Evidence map›Paper›PMID 37508768›Full record

ArticleChildren (Basel, Switzerland)2023

Household Wealth Gradient in Low Birthweight in India: A Cross-Sectional Analysis.

Bishwajit Ghose

Open access · goldAbstract read
In one paragraph

Article in Children (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.5field-weighted citation impact, top 8% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

1 author.

Bishwajit GhoseCenter for Social Capital and Environmental Research, Ottawa, ON K1M OZ2, Canada.ORCID 0000-0003-4461-3821

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A low birthweight is a common complication that can result from numerous physiological, environmental, and socioeconomic factors, and can put babies at an increased risk for health issues such as breathing difficulties, developmental delays, and even death in severe cases. In this analysis, I aim to assess the differences in the burden of low birthweight based on household wealth status in India using data from the latest National Family Health Survey (NFHS 2019-21). The sample population includes 161,596 mother-child dyads. A low birthweight is defined as a weight that is <2500 g at birth. I used descriptive and multivariate regression analyses in R studio to analyse the data. The findings show that 16.86% of the babies had a low birthweight. At the state level, the percentage of low birthweights ranges from 3.85% in Nagaland to 21.81% in Punjab. The mean birthweights range from 2759.68 g in the poorest, 2808.01 g in the poorer, 2838.17 g in the middle, 2855.06 g in the richer, and 2871.30 g in the richest wealth quintile households. The regression analysis indicates that higher wealth index quintiles have progressively lower risks of low birthweight, with the association being stronger in the rural areas. Compared with the poorest wealth quintile households, the risk ratio of low birthweight was 0.90 times lower for the poorer households and 0.74 times lower for the richest households. These findings indicate that household wealth condition is an important predictor of low birthweight by which low-income households are disproportionately affected. As wealth inequality continues to rise in India, health policymakers must take the necessary measures to support the vulnerable populations in order to improve maternal and infant health outcomes.

Indexed as

birthweighthousehold wealthIndiamaternal and child health

Identifiers

PMID37508768
PMCPMC10378485
OpenAlexW4385211113

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.