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are in Research Cannabis
use and cognitive decline in persons under 65 years of age AMERICAN
JOURNAL OF EPIDEMIOLOGY, Vol. 149, No.9 pages 794-800, 1999 Constantine G.
Lyketsos, Elizabeth Garrett, Kung-Yee Liang, and James C. Anthony ABSTRACT The
purpose of this study was to investigate possible adverse effects of cannabis
use on cognitive decline after 12 years in persons under age 65 years. This was
a follow-up study of a probability sample of the adult household residents of
East Baltimore. The analyses included 1,318 participants in the Baltimore, Maryland,
portion of the Epidemiologic Catchment Area study who completed the Mini-Mental
State Examination (MMSE) during three study waves in 1981, 1982, and 1993-1996.
Individual MMSE score differences between waves 2 and 3 were calculated for each
study participant. After 12 years, study participants' scores declined a mean
of 1.20 points on the MMSE (standard deviation 1.90), with 66% having scores that
declined by at least one point. Significant
numbers of scores declined by three points or more (15% of participants in the
18--29 age group). There
were no significant differences in cognitive decline between heavy users, light
users, and nonusers of cannabis. There
were also no male-female differences in cognitive decline in relation to cannabis
use. The authors conclude that over long time periods, in persons under age 65
years, cognitive decline occurs in all age groups. This decline is closely associated
with aging and educational level but does not appear to be associated with cannabis
use. Cognitive
capacity has multiple determinants, including genetic makeup, nutritional status,
health status, formal education, and age-related developmental processes. This
capacity generally reaches its peak in early adulthood and then declines later
in life (1). Cognitive decline is a significant public health problem, given its
association with impaired functioning and increased mortality (1) and its close
link to dementia (2-4). Dementia is defined as the occurrence of measurable, global
cognitive decline sufficient to impair functioning (5). The prevalence and incidence
of dementia, now one of the most common and serious diseases of the elderly, is
rapidly increasing as the world population ages (6, 7). Epidemiologic
studies of dementia and of cognitive decline have typically investigated individuals
over the age of 60 years. The expected prevalence of dementia in these age groups
is 2 percent or higher (6, 7), and prevalence might be as high as 48 percent in
those over age 85 (6, 7). In late life, dementing processes hamper the study of
cognitive decline as a phenomenon distinct from dementia. Additionally, recent
research suggests (8) and scientific consensus concurs (9) that dementia is best
understood as the result of cumulative effects on the brain from diseases (e.g..
Alzheimer's disease or cerebrovascular disease) and other exposures (e.g. alcohol
or tobacco use), all occurring against background, possibly lifelong, declines
in cognition associated with aging itself. However, epidemiologic knowledge regarding
cognitive decline in persons younger than age 65 is very limited. Indeed, we could
find only one published epidemiologic study of cognitive decline in younger persons:
the Seattle Longitudinal Study (10). The
Seattle Longitudinal Study followed a series of community-based cohorts of individuals
enrolled in a health maintenance organization. Sample sizes for individual cohorts
were between 500 and 997. Participants were assessed according to a large number
tests of intelligence and cognitive capacity. The main findings were that individual
cognitive abilities did not change much before age 60, with the exception of verbal
fluency. Because of attrition, the Seattle Longitudinal Study did not have sufficient
sample sizes to detect small cognitive declines in younger age groups. Furthermore,
very few individual participants were followed for spans of more than 5 years. The
major correlate of cognitive decline is increasing age (10-14). Higher educational
level (14) and higher functioning (13) are associated with less cognitive decline.
Being female or encountering stressful life events is not associated with cognitive
decline (II,13). Risk factors for dementia include age, prior cognitive impairment,
stroke, high blood pressure, heart disease, diabetes mellitus, alcohol consumption,
and depression (15-28). The use of nicotine via smoking has also been associated
with a lower risk for dementia, although this finding is controversial (29). Being
female has not been associated with the incidence of dementia (15, 17). Two recent
studies (30, 31) have reported that lesser educational attainment is a risk factor
for dementia. However, this finding has not been supported universally (17, 32,
33). The relation
between cognitive functioning or cognitive decline and use of cannabis (marijuana)
has received limited attention in epidemiologic studies. Two cognitive effects
of cannabis must be distinguished: acute effects, those associated with intoxication,
and residual effects, which persist after the drug has left the central nervous
system (34). The latter effects might be short term or long term. Cross-sectional
studies, either experimentally administering cannabis or comparing users with
nonusers, support the existence of short term residual effects of cannabis use
on attention, ability to perform psychomotor tasks, and short term memory (34,
35). These effects are more severe in women (36) and in heavy users of cannabis
as compared with light users (37). To
our knowledge, no study with published results has investigated the long term
effects of cannabis use on cognition in an epidemiologic sample. According to
Pope et al. (34), study designs best suited to addressing this issue are naturalistic
comparisons, in large epidemiologic samples, of heavy users, light users, and
nonusers of cannabis. These studies must also account for the concurrent use of
alcohol and other drugs, both illicit and legal (e.g., nicotine). In Addition
such studies must adjust for other factors known to influence cognition over time,
such as age and education, and must investigate possible interactions between
the cognitive effects of cannabis use and gender (being female). We
recently reported findings from a 13-year follow-up of 1,488 persons of all ages
who had participated in the Baltimore, Maryland, portion of the Epidemiologic
Catchment Area study (38). The Mini-Mental State Examination (MMSE) (39), a widely
used quantitative measure of cognition, was administered to participants during
wave 1 (1981) and during two follow-up waves in 1982 and 1993-1996. The design
of the study allowed us to examine cognitive decline between waves 2 and 3 in
a large epidemiologic sample. We found that cognitive decline occurred in all
age groups. Age, education, and minority status were all significantly associated
with greater cognitive decline. In
this follow-up paper, we focus our investigation on persons under age 65 years.
To our knowledge, this is the first population study that has investigated cognitive
decline in this age group, in which the prevalence of dementia is very low. This
permits better study of cognitive decline as a phenomenon distinct from dementia,
as well as its associated risk factors. We had two goals: 1) to further delineate
the epidemiology of age-specific cognitive decline in persons under 65 and 2)
to investigate any long term association between cognitive decline and use of
cannabis using a design similar to the one proposed by Pope et al. (34). MATERIALS
AND METHODS Baltimore
Epidemiologic Catchment Area follow-up The
Epidemiologic Catchment Area program has been described in detail elsewhere (40,
41). The Baltimore arm of this five-site study first entered the field in 1981,
when the first wave of in-person assessments was completed. A second wave of assessment
(including wave 2 administration of the MMSE) was conducted 1 year later, in 1982.
The Baltimore Epidemiologic Catchment Area target population consisted of the
adult household residents of eastern Baltimore City, an area with 175,211 inhabitants.
During wave 1, 4,238 individuals were designated for interview by probability
sampling methods, and 3,481 (82 percent) completed interviews. Of these persons,
2,695 completed interviews during wave 2. In
1993, all 3,481 initial participants were targeted for tracing and interviewing.
A total of 848 participants were found to have died; the remaining 2,633 were
presumed to be alive, but 415 of them could not be successfully traced. Of the
2,218 persons located, 298 refused to participate, and 1,92O completed interviews.
Of these, 1,488 had completed the MMSE during all three waves, approximately 11.5
years after wave 2. All study participants signed informed consent statements
approved by the Institutional Review Board of the Johns Hopkins University School
of Hygiene and Public Health. Participants In
these analyses, we included only those participants who were under age 65 at wave
1 and who completed the MMSE during all three study waves (n = 1,318). Measurement
of cognitive decline. For
each participant, an MMSE score difference was calculated by subtracting the wave
3 (1993-1996) MMSE score from the wave 2 (1982) MMSE score, The mean time interval
between the points at which these MMSEs were administered was 11.6 years (standard
error 0.01 years). The median interval was 11.5 years, the 25th percentile was
11.3 years, and the 75th percentile was 11.9 years. Change in MMSE score between
waves 2 and 3 Has the primary dependent variable in the analyses. Classification
of participants according to use of cannabis. Participants were separated into
five groups based on their self-reported drug use during all three waves of the
study. Group 1 ( nonusers) were those who reported in all three waves that they
had never used cannabis in any form (n = 806 (61 percent)). Group 2 (light users)
were participants who had used cannabis but had never used it daily or more often
for over 2 weeks (n = 235 (18 percent)). Group 3 were light users who reported
use of any other illicit substance in any study wave (n = 131 (10 percent)). Group
4 (heavy-users) reported during at least one study wave that they had used cannabis
daily or more often for over 2 weeks (n = 137 (10 percent)). Group 5 were heavy
users of cannabis who reported use of other illicit drugs as well (n = 8 (1 percent)).
Information on cannabis use was missing for one participant. Classification
of participants according to use of alcohol or tobacco. On
the basis of the highest alcohol intake reported for the past month during any
of the three study waves, participants were placed into three groups: never drinkers
(n = 67 (5 percent), light-to- moderate drinkers (n = 778 (59 percent)), and heavy
drinkers, defined as those who had had more than four drinks on any one day during
the past month (n = 473 (36 percent)). With respect to smoking, three groups were
defined on the basis of self-report during any of the three waves: never smokers
(n = 347 (26 percent)): occasional smokers (n = 573 (44 percent)); heavy smokers,
defined as those who smoked 20-39 cigarettes per day (or the equivalent in cigars
or pipefuls of tobacco (n = 310 (24 percent)) and very heavy smokers, those who
smoked two or more packs of cigarettes per day (or the equivalent (n = 85 (6 percent)).
Information on smoking was missing for three participants. Other
variables associated with cognitive decline used as covariates. Information
on other variables associated with cognitive decline was recorded at wave 1. Gender
was indicated as male or female. Age was grouped as follows: 18-30, 31-40, 41-50,
51-60, and 61-64 years. Minority status was indicated as African-American or Hispanic
versus other ethnicity (non-Hispanic white). Five educational subgroups were developed:
0-8 years, 9-11 years, 12 years or General Equivalency Diploma, 13-15 years, and
16 or more years, in conformance with common educational landmarks (grade school,
some high school, completed high school or the equivalent, some college, and completed
college). It is possible that some study participants, especially those in younger
age groups at wave 1, completed their education after wave 1 and were thus misclassified. Analyses Mean
MMSE score changes between waves 2 and 3 (with 95 percent confidence intervals)
are reported in the tables for the entire cohort and for subgroups by age. The
proportions of individuals who evidenced any increase, no change, a one-point
decline, a two-point decline, a three-point decline, or a four-point or greater
decline are also reported by age group. Mean change in MMSE score (with its 95
percent confidence interval) by level of cannabis use was estimated for men and
women separately. The relation between level of cannabis use and MMSE score change
between waves 2 and 3 was examined in a series of linear regression models with
MMSE score change as the dependent variable and cannabis use as the independent
variable, with or without inclusion of the other covariates. For both univariate
and multiple regression models, the association of cannabis use with change in
MMSE score is reported in the form of regression coefficients (with 95 percent
confidence intervals). Subgroups were entered into regression models individually
as "dummy" variables to allow direct comparisons of remission coefficients
using one of the subgroups as the reference category. To
validate the findings from the linear regression models, we also constructed a
series of proportional odds logit models (42) relating diseases or substance use
to MMSE score change. These were bivariate or multivariate analogs
to the linear models. The dependent variable was change in MMSE score,
grouped as follows: any increase, no change, a one-point decline, a two-point
decline, a three-point decline, or a four-point or greater decline. Findings from
these models were similar to those obtained from the linear models. For simplicity,
we report only findings from the linear models. RESULTS
Table 1 provides a description of the study cohort at wave 1 with regard to sociodemographic
variables. It also shows mean MMSE scores at each study wave. TABLE
1. Sociodemographic characteristics at the Baltimore Epidemiologic Catchment Area
study cohort at wave 1 (n = 1,318) and mean MMSE scores at waves 1-3
| Variable | Number | % |
| Age
(years) | | | | 18-30 | 545 | 41 |
| 31-40 | 319 | 24 |
| 41-50 | 179 | 14 |
| 51-60 | 185 | 14 |
| 61-64 | 90 | 7 |
| | | | | Gender | | |
| Male | 488 | 37 |
| Female | 830 | 63 |
| | | | | Race | | |
| Minority
(African-American or Hispanic) | 490 | 37 |
| Nonminority
(other) | 828 | 63 |
| | | | | Education
(years) | | | | 0-8 | 161 | 12 |
| 9-11 | 280 | 21 |
| 12/GED | 541 | 41 |
| 13-15 | 211 | 16 |
| 16
or more | 125 | 10 |
| | | | | Mean
MMSE score | | | | Wave
1(1981) | 28.65
(1.9 standard deviation) | | | Wave
2 (1982) | 28.65
(1.81 standard deviation) | | | Wave
3(1993-1996) | 27.46
(2.23 standard deviation) | | Cognitive
decline between waves 2 and 3
Table 2 shows the mean change in MMSE score between waves 2 and 3 for every age
group. It also shows the proportions of participants in each age group with specific
changes in MMSE score, as described above. Persons in all age groups had mean
declines greater than zero, with two thirds declining in score by at least one
point. The mean decline and the proportion of persons with declining scores increased
steadily with age, as expected. It is noteworthy that in every age group there
was a notable proportion of participants whose score declined three points or
more-- a change of a magnitude that merits clinical attention (43, 44). These
estimated declines must be considered in the context of MMSE measurement error,
the MMSE ceiling effect, and normal variation in MMSE scores over time (see Discussion).
TABLE
2. Mean change in Mini-Mental State Examination (MMSE) score from wave 2 (1982)
to wave 3 (1993-1996) and proportions of participants evidencing specific MMSE
score changes, by age group, Baltimore Epidemiologic Catchment Aiea study follow-up
| Age
group (years) | Change
in MMSE score | | | Mean
change | 95%
confidence interval | | 18-30
(n=545) | -0.98 | -0.83
to -1.13 | | 31-40
(n=319) | -1.08 | -0.89
to -1.27 | | 41-50
(n=179) | -1.25 | -0.92
to -1.58 | | 51-60
(n=185) | -1.52 | -1.20
to -1.84 | | 61-64
(n=90) | -2.12 | -1.52
to -2.72 | | All
ages (n=1318) | -1.20 | -1.10
to -1.30 | (EDITORIAL
NOTE: Only the first part of TABLE 2 is included to save space.)
Association
between cannabis use and score decline
Table 3 displays estimated mean changes in MMSE score according to level of cannabis
use for men and women separately. Women who were nonusers of cannabis had scores
that declined more than those of men who were nonusers. However, within male-female
groups, there were no evident differences in score decline by cannabis use for
either men or women. TABLE
3. Mean change in Mini-Mental State Examination (MMSE) score between wave 2 (1982)
end wave 3 (1993-1996) in men and women, by level of cannabis use, Baltimore Epidemiologic
Catchment Area study follow-up
| Gender
and level of cannabis use | Number | Mean
score change in MMSE | 95%
confidence interval | | Men | | | |
| Nonusers | 251 | -1.00 | -0.73
to -1.27 | | Light
users | 104 | -1.03 | -0.67
to -1.39 | | Light
users & use of drugs | 47 | -1.06 | -0.57
to -1.55 | | Heavy
users | 82 | -0.84 | -0.46
to -1.22 | | Heavy
users & use of drugs | 3 | -0.33 | +5.93
to -6.59 | | | | | |
| Women | | | |
| Nonusers | 555 | -1.46 | -1.29
to -1.63 | | Light
users | 131 | -1.04 | -0.71
to -1.37 | | Light
users & use of drugs | 83 | -1.07 | -0.77
to -1.37 | | Heavy
users | 55 | -1.15 | -0.47
to -1.83 | | Heavy
users & use of drugs | 8 | -0.60 | +3.09
to -4.29 | Table
4 displays results from the linear regression models with MMSE change between
waves 2 and 3 used as the dependent variable. The numbers shown in the table are
regression coefficients estimating the relative change in MMSE score for a given
group of cannabis users relative to nonusers. Model 1 included only cannabis use
as the covariate. Model 2 included cannabis use and use of alcohol and tobacco.
Model 3 included cannabis use plus age, gender, education, minority status, alcohol
use, and tobacco use. Model 4 included cannabis use plus all of the variables
from models 2 and 3. Both light and heavy users of cannabis evidenced less cognitive
decline than nonusers, although this finding was not statistically significant
at the conventional level of p < 0.05 (model 1). After adjustment for the other
variables in models 2-4, there was no association between cannabis use and cognitive
decline. TABLE
4. Regression coefficients indicating relative differences in Mini-Mental State
Examination (MMSE) score change between wave 2 (1982) and wave 3 (1993-1996),
by level of cannabis use, in four regression models, Baltimore Epidemiologic Catchment
Area study follow-up
| Level
of cannabis use | Model
1 (cannabis use) | | | Regression
coefficient | Standard
error | | Nonusers | | |
| Light
users | 0.28* | 0.15 |
| Light
users & use of drugs | 0.25 | 0.19 |
| Heavy
users | 0.35* | 0.18 |
| Heavy
users & use of drugs | 0.81 | 0.71 |
*
p < 0.10 (EDITORIAL
NOTE: Models 2, 3 and 4 were not included in this table, see note at end of this
article) DISCUSSION
Cognitive decline is an age-related phenomenon that affects persons of all ages,
including those under age 30 years. It becomes more pronounced with increasing
age and is most evident in persons over age 59. A significant proportion (>15
percent) of persons in all population age groups evidence declines that approach
clinical significance. We offer two interpretations of this finding. One is that
cognitive decline might be an inevitable phenomenon of aging, perhaps modified
by genetic makeup, education, nutrition, disease, and environmental exposure.
Another is that the declines are the result of slowly progressive neurodegenerative
diseases (such as Alzheimer's disease) which might be lifelong in evolution but
do not lead to clinical symptoms until much later in life (8). While these two
lines of reasoning are not mutually exclusive, the relation between age and cognitive
decline across all age groups reported here lends greater support to the former.
To our knowledge, this was the first long term prospective study in the United
States that had a community sample large enough to investigate the relationship
between cannabis use and cognitive decline in persons under age 65 years. Other
studies have found short term residual effects of cannabis use on memory and cognition
(34, 35) that are more severe among women (36) and heavy users (37). However,
our data suggest that over the long term cannabis use is not associated with greater
declines in cognition among men, women, or heavy users. The study design we used
included several of the features proposed by Pope et al. (34) as critical to addressing
the long term effects of cannabis on cognition: naturalistic follow-up, a large
sample size, a population basis, comparison of light cannabis use with heavy use,
and the construction of models accounting for the effects of gender and use of
illicit drugs, alcohol, and tobacco. Therefore, these results would seem to provide
strong evidence of the absence of a long term residual effect of cannabis use
on cognition.
Notable limitations of this study include loss to follow-up and mortality. Cognitive
functioning at base-line was a predictor of both mortality and loss to follow-up
in the Epidemiologic Catchment Area study (40). Additionally, it is possible that
some cannabis users in the study may have used cannabis on the day the MMSE was
administered. Given the acute effects on cannabis on cognition (34), this would
have tended to reduce their MMSE score on that day. This may have adversely affected
accurate measurement of MMSE score changes over time.
Given that a lower level of cognitive functioning was associated with greater
cognitive decline, these estimates of decline may be underestimates. The assessment
of cannabis use was based on self-reports and was not confirmed with biologic
measures or controlled in an experimental setting. This may have led to underestimation
of cannabis use in persons with poor memory.
Another important limitation of the study is that the MMSE is not a very sensitive
measure of cognitive decline, even though it specifically tests memory and attention.
Thus, small or subtle effects of cannabis use on cognition or psychomotor speed
may have been missed. The MMSE is not intended for the purpose for which it was
used in this study, and it contains some items that assess neurologic function
as well as cognition. Additionally, MMSE item analysis was not performed in this
study. Given the MMSE's ease of use and widespread application, it was the most
practical instrument available for brief assessment of cognitive functioning at
the time the multisite Epidemiologic Catchment Area study was planned in the late
1970s. Also, given its limited sensitivity, declines noted on the MMSE are probably
under estimates of true declines.
Other limitations of the MMSE include the fact that small errors. such as forgetting
the present day's date, may be due to measurement error and not to true decline.
Measurement error on the MMSE might be caused by a variety of factors, including
the ambient environment in which the test is taken, the respondents mood
or emotional state, the respondents adequacy of sleep the night before,
the time of day at which the test is given, and other factors. However, such errors
ought to be random and not systematic (equally distributed between study waves),
so the effect on mean estimates should "average out across the population
and across waves of assessment.
MMSE scores in this study exhibited a ceiling effect, given that most participants
scored in the 27-30 range during wave 1. However, the ceiling effect was limited
to a minority of participants, those who scored 30 points at baseline, since most
declines were small. Finally,
the small but tangible beneficial "practice effect" of repeated testing
on MMSE score would tend to lead to higher, not lower, MMSE scores at follow-up.
We conclude that cognitive decline occurs across all age groups. with a significant
proportion of persons of all ages showing declines near clinically significant
levels after 12 years. Such decline is not associated with cannabis use in either
men or women. A better understanding of predictors of cognitive decline in persons
under age 65 years might lead to interventions designed to slow or arrest such
decline. This in turn might reduce the incidence of dementia at older ages. ACKNOWLEDGMENTS This
study was supported by grant 1R01-MH47447 from the National Institute of Mental
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1999 Johns Hopkins University School of Hygiene and Public Health EDITORIAL
NOTE: Models 2, 3 and 4 were not included in Table 4, partly because there is
no specific discussion of how these models were mathematically created. They begin
to compensate for other variables, however, it is not fair to lower the existing
differences between cannabis users and nonusers - by compensating for alcohol
and tobacco use. Since these variables accelerate cognitive decline, particularly
alcohol according to this article and many other sources, one questions whether
they should be used to diminish this important finding of lower cognitive decline
among marijuana smokers as compared to nonusers. Many people would argue that
the use of cannabis helps cut down on the use of these two legal drugs, and this
is part of its beneficial effect - rather than something that must be subtracted
away from it. Also,
the p < 0.10 probability for Light users and Heavy users
means that there is a greater than a ten to one chance that this observed difference
is real or an actual difference. This is less than the p < 0.05 probability
often used in research, which is greater than a twenty to one chance that this
observed difference actually reflects a similar real difference in the population
and thus, is statistically significant. Since
this is the first major study to be published in this area of marijuana research,
more studies are needed to see if this observed trend of lowered cognitive decline
continues in marijuana smoking populations in the future. At least the authors
report that there is absolutely no evidence that marijuana causes a long-term
decline in mental functioning - as the false assertions that marijuana did indeed
cause brain damage were popular in legislative circles in the 1980s and
were used to increase marijuana penalties |