title: Cognitive lifestyle jointly predicts longitudinal cognitive decline and mortality risk.
abstract: Cognitive lifestyle measures such as education, occupation, and social engagement are commonly associated with late-life cognitive ability although their associations with cognitive decline tend to be mixed. However, longitudinal analyses of cognition rarely account for death and dropout, measurement error of the cognitive phenotype, and differing trajectories for different population sub-groups. This paper applies a joint latent class mixed model (and a multi-state model in a sensitivity analysis) that accounts for these issues to a large (n = 3,653), population-based cohort, Paquid, to model the relationship between cognitive lifestyle and cognitive decline. Cognition was assessed over a 20-year period using the Mini-Mental State Examination. Three cognitive lifestyle variables were assessed: education, mid-life occupation, and late-life social engagement. The analysis identified four latent sub-populations with class-specific longitudinal cognitive decline and mortality risk. Irrespective of the cognitive trajectory, increased social engagement was associated with a decreased mortality risk. High education was associated with the most favourable cognitive trajectory, and after adjusting for cognitive decline, with an increased mortality risk. Mid-life occupational complexity was also associated with more favourable trajectories but not with mortality risk. To realistically examine the link between cognitive lifestyle and cognitive decline, complex statistical models are required. This paper applies and compares in a sensitivity analysis two such models, and shows education to be linked to a compression of cognitive morbidity irrespective of cognitive trajectory. Furthermore, a potentially modifiable variable, late-life social engagement is associated with a decreased mortality risk in all of the population sub-groups.
authors.affiliation: Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB2 0SR, UK, riccardo.marioni@ed.ac.uk.
authors.forename: Riccardo E
authors.initials: RE
authors.lastname: Marioni
authors.forename: Cecile
authors.initials: C
authors.lastname: Proust-Lima
authors.forename: Helene
authors.initials: H
authors.lastname: Amieva
authors.forename: Carol
authors.initials: C
authors.lastname: Brayne
authors.forename: Fiona E
authors.initials: FE
authors.lastname: Matthews
authors.forename: Jean-Francois
authors.initials: JF
authors.lastname: Dartigues
authors.forename: Helene
authors.initials: H
authors.lastname: Jacqmin-Gadda
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D003071:Cognition / Q000502:physiology*; D003072:Cognition Disorders / Q000175:diagnosis / Q000401:mortality* / Q000523:psychology*; D004522:Educational Status; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D008019:Life Style; D008297:Male; D008609:Mental Status Schedule; D015233:Models, Statistical; D009483:Neuropsychological Tests; D009790:Occupations; D011237:Predictive Value of Tests; D012307:Risk Factors