title: Measuring cognitive function with age: the influence of selection by health and survival.
abstract: BACKGROUND
  Research into the pathophysiology of age-associated cognitive function and decline requires a valid estimate of cognitive function. However, this estimation can be grossly influenced by a selective loss to follow-up.
  
  
  METHODS
  We investigated the influence of health selection on the estimated age-associated cognitive function and decline by studying the effect on this estimation of study design and of the handling of multiple and missing data. We used linear regression analyses and linear mixed models to assess cognitive function from cross-sectional and longitudinal data. Repeated measures of cognitive function (assessed with dedicated neuropsychological tests) were carried out in 2 independent population-based cohort studies: the Rotterdam Study (3719 participants; mean age 71 years) and the Leiden 85-plus Study (369 participants; age 85 years).
  
  
  RESULTS
  The effect of age on cognitive function was greater in cross-sectional analyses when all participants were included than when analyses were restricted to participants with repeated measurements. The decline in cognitive function over 4.6 years of follow-up was intermediate between the cross-sectional estimates from the total sample and from the restricted sample. Moreover, the estimated decline in cognitive function was larger when using a short follow-up than when using the complete follow-up over 5 years. The estimated decline using linear mixed models was similar to analyses including those with a complete follow-up over 5 years.
  
  
  CONCLUSIONS
  Selection for health and survival results in better age-specific cognitive test scores and less cognitive decline. Statistical methods handling multiple and missing data do not fully correct for this bias.
authors.affiliation: Department of Epidemiology and Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlandes.
authors.forename: Sjoerd M
authors.initials: SM
authors.lastname: Euser
authors.forename: Miranda T
authors.initials: MT
authors.lastname: Schram
authors.forename: Albert
authors.initials: A
authors.lastname: Hofman
authors.forename: Rudi G J
authors.initials: RG
authors.lastname: Westendorp
authors.forename: Monique M B
authors.initials: MM
authors.lastname: Breteler
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D003072:Cognition Disorders / Q000453:epidemiology / Q000503:physiopathology*; D003430:Cross-Sectional Studies; D018450:Disease Progression; D005260:Female; D015577:Geriatric Assessment; D006304:Health Status; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D009483:Neuropsychological Tests; D011446:Prospective Studies; D016019:Survival Analysis