The Health and Financial Impacts of A Sugary Drink Tax Across Different Income Groups in Canada
Notice bibliographique
Résumé
Obesity remains a leading health issue and contributes to health inequality. Overconsumption of sugar-sweetened beverages (SSBs) contributes to both childhood and adult obesity, and also increases healthcare costs. Sugary drink taxes have been implemented to curb sugar intake in several countries. However, there is a concern that sugary drink taxes are regressive. This project assessed the health and financial impacts of a sugary drink tax by different income groups in Canada. The current study extended Jones’ Canadian sugary drink tax model to estimate the impact of a sugary drink tax on health and financial inequality. Sugary drinks consist of all types of beverages containing free sugar, including regular carbonated soft drinks, regular fruit drinks, non-diet sports drinks, non-diet energy drinks, sugar-sweetened coffee and tea, hot chocolate, non-diet flavoured water, flavoured milk, sugar-sweetened drinkable yogurt, and 100% juice. Income-specific parameters include: population demographics, cross- and own-price elasticities, mean BMI, sugary drink consumption, mortalities, and disease epidemiology. Our result shows that, overall, a 20% sugary drink tax was estimated to reduce the consumption of sugary drinks by an average of approximately 15%, with the lowest income quintile having a slightly greater reduction than other income quintiles. The estimated mean reduction in BMI ranged from 0.21 to 0.33 depending on sex and income quintile. These reductions were greater among the lower income quintiles for both females and males, and lessened as income increased. The 20% sugary drink tax was estimated to avert approximately 690,000 DALYs over a lifetime period among the 2016 Canadian adult population. The lowest income quintile had the most estimated DALYs averted per person. Lifetime health care savings were estimated to be $2.27, $2.16, $2.17, $2.12, and $1.98 billion for quintile 1 to quintile 5, respectively. The lowest income quintile had the greatest estimated health care savings per person. The estimated annual tax burden for the whole 2016 Canadian population (including children) was $1.4 billion. The average tax burden was estimated to be $39.00 to $44.30 per person, with the middle-income quintile bearing the heaviest burden. The lowest income quintile would pay the highest proportion of after-tax income in tax. A 20% sugary drink tax is regressive, but the estimated difference in annual tax burden was less than $6 per person. In conclusion, the model predicts that low-income Canadians would gain the most health from a sugary drinks tax. While this income group would pay the largest proportion of their incomes in tax, the difference between income groups is small. If this regressivity is a concern, then policy makers may wish to consider investing the revenue raised from sugary drinks taxes in policies that address health or income inequalities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».