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.
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: K Korkeila; S Suominen; J Ahvenainen; A Ojanlatva; P Rautava; H Helenius; M Koskenvuo Journal: Eur J Epidemiol Date: 2001 Impact factor: 8.082
Authors: Sakari Suominen; Karoliina Koskenvuo; Lauri Sillanmäki; Jussi Vahtera; Katariina Korkeila; Mika Kivimäki; Kari J Mattila; Pekka Virtanen; Markku Sumanen; Päivi Rautava; Markku Koskenvuo Journal: BMJ Open Date: 2012-03-15 Impact factor: 2.692
Authors: Jean-Paul Chretien; Laura K Chu; Tyler C Smith; Besa Smith; Margaret A K Ryan Journal: BMC Med Res Methodol Date: 2007-01-25 Impact factor: 4.615
Authors: Brian Williams; Linda Irvine; Alison R McGinnis; Marion E T McMurdo; Iain K Crombie Journal: BMC Health Serv Res Date: 2007-04-26 Impact factor: 2.655
Authors: Fiona E Matthews; Mark Chatfield; Carol Freeman; Cherie McCracken; Carol Brayne Journal: BMC Public Health Date: 2004-04-27 Impact factor: 3.295