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Record W328773195

Using Food and Beverage Price Interventions to Address Obesity

2009· article· en· W328773195 on OpenAlexvenueaboutno aff
JoAnne Sauder

Bibliographic record

VenueHealth law review · 2009
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyPublic economicsPsychological interventionObesityPublic healthFood pricesBusinessEconomicsAgricultureMedicineFood securityMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The high rate of obesity in Canada is an increasing challenge to public health. This paper will examine the possibility of using price interventions as a strategy to address the problem of obesity. Price inventions could include taxes on unhealthy foods and subsidies on healthy foods. Taxes may help individuals internalize the true cost of the food they eat, discourage unhealthy purchases and provide money to support programs that promote healthy eating. Obesity is a challenging problem with many social, economic and environmental factors. There is no simple solution to obesity. Price interventions may be an important addition to a larger strategy to reduce obesity. Currently, it is difficult to establish the efficiency of price interventions; more research is required in this area. Until this occurs, a reexamination of the definition of basic groceries under the goods and services tax/harmonized sales tax (GST/HST) to ensure that it promotes healthy eating would be a wise first step. This paper will start by examining obesity in Canada and its contributing factors, including the role of agricultural subsidies. Next, will be an examination of price interventions based on public health policy and as a response to the market. Lastly, will be a consideration of what forms food and beverage taxes and subsidies could take. Obesity as a Public Health Concern Obesity in Canada is a public health concern; it affects the quality of life of many individuals in Canada and is a significant economic drain. The rate of obesity in Canada is 23%. (1) The effect of obesity is an increase in hypertension, type II diabetes, gallbladder disease, coronary artery diseases, osteoarthritis, stoke and certain types of cancer. (2) The cost of obesity to the Canadian health care system has been estimated at $2.1 billion. (3) The cost total to the Canadian economy has been estimated to be $6.6 billion. (4) The Federal, Provincial and Territorial governments have committed to reduce the effect of obesity in Canada. (5) One contributing factor to obesity is the cost and oversupply of energy-dense foods. Energy-dense foods are those that provide a large amount of calories relative to their weight. They are less satisfying than energy-dilute foods and lead to overconsumption. (6) The price of food has continually fallen and there is an oversupply of food. (7) Calorie intake has increased in Canada; the total calories consumed by Canadians increased by 17% between 1991-2001. (8) The types of foods consumed have also changed. Canadians are consuming increasing amounts of energy-dense foods. These include cream, fats, oils and soft drinks. (9) Canadians now have access to greater amounts of less satisfying energy-dense foods at lower prices and they are consuming more of them. Rates of obesity are related to socio-economic status. Rates of obesity are higher for individuals with lower levels of education and lower incomes. (10) This may be the result of the high price and lack of access to energy dilute foods in low income areas. (11) Some low income families incur food insecurity, making unhealthy, energy dense foods their most viable options. (12) There may also be a link between the vulnerable situation of scarcity and the impulse to overeat. (13) Aboriginal Canadians have high rates of obesity and food insecurity. (14) Rural areas also have significantly higher rates of obesity and food insecurity than large urban areas. (15) In addressing obesity in Canada, targeting populations that have higher rates of obesity and ensuring the methods used to reduce obesity used are effective for them will result in more effective strategies. Agricultural Subsidies In considering price interventions, it is important to consider how the market has been skewed by agricultural subsidies. (16) The most highly subsidized agricultural commodities in Canada are corn, soybeans, tobacco, beef, sheep and milk. …

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.285

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.113
GPT teacher head0.418
Teacher spread0.305 · 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 designTheoretical or conceptual
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

Citations2
Published2009
Admission routes2
Has abstractyes

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