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Record W4409032310 · doi:10.1186/s12889-025-22432-w

Beverage consumption among adults in Newfoundland and Labrador, Canada prior to the implementation of a sugar-sweetened beverage tax

2025· article· en· W4409032310 on OpenAlexafffundabout
Daniel A. Zaltz, Rachel Prowse, Yanqing Yi, Jessica O’Dea, Scott Harding

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsMemorial University of NewfoundlandUniversity of Toronto
FundersBanting and Best Diabetes Centre, University of TorontoCanadian Institutes of Health ResearchCanadian Cancer Society
KeywordsTaxable incomeMedicineEnvironmental healthBiostatisticsConsumption (sociology)DemographyPublic healthEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Lawmakers in Newfoundland and Labrador (NL) recently passed Canada's first sugar-sweetened beverage (SSB) tax. SSB tax evaluations rely on detailed understandings of beverage consumption patterns prior to policy implementation, but there is no recent literature about such patterns among NL residents during the pre-tax period. METHODS: We recruited a convenience sample of NL adults ages 19 and older and measured participant characteristics via online surveys and beverage intake via previously-validated, semi-quantitative beverage frequency questionnaires. We generated inverse probability weights of sample selection using the Canadian Census as a representative reference sample. We described the weighted prevalence and intake among consumers of taxable SSBs (e.g., regular pop), non-taxable SSBs (e.g., sweetened milk), diet (non-nutritive sweetened) beverages and unsweetened beverages (including 100% juice). We explored weighted bivariate associations between consumption of beverages and sociodemographic characteristics identified as potential correlates of SSB intake. RESULTS: The sample (n = 1233) was 65% female, 57% between ages 30-59 years, and nearly all (94%) white. More than half (57.3%) consumed taxable SSBs weekly, and 23.2% consumed non-taxable SSBs weekly. The most-consumed (highest volume) taxable SSB was regular pop (weighted mean (SD) 2.3 (3.5) L/week); the most-consumed non-taxable SSB was sweetened, flavoured milk (mean (SD) 1.2 2.0) L/week). We found independent differences in consumption patterns (prevalence, mean intake among consumers) across each beverage category. People who were younger, had fewer years of education, reported income below the poverty threshold, or reported experiencing food insecurity had a higher prevalence and mean intake among consumers of taxable SSBs. People with fewer years of education or those who reported experiencing food insecurity had a lower prevalence and mean intake among consumers of unsweetened beverages. CONCLUSIONS: Our findings align with prior studies of socioeconomic position and SSB consumption in Canada, which collectively demonstrate that, on average, those with less education and income consume more SSBs and fewer unsweetened beverages. This research provides necessary understanding of social patterning of beverage consumption in NL prior to tax implementation. Post-tax evaluations of this policy should investigate potential impacts of the tax on diet and health equity, as well as potential beverage substitutions towards other beverage categories.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.309
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes3
Has abstractyes

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