title: Characteristics of non-responders and the impact of non-response on prevalence estimates of dementia.
abstract: BACKGROUND
  Differential distributions of sociodemographic characteristics and cognitive impairment in responders and non-responders may result in a biased prevalence estimate of dementia based on responders only.
  
  
  METHODS
  Responders (n = 2191) to a cross-sectional, two-stage community study were compared with regard to sociodemographic characteristics and cognition with three subgroups of non-responders: (A) subjects who refused to participate (n = 369), (B) subjects who were too ill or who had died prior to the screening (n = 72) and (C) subjects who had moved out of the study region or were not traceable (n = 23). Prevalence estimates specific for age and housing situation in responders and physicians' ratings of cognitive impairment were used to estimate the prevalence of dementia among non-responders.
  
  
  RESULTS
  Group A differed from responders in age and housing situation, group B in age, housing and cognition, and group C only in age. Separate prevalence estimates of dementia based on age, housing and cognition yielded figures for group A between 4.9% and 7.2%, for group B between 13.1% and 19.1%, and for group C between 2.6% and 4.2%. Joined with the prevalence rate among responders (6.5%) the best possible point estimate of the prevalence of dementia in the target population lies between 6.4% and 6.9%, i.e. within the 95% confidence interval (CI) of the prevalence among responders (5.4-7.5%).
  
  
  CONCLUSIONS
  Although in this study non-response had no important influence on the overall prevalence, the findings among the distinct non-response subgroups point to the importance of describing non-response sociodemographically as well as in terms of the study objective. The authors recommend that non-responders are categorized into distinct groups based on the reason for non-response.
authors.affiliation: Nursing Home Anna Schotanus, Heerenveen, The Netherlands.
authors.forename: F
authors.initials: F
authors.lastname: Boersma
authors.forename: J A
authors.initials: JA
authors.lastname: Eefsting
authors.forename: W
authors.initials: W
authors.lastname: van den Brink
authors.forename: W
authors.initials: W
authors.lastname: van Tilburg
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D016001:Confidence Intervals; D003430:Cross-Sectional Studies; D003704:Dementia / Q000175:diagnosis / Q000453:epidemiology*; D005260:Female; D006306:Health Surveys; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D015999:Multivariate Analysis; D009426:Netherlands / Q000453:epidemiology; D010349:Patient Compliance; D011237:Predictive Value of Tests; D015995:Prevalence; D012307:Risk Factors; D012423:Rural Health / Q000706:statistics & numerical data; D017678:Sex Distribution; D012959:Socioeconomic Factors