RESUMEN
Background: Centenarian offspring have better health and lower mortality in comparison to referent cohorts, however it is unknown whether they have preserved cognition at older ages. Methods: This prospective study of 491 centenarian offspring and 270 referent participants without familial longevity (mean baseline age 75.5 years) from the New England Centenarian Study analyzed longitudinal cognitive assessments performed using the Telephone Interview for Cognitive Status. Logistic regression was used for cognitive impairment at baseline and Cox proportional hazards regression for risk of incident cognitive impairment. Results: After adjustment for age, sex, education, stroke, and diabetes, offspring were 46% less likely to have baseline cognitive impairment (adjusted odds ratio 0.54, 95% CI 0.35-0.82) and were 27% less likely to become cognitively impaired over a median follow-up of 7.8 years (adjusted hazard ratio 0.73, 95% CI 0.53-0.99). Female gender was also independently associated with lower odds of baseline cognitive impairment and lower risk of incident cognitive impairment. Conclusions: Familial longevity may confer exposure to genetic and environmental factors that predispose centenarian offspring to preservation of cognitive function at older ages. Centenarian offspring cohorts may provide an opportunity to study cognitive resilience associated with familial longevity.
Asunto(s)
Cognición/fisiología , Disfunción Cognitiva/epidemiología , Estado de Salud , Longevidad/genética , Factores de Edad , Anciano , Disfunción Cognitiva/genética , Disfunción Cognitiva/fisiopatología , Femenino , Estudios de Seguimiento , Humanos , Incidencia , Masculino , New England/epidemiología , Prevalencia , Estudios Prospectivos , Factores de Riesgo , Factores SexualesRESUMEN
We examine whether judgments of posterior probabilities in Bayesian reasoning problems are affected by reasoners' beliefs about corresponding real-world probabilities. In an internet-based task, participants were asked to determine the probability that a hypothesis is true (posterior probability, e.g., a person has a disease, given a positive medical test) based on relevant probabilities (e.g., that any person has the disease and the true and false positive rates of the test). We varied whether the correct posterior probability was close to, or far from, independent intuitive estimates of the corresponding 'real-world' probability. Responses were substantially closer to the correct posterior when this value was close to the intuitive estimate. A model in which the response is a weighted sum of the intuitive estimate and an additive combination of the probabilities provides an excellent account of the results.
