Geographic Variation in Colorectal Cancer Incidence and the Disparities in the Prevalence of Modifiable Risk Factors Across Canada
Notice bibliographique
Résumé
Background: Colorectal cancer is the third most common cancer worldwide. There is wide geographic variation in incidence with rates varying ten-fold between high- and low-income countries. This heavy burden can be mitigated given previous research has estimated that nearly half of all colorectal cancer cases could have been prevented through healthier diets and physically active lifestyles. In Canada, there is considerable geographic variation in age-adjusted incidence rates for colorectal cancer between jurisdictions, greater than that seen for many other cancers. These wide variations likely reflect differences in the prevalence of risk factors across provinces and territories. Aim: To describe the extent of the variation in colorectal cancer incidence rates across Canada and the disparities in the prevalence of modifiable risk factors across jurisdictions known to contribute to this burden. Methods: Colorectal cancer incident cases were obtained from the Canadian Cancer Registry; 2014 was used for provinces (except Quebec where 2010 was the most recent year available) and years 2012 to 2014 were combined to achieve more stable rates for the territories, which are much smaller in population. Data on four known modifiable risk factors for colorectal cancer (excess weight, physical inactivity, alcohol intake and low fruit and vegetable consumption) were obtained from the 2015-16 combined Canadian Community Health Survey. Results: Findings suggest that there is a north-south and east-west gradient in colorectal cancer modifiable risk factors in Canada. For instance, the percentage of adults with excess body weight ranged from 56.8% in British Columbia (west) to 73.1% in New Brunswick (east) and the percentage of adults not meeting physical activity guidelines ranged from 31.8% in Yukon (north) to 50.3% in New Brunswick (east). Generally, this pattern also reflects colorectal cancer incidence rates. The highest prevalence of modifiable risk factors and rates of colorectal cancer are typically in the northern (territories) and eastern provinces of Canada. Conclusion: The global burden of colorectal cancer is expected to increase by nearly 60% by 2030; therefore, targeted interventions are needed to ensure there is not a widening gap in colorectal cancer burden worldwide. Based on current knowledge, the most effective approaches to reduce the burden of colorectal cancer include: 1) adopting public policies that make healthy choices easier and create healthier environments where people live, work and play, and 2) continuing emphasis on screening and early detection. Strategic approaches to addressing modifiable risk factors, as well as mechanisms for detecting colorectal cancer before it develops, have the potential to translate into positive effects on population health and less people developing and dying from cancer.
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 | 0,001 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».