Responders versus nonresponders in a dementia study of the oldest old: the 90+ study

Am J Epidemiol. 2013 Jun 15;177(12):1452-8. doi: 10.1093/aje/kws424. Epub 2013 Apr 7.


Because of difficulties in finding, recruiting, and diagnosing dementia in the oldest old (ages ≥90 years), most incidence studies include few very elderly persons, and little is known about the characteristics of those who refuse participation. In a California longitudinal study of dementia and aging (The 90+ Study, 2003-2011), we compared nonresponders with responders with regard to information collected 20 years earlier and the impression of dementia as determined during telephone recruitment. Of 1,815 eligible subjects, 1,514 (83%) joined the study, 182 refused, and 119 could not be contacted. Responders did not differ from nonresponders by sex or previously collected medical history or lifestyle behaviors. Recruiters' impressions of dementia were similar in responders and nonresponders who refused (35% and 38%), and among responders, impressions of dementia showed high positive predictive value (95%) but low sensitivity (51%) for a diagnosis of dementia made during the study. Although epidemiologic studies among the very old have the potential for significant nonresponse bias due to a high proportion of frail, ill, and cognitively impaired persons, strategies can improve response rates to over 80%. Classifying nonresponders on cognitive ability at recruitment, though crude, will give some idea of the selective bias in dementia prevalence and incidence estimates introduced by nonresponse due to cognitive status.

Keywords: aged; bias; cohort studies; dementia; epidemiologic methods; refusal to participate.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged, 80 and over
  • California
  • Comorbidity
  • Data Collection / statistics & numerical data*
  • Dementia / epidemiology*
  • Female
  • Health Behavior
  • Health Status
  • Humans
  • Longitudinal Studies
  • Male
  • Prevalence
  • Selection Bias*
  • Socioeconomic Factors