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Record W2094414678 · doi:10.3148/68.2.2007.73

<i>Food Insecurity and Dietary Intake</i>Of Immigrant Food Bank Users

2007· article· en· W2094414678 on OpenAlexaffvenueabout
Timothy J. Rush, Victor Ng, Jennifer D. Irwin, Larry Stitt, Meizi He

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2007
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsMiddlesex London Health UnitWestern University
Fundersnot available
KeywordsFood insecurityImmigrationEnvironmental healthPsychological interventionMedicineFood securityPopulationFood frequency questionnaireGerontologyDemographyGeographySociologyAgriculture

Abstract

fetched live from OpenAlex

PURPOSE: The degree of food insecurity and dietary intake was examined in adult Colombians who are new immigrants to Canada and use a food bank. METHODS: In-person surveys were conducted on a convenience sample of 77 adult Colombian immigrant food bank users in London, Ontario. Degree of food insecurity was measured by the Radimer/Cornell questionnaire, food intakes by 24-hour recall, sociodemographics, and questionnaires about changes in dietary patterns before and after immigration. RESULTS: Thirty-six men and 41 women participated in the study. Despite being highly educated, all respondents had experienced some form of food insecurity within the previous 30 days. The degree of food insecurity seems to be inversely associated with income and length of residency in Canada. Total daily energy intake was low, with a mean value of 1,568.3 +/- 606.0 kcal (6,217.5 +/- 2,336.4 kJ). In particular, a large proportion of participants consumed a diet low in fruits and vegetables (73%) and milk and dairy products (58%). CONCLUSIONS: Colombian immigrant food bank users new to Canada experience various degrees of food insecurity, which is associated with inadequate food intake. Interventions are needed to assist this population with adapting to society while concurrently sustaining healthy eating patterns.

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)0.009
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.290
GPT teacher head0.500
Teacher spread0.210 · 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

Citations46
Published2007
Admission routes3
Has abstractyes

Explore more

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