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Record W4288060315 · doi:10.3390/children9081119

Food Insecurity, Dietary Intakes, and Eating Behaviors in a Convenience Sample of Toronto Youth

2022· article· en· W4288060315 on OpenAlexaffabout
Alexandra Dubelt-Moroz, Marika Warner, Bryan Heal, Saman Khalesi, Jessica Wegener, Julia O. Totosy de Zepetnek, Jennifer J. Lee, Taylor Polecrone, Jasmin El-Sarraj, Emelie Holmgren, Nick Bellissimo

Bibliographic record

VenueChildren · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of TorontoUniversity of ReginaCanada Research ChairsToronto Metropolitan University
FundersNational Heart Foundation of Australia
KeywordsEnvironmental healthFood insecurityMedicineAdded sugarSaturated fatFood securityCalorieObesityGerontologyGeographyAgriculture

Abstract

fetched live from OpenAlex

BACKGROUND: Food insecurity has been shown to be associated with poor dietary quality and eating behaviors, which can have both short- and long-term adverse health outcomes in children. The objective was to investigate the food security status, dietary intakes, and eating behaviors in a convenience sample of youth participating in the Maple Leaf Sports Entertainment LaunchPad programming in downtown Toronto, Ontario. METHODS: Youth aged 9-18 years were recruited to participate in the study. Food security status, dietary intakes, and eating behaviors were collected using parent- or self-reported questionnaires online. RESULTS: Sixty-six youth (mean ± SD: 11.7 ± 1.9 years) participated in the study. The prevalence of household food insecurity was higher than the national average with at least one child under 18 years of age (27.7% vs. 16.2%). Dietary intake patterns were similar to the national trends with low intakes of fiber, inadequate intakes of calcium and vitamin D; and excess intakes of sodium, added sugar, and saturated fat. Despite a low prevalence of poor eating habits, distracted eating was the most frequently reported poor eating habit. CONCLUSIONS: Although youth were at high risk for experiencing household food insecurity, inadequate dietary intake patterns were similar to the national trends. Our findings can be used to develop future programming to facilitate healthy dietary behaviors appropriate for the target community.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.124
GPT teacher head0.396
Teacher spread0.272 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2022
Admission routes2
Has abstractyes

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