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Record W2885472700 · doi:10.1108/bfj-08-2017-0450

Food insecurity among postsecondary students in developed countries

2018· article· en· W2885472700 on OpenAlexaffabout
Sarah Lee, Mahitab A. Hanbazaza, Geoff D.C. Ball, Anna Farmer, Katerina Maximova, Noreen D. Willows

Bibliographic record

VenueBritish Food Journal · 2018
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFood insecurityEthnic groupEnvironmental healthPsychologyFood securityGeographyPolitical scienceMedicineAgriculture

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to conduct a narrative review of the food insecurity literature pertaining to university and college students studying in Very High Human Development Index countries. It aims to document food insecurity prevalence, risk factors for and consequences of food insecurity and food insecurity coping strategies among students. Design/methodology/approach English articles published between January 2000 and November 2017 were identified using electronic databases. Quality Assessment Tool for Quantitative Studies assessed the study quality of quantitative research. Findings A total of 37 quantitative, three mixed-methods and three qualitative studies were included from 80,914 students from the USA ( n =30 studies), Australia ( n =4), Canada ( n =8) and Poland ( n =1). Prevalence estimates of food insecurity were 9–89 percent. All quantitative studies were rated weak based on the quality assessment. Risk factors for food insecurity included being low income, living away from home or being an ethnic minority. Negative consequences of food insecurity were reported, including reduced academic performance and poor diet quality. Strategies to mitigate food insecurity were numerous, including accessing food charities, buying cheaper food and borrowing resources from friends or relatives. Research limitations/implications Given the heterogeneity across studies, a precise estimate of the prevalence of food insecurity in postsecondary students is unknown. Practical implications For many students studying in wealthy countries, obtaining a postsecondary education might mean enduring years of food insecurity and consequently, suffering a range of negative academic, nutritional and health outcomes. There is a need to quantify the magnitude of food insecurity in postsecondary students, to inform the development, implementation and evaluation of strategies to reduce the impact of food insecurity on campus. Originality/value This review brings together the existing literature on food insecurity among postsecondary students studying in wealthy countries to allow a better understanding of the condition in this understudied group.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.106
GPT teacher head0.430
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2018
Admission routes2
Has abstractyes

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