Evidence map›Paper›PMID 33153076›Full record

ArticleInternational journal of environmental research and public health2020

The Food Bank of Madrid: A Linear Model for Optimal Nutrition.

Rosendo Castañón, Fco Alberto Campos, Salvador Doménech Martínez, José Villar

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Rosendo CastañónInstitute for Research in Technology IIT, ICAI, Universidad Pontificia Comillas, 28015 Madrid, Spain.ORCID 0000-0001-5626-0782
Fco Alberto CamposInstitute for Research in Technology IIT, ICAI, Universidad Pontificia Comillas, 28015 Madrid, Spain.
Salvador Doménech MartínezInstitute for Research in Technology IIT, ICAI, Universidad Pontificia Comillas, 28015 Madrid, Spain.
José VillarINESC TEC-Institute for Systems and Computer Engineering, Technology and Science, 4200-465 Porto, Portugal.ORCID 0000-0001-6954-9833

Funding

Fundação para a Ciência e a Tecnologia UIDB/50014/2020
6 · The paper itself

Abstract

This work proposes a mathematical linear programming model that addresses the food provisioning problem of the food bank of Madrid. It aims to determine the most appropriate weekly decisions to meet the macro-nutritional requirements of the beneficiaries of this social service, by minimizing the total cost considering third-party donations. The model has been applied to a realistic case study considering a sociological structure of beneficiaries categorized by age and gender and representing the first decile of incomes of the Spanish population. The demand of macronutrients is satisfied by means of nine different groups of food, used to provide some level of variability in the consumption patterns of the beneficiaries. The results provide insight on cost-cutting opportunities related to centralizing the decision-making process, indicating a 10% reduction both in provisioning costs and food quantities. This suggests that the proposed model might serve as a tool for designing new strategies for the provisioning or evaluation of economic and social support policies for the food bank of Madrid.

Indexed as

Food AssistanceFood SupplyNutritional RequirementsNutritional StatusAdolescentAdultAgedChildFemaleFoodHumansLinear ModelsMaleMiddle AgedProgramming, LinearSpainCOVID-19 pandemicfood banknutrition economicsnutrition in low-income scenariosresource optimization

Identifiers

PMID33153076
PMCPMC7663117

What OpenQuestion holds

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LicenceCC BY
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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.