title: Selection bias from sampling frames: telephone directory and electoral roll compared with door-to-door population census: results from the Blue Mountains Eye Study.
abstract: Many Australian public health research studies use the telephone directory or the electoral roll as a sampling frame from which to draw study subjects. The sociodemographic, disease-state and risk-factor characteristics of subjects who could be recruited using only the telephone directory or only the electoral roll sampling frames were compared with the characteristics of subjects who would have been missed using only these sampling frames, respectively. In the first phase of the Blue Mountains Eye Study we interviewed and examined 2557 people aged 49 and over living in a defined postcode area, recruited from a door-to-door census. This represented a participation rate of 80.9 per cent and a response rate of 87.9 per cent. The telephone directory was searched for each subject's telephone number and the electoral roll was searched for each subject. Subject characteristics for those who were present in each of these sampling frames were compared with the characteristics of those subjects not included in the sampling frames. The telephone directory listed 2102 (82.2 per cent) of the subjects, and 115 (4.5 per cent) had no telephone connected. The electoral roll contained 2156 (84.3 per cent) of the subjects, and 141 subjects (5.5 per cent) could not be found in either the electoral roll or the telephone directory. Younger subjects, subjects who did not own their own homes and subjects born outside of Australia were significantly less likely to be included in either of these sampling frames. The telephone directory was also more likely to exclude subjects with higher occupational prestige, while the electoral roll was more likely to exclude unmarried persons and males. Researchers using the telephone directory and electoral roll to select subjects for study should be aware of the potential selection bias these sampling frames incur and need to take care when generalising their findings to the wider community.
authors.affiliation: National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT.
authors.forename: W
authors.initials: W
authors.lastname: Smith
authors.forename: P
authors.initials: P
authors.lastname: Mitchell
authors.forename: K
authors.initials: K
authors.lastname: Attebo
authors.forename: S
authors.initials: S
authors.lastname: Leeder
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D019352:Censuses; D016009:Chi-Square Distribution; D016001:Confidence Intervals; D003625:Data Collection / Q000379:methods*; D016208:Databases, Factual; D005260:Female; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009517:New South Wales; D015983:Selection Bias; D013689:Telephone