The impact of non-response bias due to sampling in public health studies: A comparison of voluntary versus mandatory recruitment in a Dutch national survey on adolescent health

• Published in: BMC public health Vol. 17; no. 1; pp. 276 - 10
• Main Authors: Cheung, Kei Long, ten Klooster, Peter M., Smit, Cees, de Vries, Hein, Pieterse, Marcel E.
• Format: Journal Article
• Language: English
• Published: England BioMed Central 23.03.2017; BMC
• Subjects: Adolescent; Adolescent Behavior; Adolescent Health - statistics & numerical data; Adolescents; Alcohol; Behavior; Bias; Childrens health; Community health care; Cross-Sectional Studies; Demographics; Drug abuse; Drug use; Education; Female; health behaviour; Health surveys; Humans; Logistic Models; Male; Mental health; Multivariable control; Municipalities; Netherlands - epidemiology; Non-response; Participation; Patient Selection; Polls & surveys; Population; Prevalence; Public health; Recruitment; Regression analysis; Response bias; Response rates; Risk analysis; Risk Factors; Risk taking; Sampling; sampling bias; Sampling methods; Schools; Sexual behavior; Sexual intercourse; Smoking; Studies; Substance-Related Disorders - epidemiology; Surveys and Questionnaires; Teenagers; Tobacco; Variables; Well being; Young Adult; Young adults; Netherlands; health behaviour; sampling bias; adolescents; recruitment; Non-response
• DOI: 10.1186/s12889-017-4189-8
• ISSN: 1471-2458

In public health monitoring of young people it is critical to understand the effects of selective non-response, in particular when a controversial topic is involved like substance abuse or sexual behaviour. Research that is dependent upon voluntary subject participation is particularly vulnerable to sampling bias. As respondents whose participation is hardest to elicit on a voluntary basis are also more likely to report risk behaviour, this potentially leads to underestimation of risk factor prevalence. Inviting adolescents to participate in a home-sent postal survey is a typical voluntary recruitment strategy with high non-response, as opposed to mandatory participation during school time. This study examines the extent to which prevalence estimates of adolescent health-related characteristics are biased due to different sampling methods, and whether this also biases within-subject analyses. Cross-sectional datasets collected in 2011 in Twente and IJsselland, two similar and adjacent regions in the Netherlands, were used. In total, 9360 youngsters in a mandatory sample (Twente) and 1952 youngsters in a voluntary sample (IJsselland) participated in the study. To test whether the samples differed on health-related variables, we conducted both univariate and multivariable logistic regression analyses controlling for any demographic difference between the samples. Additional multivariable logistic regressions were conducted to examine moderating effects of sampling method on associations between health-related variables. As expected, females, older individuals, as well as individuals with higher education levels, were over-represented in the voluntary sample, compared to the mandatory sample. Respondents in the voluntary sample tended to smoke less, consume less alcohol (ever, lifetime, and past four weeks), have better mental health, have better subjective health status, have more positive school experiences and have less sexual intercourse than respondents in the mandatory sample. No moderating effects were found for sampling method on associations between variables. This is one of first studies to provide strong evidence that voluntary recruitment may lead to a strong non-response bias in health-related prevalence estimates in adolescents, as compared to mandatory recruitment. The resulting underestimation in prevalence of health behaviours and well-being measures appeared large, up to a four-fold lower proportion for self-reported alcohol consumption. Correlations between variables, though, appeared to be insensitive to sampling bias.