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Record W4392925879 · doi:10.1111/add.16469

Trends in substance use and related harms among older adults in high‐income countries

2024· letter· en· W4392925879 on OpenAlexaff
Rachel Sutherland, Natasa Gisev, Sarah Larney

Bibliographic record

VenueAddiction · 2024
Typeletter
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
FundersSeqirus
KeywordsLife expectancyBaby boomersGerontologyDemographyPopulationMedicineBaby boomHarmCohortGeneration xPsychologyEnvironmental healthSociologyDemographic economics

Abstract

fetched live from OpenAlex

It was hypothesised more than 20 years ago that as the baby boomer generation aged, there would be an increase in substance use and related harms among older adults. There is an increasing body of evidence to support these projections, however, it is unclear whether our health systems are equipped to deal with the complex and multidisciplinary needs of these individuals. The global population is ageing, with those 65 years old and over increasing in number faster than all other age groups. In high-income countries, this changing demography is largely being driven by a decrease in fertility, increase in life expectancy and the ageing ‘baby boomer’ generation (individuals born during the post-war period of 1946–1964). Higher rates of substance use among baby boomers, compared to earlier generations, have been consistently documented, and while it was initially thought that many of these individuals would ‘mature out’ of such use, others have long hypothesised that as the baby boomer generation aged, there would be a substantial increase in the prevalence of substance use and related harms among older adults [e.g. 1]. This, combined with more extensive medicine use as people age, raised substantial concerns about the impact of this ageing demographic on health services, including harm reduction and substance use treatment services. So, two decades on, have these predictions eventuated? Despite surprisingly little literature examining trends in substance use and harms among this cohort in the subsequent decades, we would argue that the answer is a resounding yes, although much of the literature is based in English-speaking countries. There is evidence across high-income countries that alcohol use and related harms are increasing among older adults, although there is considerable cross-country variation, which is not surprising given well-documented differences in drinking cultures across countries. Birth cohort studies have shown that older cohorts have much higher drinking participation than younger cohorts [e.g. 2], while analyses of 179 881 adults aged ≥50 years observed repeatedly between 1998 and 2016 found that the proportion of older adults who drink alcohol increased in 13 of 21 countries [3]. Both moderate and heavy drinking in later life were reported to be increasing in Austria, Czech Republic and the United States, but decreasing in Italy and Poland. In the United States, increases in binge drinking, alcohol-related harms and alcohol-related treatment episodes have been observed among older adults over the last 20 years [e.g. 4, 5], whereas alcohol-related hospitalisations and alcohol-induced deaths among Australians aged ≥50 years have increased over the past two decades [6]. Alongside increasing alcohol use in older adults is an increased risk of adverse events associated with prescription medicines, particularly psychotropic medicines. Although psychotropic medicine use has increased among older adults in some countries [7], trends do vary across countries and medicine types. Notably, providing safe and effective medical treatment to an ageing population is recognised as an ongoing global challenge. For example, despite their potential clinical need, psychotropic medicines are a major contributor to hospitalisations in older adults [8]. Furthermore, although the concurrent use of multiple medicines (termed polypharmacy if ≥5 medicines) may be necessary to treat the multiple, chronic health needs of older adults, polypharmacy can also be associated with poor health outcomes, including increased risk of nutritional deficiencies, falls, frailty, impaired cognition, more frequent hospitalisation and premature mortality [e.g. 9]. This has important implications when understanding the potential risks of alcohol and other substance-related harms in older adults. With respect to rates of use of illicit drugs among older adults, these have received far less attention in the literature, however, there is some evidence that this is an increasing concern. In Australia and the United States, there have been increases in the use of cannabis among older adults [10], as well as an increase in the rate of treatment episodes with cannabis dependence nominated as the principal diagnosis in Australia [6]. Given the global shift towards the legalisation of cannabis (for recreational and/or medicinal purposes), increases in cannabis marketing exposure, and the subsequent increase in use of cannabis for a wide range of acute and chronic health conditions, we expect that there will be a considerable increase in the number of older adults, globally, who experience cannabis use disorder or other cannabis-related harms. The prevalence of other illicit drug use among older adults remains low [11], although there is some evidence of an increase in stimulant and opioid-related harms. Specifically, in Australia, there has been a 13-fold increase in amphetamine-type stimulant related hospitalisations and deaths among Australians aged 50 or older over the past 20 years [6], while in the United States, there have been reported increases in the prevalence of weekly cocaine use and cocaine use disorder [12], as well as an increase in older people entering treatment for heroin and substances other than alcohol [13, 14]. In Australia, the proportion of clients receiving opioid agonist treatment who are 60 years or older has increased eightfold over the past decade, overtaking the proportion of clients aged <30 years from 2018 onwards [15]. There is also concern regarding the ageing population of people who inject drugs, a phenomenon that has been documented in the United States, the United Kingdom and Australia [16, 17]. In the United Kingdom, this was found to be the result of large cohorts of people initiating injecting drug use in the 1980s and 1990s, with fewer people initiating after 2000, resulting in an older average age (30s and 40s) and longer injecting histories (≥15 years) [17]. Although these individuals may not technically meet the definition for ‘older adults’, there is increasing recognition that drug use accelerates age-related pathophysiological processes and that these individuals are, therefore, likely to experience greater age-related declines in functioning than their peers of similar chronological age. Indeed, the age range that defines ‘older adults’ is not clear in substance use research [18], and this is an area that requires urgent attention to better define the population of interest and determine appropriate responses. In summary, there is clear evidence that substance-related harms have increased among older adults in high-income countries, although there is substantial variation across countries and substances, with much of the evidence originating from English-speaking countries and comparatively little known about trends in Europe, and Central and South America. This trend is likely being driven by multiple factors, including a higher baseline level of substance use among the baby boomer generation and increasing use of psychotropic medicines as people age. However, while there have been global efforts targeting unnecessary polypharmacy with subsequent declines noted in several countries [19], the health and social needs of older adults experiencing alcohol and other drug related harms remain under researched. There is an urgent need to increase awareness of these issues among both health professionals and the older adult population, and to improve the capacity of our current health systems to provide multidisciplinary and evidence-informed interventions to address the chronic and complex health needs of these individuals. Rachel Sutherland: Conceptualization (lead); writing—original draft (lead); writing—review and editing (equal). Natasa Gisev: Conceptualization (supporting); writing—original draft (supporting); writing—review and editing (equal). Sarah Larney: Conceptualization (supporting); writing—original draft (supporting); writing—review and editing (equal). None. R.S. has received untied educational funds from Seqirus. Funding from this organisation has now ceased, and funding was for work unrelated to this paper. S.L. has received advisory board fees from Gilead Sciences, unrelated to the present paper.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.236
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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