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. Author manuscript; available in PMC: 2026 Feb 11.
Published before final editing as: J Stud Alcohol Drugs. 2025 Dec 11:10.15288/jsad.25-00346. doi: 10.15288/jsad.25-00346

Lifetime Cannabis Use Is Associated with Brain Volume and Cognitive Function in Middle-Aged and Older Adults

Anika Guha 1,*, Zening Fu 2, Vince Calhoun 2, Kent E Hutchison 1
PMCID: PMC12889878  NIHMSID: NIHMS2135359  PMID: 41379083

Abstract

Objective:

Cannabis use has increased among older adults, yet the neurocognitive effects in this demographic remain unclear. Prior work has suggested cannabis may increase brain volume in areas rich in cannabinoid (CB1) receptors, though negative effects are often reported in adolescents. This study sought to clarify the relationship between cannabis use and brain health among middle-aged and older adults.

Method:

Using data from the UK Biobank, which includes health information from over 500,000 adults, associations between cannabis use, regional brain volume, and cognition in participants aged 40–70 years (mean age = 54.5) were evaluated.

Results:

Lifetime cannabis use was positively associated with regional brain volume in CB1-rich regions, including the caudate, putamen, hippocampus, and amygdala. Greater lifetime use was also linked to better performance in learning, processing speed, and short-term memory. Individuals reporting use limited to adolescence also showed larger regional volumes and better cognitive performance than non-users. Sex differences in cannabis effects on brain volume and cognition were also observed.

Conclusions:

Results highlight that cannabis may influence brain health differently across the lifespan, potentially offering protective effects in older age while posing risks earlier in development. Protective effects may result from endocannabinoid-mediated modulation of inflammation, immune function, and neurodegeneration. Observed sex differences likely reflect variation in the endocannabinoid system and underscore the importance of considering sex as a biological variable in studies of cannabis and brain health.

Keywords: Cannabis, older adults, aging, cognition, neuroimaging, brain volume

Introduction

The global rise in cannabis use (Han & Palamar, 2020) has sparked a need to understand its long-term effects on brain health (Hafkemeijer et al., 2014; Li et al., 2024). Among adults aged 50 and older, cannabis use has increased markedly (Han & Palamar, 2020). This trend includes older adults with chronic conditions, such as those unable to take conventional pain medications, or those seeking alternatives for sleep disturbances (Han & Palamar, 2020; Han et al., 2017; Pocuca et al., 2021; Roy et al., 2020; Yang et al., 2021). Importantly, the cognitive and neurological effects of cannabis use in this demographic remain unclear.

Regional brain volume represents a key structural marker of neural integrity and clinically meaningful index of brain health in aging adults. Age-related neurodegeneration does not occur uniformly across the brain; rather, specific regions, such as the hippocampus, are particularly vulnerable to structural decline (Veldsman et al., 2021; Xiao et al., 2023). Multiple large-scale and longitudinal studies show that larger brain volumes are associated with better performance in domains of cognitive function, including memory, executive function, and sustained attention in older adults (Armstrong et al., 2020; Fletcher et al., 2018; Janacsek et al., 2022; Weerasekera et al., 2023). Larger brain volumes also mediate the relationship between aging and cognitive performance (Armstrong et al., 2020; Janacsek et al., 2022; Rangus et al., 2024), suggesting that maintaining brain structure is key to preserving cognitive abilities.

Research on cannabis and brain structure has produced mixed results. A 2019 meta-analysis linked cannabis use to reduced hippocampal and orbitofrontal volume among individuals ranging from 16–40 years of age (Lorenzetti et al., 2019). A recent UK Biobank study of individuals over the age of 60 reported an association with lower overall gray matter volume, but did not assess specific regions (Vered et al., 2024). Other studies of older adults (60 years and older) have reported increased subcortical volumes, though these had small samples and rarely included cognitive assessments or found no relationships to cognitive function (Karoly et al., 2021; Mackey et al., 2019; Thayer et al., 2017; Thayer et al., 2019). Thus, the long-term effects of cannabis on regional brain volume and cognition in aging remain unclear.

Using data from the UK Biobank, this study investigated associations between cannabis use, regional brain volume, and cognitive function in aging adults. Although assessment of cannabis use is rudimentary and fairly limited in the UK Biobank, the strength of this resource lies in its exceptionally large and well-characterized sample. Despite the lack of more detailed information on patterns, frequency, or modes of cannabis use, the scale of the sample enhances the generalizability and translational value of findings, offering insights that would be difficult to obtain from smaller studies.

It was hypothesized that cannabis use would be associated with greater brain volume consistent with earlier studies in this population (Karoly et al., 2021; Mackey et al., 2019; Thayer et al., 2017; Thayer et al., 2019), particularly in regions previously demonstrating a high density of CB1 receptors ((Fuerte-Hortigón et al., 2021; Glass et al., 1997; Herkenham et al., 1991; Weinstein et al., 2016). Although larger regional brain volumes were hypothesized in the a priori regions of interest, and larger brain volume is generally associated with better cognitive performance, prior research has typically shown a negative relationship between cannabis use and cognition. Given these mixed findings, we did not form a specific directional hypothesis for the present study (Meier et al., 2022).

Method

Study Design and Participants

De-identified data from the UK Biobank was used in accordance with STROBE reporting guidelines. Ethics are managed by the UK Biobank Ethics and Governance Council. The UK Biobank is a prospective, longitudinal, cohort study of 502,412 people living in the UK, aged 40–69 years at recruitment between 2006 and 2010, who consented in writing to long-term follow-up approximately every 4 years (Sudlow et al., 2015). Participants answered detailed questions about their health and lifestyle, underwent imaging including magnetic resonance imaging (MRI), and completed cognitive tests.

Field references for the variables analyzed are in Supplemental Table 1 and further details are available in the UK Biobank data showcase. Variables came from instance 2_0, the initial imaging visit for all participants, as this timepoint had the largest sample of participants with MRI data. Of those with data regarding cannabis use, a total of N = 25,809 individuals had volumetric brain data and N = 16,728 had cognitive assessment data for analyses of the present study.

Regional Brain Volume

Brain imaging used 3T MRI scanners following UK Biobank protocols (Miller et al., 2016). Additional information can be found in the Supplemental Methods. Bilateral brain regions of interest for the present study were selected based on their high density of cannabinoid (CB1) receptors, (Fuerte-Hortigón et al., 2021; Glass et al., 1997; Herkenham et al., 1991; Weinstein et al., 2016) thought to be especially relevant to evaluation of effects of cannabis use. Regions evaluated included: caudate, putamen, hippocampus, orbitofrontal cortex, anterior cingulate, posterior cingulate, anterior parahippocampal gyrus, and posterior parahippocampal gyrus. All regional volumes are expressed in cubic millimeters (mm3). Outliers (> ±3.29 SD) were excluded to meet statistical assumptions.

Assessment of Cognitive Function

The present study included assessment of cognitive tests associated with domains of learning, processing speed, memory, and attention due to their association with lifetime cannabis use (Meier et al., 2022). Tests evaluated included: Paired Associate Learning, Reaction Time, Symbol Digit Substitution, Numeric Memory, Prospective Memory, and Trail Making #1 and #2. Details regarding these cognitive tests can be found in the Supplemental Methods.

Variables Included in Analyses

The primary independent variable of interest was lifetime cannabis use derived from the “Ever used cannabis” variable from the UK Biobank. Participants were asked, “Have you used cannabis (marijuana, grass, hash, ganja, blow, draw, skunk, weed, spliff, dope), even if it was a long time ago?” with possible responses of “No,” “Yes, 1–2 times,” “Yes, 3–10 times,” Yes, 11–100 times,” and “Yes, more than 100 times.” To evaluate differences between non-users, moderate users, and heavy users in the present study, participants were then categorized as follows: None (0 Times), Moderate (1–100 Times), and High (More Than 100 Times). This recoding aligns with conceptually meaningful distinctions commonly used in substance use research. Specifically, the “no use” category denotes complete abstinence, which is a critical reference group when examining associations with cannabis exposure (Feingold et al., 2015). The “0–100 times” group represents low to moderate or experimental use, which has been characterized as a qualitatively different pattern from chronic or dependent use (Pacek et al., 2013). The “more than 100 times” category reflects heavier, more regular use that is often associated with increased risk of cannabis use disorder and adverse outcomes (Hasin et al., 2015).

Given evidence that cannabis use during adolescence, a period of heightened neurodevelopmental vulnerability, may have lasting effects on brain structure and function (Albaugh et al., 2021), the “Age when last took cannabis” variable was used to compare individuals who reported use during adolescence but not later in life to those who reported no history of use. An age cutoff of 25 years was selected to reflect the approximate end of neurodevelopmental maturation (Casey et al., 2008; Giedd, 2004; Sowell et al., 1999; Tamnes et al., 2010). Comparing this group to non-users allows for the examination of potential long-term consequences of adolescent only cannabis exposure, independent of ongoing or later-life use. This approach was informed by prior research linking adolescent cannabis use to alterations in brain structure and executive functioning in adulthood (Albaugh et al., 2021; Lisdahl et al., 2013; Meier et al., 2012; Orr et al., 2019).

Sex was assessed as a factor of interest to evaluate potentially meaningful interactions between sex and cannabis use. The interaction between cannabis use and age was of initial interest, though preliminary analyses did not return any significant or trending interaction effects on brain volume or cognitive measures (see Results). Therefore, age was included primarily as a covariate. Alcohol and tobacco use were considered relevant covariates of non-interest whose inclusion in analyses could serve to enhance validity by isolating cannabis-specific effects and reduce confounding effects of polysubstance use. The “Smoking Status” variable, which summarizes current/past tobacco smoking, was used to quantify smoking behavior and responses were categorized as: “Never,” “Previous,” and “Current.” Responses to the question, “Frequency of drinking alcohol” were used to quantify alcohol use and responses were categorized as: “Daily or almost daily,” “Three or four times a week,” “Once or twice a week,” “One to three times a month,” “Special occasions only,” and “Never.”

Statistical Analysis

Multivariate analyses of covariance (MANCOVAs) were conducted to evaluate effects of cannabis use and sex on regional brain volume and cognitive function while controlling for potential confounding variables. Analysis followed a factorial design, with cannabis use (lifetime cannabis use: no use, moderate use, high use; adolescent cannabis use: non-user, used only during adolescence) and sex (male, female) as the independent variables of interest. Analyses were performed using IBM SPSS (IBM Corp, 2023). Significance levels were set at p < 0.05 and all analyses were two-tailed.

In addition to age, smoking status, and alcohol use, intracranial volume (ICV) was included as a covariate of non-interest for assessment of effects on brain volumes. Wilks’ Lambda was used to determine the significance of the overall multivariate effects of cannabis use and sex. The Benjamini-Hochberg procedure was used to control for the false discovery rate and adjusted p-values are provided. Follow-up post-hoc univariate ANCOVAs were performed for regions and cognitive tests showing multivariate effects and pairwise p-values adjusted using Sidak correction are provided for main and simple effects.

Results

Demographic

Demographic variables are shown in Table 1. Significant differences between cannabis use groups were observed for age (F(2,26359) = 490.83, p < 0.001), sex (F(2,26359) = 92.83, p < 0.001), smoking status (F(2,26350) = 1426.09, p < 0.001), and frequency of alcohol use (F(4,26338)= 83.95, p < 0.001). LSD post hoc analyses demonstrated that for all these effects, significant differences were found between all three cannabis use groups following a linear trend, such that greater cannabis use was consistently associated with younger age, higher rates of smoking tobacco products and drinking alcohol, and men reported higher levels of use.

Table 1:

Demographic data for individuals included in the present study.

Lifetime Cannabis Use None (N = 20,391) 1–100 Times (N = 5,338) More than 100 Times (N = 633)
Age M = 64.3 SD = 7.4 M = 61.3 SD = 7.0 M = 58.9 SD = 6.7
Sex
 Female 56.8% 49.9% 35.2%
Smoking Status (tobacco)
 Never 70.8% 41.6% 8.3%
 Previously 27.3% 52.7% 71.1%
 Current 2% 5.6% 20.6%
Frequency of Alcohol Use
 Never 7.9% 3.6% 5.5%
 Monthly or Less 13.2% 8.3% 10.3%
 2–4 Times per Month 19.4% 17.l% 13.7%
 2–3 Times per Week 31.1% 33.1% 27.6%
 4 or More Times per Week 28.3% 37.8% 42.8%
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Note: M = Mean, SD = Standard Deviation.

Main Effect of Cannabis Use on Regional Brain Volume:

Regional brain volume differed by lifetime cannabis use (F(18,24569) = 2.0, p < 0.001, Wilk’s Λ = 0.99, η2 = 0.001). Right caudate (F(2, 24595) = 3.1, p = 0.04, adjusted p = 0.07), bilateral putamen (left: F(2,24595)= 8.0, p < 0.001, adjusted p = 0.005; right: F(2, 24595) = 4.5, p = 0.01, adjusted p = 0.04), bilateral hippocampus (left: F(2, 24595) = 7.5, p < 0.001, adjusted p = 0.005; right: F(2, 24595) = 5.3, p = 0.005, adjusted p = 0.02), bilateral amygdala (left: F(2, 24595) = 7.8, p < 0.001, adjusted p = 0.005; right: F(2, 24595) = 3.24, p = 0.04, adjusted p = 0.08), and bilateral anterior cingulate (left: F(2, 24595) =3.3, p = 0.04, adjusted p = 0.07; right: F(2, 24595) =3.5, p = 0.04, adjusted p = 0.07) demonstrated a main effect of cannabis use such that greater regional volumes were associated with higher frequency of cannabis use (Figure 1). Bilateral posterior cingulate demonstrated a main effect such that greater regional volumes were associated with a lower frequency of cannabis use (left: F(2, 24595) =3.29, p = 0.04, adjusted p = 0.07; right: F(2, 24595) = 3.46, p = 0.03, adjusted p = 0.07).

Figure 1:

Figure 1:

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Regional brain volume by a) lifetime cannabis use (no use, between 1–100 times, more than 100 times) and b) most recent cannabis use (no use, last use in adolescence [0–25 years of age]). Covariates from the model are evaluated at the following values: intracranial volume = 1,542,453.35, age = 63.44 years, smoking status (0 = Never , 1 = Previously, 2= Current) = 0.4, frequency of alcohol use (0= Never; 1 = Monthly or less, 2 = 2 to 4 times a month; 3= 2 to 3 times a week; 4= 4 or more times a week) = 2.03. Error bars denote +/−1 standard error. Asterisks represent significant differences between conditions (*p < 0.05, **p < 0.01, ** p < 0.001).

Post hoc tests revealed that the moderate cannabis use group (lifetime use between 1–100 times) demonstrated larger regional brain volumes than the no cannabis use group for left putamen (p < 0.001, adjusted p < 0.001, 95% CI [10.0, 45.8]), right putamen (p < 0.001, adjusted p = 0.02, 95% CI [2.4, 37.0]), right caudate (p = 0.03, adjusted p = 0.09, 95% CI [3.8, 36.4]), left hippocampus (p < 0.001, adjusted p < 0.001, 95% CI [6.7, 39.4]), right hippocampus (p < 0.001, adjusted p = 0.001, 95% CI [3.8, 36.4]), left amygdala (p < 0.001, adjusted p < 0.001, 95% CI [4.2, 22]), left anterior parahippocampal gyrus (p = 0.008, adjusted p = 0.02, 95% CI [0.9, 29.0]), and right anterior parahippocampal gyrus (p = 0.006, adjusted p = 0.02, 95% CI [0.1, 29.9]). The high cannabis use group (lifetime use more than 100 times) demonstrated larger brain volumes than the no cannabis use group for right amygdala (p = 0.03, adjusted p = 0.1. 95% CI [−3.9, 49.5]). The no cannabis use group demonstrated larger left posterior cingulate volumes than the high use group (p = 0.04, adjusted p = 0.4, 95% CI [−10.4, 99.9]) and larger right posterior cingulate gyrus volumes than the moderate use group (p = 0.03, adjusted p = 0.3, 95% CI [−2.2, 40.2]).

Regional brain volume also differed between non-users and those who had only used cannabis during adolescence (F(18, 21557) = 2.38, p < 0.001, Wilk’s Λ = 0.95, η2 = 0.001). Left putamen (F(1, 21557) = 17.36, p < 0.001, adjusted p = 0.0005, 95% CI [4759.8, 4772.9]), right putamen (F(1, 21557) = 10.07, p = 0.002, adjusted p = 0.007, 95% CI [4816.5, 4829.1]), left hippocampus (F(1, 21557) = 12.72 , p < 0.001, adjusted p = 0.002, 95% CI [3782.4. 3794.3]), right hippocampus (F(1, 21557) = 16.38, p < 0.001, adjusted p = 0.0005, 95% CI [3896.2, 3908.1]), left amygdala (F(1, 21557) = 8.35, p = 0.004, adjusted p = 0.01, 95% CI [1258.0, 1264.5]), and right accumbens (F(1, 21557) = 4.62, p = 0.03, adjusted p = 0.09, 95% CI [388.9, 391.8]) volumes were larger among adolescent users than non-users (Figure 1b).

Main Effect of Sex on Regional Brain Volume

Regional brain volume differed by sex (F(18,24569) = 36.2, p < 0.001, Wilk’s Λ = 0.97, η2 = 0.03). Men demonstrated larger regional volumes than women for bilateral putamen (left: F(1, 24595) = 238.6, p < 0.001, adjusted p < 0.001,95% CI [191., 246.7]; right: F(1, 24595) = 301.5, p < 0.001, adjusted p < 0.00195% CI [209.4, 263.0]), bilateral hippocampus (left: F(1, 24595) = 12.1, p < 0.001, adjusted p < 0.001, 95% CI [−19.3, 70.0]; right: F(1, 24595) = 15.7, p < 0.001, adjusted p < 0.001, 95% CI [25.1, 75.6]), bilateral amygdala (left: F(1, 24595) =43.7, p < 0.001, adjusted p < 0.001, 95% CI [31.9, 59.5]; right: F(1, 24595) =46.9, p < 0.001, adjusted p < 0.001, 95% CI [38.4, 69.3]), bilateral accumbens (left: F(1, 24595) =26.5, p < 0.001, adjusted p < 0.001, 95% CI [10.5, 23.3]; right: F(1, 24595) = 6.6, p = 0.01, adjusted p = 0.1, 95% CI [1.9, 13.9]), bilateral orbitofrontal cortex (left: F(1, 24595) = 22.8, p < 0.001, adjusted p < 0.001, 95% CI [191.5, 247.0]; right: F(1, 24595) = 20.6, p < 0.001, adjusted p < 0.001, 95% CI [209.4, 262.3]), bilateral posterior cingulate (left: F(1, 24595) =69.2, p < 0.001, adjusted p < 0.001, 95% CI [104.2, 168.3]; right: F(1, 24595) = 34.0, p < 0.001, adjusted p < 0.001, 95% CI [63.9, 129.5]), bilateral anterior parahippocampal gyrus (left: F(1, 24595) =149.0, p < 0.001, adjusted p < 0.001, 95% CI [113.5, 157.0]; right: F(1, 24595) =185.8, p < 0.001, adjusted p < 0.001, 95% CI [136.0, 182.1]), and left posterior parahippocampal gyrus (F(1, 24595) = 12.3, p < 0.001, adjusted p < 0.001, 95% CI [9.7, 33.3]). Women demonstrated larger regional volumes than men for bilateral anterior cingulate (left: F(1, 24595) =31.2, p < 0.001, adjusted p < 0.001, 95% CI [96.0, 200.0]; right: F(1, 24595) =10.1, p = 0.001, adjusted p = 0.005, 95% CI [35.8, 152.3]).

Interaction Between Cannabis Use and Sex for Regional Brain Volume:

An overall interaction between lifetime cannabis use and sex was observed (F(36,49138) = 1.47, p = 0.03, Wilk’s Λ = 0.99). Right putamen (F(2, 24569) = 4.2, p = 0.02, adjusted p = 0.1) and left accumbens (F(36,33048) = 7.3, p < 0.001, adjusted p = 0.01) demonstrated an interaction between cannabis use and sex (Figure 2). Post hoc tests revealed that for the right putamen, men in the no cannabis use group demonstrated smaller regional volume than those in the moderate cannabis use group (p < 0.001, adjusted p = 0.004, 95% CI [7.1, 55.9]) and the high cannabis use group (p = 0.02, adjusted p = 0.1, 95% CI [−6.9, 104.4]). For the left accumbens, women in the high cannabis use group demonstrated smaller regional volume than those in the no (p = 0.01, adjusted p = 0.07, 95% CI [1.0, 35.4]) or moderate (p = 0.03, adjusted p = 0.2, 95% CI [−1.1, 34.0]) cannabis use groups. Men with high use had greater left accumbens volume than non-users (p = 0.01, adjusted p = 0.02, 95% CI [0.1, 26.8]).

Figure 2:

Figure 2:

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Regional brain volume by sex (X-axis) and a) lifetime cannabis use (blue = no use, red = between 1–100 times, green = more than 100 times), and b) period of most recent cannabis use (blue = no use, red = last use in adolescence [0–25 years of age]). Covariates from the model are evaluated at the following values: intracranial volume = 1,542,453.35, age = 63.44 years, smoking status (−3 = Prefer not to answer; 0 = Never , 1 = Previous, 2= Current) = 0.4, frequency of alcohol use (0= Never; 1 = Monthly or less, 2 = 2 to 4 times a month; 3= 2 to 3 times a week; 4= 4 or more times a week) = 2.03. Error bars denote +/−1 standard error. Asterisks represent significant differences between conditions (*p < 0.05, **p < 0.01, ** p < 0.001).

A trending overall interaction between cannabis use only during adolescence and sex was also observed (F(18,21557) = 1.61, p = 0.049, Wilk’s Λ = 0.99). Right putamen (F(1, 21557) = 5.72 , p = 0.02, adjusted p = 0.1) and right hippocampus F(1, 21557) = 6.12 , p = 0.01, adjusted p = 0.1) demonstrated an interaction such that male adolescent users exhibited larger regional volume than male non-users (right putamen: p < 0.001, 95% CI [4912.0, 4933.0]; right hippocampus: p = 0.02, 95% CI [3867.1, 3909.8]; Figure 2b).

Interaction Between Cannabis Use and Age for Regional Brain Volume:

No Cannabis*Age interaction effects were observed for the regional brain volumes assessed (all p > 0.05) for either lifetime cannabis use or most recent use.

Main Effect of Cannabis Use on Cognitive Measures:

Cognitive performance differed by lifetime cannabis use (F(18,33964) = 28.8, p < 0.001, Wilk’s Λ = 0.99, η2 = 0.007). Symbol Digit Substitution (F(2, 16990)= 9.2, p < 0.001, adjusted p = 0.002), Numeric Memory (F(2, 16990)= 33.6, p < 0.001, adjusted p = 0.002), Trail Making #1 (total errors: F(2, 16990) = 3.1, p = 0.04, adjusted p = 0.06), Reaction Time (F(2, 16990) = 7.6, p < 0.001, adjusted p = 0.002), and Paired Associate Learning (F(2, 16990) = 85.7, p < 0.001, adjusted p = 0.002) demonstrated a main effect of lifetime cannabis use (Figure 3).

Figure 3:

Figure 3:

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Cognitive assessment performance by a) lifetime cannabis use (no use, between 1–100 times, more than 100 times) and b) most recent cannabis use (no use, last use in adolescence [0–25 years of age]). Covariates from the model are evaluated at the following values: age = 63.44 years, smoking status (−3 = Prefer not to answer; 0 = Never , 1 = Previous, 2= Current) = 0.4, frequency of alcohol use (0= Never; 1 = Monthly or less, 2 = 2 to 4 times a month; 3= 2 to 3 times a week; 4= 4 or more times a week) = 2.03. Error bars denote +/−1 standard error. Asterisks represent significant differences between conditions (*p < 0.05, **p < 0.01, ** p < 0.001).

Post hoc tests revealed better performance in the moderate cannabis use compared to the no cannabis group on Symbol Digit Substitution (p < 0.001, adjusted p = 0.005, 95% CI [0.07, 0.5]), Trail Making #2 (derived interference: p < 0.001, adjusted p = 0.02, 95% CI [1.4, 22.8]), Numeric Memory (p < 0.001, adjusted p < 0.001 95% CI [01, 0.2]), Paired Associate Learning (p < 0.001, adjusted p < 0.001, 95% CI [0.4, 0.7]), and Reaction Time (p < 0.001). The high cannabis use group performed better than the no cannabis group on Numeric Memory (p < 0.001, adjusted p = 0.02, 95% CI [.03, 0.4]) and Paired Associate Learning (p < 0.001, adjusted p < 0.001, 95% CI [0.3, 1.0]).

Cognitive performance also differed between non-users and those who had only used cannabis during adolescence (F(9,14703) = 10.28, p < 0.001, Wilk’s Λ = 0.98, η2 = 0.006). Adolescent users demonstrated better performance on Paired Associate Learning (F(1,14703) = 59.85 p < 0.001, adjusted p < 0.001, 95% CI [6.9, 7.0]), Symbol Digit Substitution (F(1,14703) = 15.71, p < 0.001, adjusted p < 0.001, 95% CI [19.2, 19.3]), Numeric Memory (F(1,14703) = 35.15, p < 0.001, adjusted p < 0.001, 95% CI [6.7, 6.8]), and Trail Making #2 (derived interference: F(1,14703) = 6.10, p = 0.01 adjusted p = 0.03, 95% CI [317.0, 325.0]) when compared to non-users (Figure 3b).

Main Effect of Sex on Cognitive Measures:

Cognitive performance differed by sex (F(9,16982) = 23.0, p < 0.001, Wilk’s Λ = 0.98, η2 = 0.012). Men performed better than women on Numeric Memory (F(1, 16990) =13.6, p < 0.001, adjusted p = 0.001, 95% CI [6.7, 6.8]) and Reaction Time (F(1, 16990) = 45.7, p < 0.001, adjusted p < 0.001, 95% CI [599.2, 605.5]). Women performed better than men on Trail Making #1 (duration to complete: (F(1, 16990) = 5.4, p = 0.02, adjusted p = 0.05, 95% CI [214.6, 219.3]), and Paired Associate Learning (F(1, 16990) = 105.8, p < 0.001, adjusted p < 0.001, 95% CI [7.7, 7.9]).

Interaction Between Cannabis Use and Sex for Cognitive Measures:

A trending overall interaction between lifetime cannabis use and sex was observed (F(18,33964) = 1.52, p = 0.07, Wilk’s Λ = 0.99, η2 = 0.001). Trail Making #2 (errors: F(2, 16990) = 4.39, p = 0.01, adjusted p = 0.09) demonstrated an interaction between cannabis and sex (Figure 4). Post hoc tests revealed that men in the high cannabis use group performed worse than men in the moderate use group (p < 0.001, adjusted p = 0.01, 95% CI [0.06, 0.07]). Women in the no cannabis use group performed worse than women in the moderate cannabis use group (p = 0.004, adjusted p = 0.06, 95% CI [−0.6, 0.008]).

Figure 4:

Figure 4:

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Cognitive assessment performance by sex (X-axis) and a) lifetime cannabis use (blue = no use, red = between 1–100 times, green = more than 100 times), and b) period of most recent cannabis use (blue = no use, red = last use in adolescence [0–25 years of age]). Covariates from the model are evaluated at the following values: age = 63.44 years, smoking status (−3 = Prefer not to answer; 0 = Never , 1 = Previous, 2= Current) = 0.4, frequency of alcohol use (0= Never; 1 = Monthly or less, 2 = 2 to 4 times a month; 3= 2 to 3 times a week; 4= 4 or more times a week) = 2.03. Error bars denote +/−1 standard error. Asterisks represent significant differences between conditions (*p < 0.05, **p < 0.01, ** p < 0.001).

A trending overall interaction between cannabis use only during adolescence and sex was observed (F(9,14703) = 2.19, p = 0.02, Wilk’s Λ = 0.99, η2 = 0.001), with Prospective Memory specifically demonstrating an interaction (F(1,14703) = 7.71, p = 0.006, adjusted p = 0.05), such that male adolescent users demonstrated better performance than non-users (p = 0.01, 95% CI [1.04. 1.06]), whereas female non-users demonstrated better performance than adolescent users (p = 0.01, 95% CI [1.08, 1.09]; Figure 4b).

Interaction Between Cannabis Use and Age for Cognitive Measures:

No Cannabis*Age interaction effects were observed for the measures of cognitive performance assessed (all p > 0.05).

Relationships between Regional Brain Volumes and Cognitive Measures:

As would be expected, significant relationships were observed between regional brain volume and performance on cognitive assessments (Supplemental Table 2). Larger brain volumes were generally associated with better cognitive performance, though negative associations emerged for prospective memory, potentially reflecting its categorical scoring (0–2), and for cingulate volumes with paired associate learning.

Discussion

This study investigated associations between cannabis use, brain volume, and cognitive function in middle-aged to older adults in the UK Biobank. Greater lifetime cannabis use was positively associated with brain volume in regions rich in cannabinoid receptors, including the caudate, putamen, hippocampus, and anterior cingulate. Greater lifetime use was also associated with better performance on cognitive tasks assessing learning, memory, processing speed, and task switching, aligning with growing evidence of potential neuroprotective effects of cannabis in aging populations (Cousijn et al., 2012; Høeg et al., 2024; Wetherill et al., 2015). Cannabis use only during adolescence (between 0–25 years of age) was also positively associated with regional brain volume and cognitive performance, with prior use in adolescence generally associated with larger brain volumes and better cognitive performance.

The finding of larger brain volumes among cannabis users in the present study suggests that cannabis may exert neuroprotective effects. This possibility is particularly notable given the well-established pattern of age-related brain atrophy (Fletcher et al., 2018) linked to declines in cognitive function (Armstrong et al., 2020; Fletcher et al., 2018; Lee et al., 2025) and other health outcomes and quality of life (Hahm et al., 2019; Trifan et al., 2025; Van Elderen et al., 2016). Specifically, the observed effects may reflect preservation of subcortical regions characterized by a high density of CB1 receptors. Subcortical structures that demonstrated relationships with cannabis use in the present study play key roles in critical processes (Janacsek et al., 2022; Kong et al., 2023; Pierce & Péron, 2020), such as memory (e.g., hippocampus), emotion and motivation (e.g., amygdala, accumbens), and motor control (e.g., caudate, putamen). Further, age-related declines in brain volume are often regionally specific, with the hippocampus showing particular vulnerability to volumetric reductions with age and dementia (Apostolova et al., 2012; Veldsman et al., 2021; Xiao et al., 2023). These observed relationships align with preliminary research in animal models demonstrating a critical role of CB1 receptors in neurogenesis (Jin et al., 2004). Specifically, CB1 receptor activation has been associated with hippocampal neurogenesis in adult mice (Wolf et al., 2010). Present findings suggest that cannabis use could be associated with differences in neural aging trajectories, potentially mediated by CB1 receptor–rich subcortical regions, though more research is needed.

Though surprising given negative effects in youth (Lorenzetti et al., 2019), these findings are consistent with earlier work by our group (Karoly et al., 2021; Thayer et al., 2019), and a longitudinal study of 5,000 men showing reduced cognitive decline among cannabis users (Høeg et al., 2024). Studies in animals have also repeatedly observed that low doses of THC are associated with improvements in cognition in models of aging and dementia, while these same doses are associated with deleterious cognitive effects in young animals (Bilkei-Gorzo et al., 2017; Nidadavolu et al., 2021; Suliman et al., 2018). These effects may be mediated by molecular pathways involving SIRT-1, BDNF, and upregulation of genes linked to neurogenesis and anti-inflammation (Shapira et al., 2023). Additional evidence suggests cannabinoids may mitigate amyloid-β pathology and modulate immune and inflammatory responses relevant to aging and dementia (Coles et al., 2022).

More broadly, these findings fit within a conceptual framework positing that cannabinoids, endocannabinoids, and related lipids modulate neurobiological processes, including inflammation, in ways that may vary across developmental stage. Endocannabinoids may partially mediate the impact of exogenous opioids on the immune system and downstream neuroprotective effects (Turcotte et al., 2015). Furthermore, recent studies have suggested that exogenous cannabinoids such as THC and CBD appear to impact downstream lipids involved in LOX, COX, and other pathways that influence inflammation (Morris, In Press). Future work should employ longitudinal designs to clarify how cannabis use influences neurobiological processes associated with aging and to disentangle causal pathways over time.

Interestingly, individuals whose last cannabis use was limited to adolescence tended to show more favorable outcomes relative to non-users. These findings diverge from prior studies reporting predominantly harmful effects of adolescent cannabis use (Albaugh et al., 2021; Orr et al., 2019; Volkow et al., 2014). However, this is the first study to examine the impact of adolescent only use on the aging brain much later in life. Notably, adolescence represents a sensitive period of neurodevelopment, during which the endocannabinoid system is highly active and susceptible to disruption (Lubman et al., 2015). Although cannabis exposure during this window has primarily been linked to negative alterations in brain function per prior reports (Volkow et al., 2016; Winters & Lee, 2008), present findings suggest no negative effects on the brain many years later. Outcomes may vary depending on the frequency, potency, and context of use, as well as genetic and environmental factors. These findings highlight the need for longitudinal research using fine-grained, comprehensive assessments of cannabis exposure not available in the UK Biobank dataset, including developmental timing, extent, and type of use during different developmental periods.

Although most regions showed increased volume with higher cannabis use, posterior cingulate regions showed reduced volume, suggesting region-specific vulnerabilities. Additionally, most brain regions and cognitive assessments demonstrating an effect of cannabis use demonstrated a significant difference between moderate and non-users, indicating potential benefits of moderation. Surprisingly, post hoc tests revealed no significant differences between individuals in the moderate and high use groups for the main effect of cannabis. The lack of differences between the two cannabis groups could reflect ceiling effects, such that once exposure to cannabis surpasses a threshold, additional use may not produce incremental effects on brain structure or function. Given the smaller sample size of the high use group, it is also possible that the amount of variance within this group reduced statistical power to detect more subtle differences among cannabis users.

Interactions between cannabis use and sex were observed for regional brain volumes and cognitive performance. For several brain regions, women did not demonstrate the positive relationship that was observed in men, meanwhile sex differences were mixed for assessments of cognitive function. These findings indicate that the potential protective and risk factors linked to cannabis use may differ by sex among middle-aged and older adults, with effects that likely vary across specific brain regions and domains of cognitive function. These results may reflect known sex differences in the endocannabinoid system, such as higher CB1 receptor density in males and age-related CB1 increases in females (De Fonseca et al., 1994; Riebe et al., 2010; Van Laere et al., 2008; Xing et al., 2014). Animal studies have demonstrated that females may be more sensitive to the effects of cannabinoids than men (Cooper & Craft, 2018), and a recent study found that female participants who smoked less cannabis than male participants experienced similar intoxicating effects (Wright et al., 2021). Another study found that female participants demonstrated higher peak THC blood concentrations and subjective drug effects compared to male participants (Sholler et al., 2021). Differences in the way women and men utilize cannabis may also have implications for neurocognitive effects. This could include manner of use (e.g., frequency, dosage, route of administration) and reasons for cannabis use. Women are increasingly using cannabis for medical reasons (e.g., sleep, anxiety), despite lower overall use rates than men (Cooper & Haney, 2014). More work is needed to understand how interactions between sex and cannabis use may confer changes in brain development via sex-specific neurobiological mechanisms.

Although the UK Biobank’s large sample is a major strength, limitations of the present study include categorical and self-reported cannabis use data, lack of detail on THC/CBD content, and cross-sectional design. Although many factors could be assessed as possible covariates relevant to the effects of cannabis use on brain volume and cognitive function, the present study specifically assessed age, sex, and current substance (smoking, alcohol) use. A selective approach to covariate inclusion minimizes the risks of multicollinearity, overfitting, and loss of interpretability. However, it is possible that other variables may be relevant and that unknown covariates are influencing the results. As noted above, future research will benefit from incorporation of more detailed cannabis exposure measures, longitudinal data, and inclusion of biological markers (e.g., endocannabinoids, inflammatory biomarkers) to clarify causal mechanisms and individual differences.

In summary, this study adds to a growing body of evidence that cannabis use may be associated with greater brain volume and cognitive performance in aging adults, especially in regions rich in cannabinoid receptors. These associations contrast with harmful effects often observed in youth and are supported by preclinical evidence for age-dependent cannabinoid effects. Findings also highlight the importance of dose, region-specificity, and sex in modulating cannabis’ impact on brain health.

Supplementary Material

Supplemental Methods
Supplemental Table 1
Supplemental Table 2

Public Health Significance Statement:

This study suggests that history of cannabis use among middle-aged and older adults may be linked to better brain health and cognitive performance, in contrast to the harmful effects often seen in younger people. These findings are important because they point to the possibility that cannabis could play a protective role in aging, with implications for brain health later in life. Understanding these effects can help guide public health messaging, shape future research, and inform policies around safe cannabis use for different age groups.

Funding Information

Funding from this project comes from the Rocky Mountain Cannabis Research Center (NIDA P50DA056408–02) and NIMH T32MH015442–46.

Footnotes

Author Disclosure Statement

The authors have no conflicts of interests or disclosures to report.

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Associated Data

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Supplementary Materials

Supplemental Methods
NIHMS2135359-supplement-Supplemental_Methods.docx (20.3KB, docx)
Supplemental Table 1
NIHMS2135359-supplement-Supplemental_Table_1.docx (16.6KB, docx)
Supplemental Table 2
NIHMS2135359-supplement-Supplemental_Table_2.docx (21.1KB, docx)

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