Statistical examination of hair color as a potential biasing factor in hair analysis.

We review eight different data sets in this paper for the purposes of assessing the possibility that reported color of hair can produce a systematic bias in the interpretation of hair assays. We review studies or data sets that include heroin and its metabolites, cocaine and its metabolites, MDMA and its analogs, and amphetamine and methamphetamine. The studies have utilized a variety of different degrees of color categorization, ranging from the simple dichotomy of brown and black, to a high of 12 categories. The mean number of categories reported approaches 6 (mean = 5.875). There are a total of 2791 data points in this analysis. We utilize two major statistical techniques for assessing significance; one-way analysis of variance, and Tukey's Honestly Significant Difference procedure. In circumstances were only dichotomous contrasts are possible, one-way analysis of variance is used. In contrasts involving three or more categorical groups, Tukey's procedure is used. In circumstances where the homogeneity of group variances is not sustained by the Levene statistic, we use the Tamahane procedure, allowing an assessment that assumes unequal variances. The analysis of this data fails to discern a significant color effect. We speculate that it may be that variance is large in many domains affecting analyte recovery from hair. In large groups these variations tend to regress towards a typical or mean value. Thus the data here show that while there are group or aggregate differences in these 'typical' values, they are not great when considered in relation to the within-group variations which exist for those values. It is our view that color may play a role in the accumulation of drugs in hair, however it is likely to account for only a very small part of the complex process of drug accumulation.