The economics of healthy eating
Notice bibliographique
Résumé
Obesity is a significant public health issue, and many public health programs and interventions have been developed to address it. Healthy eating at the workplace is a key component of obesity pr??vention, however, evidence of its cost and effectiveness is largely missing. This dissertation took a multi-faceted approach to the evaluation of a workplace healthy-eating intervention implemented in the Alberta Health Services: Calgary Area in September 2006. The first epidemiological study provides a snapshot of the relationship between healthy eating and obesity at the Canadian population level. National dietary patterns were derived from the Canadian Community Health Survey (CCHS) Cycle 2.2 in 2004 and the relationship between obesity and healthy eating, as reflected by the adherence to the Canada's Food Guide (CFG) in the CCHS sample, was explored. Over-consumption of Meat and Alternatives was prevalent, and positively associated with obesity. The second and third studies examined the immediate impact of the Healthy Eating Initiative (HEI). An online survey was developed to explore employees' dietary patterns at work and at home. The survey did not find evidence that employees were changing their consumption of non-recommended food at work and at home. In addition, employees who ate healthily at work also ate healthily at home. The third study used cafeteria sales data to explore the impact of HEI on employees' food purchases, especially on those items that were targeted by the Initiative. The results showed that cafeteria sales revenue did not decrease, and that sales of targeted healthy food items increased during the HEI period, after controlling for price and time. The last study modelled the effect of healthy eating in the long run using decision analysis incorporating data from the literature and the aforementioned three studies. The baseline Incremental Cost Utility Ratio (ICUR) was $9,360 per Quality Adjusted Life Years (QAL Y), but was very sensitive to changes in certain parameters, especially those that affected QALY, sucli as the relative risk (RR) of weight gain from healthy eating. This thesis provided some evidence about the impact of the HEI, and identified issues in the evaluation of such interventions that could be used to develop stronger evaluations in future.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,002 |
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 ».