The Incidence of Visual Impairment, its Risk Factors, and its Mobility Consequences: The Canadian Longitudinal Study on Aging
Notice bibliographique
Résumé
INTRODUCTION: Canada has yet to conduct high quality, prospective, population-based surveys that measure incident visual impairment, its risk factors, and adverse consequences, creating an unmet need to obtain more rigorous analysis in this regard QUESTIONS: What is the 3-year incidence of visual impairment in each province? What are the risk factors for the 3-year incidence of visual impairment? Do they include geographic, sociodemographic, lifestyle, social, health and healthcare factors? Does vision loss increase the odds of balance problems after three years? METHODS: Baseline and 3-year follow-up data were used from the Canadian Longitudinal Study on Aging. The Comprehensive Cohort included 30,097 adults ages 45-85 years old recruited from 11 sites across 7 provinces. Presenting binocular visual acuity was measured using the Early Treatment of Diabetic Retinopathy Study chart. Incidence of VI was defined as the development at follow-up of visual acuity worse than 20/40 in those with acuity better than or equal to 20/40 at baseline. Balance was measured using the one-leg balance test. Those who could not stand on one leg for at least 60 seconds were classified as having failed the test. Participants were asked about the self-report of a diagnosis of cataract, macular degeneration, or glaucoma. RESULTS: 3.88% (95% Confidence Interval (CI) 3.61, 4.17) of Canadian adults developed VI over a 3-year period. There was a high degree of variability in the incidence between Canadian provinces with a low of 1.42% in Manitoba and a high of 7.33% in Nova Scotia. Uncorrected refractive error was the leading cause of incident VI. Risk factors for incident VI included older age (odds ratio (OR)=1.07, 95% CI 1.06, 1.07), Black race (OR=2.64, 95% CI 1.36, 5.14), lower household income (OR=1.73 for those making less than $20,000 per year, 95% CI 1.24, 2.40), current smoking (OR=1.78, 95% CI 1.37, 2.32), and province. Of the 12,158 people who could stand for 60 seconds on one leg at baseline, 18% were unable to do the same at follow-up 3 years later. After adjustment for demographic and health variables, those with worse visual acuity (per 1 line) were more likely to fail the balance test at follow-up (OR=1.15, 95% CI 1.10, 1.20). Those with a report of a former (OR=1.59, 95% CI 1.17, 2.16) or current cataract (OR=1.31, 95% CI 1.01, 1.68) were more likely to fail the test at follow-up. CONCLUSION: The incidence of visual impairment is common in older Canadian adults, varies markedly between provinces, and is largely due to treatable causes. Risk factors for VI suggest sub-groups that may benefit from interventions to improve access to eye care. These data provide longitudinal evidence that vision loss increases the odds of balance problems over a 3-year period. Efforts to prevent avoidable vision loss are needed as are efforts to improve the balance of visually impaired people.
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) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| 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) | 0,001 | 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 ».