Institute of Psychiatry, London
Academic Department of Psychiatry, Royal Free Hospital, London
Correspondence: Dr Jorge A. Cervilla, Director Médico, Complejo Hospitalario San Luis, Carretera de Burgos s/n, 34004 Palencia, Spain ; e-mail : dmedica{at}sanluis.org
Declaration of interest Supported by a grant from the Medical Research Council.
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ABSTRACT |
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Aims To identify early predictors of late-life cognitive outcome.
Method Cognitive function, premorbid IQ, and cardiovascular risk exposure were recorded on 1083 subjects on entry to a hypertension treatment trial in 1983-1984. We followed up this cohort 9-12 years later to assess cognitive function with the Mini-Mental State Examination (MMSE), to update exposure status, and to obtain genomic material. Multivariate analysis was used to identify independent baseline predictors of cognitive outcome 9-12 years later.
Results We followed up 387 subjects (58.6% of survivors). After adjusting for baseline cognition, poorer cognitive outcome was found to be independently associated with a family history of dementia, increasing age, less decline in systolic blood-pressure, lower premorbid IQ (rather than limited education), and abstinence from alcohol.
Conclusions Reduction in systolic blood pressure (among hypertensives) and moderate alcohol intake could protect against cognitive deterioration in late life.
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INTRODUCTION |
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This article presents our study of factors predicting change in cognitive function in a cohort of subjects with mild hypertension who volunteered for a hypertension treatment trial. Comprehensive measures of cognitive function, vascular risk factors and vasculopathy were obtained on entry to the trial. We revisited the cohort 9-12 years after baseline, which gave us a unique opportunity to study factors influencing cognitive change over a relatively long period, as survivors aged from their late sixties to late seventies or early eighties.
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METHOD |
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The designs of both the Medical Research Council treatment trial (MRC Working Party, 1992) and its cognitive sub-study are described in detail elsewhere (Bird et al, 1990 ; Prince et al, 1996a). The MRC trial compared mortality and morbidity among 4396 subjects randomised to receive beta-blocker, a thiazide diuretic or placebo. Inclusion criteria were age 65-74 years and systolic blood pressure 160-209 mmHg. Exclusion criteria were current anti-hypertensive medication, and serious cardiovascular, cerebrovascular or other intercurrent illnesses, including dementia. Subjects were recruited in 226 UK MRC General Practice Research Framework (MRC GPRF) practices after invitations had been sent to all registered patients within the eligible age range. In 1991 we reviewed a subsample of 1545 participants from 71 of the 226 practices in an attempt to ascertain all cases of dementia and Alzheimer's disease incident since the beginning of the MRC Trial (Prince et al, 1994). In 1994, 54 of these practices were still included in the MRC GPRF and were willing to take part in a further follow-up. They had recruited 1083 subjects into the MRC trial. The MRC GPRF had been notified of 431 deaths (39.8%), leaving 652 persons potentially available (60.2%) for the re-survey. Survivors were invited to attend the practice or to be interviewed in their own homes by an MRC GPRF research nurse, for an assessment of cognitive function, a blood test, and a risk factor interview.
Measures
Baseline (Time I) cognitive function
Upon entry to the MRC trial (1983-1985, henceforward referred to as Time 1)
cognitive tests had been administered to all subjects. Fluid intelligence was
measured using : (a) The Paired Associate Learning Test (PALT)
(Inglis, 1959) ; (b) the
Trial-Making Test (TMT) (Reltan,
1959) ; and (c) Raven's Progressive Matrices (RPM)
(Raven, 1940). The TMT and
PALT were repeated 1 month later. For these two tests, the mean of the scores
at entry and after 1 month was used, to minimise random error. Principal
component analysis with varimax rotation was used to extract a single factor
from the three Time 1 measures of cognitive function accounting for 51% of the
variance, with adequate loading values for the three Time 1 tests (RPM 0.79,
TMT 0.60 and PALT 0.64). Premorbid IQ (crystallised intelligence) was measured
at Time 1 using the National Adult Reading Test (NART)
(Nelson & O'Connell,
1978).
Time 2 cognitive outcome
In the 1994 follow-up, MRC GPRF research nurses in each of the
participating practices administered the Mini-Mental State Examination (MMSE)
(Folstein et al,
1975). The MMSE was transformed by : (a) reversing the scoring, so
that high scores indicated poor function (scores were subtracted from 31,
giving a range of 1-31) ; (b) log-transforming the positively skewed data
distribution ; (c) reversing the sign of (b), so that once again high scores
indicated good function. The score of the Time 2 cognitive outcome measure
ranges from 0 to 1.49, with a mean of 0.92 and a standard deviation of 0.32.
Our analytical strategy was to use this transformed MMSE as the cognitive
outcome measure, adjusting in all analyses for the principal component factor
derived from the Time 1 cognitive measures. Factors associated with cognitive
outcome while controlling for cognitive function 9-12 years previously are in
effect predicting cognitive change.
Independent variables (explanatory measures)
Risk factors for vascular disease.
Information was recorded at Time 1 regarding the following risk factors for
vascular disease : systolic and diastolic blood pressure, serum cholesterol,
body mass index and smoking behaviour at entry to the trial (ex-smokers were
not distinguished from those who had never smoked). Repeated measures of blood
pressure over the 5-year trial period allowed the decline in systolic blood
pressure from baseline to be calculated. Thus, we calculated the mean of
successive measures and subtracted it from the entry value.
Evidence of vascular disease.
Signs of arrhythmia or ischaemia on electrocardiogram (ECG).
Additional (retrospective) exposure data.
At Time 2 we administered an expanded risk factor questionnaire to both the
subject and an informant, collecting information on years of education, diet,
alcohol use, lifetime smoking (pack-years), social class, and current area of
residence. A loading for family history of dementia was derived by estimating
the family person-years' risk for the disease (the sum of the years lived by
parents and siblings after the age of 60) and then calculating the probability
(according to the Poisson distribution), given the number of years at risk,
that the same or fewer number of dementia cases are observed in the family
pedigree. The same approach was used to estimate the loading for a family
history of heart disease and stroke.
APOE genotyping and fibrinogen.
Blood samples were taken at Time 2. One blood sample was centrifuged
immediately upon collection and serum fibrinogen concentrations assayed. The
other was stored until DNA was extracted. Apolipoprotein-E (APOE) allelic
status was determined using a PCR assay as detailed elsewhere
(Prince et al,
2000).
Statistical analysis
In a univariate analysis we tested for crude associations between the
independent variables and cognitive outcome using, as appropriate, one-way
ANOVA or simple linear regression. In a general factorial MANOVA analysis
these crude associations were first adjusted for Time 1 cognitive function. We
then explored the relationship between education, social class, NART and
cognitive outcome, and finally identified a parsimonious model for cognitive
outcome. The effect size of associations was measured, estimated by
2. We also tested for all second-order interactions. We
repeated the multivariate analysis, excluding all cases of dementia.
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RESULTS |
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Cognitive outcome
The crude associations with cognitive outcome at Time 2 are summarised in
Table 2. After adjusting for
baseline cognitive function, poorer cognitive outcome at Time 2 was associated
with increasing age, less decline in systolic blood pressure over the trial
period, a greater loading for family history of dementia, never having smoked,
abstinence from alcohol before the age of 60 and over the past 3 months, lower
social class, lower education and lower NART score. We also found a
significant trend in the association between cognitive outcome and APOE group,
in that those with an APOE 2 allele had a better cognitive outcome than
did those with APOE
3/3 alleles who, in turn, did better than those with
any APOE
4 allele. There were near significant trends for associations
between poorer cognitive outcome and both arrhythmia, recorded on ECG at
baseline, and a higher loading for family history of heart disease. We found
no association between cognitive decline and ECG ischaemia, body mass index,
serum fibrinogen, serum cholesterol, diastolic or systolic blood pressure at
entry, use of non-steroidal anti-inflammatory drugs (NSAIDs), loading for
family history of stroke, alcohol consumption over the past 3 months, rural
residence, vegetarian diet and gender.
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We compared the independent effects of social class, education and NART scores on cognitive outcome. After adjusting for Time 1 cognitive function, NART predicts cognitive decline, independently of the effects of a higher number of years of education and social class. A higher number of years of education was not independently associated with cognitive outcome. Social class predicted cognitive outcome independently of education, but not after adjusting by NART.
The most parsimonious multivariate model accounted for 29% of the variance
(Table 3). Poorer cognitive
outcome, after adjusting for Time 1 cognitive function, was independently
associated with increasing loading for family history of dementia, older age
at entry, abstinence from alcohol prior to the age of 60 and less decline in
systolic blood pressure over the trial period. APOE 4 alleles did not
add any additional explanatory power to the model (F=1.28, P=0.258
for all cases ; F=0.3, P=0.86 excluding dementia cases) and did not
modify the effect of any of the independently associated factors. APOE was
therefore excluded from the final model. We finally applied the same
parsimonious model excluding those 41 cases that had a DSM-IV diagnosis of
dementia. The parameters changed very little, although the effect of decline
in systolic blood pressure fell just beyond the traditionally accepted values
of statistical significance (P=0.06).
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DISCUSSION |
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Study limitations
Our results need however to be interpreted with caution, as there are
limitations to our study. The cohort is based on the primary care network but
consists of mildly hypertensive trial volunteers, suggesting limits to
generalisability and potential selection bias. The response rate was only
58.6% of those cohort subjects who had survived until the follow-up survey,
reflecting their age and frailty, the 9-12 year time interval and the logistic
difficulties of tracing those who had moved far away from their original MRC
research practice. Response bias cannot be excluded, even though no particular
characteristics of subjects (other than their cognitive function) recorded at
entry to the MRC trial tended not to be associated with their response status
at follow-up.
Study advantages
The main strength of the study design is the complete ascertainment of
prospectively recorded exposure data, including smoking status, serum total
cholesterol and body mass index, and repeated measures of blood pressure level
and ECG recordings, made before the onset of dementia and significant
cognitive decline. Additionally, the long (9-12 years) follow-up period
provides us with a rare opportunity to explore long-term effects of potential
risk factors for failing cognition.
Age
We found, as expected, an association between older age at entry and lower
cognitive outcome, which has been repeatedly reported previously
(Prince et al,
1996b). Age may be understood as a proxy for an
accumulation of age-related impairments that may themselves be feasible
targets for intervention (Prince et
al, 1996a).
Education, social class and premorbid IQ
Although better education was associated with better cognitive outcome in
this study, its effect was weaker than, and not independent of, that of social
class. Similarly, lower social class was only associated with cognitive
decline before adjusting for the effect of premorbid crystallised IQ. Thus, of
these three strongly correlated variables, premorbid IQ was the best
independent predictor of cognitive outcome (2=0.26 ;
P=0.023), confounding or mediating the effects of education and
social class. Our findings replicate those of a previous report and give
further support to the brain reserve hypothesis
(Schmand et al,
1997).
Vascular factors
Several cardiovascular risk factors have been reported to predict cognitive
decline (Stewart, 1999).
Atrial fibrillation was associated with cognitive impairment in one
cross-sectional study (Kilander et
al, 1998) of a sample of men after adjusting for education,
age, occupation, stroke and other vascular factors. A longitudinal study
(Alewijn et al, 1997)
has also reported an association between atrial fibrillation and cognitive
impairment after adjusting for age, gender, education and vascular risk
factors, but it was only apparent in women, and weakly so, when stroke cases
were excluded. We found a univariate association between ECG-measured
arrhythmia and cognitive decline in this longitudinal study. However, no
independent association was found when arrhythmia was added to the
multivariate model adjusting for alcohol consumption and systolic blood
pressure decline, suggesting possible confounding in previous reports.
We found no association between baseline systolic or diastolic blood pressure and cognitive outcome, in accordance with previous findings on this cohort (Bird et al, 1990 ; Prince et al, 1996a). Interestingly, we did find an association between less decline in systolic blood pressure and poorer cognitive outcome. However, this should be interpreted cautiously. A survivor effect cannot be ruled out, as we had previously reported no effect of anti-hypertensive treatment on cognition, compared to placebo, despite large randomisation group effects on blood pressure levels (Prince et al, 1996b), after 5-year follow-up of the entire cognitive sub-study cohort. Further-more, blood pressure did not predict cognitive decline over the 54 initial months of this study (Prince et al, 1996a). Nevertheless, both the Framingham (Elias et al, 1993) and the Honolulu (Launer et al, 1995) studies have provided evidence of an association between higher mid-life systolic blood pressure levels and cognitive decline in late life. In the Framingham study this association was most apparent in those left untreated (Farmer et al, 1990). Our finding is also consistent with the notion that treating hypertension may provide a means for a modest preventive intervention (Stewart, 1999).
Non-steroidal anti-inflammatory drugs (NSAIDs)
We could not replicate our earlier finding of a protective effect for
NSAIDs against cognitive decline on the PALT over the first 5 years of the MRC
trial (Prince et al,
1998). Any beneficial effect of NSAIDs may not be sustained. The
effect of NSAIDs in cognitive function is unresolved, as other studies have
found NSAIDs not to be associated with cognitive function, or even to be a
risk factor for cognitive decline (Saag
et al, 1995).
Genetic/familial factors
Although APOE 4 is associated with dementia in this sample
(Prince et al, 2000),
in univariate analysis it was only weakly associated with cognitive outcome.
Neither did APOE modify the effect of any other variable in the final model.
This finding is comparable with those of most previous studies
(Feskens et al, 1994 ;
Small, 1998) as the
association between APOE and cognitive impairment or decline is certainly less
clear than is the case when studying Alzheimer's disease or dementia cases,
especially among older old populations
(Small, 1998). A loading for
family history of dementia did predict poorer cognitive outcome, even among
those free of dementia and after adjusting for the effect of APOE. Our results
support the continuum hypothesis (Brayne
& Calloway, 1988) and suggest a multi-factorial polygenic
model, with the summation of the small effects of multiple genes influencing
propensity for cognitive deterioration across a braod continuum of normal
and pathological age-related change.
Smoking and alcohol
We found a trend for smoking to protect against poorer cognitive outcome,
which was not borne out in multivariate analysis. The association between
smoking and lower cognitive outcome was found to be confounded by the Time 1
cognitive factor, alcohol use and, to a lesser extent, by premorbid IQ. Low to
moderate alcohol consumption may have a protective role in cognitive
impairment (Launer et al,
1996 ; Dufouil et al,
1997). We found that those who were abstinent before the age of 60
had poorer cognitive outcomes than did those who drank mildly or moderately.
However, it could also be argued that those subjects who drank more and
survived till this phase of the study could be a healthier group.
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CLINICAL IMPLICATIONS AND LIMITATIONS |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication July 26, 1999. Revision received October 29, 1999. Accepted for publication November 22, 1999.