Quantifying the contribution of modifiable risk factors to socio-economic inequities in cancer morbidity and mortality: a nationally representative population-based cohort study
Notice bibliographique
Résumé
BACKGROUND: Compared with those with a higher socio-economic position (SEP), individuals with a lower SEP have higher cancer morbidity and mortality. However, the contribution of modifiable risk factors to these inequities is not known. This study aimed to quantify the mediating effects of modifiable risk factors to associations between SEP and cancer morbidity and mortality. METHODS: This study used a prospective observational cohort design. We combined eight cycles of the Canadian Community Health Survey (2000/2001-2011) as baseline data to identify a cohort of adults (≥35 years) without cancer at the time of survey administration (n = 309 800). The cohort was linked to the Discharge Abstract Database and the Canadian Mortality Database for cancer morbidity and mortality ascertainment. Individuals were followed from the date they completed the Canadian Community Health Survey until 31 March 2013. Dates of individual first hospitalizations for cancer and deaths due to cancer were captured during this time period. SEP was operationalized using a latent variable combining measures of education and household income. Self-reported modifiable risk factors, including smoking, excess alcohol consumption, low fruit-and-vegetable intake, physical inactivity and obesity, were considered as potential mediators. Generalized structural equation modelling was used to estimate the mediating effects of modifiable risk factors in associations between low SEP and cancer morbidity and mortality in the total population and stratified by sex. RESULTS: Modifiable risk factors together explained 45.6% of associations between low SEP and overall cancer morbidity and mortality. Smoking was the most important mediator in the total population and for males, accounting for 15.5% and 40.2% of the total effect, respectively. For females, obesity was the most important mediator. CONCLUSIONS: Modifiable risk factors are important mediators of socio-economic inequities in cancer morbidity and mortality. Nevertheless, more than half of the variance in these associations remained unexplained. Midstream interventions that target modifiable risk factors may help to alleviate inequities in cancer risk in the short term. However, ultimately, upstream interventions that target structural determinants of health are needed to reduce overall socio-economic inequities in cancer morbidity and mortality.
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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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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 ».