Evidence map›Paper›PMID 35548565›Full record

ArticleFrontiers in nutrition2022

Impact of Socio-Economic Factors on Nutrition Efficiency: An Application of Data Envelopment Analysis.

Mohammad Reza Pakravan-Charvadeh, Cornelia Butler Flora, Ali Emrouznejad

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 16 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

3 authors at 3 institutions in 3 countries.

Mohammad Reza Pakravan-CharvadehDepartment of Agricultural Economics and Rural Development, Lorestan University, Khorramabad, Iran.
Cornelia Butler FloraDepartment of Sociology, Kansas State University, Manhattan, KS, United States.
Ali EmrouznejadSurrey Business School, Faculty of Arts and Social Sciences, University of Surrey, Guildford, United Kingdom.
Iowa State University · USLorestan University · IRUniversity of Surrey · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Paying particular attention to sustainable food consumption in low-income households is essential for increasing human health. Due to the growing population globally, this concept will likely become more serious soon. Methods: Following the importance of optimizing food consumption for sustainability, in this study, a novel methodology is introduced for calculating nutrient intake efficiency and determining choices of food in different locations. The impact of socio-economic factors on nutrition efficiency is assessed. Data Envelopment Analysis (DEA) as a well-known linear programming (LP) and a Tobit model are used to achieve the goals. Household Consumption and Expenditure Surveys (HCESs) of 30,000 rural and urban Iranian households in all provinces in 2016 are analyzed. A Nutrient Efficiency Map (NEM) of Iran was depicted by GIS software. Results: The results showed that many townships had nutrient efficiency scores of less than 70%. Northeast townships had the lowest scores, with an efficiency score of less than 50%. Overall, townships have lower efficiency in the North (seaside cities), East (desert cities), and North East (isolated cities) when compared with other areas. Conclusion: Therefore, it is suggestible that the government should modify the support policies and the protection packages based on social, geographical, and cultural status.

Indexed as

data envelopment (DEA)efficiencynutrient intakeoptimizationsocio-economic disparityurban-rural areas

Identifiers

PMID35548565
PMCPMC9085191
OpenAlexW4224436920

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.