Secular Trends in Gastric and Esophageal Cancer Attributable to Dietary Carcinogens From 1990 to 2019 and Projections Until 2044 in China: Population-Based Study
Dossier post-publication
OpenAlex signale ce travail comme rétracté, mais aucune notice correspondante de Retraction Watch ne figure dans cette base.
Notice bibliographique
Résumé
BACKGROUND: Little is known about trends in or projections of the disease burden of dietary gastric and esophageal cancer (GEC) in China. OBJECTIVE: We aim to report GEC deaths and disability-adjusted life years (DALYs) from 1990 to 2019, predict them through 2044, and decompose changes in terms of population growth, population aging, and epidemiological changes. METHODS: We retrieved dietary GEC data from the Global Burden of Disease (GBD) online database and used joinpoint regression and age-period-cohort models to analyze trends in dietary GEC deaths and DALYs from 1990 to 2019 in China. We used a Bayesian age period cohort model of integrated nested Laplace approximations to predict the disease burden of GEC through 2044 and obtained the estimated population of China from 2020 to 2050 from the Global Health Data Exchange website. Finally, we applied a recently developed decomposition method to attribute changes between 2019 and 2044 to population growth, population aging, and epidemiological changes. RESULTS: The summary exposure values and age-standardized rates decreased significantly from 1990 to 1999, with percentage changes of -0.06% (95% CI -0.11% to -0.02%) and -0.05% (95% CI -0.1% to -0.02%), respectively. From 1990 to 2019, for dietary esophageal cancer, the percentage change in age-standardized mortality rate (ASMR) was -0.79% (95% CI -0.93% to -0.58%) and the percentage change in age-standardized DALY rate (ASDR) was -0.81% (95% CI -0.94% to -0.61%); these were significant decreases. For dietary stomach cancer, significant decreases were also observed for the percentage change in ASMR (-0.43%, 95% CI -0.55% to -0.31%) and the percentage change in ASDR (-0.47%, 95% CI -0.58% to -0.35%). In addition, data from both the joinpoint regression and annual percentage change analyses demonstrated significantly decreasing trends for the annual percentage change in ASMR and ASDR for GEC attributable to dietary carcinogens. The overall annual percentage change (net drift) was -5.95% (95% CI -6.25% to -5.65%) for dietary esophageal cancer mortality and -1.97% (95% CI -2.11% to -1.83%) for dietary stomach cancer mortality. Lastly, in 2044, dietary esophageal cancer deaths and DALYs were predicted to increase by 192.62% and 170.28%, respectively, due to age structure (121.58% and 83.29%), mortality change (76.81% and 92.43%), and population size (-5.77% and -5.44%). In addition, dietary stomach cancer deaths and DALYs were predicted to increase by 118.1% and 54.08%, with age structure, mortality rate change, and population size accounting for 96.71% and 53.99%, 26.17% and 3.97%, and -4.78% and -3.88% of the change, respectively. CONCLUSIONS: Although the predicted age-standardized rates of mortality and DALYs due to dietary GEC show downward trends, the absolute numbers are still predicted to increase in the next 25 years due to rapid population aging in China.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».