Literature DB >> 10432911

A population comparison of participants and nonparticipants in a health survey.

R C Klesges1, J E Williamson, G W Somes, G W Talcott, H A Lando, C K Haddock.   

Abstract

OBJECTIVES: This study examined the characteristics of Air Force recruits willing to take part in a health survey vs those unwilling to participate.
METHODS: US Air Force recruits undergoing basic military training (n = 32,144) were surveyed regarding demographic and health variables.
RESULTS: Respondents indicating an unwillingness to participate in a health survey reported less healthy lifestyles than those willing to participate. Prediction equations modeling the characteristics of those engaging in 4 risky behaviors were nearly identical regardless of whether those refusing to participate were included.
CONCLUSIONS: Results suggest that, despite some low estimates of health behaviors due to response bias, relationships between most risk factors are generally unaffected by those not responding to health surveys.

Entities:  

Mesh:

Year:  1999        PMID: 10432911      PMCID: PMC1508706          DOI: 10.2105/ajph.89.8.1228

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  8 in total

1.  Demographic characteristics and health behaviours of consenters to medical examination. Results from the Welsh Heart Health Survey.

Authors:  E Pullen; D Nutbeam; L Moore
Journal:  J Epidemiol Community Health       Date:  1992-08       Impact factor: 3.710

2.  Characteristics of self-selected responders to a health risk appraisal: generalizability of corporate health assessments.

Authors:  W D Lynch; T J Golaszewski; A Clearie; D M Vickery
Journal:  Am J Public Health       Date:  1989-07       Impact factor: 9.308

3.  The Swedish Health-Related Quality of Life Survey (SWED-QUAL).

Authors:  B Brorsson; J Ifver; R D Hays
Journal:  Qual Life Res       Date:  1993-02       Impact factor: 4.147

4.  Generalizability of valuations on health states collected with the EuroQolc-questionnaire.

Authors:  M L Essink-Bot; M E Stouthard; G J Bonsel
Journal:  Health Econ       Date:  1993-10       Impact factor: 3.046

5.  Non-response in a population study after an environmental disaster.

Authors:  K Foster; D Campbell; J Crum; M Stove
Journal:  Public Health       Date:  1995-07       Impact factor: 2.427

6.  Differences in the characteristics of responders and non-responders in a prevalence survey of vertebral osteoporosis. European Vertebral Osteoporosis Study Group.

Authors:  T W O'Neill; D Marsden; A J Silman
Journal:  Osteoporos Int       Date:  1995       Impact factor: 4.507

7.  Survey response rates: national and regional differences in a European multicentre study of vertebral osteoporosis.

Authors:  T W O'Neill; D Marsden; C Matthis; H Raspe; A J Silman
Journal:  J Epidemiol Community Health       Date:  1995-02       Impact factor: 3.710

8.  Baseline characteristics are not sufficient indicators of non-response bias follow up studies.

Authors:  J Vestbo; F V Rasmussen
Journal:  J Epidemiol Community Health       Date:  1992-12       Impact factor: 3.710

  8 in total
  14 in total

1.  Subgroups of refusers in a disability prevention trial in older adults: baseline and follow-up analysis.

Authors:  Christoph E Minder; Tobias Müller; Gerhard Gillmann; John C Beck; Andreas E Stuck
Journal:  Am J Public Health       Date:  2002-03       Impact factor: 9.308

2.  Programmatic influences on outcomes of an evidence-based fall prevention program for older adults: a translational assessment.

Authors:  Matthew Lee Smith; Angela K Hochhalter; Yichen Cheng; Suojin Wang; Marcia G Ory
Journal:  Transl Behav Med       Date:  2011-09       Impact factor: 3.046

3.  High prevalence of undiagnosed diabetes mellitus in Southern Germany: target populations for efficient screening. The KORA survey 2000.

Authors:  W Rathmann; B Haastert; A Icks; H Löwel; C Meisinger; R Holle; G Giani
Journal:  Diabetologia       Date:  2003-02-18       Impact factor: 10.122

4.  Non-participation and mortality in different socioeconomic groups: the FINRISK population surveys in 1972-92.

Authors:  Kennet Harald; Veikko Salomaa; Pekka Jousilahti; Seppo Koskinen; Erkki Vartiainen
Journal:  J Epidemiol Community Health       Date:  2007-05       Impact factor: 3.710

5.  Predictors of participation and attrition in a health promotion study involving psychiatric outpatients.

Authors:  Peter A Vanable; Michael P Carey; Kate B Carey; Stephen A Maisto
Journal:  J Consult Clin Psychol       Date:  2002-04

6.  Beta-blocker use and risk of fractures in men and women from the general population: the MONICA/KORA Augsburg cohort study.

Authors:  C Meisinger; M Heier; O Lang; A Döring
Journal:  Osteoporos Int       Date:  2007-03-01       Impact factor: 4.507

7.  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

8.  Comparison of participants and non-participants to the ORISCAV-LUX population-based study on cardiovascular risk factors in Luxembourg.

Authors:  Ala'a Alkerwi; Nicolas Sauvageot; Sophie Couffignal; Adelin Albert; Marie-Lise Lair; Michèle Guillaume
Journal:  BMC Med Res Methodol       Date:  2010-09-07       Impact factor: 4.615

9.  Occupational mobility and risk factors in working men: selection, causality or both? Results from the GAZEL study.

Authors:  C Ribet; M Zins; A Gueguen; A Bingham; M Goldberg; P Ducimetière; T Lang
Journal:  J Epidemiol Community Health       Date:  2003-11       Impact factor: 3.710

10.  Evaluation of a digital health resource providing physiotherapy information for postnatal women in a tertiary public hospital in Australia.

Authors:  Kate Goode
Journal:  Mhealth       Date:  2018-09-26
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