rural contexts such as Chiulo, has an important limit. Most children are not registered at birth and do not present any documents [ 18 ]. Furthermore, the date of birth is not given the importance that we are accustomed to attribute to it.…”

Section: Discussionmentioning

confidence: 99%

Analysis of risk and prognostic factors in a population of pediatric patients hospitalized for acute malnutrition at the Chiulo hospital, Angola

et al. 2021

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Background Malnutrition is a multifactorial pathology in which genetic, epigenetic, cultural, environmental, socio-economic factors interact with each other. The impact that this disease has on the health of children worldwide is dramatic. Severe acute malnutrition in particular is a disease affecting nearly 20 million preschool children worldwide, most of them in Africa and South East Asia. Objectives This work aims to investigate potential prognostic factors in the clinical evolution of acute malnutrition and potential risk factors for the development of the disease. Methods Our study was carried out at the “Hospital da Missão Catolica do Chiulo”, in Angola, where the NGO Doctors with Africa CUAMM has been operating since 2000. In the first part of the study we analyzed the characteristics and clinical evolution of 163 patients hospitalized for acute malnutrition at the UEN (Unidade Especial de Nutrição) of the Chiulo Hospital over a period of 6 months, in order to identify potential prognostic factors of the disease. The second part of our study was carried out by administering a questionnaire to a group of caregivers of malnourished children and to a group of caregivers of non-malnourished children admitted to Pediatrics for other causes, with the aim of identifying potential risk factors for the development of malnutrition. Results and conclusions The analysis of prognostic factors revealed that the most relevant are the WHZ (weight for height z-score) at the time of admission, the presence of Stunting and the presence of other pathologies or clinical conditions associated with severe acute malnutrition. The analysis of risk factors has shown that not only food shortages, but also errors in the timing of the suspension of breastfeeding and the timing of the introduction of complementary foods play an important role. Equally important were some family risk factors, including the size of the family unit and the presence of deceased children. It also emerged that the lack of knowledge of what a child needs to grow up healthy often affects the development of malnutrition. It follows that a useful and low-cost tool for preventing child malnutrition would be large-scale nutrition education campaigns.

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

Cited by 21 publications

References 44 publications

Delivery channels and socioeconomic inequalities in coverage of reproductive, maternal, newborn, and child health interventions: analysis of 36 cross-sectional surveys in low-income and middle-income countries

Delivery channels and socioeconomic inequalities in coverage of reproductive, maternal, newborn, and child health interventions: analysis of 36 cross-sectional surveys in low-income and middle-income countries

How reliable are self-reported estimates of birth registration completeness? Comparison with vital statistics systems

Analysis of risk and prognostic factors in a population of pediatric patients hospitalized for acute malnutrition at the Chiulo hospital, Angola

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