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Characterising attrition from childhood to adulthood in a 20-year cohort: which baseline factors are influential, and can bias be corrected?


Otahal, P and Blizzard, L and Hosmer, DM and Stankovich, J and Venn, A, Characterising attrition from childhood to adulthood in a 20-year cohort: which baseline factors are influential, and can bias be corrected?, Longitudinal and Life Course Studies, 12, (2) pp. 227-240. ISSN 1757-9597 (2021) [Refereed Article]

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Copyright Statement

Copyright 2020 the authors and Policy Press. The definitive, peer reviewed and edited version of this article is published in Longitudinal and Life Course Studies pp. 1-14, 2021.

DOI: doi:10.1332/175795920X16000977636901


Attrition is common in longitudinal studies and can lead to bias when the missingness pattern affects the distributions of analysed variables. Characterisation of factors predictive of attrition is vital to longitudinal research. Few studies have investigated the factors predictive of attrition from childhood cohorts with large-scale loss to follow-up. Methods to remove potential bias are available and have been well studied in scenarios of short intervening periods between contact and follow-up. Less is known about the performance of such techniques when there is a large initial loss of participants after a long intervening period. The Australian Schools Health and Fitness Survey (ASHFS) was conducted in 1985 when participants were school children aged 715 years. The first follow-up occurred 20 years later with substantial loss of participants: 80% were traced, 61% enrolled and provided brief questionnaire information, 47% provided more extensive questionnaire information and 28% attended clinics. Factors associated with attrition were examined and two common techniques, multiple imputation (MI) and inverse probability weighting (IPW) were used to determine the potential for correcting the bias in the estimate of the association between self-rated fitness and BMI in childhood. Attrition from childhood to adulthood was found to be influenced by the same factors that operate in adult cohorts: lower education, lower socio-economic position and male sex. Attrition patterns varied by the stage of follow-up. Estimated childhood associations biased by adulthood attrition were able to be corrected using MI, but IPW was unsuccessful due to a lack of completely observed informative variables.

Item Details

Item Type:Refereed Article
Keywords:attrition, bias, follow-up, imputation, inverse probability weighting, validity
Research Division:Health Sciences
Research Group:Epidemiology
Research Field:Epidemiological modelling
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the health sciences
UTAS Author:Otahal, P (Mr Petr Otahal)
UTAS Author:Blizzard, L (Professor Leigh Blizzard)
UTAS Author:Hosmer, DM (Professor David Hosmer)
UTAS Author:Stankovich, J (Dr Jim Stankovich)
UTAS Author:Venn, A (Professor Alison Venn)
ID Code:143276
Year Published:2021
Web of Science® Times Cited:1
Deposited By:Menzies Institute for Medical Research
Deposited On:2021-03-10
Last Modified:2021-12-22

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