Evidence map›Paper›PMID 35910863›Full record

ArticleFrontiers in public health2022

Simulating Potential Associated Socio-Economic Determinants With Sustainable Food Security (A Macro-Micro Spatial Quantitative Model).

Mohammad Reza Pakravan-Charvadeh, Cornelia Flora, Haider A Khan

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Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Mohammad Reza Pakravan-CharvadehDepartment of Agricultural Economics and Rural Development, Lorestan University, Khorramabad, Iran.
Cornelia FloraDepartment of Sociology, Iowa State University, Ames, IA, United States.
Haider A KhanDepartment of Economics, Josef Korbel School of International Studies, University of Denver, Denver, CO, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improving sustainable food security status, nowadays, is an important challenge globally, especially in developing countries. The policy goal should be equity-everyone has the same opportunity to be food secure-rather than equality-everyone gets the same subsidy. Since the culture and socioeconomic status within a country vary from region to region, collapsing all areas into a unique region may introduce errors and inaccurate results, as most studies carried out. This study assesses the geographical pattern of association between food security and socioeconomic factors in urban areas in Iran using a nationally and regionally representative household consumption-expenditure survey from 2010 to 2018. The logistic regression model and big data are used to achieve this goal. The results show that a substantial number of households face food insecurity in urban areas in Iran. Also, different geographic regions have various salient factors that affect food insecurity. Aggregation tests confirmed that researchers should estimate separate models for different provinces, states, and districts to assess and monitor the food security status of a country instead of estimating a unique model for the whole of the country. Geographical disparities should be considered as an important issue before suggesting any catch-all policies for a country. The geo-locational factor of households is a key determinant of the association between socioeconomic factors and food security in urban areas in Iran. In sum, the practical suggestions for improving Iranian households' food security in urban areas are as follows: (1) Developing job opportunities for the head of household. (2) Enhancing the potential for self-employment. (3) Facilitating the study of children within households including providing inexpensive uniforms, books, and materials, especially for poor households. (4) Supporting young couples in terms of accessing to financial resources and providing inexpensive essential equipment of home for them; and (5) Introduction of the importance of dietary diversity and different foods which can be cooked by using these food ingredients within a household. Comparative case studies using similar methodologies can test if our results are generalizable.

Indexed as

Family CharacteristicsFood SupplyChildFood SecurityHumansIranSocioeconomic Factorsfood securityIranlogistic regressionsocio-economic factorssustainability

Identifiers

PMID35910863
PMCPMC9333187

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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.