The Health and Financial Impacts of A Sugary Drink Tax Across Different Income Groups in Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".