title: Can the accuracy of health behaviour surveys be improved by non-response follow-ups?
abstract: BACKGROUND
  Prevalence estimates may be biased if the characteristics of respondents differ from those of non-respondents in surveys. In this study, we used a follow-up telephone interview of initial non-respondents to examine the differences--in terms of self-rated health and health behaviours--to initial postal respondents and to assess improvements in prevalence estimates.
  
  
  METHODS
  Following a postal questionnaire survey using a random sample (n = 5000) of the Finnish working-age population with a response rate of 57% (n = 2826), a follow-up telephone survey was performed based on 1261 non-respondents (response rate 56%, n = 708) in 2010. Prevalence of smoking, alcohol use, body mass index, physical activity, self-rated fitness, dietary habits and self-rated health were calculated for the survey population with and without a telephone interview. Logistic regression models were used to examine differences in health behaviours and health between the initial postal questionnaire respondents and follow-up telephone interview respondents.
  
  
  RESULTS
  The total response rate increased from 57% to 71% when the telephone respondents were included. The telephone survey indicated that both male and female telephone respondents were more often smokers, and female telephone respondents were more often heavy episodic drinkers and less often reported poor self-rated fitness than postal respondents. Nonetheless, the prevalence rates of outcome variables did not change significantly when telephone respondents were included.
  
  
  CONCLUSIONS
  The response rate of surveys can be increased by using a telephone survey in follow-up contacts with non-respondents. As non-respondents differ from respondents, this contributes to an improvement--although small--in internal validity.
authors.affiliation: 1 Department of Lifestyle and Participation, National Institute for Health and Welfare (THL) satu.helakorpi@thl.fi.
authors.forename: Satu
authors.initials: S
authors.lastname: Helakorpi
authors.affiliation: 2 Department of Alcohol, Drugs and Addiction, THL.
authors.forename: Pia
authors.initials: P
authors.lastname: Mäkelä
authors.affiliation: 3 Hjelt Institute, University of Helsinki.
authors.forename: Ansku
authors.initials: A
authors.lastname: Holstila
authors.affiliation: 1 Department of Lifestyle and Participation, National Institute for Health and Welfare (THL).
authors.forename: Antti
authors.initials: A
authors.lastname: Uutela
authors.affiliation: 4 Division of Welfare and Health Promotion, THL.
authors.forename: Erkki
authors.initials: E
authors.lastname: Vartiainen
mesh_terms: D000293:Adolescent; D000328:Adult; D000428:Alcohol Drinking / Q000453:epidemiology; D015992:Body Mass Index; D004032:Diet / Q000379:methods / Q000706:statistics & numerical data; D015444:Exercise; D005260:Female; D005387:Finland / Q000453:epidemiology; D005500:Follow-Up Studies; D015438:Health Behavior; D006304:Health Status; D006306:Health Surveys / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D010809:Physical Fitness; D011177:Postal Service; D015203:Reproducibility of Results; D012907:Smoking / Q000453:epidemiology; D011795:Surveys and Questionnaires / Q000592:standards*; D055815:Young Adult