Accounting for bias due to selective attrition: the example of smoking and cognitive decline.
Accounting for bias due to selective attrition: the example of smoking and cognitive decline.
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DOI：
10.1097/ede.0b013e318230e861
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发表时间：
2012-01
期刊：
影响因子：
--
通讯作者：
Mendes de Leon CF
中科院分区：
文献类型：
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作者：
Weuve J;Tchetgen Tchetgen EJ;Glymour MM;Beck TL;Aggarwal NT;Wilson RS;Evans DA;Mendes de Leon CF
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 drop-out. Using inverse-probability-of-attrition weights (IPAWs), we examined the influence of selective attrition on the estimated association of current smoking (versus never smoking) with cognitive decline. Chicago Health and Aging Project participants (n=3,713), aged 65–109, who were current smokers or never-smokers underwent cognitive assessments up to 5 times at 3-year intervals. We used pooled logistic regression to fit predictive models of attrition due to death or study drop-out 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. Over 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%–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 - for this attrition.
