Accounting for Bias Due to Selective Attrition The Example of Smoking and Cognitive Decline

Rush Institute for Healthy Aging and Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA.
Epidemiology (Cambridge, Mass.) (Impact Factor: 6.2). 01/2012; 23(1):119-28. DOI: 10.1097/EDE.0b013e318230e861
Source: PubMed


Selective attrition may introduce bias into analyses of the determinants of cognitive decline. This is a concern especially for risk factors, such as smoking, that strongly influence mortality and dropout. Using inverse-probability-of-attrition weights, we examined the influence of selective attrition on the estimated association of current smoking (vs. never smoking) with cognitive decline.
Chicago Health and Aging Project participants (n = 3713), aged 65-109 years, who were current smokers or never- smokers, underwent cognitive assessments up to 5 times at 3-year interval. We used pooled logistic regression to fit predictive models of attrition due to death or study dropout across the follow-up waves. With these models, we computed inverse-probability-of-attrition weights for each observation. We fit unweighted and weighted, multivariable-adjusted generalized-estimating-equation models, contrasting rates of change in cognitive scores in current versus never-smokers. Estimates are expressed as rates of change in z score per decade.
During the 12 years of follow-up, smokers had higher mortality than never-smokers (hazard ratio = 1.93 [95% confidence interval = 1.67 to 2.23]). Higher previous cognitive score was associated with increased likelihood of survival and continued participation. In unweighted analyses, current smokers' cognitive scores declined 0.11 standard units per decade more rapidly than never-smokers' (95% CI = -0.20 to -0.02). Weighting to account for attrition yielded estimates that were 56% to 86% larger, with smokers' estimated 10-year rate of decline up to 0.20 units faster than never-smokers' (95% CI = -0.36 to -0.04).
Estimates of smoking's effects on cognitive decline may be underestimated due to differential attrition. Analyses that weight for the inverse probability of attrition help compensate for this attrition.

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Available from: Jennifer Weuve, Mar 18, 2015
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    • "Even the likelihood of substantial bias from " ignoring the selection process, " which is arguably the most common strategy in the applied literature, is rarely formally quantified, although specific examples suggest it may be reasonably large. In the Chicago Health and Aging Project, accounting for selective attrition increased estimated associations between smoking and cognitive decline by 56%–86% [26]. MELODEM guidelines are intended to provide evidence to evaluate whether selection is likely to introduce a substantial bias. "
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    • "For all the aforementioned case-controlled and cohort studies, there was considerable variability in the sample sizes, the duration that participants were followed (for cohort studies), and the covariates (e.g., APOE genotype, alcohol consumption, sex, biomedical risk factors) measured and/or controlled for in statistical analyses. Survivor bias has been indicated to promote an underestimation of the smoking-related risk for AD in both case-controlled and cohort studies [88] [89] [90] [91] [92]. Specifically, elders who die prematurely from smoking-related diseases are a major source of attrition; this reduces the proportion of smokers who may have ultimately developed AD, creates attrition in cohort studies, and those smokers who do survive are biased toward healthier individuals [92]. "
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