Socio-economic factors associated with alcohol and cannabis use across waves of the COVID-19 pandemic: an intersectional analysis of a repeated cross-sectional survey
Notice bibliographique
Résumé
BACKGROUND: This study examined trends in cannabis and alcohol use among Canadian adults and across socio-economic subgroups over four waves of the COVID-19 pandemic from 2020 to 2022. Interactions between socio-economic status (SES) and gender, ethnoracial background, and age as they are associated with alcohol and cannabis use were examined. METHODS: Data were collected from nine consecutive web-based cross-sectional surveys of adults living in Canada (8,943 participants) conducted from May 2020 to January 2022. Substance use measurements included self-reported changes in alcohol and cannabis use compared to before the pandemic, heavy episodic drinking (HED) (i.e., consumption of 4 or more and 5 or more standard drinks on one drinking occasion for men and women, respectively), and cannabis use in the past 7 days. The Wilcoxon rank-sum test was used to test for equality of the prevalence of substance use. Stepwise logistic regression models were used to assess the associations of SES and its interactions with gender, ethnoracial background, and age with alcohol and cannabis use. RESULTS: The prevalence of increased alcohol and cannabis use differed through the pandemic waves depending on SES. The prevalence of HED and increased cannabis use were similar across SES groups. Having a moderate or high household income and being unemployed were associated with HED and a perceived increase in alcohol use. People in racial and ethnic minority groups with a household income of $40,000 to $79,999 had greater odds of engaging in HED than White persons in households with less than $40,000. Women and individuals aged 40 to 59 years with a high household income (≥$120,000) were more likely to report increased alcohol consumption than men and individuals aged 18 to 39 years in households with an income of less than $40,000. Protective factors associated with HED were being a woman with a university degree and an older adult with a college degree. Protective factors associated with cannabis use or perceived increases in cannabis use included women with a university degree, aged 39 years or more with a university or college degree and being in racial and ethnic minority groups with a university degree. CONCLUSIONS: Associations between SES and substance use differ by gender, race and age. To reduce health disparities, public health interventions should account for these interactions.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».