Faculty of Environment Science, Nagasaki University, Nagasaki, Japan.
Department of Medical Innovation, Osaka University Hospital, Osaka, Japan.
PLoS One. 2018 Dec 26;13(12):e0208816. doi: 10.1371/journal.pone.0208816. eCollection 2018.
Measuring biomaterials is usually subject to error. Measurement errors are classified into either random errors or biases. Random errors can be well controlled using appropriate statistical methods. But, biases due to unknown, unobserved, or temporary causes, may lead to biased conclusions. This study describes a verification method to examine whether measurement errors are random or not and to determine efficient statistical methods. A number of studies have dealt with associations between hair minerals and exposures such as health, dietary or environmental conditions. Most review papers, however, emphasize the necessity for validation of hair mineral measurements, since large variations can cause highly variable results. To address these issues, we answer the following questions: How can we ascertain the reliability of measurements?How can we assess and control the variability of measurements?How do we efficiently determine associations between hair minerals and exposures?How can we concisely present the reference values? Since hair minerals all have distinctive natures, it would be unproductive to examine each mineral individually to find significant and consistent answers that apply to all minerals. To surmount this difficulty, we used one simple model for all minerals to explore quantitative answers. Hair mineral measurements of six-year-old children were analyzed based on the statistical model. The analysis verified that most of the measurements were reliable, and their inter-individual variations followed two-parameter distributions. These results allow for sophisticated study designs and efficient statistical methods to examine the effects of various kinds of exposures on hair minerals.
测量生物材料通常会存在误差。误差可分为随机误差或偏倚。随机误差可以通过适当的统计方法进行很好的控制。但是，由于未知、未观察到或暂时的原因导致的偏倚，可能会导致有偏差的结论。本研究描述了一种验证方法，用于检查测量误差是随机的还是非随机的，并确定有效的统计方法。许多研究都涉及头发矿物质与健康、饮食或环境等暴露之间的关联。然而，大多数综述论文都强调了头发矿物质测量验证的必要性，因为较大的变化会导致结果高度可变。为了解决这些问题，我们回答了以下问题：
我们如何确定测量的可靠性？
我们如何评估和控制测量的变异性？
我们如何有效地确定头发矿物质与暴露之间的关联？
我们如何简洁地呈现参考值？
由于头发矿物质都具有独特的性质，因此逐个检查每种矿物质以找到适用于所有矿物质的有意义且一致的答案是没有成效的。为了克服这个困难，我们使用了一个简单的模型来研究所有矿物质的定量答案。根据统计模型分析了 6 岁儿童的头发矿物质测量值。分析结果验证了大多数测量值是可靠的，并且它们的个体间差异遵循双参数分布。这些结果允许使用复杂的研究设计和有效的统计方法来检查各种暴露对头发矿物质的影响。
