Cannabis Use and Psychosis: A Longitudinal Population-based Study

See the original paper here at source

Page 1

319

American Journal of Epidemiology

Vol. 156, No. 4

Printed in U.S.A.

DOI: 10.1093/aje/kwf043

ORIGINAL CONTRIBUTIONS

Cannabis Us Cannabis use and Psychosis: A Longitudinal Population-based Study

J. van Os

1,2

, M. Bak

, M. Hanssen

, R. V. Bijl

3,4

, R. de Graaf

, and H. Verdoux

Department of Psychiatry and Neuropsychology, European Graduate School of Neuroscience, Maastricht University,

Maastricht, the Netherlands.

Division of Psychological Medicine, Institute of Psychiatry, London, United Kingdom.

The Netherlands Institute of Mental Health and Addiction, Trimbos-Instituut, Utrecht, the Netherlands.

Research and Documentation Centre (WODC), Ministry of Justice, The Hague, the Netherlands.

Department of Psychiatry, Victor Segalen Bordeaux 2 University, and Hôpital Charles Perrens, Bordeaux, France.

Received for publication October 1, 2001; accepted for publication April 17, 2002.

Cannabis use may increase the risk of psychotic disorders and result in a poor prognosis for those with an

established vulnerability to psychosis. A 3-year follow-up (19971999) is reported of a general population of

4,045 psychosis-free persons and of 59 subjects in the Netherlands with a baseline diagnosis of psychotic

disorder. Substance use was assessed at baseline, 1-year follow-up, and 3-year follow-up. Baseline cannabis

use predicted the presence at follow-up of any level of psychotic symptoms (adjusted odds ratio (OR) = 2.76, 95%

confidence interval (CI): 1.18, 6.47), as well as a severe level of psychotic symptoms (OR = 24.17, 95% CI: 5.44,

107.46), and clinician assessment of the need for care for psychotic symptoms (OR = 12.01, 95% CI: 2.24,

64.34). The effect of baseline cannabis use was stronger than the effect at 1-year and 3-year follow-up, and more

than 50% of the psychosis diagnoses could be attributed to cannabis use. On the additive scale, the effect of

cannabis use was much stronger in those with a baseline diagnosis of psychotic disorder (risk difference, 54.7%)

than in those without (risk difference, 2.2%;

for interaction = 0.001). Results confirm previous suggestions that

cannabis use increases the risk of both the incidence of psychosis in psychosis-free persons and a poor

prognosis for those with an established vulnerability to psychotic disorder.

Am J Epidemiol

2002;156:31927.

cannabis; drug utilization; psychoses, substance-induced; psychotic disorders; schizophrenia

Abbreviations: BPRS, Brief Psychiatric Rating Scale; CI, confidence interval; CIDI, Composite International Diagnostic

Interview; DSM-III-R,

Diagnostic and Statistical Manual of Mental Disorders

, Third Edition, Revised; OR, odds ratio; T1, time 1

(between baseline and 1997); T2, time 2 (between 1997 (T1) and 1999).

Although converging epidemiologic findings demonstrate

that the prevalence of cannabis use is higher among subjects

with psychosis than among subjects from the general popu-

lation (13), the mechanisms underlying this comorbid asso-

ciation have not been identified fully (4, 5). It is unclear

whether subjects with incipient psychosis use cannabis to

self-medicate their psychotic symptoms or, conversely,

whether exposure to cannabis is a risk factor for onset of

psychosis (6, 7). Because this issue cannot be disentangled

by using cross-sectional or retrospective studies, prospective

studies are essential to examine the temporal relation

between cannabis use and emergence of psychosis.

A previous Swedish study (8) showed that young men

using large quantities of cannabis at conscription were at

increased risk of being admitted for schizophrenia over the

subsequent 15-year period. However, to our knowledge,

these findings have not yet been replicated in another popu-

lation-based sample. Furthermore, the Swedish study was

hampered by several limitations, such as the lack of informa-

tion on drug use over the follow-up period and the fact that

Correspondence to Prof. Jim van Os, Department of Psychiatry and Neuropsychology, Maastricht University, P.O. Box 616 (DRT

), 6200 MD

Maastricht, the Netherlands (e-mail: j.vanos@sp.unimaas.nl).

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van Os et al.

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psychosis cases were restricted to persons requiring hospital

admission.

Another unsolved question regarding the link between

cannabis use and psychosis is whether the impact of

cannabis use on subsequent psychosis, if any, is stronger in

subjects with a preexisting vulnerability to psychosis (9, 10).

Several studies of subjects with a hospital diagnosis of

psychosis have found that cannabis users have a poorer prog-

nosis than nonusers do (6, 1113). Since these findings were

obtained in clinical samples, several factors linked to

hospital-based recruitment of subjects may confound the

association between cannabis use and poor outcome in

subjects with an established vulnerability to psychosis.

The aims of the present study were to test the following

hypotheses in a population-based sample of subjects

followed up over 3 years. First, cannabis use increases the

risk of psychosis, independent of the use of other drugs;

second, those with an established vulnerability to psychotic

disorder are more susceptible to this risk-increasing effect.

MATERIALS AND METHODS

Sample

This study was part of the Netherlands Mental Health

Survey and Incidence Study (NEMESIS), a longitudinal

study of the prevalence, incidence, course, and consequences

of psychiatric disorders in the Dutch general population. The

local ethics committee approved the study proposal as well

as the manner in which informed consent was obtained from

subjects. Subjects were contacted three times: in 1996 (base-

line), in 1997 (T1-assessing the period between baseline

and T1), and in 1999 (T2-assessing the period between T1

and T2) (14, 15).

A multistage, stratified, random sampling procedure was

used to identify the sample. First, 90 municipalities were

sampled randomly. Second, addresses of private households

were selected randomly. Third, the person in the private

household who had had the most recent birthday and was

aged 1864 years was asked to participate. Persons living in

institutions, including those residing in psychiatric hospitals,

were not included in the sampling frame. A total of 7,076

subjects were enlisted at baseline. The response rate was

69.7 percent. No difference in psychiatric morbidity based

on the 12-item General Health Questionnaire was found

between responders and nonresponders (14, 15). At T1,

5,618 subjects participated for the second time; at T2, 4,848

subjects participated.

Instruments

The study sample was interviewed at home by using the

Composite International Diagnostic Interview (CIDI),

version 1.1 (16) for all three measurements. The CIDI gener-

ates

Diagnostic and Statistical Manual of Mental Disorders

Third Edition, Revised (DSM-III-R) diagnoses and is

designed for trained interviewers who are not clinicians.

Interviewers read the questions and record respondents'

answers, making the CIDI essentially a self-report instru-

ment (17). The CIDI psychosis section (G) consists of 17

core psychosis items (G1G13, G15, G16, G20, and G21) on

delusions (13 items) and hallucinations (four items). These

psychosis items correspond to classic psychotic symptoms

such as persecution, thought interference, auditory halluci-

nations, and passivity phenomena.

Clinical reinterviews for psychotic symptoms

Because psychotic symptoms may be difficult to diagnose

by lay interviewers, especially the clinical relevance of such

symptoms (1820), clinical reinterviews were conducted by

telephone by an experienced clinician (psychiatrist, senior

psychiatric trainee, or psychologist) for all subjects who had

evidence of significant psychosis at baseline and at T2 (21,

22). Since the yearly incidence of psychosis is very low, no

attempt was made to conduct clinical reinterviews at T1, just

1 year after the baseline interview. However, cases of

psychosis that were incident between baseline and T1 would

still have been identified at the T2 interview if the subjects

continued to experience symptoms between T1 and T2,

which is likely for the majority of cases who had any signif-

icant level of psychotic symptoms. The proportions of

eligible subjects who were reinterviewed successfully by the

clinician were 47.2 percent at baseline and 74.4 percent at

T2.The reinterviews were conducted by using questions from

the Structured Clinical Interview for DSM-III-R (SCID), an

instrument with proven reliability and validity in diagnosing

schizophrenia (21). If the clinician's CIDI psychosis

symptom rating did not coincide with that of the lay inter-

viewer, the rating of the lay interviewer was replaced with

that of the clinician. These corrected CIDI ratings were then

entered into the CIDI diagnostic program. The DSM-III-R

diagnoses of psychotic disorder at baseline were thus based

on the Structured Clinical Interview for DSM-III-R data

from these clinical reinterviews. Since no assessment of the

need for treatment was made at baseline for subjects with a

DSM-III-R diagnosis of psychosis (see below), this group

included subjects who were clinical psychosis cases but also

subjects whose psychotic experiences were not associated

with the need for treatment. Thus, these subjects are here-

after referred to in this paper as persons with an established

vulnerability to psychosis.

T2 assessment of incident psychotic symptoms

At T2, three Brief Psychiatric Rating Scale (BPRS) items

(22)-"unusual thought content," "hallucinations," and

"conceptual disorganization"-were additionally scored by

the clinician who conducted the telephone clinical reinter-

view. The scores for each symptom ranged from 1, "absent"

to 7, "very severe." Ratings of 23 indicate nonpathologic

intensities of symptoms, and 47 indicate pathologic intensi-

ties of symptoms (23). The BPRS items "unusual thought

content" and "hallucinations" represent the positive symp-

toms for psychosis and were used in the analyses in two

ways: 1) any rating of more than 1 for either of these items

(hereafter referred to as BPRS any psychosis) and 2) any

rating of 4 or more on either of these items (hereafter

referred to as BPRS pathology-level psychosis). To skew the

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sample toward subjects with a lifetime first-ever occurrence

of symptoms, we included only those subjects who, at the

baseline interview, had a rating of lifetime

absence

for all of

the individual items in the CIDI psychosis section.

T2 assessment of incident cases of psychosis

Since the most widely used system of classifying psychi-

atric disorders, the DSM-III-R (24), allocates "patient

status" on the basis of disability and distress rather than clin-

ical need, and persons in need of treatment may not be iden-

tified reliably, especially in population-based research (25),

we used a procedure yielding a needs-based diagnosis to

identify incident cases of psychosis at T2. Following each

interview by clinicians at T2, a consensus meeting was

organized that was attended by two psychologists and two

psychiatrists, during which all available information

regarding the case of psychosis was presented by the person

who had conducted the telephone interview. The four clini-

cians reached a consensus regarding whether there was a

need for mental health care in the context of psychotic symp-

toms, as defined in the Camberwell Assessment of Need

(CAN) (26). The diagnoses that resulted from the consensus

meeting were categorized as 1) no need for care in relation to

psychotic symptoms or 2) probable or definite need for care

in relation to psychotic symptoms. Validation of the needs-

based diagnosis has been described in previous papers (M.

Hanssen, Maastricht University, unpublished manuscript;

M. Bak, Maastricht University, unpublished manuscript).

Drug use assessment

The L section of CIDI assesses use of a variety of

substances. Included in the current analyses were questions

about the following substances: cannabis, psychostimulants,

cocaine, phencyclidine (PCP), and psychedelics. Psycho-

stimulants, cocaine, phencyclidine, and psychedelics were

combined into one group of "other drugs." Two types of

exposure variables were constructed: 1) any use (hereafter

referred to as any use) and 2) frequency of use over all three

assessment periods (hereafter referred to as cumulative

frequency). Any use at baseline, T1, or T2 was defined as

any frequency of use (lifetime any use at baseline, use over

the previous period at T1 and T2). Frequency of use during

the period of heaviest use was expressed on a 15 scale

(nearly every day, 34 days per week, 12 days per week, 1

3 days per month, less than once a month). Cumulative

frequency was the overall longitudinal exposure defined as

the sum of the five-level frequency ratings at baseline, T1,

and T2. This score, with a range of 115, was also divided

into three groups (15, 610, 1115).

Analyses

Associations between cannabis use and psychosis

outcome.

Associations between drug use and psychosis

outcome were expressed as odds ratios. The odds ratio

expressed the risk of developing the psychosis outcome for

those using drugs relative to those not using drugs. Adjusted

odds ratios were computed by using logistic regression (27)

in the STATA statistical software program (28). All analyses

were a priori adjusted for age (10-year groups), sex, ethnic

group (0, subject and both parents born in the Netherlands; 1,

other), level of education (four levels), unemployment, and

single marital status. In addition, we also controlled for two

previous risk factors for psychosis identified in the cohort:

urbanicity (three levels) and experience with discrimination

(four levels) (29).

To examine whether the effect of cannabis use at baseline

on psychosis at follow-up was a proxy effect of cannabis use

at follow-up, we entered cannabis any use at baseline,

cannabis any use at T1 follow-up, and cannabis any use at T2

follow-up simultaneously in the adjusted models of the two

psychosis outcomes. To assess whether any effect of

cannabis was independent of use of other drugs associated

with psychosis, models in which cannabis and other drugs

were entered jointly were compared with models in which

cannabis and other drugs were entered separately.

Risk set and sensitivity analyses.

All of the analyses,

with the exception of the interaction effects (see below),

were conducted in the group of subjects who 1) at baseline,

had a score of lifetime absence for all individual items in the

CIDI psychosis section (5,838 of 7,076 subjects, 82.5

percent (30)); 2) had had a CIDI interview at T2 (

= 4,848);

and 3) at T2, had not missed being reinterviewed by clini-

cians about the presence of psychotic symptoms if they had

been eligible for this clinical reinterview. This risk set

included 4,045 subjects. To check for possible fluctuations

in sample demographic stability occasioned by conditions 1

and 2, the age and sex distributions of the groups identified

by conditions 1 and 2 were compared with the risk set of

4,045 subjects. The proportion of men across the groups of

5,838 (condition 1), 4,848 (condition 2), and 4,045 (risk set)

was 52.6, 53.5, and 52.7 percent, respectively, and mean age

was 41.6, 41.2, and 41.5 years, respectively.

Because we did not reinterview all of the eligible subjects

at T2 who had shown evidence of psychosis (the clinical

reinterview rate at T2 was 74.4 percent, as noted above), we

conducted sensitivity analyses to examine whether differen-

tial attrition could have biased any findings. These analyses

were performed by substituting missing data, for the subjects

who had missed clinical reinterview, in such a way that the

extremes of any bias could be quantified. In the first sensi-

tivity analysis, all missing subjects were allocated to the

category of caseness of BPRS pathology-level psychosis; in

the second type of analysis, all missing subjects were allo-

cated to the category of noncaseness. In the same manner, we

tested whether attrition in the sample as a whole (

n =

7,076

at baseline,

n =

4,848 at T2) could have biased the findings.

Population attributable fraction.

The population attribut-

able risk fraction, or the proportion of psychosis outcomes

that could have been prevented if cannabis use 1) were a

causal risk factor and 2) were eliminated completely from

the population, is a measure of the public health importance

of an exposure. It was derived from the adjusted associations

between cannabis use and psychosis in the logistic regres-

sion models by using the AFLOGIT procedure in STATA

software (28), which allows for estimating the population

attributable fraction from within a logistic regression frame-

work, thus enabling confounders to be taken into account.

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Interaction between cannabis use and vulnerability to

psychosis.

To assess the effect of cannabis in those with an

established vulnerability to psychosis, the effect of cannabis

on the psychosis outcomes at T2 was estimated in the group

of subjects who, at baseline, had had a DSM-III-R lifetime

diagnosis of any affective or nonaffective psychotic disorder

(

= 59 with baseline and T2 outcome data) and was then

compared with the effect of cannabis in the risk set (

4,045). The group of 59 subjects who had a psychotic

disorder and T2 outcome data came from a larger group of

107 who had a baseline DSM-III-R diagnosis of psychotic

disorder. A comparison between the 59 psychosis cases with

and the 48 without T2 outcome data revealed no differences

in terms of baseline cannabis use (

= 1.0, df = 1,

= 0.31),

age (

= 0.55, df = 105,

= 0.58), or sex (

= 2.7, df = 1,

= 0.10). In line with recent advances in the conceptualiza-

tion of interaction, we calculated the statistical additive

interaction and estimated from that the population amount of

biologic synergism between cannabis use and psychosis

vulnerability (refer to the Appendix) (31). To calculate the

statistical interaction under an additive model, the BINREG

procedure in STATA software (28), which fits generalized

linear models for the binomial family estimating risk differ-

ences, was used to model interactions between cannabis (any

use) and psychosis vulnerability (any lifetime diagnosis of

psychosis).

RESULTS

Cannabis use and psychosis

In the risk set of 4,045 subjects who, at the baseline inter-

view, had a rating of lifetime absence for all individual items

in the CIDI psychosis section, seven subjects (0.17 percent)

at T2 had a probable/definite need for care related to

psychotic symptoms. The number of subjects at T2 with

BPRS any psychosis was 38 (0.94 percent), and the number

with BPRS pathology-level psychosis was 10 (0.25 percent).

Subjects with a psychosis outcome at T2 had higher levels

of cannabis use at baseline (table 1). Cannabis any use at

baseline and cumulative frequency were associated with a

high risk of psychosis outcome at T2 (table 2). The associa-

tions generally remained significant after adjustment for age,

sex, ethnic group, single marital status, level of education,

urbanicity, and level of discrimination. Additional adjust-

ment for the presence of any CIDI lifetime diagnosis at base-

line (to exclude the possibility that cannabis use at baseline

was secondary to a nonpsychotic DSM-III-R diagnosis,

which, in turn, was a prodrome of later psychosis) changed

the parameters by only a tiny amount (e.g., BPRS pathology-

level outcome-cannabis any use at baseline: odds ratio

(OR) = 23.32, 95 percent confidence interval (CI): 4.92,

110.50; cumulative frequency: OR = 4.17, 95 percent CI:

2.34, 7.42).

Distal versus proximal effects

For the three psychosis outcomes, the effect of baseline

cannabis use was much stronger than the effects of more

proximal cannabis use at T1 and T2. This finding indicated

that the effects of cannabis use at baseline on psychosis at

follow-up was not a proxy effect of cannabis use at follow-

up (table 3).

Cannabis and other substances

Use of other drugs, as defined in Materials and Methods,

was strongly associated with the three psychosis outcomes

when entered separately in the model. However, when

entered jointly with cannabis, the effects were greatly

reduced or even disappeared altogether, while the effect of

cannabis remained (table 4).

Population attributable fraction

The population attributable fraction was calculated for the

"any use" exposure and the three outcomes. The population

attributable fractions were 13.4 percent for BPRS any

psychosis, 67.1 percent for BPRS pathology-level psychosis,

and 50.4 percent for needs-based diagnosis of psychotic

TABLE 1. Patterns of cannabis use and psychosis outcome, the Netherlands Mental Health Survey and Incidence Study, 19961999

T2, time 2 (between 1997 and 1999); BPRS, Brief Psychiatric Rating Scale (Psychol Rep 1962;10:799812); , absence of the outcome; +,

presence of the outcome.

Some percentages do not total 100 because of rounding.

Cannabis exposure

psychosis outcome

BPRS

any psychosis

BPRS pathology-level psychosis

Needs-based diagnosis of psychotic disorder

Outcome

(

= 4,007)

Outcome+

(

= 38)

Outcome

(

= 4,035)

Outcome+

(

= 10)

Outcome

(

= 4,038)

Outcome+

(

= 7)

No.

Baseline any use

304

7.59

21.05

305

7.56

308

7.63

57.14

Cumulative

frequency

No use

3,622

91.7

79.0

3,649

91.7

30.0

3,649

91.6

42.9

Lowest level

264

6.7

7.9

265

6.7

20.0

265

6.7

28.6

Middle level

0.9

5.3

0.9

20.0

0.9

Highest level

0.8

7.9

0.8

30.0

0.8

28.6

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disorder. These fractions indicated that, assuming that the

relation between cannabis use and psychosis is causal, the

incidence of the three psychosis outcomes would be reduced

by 13, 67, and 50 percent, respectively, if the cannabis expo-

sure were eliminated from the population.

Interaction with vulnerability to psychosis

Of the 59 subjects with a DSM-III-R diagnosis of any

psychosis at baseline for whom follow-up data at T2 were

available, nine (15.3 percent) reported cannabis any use at

baseline. In the risk set, this proportion was 7.7 percent (

312). On the additive scale, the increase in the risk of having

the psychosis outcome at T2 was much higher in the group

with a baseline diagnosis of psychotic disorder than in that

without such a diagnosis, although the increase was still

significant in the latter group. The difference in risk between

those with and without psychotic disorder at baseline was

statistically significant for two psychosis outcomes (table 5).

By following the procedure developed by Darroch (31)

(refer to the Appendix), we calculated what proportion of the

BPRS pathology-level psychosis outcome in subjects both

TABLE 2. Associations between cannabis use and time 2 psychosis outcome, the Netherlands Mental Health Survey and Incidence

Study, 19961999

T2, time 2 (between 1997 and 1999); BPRS, Brief Psychiatric Rating Scale (Psychol Rep 1962;10:799812); OR, odds ratio; CI, confidence interval.

Adjusted for age, sex, ethnic group, single marital status, level of education, urbanicity, and level of discrimination.

Reference category.

§ No exposed persons had the outcome.

¶ The increase in risk with one unit change in cannabis frequency.

Cannabis exposure

psychosis outcome

BPRS

any psychosis

(

= 38)

BPRS pathology-level psychosis

(

= 10)

Needs-based diagnosis of psychotic disorder

(

= 7)

95% CI

Adjusted

95% CI

Adjusted

95% CI

Adjusted

95% CI

Baseline any

use

3.25 1.48, 7.15

2.76

1.18, 6.47

28.54

7.34, 110.91

24.17

5.44, 107.46

16.15 3.60, 72.47

12.01

2.24, 64.34

Cumulative

frequency

No use

Lowest level

1.37 0.42, 4.52

1.23

0.36, 4.23

9.18

1.53, 55.18

7.90

1.15, 54.09

9.18 1.53, 55.18

5.10

0.66, 39.21

Middle level

7.10 1.63, 30.91

4.90

10.4, 23.14

71.55 11.58, 441.94

54.46

7.17, 413.73

-§

Highest level 11.32 3.29, 38.99

6.81

1.79, 25.92

114.03 22.17, 586.50

74.67

11.76, 474.32

73.72 11.92, 455.76

47.77

5.91, 385.94

Linear trend¶

2.23 1.53, 3.24

1.89

1.25, 2.85

4.96

3.08, 8.00

4.27

2.44, 7.45

3.97 2.22, 7.10

3.53

1.76, 7.09

TABLE 3. Effects of cannabis use distal and proximal to psychosis outcome, the Netherlands Mental Health Survey and Incidence

Study, 19961999

T2, time 2 (between 1997 (T1) and 1999); BPRS, Brief Psychiatric Rating Scale (Psychol Rep 1962;10:799812); OR, odds ratio; CI,

confidence interval; T1, time 1 (between baseline and 1997).

Adjusted for age, sex, ethnic group, single marital status, level of education, urbanicity, and level of discrimination; reference category,

those subjects who did not use cannabis at the three specified time points.

Drug exposure

psychosis outcome

BPRS

any psychosis

(

= 38)

BPRS pathology-level psychosis

(

= 10)

Needs-based diagnosis of psychotic

disorder (

= 7)

Adjusted OR

95% CI

Adjusted OR

95% CI

Adjusted OR

95% CI

Separate effects

Any use at baseline

2.76

1.18, 6.47

24.17

5.44, 107.46

12.01

2.24, 64.34

Any use at T1

2.96

0.96, 9.22

14.91

3.39, 65.57

11.07

1.62, 75.76

Any use at T2

3.17

1.02, 9.92

15.08

3.35, 68.00

9.36

1.39, 63.13

Jointly entered in the same

model

Any use at baseline

2.22

0.78, 6.31

15.78

2.83, 88.05

7.73

1.09, 54.74

Any use at T1

1.13

0.18, 7.15

1.35

0.14, 13.11

1.75

0.08, 40.35

Any use at T2

1.68

0.28, 10.19

2.32

0.25, 21.90

1.86

0.09, 38.52

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exposed to cannabis and having an established vulnerability

to psychosis was attributable to the synergistic action of

these two factors. This calculation revealed that between 79

and 82 percent was due to the synergistic action of these two

factors.

Sensitivity analyses

The results regarding the BPRS pathology-level psychosis

outcome and missing clinical reinterview data were as

follows: 1) assuming that all subjects for whom values were

missing were noncases-cannabis any use: OR = 24.36, 95

percent CI: 5.48, 108.37; cannabis cumulative frequency: OR

= 4.27, 95 percent CI: 2.45, 7.47; and 2) assuming that all

subjects for whom values were missing were cases-cannabis

any use: OR = 3.30, 95 percent CI: 1.30, 8.33; cannabis cumu-

lative frequency: OR = 2.17, 95 percent CI: 1.41, 3.34. The

results regarding the BPRS pathology-level psychosis

outcome and missing data due to general sample attrition were

as follows: 1) assuming that all subjects for whom values

TABLE 4. Effects of cannabis use on psychosis in relation to use of other substances, the Netherlands Mental Health Survey and

Incidence Study, 19961999

T2, time 2 (between 1997 and 1999); BPRS, Brief Psychiatric Rating Scale (Psychol Rep 1962;10:799812); OR, odds ratio; CI, confidence

interval.

Adjusted for age, sex, ethnic group, single marital status, level of education, urbanicity, and level of discrimination.

Reference category, those subjects who did not use cannabis or other drugs at baseline (baseline any use) or at all three time points

(cumulative frequency).

§ Psychostimulants, cocaine, phencyclidine (PCP), and psychedelics were combined into one group of "other drugs."

¶ Linear trend for the adjusted odds ratio: an increase in risk with one unit change in cannabis frequency.

Drug exposure

psychosis outcome

BPRS

any psychosis

(

= 38)

BPRS pathology-level psychosis

(

= 10)

Needs-based diagnosis of psychotic

disorder (

= 7)

Adjusted OR

95% CI

Adjusted OR

95% CI

Adjusted OR

95% CI

Separate effects

Baseline any use

Cannabis

2.76

1.18, 6.47

24.17

5.44, 107.46

12.01

2.24, 64.34

Other drugs ,§

5.38

1.48, 19.56

23.47

4.99, 110.35

9.55

0.90, 101.52

Cumulative frequency¶

Cannabis

1.89

1.25, 2.85

4.27

2.44, 7.45

3.53

1.76, 7.09

Other drugs

2.57

1.31, 5.04

4.59

2.17, 9.74

2.84

0.95, 8.49

Jointly entered in the same model

Baseline any use

Cannabis

2.11

0.78, 5.71

16.93

3.33, 86.13

10.51

1.75, 63.21

Other drugs

2.99

0.68, 13.25

3.95

0.77, 20.27

1.89

0.15, 23.57

Cumulative frequency¶

Cannabis

1.65

1.00, 2.73

3.73

1.99, 7.01

3.47

1.64, 7.37

Other drugs

1.64

0.71, 3.80

1.83

0.75, 4.50

1.09

0.26, 4.52

TABLE 5. Interactions between cannabis any use and existing vulnerability to psychosis on the additive scale (risk difference), the

Netherlands Mental Health Survey and Incidence Study, 19961999

BPRS, Brief Psychiatric Rating Scale (Psychol Rep 1962;10:799812); CI, confidence interval.

Risk of having the psychosis outcome at T2 (time 2 (between 1997 and 1999)).

Tests whether an increase in risk in the "any psychosis" group is significantly greater than an increase in risk in the "no psychosis" group.

BPRS

any psychosis (

= 54)

BPRS pathology-level psychosis

(

= 22)

Needs-based diagnosis of psychotic

disorder (

= 15)

Increase (%)

95% CI

Increase (%)

95% CI

Increase (%)

95% CI

Increase in risk associated with

baseline cannabis any use

No psychosis (

= 4,045)

1.8

0.0, 3.5

2.2

0.5, 3.8

1.3

0.05, 2.5

Any psychosis (

= 59)

46.7

13.9, 79.4

54.7

22.6, 86.8

23.3

8.6, 55.2

Additive interaction

= 7.21, df = 1,

= 0.0073

= 10.26, df = 1,

= 0.0014

= 1.85, df = 1,

= 0.17

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325

Am J Epidemiol

Vol. 156, No. 4, 2002

were missing were noncases-cannabis any use: OR = 25.17,

95 percent CI: 5.64, 112.24; cannabis cumulative frequency:

OR = 4.27, 95 percent CI: 2.44, 7.45; and 2) assuming that all

subjects for whom values were missing were cases-cannabis

any use: OR = 1.11, 95 percent CI: 0.89, 1.38; cannabis cumu-

lative frequency: OR = 4.27, 95 percent CI: 2.44, 7.45.

DISCUSSION

This population-based prospective study showed that a

baseline history of cannabis use increased the risk of a

follow-up psychosis outcome for subjects with a lifetime

absence of psychosis, with a dose-response relation between

exposure load and psychosis outcome. A baseline lifetime

history of cannabis use was a stronger predictor of psychosis

outcome than was use over the follow-up period and use of

other drugs. A strong additive interaction was found between

cannabis use and established vulnerability to psychotic

disorder: the difference in risk of psychosis at follow-up

between those who did and did not use cannabis was much

stronger for those with an established vulnerability to

psychosis at baseline than for those without one. Sensitivity

analyses showed that differential attrition was unlikely to

have contributed to the results. In addition, previous analyses

of this sample have shown that psychopathology had only

weak-to-moderate effects on attrition at T1 (32).

The present findings have to be interpreted in light of poten-

tial methodological limitations. We cannot exclude underre-

porting of drug use, because it was assessed by using self-

reported data and was not confirmed with toxicologic

screening. However, urine testing does not provide informa-

tion on lifetime use, and there is little reason to suspect that

cannabis use was underreported; personal use of cannabis is

legal in the Netherlands, and cannabis is widely accepted as a

recreational drug. As a consequence of the limited number of

subjects who had a needs-based psychotic disorder, the effect

size of some associations could not be calculated, and some

interval estimations were imprecise. Some cases of psychosis

arising between baseline and T1, when no clinical reinter-

views were conducted, may have been missed at the T2 inter-

view if subjects' symptoms did not persist beyond the T1

interview. This possibility could, in theory, have biased our

findings if these had been the cases in which cannabis had no

effect, or a protective effect, on the development of psychotic

symptoms. However, when we examined the association

between baseline any cannabis use and any self-report of

psychotic symptoms at T1 in subjects who had been psychosis

free at baseline, the odds ratio was large and in the same direc-

tion (OR = 2.64, 95 percent CI: 1.54, 4.52). Although this

association was based on self-reported psychotic symptoms at

T1 instead of clinical assessment, it is unlikely that clinical

reinterview would have substantially changed the strength or

direction of this association.

In accordance with the findings reported by Andreasson et

al. (8), the present study shows that psychosis-free subjects

who have a lifetime history of cannabis use are at increased

risk of a psychosis outcome. As in the Swedish study (8),

further evidence supporting the hypothesis of a causal rela-

tion is demonstrated by the existence of a dose-response

relation (33) between cumulative exposure to cannabis use

and the psychosis outcome.

The strengths of the present study are that drug use was

documented in the context of a structured diagnostic inter-

view at baseline and over the follow-up period and that defi-

nition of psychosis outcome was not restricted to cases of

psychosis requiring hospitalization, which are but the

extreme of a continuum of psychotic experiences (29). Thus,

the present findings provide answers to questions raised by

the Swedish cohort study (8). First, the association between

cannabis use and psychosis outcome is not restricted to the

most severe outcome; that is, there is a continuum of risk

ranging from increased occurrence of psychotic symptoms

to incidence of cases in need of treatment. Second, the asso-

ciation is independent of use of other drugs at baseline and

over the follow-up period. Third, the finding that psychosis

outcome is more strongly predicted by a baseline lifetime

history of use than by recent use contributes to clarifying the

temporal relation between cannabis exposure and increased

risk of psychosis. This finding suggests that this association

is not fully explained by the short-term effects of cannabis

leading to acute occurrence of psychotic experiences (5).

Any claim of a causal relation between cannabis use and

psychosis would be further supported by a plausible biologic

mechanism (33, 34). Long-term effects of cannabis on the risk

of psychosis outcome may be due to long-lasting dysregula-

tion of endogenous anadamide/cannabinoid systems medi-

ating the effects of tetrahydrocannabinol on the brain. Other

neurotransmission systems modulated by cannabinoid recep-

tors may also be involved. Some recent findings indirectly

support this cannabinoid-receptor hypothesis. An increased

density of cannabinoid-1 receptors has been found in the

caudate-putamen of cannabis users (35), and there are close

interactions between cannabinoid and dopaminergic systems

(36) that are thought to underlie psychotic symptoms. Experi-

mental evidence in rodents has demonstrated that chronic

exposure to delta9-tetrahydrocannabinol induces sensitization

of monoaminergic neurotransmitter systems thought to be

involved in psychosis (37). A limited number of studies have

reported changes in the endogenous cannabinoid concentra-

tion (38) or in the number of cannabinoid receptors (35) in

subjects who have schizophrenia. These findings, which have

to be interpreted with caution since they have been obtained in

samples of patients with chronic disease, nevertheless suggest

that dysregulation of the cannabinoid system may be impli-

cated in the pathophysiology of psychosis. It can be

hypothesized that the neurobiologic changes induced by

tetrahydrocannabinol may interact with a preexisting vulnera-

bility to dysregulation of the cannabinoid system or to other

neurotransmission systems interacting with the cannabinoid

system. In accordance with this hypothesis, the present find-

ings demonstrate that the impact of cannabis use on psychosis

outcome is especially marked in subjects with an established

vulnerability to psychosis. The difference in the risk of

psychosis at follow-up between those who did and did not use

cannabis was much stronger for those with a baseline vulner-

ability to psychosis (54.7 percent) than for those without a

baseline experience of psychosis (2.2 percent).

About 80 percent of the psychosis outcome associated

with exposure to both cannabis and an established vulnera-

Page 8

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van Os et al.

Am J Epidemiol

Vol. 156, No. 4, 2002

bility to psychosis was attributable to the synergistic action

of these two factors. This finding indicates that, of the

subjects exposed to both a vulnerability to psychosis and

cannabis use, approximately 80 percent had the psychosis

outcome because of the combined action of the two risk

factors and only about 20 percent because of the action of

either factor alone.

In conclusion, this prospective study confirms previous

suggestions that cannabis use is an independent risk factor for

the emergence of psychosis in psychosis-free persons and

that those with an established vulnerability to psychotic

disorder are particularly sensitive to its effects, resulting in a

poor outcome. These findings have public health implica-

tions. If a causal relation between cannabis use and psychosis

outcome is assumed, the population attributable fraction-

that is, the maximum proportion of psychosis outcomes

attributable to cannabis use in psychosis-free subjects-is

higher than 50 percent. Although this high percentage can be

misleading because it also includes the effects of all other

causal risk factors that interact with cannabis, there is never-

theless cause for concern given the widespread use of

cannabis by adolescents and young adults (3941). The

percentage of cases that may be prevented by suppressing

exposure to this risk factor may not be negligible.

ACKNOWLEDGMENTS

Supported by a grant from the Dutch Ministry of Health.

REFERENCES

1. Degenhardt L, Hall W. The association between psychosis and

problematical drug use among Australian adults: findings from

the National Survey of Mental Health and Well-Being. Psychol

Med 2001;31:65968.

2. Regier D, Farmer M, Rae D, et al. Comorbidity of mental disor-

ders with alcohol and other drug abuse. Results from the Epide-

miologic Catchment Area (ECA) Study. JAMA 1990;264:

251118.

3. Kessler R, Crum R, Warner L, et al. Lifetime co-occurrence of

DSM-III-R alcohol abuse and dependence with other psychiat-

ric disorders in the National Comorbidity Survey. Arch Gen

Psychiatry 1997;54:31321.

4. Thornicroft G. Cannabis and psychosis. Is there epidemiologi-

cal evidence for an association? Br J Psychiatry 1990;157:25

33.

5. Johns A. Psychiatric effects of cannabis. Br J Psychiatry 2001;

178:11622.

6. Linszen DH, Dingemans P, Lenior M. Cannabis abuse and the

course of recent-onset schizophrenic disorders. Arch Gen Psy-

chiatry 1994;51:2739.

7. Hambrecht M, Hafner H. Substance abuse and the onset of

schizophrenia. Biol Psychiatry 1996;40:115563.

8. Andreasson S, Allebeck P, Engstrom A, et al. Cannabis and

schizophrenia. A longitudinal study of Swedish conscripts.

Lancet 1987;2:14836.

9. McGuire PK, Jones P, Harvey I, et al. Morbid risk of schizo-

phrenia for relatives of patients with cannabis-associated psy-

chosis. Schizophr Res 1995;15:27781.

10. van Os J, Marcelis M. The ecogenetics of schizophrenia: a

review. Schizophr Res 1998;32:12735.

11. Martinez-Arevalo MJ, Calcedo-Ordonez A, Varo-Prieto JR.

Cannabis consumption as a prognostic factor in schizophrenia.

Br J Psychiatry 1994;164:67981.

12. Kovasznay B, Fleischer J, Tanenberg-Karant M, et al. Sub-

stance use disorder and the early course of illness in schizophre-

nia and affective psychosis. Schizophr Bull 1997;23:195201.

13. Verdoux H, Liraud F, Gonzales B, et al. Suicidality and sub-

stance misuse in first-admitted subjects with psychotic disor-

der. Acta Psychiatr Scand 1999;100:38995.

14. Bijl RV, van Zessen G, Ravelli A, et al. The Netherlands Mental

Health Survey and Incidence Study (NEMESIS): objectives and

design. Soc Psychiatry Psychiatr Epidemiol 1998;33:5816.

15. Bijl RV, Ravelli A, van Zessen G. Prevalence of psychiatric

disorder in the general population: results of the Netherlands

Mental Health Survey and Incidence Study (NEMESIS). Soc

Psychiatry Psychiatr Epidemiol 1998;33:58795.

16. Smeets RMW, Dingemans PMAJ. Composite International

Diagnostic Interview (CIDI). Version 1.1. Geneva, Switzer-

land: World Health Organization, 1993.

17. Eaton WW, Neufeld K, Chen LS, et al. A comparison of self-

report and clinical diagnostic interviews for depression: diag-

nostic interview schedule and schedules for clinical assessment

in neuropsychiatry in the Baltimore epidemiologic catchment

area follow-up. Arch Gen Psychiatry 2000;57:21722.

18. Helzer JE, Robins LN, McEvoy LT, et al. A comparison of clin-

ical and diagnostic interview schedule diagnoses. Physician

reexamination of lay-interviewed cases in the general popula-

tion. Arch Gen Psychiatry 1985;42:65766.

19. Anthony JC, Folstein M, Romanoski AJ, et al. Comparison of

the lay diagnostic interview schedule and a standardized psy-

chiatric diagnosis. Experience in eastern Baltimore. Arch Gen

Psychiatry 1985;42:66775.

20. Cooper SA, Collacott RA. Relapse of depression in people with

Down's syndrome. Br J Develop Disabil 1994;40:327.

21. Spitzer RL, Williams JB, Gibbon M, et al. The Structured Clin-

ical Interview for DSM-III-R (SCID). I: history, rationale, and

description. Arch Gen Psychiatry 1992;49:6249.

22. Overall JE, Gorham DR. The Brief Psychiatric Rating Scale.

Psychol Rep 1962;10:799812.

23. Lukoff D, Nuechterlein KH, Ventura J. Manual for the

Expanded Brief Psychiatric Rating Scale. Schizophr Bull 1986;

12:594602.

24. American Psychiatric Association. Diagnostic and statistical

manual of mental disorders: DSM-III-R. 3rd ed, rev. Washing-

ton, DC: American Psychiatric Association, 1987.

25. Spitzer RL. Diagnosis and need for treatment are not the same.

(Comment). Arch Gen Psychiatry 1998;55:120.

26. Slade M, Phelan M, Thornicroft G, et al. The Camberwell

Assessment of Need (CAN): comparison of assessments by

staff and patients of the needs of the severely mentally ill. Soc

Psychiatry Psychiatr Epidemiol 1996;31:10913.

27. Clayton D, Hills M. Poisson and logistic regression. In: Clayton

D, Hills M, eds. Statistical models in epidemiology. Oxford,

United Kingdom: Oxford Science Publications, 1993:22736.

28. Stata Corporation. STATA statistical software, release 7.0. Col-

lege Station, Texas: Stata Corporation, 2001.

29. van Os J, Hanssen M, Bijl RV, et al. Prevalence of psychotic

disorder and community level of psychotic symptoms: an

urban-rural comparison. Arch Gen Psychiatry 2001;58:6638.

30. van Os J, Hanssen M, Bijl RV, et al. Strauss (1969) revisited: a

psychosis continuum in the general population? Schizophr Res

2000;45:1120.

Page 9

Cannabis Use and Psychosis

327

Am J Epidemiol

Vol. 156, No. 4, 2002

31. Darroch J. Biologic synergism and parallelism. Am J Epide-

miol 1997;145:6618. (Comments published in Am J Epide-

miol 1998;147:8990).

32. de Graaf R, Bijl RV, Smit F, et al. Psychiatric and sociodemo-

graphic predictors of attrition in a longitudinal study: the Neth-

erlands Mental Health Survey and Incidence Study

(NEMESIS). Am J Epidemiol 2000;152:103947.

33. Hill A. The environment and disease: association or causation?

J Royal Soc Med 1965;58:295300.

34. Susser M. What is a cause and how do we know one? A gram-

mar for pragmatic epidemiology. Am J Epidemiol 1991;133:

63548.

35. Dean B, Sundram S, Bradbury R, et al. Studies on [3H]CP

55940 binding in the human central nervous system: regional

specific changes in density of cannabinoid-1 receptors associ-

ated with schizophrenia and cannabis use. Neuroscience 2001;

103:915.

36. Tanda G, Pontieri F, Di Chiara G. Cannabinoid and heroin acti-

vation of mesolimbic dopamine transmission by a common

opoid receptor mechanism. Science 1997;276:204850.

37. Gorriti MA, Rodriguez de Fonseca F, Navarro M, et al. Chronic

(-)-delta9-tetrahydrocannabinol treatment induces sensitization

to the psychomotor effects of amphetamine in rats. Eur J Phar-

macol 1999;365:13342.

38. Leweke FM, Giuffrida A, Wurster U, et al. Elevated endog-

enous cannabinoids in schizophrenia. Neuroreport 1999;10:

16659.

39. Webb E, Ashton C, Kelly P, et al. Alcohol and drug use in UK

university students. Lancet 1996;348:9225.

40. Perkonigg A, Lieb R, Hofler M, et al. Patterns of cannabis use,

abuse and dependence over time: incidence, progression and

stability in a sample of 1228 adolescents. Addiction 1999;94:

166378.

41. Smart R, Ogborne A. Drug use and drinking among students in

36 countries. Addict Behav 2000;25:45560.

APPENDIX

Estimating the Amount of Biologic Synergism between

Two Causes

Let us assume that there are two risk factors for schizo-

phrenia,

and

Risk

is a measure of the proportion of

persons who develop schizophrenia. If there are two risk

factors,

and

, there are four possible exposure states

according to whether each factor is present (+) or absent (),

and each of these four exposure states carries a specific risk.

Thus, the risk of schizophrenia in the population exposed to

only is

(

), and the risk in the population exposed to

only is

(

). The risk of schizophrenia in the population

exposed to neither

nor

, whereas the risk in the popu-

lation exposed to both

and

(

). On the additive

scale, the

effect

of a risk factor is expressed as a

risk differ-

ence

. For example, if

(

) is 0.25 and

is 0.10, the effect of

is 0.25 0.10 = 0.15. We can thus express the effect of

(

)

, the effect associated with

(

)

, and the

effect associated with the

exposure as

(

)

. The

following table shows the effects associated with the four

different exposure states:

Because the combined effect of

and

(

)

, the

excess of this effect over the sum of the solitary effects of

and

is as follows: [

(

)

] [

(

)

] [

(

)

] =

[

(

)

(

)

(

) +

If [

(

)

(

)

(

) +

] > 0,

and

are said to interact

on the additive scale. We will hereafter refer to [

(

)

(

)

(

) +

] as the statistical additive interaction.

How can we quantify the extent to which

and

act

synergistically, that is, in some way depend on each other, or

coparticipate, in disease causation? Let us consider the

proportion of persons in the population who developed schiz-

ophrenia after exposure to both

and

, or

(

). It is

possible that some of these persons would also have

contracted the disorder after exposure to either

alone.

The degree to which some persons would also have

contracted the disorder after exposure to either

alone

is referred to as the degree of

parallelism

. If there is paral-

lelism,

and

"compete" to cause schizophrenia, and, the

more they compete, the smaller the proportion of persons

who contracted the disease because of the

coparticipation

and

. Thus, parallelism can be thought of as the opposite

of synergism. For example, in the extreme case of 100

percent parallelism, where all persons exposed to

and

had developed the disease because of the causal action of

either

alone, no person could have contracted schizo-

phrenia because of the coparticipation of

and

. In this

case, the amount of synergism would be zero. In practice, it is

impossible to assess the amount of parallelism and the

amount of synergy in persons exposed to both

and

However, it can be shown that the amount by which syner-

gism exceeds parallelism equals the excess of

(

) over the

sum of the solitary effects of

and

(i.e., the statistical addi-

tive interaction as shown above) (33). In other words, |syner-

gism| |parallelism| = [

(

)

(

)

(

) +

The amount of synergy can then be approximated by using

the following table (33):

The variables

1 and

2 are two unknowns that sum with

synergism and parallelism to [

(

)

(

)] and [

(

) R],

respectively. In our study, the risks were

= 0.08 percent;

(

) = 12 percent,

(

) = 2.2 percent; and

(

) = 67

percent. Filling in these risks in the table above reveals that

synergism is 7982 percent.

(

)

(

)

(

)

|synergism|

(

)

(

)

|parallelism|

(

)

(

)

(

)

(

)