Addiction最新文献

Aims: We measured the association between prescribed stimulant medications and overdose among individuals receiving opioid agonist therapy (OAT) for opioid use disorder.

Design: Retrospective cohort study using the British Columbia Provincial Overdose Cohort, a linked administrative database.

Setting: We used data from British Columbia, Canada, from January 2015 through February 2020.

Participants: In total, 9395 individuals contributed 18 273 person-years of follow-up while dispensed OAT.

Measurements: We examined the association between stimulant prescription (primary exposure) and fatal or non-fatal overdose (primary outcome, allowing for recurrent events) after adjusting for potential confounders including sociodemographic characteristics and substance use patterns. As a secondary analysis, we evaluated type of OAT (full agonists involving methadone or slow-release oral morphine versus partial agonist involving buprenorphine/naloxone alone) as a potential effect modifier.

Findings: There were 1746 overdose events; 37 (2.1%) were fatal. Overall, there was no increased risk of overdose among individuals dispensed a stimulant medication while on OAT [adjusted Cox regression hazard ratio (AHR) = 1.13, 95% confidence interval (95% CI) = 0.86-1.49, P = 0.39]. When analyzed by type of OAT medication, for individuals on buprenorphine, dispensation of a stimulant medication was associated with a reduced risk of overdose (AHR = 0.47, 95% CI = 0.23-0.96, P = 0.037) while, for individuals on full agonist OAT, dispensation of a stimulant medication was associated with an increased risk of overdose (AHR = 1.51, 95% CI = 1.09-2.07, P = 0.012).

Conclusions: There does not appear to be an overall increased risk of overdose for individuals co-prescribed a stimulant medication with opioid agonist therapy (OAT). There appears to be a reduced risk of overdose for individuals dispensed buprenorphine with a stimulant medication compared with those dispensed buprenorphine alone, and an increased risk of overdose for individuals dispensed full agonist OAT (methadone or slow-release oral morphine) with a stimulant medication compared with those dispensed full agonist OAT alone.

Background and aims: Primary care systems often screen for unhealthy alcohol use with brief self-report tools such as the 3-item Alcohol Use Disorders Identification Test for consumption (AUDIT-C). There is little research examining whether change in alcohol use measured on the AUDIT-C captures meaningful change in outcomes affected by alcohol use. This study aimed to measure the association between change in AUDIT-C and change in all-cause hospitalization risk, measured in the year after each AUDIT-C.

Design: Retrospective cohort study.

Setting: Health system in the state of Washington, USA, that conducts annual screening with the AUDIT-C in outpatient care.

Participants: Adults (n = 165 101) who had completed at least two AUDIT-Cs 11-24 months apart (2016-2020).

Measurements: AUDIT-C scores were grouped into five risk categories reflecting no drinking (0), drinking without unhealthy alcohol use [1-2 (female)/1-3 (male)] and unhealthy alcohol use with moderate risk [3-6 (female)/4-6 (male)], high risk (7-8), and very high risk (9-12). Changes in AUDIT-C were based on the number of category levels that changed (0-4). Hospitalizations were binary, reflecting one or more hospitalizations in the 365 days after each AUDIT-C, identified from insurance claims.

Findings: Of 165 101 eligible patients, 5.7% and 6.1% were hospitalized the year after the first and second AUDIT-C, respectively. Decreases in AUDIT-C risk category of 1 or ≥2 levels were associated with statistically significant decreases in risk of hospitalization, compared with the change in hospitalization risk for those with no change in AUDIT-C [1-level decrease: ratio of adjusted risk ratios (aRR) = 0.92, 95% confidence interval (CI) = 0.86-0.99; ≥2-level decrease: ratio of aRR = 0.68, 95% CI = 0.58-0.81]. Increases in AUDIT-C risk category of 1 or ≥2 levels were not associated with statistically significant differences in risk of hospitalization, compared with those with no change in AUDIT-C.

Conclusions: A decrease in AUDIT-C score risk category is associated with a decreased risk of both all-cause hospitalizations and hospitalizations with conditions directly or potentially attributable to alcohol. An increase in AUDIT-C score does not appear to be associated with a change in risk of hospitalization in the following year.

Aims: To measure effects between educational attainment and alcohol use as a driver of unequal alcohol-attributable mortality.

Design: Nation-wide cohort study using a longitudinal design, linking data from the 1997-2018 National Health Interview Survey to mortality data of the National Death Index in 2019. The study has an average follow-up time of 10.7 years (SD = 6.4).

Setting: United States.

Participants: Nationally representative sample of adults aged 25 years and older.

Measurements: The outcome was time to 100% alcohol-attributable mortality, censored or last presumed alive by 31 December 2019. Socioeconomic status was operationalized via educational attainment; alcohol use was self-reported and operationalized using a categorical measure with lifetime abstainers as reference category.

Findings: Of a total of 562 632 adults, 901 (635 men and 266 women) died during follow-up from a 100% alcohol-attributable cause of death [15 per 100 000 person years (PY)]. We found a strong interaction effect between low education and Category III alcohol use (>60 g and >40 g per day for men and women, respectively), which was of additive nature as shown by the Aalen's additive hazards model, with 83.68 additional deaths per 100 000 PY (95% confidence interval = 16.48-150.87) found in individuals with low education with Category III drinking compared with a situation when there was no interaction between the two risk factors. A large and statistically significant relative excess risk due to interaction (RERI) of 32.05 from the Cox model supported the interaction. For individuals with low education, the risk associated with Category III drinking was double that for those with high education.

Conclusions: In the United States, people with combined low education and high alcohol consumption (>60 g/day for men, >40 g/day for women) appear to have a higher risk of 100% alcohol-attributable mortality compared with other combinations of educational attainment and drinking.

Background and aims: Opioid smoking is becoming more common in the United States. The aim of this analysis was to estimate relative mortality risk among those who primarily smoke opioids compared with those who inject.

Design: Retrospective propensity score-matched cohort analysis.

Setting: 2006-2021 US treatment episode data from SAMHSA TEDS-D.

Participants: We matched 287 481 individuals in a substance use treatment program reporting smoking opioids as their primary substance use to an equal weighted number of individuals in a substance use treatment program reporting injecting opioids as their primary substance use. The majority of individuals reporting smoking were male (62.6%), 21-29 years old (47.9%), white (65.7%), independently housed (54.3%) and in the West Census Region (70.3%). Cohort characteristics were closely balanced after matching.

Measurements: The outcome of interest was death during a treatment episode. Variables used for matching were year, opioid category, gender, race/ethnicity, age category, census region, housing status, employment status, number of prior treatment admissions, variables associated with opioid use severity (opioid use frequency, treatment setting intensity, age at first opioid use, use of medication-assisted treatment) and other reported substance use (methamphetamine, alcohol, benzodiazepines, cocaine).

Findings: The mortality rate was 6.5 [95% confidence interval (CI) = 5.9-7.1] per 1000 person-years in the smoking cohort and 9.7 (95% CI = 8.8-10.8) per 1000 person-years in the injection cohort, with a mortality rate ratio of 0.67 (95% CI = 0.58-0.77).

Conclusions: Among individuals in substance use treatment in the United States, those who usually smoke opioids appear to have a lower all-cause mortality risk than those who usually inject.

Background and aim: Sedative, hypnotic or anxiolytic use disorders (SHA-UD) are defined by significant impairment or distress caused by recurrent sedative, hypnotic or anxiolytic use. This study aimed to measure trends in the prevalence of SHA-UD diagnoses in adolescent and young adult US Medicaid enrollees from 2001 to 2019.

Design: Annual, cross-sectional study, 2001-2019.

Setting: Medicaid Analytic eXtracts (MAX) and Transformed Medicaid Analytic Files (TAF) from 42 US states with complete data.

Participants/cases: Adolescents (13-17 years) and young adults (18-29 years) with ≥10 months Medicaid enrollment in the calendar year; analytic sample contained 5.7 (2001) to 13.2 (2019) million persons per year.

Measurements: Annual prevalence of SHA-UD in adolescent and young adult Medicaid enrollees [defined as an inpatient or outpatient ICD code (304.1x, 305.4x, F13.1x, F13.2x) in the calendar year] was stratified by sex, race/ethnicity, receipt of a benzodiazepine, z-hypnotic or barbiturate prescription, and selected mental health diagnoses. Absolute and relative percent-changes from 2001 vs. 2019 were summarized. Secondary analyses were restricted to states with more consistent data capture.

Findings: The prevalence of SHA-UD diagnoses statistically significantly increased for adolescents (0.01% to 0.04%) and young adults (0.05% to 0.24%) from 2001 to 2019. Increasing trends were observed in sex and race/ethnicity subgroups, with greatest relative increases among Non-Hispanic Black (624%) and Hispanic (529%) young adults. The trend increased among those with and without a benzodiazepine, z-hypnotic or barbiturate prescription; i.e. young adults with (2001 = 0.39% to 2019 = 1.77%) and without (2001 = 0.03% to 2019 = 0.18%) a prescription. Most adolescents (76%) and young adults (91%) with a SHA-UD diagnosis in 2019 had a comorbid substance use disorder.

Conclusions: Sedative, hypnotic or anxiolytic use disorders (SHA-UD) diagnoses increased 3- to 5-fold between 2001 and 2019 for adolescent and young adult US Medicaid enrollees, with prevalence remaining low in adolescents. The increase over two decades may be attributed to changes in the availability, use and misuse of sedative, hypnotic and anxiolytic medications and to increased detection, awareness and diagnosing of SHA-UD.

Background/aims: E-cigarettes are frequently used by people who smoke. This study measured how the prevalence and patterns of smoking and vaping ('dual use') in England have changed as the vaping market has rapidly evolved.

Design: Representative monthly cross-sectional survey, July 2016 to April 2024.

Setting: England.

Participants: 128 588 adults (≥18y).

Measurements: Logistic regression estimated associations between survey wave and dual use. Descriptive statistics were used to analyse patterns of smoking and vaping, overall and by sociodemographic, smoking and vaping characteristics and harm perceptions of e-cigarettes vs. cigarettes.

Findings: Across the period, the overall prevalence of dual use increased non-linearly from 3.5% to 5.3% of adults [prevalence ratio (PR) = 1.49 (1.25-1.76)]. Among adults who smoked, the proportion who also vaped was relatively stable up to mid-2021, at an average of 18.6% between July 2016 and May 2021, then increased rapidly to 34.2% by April 2024 [PR = 1.76 (1.48-2.09)]. This increase was greatest at younger ages [e.g. from 19.6% to 59.4% among 18- to 24-year-olds; PR = 3.04 (2.28-4.23)]. The most common pattern of dual use across the period was daily cigarette smoking with daily vaping [49.0% (47.3-50.8%)]. Over time, the proportion of dual users reporting daily cigarette smoking with non-daily vaping decreased [from 35.2% to 15.0%; PR = 0.43 (0.29-0.63)], offset primarily by an increase in the proportion reporting non-daily cigarette smoking with daily vaping [from 7.6% to 21.5%; PR = 2.84 (1.71-4.72)]. Daily cigarette smoking with daily vaping was more common (and non-daily cigarette smoking with daily vaping less common) among dual users who were older, less advantaged, mainly smoked hand-rolled cigarettes, had stronger urges to smoke and had been vaping for ≤6 months. Daily vaping was more common among dual users who thought e-cigarettes were less/equally harmful as cigarettes, or were unsure.

Conclusions: In England, vaping prevalence has increased rapidly among adults who smoke since 2021, which was when disposable e-cigarettes started to become popular. Since 2016, patterns of dual use have shifted away from more frequent smoking towards more frequent vaping. This may be the result of increasing prevalence of dual use among younger adults, who are more likely than older dual users to smoke non-daily and vape daily.

Aims: Some cannabis consumption methods (e.g. smoking, vaping, dabbing) are associated with more harms than others (e.g. sublingual, transdermal). We aimed to examine differences in prevalence of cannabis consumption methods by people with medically recommended-only vs. nonmedical-only cannabis use.

Design and setting: Cross-sectional, US nationally representative data from the 2022 National Survey on Drug Use and Health (NSDUH).

Participants: 14 271 NSDUH participants aged ≥12 with past-year cannabis use.

Measurements: NSDUH asked respondents with past-year cannabis use about their consumption methods [i.e. smoking, vaping, eating or drinking, dabbing (consuming a concentrated form with a dab rig/pen), oral/sublingual, transdermal or taking pills] and if healthcare professionals recommended any cannabis use. If 'no', respondents were classified as having 'nonmedical-only cannabis use'. If 'yes', they were asked if all cannabis use was recommended and, if so, they were classified as having 'medically recommended-only cannabis use'; otherwise, they were classified as having 'medical and nonmedical cannabis use'.

Findings: Among people reporting cannabis use, 10.7% [95% confidence interval (CI) = 9.7%-11.7%] reported medically recommended-only use, and 83.0% (95% CI = 81.7%-84.3%) reported nonmedical-only use. Smoking was the predominant method for nonmedical-only use (79.2%, 95% CI = 77.7%-80.7%) and for medically recommended-only use (73.7%, 95% CI = 68.8%-78.2%). Vaping prevalence (45.6%, 95% CI = 40.9%-50.4%) and eating/drinking prevalence (45.7%, 95% CI = 40.7%-50.7%) were similar among people with medically recommended-only use. Vaping prevalence was 1.3 times higher [adjusted prevalence ratio (APR) = 1.3, 95% CI = 1.2-1.4] for medically recommended-only than for nonmedical-only use (38.3%, 95% CI = 32.7%-44.3%). Dabbing prevalence was 1.5 times higher (APR = 1.5, 95% CI = 1.3-1.7) for medically recommended-only than for nonmedical-only use [24.4% (95% CI = 20.5%-28.8%) vs 16.4% (95% CI = 15.3%-17.7%)]. Higher prevalence of oral/sublingual and transdermal methods was associated with medically recommended-only use.

Conclusions: Among people with past-year medically recommended-only cannabis use in the US, three-fourths reported smoking cannabis and almost half reported vaping and eating/drinking cannabis. Cannabis vaping prevalence and dabbing prevalence were 1.3-1.5 times higher, respectively, among people with medically recommended-only use than people with nonmedical-only use.