Literature DB >> 9694185

Morbidity in responders and non-responders in a register-based population survey.

M van den Akker1, F Buntinx, J F Metsemakers, J A Knottnerus.   

Abstract

BACKGROUND: Non-response analysis is often restricted to the influence of age, sex and socio-economic status on response status. In this study the health status of responders and non-responders was also compared.
RESULTS: Responders were comparable to non-responders with regard to the number of diagnosed disorders as well as to the prevalences of disorders within body systems. Non-responders only showed psychological disorders more often.
CONCLUSION: It is useful to assess the relation between non-response and morbidity patterns in other studies as well, in order to detect selective non-response and bias.

Entities:  

Mesh:

Year:  1998        PMID: 9694185     DOI: 10.1093/fampra/15.3.261

Source DB:  PubMed          Journal:  Fam Pract        ISSN: 0263-2136            Impact factor:   2.267


  14 in total

1.  Non-response and related factors in a nation-wide health survey.

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

2.  A demonstration of the impact of response bias on the results of patient satisfaction surveys.

Authors:  Kathleen M Mazor; Brian E Clauser; Terry Field; Robert A Yood; Jerry H Gurwitz
Journal:  Health Serv Res       Date:  2002-10       Impact factor: 3.402

3.  Investigating Respondents and Nonrespondents of a Postal Breast Cancer Questionnaire Survey Regarding Differences in Age, Medical Conditions, and Therapy.

Authors:  Anna L Frobeen; Christoph Kowalski; Verena Weiß; Holger Pfaff
Journal:  Breast Care (Basel)       Date:  2016-04-27       Impact factor: 2.860

4.  Baseline recruitment and analyses of nonresponse of the Heinz Nixdorf Recall Study: identifiability of phone numbers as the major determinant of response.

Authors:  A Stang; S Moebus; N Dragano; E M Beck; S Möhlenkamp; A Schmermund; J Siegrist; R Erbel; K H Jöckel
Journal:  Eur J Epidemiol       Date:  2005       Impact factor: 8.082

5.  Health and demographic characteristics of respondents in an Australian national sexuality survey: comparison with population norms.

Authors:  D M Purdie; M P Dunne; F M Boyle; M D Cook; J M Najman
Journal:  J Epidemiol Community Health       Date:  2002-10       Impact factor: 3.710

6.  The male-female health-survival paradox: a survey and register study of the impact of sex-specific selection and information bias.

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

Review 7.  Men: good health and high mortality. Sex differences in health and aging.

Authors:  Anna Oksuzyan; Knud Juel; James W Vaupel; Kaare Christensen
Journal:  Aging Clin Exp Res       Date:  2008-04       Impact factor: 3.636

8.  Non-response in a nationwide follow-up postal survey in Finland: a register-based mortality analysis of respondents and non-respondents of the Health and Social Support (HeSSup) Study.

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

9.  Non response, incomplete and inconsistent responses to self-administered health-related quality of life measures in the general population: patterns, determinants and impact on the validity of estimates - a population-based study in France using the MOS SF-36.

Authors:  Joel Coste; Laurent Quinquis; Etienne Audureau; Jacques Pouchot
Journal:  Health Qual Life Outcomes       Date:  2013-03-13       Impact factor: 3.186

10.  When "no" might not quite mean "no"; the importance of informed and meaningful non-consent: results from a survey of individuals refusing participation in a health-related research project.

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

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