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Record W2946493676 · doi:10.3390/nu11051152

Snack Consumption Patterns among Canadians

2019· article· en· W2946493676 on OpenAlexaffabout
Hassan Vatanparast, Naorin Islam, Rashmi Prakash Patil, Mojtaba Shafiee, Jessica Smith, Susan J. Whiting

Bibliographic record

VenueNutrients · 2019
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of Saskatchewan
FundersGeneral Mills
KeywordsSnackingEnvironmental healthSnack foodObesityMedicineConsumption (sociology)DemographyGerontologyFood scienceBiology

Abstract

fetched live from OpenAlex

The snacking prevalence, frequency of daily snack consumption, and the contribution of snacks to daily energy intake have substantially increased globally. The aim of this study was to examine the patterns of snack consumption among a representative sample of Canadians aged 2 and older. Nationally representative dietary data from the Canadian Community Health Survey (CCHS) conducted in 2015 (n = 19,677 participants aged ≥2 years) were used to describe snacking patterns. In all, 80.4% of Canadians reported consuming at least one snack per day, which varied between different age groups from 77.0% (≥55 years) to 96.4% (2–5 years). About 37% of snack consumers reported only one snack episode per day but nearly 10% reported four or more episodes of snacking. Snacking contributed to nearly 23% of total daily energy intake in Canadians, which was highest among younger children (27%) and lowest among older adults (20.8%). There were no significant differences in obesity measures comparing snack consumers and non-consumers in children and adults. Snacking considerably contributes to total nutrient and energy intake of Canadians. Promoting nutrient-dense snacks provides an opportunity to improve overall diet quality.

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 categoriesInsufficient 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 score0.031
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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

Citations61
Published2019
Admission routes2
Has abstractyes

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