Tax awareness and perceived cost of sugar-sweetened beverages in four countries between 2017 and 2019: findings from the international food policy study
Notice bibliographique
Résumé
BACKGROUND: The public health benefits of sugar-sweetened beverage (SSB) taxes often rely on, among other things, changes to consumer purchases. Thus, perceived cost of SSBs and signalling effects-via awareness of the tax-may impact the effectiveness of SSB taxes on consumer purchases. OBJECTIVE: The study sought to examine perceived cost of SSBs, tax awareness, and changes in beverage purchasing over time and across four countries with and without SSB taxes. METHODS: The study used data from the 2017, 2018 and 2019 waves of the International Food Policy Study. Annual cross-sectional online surveys were conducted in Australia, Mexico, UK and US, which captured perceived cost of SSBs relative to non-SSBs in all countries (with Australia as a no-tax comparator), and measures of tax awareness and participants' reported changes in beverage purchasing in response to SSB taxes in Mexico (tax implemented in 2014), UK (tax implemented in 2018) and US (subnational taxes since 2015). Logistic regression models evaluated the measures across years and socio-demographic groups. RESULTS: Perceived cost of SSBs relative to non-SSBs was higher in Mexico (all three years) and the UK (2018 and 2019 following tax implementation) than Australia and the US. Tax awareness was higher in UK than Mexico, and decreased over time among Mexican respondents. Patterns of reported beverage purchasing changes in response to the tax were similar across Mexico, UK and US, with the largest changes reported by Mexican respondents. Respondents with characteristics corresponding to lower socioeconomic status were less likely to be aware of an SSB tax, but more likely to perceive SSBs to cost more than non-SSBs and report changes in purchasing in response to the tax, where there was one. CONCLUSIONS: This study suggests that in countries where a national SSB tax was present (Mexico, UK), perceived cost of SSBs and tax awareness were higher compared to countries with no SSB tax (Australia) or subnational SSB taxes (US), respectively, and suggests that perceived cost and tax awareness represent distinct constructs. Improving the 'signalling effect' of existing SSB taxes may be warranted, particularly in tax settings where consumer behaviour change is a policy objective.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».