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Record W3014424366 · doi:10.1016/j.ehb.2020.100869

The health and financial impacts of a sugary drink tax across different income groups in Canada

2020· article· en· W3014424366 on OpenAlex
Kai-Erh Kao, Amanda Jones, Arto Öhinmaa, Mike Paulden

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEconomics & Human Biology · 2020
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of Alberta
FundersHeart and Stroke Foundation of Canada
KeywordsDemographyPopulationConsumption (sociology)Environmental healthOverconsumptionMedicineEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Overconsumption of sugar-sweetened beverages (SSBs) contributes to childhood and adult obesity and numerous related diseases, including heart disease, strokes, cancers, and type 2 diabetes. It also increases healthcare costs. Sugary drink taxes have been implemented in several countries to curb sugar intake. However, there is a concern that sugary drink taxes are regressive. This study assessed the health and financial impacts of a simulated sugary drink tax across different income groups in Canada. METHODS: A proportional multi-state life table-based Markov model simulated the 2016 Canadian population by income quintile. The model applied a 20 % tax on sugary drinks and determined the effects on type 2 diabetes and BMI-related diseases compared to no intervention. The income-specific parameters modelled included: population demographics; cross- and own-price elasticities; mean BMI; sugary drink consumption; mortality; and disease epidemiology. RESULTS: A 20 % sugary drink tax was estimated to reduce the consumption of sugary drinks by an average of around 15 %, with a greater reduction in the lowest income quintile. The estimated mean reduction in BMI ranged from 0.21 to 0.33, dependent upon sex and income quintile; these reductions were greater among the lower income quintiles for both females and males. The 20 % sugary drink tax was estimated to avert approximately 690,000 DALYs over a lifetime among the 2016 Canadian adult population; estimated DALYs averted were approximately 156,000, 140,000, 137,000, 134,000, and 125,000 for the lowest through to the highest income quintile, respectively. Lifetime health care savings were estimated to be $2.27bn, $2.16bn, $2.17bn, $2.12bn, and $1.98bn for the lowest through to the highest income quintile, respectively. The estimated annual tax burden for the 2016 Canadian population was $1.4bn. The average absolute tax burden was estimated to be $39.00 to $44.30 per person, with the middle-income quintile bearing the heaviest absolute tax burden. The lowest income quintile would pay the highest proportion of income in tax, implying that the tax is regressive. CONCLUSIONS: Low-income Canadians would gain the most health benefit from a sugary drinks tax. However, the lowest income quintile would also pay the largest proportion of income in tax. A tax on sugary drinks is therefore financially regressive but forecast to reduce health disparities across Canada.

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.

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 score0.666
Threshold uncertainty score0.831

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)0.0000.000

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 head0.015
GPT teacher head0.267
Teacher spread0.253 · 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