Nonmedical use of benzodiazepines and Z-drugs in the UK.

AIMS: To estimate prevalence of last 12-month nonmedical use (NMU) of benzodiazepines and Z-drugs (the nonbenzodiazepine hypnotics zaleplon, zolpidem and zopiclone) in the UK. METHODS: Data were collected using the Non-Medical Use of Prescription Drugs survey with poststratification weighting applied to be representative of the UK population (≥16 years). Participants were questioned about whether they had nonmedically used benzodiazepines and/or Z-drugs in the last 12-months and from where they had obtained the drug (including via a prescription, or illicitly from a friend/family member, a dealer or via the internet). Additional questions were asked about last 12-month use of illicit drugs (cannabis, cocaine, 3,4-methylenedioxymethylamphetamine [MDMA], non-pharmaceutical amphetamine, crack cocaine and/or heroin). RESULTS: The study included 10 006 eligible participants representing approximately 52 927 000 UK adults. The estimated prevalence of past 12-month NMU of any benzodiazepine and/or Z-drug was 1.2% (95% confidence interval: 1.0-1.5) corresponding to approximately 635 000 adults; amongst this group only an estimated 4.6% (1.2-8.0) had NMU of both a benzodiazepine and a Z-drug. The highest prevalence of NMU for only Z-drugs was among those who had used heroin in the last 12-months (5.4%, 2.7-10.5), whilst the highest prevalence of NMU for only benzodiazepines was among those who had used illicit stimulants in the last 12-months: cocaine (5.9%, 3.8-8.9), amphetamine (5.6%, 3.1-10.0) and MDMA (5.2%, 3.1-8.8). The drug non-medically used was more commonly acquired without than with a prescription for both only benzodiazepines (70.2%, 59.4-81.1 compared to 51.3%, 41.5-64.6) and only Z-drugs (75.6%, 61.6-89.7 compared to 33.9%, 16.9-51.0). CONCLUSION: There is little overlap between benzodiazepine and Z-drug NMU suggesting distinct nonmedical use of the drugs; future studies need to explore whether this relates to personal preference, drug availability or other factors. A significant proportion are acquiring these drugs for NMU without a prescription, so without guidance and monitoring from a medical practitioner. While the dangers of mixing benzodiazepines and heroin/other opioids are well documented, there is a paucity of data regarding concomitant NMU of benzodiazepines and stimulant drugs, or NMU of Z-drugs and opioids, and, given the prevalence of these combinations, this requires further investigation.

Prevalence and description of kratom (Mitragyna speciosa) use in the United States: a cross-sectional study.

BACKGROUND AND AIMS: Mitragyna speciosa ('kratom') contains mu opioid partial agonists. It is widely available, and occasionally used as a home remedy for opioid use disorder. The Drug Enforcement Agency considers kratom a drug of concern; however, prevalence of use and role in drug misuse are unknown. This study aimed to characterize kratom use in the United States. DESIGN: Cross-sectional Survey of Non-Medical Use of Prescription Drugs (NMURx) Program, 2018 third quarter and 2019 first quarter. SETTING: A validated non-probability online survey in the United States. PARTICIPANTS: A total of 59 714 respondents aged 18 years or older, weighted to represent the adult US population (n = 252 063 800). MEASUREMENTS: In addition to prevalence of past-year kratom and other drug use, behavior proportions were estimated. The Drug Abuse Screening Test (DAST-10) estimated consequences of drug abuse. FINDINGS: The estimated prevalence of past-year kratom use in the adult US population was 0.8% [95% confidence interval (CI) = 0.7-0.9], representing 2 031 803 adults. Life-time prevalence was 1.3% (95% CI = 1.2-1.4), representing 3 353 624 adults. Kratom users were younger (mean 35 years, P < 0.001), with higher proportions of males (61.0 versus 48.6%, P < 0.001), students (14.1 versus 7.5%, P < 0.001) and health-care professionals (9.7 versus 4.5%, P < 0.001) and fewer bachelor's/advanced degree graduates (33.4 versus 42.6%, P < 0.001) compared with non-users. Results were inconclusive on whether there was a difference in kratom use by race, household income or employment status. Among those with past-year kratom use, 36.7% (95% CI = 32.1-41.3) non-medically used prescription opioids, 21.7% (95% CI = 18.0-25.5) used illicit opioids, 54.4% (95% CI = 49.5-59.3) used another illicit drug and 67.1% (95% CI = 62.5-71.8) used cannabis. The DAST-10 profile was more often substantial/severe in kratom users (21 versus 1%, P < 0.001) compared with non-users. CONCLUSIONS: Estimated United States past-year prevalence of kratom use is 0.8%, and kratom users tend to have more serious substance abuse profiles than non-users or users of cannabis, alcohol or cigarettes. To our knowledge, this is the first description of kratom use at the national level.

Non-medical use of benzodiazepines and GABA analogues in Europe.

AIMS: We investigated the prevalence of non-medical use (NMU) of benzodiazepines and GABA analogues in Europe. METHODS: Data were collected using the online Non-Medical Use of Prescription Drugs (NMURx) survey from France, Germany, Italy, Spain and the UK. RESULTS: The study included 55 223 eligible surveys which, after post-stratification weights were applied, represented approximately 260 million European adults. Lifetime NMU of benzodiazepines was highest in Spain (6.5%, 95% CI: 6.0-7.0) and lowest in Germany (1.7%, 1.5-2.0). Lifetime NMU of GABA analogues was highest in Germany (5.4%, 5.0-5.7) and lowest in France (2.2%, 1.9-2.5) and the UK (2.2%, 1.9-2.6) While no notable difference was observed for France or the UK, there was a higher prevalence of last 12-month NMU of benzodiazepines compared to GABA analogues in Italy (2.4 times higher) and Spain (3.0 times higher) and a higher prevalence of NMU of GABA analogues compared to benzodiazepines in Germany (2.6 times higher). CONCLUSION: This study shows that there is variation in NMU of benzodiazepines and GABA analogues among countries. Of particular interest is the high incidence of GABA analogue NMU in Germany and benzodiazepine NMU in Spain. Further research to identify factors and motivations responsible for the higher prevalence observed are essential to inform public health policies in those countries.

An Online Survey for Pharmacoepidemiological Investigation (Survey of Non-Medical Use of Prescription Drugs Program): Validation Study.

BACKGROUND: In rapidly changing fields such as the study of drug use, the need for accurate and timely data is paramount to properly inform policy and intervention decisions. Trends in drug use can change rapidly by month, and using study designs with flexible modules could present advantages. Timely data from online panels can inform proactive interventions against emerging trends, leading to a faster public response. However, threats to validity from using online panels must be addressed to create accurate estimates. OBJECTIVE: The objective of this study was to demonstrate a comprehensive methodological approach that optimizes a nonprobability, online opt-in sample to provide timely, accurate national estimates on prevalence of drug use. METHODS: The Survey of Non-Medical Use of Prescription Drugs Program from the Researched Abuse, Diversion and Addiction Related Surveillance (RADARS) System is an online, cross-sectional survey on drug use in the United States, and several best practices were implemented. To optimize final estimates, two best practices were investigated in detail: exclusion of respondents showing careless or improbable responding patterns and calibration of weights. The approach in this work was to cumulatively implement each method, which improved key estimates during the third quarter 2018 survey launch. Cutoffs for five exclusion criteria were tested. Using a series of benchmarks, average relative bias and changes in bias were calculated for 33 different weighting variable combinations. RESULTS: There were 148,274 invitations sent to panelists, with 40,021 who initiated the survey (26.99%). After eligibility assessment, 20.23% (29,998/148,274) of the completed questionnaires were available for analysis. A total of 0.52% (157/29,998) of respondents were excluded based on careless or improbable responses; however, these exclusions had larger impacts on lower volume drugs. Number of exclusions applied were negatively correlated to total dispensing volume by drug (Spearman ρ=-.88, P<.001). A weighting scheme including three demographic and two health characteristics reduced average relative bias by 31.2%. After weighting, estimates of drug use decreased, reflecting a weighted sample that had healthier benchmarks than the unweighted sample. CONCLUSIONS: Our study illustrates a new approach to using nonprobability online panels to achieve national prevalence estimates for drug abuse. We were able to overcome challenges with using nonprobability internet samples, including misclassification due to improbable responses. Final drug use and health estimates demonstrated concurrent validity to national probability-based drug use and health surveys. Inclusion of multiple best practices cumulatively improved the estimates generated. This method can bridge the information gap when there is a need for prompt, accurate national data.

Nonmedical use of alprazolam in the UK: Results from a nationally representative survey.

There is concern in the UK about nonmedical use (NMU) of alprazolam (Xanax). We investigated the epidemiology of alprazolam NMU compared with diazepam using data from the Survey of Non-Medical Use of Prescription Drugs (NMURx) programme (collected 28 September-1 December 2017). The survey included 10 019 respondents and was weighted by age, sex and region to represent 52 927 659 UK adults. The estimated national prevalence of lifetime NMU of alprazolam was 0.32% (95% confidence interval: 0.19-0.46), and 1.30% (1.06-1.54) for diazepam. The prevalence of NMU in the last 90 days was significantly different when split by age category for alprazolam (P < .001), but not for diazepam (P = .262) with alprazolam NMU being more common among younger adults (age 16-24 years: 0.37%; age 25-34 years: 0.14%; 35 years or older: 0.01%). Further research is needed to fully understand the motivations of alprazolam NMU and to monitor whether the popularity of alprazolam will rise.