TY - JOUR T1 - Association of attrition with mortality: findings from 11 waves over three decades of the Whitehall II study JF - Journal of Epidemiology and Community Health JO - J Epidemiol Community Health SP - 824 LP - 830 DO - 10.1136/jech-2019-213175 VL - 74 IS - 10 AU - Mifuyu Akasaki AU - Mika Kivimäki AU - Andrew Steptoe AU - Owen Nicholas AU - Martin J Shipley Y1 - 2020/10/01 UR - http://jech.bmj.com/content/74/10/824.abstract N2 - Background Attrition, the loss of participants as a study progresses, is a considerable challenge in longitudinal studies. This study examined whether two forms of attrition, ‘withdrawal’ (formal discontinued participation) and ‘non-response’ (non-response among participants continuing in the study), have different associations with mortality and whether these associations differed across time in a multi-wave longitudinal study.Methods Participants were 10 012 civil servants who participated at the baseline of the Whitehall II cohort study with 11 data waves over an average follow-up of 28 years. We performed competing-risks analyses to estimate sub-distribution HRs and 95% CIs, and likelihood ratio tests to examine whether hazards differed between the two forms of attrition. We then applied linear regression to examine any trend of hazards against time.Results Attrition rate at data collections ranged between 13% and 34%. There were 495 deaths recorded from cardiovascular disease and 1367 deaths from other causes. Study participants lost due to attrition had 1.55 (95% CI 1.26 to 1.89) and 1.56 (1.39 to 1.76) times higher hazard of cardiovascular and non-cardiovascular mortality than responders, respectively. Hazards for withdrawal and non-response did not differ for either cardiovascular (p value =0.28) or non-cardiovascular mortality (p value =0.38). There was no linear trend in hazards over the 11 waves (cardiovascular mortality p value =0.11, non-cardiovascular mortality p value =0.61).Conclusion Attrition can be a problem in longitudinal studies resulting in selection bias. Researchers should examine the possibility of selection bias and consider applying statistical approaches that minimise this bias. ER -