Effects of Self-Reported Health Conditions and Pesticide Exposures on Probability of Follow-Up in a Prospective Cohort Study

Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina 27709, USA.
American Journal of Industrial Medicine (Impact Factor: 1.74). 11/2009; 53(5):486-96. DOI: 10.1002/ajim.20789
Source: PubMed


We investigated the potential for selection bias due to non-participation in the follow-up of a large prospective cohort study.
Licensed pesticide applicators (52,395 private; 4,916 commercial) in the Agricultural Health Study provided demographic, health, and pesticide exposure information at enrollment (1993-1997) and in a 5-year follow-up telephone interview. Factors associated with non-participation in the follow-up were identified using multiple logistic regression. Potential for selection bias was evaluated by comparing exposure-disease associations between the entire cohort and the follow-up subset.
Sixty-six percent of private and 60% of commercial applicators completed the follow-up interview. Private and commercial applicators who did not complete the follow-up reported at enrollment younger age, less education, lower body mass index, poorer health behaviors but fewer health conditions, and lower pesticide use. Estimates of exposure-disease associations calculated with and without non-participants did not indicate strong selection bias.
Differences between non-participants and participants in the follow-up interview were generally small, and we did not find significant evidence of selection bias. However, the extent of bias may depend on the specific exposure and outcome under study.

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    • " / or selection bias could still occur . In addition , c - statistics for the dropout models , while not used to select variables for inclusion in our models for the weights , ranged from 0 . 60 to 0 . 61 , which suggests that dropout in the AHS is mostly random or that our models did not predict dropout well . The former seems more likely because Montgomery et al . ( 2010 ) found that applicators who reported physician - diagnosed depression at enrollment were equally likely to drop out of the AHS before the first follow - up interview in 1998 – 2003 as applicators who did not report depression ( OR = 0 . 92 ; 95% CI : 0 . 82 , 1 . 02 after adjustment for age , state , education , and smoking ) . Our inf"
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