European Journal of Epidemiology

, Volume 21, Issue 5, pp 351–358

Predictors of follow-up and assessment of selection bias from dropouts using inverse probability weighting in a cohort of university graduates

  • Alvaro Alonso
  • María Seguí-Gómez
  • Jokin de Irala
  • Almudena Sánchez-Villegas
  • Juan José Beunza
  • Miguel Ángel Martínez-Gonzalez
Methods

Abstract

Dropouts in cohort studies can introduce selection bias. In this paper, we aimed (i) to assess predictors of retention in a cohort study (the SUN Project) where participants are followed-up through biennial mailed questionnaires, and (ii) to evaluate whether differential follow-up introduced selection bias in rate ratio (RR) estimates. The SUN Study recruited 9907 participants from December 1999 to January 2002. Among them, 8647 (87%) participants answered the 2-year follow-up questionnaire. The presence of missing information in key variables at baseline, being younger, smoker, a marital status different of married, being obese/overweight and a history of motor vehicle injury were associated with being lost to follow-up, while a self-reported history of cardiovascular disease predicted a higher retention proportion. To assess whether differential follow-up affected RR estimates, we studied the association between body mass index and the risk of hypertension, using inverse probability weighting (IPW) to adjust for␣confounding and selection bias. Obese individuals had a higher crude rate of hypertension compared with␣normoweight participants (RR = 6.4, 95% confidence interval (CI): 3.9–10.5). Adjustment for confounding using IPW attenuated the risk of hypertension associated to obesity (RR = 2.4, 95% CI: 1.1–5.3). Additional adjustment for selection bias did not modify the estimations. In conclusion, we show that the follow-up through mailed questionnaires of a geographically disperse cohort in Spain is possible. Furthermore, we show that despite existing differences between retained or lost to follow-up participants this may not necessarily have an important impact on the RR estimates of hypertension associated to obesity.

Keywords

Attrition Body mass index Cohort studies Hypertension Inverse probability weighting Selection bias 

Abbreviations

BMI

body mass index

CI

confidence interval

HTN

hypertension

IPW

inverse probability weighting

MET

metabolic equivalent

RR

rate ratio

SUN

Seguimiento Universidad de Navarra

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Alvaro Alonso
    • 1
    • 2
  • María Seguí-Gómez
    • 1
    • 3
  • Jokin de Irala
    • 1
  • Almudena Sánchez-Villegas
    • 1
    • 4
  • Juan José Beunza
    • 1
  • Miguel Ángel Martínez-Gonzalez
    • 1
  1. 1.Department of Preventive Medicine and Public HealthSchool of Medicine, University of NavarraPamplonaSpain
  2. 2.Department of EpidemiologyHarvard School of Public HealthBostonUSA
  3. 3.Bloomberg School of Public HealthJohns Hopkins UniversityBaltimoreUSA
  4. 4.Department of Clinical SciencesUniversity of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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