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

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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.

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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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Acknowledgements

The authors are indebted to Dr Miguel Hernán for comments on this manuscript and Ms Carmen de la Fuente for technical assistance. Also, they thank the continuous collaboration of the participants in the SUN Study. The SUN Study has received funding from the Spanish Ministry of Health (Grants PI040233, G03/140, and PI030678), the Navarra Regional Government (43/2002 and 41/2005) and the University of Navarra. Dr Alonso was supported partially by a Fulbright fellowship and a MMA Foundation grant.

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Authors and Affiliations

  1. Department of Preventive Medicine and Public Health, School of Medicine, University of Navarra, Pamplona, Spain

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

  2. Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA

    Alvaro Alonso

  3. Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    María Seguí-Gómez

  4. Department of Clinical Sciences, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Almudena Sánchez-Villegas

Authors
  1. Alvaro Alonso
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  2. María Seguí-Gómez
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  3. Jokin de Irala
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  4. Almudena Sánchez-Villegas
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  5. Juan José Beunza
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  6. Miguel Ángel Martínez-Gonzalez
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Correspondence to Alvaro Alonso.

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Alonso, A., Seguí-Gómez, M., de Irala, J. et al. Predictors of follow-up and assessment of selection bias from dropouts using inverse probability weighting in a cohort of university graduates. Eur J Epidemiol 21, 351–358 (2006). https://doi.org/10.1007/s10654-006-9008-y

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