Midlife physical activity and cognition later in life: a

prospective twin study

Iso-Markku Pa, Waller Kb, Vuoksimaa Ec,d, Heikkilä Kc, Rinne Je, Kaprio Jc,d,e, Kujala UMb

a Department of Clinical Physiology and Nuclear Medicine, HUS Medical Imaging Center,

Helsinki University Central Hospital and University of Helsinki, Helsinki, FINLAND

b Department of Health Sciences, University of Jyväskylä, FINLAND

c Department of Public Health, University of Helsinki, FINLAND

d Institute for Molecular Medicine, University of Helsinki, Helsinki, FINLAND

e Clinical Neurology, Turku PET Centre, University of Turku, Turku, FINLAND

e Department of Health, National Institute for Health and Welfare, Helsinki, FINLAND

Corresponding author: Paula Iso-Markku, Helsinki University Hospital, HUS Medical

Imaging Center, Nuclear Medicine Department, Haartmaninkatu 4, FI-00290 Helsinki,

Finland. Telephone number: E-mail: paula.iso-markku@helsinki.fi

Running title: Physical activity and cognition1

Abstract

Background: Physical activity has been associated with a reduced risk of cognitive decline

but the nature of this association remains obscure.

Objective: To study associations between midlife physical activity and cognition in old age

for a prospective cohort of Finnish twins.

Methods: Physical activity in the Finnish Twin Cohort was assessed using questionnaire

responses collected in 1975 and 1981. After a mean follow-up of 25.1 years, the subjects’

(n=3050; mean age 74.2; range 66-97) cognition was evaluated with a validated telephone

interview. Both participation in vigorous physical activity, and the volume of physical

activity, divided into quintiles, were used as predictors of cognitive impairment. Metrics

collected by TELE were used to categorize participants as: cognitively impaired, suffering

mild cognitive impairment, or cognitively healthy.

Results: Participation in vigorous physical activity compared to non-participation for both

1975 and 1981 was associated with a lower risk of cognitive impairment in individual-based

analyses (fully adjusted OR 0.50, 95% CI 0.35- 0.73). Pairwise analyses yielded similar but

statistically non-significant associations. In terms of the volume of physical activity, the most

active quintile of individuals (OR 0.69, 95% CI 0.46- 1.04) had a reduced risk of cognitive

decline compared with the most sedentary quintile in the fully adjusted model although no

clear dose-response was found.

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Conclusion: Vigorous midlife physical activity was associated with less cognitive

impairment but without a clear dose-response association between the volume of physical

activity and cognition.

Key words: Dementia; exercise; genetics; cohort studies; cognition

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Introduction

Future decades are likely to see an increased prevalence of dementia given our ageing

population despite evidence to show that age-specific dementia may be declining in younger

generations (1, 2). While lifestyle factors are increasingly implicated as important

determinants of dementia, the causal nature of an individual’s intrinsic contribution to

dementia has yet to be established (3).

The majority of prospective cohort studies on midlife physical activity and later

cognitive decline or dementia have found a negative association between physical activity and

impaired cognition (4-7) with one study finding an association only in women (8), and one no

association at all (9). Midlife is a relevant time at which to investigate physical activity as a

predictor of later cognitive decline given that the neuropathologic changes attributable to

Alzheimer’s disease (the most common cause of dementia) start to accumulate decades before

clinical onset (10). In this respect, the timing of the previously mentioned studies were ideal

(midlife), with lengthy follow-ups (from 9 to 28 years) and considerable cohort sizes (from

one thousand to several thousand). However, a recurrent criticism that could be leveled at

these studies is their failure to control for potentially confounding genetic factors, given that

genetic influences exist for both physical activity (11) and liability to dementia (12). Thus,

there may be shared genetic factors that can account for the associations reported thus far in

observational studies.

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Randomized controlled trials (RCT) provide the best tool with which to assess

causality. Meta-analysis of RCTs support the cause-and-effect relationship of physical activity

and improved cognition, but the duration of exercise interventions is limited (13). Twin

studies offer a unique way with which to control for genetics and the environment, as

cognitive differences among genetically identical monozygotic twin pairs must arise from

non-genetic causes including differences in physical activity levels. To our knowledge, of the

three prior twin studies for physical activity and later cognition, none had, however, a

sufficient number of monozygotic twin pairs discordant for cognition to indisputably control

for genetics (14-16). Additionally, apart from our earlier twin study the earlier twin studies

have been sub-cohorts, they have had only one simple physical activity indicator as covariate

and we have a continuous outcome measure instead of a dichotomous.

Previous studies among Finnish twin cohort on physical activity and dementia

have investigated dementia mortality (17) and physical activity as a covariate among other

vascular risk factors predisposing to cognitive impairment (14). These studies have shown an

association between physical activity and cognition and therefore a more detailed study is

indicated. Here, we investigated if middle age physical activity is a protective factor of old

age cognitive impairment. We investigated both vigorous physical activity and the volume of

physical activity.

Methods

Study cohort

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The older cohort of the Finnish Twin Study consists of all the same-sex twins in Finland born

before 1958 with both co-twins alive in 1967 (18). Broad health questionnaires including

several questions on physical activity were sent to the cohort members in 1975 and 1981

(Figure 1). The response rates for these questionnaires have been high; 89% in 1975, and 84%

in 1981. After a lengthy follow-up (mean 25.1 years), the older cohort members were asked to

participate in a telephone screen to establish their cognitive function. Informed consent to

participate in the interview and study was obtained at the beginning of the interview. The

interviews have been done in three waves. For the monozygotic twins born in 1937 or earlier,

interviews took place between 1999 and 2001. In this wave, an additional criterion was used:

both twin members had to be alive. The second wave of interviews took place between 2003

and 2007 for dizygotic twins and twins of unknown zygosity born in 1937 or earlier. The third

wave of interviews, including twins born between 1938 and 1944, began in 2014 and is still in

progress. The mean age of the participants was 74.1 years (range 65.7 -97.2) at the time of

their cognition screening. Altogether, 3050 twins (994 twin pairs; 405 monozygotic, 570

dizygotic, and 19 pairs of unknown zygosity) with sufficient baseline physical activity data

have been interviewed and their data entered at the time of this study (12th November 2015).

The current study has been approved by the joint ethical committee of University of Turku

and Turku University Hospital, and by the ethics committee of the Hospital District of

Southwest Finland.

Physical activity

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In this study, we looked at both the volume of physical activity and participation in vigorous

physical activity. Participation in vigorous physical activity was assessed both in 1975 and

1981 by answering options 2, 3, or 4 to the following question: “On average, is your leisure-

time physical activity as strenuous as: (1) walking, (2) alternately walking and jogging, (3)

jogging (light running), (4) running?” If the participant did not answer this question, the

person was categorized as not participating in vigorous physical activity that year because

most of these participants had answered in another question that they do not engage in

physical activities at all. For the year 1975 the number of non-responders to the question of

vigorous physical activity was 219 and of these participants, 196 had answered in another

question that they do not engage in any leisure-time physical activities. For the year 1981

there were 150 non-responders to the question of vigorous physical activity and of these

participants, 141 had answered before that they do not engage in any leisure-time physical

activities. Taking into account participant’s long-term engagement in vigorous physical

activity, we divided the participants into three categories: the persistent vigorous activity

category was applied to those who reported vigorous activity both years (i.e. answered one of

the alternatives 2-4 in both years), persistent inactivity described those who did not participate

in vigorous physical activity in either of the years (i.e. answered alternative 1 in both years),

and changed activity described participants who changed from vigorously active in 1975 to

vigorously inactive in 1981 or vice versa (slightly modified from 19, 17). Participants who

increased their vigorous activity from null and participants who decreased their activity to

null were combined because in earlier analyses (17) these categories had similar results.

The term vigorous is used in a different context in our paper than what is

generally used in literature. According to Howley’s classification (20) ‘alternately walking 7

and jogging’ (= physical activity more vigorous than normal walking) means vigorous

physical activity for all unfit subjects as is in our classification of vigorous physical activity.

However for high fit subjects this type of activity may be only moderate physical activity.

Determining the individualized vigorous intensity level of physical activity is an unresolved

challenge in physical activity research also when it is done using objective recordings such as

accelerometry recordings of different types of real life exercises. In our study, we aimed at

especially trying to look into the ability and interest of participating in physical exercises

more strenuous than walking – may it be vigorous for unfit persons or moderate exercise for

fit persons- and see whether it has effect on later cognition.

The volume or extent of physical activity was assessed according to responses to

questions on average intensity, average duration, and monthly frequency of leisure-time

physical activity and on physical activity during the commute to and from work. Based on

these data, an index of metabolic equivalent (i.e. multiples of metabolic resting energy

expenditure (MET)) was created by multiplying the intensity (expressed in METs) by the

mean duration and frequency of physical activity (20) adding both leisure and commute

physical activity. First, we calculated the mean MET index from 1975 and 1981 ((MET index

in 1975 + MET index in 1981) / divided by 2) which was subsequently subdivided into

quintiles (22). Mean MET quintiles were then used as predictors in the study. Secondly,

participation in persistent physical activity was formed; for that we first divided MET index

from both 1975 and 1981 into quintiles (17, slightly modified from 20). The volume of

physical activity in MET quintile I was 0 -0.59 MET-hours per day (MET-h/d) and the MET

index of quintiles II-V was 0.6- 30.1 MET-h/d. For example, a person who reported no

physical activity during work journeys but engaged in leisure-time physical activity as

strenuous as walking of half an hour to less than one hour duration on average from 3 to 5

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times per month, received a MET index value of 0.4 MET-h/d and belonged to the most

inactive MET quintile. Further division was administered to take into account the two time

points in which physical activity was measured (based on our earlier work (17) showing that

the most sedentary MET quintile was at the greatest risk for subsequent cognitive decline).

Group one contained individuals who were in the least active quintile for both years

(persistently inactive). Group two comprised individuals in the least active MET quintile in

1975, but not in 1981, or vice versa (changed activity). The third group comprised individuals

who were persistently active, and belonged to MET quintiles II-V for both baseline years

(persistently active). Thus acquired categorization reflects well the effect of long-term

physical inactivity and the rationale for the changed activity group was same as in vigorous

physical activity.

For additional analyses, a log transformed mean MET index from 1975 and

1981 was used, without categorization.

Cognition and covariates

We used TELE (a telephone assessment of dementia), TICS (Telephone

Interview for Cognitive Status) and total score (a combination of TELE and TICS) to evaluate

cognition in this study. We present only the results using TELE and the total score, as the

results for TICS were very similar to those from TELE. TELE is used in the main analyses of

this study because of its validated categorization (23). Total score was used in linear

regression analyses because it has normal distribution, unlike TELE and TICS.

TELE is based on the 10-Item Mental Status Questionnaire and comprises

questions on basic knowledge as well as word recall, serial subtraction, orientation, and 9

attention. TELE discriminates well between healthy cognition and dementia (24), correlates

strongly with Mini-Mental Status Examination (MMSE) results, and has been validated in a

Finnish population (23). The following TELE score cut-offs were used in this study to

minimize the amount of false-positives and false-negatives; cognitive impairment < 16 points,

mild cognitive impairment (MCI) 16-17.5 points, and intact cognition 17.6- 20 points (23).

Although we aim to investigate risk factors for dementia, the diagnosis of dementia can’t be

solely based on TELE and therefore the term cognitive impairment is used instead of

dementia. Our use of the term “discordant for cognition” describes twin pairs for which the

other twin has intact cognition and the other cognitive impairment.

For additional analyses, total score was used. Total score combines TELE and

TICS (Telephone Interview for Cognitive Status) scores (25). TICS is modeled after MMSE

and has some shared items with TELE but also additional items on naming to verbal

description, sentence repetition, and word opposites (26). Overlapping items of TELE and

TICS instruments were asked once, and thus contributed only once to the total score.

Covariates used in this study are age, the length of follow-up, sex, body mass

index (BMI), hypertension, binge drinking, education and smoking. All these are self-reports

from the 1981 questionnaire except for length of follow-up and age, which were computed

from the date of response to the questionnaire, and the participant’s date of birth from the

official population register. The participant was categorized as a binge drinker if he or she

reported drinking at least once a month more than five bottles of beer, more than one bottle of

wine, or more than half a bottle of spirits on one occasion (27). Education was defined as

years of formal schooling. Smoking is used as four category covariate: current daily smoker,

former smoker, occasional smoker, and non-smokers having never smoked cigarettes (28).

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The participant was categorized as having hypertension if they reported hypertension in the

questionnaire from 1981, or had hypertension medication according to information provided

from the Social Insurance Institution of Finland.

To eliminate the possibility of physical inactivity due to chronic disease, we also

repeated our analyses using a subgroup of healthy subjects at baseline (n= 1766). The most

common chronic diseases, such as diabetes, coronary artery disease, chronic obstructive

pulmonary disease, and malignant cancers were excluded from this subanalysis (see reference

19 for detailed exclusion criteria).

Data analyses

Multinomial logistic regression analysis was used to evaluate odds ratios (OR) with 95%

confidence intervals (CI) for cognitive impairment and mild cognitive impairment vs. normal

cognition, according to physical activity levels in individual-based analyses. This analysis is

based on twin individuals, but with statistical compensation (using robust estimators of

variance (29)) for the lack of independence using twins sampled as twin pairs. In pairwise

analyses using TELE data, conditional logistic regression model was used for with-in pair

comparison: comparing outcomes in twins with their co-twin of different activity level. The

model was used separately to compare cognitive impairment vs. normal cognition, and mild

cognitive impairment vs. normal cognition. Linear regression analysis was used in the

analyses with total score. In these analyses, physical activity was studied first in categories,

and then as a continuous variable. In the individual-based analyses of the volume of physical

activity as a continuous variable, a log transformed MET index was used because MET index

was not initially normally distributed. In pairwise analyses the with-in pair differences

11

between baseline mean MET indices were compared with the within-pair differences in total

score at the end of the follow-up.

For all regression analyses, the inactive group was used as a reference group.

Age, the length of follow-up, and sex, were included as covariates in the basic model. We

continued analyses by adding binge drinking and education as covariates. In the final model,

we also included the following covariates reflecting vascular morbidity: hypertension, BMI,

and smoking. As additional analyses, linear, logistic, and conditional logistic regression

models were also applied to a subgroup of healthy participants at baseline. In one analysis,

logistic regression model was used with the mean MET index from 1975 and 1981 divided

into quintiles. The clinical significance of a physical activity difference is different for

example for the differences: 0 MET-h/d and 4 MET-h/d vs. 10 MET-h/d and 14 MET-h/d.

This is why, in the analysis comparing with-in pair differences in a linear regression model,

the physical activity level of the less active twin was used as a covariate.

Results

At the end of the follow-up period (mean, 25.1 years; range, 16.5- 33.9 years), 367 (12.0 %,

N= 3050) participants had cognitive impairment. The mean age of the participants was 49.1

years (range: 37.9–74.9 years) in 1981 at the time of the second questionnaire. The baseline

characteristics of our study cohort, according to persistence of vigorous physical activity, are

detailed in Table 1. These data shows that the participants in the persistent vigorous activity

group had significantly lower BMI, less hypertension, and longer education at baseline

compared to those who were persistently inactive. A significantly greater percentage of the

participants in the persistent vigorous activity group were also binge drinkers.

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TELE analyses

In the individual logistic regression model analyses of persistence of vigorous activity, both

the persistent vigorous activity group (OR 0.35, 95% CI 0.24- 0.50) and the change group

(OR 0.73, 95% CI 0.55- 0.97) had significantly lower OR for impaired cognition compared to

the persistently inactive in the model adjusted for age, the length of the follow-up, and sex

(Table 2). In the final model (including also hypertension, BMI, and the smoking variables)

only the persistent vigorous activity group had still significantly lower OR for impaired

cognition (OR 0.50, 95% CI 0.35-0.73). In a subgroup of healthy participants at baseline (n =

2210), the risk of cognitive impairment was also reduced in the persistent vigorous activity

group with an OR in the final model of 0.48 (95% CI 0.30- 0.75). An interaction test did not

identify any sex-related differences in our data.

In pairwise analyses twins from the persistent vigorous activity group had a

reduced, though statistically non-significant, age- and the length of the follow-up adjusted OR

0.59 (95% CI 0.19-1.80) for developing cognitive impairment compared to their co-twins

from the persistent inactivity group. The risk of mild cognitive impairment also seemed

reduced for the persistent vigorous activity group although this metric was found to be

statistically non-significant in the model adjusted for age, sex, and the length of follow-up,

and in the final model. Of 124 twin pairs clearly discordant for cognition at follow-up (intact

cognition vs cognitive impairment), there were only eight twin pairs clearly discordant also

for the persistence of vigorous physical activity in baseline. Of these, two were monozygotic

and the inactive co-twin had cognitive impairment. Of the discordant dizygotic twin pairs,

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there were three pairs in which the inactive co-twin was cognitively impaired and three cases

vice versa.

In the individual-based analyses of the volume of physical activity (using the

mean MET index quintiles from 1981 and 1975), the risk of cognitive impairment was

greatest for the most inactive quintile METQI (Figure 2A). The reduced risk for cognitive

impairment was significant for the three most active quintiles (in the model adjusted for age,

sex, and the length of follow-up). The results in our final fully-adjusted model were very

similar, but the smaller risk for cognitive impairment remained significant only in the MET

QIII compared to METQI (Figure 2B). As for the risk of mild cognitive impairment, the two

most active quintiles had a significantly larger risk than the most sedentary quintile in our

final model, although the difference was only barely significant.

The persistently active individuals who engaged in at least some physical

activity over both of the assessed years, i.e. belonged to MET quintile II-V, had a

significantly lower risk of impaired cognition compared to the persistently inactive

individuals in the age-, sex- and the length of follow-up adjusted model (OR 0.45, 95% CI

0.32-0.62) as well as in the final model (OR 0.61, 95% CI 0.43- 0.88) (Table 3). In a

subgroup of healthy participants (n= 2210), those who were persistently active had a

significantly lower risk of cognitive impairment in the model adjusted for age, sex and the

length of the follow-up (OR 0.46, 95% CI 0.29-0.72) but in the final model the result was

attenuated and lost significance (OR 0.88, 95% CI 0.63–1.24). In pairwise analyses the age-

and the length of follow-up adjusted OR for cognitive impairment was reduced, but

statistically non-significant for persistently active (including in QII-V); OR 0.43 (95% CI

0.15-1.26) versus their co-twins from the persistently inactivity group. No significant

14

differences were seen for the risk of mild cognitive impairment according to group of

persistent physical activity. Within 124 twin pairs clearly discordant for cognition at follow-

up (intact cognition vs. cognitive impairment), only 16 twin pairs were also discordant for

their baseline volume of physical activity. Of these twin pairs four were monozygotic, and for

three of these pairs, the inactive co-twin had cognitive impairment. In the remaining pair, the

active twin had cognitive impairment. For the discordant dizygotic twins, in seven pairs the

inactive twin had cognitive impairment, and vice versa for the remaining four pairs.

Total score analyses

In the individual-based linear regression model of persistence of vigorous physical activity

and cognition (Table 4), twins who engaged persistently in vigorous physical activity had

higher total scores (better cognition) compared with twins who were persistently inactive.

These data were statistically significant in the model adjusted for age, sex and the length of

follow-up, in the final model, and in a subgroup of healthy participants at baseline (β-estimate

in the final model 0.91, 95% CI 0.47-1.35). In a linear regression model of the different

groups of volume of physical activity, the persistently active twins had higher total scores in

the model adjusted for age, sex, and the length of the follow-up, and in the final model, but

not in the fully adjusted model in the subgroup of healthy participants (Table 4).

In a linear regression model of log transformed mean MET and total score,

greater physical activity was associated with better cognition in the model adjusted for sex,

age and the length of follow-up but not in the final model (Table 5). When within-pair

differences in MET score were compared with within-pair differences in total score, no

association was found in any of the models for all pairs, monozygotic pairs or dizygotic pairs.

15

Discussion

Participants who were persistently vigorously active in midlife had a decreased risk for

subsequent impaired cognition. This finding is in line with our earlier study in which

persistent vigorous physical activity in adulthood was associated with a lowered risk of

dementia mortality (17), and agrees with prior evidence on physical activity and cognition

(30). Regarding the volume of physical activity, belonging to the most sedentary MET index

quintile in both years, in 1975 and 1981, was associated with a significantly greater risk of

cognitive impairment compared to those with persistently higher physical activity. In the

analyses of mean MET index quintiles from 1975 and 1981, the METQI stands out with

greater risk of cognitive impairment. The differences between the other MET quintiles were

small and no systematic reduction of risk for cognitive impairment is seen through the

quintiles in the final fully adjusted model. Nor were log transformed MET scores significantly

associated with cognition in the final model. Our study does not, therefore, support a dose-

response association unlike recent meta-analyses (31-32). Our study also is in line with the

recent meta-analyses agreeing that already a moderate amount of physical activity is sufficient

to provide cognition-protective benefits (31-32).

Pairwise analyses comparing twins discordant for persistence of vigorous

physical activity showed similar results to those in the individual analyses. These within-pair

associations were non-significant which is likely due to the smaller number of twin pairs

discordant for physical activity. This finding agrees with our earlier twin study and with

another twin study, that addressed dementia and the intensity of exercise, in which a rather

similar risk reduction was reported as in our study (OR 0.66 in the final model in this study)

(16). However, these studies (16, 14, current study) are contradicted by another twin study

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(15) but the measure of physical activity in that study may be less accurate than in our study

(crude sum score 0-4, one score for each: outdoor activities, sports, gardening and home

improvement and physical exercise after age 35). Additionally, excluding our earlier twin

study the prior twin studies have consisted of sub-cohorts, the outcome has been dementia

instead of cognition and they have had only one simple measure of physical activity whereas

we have looked into physical activity extensively. In our study, the number of twin pairs in

our analyses (n= 120-994) exceeds the number of twin pairs in the earlier twin studies with

reliable measures of physical activity (n= 90 (2) and n= 54-67 (14)). Our pairwise analyses of

the volume of physical activity and cognition with 994 twin pairs showed no dose-response

association between the two. To our knowledge, this association has not been studied using

such a large number of twins, which underscores the novelty of our data. To conclude, our

study provides robust evidence to show that when taking into account genetic and familial

confounding, no association exists between the volume of physical activity and cognition.

Although our results from pairwise analyses controlling for genetic and familial confounding

suggest that vigorous physical activity is associated with a reduced risk of future cognitive

impairment, and the results from an earlier twin study, with a reliable measure of physical

activity (16), also support this association, larger, multicenter studies are needed.

Our study extends the earlier studies. In comparison to our prior study of midlife

health habits in the same twin cohort (14) we have now increased the study population from

2 165 cognition interviewed subjects with adequate questionnaire data to 3050, with the

number of discordant twin pairs increased from 54-67 to 120 – 124 in the conditional

regression model, and to 994 in the linear regression model. Additionally, we have now

provided a more reliable estimate of long-term physical activity because of two measurement

points of physical activity, set six years apart. We have also analyzed the data in more detail

17

according to physical activity, also including pairwise analyses among twin pairs discordant

for physical activity. The consistent point estimates from individual and within-pair analyses

support a causal interpretation, but given the lack of significance in the pairwise analyses,

caution in our conclusion is warranted.

Three main pathways are suggested to underlie the protective mechanisms

afforded by physical activity against cognitive impairment. These are the vascular pathway,

the neurobiological pathway and inhibition of amyloid-β accumulation (33-36). In our study,

even after taking into account selected vascular risk factors, the positive association between

physical activity and cognition remained significant. Our results are, therefore, in line with

others who suggest that physical activity influences cognition in more ways than vascular

mechanisms alone (36). On the other hand, physical activity in childhood and in adolescence

has been associated with better academic performance and improved brain function and

structure (37). Therefore, one possibility is also a pathway in which physical activity in early

life creates a cognitive reserve that buffers against the unfavorable effects of aging and

reduced brain function. In our study, we had combined the groups who increased or decreased

physical activity (in regards of both vigorous and volume of physical activity) to increase the

number of participants in each category, but when analyzed separately both decreasing

vigorous physical activity or the volume of physical activity were associated with decreased

risk of cognitive impairment suggesting that physical activity in midlife or young adulthood is

of essential and may create the above mentioned buffer against cognitive decline.

Alternatively, high cognitive abilities could also be associated with a more devoted engaging

in physical activities in midlife, thus, making it difficult to decipher which is the ultimate

reason for better cognition in midlife. The evidence from randomized controlled trials,

however, speaks against this pathway (13).

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Our study has several strengths. The older Finnish twin cohort can be considered

to be a good representation of the Finnish population. Our two measurement points for

physical activity also provide a more reliable estimate of the long-term engagement in

physical activities. The twin study design allows us insight into familial confounding factors.

We controlled for many confounding factors providing support for the notion that physical

activity is an independent protective factor against cognitive impairment. In our study, the

results were also similar in a smaller subgroup of healthy individuals at baseline, physical

activity was queried in midlife, and we had a very lengthy follow-up (mean 25.1 years).

Taken together, our results are unlikely to reflect reverse causality.

We should also acknowledge that our study has its limitations. Both physical

activity and confounding factors were self-reported, although hypertension and BMI are

shown to be quite reliably reported in the Finnish population (38-40). The number of twin

pairs discordant for cognition and physical activity, however, could have been more

substantial. It is noteworthy that age is one of the strongest risk factors for dementia and the

age range of our study cohort at the time of the cognitive assessment is quite wide (65.7- 97.2

years). We have, however, taken age into account in all our analyses except for the pairwise

twin analyses in which the twins are compared against their co-twins and there is no age

difference at the time of cognition evaluation. One limitation also is that we had no

assessment of cognition at baseline. Thus, we cannot exclude the possibility that physically

active participants had better cognition already at baseline.

Clinical dementia diagnosis requires extensive neuropsychological testing, a

doctor’s thorough clinical evaluation face to face, a detailed interview with a relative or

another close person of the patient, exclusion of other diseases causing memory complaints or

cognitive disturbance, and finally imaging studies to ascertain the diagnosis (41). A brief 19

telephone interview is insufficient for the diagnosis of dementia. However, in this study we

have used a validated telephone interview for the purposes of detecting persons with cognitive

impairment. The method has been validated and screens with a good reliability persons with

cognitive impairment. The sensitivity and specificity of the TELE to differentiate AD from

healthy cognition has been 90.0 and 88.5 % in a Finnish validation study (23) and now our

limit for cognitive impairment is even stricter. The possibility of misinterpretations or factors

such as hearing impairment hampering the interviews with older persons, however, does

prevail and is one limitations of our study.

In conclusion, our individual-based analyses support the hypothesis that

vigorous physical activity protects against cognitive impairment and similar trends were

observed after taking into account genetic and familial confounding. A fairly moderate

amount of physical activity seems sufficient to confer memory-protecting benefits. However,

our study shows no clear dose-response association between the volume of physical activity

and cognition in pairwise analyses that control for genetic and familial confounding.

Acknowledgments:

We thank the Finnish Ministry of Education and Culture (U.M.K.), the Academy of Finland

(grants 265240 and 263278 to J.K.), HUS Medical Imaging and the Juho Vainio Foundation

(salary and grant for P.I.) for supporting this study. The funding sources had no role in the

study design, data collection, analysis, interpretation, or review of this study. The authors

declare no conflicting or competing interests.

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References

[1] Norton S, Matthews FE, Brayne C (2013) A commentary on studies presenting

projections of the future prevalence of dementia. BMC Public Health 13, 1.

[2] Langa KM (2015) Is the risk of Alzheimer's disease and dementia declining?

Alzheimers Res Ther 7, 34.

[3] Daviglus ML, Plassman BL, Pirzada A, Bell CC, Bowen PE, Burke JR, Connolly ES

Jr, Dunbar-Jacob JM, Granieri EC, McGarry K, Patel D, Trevisan M, Williams JW Jr

(2011) Risk factors and preventive interventions for Alzheimer disease: state of the

science. Arch Neurol 68, 1185-90.

[4] Rovio S, Kåreholt I, Helkala EL,Viitanen M, Winblad B, Tuomilehto J, Soininen H,

Nissinen A, Kivipelto M (2005) Leisure-time physical activity at midlife and the risk

of dementia and Alzheimer's disease. Lancet Neurol 4, 705–11.

[5] Chang M, Jonsson PV, Snaedal J, Bjornsson S, Saczynski JS, Aspelund T, Eiriksdottir

G, Jonsdottir MK, Lopez OL, Harris TB, Gudnason V, Launer LJ (2010) The effect of

midlife physical activity on cognitive function among older adults: AGES-Reykjavik

Study. J Gerontol A Biol Sci Med Sci 65, 1369-74.

[6] Tolppanen AM, Solomon A, Kulmala J, Kåreholt I, Ngandu T, Rusanen M,

Laatikainen T, Soininen H, Kivipelto M (2015) Leisure-time physical activity from

mid- to late life, body mass index, and risk of dementia. Alzheimers Dement 11, 434-

443.e6.

21

[7] Singh-Manoux A, Hillsdon M, Brunner E, Marmot M (2005) Effects of physical

activity on cognitive functioning in middle age: evidence from the Whitehall II

prospective cohort study. Am J Public Health 95, 2252-8.

[8] Kåreholt I, Lennartsson C, Gatz M, Parker MG (2011) Baseline leisure time activity

and cognition more than two decades later. Int J Geriatr Psychiatry 26, 65-74.

[9] Morgan GS, Gallacher J, Bayer A, Fish M, Ebrahim S, Ben-Shlomo Y (2012) Physical

activity in middle-age and dementia in later life: findings from a prospective cohort of

men in Caerphilly, South Wales and a meta-analysis. J Alzheimers Dis 31, 569-80.

[10] Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS,

Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue

MC, Trojanowski JQ (2013) Tracking pathophysiological processes in Alzheimer’s

disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 12,

207-16

[11] Stubbe JH, Boomsma DI, Vink JM, Cornes BK, Martin NG, Skytthe A, Kyvik

KO, Rose RJ, Kujala UM, Kaprio J, Harris JR, Pedersen NL, Hunkin J, Spector TD,

de Geus EJ (2006) Genetic influences on exercise participation in 37,051 twin pairs

from seven countries. PLoS One 1, e22.

[12] Lee T, Henry JD, Trollor JN, Sachdev PS (2010) Genetic influences on

cognitive functions in the elderly: a selective review of twin studies. Brain Res Rev 64,

1-13.

[13] Smith PJ, Blumenthal JA, Hoffman BM, Cooper H, Strauman TA, Welsh-

Bohmer K, Browndyke JN, Sherwood A (2010) Aerobic exercise and neurocognitive

performance: a meta-analytic review of randomized controlled trials. Psychosom Med

72, 239-52.

22

[14] Virta JJ, Heikkilä K, Perola M, Koskenvuo M, Räihä I, Rinne JO, Kaprio J

(2013) Midlife cardiovascular risk factors and late cognitive impairment. Eur J

Epidemiol 28, 405-16.

[15] Carlson MC, Helms MJ, Steffens DC, Burke JR, Potter GG, Plassman BL

(2008) Midlife activity predicts risk of dementia in older male twin pairs. Alzheimers

Dement 4, 324-31.

[16] Andel R, Crowe M, Pedersen NL, Fratiglioni L, Johansson B, Gatz M (2008)

Physical exercise at midlife and risk of dementia three decades later: a population-

based study of Swedish twins. J Gerontol A Biol Sci Med Sci 63, 62-6.

[17] Iso-Markku P, Waller K, Kujala UM, Kaprio J (2015) Physical activity and

dementia: Long-term follow-up study of adult twins. Ann Med 47, 81-7.

[18] Kaprio J, Sarna S, Koskenvuo M, Rantasalo I (1978) The Finnish Twin

Registry: formation and compilation, questionnaire study, zygosity determination

procedures and research program. Prog Clin Biol Res 24B, 179-84.

[19] Kujala UM, Kaprio J, Koskenvuo M (2002) Modifiable risk factors as

predictors of all-cause mortality: the roles of genetics and childhood environment. Am

J Epidemiol 156, 985-93.

[20] Howley ET (2001), Type of activity: resistance, aerobic and leisure versus

occupational physical activity. Med Sci Sports Exerc 33(6 Suppl), S364-9.

[21] Kujala UM, Kaprio J, Sarna S, Koskenvuo M (1998) Relationship of leisure-

time physical activity and mortality: the Finnish twin cohort. JAMA 279, 440-4.

[22] Waller K, Kaprio J, Lehtovirta M, Silventoinen K, Koskenvuo M, Kujala UM

(2010) Leisure-time physical activity and type 2 diabetes during a 28 year follow-up in

twins. Diabetologia 53, 2531-7.

23

[23] Järvenpää T, Rinne JO, Räihä I, Koskenvuo M, Löppönen M, Hinkka S,

Kaprio J (2002) Characteristics of two telephone screens for cognitive impairment.

Dement Geriatr Cogn Disord 13, 149-55.

[24] Gatz M, Reynolds CA, John R, Johansson B, Mortimer JA, Pedersen NL

(2002) Telephone screening to identify potential dementia cases in a population-based

sample of older adults. Int Psychogeriatr 14, 273-89.

[25] Laitala VS, Kaprio J, Koskenvuo M, Räihä I, Rinne JO, Silventoinen K (2009)

Coffee drinking in middle age is not associated with cognitive performance in old age.

Am J Clin Nutr 90, 640-6.

[26] Brandt J, Spencer M, Folstein M (1988) The telephone interview for cognitive

status. Neuropsychiatry Neuropsychol Behav Neurol 1, 111-7.

[27] Kaprio J, Koskenvuo M, Langinvainio H, Romanov K, Sarna S, Rose RJ

(1987) Genetic influences on use and abuse of alcohol: a study of 5638 adult Finnish

twin brothers. Alcohol Clin Exp Res 11, 349–56.

[28] Kaprio J, Koskenvuo M (1988) A prospective study of psychological and

socioeconomic characteristics, health behavior and morbidity in cigarette smokers

prior to quitting compared to persistent smokers and non-smokers. J Clin Epidemiol

41, 139–50.

[29] Williams RL (2000) A note on robust variance estimation for cluster-correlated

data. Biometrics 56, 645–6.

[30] Blondell SJ, Hammersley-Mather R, Veerman JL (2014) Does physical

activity prevent cognitive decline and dementia?: A systematic review and meta-

analysis of longitudinal studies. BMC Public Health 14, 510.

24

[31] Hamer M, Chida Y (2009) Physical activity and risk of neurodegenerative

disease: a systematic review of prospective evidence. Psychol Med 39, 3-11.

[32] Sofi F, Valecchi D, Bacci D, Abbate R, Gensini GF, Casini A, Macchi C

(2011) Physical activity and risk of cognitive decline: a meta-analysis of prospective

studies. J Intern Med 269, 107-17.

[33] Adlard PA, Perreau VM, Pop V, Cotman CW (2005) Voluntary exercise

decreases amyloid load in a transgenic model of Alzheimer’s disease. J Neurosci 25,

4217-21.

[34] van Praag H (2008) Neurogenesis and exercise: past and future directions.

Neuromolecular Med 10, 128-40.

[35] Vaynman S, Ying Z, Gomez-Pinilla F (2003) Interplay between brain-derived

neurotrophic factor and signal transduction modulators in the regulation of the effects

of exercise on synaptic-plasticity. Neuroscience 122, 647-57.

[36] Rovio S, Spulber G, Nieminen LJ, Niskanen E, Winblad B, Tuomilehto J,

Nissinen A, Soininen H, Kivipelto M (2010) The effect of midlife physical activity on

structural brain changes in the elderly. Neurobiol Aging 31, 1927-36.

[37] Voss MW, Nagamatsu LS, Liu-Ambrose T, Kramer AF (2011) Exercise, brain,

and cognition across the life span. J Appl Physiol (1985) 111, 1505-13.

[38] Haapanen N, Miilunpalo S, Pasanen M, Oja P, Vuori I (1997) Agreement

between questionnaire data and medical records of chronic diseases in middle-aged

and elderly Finnish men and women. Am J Epidemiol 145, 762-9.

[39] Hernelahti M, Kujala UM, Kaprio J, Karjalainen J, Sarna S (1998)

Hypertension in master endurance athletes. J Hypertens 16, 1573-7.

25

[40] Mustelin L, Silventoinen K, Pietiläinen K, Rissanen A, Kaprio J (2009)

Physical activity reduces the influence of genetic effects on BMI and waist

circumference: a study in young adult twins. Int J Obes 33, 29-36.

[41] Waldemar G1, Dubois B, Emre M, Georges J, McKeith IG, Rossor M,

Scheltens P, Tariska P, Winblad B; EFNS (2007) Recommendations for the diagnosis

and management of Alzheimer's disease and other disorders associated with dementia:

EFNS guideline. Eur J Neurol 14, e1-26.

26

Table 1. Baseline characteristics in 1981 and TELE score at follow-up in our cohort of 3050

individuals categorized according to the persistence of vigorous physical activity *

Variable

No vigorous

activity in 1975

or 1981

Change (vigorous

activity in either

1975 or 1981 but not

both)

Persistent

vigorous activity

for both years)

All, n (%) 1282 (42.0) 850 (27.9) 918 (30.1)

TELE score (mean SD) 17.5 (2.5) 18.0 (2.1) 18.4 (1.8)

Male, n (%)† 507 (39.5) 631 (74.2) 416 (45.3)

Female, n (%)† 775 (60.5) 434 (51.1) 287 (31.2)

Monozygotic, n (%)† 395 (30.8) 252 (29.6) 288 (31.4)

Dizygotic, n (%)† 865 (67.5) 581 (68.4) 603 (65.6)

Zygosity unknown, n (%)† 22 (1.7) 17 (2.0) 27 (2.9)

Age (yr) at 1981 (mean SD)

†

51.4 (7.5) 48.3 (6.6) 46.7 (6.2)

Education in years at 1981

(mean SD) †

7.0 (2.3) 7.6 (2.6) 8.5 (3.4)

Binge drinkers 1981 (%)† 152 (11.9) 124 (14.6) 186 (20.3)

BMI in 1981 (mean SD) † 25.4 (3.3) 24.9 (3.2) 24.3 (2.5)

Smoking status in 1981, n

(%)†

never smoked 789 (62.6) 459 (54.7) 476 (52.6)

occasional smoker 40 (3.2) 21 (2.5) 33 (3.6)

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former smoker 249 (19.7) 206 (24.6) 252 (27.8)

current smoker 183 (14.5) 153 (18.2) 144 (15.9)

Hypertension, n (%)† 145 (11.3) 62 (7.3) 30 (3.3)

Healthy in 1981, n (%)† 815 (63.6) 766 (90.1) 629 (68.5)

* Classification according to the persistence of vigorous physical activity (i.e. more strenuous than walking) were: no vigorous physical activity in 1975 or 1981 (none), vigorous physical activity in either 1975 or 1981 but not in both years (change), and vigorous physical activity for both years (persistent).

† Group differences (as described above) in baseline characteristics were significant ( p < 0.001 by symmetry and marginal homogeneity test and linear regression). Percentages entered on the first row indicate the fraction of participants in each activity category. Percentages entered in subsequent rows show the proportion of participants’ affirmative for each specified variable (e.g. hypertension).

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Table 2. Odds ratios for cognitive impairment according to TELE analyses for groups stratified by the persistence of vigorous physical activity in 1975 and 1981.

Individual analyses † Pairwise analyses ‡

Cognitive impairment Mild cognitive impairment Cognitive impairment Mild cognitive impairment

Vigorous physical

activity in 1975 and 1981*

Age, follow-up,

and sex adjusted

Final model § Age, follow-up,

and sex adjusted

Final model § Age and follow-up

adjusted

Final model § Age and follow-

up adjusted

Final model §

OR (95 % CI)

All (3050)

None 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Change 0.73 (0.55- 0.97) 0.86 (0.64- 1.17) 0.89 (0.71- 1.11) 0.98 (0.78- 1.24) 0.64 (0.25- 1.66) 0.77 (0.21- 2.80) 1.26 (0.78- 2.06) 1.27 (0.73- 2.20)

Persistent 0.35 (0.24- 0.50) 0.50 (0.35- 0.73) 0.68 (0.54- 0.86) 0.88 (0.69- 1.12) 0.59 (0.19- 1.80) 0.44 (0.11- 1.84) 0.70 (0.41- 1.21) 0.60 (0.32- 1.10)

Healthy (2210)

None 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Change 0.71 (0.49- 1.02) 0.83 (0.56- 1.22) 0.92 (0.70- 1.21) 1.04 (0.77- 1.38 0.48 (0.13- 1.82) 1.03 (0.16- 6.77) 1.61 (0.82- 3.17) 2.05 (0.88- 4.76)

Persistent 0.35 (0.23- 0.55) 0.48 (0.31- 0.75) 0.72 (0.55- 0.95) 0.89 (0.67- 1.19) 0.56 (0.11- 2.74) 0.64 (0.09- 4.73) 0.73 (0.37- 1.47) 0.67 (0.29- 1.56)

* The three different groups according to the persistence of vigorous physical activity (i.e. more strenuous than walking) were: no vigorous physical activity in 1975 or 1981 (none), vigorous physical activity in either 1975 or 1981 (change), and vigorous physical activity in both years 1975 and 1981 (persistent).

† In the individual analyses, the individuals in the two groups were compared against each other.

29

‡ In pairwise analyses, the twins in the two groups were compared against their co-twins (in the age and length of follow-up adjusted model, the number of twin pairs in the analysis comparing healthy cognition and cognitive impairment was 124; the number of twins in the analysis comparing healthy cognition with mild cognitive impairment was 468. For the final model, these metrics were 120 and 426 respectively).

§ The final model was adjusted for age, follow-up, sex, binge drinking, education, hypertension, BMI and smoking (n=2927 for the whole cohort, n=2130 for the healthy individuals, n=120 for twin pairs discordant for cognition, and n=62 for healthy twin pairs at baseline who were discordant for cognition at the end of the follow-up).

|| The results that are statistically significant are printed in bold numbers.

30

Individual analyses † Pairwise analyses ‡

Cognitive impairment MCI Cognitive impairment MCI

Volume of physical

activity in 1975 and 1981 *

Age, follow-up, and

sex adjusted

Final model § Age, follow-up,

and sex adjusted

Final model § Age and follow-

up adjusted

Final model § Age and

follow-up

adjusted

Final model §

OR (95 % CI)

All (3050)

None 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Change 0.75 (0.53- 1.06) 0.82 (0.56- 1.19) 0.93 (0.68- 1.26) 0.93 (0.68- 1.28) 0.49 (0.12- 1.97) 0.55 (0.09- 3.58) 1.21 (0.63- 2.33) 1.13 (0.55- 2.33)

Persistent 0.45 (0.32- 0.62) 0.61 (0.43- 0.88) 0.86 (0.65- 1.13) 1.05 (0.79- 1.49) 0.43 (0.15- 1.26) 0.36 (0.07- 1.68) 1.08 (0.61- 1.90) 0.88 (0.46- 1.68)

Healthy (2210)

None 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Change 0.72 (0.44- 1.16) 0.85 (0.51- 1.44) 0.87 (0.60- 1.27) 0.92 (0.63- 1.37) 2.50 (0.17- 37.4) 1.13 (0.06- 22.2) 1.00 (0.39- 2.55) 1.14 (0.37- 3.50)

Persistent 0.46 (0.29- 0.72) 0.68 (0.42- 1.11) 0.88 (0.63- 1.24) 1.16 (0.81- 1.64) 0.25 (0.04- 1.50) 0.28 (0.02- 3.54) 0.94 (0.42- 2.08) 0.71 (0.28- 1.83)

Table 3. The odds ratios for cognitive impairment and mild cognitive impairment according TELE data for groups stratified by their volume of physical activity in 1975 and 1981.

* Volume of physical activity was measured in five quintiles of MET hours/day (MET = metabolic equivalent i.e. multiples of metabolic energy expenditure) calculated from the reported intensity, frequency, and duration of leisure physical activity and physical activity during work journeys. Further division into three groups was made to take into account two baseline measurements: firstly the ones who belonging to MET quintile I (the least physically active quintile) in both years 1975 and 1981 (“none”), secondly the ones who belonged to MET quintile I in 1975 but not in 1981 or vice versa (the “change” group), and thirdly the persistently active ones who did not belong to the MET quintile I in either year (the “persistent” group).

31

† In the individual analyses the individuals in the two groups were compared against each other.

‡ In the pairwise analyses the twins in the two groups were compared against their co-twins (the number of twin pairs in the analysis comparing healthy cognition and cognitive impairment 124, number of twins in the analysis comparing twins with healthy cognition and mild cognitive impairment 468 in the age and the length of the follow-up adjusted model, and n= 120 and n= 426 in the final model).

§The final model was adjusted for age, follow-up, sex, binge drinking, education, hypertension, BMI and smoking (n=2927 for the whole cohort, n=2130 for the healthy individuals, n=120 for twin pairs discordant for cognition, and n=62 for healthy twin pairs at baseline who were discordant for cognition at the end of the follow-up).

|| The results that are statistically significant are printed in bold numbers.

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Table 4. β-estimates for total cognitive score according to persistence of vigorous physical activity and volume of physical activity in 1975 and 1981*

Persistence of vigorous physical activity * Volume of physical activity from 1975 and 1981 †

Level of physical activity in

1975 and 1981

Age, follow-up,

and sex

adjusted

Age, follow-up, sex,

binge drinking, and

education adjusted ‡

Final model § Age, follow-up, and

sex adjusted

Age, follow-up, sex,

binge drinking, and

education adjusted ‡

Final model §

β-estimate (95 % CI)

All (3050)

None (1282) 0.00 0.00 0.00 0.00 0.00 0.00

Change (850) 0.83 (0.37- 1.28) 0.51 (0.07- 0.94) 0.44 (0.00-0.87) 0.64 (-0.06- 1.34) 0.49 (-0.18- 1.16) 0.52 (-0.17- 1.21)

Persistent (918) 1.94 (1.49- 2.39) 1.08 (0.64- 1.51) 0.91 (0.47- 1.35) 1.68 (1.04- 2.32) 0.97 (0.35- 1.59) 0.85 (0.22- 1.48)

Healthy (2210)

None (815) 0.00 0.00 0.00 0.00 0.00 0.00

Change (629) 0.71 (0.21- 1.22) 0.45 (-0.03-0.93) 0.34 (-0.14- 0.83) 0.58 (-0.17- 1.33) 0.46 (-0.27- 1.18) 0.38 (-0.36- 1.12)

Persistent (766) 1.70 (1.20- 2.21) 1.01 (0.53- 1.49) 0.81 (0.33- 1.29) 1.38 (0.71- 2.05) 0.71 (0.06- 1.37) 0.47 (-0.20- 1.14)

* The three different groups according to persistence of vigorous physical activity (i.e. more strenuous than walking) were: no vigorous physical activity in 1975 or 1981 (none), vigorous physical activity in either 1975 or 1981 (change) and vigorous physical activity in both years (persistent).

† Volume of physical activity was measured in five quintiles of MET hours/day (MET = metabolic equivalent i.e. multiples of metabolic energy expenditure), calculated from the reported intensity, frequency, and duration of leisure physical activity and physical activity during work journeys. Further division into three groups was made to take into account two baseline measurements: firstly the ones belonging to MET quintile I (the least physically active quintile) in both years (labeled “none”), secondly the ones belonging to MET quintile I in 1975 but not in 1981 or vice versa (the “change” group), and thirdly the persistently active participants who did not belong to the MET quintile I in either year (the “persistent” group).

33

‡ In the model adjusted for education and binge drinking in addition to age, the length of follow-up, and sex, the number of participants was 2985 for the whole cohort and 2177 for the healthy participants at baseline.

§ The final model was adjusted for age, sex, follow-up, binge drinking, education, smoking, hypertension, and BMI (n=2927 for the whole cohort, n=2130 for the healthy participants at baseline).

|| The results that are statistically significant are printed in bold numbers.

34

Table 5. β-estimates for total cognitive score according to the mean MET from 1975 and 1981

35

Individual analyses * Pairwise analyses †

Level of

physical

activity ‡

Age, follow-up,

and sex

adjusted

Age, follow-up, sex,

binge drinking, and

education adjusted §

Final model || Level of physical

activity {

Unadjusted Binge drinking, education,

and the physical activity level

of the more inactive twin

adjusted §

Final model ||

β- estimate (95 % CI)

All All

(n=3050) 0.87 (0.51- 1.22) 0.41 (0.07- 0.76) 0.32 (-0.03- 0.67) (n= 994) -0.08 (-0.24- 0.09) -0.04 (-0.21- 0.13) -0.06 (-0.23- 0.11)

Healthy Healthy

(n=2210) 0.45 (0.07- 0.83) 0.09 (-0.27- 0.46) -0.07 (-0.45- 0.31) (n=603) -0.04 (-0.21- 0.14) -0.01 (-0.18- 0.16) -0.05 (-0.22- 0.13)

Monozygotic pairs

(n= 405) 0.15 (-0.21- 0.50) 0.15 (-0.21- 0.51) 0.18 (-0.19- 0.55)

Dizygotic pairs

(n= 570) -0.10 (-0.30- 0.09) -0.04 (-0.23- 0.16) -0.06 (-0.26- 0.14)

* In the individual analyses, individuals in the two groups were compared with each other.

† In the pairwise analyses the differences between twin pairs were analyzed.

‡ Log transformations of volume of physical activity measured in METs (metabolic equivalents of energy expenditure) from 1975, 1981, and from the mean MET from 1975 and 1981 where the MET index has first been added with 1 MET-h/d, then log transformed.

§ In the model adjusted for education, binge drinking, and the physical activity level of the more passive twin in the twin pair, in addition to age, the length of follow-up, and sex (n= 2985 for all, n= 2177 for the healthy participants), and in the paired model comparing differences between twin pairs and adjusting for binge drinking and education (n= 957 for all and n= 586 for healthy participants, n= 386 for monozygotic pairs, n= 553 for dizygotic pairs).

|| The final model was adjusted for age, sex, follow-up, binge drinking, education, smoking, hypertension, and BMI (n=2927 for all, n= 2130 for the healthy participants) and in the paired model comparing differences between twin pairs (n= 926 for all and n= 563 for the healthy participants, n= 375 for monozygotic pairs, n= 534 for dizygotic pairs) .

{ Difference of mean MET from 1975 and 1981 within twin pairs.

** The results that are statistically significant are printed in bold numbers.

36

Figure 1. Flowchart of the study

Figure 2. Odds ratios for cognitive impairment and mild cognitive impairment in the individual-based analyses of the volume of physical activity using the mean

MET index quintiles from 1981 and 1975 *, †

Figure 2A. Model adjusted for age, sex, and the length of follow-up ‡

Figure 2B. Final fully-adjusted model §

*The subjects are divided into five quintiles according to their mean MET index (hours/day) from years 1975 and 1981 (MET QI: < 0.66, MET QII 0.67-1.31, MET QIII 1.32-2.13, MET QIV 2.14-3.34, MET QV 3.34-

29).

† Black columns describe the odds ratios for cognitive impairment and gray columns describe the odds ratios for mild cognitive impairment.

‡ The number of subjects in the model adjusted for age, the length of the follow-up, and sex was 3050.

§ The number of subjects in the final model (adjusted for age, the length of the follow-up, sex, binge drinking, education, hypertension, smoking and BMI) was 2927.

37

38

39

40