Addiction最新文献

Aims: To determine: (1) the circumstances of death and case characteristics of heroin-related toxicity deaths aged ≥ 65 years in Australia, 2000-2025 and (2) the toxicological profile and major autopsy findings.

Design: Retrospective study of fatal heroin overdose cases aged ≥65 years, 2000-2025.

Setting: Australia-wide.

Cases: 59 cases were identified (65-69 years: 37, ≥70 years: 22), 51 (86.4%) male.

Measurements: Circumstances of death, toxicology, major autopsy findings.

Findings: No case occurred in the period 2000-2010, two between 2011 and 2015 and 57 between 2016 and 2025. All had documented histories of both substance use problems and injecting drug use. Cause of death was drug toxicity (n = 36, 61.0%) or combined drug toxicity and disease (n = 23, 39.0%), the majority being unintentional (n = 49, 83.1%). The final route of administration was by injection in 58 cases. Amongst cases in which toxicology was available for inspection (n = 52), the median free morphine concentration was 0.2 mg/l (0.0-3.7 mg/l), and 6-acetylmorphine was present in 34 (65.4%). Psychoactive drugs other than heroin were present in 45 (86.5%) cases. Of autopsied cases, 18 (56.3%) had severe coronary artery disease, 14 (43.8%) cardiomegaly and 11 (34.4%) replacement fibrosis, indicating a past infarct. Five cases (15.6%) were diagnosed with acute bronchopneumonia, and chronic obstructive pulmonary disease was detected in 12 (37.5%).

Conclusions: A new senior demographic of people who use heroin has emerged in Australia and is being reflected in overdose deaths. Systemic disease contributed to a large proportion of deaths between 2000 and 2025, and the toxicology is consistent with shorter survival times compared with younger cases.

Background and aims: There is evidence to suggest that earlier initiation to alcohol increases the rate and severity of alcohol consumption. However, this often overlooks the fact that earlier initiation also means a longer drinking history. This paper estimated differences in patterns of alcohol use and harm across adolescence and early adulthood, allowing for the fact that the patterns over time may differ depending on the age at which initiation occurred.

Design: Prospective cohort study.

Setting: Australia.

Participants: The Australian Parental Supply of Alcohol Longitudinal Study (APSALS), a cohort of n = 1906 adolescents recruited in adolescence (mean age 12.9) from 107 Australian schools and followed up until adulthood (11 annual waves total, 2010-2021).

Measurements: We defined age of initiation as the age at which alcohol consumption was first reported in the study. Our outcomes were amount of alcohol consumed, monthly heavy episodic drinking, alcohol-related harm and self-reported symptoms of alcohol use disorder in the years following initiation.

Findings: Those who initiated at age 12 had a lower risk of consumption [risk ratio (RR) 0.01; 95% confidence interval (CI) = 0.01-0.02] in the year following initiation (age 13), compared with those who initiated at age 18. Similarly, those who initiated at age 15 had a lower risk of alcohol use disorder in the year after initiation (RR 0.66; 95% CI = 0.52-0.83), compared with those who initiated at age 18. However, at age 20, those who initiated at age 12 showed higher consumption (RR 1.57; 95% CI = 1.18-2.09), monthly heavy episodic drinking (RR 1.24; 95% CI = 1.02-1.51) and alcohol-related harms [incidence-rate ratio (IRR) 1.73; 95% CI = 1.21-2.46] than those who initiated at age 18. Similar results were seen for symptoms consistent with DSM-IV alcohol dependence (RR 1.20; 95% CI = 1.05-1.38), DSM-IV alcohol abuse (RR 1.54; 95% CI = 1.04-2.29) and DSM-5 alcohol use disorder (RR 1.36; 95% CI = 1.12-1.65). However, there was evidence of ageing out, with risk of heavy episodic drinking and alcohol-related harm peaking around age 20 and then declining, regardless of when initiation occurred.

Conclusions: Later initiation to alcohol appears to be associated with more rapid escalation in drinking and related harm, but lower 'peak' harm than earlier initiation. The findings support the current guidelines recommending adolescents avoid alcohol until adulthood, and reinforce the need for public health intervention targeting both children and parents.

Background and aims: Cannabis legalization has increased product availability and use, subsequently necessitating efficient measurements of cannabis use that accurately reflect biomarkers of cannabis exposure (e.g. blood cannabinoid levels). The present study thus sought to compare cannabis use metrics and their associations with biomarkers and examine whether these associations were moderated by sex or age.

Design: Observational study using data from five larger studies.

Setting: Data collection and recruitment occurred in the greater Boulder/Denver metropolitan area in Colorado, USA.

Participants: Individuals (n = 1090, M_age = 32.89, SD = 12.97; 78.35% White; 51.56% female) included regular cannabis users (M_use = 16 days/past month and 4 times/day).

Measurements: Participants completed assessments of typical quantity and frequency of cannabis use via an in-house survey (Cannabis Quantity and Frequency Scale; CQFS) versus past month use via the Timeline Follow Back (TLFB). Cannabis biomarkers were also collected, including blood levels of delta-9 tetrahydrocannabinol (THC) after immediate use and baseline levels of the primary THC metabolite, 11-nor-9-carboxy-tetrahydrocannabinol (THC-COOH) FINDINGS: Separate mixed effects models using TLFB versus CQFS cannabis metric predictors of the two biomarkers including moderators of sex and age resulted in higher adjusted R² values for the CQFS versus TLFB model predicting THC-COOH (0.30 vs 0.27, respectively) and for the TLFB versus CQFS model predicting THC (0.24 vs 0.21, respectively). Additionally, greater CQFS total times of any cannabis/day (i.e. total times/day) was associated with increased THC-COOH [B = 5.85, 95% confidence interval (CI) = 0.66-11.03, P = 0.03] while it was associated with increased THC among males only (B_interaction = 7.80, 95% CI = 0.25-15.34, P = 0.04). TLFB days/month was statistically significantly, positively related with both THC-COOH and THC (B = 2.39, 95% CI = 1.00-3.79, P < 0.001 and B = 4.18, 95% CI = 0.98-7.38, P = 0.01, respectively) with no statistically significant interactions.

Conclusions: The Cannabis Quantity and Frequency Scale (CQFS) measurement of total times/day appears to be a better predictor of general cannabis use than the Timeline Follow Back (TLFB) method. In contrast, TLFB appears to be better at predicting acute use of cannabis than the CQFS.

Background and aims: Understanding lifetime alcohol exposure is fundamental to appreciating the risks of alcohol dependence and the multiplicity of alcohol-related harms, such as cirrhosis. However, most research relies on self-reported alcohol use measures that rarely extend beyond recent consumption. This represents a critical limitation in assessing the relationship between alcohol exposure and biological or psychological outcomes. Concerns about recall bias may be overstated and risk obstructing translational research into long-term effects of alcohol, including treatment engagement. This scoping review examined the evidence for the reliability and validity of self-reported measures of lifetime alcohol consumption.

Methods: We searched the MEDLINE, EMBASE and PsycINFO databases in June 2024 for English-language articles published since 1970. We included studies that performed at least one of the following psychometric assessments on a lifetime alcohol exposure measure: test-retest reliability, internal consistency, concurrent validity or construct validity.

Results: The search identified 1607 unique records. After title and abstract screening, 24 studies underwent full-text review, with nine meeting the inclusion criteria. Most studies were conducted in North America (78%). The most frequently used instrument was the Lifetime Drinking History (LDH) (67%). Across all studies, there were 6010 participants (3478 male, 2532 female), with sample sizes ranging from 49 to 3255. In 78% of studies, alcohol exposure data were collected via face-to-face interview. Eight studies assessed test-retest reliability, with retest intervals ranging from 14 days to 13 years; none assessed internal consistency. Three studies (33%) formally assessed validity. Where assessed, test-retest reliability and concurrent and construct validity were moderate to strong. Test-retest reliability ranged from 0.67 to 0.92, and concurrent and construct validity with external reference measures ranged from 0.40 to 0.80, indicating generally acceptable performance.

Conclusions: Existing instruments for measuring lifetime alcohol exposure appear to be valid and reliable and can overcome concerns regarding biases; however, these instruments vary in structure, lack standardisation and may fail to capture binge or episodic drinking, highlighting important gaps for refinement.

Background and aims: Gamma-hydroxybutyrate (GHB) is an endogenous neurochemical and illicit synthetic drug. Its precursors, gamma-butyrolactone (GBL) and 1,4-butanediol (1,4-BD), are often used as substitutes. We aimed to describe GHB-related harms in New South Wales (NSW), Australia.

Design, setting and cases: Descriptive epidemiological study of data from three administrative datasets: emergency department (ED) presentations from 88 hospitals (1 July 2015 to 31 January 2024 - the latest available), admitted patient data from all NSW hospitals (1 July 2015 to 30 June 2023) and a subset of NSW Police Force seizure data. Note: analysis was not undertaken, data are presented descriptively.

Measurements: ED presentations and hospitalisations were analysed for GHB-related presentations and admissions including severity of presentation, intubation and intensive care. NSW Police Force seizure data were examined for all analytically confirmed samples of GHB, GBL and 1,4-BD to assess trends over time.

Findings: Over the study period, there were 9612 GHB-related ED presentations. Between July 2023 and January 2024, this was 101 per 100 000 unplanned presentations, relative to the previous full-year peak of 73.7 per 100 000 in 2022-2023 and the 2015-2016 rate of 24.9 per 100 000. The majority (56.1%) were assessed as Australian Triage Category 1 or 2, indicating the highest level of need. ED presentations in regional or remote areas accounted for 13.8% of all presentations in the most recent data, relative to 3.4% at the start of the study period. Hospitalisations totalled 6420 episodes, peaking at 19.6 per 100 000 population in 2020-2021. Nearly one in five patients required intubation, and a similar proportion required admission to intensive care. There was a trend of women accounting for a larger proportion of ED presentations and hospitalisations over time. GHB accounted for 0.1% of all police seizures analysed, and showed a shift from GBL to 1,4-BD dominance from 2022 onwards.

Conclusions: Gamma-hydroxybutyrate-related emergency department presentations and hospitalisations in New South Wales, Australia, appear to have increased over the period from 2015 to 2024, which can support public health campaigns to reduce gamma-hydroxybutyrate-related harms.

Background and aims: Understanding the relationship between heat and drug overdose mortality is critical given the ongoing overdose crisis and rising global temperatures driven by climate change. Evidence from local jurisdictions in the United States (US) and Canada indicates that exposure to heat is associated with increased drug overdose fatalities, but the widespread impact of heat on national drug overdose deaths is undetermined. We aimed to determine the effect of heat exposure on drug overdose mortality in the US.

Design: An observational study using monthly, county-level data from 1999 to 2020 and a fixed effect model estimated with linear regression. The model accounts for time-invariant county-month factors and state-level time-specific shocks.

Setting: All counties in the continental US during the months of June to September from 1999 to 2020.

Participants: Decedents in the National Center for Health Statistics restricted Vital Statistics mortality data with a cause of death of a drug overdose, aggregated to county-level mortality rates.

Measurements: All drug overdose mortality rate per 100 000 population. The monthly average maximum heat index (measured in degrees Celsius) was collected from the Centers for Disease Control and Prevention National Environmental Public Health Tracking Network.

Findings: A one-degree Celsius increase in the heat index was associated with an increase in all drug overdose mortality by 0.0098 deaths per 100 000 population [95% confidence interval (CI) = 0.0057-0.014, P < 0.001], with significant effects for deaths related to opioids (0.0060 deaths, 95% CI = 0.0026-0.0095, P < 0.001), cocaine (0.0028 deaths, 95% CI = 0.0012-0.0045, P < 0.001) and psychostimulants (0.0028 deaths, 95% CI = 0.0015-0.0041, P < 0.001). In further analyses, larger impacts were observed after 2013, in counties with greater levels of social vulnerability and in suburban and urban counties. Estimates suggest that approximately 150 excess drug overdose deaths occurred per year during the hottest periods due to heat exposure.

Conclusions: Exposure to heat appears to be associated with increases in drug overdose deaths in the United States in recent decades.

Background and aims: Alcohol consumption is a key preventable cause of disease and injury worldwide. Recent evidence suggests that younger generations may be consuming less alcohol. However, it is still uncertain whether this trend is temporary or indicative of an enduring generational shift. This study sought to determine whether there are generational differences in alcohol consumption in Australia, while accounting for age and other sociodemographic factors.

Design and setting: The analysis used data from the Household Income and Labour Dynamics in Australia (HILDA) Survey.

Participants: The analysis included 23 368 participants (51.9% female) across 23 waves of data. Participants were classified into different generational cohorts according to Pew Research Centre definitions: Silent Generation (1928-1945), Baby Boomers (1946-1964), Generation X (1965-1980), Millennials (1981-1996) and Generation Z (1997-2012).

Measurements: The study included three outcome measures: 1) abstention; 2) typical alcohol consumption per drinking occasion; and 3) typical weekly alcohol consumption.

Findings: Although the likelihood of abstaining from alcohol consumption increased with age, Generation Z [odds ratio (OR) = 17.74, 95% confidence interval (CI) = 13.22-23.80, P < 0.001], Millennials (OR = 9.67, 95% CI = 7.98-11.71, P < 0.001) and Generation X (OR = 3.29, 95% CI = 2.75-3.92, P < 0.001) exhibited increased odds of abstention when compared with Baby Boomers, while the Silent Generation demonstrated decreased odds (OR = 0.33, 95% CI = 0.27-0.41, P < 0.001). Among drinkers, the quantity of per-occasion alcohol consumption reached its peak in early adulthood. Millennials (β = 0.52, 95% CI = 0.44-0.60, P < 0.001) and Generation X (β = 0.40, 95% CI = 0.32-0.47, P < 0.001) self-reported a significantly higher quantity of per-occasion alcohol consumption compared with Baby Boomers, while Generation Z did not significantly differ (β = 0.10, 95% CI = -0.02 to 0.23, P = 0.106) and the Silent Generation consumed significantly less (β = -0.21, 95% CI = -0.30 to -0.11, P < 0.001). Weekly quantity of alcohol consumption among drinkers peaked in early adulthood and midlife, with the Silent Generation [exp(β) = 1.16, 95% CI = 1.09-1.23, P < 0.001] exhibiting the highest levels of consumption, while Generation Z [exp(β) = 0.57, 95% CI = 0.53-0.62, P < 0.001] and Millennials [exp(β) = 0.77, 95% CI = [0.73-0.81, P < 0.001] demonstrated the lowest (compared to Baby Boomers).

Conclusions: In Australia, there appear to be generational differences in alcohol consumption, including an increase in abstention and an overall reduction in alcohol consumption among Generation Z compared with previous generations.

Background and aims: Tobacco smoking has declined dramatically in many high-income countries over the past seventy years. Studies that have mapped this trend have relied on repeat cross-sectional or retrospectively measured smoking data, which have limitations regarding accurate measurement, inclusion of early smokers, and capturing of within-person change over time. Here, we introduce a new resource detailing harmonisable smoking data in four British birth cohort studies spanning 1946-2018 and use these data to document age and cohort changes in smoking.

Design: Longitudinal data from four nationally representative British Birth Cohort Studies, born 1946, 1958, 1970 and 2000/02, respectively.

Setting: Great Britain.

Participants: 50 942 participants were eligible for inclusion in this study (5362 in the 1946c, 16 178 in the 1958c, 16 036 in the 1970c, and 13 366 in the 2001c). Data collection spanned the years 1946-2018.

Measurements: Prevalence of daily smoking and cigarettes smoked per day were measured prospectively at various points across the life course via self-report.

Findings: The prevalence of smoking and the average number of cigarettes smoked by daily smokers declined between each successive cohort. At age 42/43y, prevalence of daily smoking was 33.6% (95% confidence interval [CI] = 31.8%, 35.5%) in the 1946c, 27.3% (95% CI = 26.5%, 28.2%) in the 1958c, and 22.1% (95% CI = 21.3%, 22.8%) in the 1970c. Males smoked more and with greater intensity than females, on average, though sex differences were smaller in latter cohorts. Within a cohort, the prevalence and intensity of smoking peaked in early adulthood (< age 30y) and declined thereafter; participants who continued to smoke daily smoked fewer cigarettes as they grew older.

Conclusions: In Great Britain, smoking prevalence and cigarette consumption appear to have declined substantially between cohorts born across the latter half of the twentieth and early twenty-first centuries. The British Birth Cohorts represent a unique and largely underutilized resource for investigating trends in smoking across life (prenatal to old age) and by year of birth (1946-2001), including changes in the determinants, correlates, and consequences of smoking. We provide syntax and information on items on smoking in these cohorts to catalyse future research, also available at: https://cls-data.github.io/smoking-in-the-cohorts/.

At a time when extensive societal and public health reform is needed to address the factors driving ‘deaths of despair’ in the United Kingdom, the term seems more relevant than ever [1].

Deaths of despair in England, particularly drug- and alcohol-related deaths in males [2], have continued to increase in incidence since the turn of the century (with similar patterns evident in other parts of the United Kingdom). The age-standardised mortality rates attributed to drugs, alcohol and suicide robustly covary across the regions of England (Figure 1). This suggests that the social context in which these deaths occur is important and, as with other health outcomes, indicates that they might have some shared risk factors. It is also apparent that the risk of suicide is greater in those with substance use disorder [3]. Although there are several distinct individual risk factors for drug-, alcohol- and suicide-related deaths, shared risk factors do indeed play a key role [4]. Shared risk factors include unemployment or employment in elementary occupations, living alone, living in the North of England and being middle-aged and of white British ethnicity [4]. In line with this, Figure 1 shows that, across the regions of England, deaths of despair covary with income, economic inactivity and household deprivation. This is not to say that any one of these factors directly causes deaths of despair, rather, this serves to highlight that social context—made up of multiple, intertwined factors—should not be ignored when considering deaths of despair. These causes of death, therefore, appear not to be entirely disparate phenomena because they have shared social determinants [5, 6]. This is in broad alignment with data from the United States, where social isolation and unemployment, which vary by region, are associated with deaths of despair [7].

Withdrawal from the labour force, deprivation and social isolation can, directly or indirectly, lead to increased risk of mental ill health, such as depression and anxiety, as well as substance misuse [8-10]. This, in turn, can lead to diseases of despair, such as suicidal ideation or addiction to, or dependence on, alcohol or illicit drugs, and, eventually, death of despair. In this regard, diseases of despair follow a similar chronic time course, with death often occurring after prolonged mental illness or misuse of drugs or alcohol (or a combination of these). An individual's response to the societal factors which drive despair is likely to determine their risk of disease and death of despair. Similarly, it is clear that the social environment in which an individual experiences personal risk factors plays a role in determining their risk of death of despair [6]. This indicates a complex interaction between personal and societal factors, which are difficult to disentwine. A greater und