Evidence map›Paper›PMID 39425063›Full record

ArticleBMC public health2024

Income and education disparities in childhood malnutrition: a multi-country decomposition analysis.

Mukhtar A Ijaiya, Seun Anjorin, Olalekan A Uthman

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mukhtar A Ijaiya, Data-Lead Africa, 10th street, Bassan Plaza, Block F, 3rd floor, Central Business District, Abuja, Nigeria. Mukhtarijaiya@yahoo.com.
Seun AnjorinBig Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Olalekan A UthmanWarwick Centre for Global Health, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, CV4 7AL, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionChildhood malnutrition is a complex issue with a range of contributing factors. The consequences of malnutrition are severe, particularly for children. This study aims to identify the factors contributing to inequality gaps in childhood malnutrition. Our study provides insights into modifiable elements to inform interventions targeted at distinct contexts and populations to improve child nutrition.

methodsThis study utilized data from the Demographic and Health Surveys (DHS) of 27 countries. First, the risk differences (RDs) between the prevalence of childhood malnutrition among the determinant variables, household income, and maternal education categories were calculated. The Blinder‒Oaxaca decomposition was subsequently used to determine the extent to which the difference in childhood malnutrition prevalence between low-income and high-income groups and maternal education levels results from the contributory effects of the explanatory variables: child and maternal individual-level compositional factors.

resultsWe examined data from 138,782 children in 27 countries from 2015 to 2020. The prevalence of childhood malnutrition (10.5%) varied across countries, ranging from 6.5% in Burundi to 29.5% in Timor Leste. On average, the prevalence of childhood malnutrition was 11.0% in low-income households and 10.7% among mothers without education. Some nations had pro-low-income (i.e., malnutrition concentrated among children from poor households) or pro-no-maternal education (i.e., malnutrition concentrated among children from mothers with no formal education) inequality in childhood malnutrition, but most did not. We found a complex interplay of compositional effects, such as the child's age, maternal education, maternal health behavior, and place of residence, that influence the inequality in childhood malnutrition rates across 10 pro-low-income countries. In addition, we also found that a complex mix of compositional effects, such as the household wealth index, maternal health behavior, and maternal age, contribute to childhood malnutrition inequality between educated and uneducated mothers across the 7 pro-no maternal education countries.

conclusionThe prevalence of childhood malnutrition varies among low-income, high-income, and no maternal education-maternal education groups. This study highlights the need for a country-specific approach to addressing childhood malnutrition, with policies and interventions tailored to each country's specific context.

Indexed as

Child Nutrition DisordersEducational StatusHealth Status DisparitiesIncomeAdolescentAdultChildChild, PreschoolFemaleGlobal HealthHealth SurveysHumansInfantMalePrevalenceSocioeconomic FactorsChildEducationIncomeMalnutrition

Identifiers

PMID39425063
PMCPMC11490161

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.