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Record W2226482507

An economic analysis of obesity, health claims, and regulations

2015· dissertation· en· W2226482507 on OpenAlexfundaboutno aff
Solomon Akowuah

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2015
Typedissertation
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersPublic Health AgencyPublic Health Agency of CanadaWorld Health Organization
KeywordsObesityEconomic analysisEnvironmental healthMedicineBusinessPublic economicsEconomicsInternal medicineClassical economics
DOInot available

Abstract

fetched live from OpenAlex

Obesity is becoming an increasing cause of concern worldwide. This thesis examines the determinants and prevalence of obesity, and evaluates the potential health-related cost savings associated with the implementation and promotion of the health claim on low-calorie diets and obesity in Canada. Using data from 2004 Canadian community health survey and reviews of medical/nutritional literature, a Multilevel Multinomial Logistic Regression Model and a variation of Cost of illness approach reveal the following. We found that almost two-thirds of Canadians are overweight/obese. We also found that the aged, males, married, people born in America, less educated, physically inactive, and inadequate fruits/vegetable consumers have increased risk of becoming obese. A 5%-10% reduction in caloric intake due to health-information/health-claims results in nontrivial health-related base savings of CAD$2.09 billion with range of CAD$360 million to CAD$4.18 billion. Stronger economic policies such as subsidies/taxes on low-calorie/high-calorie diets could potentially lead to social optimal calorie consumption.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.343
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2015
Admission routes2
Has abstractyes

Explore more

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