Faculty of Medicine, University of Castilla-La Mancha, Albacete, Spain.
Department of Applied Physics, University of Castilla-La Mancha, Albacete, Spain.
Environ Monit Assess. 2020 Jan 2;192(2):77. doi: 10.1007/s10661-019-8021-z.
Several studies have characterized personal exposure to RF-EMF, which allows possible effects on health to be studied. All equipment has a detection limit, below which we obtain nondetects or censored data. This problem is a challenge for researchers as it makes the analysis of such data complex. We suggest reconsidering the statistical protocols of the nondetects analysis by comparing four different methods. Three of them substitute censored data using different approaches: regression on order of statistics (ROS) to simulate data below the detection limit (Method 1), substituting nondetect values by the detection limit divided by 2 (Method 2), a naïve calculation (Method 3) using the detection limit as a valid measurement. The fourth method consists of considering censored data to be missing values (Method 4). This article examines how these methods affect the quantification of personal exposure. We considered data from 14 frequency bands from FM to WiMax measured in Albacete (Spain) for 76 days every 10 s by a personal exposimeter (PEM) Satimo EME Spy 140.Methods 3 and 2 gave similar mean and median values to Method 1, but both underestimated the mean values when high nondetects records occurred, which conditioned the physical description of the real situation. The mean values calculated by Method 4 differed from those obtained by Method 1 but were similar when the percentage of nondetects was below 20%.Our comparison suggests that nondetects can be neglected when the percentage of censored data is low to provide a more realistic physical situation.
已有多项研究对射频电磁场的个体暴露情况进行了描述，这使得对健康影响的研究成为可能。所有设备都有一个检测下限，低于该下限则会获得未检出或截尾数据。这个问题对研究人员来说是一个挑战，因为它使此类数据的分析变得复杂。我们建议通过比较四种不同的方法来重新考虑未检出分析的统计方案。其中三种方法使用不同的方法替代截尾数据：基于有序统计量的回归（ROS）来模拟检测限以下的数据（方法 1）、用检测限除以 2 替代未检出值（方法 2）、使用检测限作为有效测量值的简单计算（方法 3）。第四种方法是将截尾数据视为缺失值（方法 4）。本文研究了这些方法如何影响个体暴露的量化。我们考虑了在西班牙阿尔瓦塞特市用个人暴露计（PEM）Satimo EME Spy 140 每 10 秒测量的 14 个从 FM 到 WiMax 的频率波段的 76 天数据。方法 3 和 2 给出的均值和中位数与方法 1 相似，但当出现大量未检出记录时，两者都低估了均值，从而影响了对实际情况的物理描述。方法 4 计算的均值与方法 1 不同，但当未检出率低于 20%时，两者相似。我们的比较表明，当截尾数据的百分比较低时，可以忽略未检出值，以提供更现实的物理情况。
