Department of Criminology and Criminal Justice, University of South Carolina, Columbia, SC 29208, USA.
Drug Test Anal. 2013 Jan;5(1):62-7. doi: 10.1002/dta.1430. Epub 2012 Nov 21.
The average potency of illicit marijuana in the USA has increased substantially over the past four decades, and observers have suggested a number of likely reasons for this. One set of hypotheses points to a market that has evolved from foreign to domestic sources of supply, and to continuing advances in sophisticated cultivation techniques. Another set of hypotheses points to testing artifacts related to changes in the sampling, handling, and testing of illicit marijuana. The current study uses data from the federally sponsored Potency Monitoring Program, which performs ongoing forensic analysis of seized marijuana samples, to assess the extent to which the observed increase in cannabis potency in the USA between 1970 and 2010 is a function of genuine shifts in illicit marijuana markets or testing artifacts related to changes in the quality of seized marijuana. The study finds, after adjusting for marijuana quality, that the apparent 10.5 factor increase in mean reported THC% between the 1970s and the 2000s is instead on the order of a six- to seven-fold increase. By this accounting, then, the reported long-term rise in potency is roughly 57-67% as great when the quality of the tested marijuana is taken into account. This study's findings, therefore, caution against the uncritical use of potency monitoring data and highlight the importance of assessing potency measurement reliability and addressing data quality issues in future policy analytic research.
在过去的四十年中,美国非法大麻的平均效力大幅增加,观察人士提出了许多可能的原因。一组假设指向一个从外国供应源转变为国内供应源的市场,以及不断发展的复杂种植技术。另一组假设指向与非法大麻的采样、处理和测试相关的测试文物的变化。本研究使用了联邦赞助的效力监测计划的数据,该计划对缉获的大麻样本进行持续的法医分析,以评估美国大麻效力在 1970 年至 2010 年间观察到的增长在多大程度上是由于非法大麻市场的真正变化,或者与缉获大麻质量变化相关的测试文物。研究发现,在调整大麻质量后,1970 年代至 2000 年代之间报告的 THC%平均增加 10.5 倍,实际上是增加了六到七倍。按照这种说法,那么,当考虑到测试大麻的质量时,报告的长期效力上升幅度约为 57-67%。因此,本研究的结果告诫人们不要不加批判地使用效力监测数据,并强调在未来的政策分析研究中评估效力测量可靠性和解决数据质量问题的重要性。