title: Random sample community-based health surveys: does the effort to reach participants matter?
abstract: OBJECTIVE
  Conducting health surveys with community-based random samples are essential to capture an otherwise unreachable population, but these surveys can be biased if the effort to reach participants is insufficient. This study determines the desirable amount of effort to minimise such bias.
  
  
  METHODS
  A household-based health survey with random sampling and face-to-face interviews. Up to 11 visits, organised by canvassing rounds, were made to obtain an interview.
  
  
  METHODS
  Single-family homes in an underserved and understudied population in North Miami-Dade County, Florida, USA.
  
  
  METHODS
  Of a probabilistic sample of 2200 household addresses, 30 corresponded to empty lots, 74 were abandoned houses, 625 households declined to participate and 265 could not be reached and interviewed within 11 attempts. Analyses were performed on the 1206 remaining households.
  
  
  METHODS
  Each household was asked if any of their members had been told by a doctor that they had high blood pressure, heart disease including heart attack, cancer, diabetes, anxiety/ depression, obesity or asthma. Responses to these questions were analysed by the number of visit attempts needed to obtain the interview.
  
  
  RESULTS
  Return per visit fell below 10% after four attempts, below 5% after six attempts and below 2% after eight attempts. As the effort increased, household size decreased, while household income and the percentage of interviewees active and employed increased; proportion of the seven health conditions decreased, four of which did so significantly: heart disease 20.4-9.2%, high blood pressure 63.5-58.1%, anxiety/depression 24.4-9.2% and obesity 21.8-12.6%. Beyond the fifth attempt, however, cumulative percentages varied by less than 1% and precision varied by less than 0.1%.
  
  
  CONCLUSIONS
  In spite of the early and steep drop, sustaining at least five attempts to reach participants is necessary to reduce selection bias.
authors.affiliation: INSERM Research Unit U-1178, "Mental Health and Public Health", Hôpital Paul Brousse, Villejuif, France.
authors.forename: Antoine
authors.initials: A
authors.lastname: Messiah
authors.affiliation: Department of Medical and Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida, USA.
authors.forename: Grettel
authors.initials: G
authors.lastname: Castro
authors.affiliation: Department of Medical and Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida, USA.
authors.forename: Pura
authors.initials: P
authors.lastname: Rodríguez de la Vega
authors.affiliation: Department of Medical and Health Sciences Research, Herbert Wertheim College of Medicine, Florida International University, Miami, Florida, USA.
authors.forename: Juan M
authors.initials: JM
authors.lastname: Acuna
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000453:epidemiology; D005191:Family Characteristics; D005260:Female; D005431:Florida / Q000453:epidemiology; D006262:Health / Q000706:statistics & numerical data*; D006304:Health Status; D006306:Health Surveys / Q000379:methods* / Q000592:standards; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D001523:Mental Disorders / Q000453:epidemiology; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology; D015995:Prevalence; D012111:Residence Characteristics; D015983:Selection Bias; D012959:Socioeconomic Factors
keywords: EPIDEMIOLOGY; PUBLIC HEALTH; STATISTICS & RESEARCH METHODS