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Enregistrement W7071651089

Supporting healthy and sustainable campuses: Examining food and nutrition interventions in real-world settings

2021· dissertation· en· W7071651089 sur OpenAlexaboutno aff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2021
Typedissertation
Langueen
DomaineMedicine
ThématiqueConsumer Attitudes and Food Labeling
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionSustainabilityPublic healthFocus groupCalorieFood choiceFood systemsHealth promotionLabelling
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Food and nutrition are major contributors to public health and environmental sustainability challenges. There is currently an unprecedented level of focus on identifying interventions to support eating patterns that are consistent with human and planetary health. Post-secondary campuses represent a microcosm of food environments, providing a real-world setting for evaluating the potential for interventions to improve healthy and environmentally sustainable eating among students. However, the current state of evidence on interventions to support healthy and sustainable eating within post-secondary settings is not well understood. Additionally, there is high policy interest in calorie labelling at the point-of-purchase as a strategy to support healthy eating patterns; however, evidence from real-world settings comparing the impact of numeric versus interpretive calorie labelling on food and beverage purchases is limited. \n \nObjectives: The objectives of this dissertation were to: (1) investigate the extent to which health and environmental sustainability are considered in the implementation and evaluation of food and nutrition interventions on post-secondary campuses (Chapter 4); (2) evaluate the impact of numeric and interpretive calorie labelling at the point-of-purchase on consumer noticing, use, and perceptions of the labels, as well as calories purchased and sales (Chapter 5); and (3) examine the implications of numeric and interpretive calorie labelling on quality of foods and beverages purchased based on food groups and nutrients of public health concern (Chapter 6). \n \nMethods and results: The first study (Chapter 5) presents a scoping review of food and nutrition interventions implemented and evaluated on post-secondary campuses to examine the extent to which they integrate considerations related to human health and/or environmental sustainability, as well as to synthesize the nature and effectiveness of interventions and to identify knowledge gaps in the literature. Drawing upon 38 peer-reviewed articles, representing 37 unique interventions, interventions were synthesized according to policy domains within the World Cancer Research Fund’s NOURISHING framework. Overall, interventions to support both healthy and environmentally sustainable eating patterns within the context of postsecondary contexts are limited and there is a greater emphasis on human health versus sustainability. \n \nThe second study (Chapter 6) is comprised of a pre-post quasi-experimental controlled study, where three post-secondary cafeterias were randomized to receive numeric calorie labels, traffic light labelling (red, amber, or green symbol for calories), or no labelling for two weeks. Exit surveys, collecting information on socio-demographics, details of most recent purchase, and consumer noticing, use, and perceptions of labels, were conducted with cafeteria patrons prior to (n=862) and following (n=980) implementation of labels. Generalized estimating equations compared the effects of the labels on noticing, use and perceptions of labels, and calories purchased. Sales data were also collected and examined using ANOVA tests. The increase in noticing of nutrition information from pre-test to post-intervention was significantly greater at the numeric site (+19.5%; OR=3.13, 95% CI=1.79–5.47) and the traffic light labelling site (+33.6%; OR=5.14, 2.95–8.96) than the control (–0.53%). Reported use of nutrition information was significantly greater from pre-test to post-intervention at the numeric (+9.20% vs. –0.30%; OR=2.43, 95% CI=1.14–5.19) and traffic light labelling (+27.5%; OR=5.26, 2.51–11.0) sites relative to the control. Among post-intervention patrons, 32% rated numeric and 48% rated traffic light labels as easy to understand, and 25% rated numeric and 42% rated traffic light labels as easy to use. No differences in three-way interactions with site and time were observed by gender, health literacy, disordered eating, and socioeconomic status for noticing, use, and perceptions of nutrition information. The analyses of the impact of the labels on calories purchased were inconclusive given the assumption of parallel trends across sites could not be satisfied. Numeric and traffic light labels had no effect on total sales, total transactions, and sales per patron. \n \nThe third study (Chapter 7) utilized data collected from the calorie labelling intervention to examine implications for quality of purchases based on food groups and nutrients of public health concern. The change in purchases of green-, amber-, and red-labelled items and in food groups and nutrients purchased at all sites from pre-test to post-test was assessed. Foods and beverages were coded to food composition databases to calculate amounts of food groups and nutrients, including fruits, vegetables, whole grains, refined grains, plant-based proteins, red meats, added sugars, saturated fats, and sodium, expressed per 1000 kcal. No change in purchasing of red-, amber-, and green-categories at the numeric and traffic light labelling sites versus the control was observed, though the assumption of parallel trends across sites could not be satisfied. A significant three-way interaction between site, time, and socioeconomic status was observed for purchases of red-labelled items (β=0.11, 95% CI=0.02–0.21; p=0.01). There was a 0.57 oz equivalents/1000 kcal decrease in refined grains purchased at the traffic light labelling site (β=-1.07, 95% CI=-1.82– -0.31; p=0.005) and a 0.05 tsp/1000 kcal decrease in added sugars purchased at the numeric site (β=4.71, 95% CI=0.97–8.45; p=0.01) versus the control. No differences were observed for other nutrients and food groups. \n \nConclusions: This dissertation examines evidence from real-world settings to improve our understanding of how food and nutrition interventions can support healthy and sustainable eating patterns among post-secondary students. There is a paucity of interventions considering the complexity and interconnectivity of human and planetary health; such approaches are needed to address structural determinants that shape food systems and eating patterns. With respect to a specific nutrition intervention of high policy relevance in Canada, numeric and traffic light calorie labelling at the point-of-purchase has the potential to improve noticing and use of nutrition information, with greater proportions of patrons reporting that TLL were easy to use and understand. Given the lack of parallel trends needed to satisfy the assumptions for quasi-experimental trials, the impact of the labels on purchasing by calories, food groups, and nutrients requires further investigation using group-level sales data. Future research should consider a ‘whole-of-systems’ approach to identify and evaluate complementary strategies that holistically consider impacts on both human and planetary health.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,015
score de la tête « metaresearch » (Gemma)0,024
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,080

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0150,024
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,002
Communication savante0,0050,003
Science ouverte0,0020,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,022
Tête enseignante GPT0,285
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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