Context Physical activity may help maintain cognitive function in older adults.
Objective To examine the relation of long-term regular physical activity, including
walking, to cognitive function.
Design Women reported participation in leisure-time physical activities on
biennial mailed questionnaires beginning in 1986. We assessed long-term activity
by averaging energy expenditures from questionnaires in 1986 through participants'
baseline cognitive assessments (1995 to 2001). We used linear regression to
estimate adjusted mean differences in baseline cognitive performance and cognitive
decline over 2 years, across levels of physical activity and walking.
Setting and Participants Nurses' Health Study, including 18 766 US women aged 70 to 81 years.
Main Outcome Measure Validated telephone assessments of cognition administered twice approximately
2 years apart (1995 to 2001 and 1997 to 2003), including tests of general
cognition, verbal memory, category fluency, and attention.
Results Higher levels of activity were associated with better cognitive performance.
On a global score combining results of all 6 tests, women in the second through
fifth quintiles of energy expenditure scored an average of 0.06, 0.06, 0.09,
and 0.10 standard units higher than women in the lowest quintile (P for trend <.001). Compared with women in the lowest physical activity
quintile, we found a 20% lower risk of cognitive impairment for women in the
highest quintile of activity. Among women performing the equivalent of walking
at an easy pace for at least 1.5 h/wk, mean global scores were 0.06 to 0.07
units higher compared with walking less than 40 min/wk (P≤.003). We also observed less cognitive decline among women who
were more active, especially those in the 2 highest quintiles of energy expenditure.
Women in the fourth and fifth quintiles had mean changes in global scores
that were 0.04 (95% confidence interval, 0.02-0.10) and 0.06 (95% confidence
interval, 0.02-0.11) standard units better than those in the lowest quintile.
Conclusion Long-term regular physical activity, including walking, is associated
with significantly better cognitive function and less cognitive decline in
older women.
The fastest growing age segment in the United States will soon be adults
aged 65 years and older,1 a group at high risk
for developing dementia. Efforts to reduce dementia may be most successful
at the earliest stages of disease development; subtle decrements in cognitive
function predict dementia many years later and may be considered a marker
of preclinical disease.2-5 Thus,
research on risk factors for diminished cognitive function in aging adults
is of critical public health importance.
Accumulating evidence from animal6-9 and
human studies,10-21 including
small-scale clinical trials,22 suggests that
physical activity may reduce the risk of poor cognition and early cognitive
decline. However, several issues have received limited consideration. Most
important, the intensity of activity required to preserve cognitive function
remains unclear. Walking is one of the most common23 and
among the most practical leisure-time activities practiced by older adults.
Yet only 1 study has prospectively explored the potential benefits of walking
on cognitive function, and in that study physical activity was assessed at
only 1 point in time.19 Thus, we examined physical
activity, including walking, and cognitive function in a large cohort of older
women.
The Nurses' Health Study began in 1976 when 121 700 female registered
nurses, aged 30 to 55 years and living in 11 US states, returned a mailed
questionnaire about their medical history and health-related behaviors.24 Since then, the women have completed questionnaires
every 2 years; detailed items on physical activity were added beginning in
1986. To date, we have maintained follow-up of more than 90% of the original
participants. This study was approved by the institutional review board of
Brigham and Women's Hospital (Boston, Mass). Women gave informed consent to
participate at the time of their cognitive assessment.
From 1995 to 2001, we invited participants aged 70 years and older with
no history of stroke to participate in a study of cognitive function. Of the
22 715 women who were eligible, we were unable to contact 1031 (4.5%).
Of those remaining, 7.7% refused to participate. After excluding women who
were missing data on educational attainment or physical activity, women with
Parkinson disease, and women unable to walk, our main analysis of physical
activity and baseline cognitive function was based on 18 766 women. Second
cognitive assessments were administered a mean of 1.8 years (SD, 0.4) after
baseline testing. Excluding those who died (n = 15), to date we have attempted
second assessments in 89% of participants in our baseline analysis. Of these,
99% completed a second assessment and 1.3% refused or were lost to follow-up.
Thus, analyses of change in cognition included 16 466 women.
Cognitive Function Assessment
All cognitive testing was administered using validated telephone interviews
conducted by trained nurses. In the initial interview, we administered only
the Telephone Interview for Cognitive Status (TICS)25 and
gradually added 5 more tests as participants' enthusiasm for cognitive testing
became clear. Thus, the sample size differs somewhat across the cognitive
tests, although participation rates remained identical for all tests, and
there was no relation between physical activity and the number of tests administered.
The TICS (n = 18 766) is modeled on the Mini-Mental State Examination
(MMSE). Brandt et al25 reported a strong linear
correlation between scores on the TICS and MMSE (Pearson correlation, 0.94),
and high test-retest reliability. A test of delayed recall of the 10-word
list from the TICS (n = 16 372) was 1 of the 5 tests added to our battery.
We also added the East Boston Memory Test (EBMT)26,27 to
assess immediate (n = 18 055) and delayed (n = 18 029) paragraph
recall. We administered a test of category fluency in which participants were
asked to name as many animals as they could in 1 minute28 (n
= 18 047). Finally, participants were administered the Digit Span Backwards
test29 (n = 16 382), which measures working
memory and attention.
To summarize the overall association of physical activity with cognitive
performance, for women given all 6 tests (n = 16 353) we constructed
a global score by averaging the z scores from all
tests. To assess overall verbal memory, a strong predictor of developing Alzheimer
disease,30 we combined the immediate and delayed
recalls of the EBMT and the TICS 10-word list, for women given all 4 tests
(n = 16 370), by averaging the z scores from
these tests. Such composite scores are regularly used in published research
on cognition5,31 because they
integrate information from a variety of sources and thus provide a more stable
representation of cognitive function than a single test.
We extensively tested the reliability and validity of our telephone
procedure for assessing cognition in high-functioning, educated women. We
found high reliability of test performance among 35 women given the TICS twice,
31 days apart (test-retest correlation, 0.7, P<.001).
In a validation study we conducted among 61 nuns from the Rush Religious Orders
Study5 of similar age and educational status
to our participants, global scores from our brief telephone-administered cognitive
assessment correlated highly with global scores from in-person interviews
(r = 0.8).
Physical Activity Assessment
Beginning in 1986, and again in 1988, 1992, and each subsequent biennial
questionnaire, we requested detailed information on leisure-time physical
activity. Women were asked to estimate the average amount of time per week
during the past year spent on the following activities: running (≤10 min/mile);
jogging (>10 min/mile); walking or hiking outdoors; racquet sports; lap swimming;
bicycling; aerobic dance or use of exercise machines; other vigorous activities
(eg, lawn mowing); and low-intensity exercise (eg, yoga, stretching, toning).
Participants also indicated their usual outdoor walking pace: easy (>30 min/mile),
normal (21-30 min/mile), brisk (16-20 min/mile), or very brisk (≤15 min/mile),
and the number of flights of stairs climbed daily. We assigned each activity
a metabolic equivalent value (MET) according to accepted standards,32 where 1 MET is proportional to the energy expended
while sitting quietly. MET values were 12 for running; 8 for stair-climbing;
7 for jogging, racquet sports, lap-swimming and bicycling; 6 for aerobic dance,
use of exercise machines, and other vigorous activities; and 4 for yoga, stretching,
or toning. MET values for walking varied by reported pace, from 2.5 METs for
easy pace to 4.5 METs for very brisk pace. For each activity, we estimated
the energy expended in MET-hours/wk, by multiplying its MET value by the time
spent performing it.
In validation studies among women in the Nurses' Health Study II (a
similar cohort of nurses), participants' responses, 1 year apart, to these
questions on activity were reasonably correlated (r =
0.59), given the expected true changes that might occur over a 1-year period.33 Moreover, physical activity recalled for the previous
year correlated strongly with past-week recalls of physical activity (r = 0.79) and with physical activity logged in diaries
during the year (r = 0.62).
Physical Activity. To assess long-term physical
activity and to reduce the impact of any recent changes in activity due to
health status (ie, "reverse causation" bias), our main analyses were based
on the average of energy expenditures from the 1986 questionnaire through
the questionnaire immediately preceding the baseline cognitive assessment.
Thus, the averaged expenditures were calculated from a mean of 5 reports per
woman over 8 to 15 years. The last reports of activity occurred, on average,
1.8 years prior to the baseline cognitive assessments. For analysis, we divided
the averaged energy expenditures into quintiles.
Walking. In examining walking, we excluded
women who reported participation in vigorous activities (6-MET intensity or
greater), to disentangle the effects of walking from those of walking accompanied
by more vigorous activity, leaving 7982 women for baseline analyses. Analyses
of walking are based on average energy expended on walking from 1986 through
the questionnaire immediately preceding the baseline cognitive assessment.
Due to the smaller sample size in this analysis and the narrower distribution
of energy expenditure in this group, we divided women into quartiles of walking
expenditures rather than quintiles.
Statistical Models. We used multiple linear
regression to compare mean baseline cognitive function and mean decline in
cognitive performance over 2 years across categories of average physical activity
and walking. We constructed 2 sets of models. In the first, we adjusted for
factors that may confound the association between physical activity and cognition,
including age at cognitive assessment, education (registered nurse degree,
bachelor's degree, advanced graduate degree), husband's education (high school
diploma or less, college degree, advanced graduate degree; an additional measure
of socioeconomic status), alcohol consumption (measured using a food frequency
questionnaire as none, up to 1 drink/week, 2-6 drinks/week, ≥1 drink/day),
smoking (current, past, never), aspirin use (nonuser, 1 time/month to 2 times/week,
≥3 days/week), ibuprofen use (nonuser, current user), vitamin E supplementation
(yes, no), antidepressant use (yes, no), poor mental health on the mental
health scale of the Short Form-36 (SF-36), history of osteoarthritis, history
of emphysema or chronic bronchitis, low vitality on the energy-fatigue scale
of the SF-36, problems with balance, moderate to severe bodily pain, and health
limitations in walking a block. Adjustments for additional factors such as
use of postmenopausal hormone therapy and apolipoprotein E ∊4 did not
alter the results and were not included in the final model.
In a second set of models, we added vascular factors that might be either
confounders or intermediates in the causal pathway between physical activity
and cognitive function, including high blood pressure, elevated cholesterol
level, type 2 diabetes, coronary heart disease, coronary artery bypass graft
surgery, congestive heart failure, transient ischemic attack, and carotid
endarterectomy (women with stroke had already been excluded from participation
in the baseline cognitive testing). Additionally, for our analyses of walking,
we included terms for stair-climbing and other low-intensity activities. All
information on potential confounding and intermediate variables was identified
via the biennial questionnaires and women's status for each variable was considered
through the questionnaire immediately preceding the cognitive assessment.
Variables assessed multiple times were averaged for the model.
In analyses of cognitive decline, we adjusted for the covariates listed
above, again with the status for each variable defined as of the questionnaire
preceding the baseline cognitive assessment, as well as baseline cognitive
test score.
To help interpret the mean differences in scores that we observed, we
provide here the mean differences in cognitive scores that we found between
different age groups, estimated from our multiple regression models, allowing
a contrast of mean differences across age with mean differences across physical
activity categories. For example, in our models, we found a mean difference
of 0.08 standard units on the global score associated with each 2-year increment
in age.
In additional analyses to help interpret clinical significance, we focused
on participants in the lowest 10% of the distribution of cognitive performance.
Such a population-based 10% cut-off point is a sensitive and specific marker
of cognitive impairment34 and has been used
in other studies.35-37 We
computed adjusted prevalence odds ratios (ORs) of cognitive impairment using
multiple logistic regression models including the potential confounding variables
described above. We conducted analyses using SAS version 8.2 (SAS Institute
Inc, Cary, NC) and P<.05 as the level of significance.
A wide range of energy was expended on leisure-time activity (Table 1). Women were of similar age across
quintiles of physical activity. Compared with women in lower quintiles of
activity, women in higher quintiles were less likely to smoke and more likely
to consume moderate levels of alcohol. As expected, women in higher quintiles
were less likely to report problems with balance, health limitations in walking,
and high levels of fatigue. Finally, as anticipated, cardiovascular disease,
pulmonary disease, and diabetes were all less prevalent among more active
women.
After adjusting for potential confounding factors, we found statistically
significant trends of increasingly higher mean scores on all the cognitive
measures with higher levels of long-term physical activity (Table 2). Further adjustment for vascular factors had little impact
on these findings (data available from authors on request). Although the absolute
differences in score may appear small, the mean differences we found across
quintiles of physical activity were equivalent to the mean differences we
observed for women 2 to 3 years apart in age. In addition, we found a significant
association between physical activity and the odds of cognitive impairment.
On the global score, women in the highest quintile of activity had 20% lower
odds of cognitive impairment at baseline than women in the lowest quintile
(OR, 0.80, 95% confidence interval [CI], 0.67-0.95).
We believe it is unlikely that women's health influenced their activity
rather than the reverse, since we considered energy expenditures beginning
when women were largely in their early 60s and ending 2 years prior to cognitive
testing. Nonetheless, we conducted several alternative analyses to further
address this issue. We examined physical activity reported at mid-life by
using questionnaire reports from only women aged 60 to 62 years between 1986
and 1988 (n = 7907), and these results were similar (Table 3). In addition, in analyses excluding women reporting extremes
of activity (eg, the least active quintile, the most active quintile) and
in analyses excluding women with disabling symptoms and conditions (eg, pulmonary
and cardiovascular disease, balance problems, and any reported health limitations
in walking several blocks), the positive association between higher levels
of physical activity and cognitive function persisted.
Among women who had not participated in vigorous activity, the quartiles
of average energy expended on walking were less than 1.9 MET-hours/wk, 1.9
to 4.2, 4.3 to 8.5, and greater than 8.5. These cut points are approximately
equivalent to walking at a pace of 21-30 min/mile for less than 38 min/wk,
38 minutes to 1.4 hours, 1.5 to 2.8 hours, and more than 2.8 h/wk. We found
significantly higher cognitive scores for women in the third and fourth quartiles
of walking on all our cognitive measures (Table 4). These findings are consistent with those for overall physical
activity, which indicated significant associations between better cognitive
performance and 5.2 or more MET-hours/wk of energy expenditure. In our data,
differences in cognitive scores associated with walking at an easy pace for
at least 1.5 h/wk (vs <38 min/wk) were equivalent to those we observed
for women approximately 1.5 years apart in age.
We found that regular physical activity was associated with less cognitive
decline (Table 5). On almost all
the cognitive measures higher levels of activity were associated with less
cognitive decline, and aside from category fluency, these trends were significant
at the P<.001 level. Results were generally consistent
in analyses in which we did not adjust for baseline cognitive performance
and in analyses in which we excluded women who performed in the bottom 10%
of a given cognitive measure at baseline (data available on request).
In this large, prospective study of older women, higher levels of long-term
regular physical activity were strongly associated with higher levels of cognitive
function and less cognitive decline. Specifically, the apparent cognitive
benefits of greater physical activity were similar in extent to being about
3 years younger in age and were associated with a 20% lower risk of cognitive
impairment. The association was not restricted to women engaging in vigorous
activities: walking the equivalent of at least 1.5 hours per week at a 21-30
min/mile pace was also associated with better cognitive performance.
Several limitations to our study should be considered. In this observational
study, results may be confounded by unmeasured factors. However, our homogeneous
population of nurses minimizes the possibility that more active women had
substantially better health care or health knowledge than less active women.
Additionally, findings were robust to adjustments for numerous potential confounders,
including a variety of health-related factors, and the apparent association
between physical activity and cognition was consistent in analyses including
only the healthiest participants with no reports of physically disabling conditions
and symptoms.
Second, our findings could reflect "reverse causation," such that preexisting
cognitive impairment caused a reduction in physical activity. Averaging reported
physical activity levels over many years likely reduces this possibility;
moreover, after imposing a minimum 9-year lag between the report of physical
activity and the assessment of cognitive function, we still found a positive
association between activity and cognition.
Our short follow-up period for measuring change in cognitive function
is also a limitation. However, we initially collected information on physical
activity 8 to 15 years prior to the baseline cognitive testing, and we were
able to assess cognition among a large proportion of the women who provided
data on their activity in 1986. Furthermore, our longitudinal results for
cognitive decline over 2 years were entirely consistent with our findings
for baseline cognition, with higher levels of activity strongly associated
with less decline.
Finally, we did not assess development of dementia in our cohort. However,
subtle decrements in cognition are a key predictor of dementia development2-4 and may be considered
a preclinical marker of early stages of dementia onset. In the Framingham
study,2 performance on tests of verbal memory
predicted Alzheimer disease up to 22 years later: there was a 60% increase
in risk for each standard deviation difference in baseline performance (relative
risk, 1.57; 95% CI, 1.31-1.87). Over 6 years of follow-up in the Kungsholmen
Project,3 mean MMSE scores were 6.84 points
lower at baseline for those who subsequently developed Alzheimer disease than
those who did not, and those with poor performance on delayed verbal recall
were 61% more likely to develop Alzheimer disease. Over 5 years of follow-up
in the MoVIES study,4 each standard deviation
difference in decline in verbal memory was associated with a 2.5-fold higher
rate of Alzheimer disease development. To evaluate this relation in our study,
we administered the Dementia Questionnaire, a validated telephone informant
interview for diagnosing dementia,38 to 88
of our participants. An experienced neurologist from the Massachusetts Alzheimer
Disease Research Center reviewed the findings, blinded to participants' cognitive
testing. Over 3 years of follow-up, dementia diagnosis was nearly 8 times
as likely among women who scored poorly on the TICS (OR, 7.6; 95% CI, 2.2-25),
with a statistically significant, 11.6-fold increase for women performing
poorly (defined as the lowest 10% of the distribution) on the verbal memory
score.
Several mechanisms may potentially explain the relation between physical
activity and cognitive function. Physical activity likely sustains the brain's
vascular health by lowering blood pressure, improving lipoprotein profiles,
promoting endothelial nitric oxide production,39 and
ensuring adequate cerebral perfusion.40,41 Similarly,
emerging evidence of a relation between insulin and amyloid β42,43 (amyloid β plaques are a hallmark
pathologic feature of Alzheimer disease) suggest that the benefits of aerobic
activity on insulin resistance and glucose intolerance44-46 may
be another mechanism by which physical activity could prevent or delay cognitive
decline. Physical activity may also directly affect the brain, potentially
preserving neuronal structure and promoting the expansion of neural fibers,
synapses, and capillaries.41,47 In
general, small clinical trials support cognitive benefits of physical activity,22 yet due to practical limitations, it is difficult
for trials to assess a wide variety of activities or long-term activity.
Large observational epidemiologic studies also suggest apparent benefits
of physical activity on cognitive function. In particular, 4 large-scale prospective
studies on this relation all have reported that greater activity is related
to less cognitive decline.13,16,17,19 The
Study of Osteoporotic Fractures (SOF) is the only large-scale study that has
examined walking in relation to cognitive decline.19 Among
5925 women, aged 65 years and older, those who reported walking greater distances
and those who were more physically active overall had smaller declines on
the modified MMSE (P<.001 for both). Specifically,
women in the highest quartile of walking distance (median, 175 blocks/wk)
were 35% less likely (OR, 0.65; 95% CI, 0.54-0.78) than women in the lowest
quartile (median, 7 blocks/wk) to experience cognitive decline over 6 to 8
years. These results were adjusted for numerous health indicators, including
chronic diseases and functional limitations. Yet it remains possible that
reverse causation explains some of the effects observed by all these studies.
For example, in the SOF study, physical activity was first assessed at baseline,
when half of the women were at least 70 years old and 43% had at least 1 confirmed
health condition (eg, hypertension, diabetes, myocardial infarction). Thus,
our findings serve as an important complement to the previous studies because
our long-term follow-up and large sample size permit more detailed consideration
of potential bias from a variety of health-related factors; for example, we
examined activity reported at younger ages and considered numerous health-related
exclusions.
In summary, in our study, as well as in other epidemiologic investigations,
higher levels of physical activity, including walking, are associated with
better cognitive function and less cognitive decline. Importantly, our data
suggest that the apparent differences in cognition we observed between women
with higher vs lower levels of activity were similar in magnitude to the differences
in cognition we found among women 2 to 3 years apart in age.
1.US Bureau of the Census. 65+ in the United States. In: Current Population Reports, Special Studies. Washington, DC: US Government Printing Office; 1996:23-190.
2.Linn RT, Wolf PA, Bachman DL.
et al. The "preclinical phase" of probable Alzheimer's disease: a 13-year
prospective study of the Framingham cohort.
Arch Neurol.1995;52:485-490.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7733843&dopt=Abstract
Google Scholar 3.Small BJ, Fratiglioni L, Viitanen M, Winblad B, Bäckman L. The course of cognitive impairment in preclinical Alzheimer disease:
3- and 6-year follow-up of a population-based sample.
Arch Neurol.2000;57:839-844.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10867781&dopt=Abstract
Google Scholar 4.Kawas CH, Corrada MM, Brookmeyer R.
et al. Visual memory predicts Alzheimer's disease more than a decade before
diagnosis.
Neurology.2003;60:1089-1093.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12682311&dopt=Abstract
Google Scholar 5.Bennett DA, Wilson RS, Schneider JA.
et al. Natural history of mild cognitive impairment in older persons.
Neurology.2002;59:198-205.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12136057&dopt=Abstract
Google Scholar 6.Black JE, Isaacs KR, Anderson BJ, Alcantara AA, Greenough WT. Learning causes synaptogenesis, whereas motor activity causes angiogenesis,
in cerebellar cortex of adult rats.
Proc Natl Acad Sci U S A.1990;87:5568-5572.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=1695380&dopt=Abstract
Google Scholar 7.Neeper SA, Gómez-Padilla F, Choi J, Cotman C. Exercise and brain neurotrophins.
Nature.1995;373:109.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7816089&dopt=Abstract
Google Scholar 8.Gómez-Pinilla F, Dao L, So V. Physical exercise induces FGF-2 and its mRNA in the hippocampus.
Brain Res.1997;764:1-8.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9295187&dopt=Abstract
Google Scholar 9.van Praag H, Christie BR, Sejnowski TJ, Gage FH. Running enhances neurogenesis, learning, and long-term potentiation
in mice.
Proc Natl Acad Sci U S A.1999;96:13427-13431.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10557337&dopt=Abstract
Google Scholar 10.Clarkson-Smith L, Hartley AA. Structural equation models of relationships between exercise and cognitive
abilities.
Psychol Aging.1990;5:437-446.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2242248&dopt=Abstract
Google Scholar 11.Berkman LF, Seeman TE, Albert M.
et al. High, usual and impaired functioning in community-dwelling older men
and women: findings from the MacArthur Foundation Research Network on Successful
Aging.
J Clin Epidemiol.1993;46:1129-1140.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8410098&dopt=Abstract
Google Scholar 12.Hultsch DF, Hammer M, Small BJ. Age differences in cognitive performance in later life: relationships
to self-reported health and activity life style.
J Gerontol Psychol Sci.1993;48:P1-P11.Google Scholar 13.Albert MS, Jones K, Savage CR.
et al. Predictors of cognitive change in older persons: MacArthur studies
of successful aging.
Psychol Aging.1995;10:578-589.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8749585&dopt=Abstract
Google Scholar 14.Emery CF, Huppert FA, Schein RL. Relationships among age, exercise, health, and cognitive function in
a British sample.
Gerontologist.1995;35:378-385.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7622090&dopt=Abstract
Google Scholar 15.Carmelli D, Swan GE, LaRue A, Eslinger PJ. Correlates of change in cognitive function in survivors from the Western
Collaborative Group Study.
Neuroepidemiology.1997;16:285-295.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9430128&dopt=Abstract
Google Scholar 16.Ho SC, Woo J, Sham A, Chan SG, Yu ALM. A 3-year follow-up study of social, lifestyle and health predictors
of cognitive impairment in a Chinese older cohort.
Int J Epidemiol.2001;30:1389-1396.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11821352&dopt=Abstract
Google Scholar 17.Laurin D, Verreault R, Lindsay J, MacPherson K, Rockwood K. Physical activity and risk of cognitive impairment and dementia in
elderly persons.
Arch Neurol.2001;58:498-504.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11255456&dopt=Abstract
Google Scholar 18.Schuit AJ, Feskens EJ, Launer LJ, Kromhout D. Physical activity and cognitive decline, the role of the apolipoprotein
e4 allele.
Med Sci Sport Exerc.2001;33:772-777.Google Scholar 19.Yaffe K, Barnes D, Nevitt M, Lui L-Y, Covinsky K. A prospective study of physical activity and cognitive decline in elderly
women: women who walk.
Arch Internal Med.2001;161:1703-1708.Google Scholar 20.Williams P, Lord SR. Effects of group exercise on cognitive functioning and mood in older
women.
Aust N Z J Public Health.1997;21:45-52.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9141729&dopt=Abstract
Google Scholar 21.Kramer AF, Hahn S, Cohen NJ.
et al. Ageing, fitness and neurocognitive function.
Nature.1999;400:418-419.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10440369&dopt=Abstract
Google Scholar 22.Colcombe S, Kramer AF. Fitness effects on the cognitive function of older adults: a meta-analytic
study.
Psychol Sci.2003;14:125-130.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12661673&dopt=Abstract
Google Scholar 23.US Department of Health and Human Services. Chapter 5: Patterns and trends in physical activity. In: Physical Activity and Health: A Report of the
Surgeon General. Atlanta, Ga: US Dept of Health and Human Services,
Centers for Disease Control and Prevention, National Center for Chronic Disease
Prevention and Health Promotion; 1996:175-185.
24.Colditz GA, Manson JE, Hankinson SE. The Nurses' Health Study: 20-year contribution to the understanding
of health among women.
J Women Health.1997;6:49-62.Google Scholar 25.Brandt J, Spencer M, Folstein M. The telephone interview for cognitive status.
Neuropsychiatry Neuropsychol Behav Neurol.1988;1:111-117.Google Scholar 26.Albert M, Smith LA, Scherr PA, Taylor JO, Evans DA, Funkenstein HH. Use of brief cognitive tests to identify individuals in the community
with clinically diagnosed Alzheimer's disease.
Int J Neurosci.1991;57:167-178.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=1938160&dopt=Abstract
Google Scholar 27.Scherr PA, Albert MS, Funkenstein HH.
et al. Correlates of cognitive function in an elderly community population.
Am J Epidemiol.1988;128:1084-1101.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3189282&dopt=Abstract
Google Scholar 28.Goodglass H, Kaplan E. The Assessment of Aphasia. Philadelphia, Pa: Lea & Febiger; 1983.
29.Lezak MD. Chapter 9: Orientiation and Attention. In: Neuropsychological Assessment. 3rd ed.
New York, NY: Oxford; 1995:335-384.
30.Small BJ, Mobly JL, Laukka EJ, Jones S, Backman L. Cognitive deficits in preclinical Alzheimer's disease.
Acta Neurol Scand.2003;107(suppl 179):29-33.Google Scholar 31.Bretsky P, Guralnik JM, Launer L, Albert M, Seeman TE.MacArthur Studies of Successful Aging. The role of APOE-epsilon4 in longitudinal cognitive decline: MacArthur
Studies of Successful Aging.
Neurology.2003;60:1077-1081.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12682309&dopt=Abstract
Google Scholar 32.Ainsworth BE, Haskell WL, Leon AS, Jacobs Jr DR, Paffenbarger Jr RS. Compendium of physical activities: classification of energy costs of
human physical activities.
Med Sci Sport Exerc.1992;25:71-80.Google Scholar 33.Wolf AM, Hunter DJ, Colditz GA.
et al. Reproducibility and validity of a self-administered physical activity
questionnaire.
Int J Epidemiol.1994;23:991-999.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7860180&dopt=Abstract
Google Scholar 34.Ganguli M, Belle S, Ratcliff G.
et al. Sensitivity and specificity for dementia of population-based criteria
for cognitive impairment: the MoVIES project.
J Gerontol.1993;48:M152-M161.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8315228&dopt=Abstract
Google Scholar 35.Chandra V, DeKosky ST, Pandav R.
et al. Neurologic factors associated with cognitive impairment in a rural
elderly population in India: the Indo-US Cross-National Dementia Epidemiology
Study.
J Geriatr Psychiatry Neurol.1998;11:11-17.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9686747&dopt=Abstract
Google Scholar 36.Yaffe K, Krueger K, Sarkar S.
et al. Cognitive function in postmenopausal women treated with raloxifene.
N Engl J Med.2001;344:1207-1213.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11309635&dopt=Abstract
Google Scholar 37.Mulsant BH, Pollock BG, Kirshner M, Shen C, Dodge H, Ganguli M. Serum anticholinergic activity in a community-based sample of older
adults: relationship with cognitive performance.
Arch Gen Psychiatry.2003;60:198-203.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12578438&dopt=Abstract
Google Scholar 38.Kawas C, Segal J, Stewart WF, Corrada M, Thal LJ. A validation study of the Dementia Questionnaire.
Arch Neurol.1994;51:901-906.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8080390&dopt=Abstract
Google Scholar 39.Taddei S, Galetta F, Virdis A.
et al. Physical activity prevents age-related impairment in nitric oxide availability
in elderly athletes.
Circulation.2000;101:2896-2901.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10869260&dopt=Abstract
Google Scholar 40.Rogers RL, Meyer JS, Mortel KF. After reaching retirement age physical activity sustains cerebral perfusion
and cognition.
J Am Geriatr Soc.1990;38:123-128.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2299115&dopt=Abstract
Google Scholar 41.Churchill JD, Galvez R, Colcombe S, Swain RA, Kramer AF, Greenough WT. Exercise, experience and the aging brain.
Neurobiol Aging.2002;23:941-955.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12392797&dopt=Abstract
Google Scholar 42.Farris W, Mansourian S, Chang Y.
et al. Insulin-degrading enzyme regulates the levels of insulin, amyloid β-protein,
and the β-amyloid precursor protein intracellular domain in vivo.
Proc Natl Acad Sci U S A.2003;100:4162-4167.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12634421&dopt=Abstract
Google Scholar 43.Watson GS, Peskind ER, Asthana S.
et al. Insulin increases CSF Aβ42 levels in normal older adults.
Neurology.2003;60:1899-1903.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12821730&dopt=Abstract
Google Scholar 44.Wareham NJ, Wong M-Y, Day NE. Glucose intolerance and physical inactivity: the relative importance
of low habitual activity energy expenditure and cardiorespiratory fitness.
Am J Epidemiol.2000;152:132-139.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=10909950&dopt=Abstract
Google Scholar 45.Thompson PD, Crouse SF, Goodpaster B, Kelley D, Moyna N, Pescatello L. The acute versus the chronic response to exercise.
Med Sci Sport Exerc.2001;33(6 suppl):S438-S445.Google Scholar 46.Van Dam RM, Schuit AJ, Feskens EJ, Seidell JC, Kromhout D. Physical activity and glucose tolerance in elderly men: the Zutphen
Elderly study.
Med Sci Sport Exerc.2002;34:1132-1136.Google Scholar 47.Chodzko-Zajko WJ, Moore KA. Physical fitness and cognitive functioning in aging.
Exerc Sport Sci Rev.1994;22:195-220.http://www.ncbi.nlm.nih.gov/htbin-post/Entrez/query?db=m&form=6&Dopt=r&uid=entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=7925543&dopt=Abstract
Google Scholar