Evidence map›Paper›PMID 39656694›Full record

ArticlePloS one2024

Ethnicity/caste and child anthropometric outcomes in India using the National Family Heath Survey 2015-16 and 2019-21.

Sakshi Pandey, Dil Bahadur Rahut, Tetsuya Araki

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Do Ethnicity/Caste-Based Disparities Influence Childhood Anemia in India?Journal of racial and ethnic health disparities · 2026
    Article
  2. 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.

Sakshi PandeyGraduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.ORCID 0009-0008-6699-7436
Dil Bahadur RahutAsian Development Bank Institute, Tokyo, Japan.ORCID 0000-0002-7505-5271
Tetsuya ArakiGraduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Socioeconomic inequalities are known to negatively impact anthropometric outcomes among children, particularly in developing countries. This study, therefore, assesses the gap in anthropometric outcomes of children 6-59 months along the ethnicity-based social groups in India using the National Family Heath Survey 2015-16 and 2019-21. The paper utilizes logistic regression models, the exogenous switching treatment effect regression (ESTER) model, and the Blinder-Oaxaca Model to disentangle the role of ethnicity (referred to as caste in India) in influencing child anthropometric outcomes while accounting for socio/economic factors. Approximately 35% of children in the sample were stunted and 20% wasted. Result indicates that despite the progress made in reducing child undernutrition between the two survey periods, there is a higher risk of chronic growth faltering (stunting) and underweight in socially disadvantageous groups, and these ethnicity-based disparities exist independent of education and household economic status. To improve children's nutritional status, India needs to develop new nutrition strategies prioritizing double-duty action due to the persistence of undernutrition and rising overweight/obesity among children. The study suggests a need for a distinguished understanding of the underlying causes of chronic and acute forms of malnourishment, and separate interventions are required to reduce the disparities among disadvantaged groups, particularly in tribal communities.

Indexed as

EthnicityAnthropometryChild, PreschoolFemaleGrowth DisordersHumansIndiaInfantMaleMalnutritionNutritional StatusSocial ClassSocioeconomic FactorsThinness

Identifiers

PMID39656694
PMCPMC11630627

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.