Nontraditional risk factors combine to predict Alzheimer disease and dementia

Neurology. 2011 Jul 19;77(3):227-34. doi: 10.1212/WNL.0b013e318225c6bc. Epub 2011 Jul 13.


Objective: To investigate whether dementia risk can be estimated using only health deficits not known to predict dementia.

Methods: A frailty index consisting of 19 deficits not known to predict dementia (the nontraditional risk factors index [FI-NTRF]) was constructed for 7,239 cognitively healthy, community-dwelling older adults in the Canadian Study of Health and Aging. From baseline, their 5-year and 10-year risks for Alzheimer disease (AD), dementia of all types, and survival were estimated.

Results: The FI-NTRF was closely correlated with age (r2 > 0.96, p < 0.001). The incidence of AD and dementia increased exponentially with the FI-NTRF (r2 > 0.75, p < 0.001 over 10 years). Adjusted for age, sex, education, and baseline cognition, the odds ratio of dementia increased by 3.2% (p = 0.021) for each deficit (that was not known to predict dementia) accumulated, outperforming the individual cognitive risk factors. The FI-NTRF discriminated people with AD and all-cause dementia from those who were cognitively healthy with an area under the receiver operating characteristic curve of 0.66 ± 0.03.

Conclusions: Comprehensive re-evaluation of a well-characterized cohort showed that age-associated decline in health status, in addition to traditional risk factors, is a risk factor for AD and dementia. General health may be an important confounder to consider in dementia risk factor evaluation. If a diverse range of deficits is associated with dementia, then improving general health might reduce dementia risk.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Alzheimer Disease / diagnosis*
  • Alzheimer Disease / epidemiology*
  • Canada / epidemiology
  • Cognition
  • Dementia / diagnosis*
  • Dementia / epidemiology*
  • Educational Status
  • Female
  • Humans
  • Incidence
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Retrospective Studies
  • Risk Factors