BACKGROUND: The types and quantity of non-response in surveys influence the extent to which the results may be generalized. This study analysed trends in non-response in the Danish Health Interview Surveys from 1987 to 1994 and used the National Patient Registry to assess whether non-response biased the estimated population prevalence of morbidity when solely based on responders. METHODS: The data were for the 23,096 adults sampled for the Danish Health Interview Surveys in 1987, 1991 and 1994. All were followed using the National Patient Registry to obtain such information as hospital admissions. RESULTS: Non-response increased from 20.0% in 1987 to 22.6% in 1994. Four combinations of background variables characterized the non-response: gender and age; gender and civil status; county of residence and age; survey year and age. Non-respondents and respondents had identical gender- and age-standardized hospital admission rates for approximately 5 years before and 2 years after data collection, but non-respondents had a significantly higher rate immediately before and during data collection. Admissions rates were analysed according to reasons for non-response. Refusers had a lower admission rate than respondents before data collection but similar during and after data collection. The rate was higher during the whole period among ill or disabled non-respondents. Among people who could not be contacted during the data collection period a higher admission rate was only found immediately before and during data collection. CONCLUSIONS: Although admission rates differed between respondents and non-respondents these differences were too small to bias the estimated population prevalence of morbidity when solely based on respondents.
BACKGROUND: The types and quantity of non-response in surveys influence the extent to which the results may be generalized. This study analysed trends in non-response in the Danish Health Interview Surveys from 1987 to 1994 and used the National Patient Registry to assess whether non-response biased the estimated population prevalence of morbidity when solely based on responders. METHODS: The data were for the 23,096 adults sampled for the Danish Health Interview Surveys in 1987, 1991 and 1994. All were followed using the National Patient Registry to obtain such information as hospital admissions. RESULTS: Non-response increased from 20.0% in 1987 to 22.6% in 1994. Four combinations of background variables characterized the non-response: gender and age; gender and civil status; county of residence and age; survey year and age. Non-respondents and respondents had identical gender- and age-standardized hospital admission rates for approximately 5 years before and 2 years after data collection, but non-respondents had a significantly higher rate immediately before and during data collection. Admissions rates were analysed according to reasons for non-response. Refusers had a lower admission rate than respondents before data collection but similar during and after data collection. The rate was higher during the whole period among ill or disabled non-respondents. Among people who could not be contacted during the data collection period a higher admission rate was only found immediately before and during data collection. CONCLUSIONS: Although admission rates differed between respondents and non-respondents these differences were too small to bias the estimated population prevalence of morbidity when solely based on respondents.
Authors: Vibeke Koushede; Ola Ekholm; Bjørn E Holstein; Anette Andersen; Ebba Holme Hansen Journal: Int J Public Health Date: 2010-09-01 Impact factor: 3.380
Authors: Adrian P Mundt; Marion C Aichberger; Thomas Kliewe; Yuriy Ignatyev; Seda Yayla; Hannah Heimann; Meryam Schouler-Ocak; Markus Busch; Michael Rapp; Andreas Heinz; Andreas Ströhle Journal: Community Ment Health J Date: 2012-12
Authors: Carlos H Martinez; Swetha Raparla; Craig A Plauschinat; Nicholas D Giardino; Barbara Rogers; Julien Beresford; Judith D Bentkover; Amy Schachtner-Appel; Jeffrey L Curtis; Fernando J Martinez; MeiLan K Han Journal: J Womens Health (Larchmt) Date: 2012-12 Impact factor: 2.681
Authors: Anna Oksuzyan; Inge Petersen; Henrik Stovring; Paul Bingley; James W Vaupel; Kaare Christensen Journal: Ann Epidemiol Date: 2009-05-19 Impact factor: 3.797