Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Int J Epidemiol. 2013 Jun;42(3):849-59. doi: 10.1093/ije/dyt077.
Within-person variability in measured values of a risk factor can bias its association with disease. We investigated the extent of regression dilution bias in calculated variables and its implications for comparing the aetiological associations of risk factors.
Using a numerical illustration and repeats from 42,300 individuals (12 cohorts), we estimated regression dilution ratios (RDRs) in calculated risk factors [body-mass index (BMI), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)] and in their components (height, weight, waist circumference, and hip circumference), assuming the long-term average exposure to be of interest. Error-corrected hazard ratios (HRs) for risk of coronary heart disease (CHD) were compared across adiposity measures per standard-deviation (SD) change in: (i) baseline and (ii) error-corrected levels.
RDRs in calculated risk factors depend strongly on the RDRs, correlation, and comparative distributions of the components of these risk factors. For measures of adiposity, the RDR was lower for WHR [RDR: 0.72 (95% confidence interval 0.65-0.80)] than for either of its components [waist circumference: 0.87 (0.85-0.90); hip circumference: 0.90 (0.86-0.93) or for BMI: 0.96 (0.93-0.98) and WHtR: 0.87 (0.85-0.90)], predominantly because of the stronger correlation and more similar distributions observed between waist circumference and hip circumference than between height and weight or between waist circumference and height. Error-corrected HRs for BMI, waist circumference, WHR, and WHtR, were respectively 1.24, 1.30, 1.44, and 1.32 per SD change in baseline levels of these variables, and 1.24, 1.27, 1.35, and 1.30 per SD change in error-corrected levels.
The extent of within-person variability relative to between-person variability in calculated risk factors can be considerably larger (or smaller) than in its components. Aetiological associations of risk factors should be compared through the use of error-corrected HRs per SD change in error-corrected levels of these risk factors.
在个体内测量的风险因素值的变异性可能会对其与疾病的关联产生偏差。我们研究了计算变量中回归稀释偏差的程度及其对比较风险因素病因关联的影响。
使用数值说明和来自 42300 名个体（12 个队列）的重复测量，我们假设长期平均暴露是感兴趣的，估计了计算风险因素（体重指数（BMI）、腰臀比（WHR）和腰高比（WHtR））及其组成部分（身高、体重、腰围和臀围）中的回归稀释比（RDR）。假设长期平均暴露是感兴趣的。比较了每个标准偏差（SD）变化的：（i）基线和（ii）错误校正水平下，肥胖指标的风险校正危害比（HR）。
计算风险因素的 RDR 强烈依赖于这些风险因素的组成部分的 RDR、相关性和比较分布。对于肥胖指标，WHR 的 RDR 低于其任何组成部分[腰围：0.72（95%置信区间 0.65-0.80）]；[腰围：0.87（0.85-0.90）；臀围：0.90（0.86-0.93）]或 BMI：0.96（0.93-0.98）和 WHtR：0.87（0.85-0.90）]，主要是因为腰围和臀围之间的相关性更强，分布更相似，而身高和体重之间或腰围和身高之间的相关性更弱。BMI、腰围、WHR 和 WHtR 的错误校正 HR 分别为这些变量基线水平每 SD 变化 1.24、1.30、1.44 和 1.32，错误校正水平每 SD 变化 1.24、1.27、1.35 和 1.30。
与计算风险因素的组成部分相比，个体内变异性相对于个体间变异性的程度可能大得多（或小得多）。应通过使用错误校正 HR 来比较风险因素的病因关联，每 SD 变化这些风险因素的错误校正水平。
