AbstractBackgroundDropout from studies can lead to biased exposure-outcome estimates if the outcome is associated with continued participation, but this cannot be investigated using incomplete data. Linkage to external datasets provides a means of obtaining outcome – or proxy outcome - data on non-responders.MethodsWe examined the association between baseline socio-demographic factors and participation in the Avon Longitudinal Study of Parents and Children. We investigated whether child and adolescent outcomes measured in linked education and primary care data were associated with participation after accounting for baseline factors. To demonstrate the potential for bias, we examined whether the association between maternal smoking and these outcomes differed in the subsample who completed the 19-year questionnaire.ResultsLower levels of school attainment, lower GP consultation and prescription rates, higher BMI, special educational needs (SEN) status, not having an asthma diagnosis, depression and being a smoker were all associated with lower participation after adjustment for baseline factors. For example, adjusted odds ratio (OR) for participation comparing ever smokers (by 18 years) to non-smokers: 0.65, 95% CI (0.56, 0.75). The association of maternal smoking differed between the subsample of participants at 19 years and the entire sample, although differences were small and confidence intervals overlapped. For example: for SEN status OR=1.19 (1.06, 1.33) (all participants); OR=1.03 (0.79, 1.45) (subsample).ConclusionsLinkage to routine data provides a unique opportunity to compare continuing participators to those who drop out, and the impact this self-selection can have on results. Cohort studies should use linkage to routine data to explore participation and conduct sensitivity analyses.Key messagesEducational and health-related characteristics are strongly associated with ongoing participation in the Avon Longitudinal Study of Parents and Children after adjustment for detailed socio-demographic factors.This could bias analyses using the dataset, with bias dependent on the variables used in the analysis and their impact on participation.Linkage to routine data provides a means of assessing whether factors measured across the life course are associated with ongoing participation in observational studies and the potential impact of this in terms of bias.Researchers can use linkage to external sources of data to make informed decisions about the likely impact of selective participation and to guide their analyses.
Socio-demographic factors relating to mothers' self-efficacy in preventing childhood diarrhea: a longitudinal study
