Risk Factors For Sexually Transmitted Diseases in Canada and Provincial Variations
Notice bibliographique
Résumé
Aim: To estimate factors associated with having ever had a Sexually Transmitted Disease (STDs) in Canada and explore provincial variation. Methods: The 2009-2010 Canadian Community Health Survey (CCHS) was used to examine demographic and behavioral factors associated with having ever had an STD. Univariate and multivariate analyses were conducted. Also, probit models were employed to estimate the probability of having ever had an STD in Canada. Results: People living in the Territories had the highest probability of having ever been diagnosed with an STD (OR = 2.11, 95% CI (1.76, 2.52)) and residents from Maritime Provinces were least likely to have been diagnosed with an STD (OR = .64, 95 % CI (.55, .74)). Women were more likely to have ever had an STD with an odds ratio of 2.06 (95% CI (1.90, 2.24)). In our study, income, marriage, and education were found to be protective factors. Behavioral factors such as smoking and binge drinking had significant harmful effects on sexual health. Daily smokers were 1.56 times (95% CI (1.43, 1.71)) more likely to have been diagnosed with an STD compared with non-smokers. Similarly, individuals with binge drinking frequency of more than once per week had 2.57 (95% CI (2.15, 3.07)) higher odds of having ever had an STD. Conclusion: Both demographic and behavioral factors influence the likelihood of having ever been diagnosed with an STD in Canada. Women, people with lower income, lower education, or unmarried are more likely to have ever had an STD. Smoking and binge drinking are significantly associated with an increase in the likelihood of ever having an STD in Canada. Appropriate policy interventions could address some of these factors leading to reductions in STD incidence and prevalence in Canada.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».