The socio-economic patterning of survey participation and non-response error in a multilevel study of food purchasing behaviour: area- and individual-level characteristics.
OBJECTIVE
To undertake an assessment of survey participation and non-response error in a population-based study that examined the relationship between socio-economic position and food purchasing behaviour.


METHODS
The study was conducted in Brisbane City (Australia) in 2000. The sample was selected using a stratified two-stage cluster design. Respondents were recruited using a range of strategies that attempted to maximise the involvement of persons from disadvantaged backgrounds: respondents were contacted by personal visit and data were collected using home-based face-to-face interviews; multiple call-backs on different days and at different times were used; and a financial gratuity was provided.


METHODS
Non-institutionalised residents of private dwellings located in 50 small areas that differed in their socio-economic characteristics.


RESULTS
Rates of survey participation - measured by non-contacts, exclusions, dropped cases, response rates and completions - were similar across areas, suggesting that residents of socio-economically advantaged and disadvantaged areas were equally likely to be recruited. Individual-level analysis, however, showed that respondents and non-respondents differed significantly in their sociodemographic and food purchasing characteristics: non-respondents were older, less educated and exhibited different purchasing behaviours. Misclassification bias probably accounted for the inconsistent pattern of association between the area- and individual-level results. Estimates of bias due to non-response indicated that although respondents and non-respondents were qualitatively different, the magnitude of error associated with this differential was minimal.


CONCLUSIONS
Socio-economic position measured at the individual level is a strong and consistent predictor of survey non-participation. Future studies that set out to examine the relationship between socio-economic position and diet need to adopt sampling strategies and data collection methods that maximise the likelihood of recruiting participants from all points on the socio-economic spectrum, and particularly persons from disadvantaged backgrounds. Study designs that are not sensitive to the difficulties associated with recruiting a socio-economically representative sample are likely to produce biased estimates (underestimates) of socio-economic differences in the dietary outcome being investigated.
Turrell
Gavin
G
Queensland University of Technology, School of Public Health, Victoria Park Road, Kelvin Grove, Queensland 4059. g.turrell@qut.edu.au
Patterson
Carla
C
Oldenburg
Brian
B
Gould
Trish
T
Roy
Marie-Andree
MA
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001519:Behavior; D016000:Cluster Analysis; D003625:Data Collection / Q000379:methods; D003710:Demography; D004032:Diet; D005260:Female; D005518:Food Preferences; D006801:Humans; D008297:Male; D008875:Middle Aged; D011793:Queensland; D018401:Sample Size; D012494:Sampling Studies; D012923:Social Class; D012959:Socioeconomic Factors