The health and social effects of nonmedical cannabis use
New WHO publication on cannabis
Chapter 6. Mental health and psychosocial outcomes of long-term cannabis use
The adverse psychosocial and mental health outcomes that are correlated
with long-term cannabis use are most often seen in daily or near-daily users.
This section of the document summarizes evidence on the best researched of
these health outcomes – namely dependence, educational outcomes, the use of
other illicit drugs, cognitive impairment, mental disorders (psychoses,
depression and other disorders) and suicidality (risk, ideation, attempts and
mortality). 6.1.1 Long-term cannabis use and dependence Cannabis dependence is a
cluster of behavioural, cognitive and physiological phenomena that develop
after repeated cannabis use. A diagnosis of dependence requires that three or
more of the following criteria are met in the previous year: (a) strong desire or sense
of compulsion to take the substance; (b) difficulties in
controlling substance-taking behaviour in terms of its onset, termination, or
levels of use; (c) a physiological
withdrawal state (see F1x.3 and F1x.4) when substance use has ceased or been
reduced, as evidenced by: the characteristic withdrawal syndrome for the
substance; or use of the same (or a closely related) substance with the
intention of relieving or avoiding withdrawal symptoms; (d) evidence of tolerance,
such that increased doses of the psychoactive substances are required in order
to achieve effects originally produced by lower doses (clear examples of this
are found in alcohol- and opiate-dependent individuals who may take daily doses
sufficient to incapacitate or kill nontolerant users); (e) progressive neglect of
alternative pleasures or interests because of psychoactive substance use,
increased amount of time necessary to obtain or take the substance or to
recover from its effects; (f) persisting with
substance use despite clear evidence of overtly harmful consequences, such as
harm to the liver through excessive drinking, depressive mood states consequent
to periods of heavy substance use, or drug-related impairment of cognitive
functioning; efforts should be made to determine that the user was actually, or
could be expected to be, aware of the nature and extent of the harm” (WHO,
1992). Harmful use of cannabis and
cannabis dependence are the most common forms of drug-use disorders in
epidemiological surveys in Australia, Canada and the USA. These disorders
affect 1-2% of adults in the past
year, and 4-8% of adults during their
lifetime (Hall & Pacula, 2010; Anthony, 2006). As
noted, the risk of dependence has been estimated at 16% in those who initiated cannabis use in adolescence (Anthony, 2006) and
33-50% in daily cannabis users (van der Pol et al., 2013).
We do not know how these risk estimates from the early 1990s may have been
affected by changes in diagnostic criteria for dependence in DSM-5 or by
changes in the potency of cannabis products. However, based on DSM-IV and the
large representative USA NESARC study, higher proportions of lifetime users
seem to have developed cannabis use disorders (Lev-Ran et al., 2013; Fischer et
al., 2015), and nearly 3 of 10 cannabis users in the USA manifested a
cannabis-use disorder in 2012-2013 ( Hasin et
al., 2015). Humans develop tolerance to
THC (Lichtman & Martin, 2005) and
cannabis users who seek help for cannabis-use problems often report withdrawal
symptoms such as anxiety, insomnia, appetite disturbance and depression (Budney & Hughes, 2006). These symptoms are of sufficient severity to impair everyday functioning
(Allsop et al., 2012) and they are markedly
attenuated by doses of an oral cannabis extract (Sativex)
that contains THC (Allsop et al., 2014). Cannabis
dependence in and of itself is not the only problem for heavy users. By
increasing the duration of regular use, dependence may also increase the risk
of any long-term health risks of cannabis that may occur after decades of use,
such as cardiovascular and respiratory diseases, and possibly cancers. These
risks are discussed in chapter seven of the report. The
mortality of patients with cannabis dependence is also of concern. A study of
46 548 individuals hospitalized in California between 1990 and 2005 with
ICD-9 diagnoses of cannabis dependence and cannabis abuse were followed for 16
years. Age-, sex- and race-adjusted standardized mortality rates (SMRs) were
generated. Out of the total cohort of people with cannabis-use disorder
diagnosis, 1809 deaths across all years were identified (Callaghan et al.,
2012). This is an approximately
four-fold higher risk of mortality when compared with that of the general
population. The underlying reasons for the elevated standardized mortality
rates in the cannabis cohort are unknown. 6.1.2 Long-term cannabis
use and cognitive function The 1990s case-control studies found that regular cannabis users had
poorer cognitive performance than non-cannabis-using controls (Hall, Solowij & Lemon, 1994). The challenge was to decide
whether cannabis use impaired cognitive performance, or if persons with poorer
cognitive functioning were more likely to become regular cannabis users, or
both (Hall, Solowij & Lemon, 1994).
Better-controlled case-control studies since then (Crane et al., 2013; Solowij & Battisti, 2008;
Grant et al., 2003; Schreiner & Dunne, 2012) have consistently found
deficits in verbal learning, memory and attention in regular cannabis users
(see section 5.1.2). These deficits have usually been correlated with the
duration and frequency of cannabis use, the age of initiation and the estimated
cumulative dose of THC (Solowij, 2002; Solowij & Pesa, 2012; Solowij et al., 2011). It remains unclear whether cognitive
function fully recovers after cessation of cannabis use, with studies producing
conflicting results (Solowij, 2002; Solowij & Pesa, 2012). A longitudinal study from the Dunedin birth cohort suggested that
sustained heavy cannabis use over several decades produced substantial declines
in cognitive performance that may not be wholly reversible. This study assessed
changes in IQ between age 13 (before cannabis was used) and at age 38 in 1037
New Zealanders born in 1972 or 1973 (Meier et al., 2012). Early and persistent
cannabis users showed an average decline of eight IQ points compared with peers
who had not used cannabis, and cannabis-using peers who had not used cannabis
in this sustained way. Rogeberg (2013) argued that
the apparent effect of sustained cannabis use on IQ could be due to failure to
control for socioeconomic status. Further analysis of the Dunedin data did not
support Rogeberg’s hypothesis (Moffitt et al., 2013).
A recent study in the USA has provided support for the study of Meier et al. in
finding an association between poorer verbal memory and sustained daily use of
cannabis throughout adult life (Auer et al., 2005). As noted in section 4.1, studies of brain structure and function in
cannabis users provide some support for these epidemiological findings. MRI
studies have reported structural changes in the hippocampus, prefrontal cortex
and cerebellum in chronic cannabis users (Yücel et
al., 2008) and these were largest in
persons who had used cannabis the longest. A recent systematic review
(Lorenzetti et al., 2013) found a consistent reduction in hippocampal volume in
long-term daily users. Excluding the possibility of reverse causation as an explanation for
these findings has been difficult because younger persons with poorer cognitive
performance are more likely to become regular cannabis users. There are also
shared risk factors for regular cannabis use and poor cognitive performance. A
causal role for regular cannabis use has biological plausibility in that
cannabis acutely impairs cognitive performance, and neuroimaging studies have
found relationships between the frequency and duration of cannabis use and
structural and functional changes in brain regions implicated in memory and
cognition. 6.1.3 Long-term
psychosocial consequences of adolescent cannabis use 6.1.3.1 Social and educational outcomes Longitudinal studies since the 1990s have found that cannabis use before
the age of 15 years predicts early school-leaving and this persists after
adjustment for confounders (e.g. (Ellickson et al.,
1998)). A meta-analysis of three Australian and New Zealand longitudinal
studies (Horwood et al., 2010) confirmed this
finding. Longitudinal
studies have also shown that early initiation of heavy cannabis use is
associated with lower income, lower college degree completion, a greater need
for economic assistance, unemployment, and use of other drugs (Fergusson et
al., 2016; Fergusson & Boden, 2008; Brook et al., 2013). It is plausible that educational outcomes in regular cannabis users are
impaired for a combination of reasons: a higher pre-existing risk of
educational problems in those who become regular cannabis users, the adverse
effects of regular cannabis use on learning in school, increased affiliation of
regular cannabis users with other cannabis-using peers who reject school, and
the strong desire of younger cannabis users to make a premature transition to
adulthood by leaving school (Lynskey
& Hall, 2000). A recent Australian twin study has raised doubts about a causal
interpretation of the association between adolescent cannabis use and early
school-leaving (Verweij et al., 2013). The study
found that the association between early cannabis use and early school-leaving
was explained by shared genetic and environmental risk factors. These findings
have been supported by two twin studies in the USA (Grant et al., 2012; Bergen
et al., 2008), which suggest that the association may be explained by higher
levels of recruitment to cannabis use among adolescents who are at higher risk
of leaving school earlier. In an earlier Australian, study early-onset users had significantly
higher rates of later substance use, juvenile offending, mental health
problems, unemployment and school dropout. The links between early-onset
cannabis use and later outcomes were largely explained by two routes that
linked cannabis use to later adjustment. First, those electing to use cannabis
were a high-risk population characterized by social disadvantage, childhood
adversity, early-onset behavioural difficulties and adverse peer affiliations.
Secondly, early-onset cannabis use was associated with subsequent affiliations with
delinquent and substance-using peers, moving away from home and dropping out of
education, with these factors in turn being associated with increased
psychosocial risk (Fergusson et al., 1997). A substantial proportion of those
who become cannabis users continued to smoke tobacco and use alcohol in a
harmful or hazardous way and they were more likely to use a range of other
illicit drugs (Hasin et al., 2015). 6.1.3.2 Other illicit drug use Epidemiological studies in Australia, New Zealand and the USA in the
1970s and 1980s found that regular cannabis
users were more likely to use heroin and cocaine, and that the younger they
were when they first used cannabis the more likely they were to use the other
drugs (Kandel, 2002). Three explanations were offered for these patterns: (a) that cannabis
users had more opportunities to use other illicit drugs because these were
supplied by the same black market as cannabis; (b) that early cannabis users
were more likely to use other illicit drugs for reasons that were unrelated to
their cannabis use (e.g. their propensity to take risks, behave impulsively, or
engage in sensation-seeking); and (c) that the pharmacological effects of
cannabis increased a young person’s interest in using other illicit drugs (Hall
& Pacula, 2010). Patterns of drug involvement similar to those
in the USA have been reported in a number of countries by epidemiological
research (Swift et al., 2012), although the order in which drugs are used
varies with the prevalence of different illicit drugs among adults (Degenhardt et al., 2010). Research has also supported the
first two hypotheses in that young people in the USA who have used cannabis
report more opportunities to use cocaine at an earlier age (Wagner &
Anthony, 2002). Additionally, socially deviant young people (who are also more
likely to use cocaine and heroin) start using cannabis at an earlier age than
their peers (Fergusson, Boden & Horwood, 2008). Simulations suggest that shared risk factors
could explain these relationships between cannabis and other illicit drug use (Morral, McCaffrey & Paddock, 2002). The shared risk
factor hypothesis has been tested in longitudinal studies by assessing whether
cannabis users are more likely to report heroin and cocaine use after
statistically controlling for confounding factors (Lessem
et al., 2006; Fergusson, Boden & Horwood, 2006).
Adjustment for confounders has reduced but not eliminated the relationship
(Hall & Lynskey, 2005). Studies of twins who are discordant for
cannabis use (i.e. one used cannabis and the other did not) have been used to
test whether shared genetic vulnerability explains the higher rates of illicit
drug use among heavy cannabis users. Lynskey and
colleagues (2003) found that the twin who had used cannabis prior to age 17 was
more likely to have used other illicit drugs than the co-twin who had not. This
relationship persisted after controlling for non-shared environmental factors.
Similar results have been reported in discordant twin studies in the USA (Grant
et al., 2010) and Netherlands (Lynskey, Vink & Boomsma, 2006). Preclinical studies of early adolescent
exposure to THC in rodents are supportive of these findings. Adult
rats pre-treated with THC during adolescence and then allowed to mature to
adults without THC are more likely to use heroin than rats not exposed to
cannabis during adolescence. The endogenous opioid system was also disturbed in
the brain of adults exposed to THC during adolescence (Ellgren,
Spano & Hurd, 2007; Ellgren,
2008; Tomasiewicz et al., 2012). 6.1.3.3 Tobacco and alcohol use In the early 1990s, cigarette smoking in many developed countries
generally started before cannabis use, and regular tobacco smoking was a
predictor of regular cannabis use and was regarded as a gateway to cannabis
use. Over the past 20 years the relationship between cannabis and tobacco use
has changed in some developed countries with a low prevalence of cigarette
smoking and a high prevalence of cannabis use. In Australia and the USA, as a
result of public health campaigns to prevent tobacco smoking among young
people, young people increasingly start cannabis smoking before they smoke
tobacco (Johnston et al., 2010). In these countries cannabis use increases the
risk of becoming a tobacco smoker, a pattern described as a “reverse gateway”
(Patton et al., 2005). Both gateway patterns probably reflect a shared route of
administration (smoking) (Agrawal & Lynskey,
2009), the fact that cannabis smokers affiliate with tobacco smokers, and the
effects of mixing tobacco and cannabis in joints. In connection with the 2011
European School Survey Project on Alcohol and Other Drugs (ESPAD), a special
study was undertaken on the prevalence of polydrug
use among students from European countries that participated in the 2011 ESPAD
survey (Hibell et al., 2012).
Polydrug use was defined as the use of more than one
of the following substances: tobacco (more than five cigarettes per day in the
past 30 days), alcohol (consumption on 10 or more occasions in the past 30
days), cannabis (any use in the past 30 days), other illicit drugs (any
lifetime use) and tranquillizers/sedatives without a prescription (any lifetime
use). The overall prevalence of polydrug use
(2-plus substances) in the total sample was very close to 9% in both survey
years. The combination tobacco-cannabis was found in 9.7%
of the polydrug group and the combination alcohol-cannabis was found in 5.7 %. The most common
combination was tobacco–alcohol which was found in 12.4 % of the group (Hibell et al., 2012). 6.1.4 Psychosis and schizophrenia In discussing relationships between cannabis use, psychosis and
schizophrenia, it is necessary to define psychosis and schizophrenia clearly.
Schizophrenia is a mental and behavioural disorder classified in the ICD-10.
Schizophrenia is characterized by distortions in thinking, perception,
emotions, language, sense of self and behaviour. Common experiences include
hearing voices and delusions (WHO, 1992). Regular cannabis use has been
reported to be more common among persons with schizophrenia (Myles, Myles &
Large, 2015). The regular use of cannabis with a higher THC content and a lower
CBD concentration may increase the risk for schizophrenia and lower the age of
onset of the disease (Di Forti et al., 2014, 2015) A 15-year follow-up study of schizophrenia among 50 465 Swedish
male conscripts found that those conscripts who had tried cannabis by age the
age of 18 years were 2.4 times more likely to be diagnosed with schizophrenia
over the next 15 years than those who had not (Andréasson
et al., 1987). After statistical adjustment for a personal history of
psychiatric disorder by age 18 and a number of psychosocial confounders, those
who had used cannabis 10 or more times by age 18 were 2.3 times more likely to
be diagnosed with schizophrenia than those who had not used cannabis. Zammit et al. (2002) reported a 27-year follow-up
of the above-mentioned Swedish cohort. They also found a dose-response relationship between frequency of
cannabis use at the age of 18 years and the risk of schizophrenia during the
whole follow-up period (although the strength of the relationship declined with
age). This effect persisted after statistically controlling for confounding
factors. The researchers estimated that 13% of cases of schizophrenia would
have been averted if no one in the cohort had used cannabis. The Swedish cohort findings have been supported in smaller longitudinal
studies in the Netherlands (van Os et al., 2002),
Germany (Henquet et al., 2004) and New Zealand (Arseneault et al., 2002; Fergusson, Horwood
& Swain-Campbell, 2003; Stefanis et al., 2014).
All of these studies found a relationship between cannabis use and psychotic
disorders or psychotic symptoms and these relationships persisted after
adjustment for confounders. A meta-analysis of these longitudinal studies
(Moore et al., 2007) reported that psychotic symptoms or psychotic disorders
were higher in regular cannabis users than in non-users (OR
2.09 [95% CI: 1.54, 2.84]). Reverse causation is a possible explanation of these findings if persons
with schizophrenia use cannabis to relieve the symptoms of their illness. This
possibility has been addressed to some extent in some of these longitudinal
studies by excluding cases who reported psychotic symptoms at baseline, or by
statistically adjusting for pre-existing psychotic symptoms. However, several
large studies show that cannabis use preceded onset of psychosis (Andréasson et al., 1987; DiForti
et al., 2009; Fergusson et al., 2003). A second possibility is the common cause hypothesis – i.e. that the
association is explained by other factors (e.g. genetic risk, childhood abuse)
that increase the risk that young people will use cannabis and develop
schizophrenia. This possibility has been addressed in some studies by comparing
the rate of schizophrenia in persons who abuse different drugs. In a nationwide
cohort of 30 547 patients receiving treatment for substance use disorders
in Chile, there was an increased risk of a diagnosis of schizophrenia among
cannabis users compared with patients who were users of other drugs (RR = 2.08,
1.6–2.7) and a dose-response association
between cannabis use and risk of a schizophrenia diagnosis (Jorquera
et al., 2015). The common cause hypothesis
has been harder to exclude because the association between cannabis use and
psychosis is attenuated after statistical adjustment for potential confounders
in many studies, and no study has been able to assess all plausible
confounders. Genetic epidemiological studies have assessed the degree to which
shared genetic risk factors may explain the association between cannabis use
and psychoses. These have included studies of sib-pairs (McGrath et al., 2010),
studies of the strength of the relationship between cannabis and psychosis in
persons who differ in genetic relationship (Giordano et al., 2014), and
correlations between polygenic risk scores for schizophrenia and cannabis use
in large twin samples (Power et al., 2014). These studies suggest that shared
genetic factors may explain some but not all of the association between
cannabis and psychosis. Researchers who favour a
causal explanation point to its biological plausibility (e.g. (Di Forti et al., 2009)). This is indicated by double-blind
studies which show that THC produces dose-related increases in positive and
negative symptoms of psychosis in persons who do and do not have psychoses
(D'Souza, 2004; Morrison, 2009; Murray et al., 2013). Psychotic syndromes have
also been reported in patients who have been treated with the cannabinoid
extract Sativex (Therapeutic Goods Administration,
2013). Compared with matched controls, those with
psychotic disorders, and their siblings, are more sensitive to the
psychotogenic effects of acute THC administration (D’Souza et al, 2005;
Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014). A
recent case-control study by Di Forti et al (2009)
suggested that regular use of cannabis with high levels of THC and low levels
of CBD increased the risk of developing schizophrenia by 3-5 times. Researchers who remain
sceptical about a causal role for cannabis (e.g. Gage, Zammit
& Hickman, 2013) point to the absence of an increase in the incidence of
schizophrenia as cannabis use increased among young adults. The evidence is
mixed. An Australian modelling study did not find any marked increase in
incidence after steep increases in cannabis use during the 1980s and 1990s (Degenhardt, Hall & Lynskey,
2003). However, a similar modelling study in the United Kingdom (Hickman et
al., 2007) argued that it was too early to say. Two case register studies in
Britain (Boydell et al., 2006) and Switzerland (Ajdacic-Gross et al., 2007) reported an increased incidence
of psychoses in recent birth cohorts, but a United Kingdom study of general
practice patients did not (Advisory Council on the Misuse of Drugs, 2008). The available evidence points to a modest contributory causal role for
cannabis in schizophrenia. There is a consistent dose-response relationship in a
number of prospective studies between cannabis use in adolescence and the risk
of developing psychotic symptoms or schizophrenia. Self-medication is
implausible, and a causal relationship is biologically plausible (see Evins, in Haney & Evins,
2016). Researchers who are not convinced by the evidence argue that these
studies have not excluded the possibility that the relationship is explained by
residual confounding (see Haney, in Haney & Evins,
2016). Depression is a common mental health problem and one of the most
important contributors to the global burden of disease (Ustün
et al., 2004; Moussavi et al., 2007). Findings of
high prevalence of comorbid cannabis use and depression have been replicated in
many large-scale cross-sectional studies and in mental health surveys. Persons
with cannabis-use disorders have higher rates of depressive disorders (Swift, Hall & Teesson, 2001). In longitudinal studies, the relationship
between regular cannabis use and depression has been much weaker than that for
cannabis and psychosis (Degenhardt & Hall,
2012; Manrique-Garcia et al., 2012; Fergusson & Horwood, 1997).
Meta-analyses of these studies (Moore et al., 2007) found modest associations
between regular or heavy cannabis use and depressive disorders (Moore at al.,
2007: OR = 1.49 [95% CI: 1.15, 1.94]; Lev-Ran et al., 2014: OR = 1.62 [95% CI 1.21-2.16]). Many of
these studies did not adequately control for confounders, or excluded the
possibility that depressed young people were more likely to use cannabis (Horwood et al., 2012) and in some studies associations
disappear when better control is introduced (Feingold et al., 2015). Much the same has been true of studies of
cannabis-use disorders among persons diagnosed with bipolar disorders (e.g.
(Lai & Sitharthan, 2012; Lev-Ran et al., 2013; Silberberg, Castle & Koethe, 2012; Agrawal, Nurnberger
& Lynskey, 2011)). In one longitudinal study,
cannabis use at baseline predicted an increased risk of manic symptoms in a
three-year follow-up (Henquet et al., 2006). However,
these studies have not adequately controlled for confounding variables or ruled
out reverse causation with cannabis being used to lift depressed mood
and reduce manic excitement (Silberberg, Castle & Koethe,
2012). Persons with cannabis-use disorders also have higher rates of anxiety,
conduct disorders, eating disorder and personality disorders (Goodman &
George, 2015). The reasons for these common patterns of comorbidity have not
been as well investigated in prospective studies as those between cannabis-use
disorders and psychosis and depression. It remains to be discovered whether
these disorders increase the risks of using cannabis (as is plausible for
conduct and personality disorders), whether their outcomes are worsened by
cannabis-use disorders, and to what degree these disorders share common risk
factors with cannabis-use disorders (Hall, Degenhardt,
& Teesson, 2009). The high prevalence of comorbidity between drug-use disorders and other
mental disorders does not mean that one causes the other, but comorbidity
between mental and substance-use disorders is highly prevalent across
countries. In general, people with a substance-use disorder had higher comorbid
rates of mental disorders than vice versa, and people with drug-use disorders
had the highest rates of comorbid mental disorders. In general, while there are
associations between regular cannabis use or cannabis-use disorders and most
mental disorders, causality has not been established. Reverse causation and
shared risk factors cannot be ruled out as explanations of these relationships. 6.1.6 Suicide risk, ideation and attempts Bagge and Borges (Bagge
& Borges, 2015) conducted a case-crossover study of 363 persons who had
recently attempted suicide and were treated in a trauma hospital for a suicide
attempt within the previous 24 hours in the state of Mississippi, USA. The
researchers compared rates of cannabis use in the 24 hours leading up to the
suicide (case period) to that in the 24 hours of the day before the suicide
(control period). They found that 10.2% of suicide attempters had used cannabis
in the case period while 13.2% used cannabis in the control period. The USA’s Drug Abuse Warning Network (DAWN) estimated rates of cannabis
use among drug-related visits to hospital emergency departments for suicide in
2011 (SAMHSA, 2013). Cannabis was coded as positive if hospital staff perceived
it to be the cause or a contributor to the emergency visit. Cannabis was
involved in an estimated 6.5% of drug-related suicide attempts, and in 46% of
attempts the person also used alcohol. In the 23% of drug-related suicide
attempts with toxicology reports, 16.8% tested positive for cannabis, although
this cannabis use could have occurred days or even up to one week earlier. In
general, 9.5% of all toxicology reports for deaths by suicide (Borges, Bagge & Orozco, 2016) show the presence of
cannabis. There is preliminary evidence of higher detection of cannabis among
suicide decedents that do not involve overdose (CDC, 2006) and higher
detections among male suicide decedents using non-overdose methods than among
females (Darke, Duflou
& Torok, 2009; Shields et al., 2006). Homicide
victims appear to have higher detection rates of cannabis at the time of death
than suicide victims do (Darke, Duflou
& Torok, 2009; Sheehan et al., 2013). Overall, studies on cannabis use and suicide ideation and attempts have
produce mixed results. A case-control study of 302 serious suicide attempts in
New Zealand and general hospital community controls (Beautrais,
Joyce & Mulder, 1999) found an association between harmful use of cannabis
and suicide attempt. The association was substantially reduced after
statistical adjustment for confounding. A small case-control study in the USA
did not find an association (Petronis et al., 1990).
Results from longitudinal studies are more numerous and have varied as to
whether the associations persisted after adjustment for confounders, with newer
and larger studies reporting positive associations. Fergusson and colleagues
(Fergusson, Lynskey & Horwood,
1996; Fergusson & Horwood, 1997) found that
regular cannabis use at the age of 15 years predicted ideation and attempts at
16-17 years in New Zealand,
but these associations disappeared after controlling for confounders (Fergusson
& Horwood, 1997). A 30-year follow-up of the cohort
(van Ours et al., 2013) found a dose-response relation between cannabis use and suicidal ideation that
persisted after controlling for confounding variables. The New Zealand Dunedin
birth cohort (McGee, Williams & Nada-Raja, 2005) also reported an
association between cannabis use at 15 years of age and suicidal ideation at 18-21 years of age, but this was no longer
statistically significant after adjustment for confounders. A pooled analysis
of Australian and New Zealand cohort studies found a dose-response relation between the frequency of
cannabis use before the age of 17 years and suicide attempts at 17-25 years (Silins et
al., 2014). Longitudinal studies in the
USA and other countries have found associations between cannabis use and
suicidality over varying follow-up periods. In some studies the associations
vary with age and the measure of cannabis use (e.g. Newcomb, Vargas-Carmona &
Galaif, 1999; Newcomb, Scheier
& Bentler, 1993). Others have found associations
with suicidal ideation but not with suicide attempts (Juon
& Ensminger, 1997). In some studies the
association has persisted after controlling for confounding variables (e.g. Bovasso, 2001; Borowsky, Ireland
& Resnick, 2001; Clarke et al, 2014; Pedersen, 2008), whereas in other
studies it has not persisted, or has persisted only among subgroups (e.g.
Wilcox & Anthony, 2004; Zhang & Wu, 2014; Wichstrom,
2000). There have been very few studies of associations between regular
cannabis use and death by suicide. A follow-up study of Swedish conscripts (Andréasson & Allebeck, 1990)
reported that those who had used cannabis more than 50 times by the age of 18
years were at increased risk of dying by suicide. The same association was
observed in a 33-year follow-up (Price, 2009) but it was no longer significant
after adjusting for baseline alcohol, tobacco and other drug use, and psychiatric
disorders. A case-control study conducted among 108 individuals who committed
suicide and 108 who died in accidents, matched for age and gender, in Cali,
Colombia, found an increased odds ratio (OR=2.85(95% CI= 1.31–6.24) among those
with cannabis-use disorders (Palacio et al., 2007). A large case-control study
of 1463 suicides and 7392 natural deaths (Kung, 2003; Kung, 2005) found an
association between any cannabis use and suicide risk after adjusting for
depression, alcohol and mental health services. So did a four-year follow-up of
a large group of patients with cannabis-use disorders in Denmark, which found
an increased risk (Males OR=2.28 (95% CI=1.54– 3.37); Females OR=4.82 (95% CI=
2.47–9.39)) of suicide among those with cannabis-use disorders (Arendt, 2013). 6.1.8 Areas that require more research There
have been recent reports that higher proportions of lifetime users seem to have
developed cannabis-use disorders. As a
result, updated longitudinal research (including dose-response,
potency, frequency of use, and age of onset and reason for use) is needed to
identify if and why more users seem to develop cannabis-use disorders. Better epidemiological and
longitudinal studies are needed to determine the association between cannabis
use and the risk of different types of mental disorders and suicidal ideation,
attempts and death. These studies should include a wide age range, diverse
social and geographical populations, and should better measure cannabis use in
order to assess dose-response relations. While the evidence tends to
suggest that cannabis use is associated with suicide ideation and suicidal
behaviour, the lack of homogeneity in the measurement of cannabis exposure
across studies and, in some instances, the lack of systematic control for known
risk factors are clear limitations in current knowledge
(Borges, Bagge & Orozco, 2016).