Evidence map›Paper›PMID 35704632›Full record

ArticlePloS one2022

Connected and extracted: Understanding how centrality in the global wheat supply chain affects global hunger using a network approach.

Subhashni Raj, Catherine Brinkley, John Ulimwengu

Abstract read
In one paragraph

Article in PloS one, 2022. 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. 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.

Subhashni RajDepartment of Human, Ecology, University of California, Davis, CA, United States of America.ORCID 0000-0002-4000-698X
Catherine BrinkleyDepartment of Human, Ecology, University of California, Davis, CA, United States of America.
John UlimwenguInternational Food Policy Research Institute, Washington, DC, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While global food trade has allowed countries to buffer against domestic food production shortfalls and gain access to larger markets, engaging in trade has also opened economies up to shocks and increased extraction of food resources. With this research, we analyze how the global grain network influences country-level nourishment, while controlling for per capita land and food production. First, we model the trade network structure of the global wheat supply chain to measure the centrality or positionality of countries. We use spatial regression analysis to assess the impact of trade networks, volume, purchasing power, production capacity and geography on undernourishment. We find that the six countries most central to the global grain trade by betweenness and eigenvector centralities account for more than half of all wheat exports globally by volume. The centrality of these countries as opposed to volume of wheat produced or traded, determines their influence in the wheat supply chain network. The parametric component of our analysis confirms that trade, and centrality have significant implications for national levels of nourishment. Our findings suggest that for countries with low purchasing power, increasing centrality allows improvements in nourishment levels but for countries with very high purchasing power, increasing centrality can increase hunger outcomes. To counteract perturbations and shortfalls such as those being experienced currently in the globalized food system, local and regional governments may consider refocusing on regional and local based food systems.

Indexed as

HungerTriticumEdible GrainFood Supply

Identifiers

PMID35704632
PMCPMC9200319

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.