Kaune W T, Davis S, Stevens R G, Mirick D K, Kheifets L
EM Factors, Richland, Washington 99352, USA.
Bioelectromagnetics. 2001 May;22(4):232-45.
Considerable interest has developed during the past ten years regarding the hypothesis that living organisms may respond to temporal variability in ELF magnetic fields to which they are exposed. Consequently, methods to measure various aspects of temporal variability are of interest. In this paper, five measures of temporal variability were examined: Arithmetic means (D(mean)) and rms values (D(rms)) of the first differences (i.e., absolute value of the difference between consecutive measurements) of magnetic field recordings; "standardized" forms of D(rms), denoted RCMS, obtained by dividing D(rms) by the standard deviations of the magnetic field data; and mean (F(mean)) and rms (F(rms)) values of fractional first differences. Theoretical investigations showed that D(mean) and D(rms) are virtually unaffected by long-term systematic trends (changes) in exposure. These measures thus provide rather specific measures of short-term temporal variability. This was also true to a lesser extent for F(mean) and F(rms). In contrast, the RCMS metric was affected by both short-term and long-term exposure variabilities. The metrics were also investigated using a data set consisting of twice-repeated two-calendar-day recordings of bedroom magnetic fields and personal exposures of 203 women residing in the western portion of Washington State. The predominant source of short-term temporal variability in magnetic field exposures arose from the movement of subjects through spatially varying magnetic fields. Spearman correlations between TWA bedroom magnetic fields or TWA personal exposures and five measures of temporal variability were relatively low. Weak to moderate levels of correlation were observed between temporal variability measured during two different sessions separated in time by 3 or 6 months. We conclude that first difference and fractional difference metrics provide specific and fairly independent measures of short-term temporal variability. The RCMS metric does not provide an easily interpreted measure of short-term or long-term temporal variability. This last result raises uncertainties about the interpretation of published studies that use the RCMS metric.
在过去十年中，关于生物体可能会对其所暴露的极低频磁场的时间变化做出反应这一假说，已经引发了相当大的关注。因此，用于测量时间变化各个方面的方法备受关注。在本文中，研究了五种时间变化的测量方法：磁场记录的一阶差分（即连续测量值之间差值的绝对值）的算术平均值（D(mean)）和均方根值（D(rms)）；通过将D(rms)除以磁场数据的标准差得到的D(rms)的“标准化”形式，记为RCMS；以及一阶分数差分的平均值（F(mean)）和均方根值（F(rms)）。理论研究表明，D(mean)和D(rms)几乎不受长期系统性暴露趋势（变化）的影响。因此，这些测量方法提供了相当具体的短期时间变化测量。F(mean)和F(rms)在较小程度上也是如此。相比之下，RCMS指标受到短期和长期暴露变化的影响。还使用了一个数据集对这些指标进行了研究，该数据集包括对华盛顿州西部203名女性卧室磁场和个人暴露情况进行的两次重复的为期两天的记录。磁场暴露中短期时间变化的主要来源是受试者在空间变化的磁场中移动。卧室磁场的时间加权平均值（TWA）或个人暴露的TWA与五种时间变化测量方法之间的斯皮尔曼相关性相对较低。在相隔3个月或6个月的两个不同时间段测量的时间变化之间，观察到了弱到中等程度的相关性。我们得出结论，一阶差分和分数差分指标提供了短期时间变化的具体且相当独立的测量。RCMS指标并不能提供一个易于解释的短期或长期时间变化测量。最后这个结果引发了对使用RCMS指标的已发表研究解释的不确定性。
