Rush Institute for Healthy Aging and Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA.
Epidemiology. 2012 Jan;23(1):119-28. doi: 10.1097/EDE.0b013e318230e861.
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.
选择性流失可能会给分析认知能力下降的决定因素带来偏差。对于像吸烟这样强烈影响死亡率和辍学率的风险因素来说，这尤其令人担忧。我们使用逆概率赋权法，研究了选择性流失对当前吸烟（与从不吸烟相比）与认知能力下降之间关联的估计的影响。
芝加哥健康与衰老项目参与者（n = 3713），年龄 65-109 岁，为当前吸烟者或从不吸烟者，每 3 年进行一次认知评估，最多进行 5 次。我们使用多波随访的死亡或研究退出的累积逻辑回归来拟合流失的预测模型。根据这些模型，我们为每个观察值计算了逆概率赋权。我们拟合了未加权和加权的多变量调整广义估计方程模型，对比了当前吸烟者和从不吸烟者的认知评分变化率。估计值表示每十年 z 分数的变化率。
在 12 年的随访期间，吸烟者的死亡率高于从不吸烟者（风险比= 1.93 [95%置信区间= 1.67-2.23]）。较高的先前认知评分与生存和继续参与的可能性增加有关。在未加权分析中，当前吸烟者的认知评分比从不吸烟者每年快 0.11 个标准差单位下降（95%CI = -0.20 至 -0.02）。为了考虑流失而进行的加权得出的估计值要大 56%至 86%，吸烟者的 10 年估计下降速度比从不吸烟者快 0.20 个单位（95%CI = -0.36 至 -0.04）。
由于流失的差异，吸烟对认知能力下降的影响的估计可能被低估。对逆概率进行加权的分析有助于弥补这种流失。
