Self-selection in epidemiological studies may introduce selection bias and influence the validity of study results. To evaluate potential bias due to self-selection in a large prospective pregnancy cohort in Norway, the authors studied differences in prevalence estimates and association measures between study participants and all women giving birth in Norway. Women who agreed to participate in the Norwegian Mother and Child Cohort Study (43.5% of invited; n = 73 579) were compared with all women giving birth in Norway (n = 398 849) using data from the population-based Medical Birth Registry of Norway in 2000–2006. Bias in the prevalence of 23 exposure and outcome variables was measured as the ratio of relative frequencies, whereas bias in exposure-outcome associations of eight relationships was measured as the ratio of odds ratios.
Statistically significant relative differences in prevalence estimates between the cohort participants and the total population were found for all variables, except for maternal epilepsy, chronic hypertension and pre-eclampsia. There was a strong under-representation of the youngest women (<25 years), those living alone, mothers with more than two previous births and with previous stillbirths (relative deviation 30–45%). In addition, smokers, women with stillbirths and neonatal death were markedly under-represented in the cohort (relative deviation 22–43%), while multivitamin and folic acid supplement users were over-represented (relative deviation 31–43%). Despite this, no statistically relative differences in association measures were found between participants and the total population regarding the eight exposure-outcome associations.
Using data from the Medical Birth Registry of Norway, this study suggests that prevalence estimates of exposures and outcomes, but not estimates of exposure-outcome associations are biased due to self-selection in the Norwegian Mother and Child Cohort Study.