Evidence map›Paper›PMID 30110376›Full record

ArticlePloS one2018

The role of agriculture in women's nutrition: Empirical evidence from India.

Tanvi Rao, Prabhu Pingali

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

1 citing paper in PubMed, 13 citations in OpenAlex.

  1. Food Insecurity and Dietary Intake among Rural Indian Women: An Exploratory Study.International journal of environmental research and public health · 2021
    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

2 authors at 2 institutions in 1 country.

Tanvi RaoIMPAQ International LLC, Washington, D.C., United States of America.ORCID 0000-0002-0184-522X
Prabhu PingaliCharles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, New York, United States of America.
Cornell University · USImpaq International (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we establish a statistically important relationship between household agricultural income and women's BMI using a five-year panel dataset of rural households drawn from 18 villages across five Indian states. Using within household variation over time, we estimate both the extent to which short-term changes in agricultural income are associated with short-term changes in BMI, and the effect of agricultural income growth on BMI growth over a longer term. Over the longer term, and for the group of households that regularly farm, we find a 10 percentage point agricultural income growth to be associated with a 0.10 percentage point growth in BMI. Consistent with the literature, this effect is economically modest, but important considering that we do not find a corresponding effect for growth in non-agricultural income. We show that both the own-production and market purchase of food are associated with nutritional improvements. While women's BMI is associated with an increase in the consumption of own-produced cereals, the market plays an important role in facilitating access to more nutritious foods like pulses. Lastly, we also find that effects of agricultural income are driven by younger women, in the age-group 15-25 years, who face a particularly strong nutritional disadvantage in India.

Indexed as

Body Mass IndexIncomeAdolescentAdultAgricultureCross-Sectional StudiesDietFemaleHumansIndiaNutritional StatusRural PopulationTime FactorsYoung Adult

Identifiers

PMID30110376
PMCPMC6093637
OpenAlexW2887903426

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.