Association Between Household Online Grocery Delivery Service Use and Food and Drink Purchase Behavior in England: Cross-Sectional Analysis
Notice bibliographique
Résumé
BACKGROUND: Online grocery delivery services (OGDSs) are a popular way of acquiring food. However, it is unclear whether OGDS use is associated with the healthiness of purchases and whether there are sociodemographic differences in OGDS use. If so, the increased prevalence of OGDS use may have implications for population diet, and differential OGDS use could contribute to diet inequalities. OBJECTIVE: This study aimed to examine whether OGDS use varies by sociodemographic characteristics and is associated with the amount and types of groceries purchased. METHODS: Item-level take-home food and drink purchase data (n=3,233,920 items) from households in London and the North of England were available from the 2019 UK Kantar fast-moving consumer goods panel (N=1911). Purchases were categorized as being bought online or in-store. We used logistic regression to estimate the likelihood of an above-median frequency of OGDS use by sociodemographic characteristics. We used Poisson regression to estimate the differences in energy and nutrients purchased by households that had above- and below-median OGDS use and the proportion of energy purchased from products high in fat, salt, and sugar (HFSS) online versus in-store among households that used both shopping methods (n=665). RESULTS: In total, 668 (35%) households used OGDSs at least once in 2019. Of the households that used OGDSs, the median use was 5 occasions in 2019. Households were more likely to have above-median use in London versus in the North of England (odds ratio 1.29, 95% CI 1.01-1.65) and if they had a higher annual household income (odds ratio 1.56, 95% CI 1.02-2.38 for ≥£50,000 [US $64,000] vs <£20,000 [$25,600]). Households with above-median OGDS use had a higher weekly mean purchase of energy by 1461 (95% CI 1448-1474) kcal per person compared with households with below-median OGDS use. For households that used a combination of in-store and online shopping, HFSS products made up a lower proportion (-10.1%, 95% CI -12% to -8.1%) of energy purchased online compared to in-store. CONCLUSIONS: Differences in grocery purchases between households with above- and below-median OGDS use could have positive or negative consequences. The extra energy purchased among households with above-median OGDS use could lead to overconsumption or food waste, which has negative consequences for population and environmental health. Alternatively, this extra energy may be replacing out-of-home purchasing, which tends to be less healthy, and may be beneficial for the population diet. Households made fewer HFSS purchases when shopping online compared to in-store, which may be due to differences in the shopping environment or experience, such as fewer promotions and advertisements when shopping online or not having to transport and carry purchases home. As higher-income households used OGDS more frequently, the implications of this sociodemographic pattern on dietary inequalities must be explored.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
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 ».