title: Cancer patients' participation in population-based health surveys: findings from the HUNT studies.
abstract: BACKGROUND
  The magnitude of participation bias due to non-participation should be considered for cancer patients invited to population-based surveys. We studied participation rates among persons with and without cancer in a large population based study, the Nord-Trøndelag Health Study (HUNT).
  
  
  METHODS
  Citizens 20 years or above living in the Nord-Trøndelag County of Norway have been invited three times to comprehensive health surveys. The invitation files with data on sex, invitation date and participation were linked to the Cancer Registry of Norway. In a first step unadjusted crude participation rates (participants/invited persons) were estimated for cancer patients (CaPts) and non-cancer persons (NonCaPers), followed by logistic regression analyses with adjustment for age and sex. To evaluate the "practical" significance of the estimated odds ratios in the cancer diagnosis group, relative risks were also estimated comparing the observed rates to the estimated rates under the counterfactual assumption of no earlier cancer diagnosis among CaPts.
  
  
  RESULTS
  Overall 3 % of the participants in the three HUNT studies were CaPts and 59 % of them had been diagnosed with their first life-time cancer >5 years prior to each survey. In each of the three HUNT surveys crude participation rates were similar for CaPts and NonCaPers. Adjusted for sex and age, CaPts' likelihood to participate in HUNT1 (1984-86) and HUNT2 (1995-97), but not in HUNT3 (2006-2008), was statistically significantly reduced compared to NonCaPers, equaling a relative risk of 0.98 and 0.96, respectively. The lowest odds ratio emerged for CaPts diagnosed during the last 2 years preceding a HUNT invitation. Only one-third of CaPts participating in a survey also participated in the subsequent survey compared to approximately two-thirds of NonCaPers, and 11 % of CaPts participated in all three HUNT surveys compared to 37 % of NonCaPers.
  
  
  CONCLUSIONS
  In the three HUNT surveys no or only minor participation bias exist as to CaPts' participation rates. In longitudinal studies selection bias as to long-term cancer survivorship should be taken into account, the percentage of repeatedly participating CaPts diminishing more strongly than among NonCaPers.
authors.affiliation: National Advisory Unit for Late Effects after Cancer Therapy, Oslo University Hospital, Radium Hospitalet and Cancer Registry of Norway, P.O.Box 4953, Nydalen, 0424, Oslo, Norway. sdf@ous-hf.no.|Faculty of medicine, University of Oslo, Oslo, Norway. sdf@ous-hf.no.
authors.forename: Sophie D
authors.initials: SD
authors.lastname: Fosså
authors.affiliation: National Advisory Unit for Late Effects after Cancer Therapy, Oslo University Hospital, Radium Hospitalet and Cancer Registry of Norway, P.O.Box 4953, Nydalen, 0424, Oslo, Norway. a.a.dahl@ibv.uio.no.|Faculty of medicine, University of Oslo, Oslo, Norway. a.a.dahl@ibv.uio.no.
authors.forename: Alv A
authors.initials: AA
authors.lastname: Dahl
authors.affiliation: HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway. Arnulf.Langhammer@ntnu.no.
authors.forename: Arnulf
authors.initials: A
authors.lastname: Langhammer
authors.affiliation: Oslo Center for Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway. Harald.Weedon-Fekjar@medisin.uio.no.
authors.forename: Harald
authors.initials: H
authors.lastname: Weedon-Fekjær
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006306:Health Surveys / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D009664:Norway / Q000453:epidemiology; D010358:Patient Participation / Q000706:statistics & numerical data*; D012042:Registries / Q000706:statistics & numerical data; D012737:Sex Factors; D055815:Young Adult