Epidemiology of drug use in Perugia (Italy) through the analysis of the Keratin Matrix

Authors

  • Isabella Mercurio Hospital Santa Maria alle Scotte, Siena
  • Gianmarco Troiano University of Siena
  • Paola Melai University of Perugia
  • Veronica Agostinelli University of Perugia
  • Rosaria Simone University of Naples Federico II
  • Nicola Nante University of Siene
  • Mauro Bacci University of Perugia

DOI:

https://doi.org/10.2427/11732

Abstract

Background Drugs and their metabolites can be incorporated into hair so hair testing has become s an alternative and complementary method to assess the extent of drugs abuse. The aim of our study has been to use hair samples to rebuild the epidemiology of illicit substances use  in Perugia.

Methods We conducted a cross-sectional study from May to July 2012 asking hairdressers of Perugia to collect hair samples and to compile a schedule for each one. The samples were analyzed in laboratory: the extraction of basic substances was performed adding methanol; the extraction of acid substances was obtained adding  NAOH.  After derivatization, 1μl of each solution was analyzed through gas chromatography / mass spectrometry The data were  organized in a database and processed using R version 3.2.2.

Results We collected 238 samples. The most detected drugs were: THC-TMS identified in 15 samples, MDMA in 9, Beg-TMS in 8. There is a statistically significant difference in drug use between centre (23,36%) and periphery (5,34%). Age and sex have not represented influencing factors. The substance with the highest concentration in the keratin matrix is ketamine (9834,86 ng/100 mg of hair).

Conclusions The use of keratin matrix offers high advantages in the toxicological analysis compared to conventional biological matrices and let us analyze the situation in Perugia where the increased market of drugs caused constant rise of drug addiction. However, because of the limits of this method, only the simultaneous use of keratin matrix and other traditional indicators, could furnish more precise information.

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Published

2022-04-08

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Original articles