Undercorrection of refractive error and cognitive function: the Beijing Eye Study 2011
Notice bibliographique
Résumé
Cognitive impairment is a hallmark of age-related dementias such as Alzheimer's disease. It was the aim of our study to search for ocular factors, which are associated with a low cognitive function. To avoid confounding factors by a referral bias, we addressed the question in a population-based investigation. The Beijing Eye Study 2011 is a population-based cross-sectional study in northern China and included 3469 participants. The Medical Ethics Committee of the Beijing Tongren Hospital approved the study protocol, and all participants gave informed written consent. The study has already been described in detail previously (Jonas et al. 2009). Cognitive function was assessed using the Mini-Mental State Examination (MMSE) scale. Cognitive function measurements were available for 3127 (90.1%) study participants. The mean cognitive function score was 26.3 ± 3.7 (median: 27; range: 2–30; 95% CI: 17–30). In multivariate analysis, increasing cognitive function score was significantly associated with younger age (p < 0.001), female gender (p = 0.009), rural region of habitation (p = 0.005), higher body height (p = 0.002), higher level of education (p < 0.001), type of occupation (p = 0.001), lower score of psychic depression (p < 0.001), higher best-corrected visual acuity (p < 0.001), lower amount of undercorrection of refractive error (p = 0.02), wearing of glasses (p < 0.001) and history of cardiovascular disorder (p = 0.002) (Table 1). After adjustment for age, region of habitation, body height, level of education, higher type of occupation, score of psychic depression and best-corrected visual acuity, the cognitive score of our study participants was significantly higher the better corrected was their refractive error. Correspondingly, subjects wearing glasses for correction of their refractive error as compared to subjects without glasses showed a significantly higher cognitive score. Previous studies have provided evidence associating dementia and visual impairments; however, none of the studies showed an association with the degree of myopia or undercorrection of refractive error. In an 8.5-year follow-up study of 625 elderly people with normal cognition at baseline, Rogers and Langa found that poor vision was associated with development of dementia and that individuals with very good or excellent vision at baseline had a 63% reduced risk of dementia over participants with poorer vision (Rogers & Langa 2010). In the recent Singapore Malay Eye Study (Ong et al. 2012), people with visual impairment both before and after refractive correction were significantly more likely to have cognitive dysfunction. In a study on 2140 non-institutionalized Mexican Americans aged 65 and older with a follow-up of up to 7 years, near vision impairment, but not distance vision or hearing impairments, was associated with cognitive decline (Reyes-Ortiz et al. 2005). A magnetic resonance imaging study showed a regional expansion of grey matter volume in area V2 contralateral to the eye operated on cataract, at 6 weeks after cataract surgery (Lou et al. 2013). As our study as cross-sectional investigation did not allow drawing conclusions on longitudinal, causal associations, our findings do not constitute a proof of a causal relationship between undercorrection of refractive error and low cognitive function score. The results however suggest that low vision and the undercorrection of refractive error leading to low habitual vision are associated or risk factors for cognitive dysfunction. It may potentially indicate that not only cerebral training as shown in previous studies, but also adequate vision by providing the best possible correction of refractive error, may be protective measures against the development of cognitive dysfunction. Simple, cheap treatment of refractive errors by providing proper eye glasses to people may thus not only improve their quality of life, but may potentially also provide a cost-effective prophylaxis of dementia.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 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 ».