title: Estimating bias from loss to follow-up in the Danish National Birth Cohort.
abstract: Loss to follow-up in cohort studies may result in biased association estimates. Of 61,895 women entering the Danish National Birth Cohort and completing the first data-collection phase, 37,178 (60%) opted to be in the 7-year follow-up. Using national registry data to obtain end point information on all members of the cohort, we estimated associations in the baseline and the 7-year follow-up participant populations for 5 exposure-outcome associations: (a) size at birth and childhood asthma, (b) assisted reproductive treatment and childhood hospitalizations, (c) prepregnancy body mass index and childhood infections, (d) alcohol drinking in early pregnancy and childhood developmental disorders, and (e) maternal smoking in pregnancy and childhood attention-deficit hyperactivity disorder (ADHD). We estimated follow-up bias in the odds or rate ratios by calculating relative ratios. For all but one of the above analyses, the bias appeared to be small, between -10% and +8%. For maternal smoking in pregnancy and childhood ADHD, we estimated a positive bias of approximately 33% (95% bootstrap limits of -30% and +152%). The presence and magnitude of bias due to loss to follow-up depended on the nature of the factors or outcomes examined, with the most pronounced contribution in this study coming from maternal smoking. Our methods and results may inform bias analyses in future pregnancy cohort studies.
authors.affiliation: Department of Epidemiology, School of Public Health, University of California, Los Angeles, CA 90095, USA. ngreene@ucla.edu
authors.forename: Naomi
authors.initials: N
authors.lastname: Greene
authors.forename: Sander
authors.initials: S
authors.lastname: Greenland
authors.forename: Jørn
authors.initials: J
authors.lastname: Olsen
authors.forename: Ellen Aagaard
authors.initials: EA
authors.lastname: Nohr
mesh_terms: D000328:Adult; D000367:Age Factors; D015982:Bias; D002648:Child; D015331:Cohort Studies; D003718:Denmark / Q000453:epidemiology; D004194:Disease / Q000209:etiology; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008423:Maternal Age; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D012042:Registries; D055815:Young Adult