There is currently a debate in the literature on chemical drug analysis concerning the contribution of biophysical attributes associated with specimens and specimen donors to assay outcome. In recent years this debate has focused on hair analysis, but has in the past also been raised in urinalysis interpretation. In this article we examine several aspects of that controversy. First, we present data regarding the effects of hair color on the distribution of positive hair testing results for three drug classes. We compare these results to negative hair samples from comparable donors. This data is derived from head hair from preemployment donors that was classified according to seven visual color categories. We determined the distribution of colors for hair samples devoid of any of three assayed drugs (amphetamines, cocaine, and cannabinoids). Subsequently, this distribution was compared with the distributions for hairs that had rested positive for amphetamines, cocaine or cannabinoids. We examined a total of 2000 randomly selected samples; 500 negative hair samples and 500 positive samples for each of three drugs: cannabinoids, cocaine, and amphetamine. We also evaluated ethnic/racial factors in relation to positive urinalyses for various ethnic/racial groups. We examined approximately 4000 urine specimens from two different groups, each constituting around 2000 specimens. In addition to ethnicity/race and urinalysis outcome, we also examined the relationship between the hair color distributions of urine donors and the corresponding urinalysis results for the three drug classes. We also compared them to drug-negative samples. Our summary impression is that the observed outcome patterns were largely consistent with differences in drug preferences among the various societal groups. There was little evidence of a pattern attributable to hair color bias alone or selective binding of drugs to hair of a particular color. Likewise, there was no discernible pattern associated with race or ethnicity that would lend support to a "race effect" in drug analysis. (C) 2000 Elsevier Science Ireland Ltd. All rights reserved.
