title: Effect on trend estimates of the difference between survey respondents and non-respondents: results from 27 populations in the WHO MONICA Project.
abstract: BACKGROUND
  In the World Health Organization (WHO) MONICA (multinational MONItoring of trends and determinants in CArdiovascular disease) Project considerable effort was made to obtain basic data on non-respondents to community based surveys of cardiovascular risk factors. The first purpose of this paper is to examine differences in socio-economic and health profiles among respondents and non-respondents. The second purpose is to investigate the effect of non-response on estimates of trends.
  
  
  METHODS
  Socio-economic and health profile between respondents and non-respondents in the WHO MONICA Project final survey were compared. The potential effect of non-response on the trend estimates between the initial survey and final survey approximately ten years later was investigated using both MONICA data and hypothetical data.
  
  
  RESULTS
  In most of the populations, non-respondents were more likely to be single, less well educated, and had poorer lifestyles and health profiles than respondents. As an example of the consequences, temporal trends in prevalence of daily smokers are shown to be overestimated in most populations if they were based only on data from respondents.
  
  
  CONCLUSIONS
  The socio-economic and health profiles of respondents and non-respondents differed fairly consistently across 27 populations. Hence, the estimators of population trends based on respondent data are likely to be biased. Declining response rates therefore pose a threat to the accuracy of estimates of risk factor trends in many countries.
authors.affiliation: Department of Epidemiology and Health Promotion, National Public Health Institute (KTL), Mannerheimintie 166, FIN-00300 Helsinki, Finland. hanna.tolonen@ktl.fi
authors.forename: Hanna
authors.initials: H
authors.lastname: Tolonen
authors.forename: Annette
authors.initials: A
authors.lastname: Dobson
authors.forename: Sangita
authors.initials: S
authors.lastname: Kulathinal
mesh_terms: D015982:Bias; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D003625:Data Collection / Q000706:statistics & numerical data* / Q000639:trends*; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D012307:Risk Factors; D012959:Socioeconomic Factors; D014944:World Health Organization