Factors influencing attrition in 35 Alzheimer's Disease Centers across the USA: a longitudinal examination of the National Alzheimer's Coordinating Center's Uniform Data Set

Aging Clin Exp Res. 2019 Sep;31(9):1283-1297. doi: 10.1007/s40520-018-1087-6. Epub 2018 Dec 10.


Objective: A lack of understanding of the causes of attrition in longitudinal studies of older adults may lead to higher attrition rates and bias longitudinal study results. In longitudinal epidemiological studies of Alzheimer's disease and related dementias, high rates of attrition may cause a systematic underestimation of dementia prevalence and skew the characterization of the disease. This can compromise the generalizability of the study results and any inferences based on the surviving sample may grossly misrepresent the importance of the risk factors for dementia. The National Institute on Aging outlined a National Strategy for Recruitment and Participation in Alzheimer's Disease Clinical Research to address this problem, providing evidence of the magnitude of this problem.

Method: To explore predictors of attrition, this study examined the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, a repository of observations of older adults spanning 11 years, using survival analysis. Four samples were examined: the full sample (n = 30,433), the alive subsample excluding those who died (n = 24,231), the MRI sample [participants with complete MRI data (n = 1104)], and the alive MRI subsample [participants with MRI data excluding those who died (n = 947)].

Results: Worsening cognitive impairment, neuropsychiatric symptoms, and difficulty with functional activities predicted attrition, as did lower hippocampal volume in the MRI subsample. Questionable co-participant reliability and an informant other than a spouse also increased risk of attrition.

Discussion: Special considerations exist in recruiting and retaining older adults in longitudinal studies, and results of baseline psychological, functional, and cognitive functioning should be used to identify targeted retention strategies.

Keywords: Alzheimer’s disease; Attrition; Dementia; Dropout; Functional difficulties; Hippocampal volume; Longitudinal study; Neuropsychiatric symptoms.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Alzheimer Disease* / mortality
  • Alzheimer Disease* / physiopathology
  • Cognitive Dysfunction / psychology
  • Datasets as Topic
  • Disease Progression*
  • Female
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Patient Dropouts / statistics & numerical data*
  • Proportional Hazards Models
  • Reproducibility of Results
  • Risk Factors