Effects of cardiorespiratory fitness and cerebral blood flow on cognitive ...

Neurobiology of Aging 31 (2010) 2047–2057

Effects of cardiorespiratory fitness and cerebral blood flow on cognitive outcomes in older women Allison D. Brown a , Carly A. McMorris b , R. Stewart Longman c,d , Richard Leigh a,f , Michael D. Hill d,e,f,g , Christine M. Friedenreich h , Marc J. Poulin a,d,e,i,j,∗ a

j

Department of Physiology & Biophysics, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada b Department of Psychology, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada c Department of Psychology, Calgary Health Region, 1403 29th Street NW, Calgary, Alberta T2N 2T9, Canada d Hotchkiss Brain Institute, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada e Department of Clinical Neurosciences, Faculty of Medicine, 1403 29th Street NW, University of Calgary, Calgary, Alberta T2N 2T9, Canada f Department of Medicine, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada g Department of Community of Health Science, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada h Division of Population Health, Alberta Cancer Board, 1331 29th Street NW, Calgary, Alberta T2N 4N2, Canada i Faculty of Kinesiology, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 1N4, Canada Libin Cardiovascular Institute of Alberta, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada Received 13 August 2008; received in revised form 7 November 2008; accepted 13 November 2008 Available online 27 December 2008

Abstract The mechanisms by which aerobic fitness confers beneficial effects on cognition with aging are unclear but may involve cerebrovascular adaptations. In a cross-sectional study of women from the community (n = 42; age range = 50–90 years), we sought to determine whether physical fitness is associated with higher cerebrovascular function, and its relationship to cognition. Main outcome measures included resting ˙ 2 max) and cognition. Physically fit women had lower resting mean cerebral blood flow, cerebrovascular reserve, physical fitness (i.e., VO arterial pressure (MAP) and higher cerebrovascular conductance (CVC) than sedentary women. Overall cognition was negatively correlated ˙ 2 max. VO ˙ 2 max was a predictor of resting CVC and MAP, and CVC and MAP when end-tidal with age and positively correlated with VO gases were held constant at near-resting values. MAP and CVC were predictors of cognition. This study identified strong associations between physical fitness, vascular function and cognition, and provides new understanding regarding the mechanisms by which fitness positively impacts cognition with aging. The implications of this research are considerable and warrant future investigation. © 2008 Elsevier Inc. All rights reserved. Keywords: Cerebrovascular circulation; Women; Hypertension; Transcranial Doppler ultrasound; Aging; Exercise; Cognitive function

1. Introduction The cresting of the wave of baby boomers begins in 2011 as the first of the Silver Tsunami have their 65th birthdays, which will lead to a doubling of the proportion of the population over 65 years in the ensuing 25 years. Women ∗ Corresponding author at: Department of Physiology & Biophysics, Faculty of Medicine, University of Calgary, HMRB-212, 3330 Hospital Dr. NW, Calgary, Alberta T2N 4N1, Canada. Tel.: +1 403 220 8372; fax: +1 403 210 8420. E-mail address: [email protected] (M.J. Poulin).

0197-4580/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.neurobiolaging.2008.11.002

over the age of 80 are the fastest growing sub-group of this population. Many believe that they can expect to live the majority of their remaining years with moderate or severe dependence because of various chronic diseases. Furthermore, cognitive decline and dementia will reach epidemic proportions in western countries. The link between cerebrovascular disease and clinical dementia has been strongly supported by findings from the Nun study (Snowdon et al., 1997), which reported that patients with pathological findings of Alzheimer’s dementia have a much greater chance of showing clinical dementia if they have concurrent cerebral infarcts. Indeed, it is estimated that 5% of all persons age 65

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and older have vascular cognitive impairment (Rockwood et al., 2000). The notion that physical activity affects cognitive performance has been investigated for over 30 years (Diesfeldt and Diesfeldt-Groenendijk, 1977). However, despite the literature showing that physical activity has a favorable effect on cognition in older populations, the underlying mechanisms remain unknown. This important knowledge gap was recognized in the recent document a National Public Health Road Map to Maintaining Cognitive Health (CDCPAA, 2007) that included several recommendations about the need to understand the mechanisms by which physical activity promotes vascular and cognitive health. Aging is associated with a progressive decline in baseline cerebral blood flow that differs in men and women (Strandgaard, 1993; Yonas et al., 1993). In pre-menopausal women, the decline in cerebral blood flow with age is less pronounced than in men but is accelerated after menopause and persists into old age (Matteis et al., 1998). This biphasic phenomenon of cerebral blood flow changes in women might be explained by the beneficial effects of ovarian hormone modulation of cerebral blood flow before menopause, followed by a predominant influence of other factors thereafter. Aging is also associated with a decline in cognitive function and is associated with Alzheimer’s disease and vascular dementia (Albert et al., 1995). Physical inactivity is a modifiable risk factor for stroke (Gorelick et al., 1999; Rossouw et al., 2002). Conversely, physical activity has been shown to correlate with greater maintenance of cognitive ability, particularly executive control functions, with age (Kramer et al., 2003). More recently, cardiorespiratory fitness has been found to be associated with reduced brain atrophy in Alzheimer’s disease (Burns et al., 2008). However, the mechanisms whereby physical activity exerts a beneficial effect on the cerebral circulation and on cognition remain to be defined. Although little is known about the mechanisms of regulation in older humans, a recent study in young adults (Pereira et al., 2007) and recent studies in animals have provided compelling evidence for the role of vascular adaptations including angiogenesis (Black et al., 1990; Churchill et al., 2002), and the possible involvement of neurogenesis and synaptogenesis (Black et al., 1990; Pereira et al., 2007; Swain et al., 2003). In a 4-year prospective longitudinal study, it was found that those individuals who were physically inactive in the first 4 years of retirement showed significant declines in cerebral perfusion and general cognition while those individuals who continued to work or who were physically active maintained perfusion and general cognition (Rogers et al., 1990). However, the relation between cognitive function and changes in cerebrovascular reserve with age and physical fitness has not previously been investigated. We tested the hypotheses that being physically active would be associated with greater retention of cognitive function and cerebrovascular reserve than being sedentary, and that the relation between fitness and cognition has a vascular basis.

2. Methods A cross-sectional study design with detailed physiological assessment was used. Postmenopausal women aged 50–90 years were identified in the community through advertisements at the University of Calgary, Calgary Health Region, and in the general community. Eligibility criteria included: non-smokers, ability to perform moderate exercise, body mass index (BMI) ≤30 kg/m2 (thus, avoiding co-morbidities associated with obesity), normal spirometry, less than 20% stenoses of the carotid arteries, and no evidence of significant co-morbid disease or pharmacologic therapies, as determined by the study physician, that would interfere with their ability to exercise or with study outcomes. Specific exclusion criteria included heart and/or chest pains upon physical exertion; fainting spells/dizziness; recent surgery or major trauma ( 90% of age-predicted active and fit (defined by VO ˙ 2 max ≤ 90% of agevalues) or sedentary (defined by VO

predicted values) groups based on aged-predicted VO2 max values (Fitzgerald et al., 1997; Tanaka et al., 1997). General responses to sub-maximal exercise were evaluated by taking steady state means for the baseline period (2 min average), during steady-state exercise (15 s average) and the recovery period (15 s average). Descriptive statistics were performed on all variables. First, product–moment correlation coefficients were estimated to determine the strength of the associations between age, fitness, vascular measures and cognition. Data were initially examined for normality before being analyzed using analysis of co-variance (ANCOVA). Correlations and ANCOVAs controlled for important potential confounding factors (e.g., age, education, body fat, blood pressure and ovarian hormones). Moreover, linear regressions were completed to determine the extent to which physical fitness (i.e., VO2 max) was a predictor of vascular health. These analyses were unadjusted for age. Finally, multiple linear regressions were completed to determine potential predictors of vascular function and cognition. These analyses included age and free testosterone as covariates in the models because they have been shown to be important factors affecting cognition. Only main effects were considered. Education was initially included but not found to have a significant influence on any of the cognitive outcomes and was subsequently excluded from further models. Two-sided tests and a criterion alpha of 0.05 were adopted for all analyses.

3. Results A call for volunteers resulted in 161 inquiries. From this group, 51 women were screened of which 9 women were excluded. Forty-two completed the full study protocol. The mean (S.D.) age was 65.1 (8.4) years. Descriptive data for the sample are presented in Table 1. All women in the active group undertook regular aerobic exercise and all but one woman in the sedentary group did not undertake regular aerobic exercise. The criteria for achieving VO2 max included a leveling of oxygen uptake despite an increase in workload and a respiratory exchange ratio (RER) > 1.05. In total 34/41 women (83%) achieved these criteria (Table 1). Women in the active group had a lower resting MAP compared with those in the sedentary group (69.1 (9.3) mmHg vs. 77.4 (14.5) mmHg, p = 0.015). MAP was also lower in the active group during submaximal exercise (Fig. 1). Women in the active group also had a lower resting MAP compared with women in the sedentary group during hypercapnia (8 Torr; 87.4 (1.9) mmHg vs. 95.5 (3.8) mmHg, p = 0.015)(Fig. 1). Younger women had lower baseline MAP compared to the old group (85.9 (12.3) mmHg vs. 89.1 (12.0) mmHg, p = 0.016) but this difference in age-specific results was not found during sub-maximal exercise or during recovery from exercise. MAPREST was negatively correlated with VO2 max (r = −0.414, p = 0.028).


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Table 1 Physical characteristics of study subjects, Alberta, Canada, 2006–2007.

Age (years) Height (cm) Weight (kg) Body mass index (kg/m2 ) Body fat (%) Waist:hip ratio FVC (l) FEV1 (l) ˙ 2 max relative (ml kg−1 min−1 ) VO ˙ 2 max absolute (l min−1 ) VO ˙ 2 max percent predicted (%) VO ˙ 2 max RER at completion of the VO RPE (Borg scale) Physical activity (met h week−1 year−1 ) Estradiol (pmol l−1 ) Progesterone (nmol l−1 ) Sex hormone binding globulin (nmol l−1 ) Albumin (g l−1 ) Testosterone (nmol l−1 ) Free testosterone (pmol l−1 )

Overall

By age groups

n = 42

Young n = 21

65.1 ± 8.4 161.3 ± 6.0 66.7 ± 10.0 25.6 ± 3.7 36.5 ± 5.3 0.79 ± 0.05 3.1 ± 0.6 2.4 ± 0.4 25.6 ± 5.6 1.67 ± 0.3 101.2 ± 22.6 1.16 ± 0.11 16.4 ± 2.7 81.2 ± 47.6 25.7 ± 37.4 1.3 ± 0.5 52.1 ± 25.0 42.8 ± 2.7 0.81 ± 0.59 11.9 ± 9.9

58.3 161.7 69.0 26.4 37.5 0.79 3.32 2.57 26.0 1.75 91.6 1.21 17.5 72.9 38.9 1.6 42.2 43.3 0.76 12.6

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

4.2 6.3 11.3 3.8 4.8 0.05 0.5 0.4 6.1 0.3 21.8 0.11 2.3 45.7 44.7 0.4 17.2 2.7 0.74 12.8

By fitness groups Old n = 21 72.0 161.0 64.3 24.9 35.6 0.79 2.89 2.09 25.1 1.59 111.9 1.11 15.4 95.1 11.7 1.0 62.0 42.6 0.86 11.2

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

5.3* 5.8 8.1 3.4 5.7 0.05 0.5* 0.3* 5.2 0.3 18.8* 0.09* 2.8 48.3* 23.6 0.5* 28.0 2.5* 0.44 6.1

Fit n = 28 66.1 160.8 62.8 24.3 34.7 0.78 3.13 2.34 28.0 1.75 112.7 1.17 16.7 98.3 21.8 1.3 57.7 43.5 0.73 9.9

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

Sedentary n = 13 8.4 5.8 7.0 3.0 4.7 0.05 0.6 0.5 4.7 0.3 15.4 0.10 2.7 48.3 41.4 0.5 26.8 2.7 0.47 7.1

62.3 161.5 74.9 28.7 40.8 0.81 3.05 2.36 20.0 1.49 74.5 1.16 16.2 48.5 32.9 1.4 42.4 41.3 0.95 15.2

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

7.7 6.1 10.9† 3.4† 4.3† 0.06 0.5 0.4 3.0† 0.2† 11.0† 0.13 2.8 20.5† 28.6 0.6† 16.9† 2.3† 0.77 13.2

Values represent mean ± standard deviation. Age groups were defined as young (50–64 years) and old (65–90 years), fitness groups were defined as fit (>90% age predicted VO2 max) and sedentary (≤90% age predicted VO2 max). Abbreviations: FVC, forced vital capacity; FEV1 , forced expiratory volume in 1 s; VO2 max, maximal oxygen consumption; RER, respiratory exchange ratio, the ratio of carbon dioxide production to oxygen consumption; RPE, rating of perceived exertion. * Significantly different from young group by p ≤ 0.01. † Significantly different from fit group by p ≤ 0.01.

CVCREST was positively correlated with VO2 max (r = 0.50, p = 0.006). CVC was higher in the active group compared to the sedentary group at baseline (0.68 (0.19) cm s−1 mmHg−1 vs. 0.65 (0.15) cm s−1 mmHg−1 ),

p = 0.010), during sub-maximal exercise (0.62 (0.15) cm s−1 mmHg−1 vs. 0.59 (0.12) cm s−1 mmHg−1 , p = 0.017) and with recovery (0.63 (0.15) cm s−1 mmHg−1 vs. 0.62 (0.12) cm s−1 mmHg−1 , p = 0.014). During isocapnia and

Fig. 1. Vascular responses to sub-maximal exercise and hypercapnia in sedentary (open circles; n = 12) and physically active and fit (solid circles; n = 26) women. p-Values represent between-group differences at each time point and error bars represent S.D. Abbreviations: MAP, mean arterial pressure (mmHg); CVC, cerebrovascular conductance (cm s−1 mmHg−1 ); isocapnia, end-tidal PCO2 = +1 Torr above resting values; HC + 5, end-tidal PCO2 = +5 Torr above resting values; HC + 8, end-tidal PCO2 = +8 Torr above resting values.

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hypercapnia, CVC was higher in the active group compared with the sedentary group (8 Torr; 0.88 (0.04) cm s−1 mmHg−1 vs. 0.83 (0.04) cm s−1 mmHg−1 , p = 0.004) (Fig. 1). The old group had a higher CVCREST than the young group (0.99 (0.19) cm s−1 mmHg−1 vs. 0.97 (0.20) cm s−1 mmHg−1 , p = 0.016). CVC was negatively correlated with age during all portions of the sub-maximal exercise test for baseline (r = −0.49, p = 0.006), exercise (r = −0.389, p = 0.034) and recovery (r = −0.46, p = 0.011). Resting CVC and MAP are considered indicators of vascular health and aging (Dastur, 1985; Lautt, 1989). Thus, the effect of fitness (i.e., VO2 max) was examined on resting and isocapnic MAP and CVC. VO2 max predicted both CVCREST and MAPREST . VO2 max also predicted MAPISO and CVCISO (Table 2). The primary outcome, cognitive function, was negatively correlated with age (r = −0.39, p = 0.012) (Fig. 2). Cognitive function scores were higher in the young group compared to the old group (4.28 (11.6) vs. −4.12 (11.2) relative score, p = 0.001) when controlling for the co-variables of education and physical fitness (i.e., VO2 max) (Fig. 2). Similar relations were found in the domains of cognitive speed, perception, verbal ability and executive function. Both testosterone and free testosterone were negatively correlated with overall cognitive function (r = −0.45, p = 0.011 and r = −0.34, p = 0.038, respectively). Testosterone and free testosterone were negatively correlated with cognitive speed, perception and executive function. Estrogen

Table 2 Predictive model correlation coefficients and p-values for outcomes of physical fitness and vascular health, Alberta, Canada, 2006–2007. Model outcome variable

r

p-Value

CVCREST MAPREST MAPISO CVCISO

0.514 0.399 0.331 0.533

0.004 0.018 0.042 0.002

Results from regression analyses indicating that fitness is a predictor of vascular health. Resting CVC and MAP have previously been shown to be good measures of vascular aging (see Dastur, 1985; Lautt, 1989). Therefore, the effect of fitness was examined on these parameters. Statistical models (linear regressions) were developed in which VO2 max (ml kg−1 min−1 ) was used as the index of fitness. Regression equations are below: CVCREST = (0.019) × VO2 max + 0.482; MAPREST = (−0.837) × VO2 max + 93.101; MAPISO = (−0.704) × VO2 max + 98.431; CVCISO = (0.016) × VO2 max + 0.325. Abbreviations: CVCREST , resting cerebrovascular conductance (cm s−1 mmHg−1 ); MAPREST , resting mean arterial blood pressure (mmHg); MAPISO , resting mean arterial blood pressure (mmHg) when end-tidal PCO2 and PO2 are regulated near resting values (i.e., isocapnia and euoxia); CVCISO , CVC during isocapnia and euoxia; VO2 max, maximal oxygen consumption (ml kg−1 min−1 ); r, correlation coefficient. The general form of the mathematical equations is Y = bX + a, where b is the regression coefficient, X is VO2 max, and a is the regression constant.

and progesterone were not correlated to overall cognition or any of the component domains of cognition. Cognitive function was correlated with VO2 max (r = 0.41, p = 0.008) (Fig. 2). Cognitive function was higher in the

Fig. 2. Relation between overall cognition, age and physical fitness. Overall cognitive score was derived by converting each domain score into a Z-score, and summing these, equally weighting each domain. Scores are performance relative to the entire cohort. Cognition has a negative relationship with age and is higher in young women. Cognition has a positive relationship with physical fitness and is higher in physically active and fit women. Error bars represent S.D. Abbreviation: VO2 max, maximal oxygen consumption.


active group compared with the sedentary group (1.63 (11.7) vs. −2.47 (12.3) relative score, p = 0.007) when controlling for education and age (Fig. 2). Similar relations were found in the cognitive domains of cognitive speed (r = 0.391, p = 0.013; 0.49 (2.97) vs. −0.59 (3.46) relative score for active and sedentary groups, respectively, p = 0.014), verbal ability (r = 0.300, p = 0.060; 0.25 (1.41) vs. −0.58 (2.26) relative score for active and sedentary groups, respectively, p = 0.030), perception (r = 0.351, p = 0.026; 0.03 (1.51) vs. −0.05 (1.63) relative score for active and sedentary groups, respectively, p = 0.003) and executive function (r = 0.304, p = 0.056; 0.31 (3.44) vs. −0.65 (3.78) relative score for active and sedentary groups, respectively, p = 0.071). As VO2 max was shown to be a predictor of vascular health (i.e., MAP and CVC) and also to be a predictor of cognitive function, we reasoned the positive association between fitness (i.e., VO2 max) and cognition may have a cerebrovascular basis. Thus, MAP and CVC were selected as measures of vascular health to examine the affects on cognitive function. While CVCREST and MAPREST were not predictors of overall cognitive function or any of the cognitive domains, MAPISO was a predictor of overall cognitive function (p = 0.001, r = 0.657), cognitive speed (p ≤ 0.001, r = 0.702, ES = 2.0), verbal memory (p = 0.015, r = 0.493) and attention (p = 0.002, r = 0.535). CVCISO was similarly a predictor of overall cognitive function (p = 0.004, r = 0.594). MAPREST and MAPISO as well as CVCREST and CVCISO were examined as possible predictors of cognitive function as they were shown by linear regression to be predicted by VO2 max (Table 2). Cognitive function was predicted by both MAPISO and CVCISO . Cognitive speed was predicted by all of the vascular variables (MAPREST , MAPISO , CVCREST and CVCISO ) (Table 3). Verbal ability was predicted by CVCISO and MAPREST , whereas verbal memory was predicted by MAPISO and MAPREST . Visual memory was only predicted by CVCISO (Table 3).

4. Discussion 4.1. Major ﬁndings This human physiology study has identified strong and significant associations between physical fitness and cognition, physical fitness and cerebrovascular function that persist after controlling for important factors such as age, and provides new evidence to support the idea that the beneficial effects of physical fitness on cognition are mediated, at least in part, at a macrovascular level. Novel findings include: (1) an increase in cerebrovascular conductance with fitness, suggesting that the vascular benefits that have been reported previously in the systemic circulation are also conferred to the brain; (2) the independent prediction of both mean arterial pressure and cerebrovascular conductance by VO2 max, suggesting that fitness may have some protective affects on the vasculature; (3)

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cerebrovascular conductance and mean arterial pressure are significant predictors of cognitive functioning. The finding of a negative association of aging and cognition, and a positive association of fitness and cognitive function are consistent with previous findings (Colcombe et al., 2004; Emery et al., 1995; Kramer et al., 2003, 2006; Lautenschlager and Almeida, 2006; Young, 1979). It has previously been shown that testosterone levels in women are negatively correlated with cognitive function tests that tend to show a female advantage (Schattmann and Sherwin, 2007b; Thilers et al., 2006). While recent studies (Schattmann and Sherwin, 2007a,b) have suggested that free testosterone may be a superior index of testosterone as it represents unbound and therefore bioavailable levels, this study found similar relations between both free testosterone and total testosterone and cognition. The findings from this study suggest that this negative influence of testosterone (i.e., either total or free testosterone) has broader negative impact on cognition in postmenopausal women than previously thought. The expected beneficial consequence of physical fitness on blood pressure and the increasing pressure with age were found. It is known that MAP is lower in younger and fitter people (Davies and Daggett, 1977; Fleg et al., 1995; Martin et al., 1991; Wolfe et al., 1985) and that cerebrovascular resistance increases with aging (Naritomi et al., 1979). However, a novel finding in this study is that resting CVC is higher in active compared with sedentary women and this may represent a different cerebrovascular set-point at rest. It is also interesting to note that the CVC responses to submaximal exercise and to the hypercapnic stimulus in the active and fit group are shifted upward compared with the responses in sedentary group. However, during submaximal exercise the magnitude of the changes in CVC are comparable (i.e., parallel lines) in both groups. During hypercapnia, when the brain’s requirement for increased blood flow is significant, CVC is higher in the fit and active group. Future research is required to investigate whether the observed differences at rest and during increased cerebrovascular demands might be explained by factors such as increases in endothelial function and nitric oxide bioavailability, and decreases in vascular oxidative stress. A second novel finding is that VO2 max independently predicts both MAP and CVC. Collectively, these findings support the hypothesis that fitness predicts cerebrovascular health. While resting CVC and MAP were not significant predictors of cognitive functioning, both CVC and MAP during isocapnia were. In this study, isocapnia represented a one-unit increase of end-tidal PCO2 above the resting level, and it is possible that this control over end-tidal PCO2 helps reveal relations not apparent during resting measurements because of natural breath by breath fluctuations in resting end-tidal PCO2 . This interpretation is supported by prior work showing that holding end-tidal PCO2 constant slightly above resting values decreases cerebral blood flow variability by 18% (Harris et al., 2006).

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Table 3 Predictive model parameters and outcomes of vascular health and cognitive function, Alberta, Canada, 2006–2007. Model outcome Variable Overall cognitive function Overall MAPISO Age Free T Constant Overall cognitive function Overall CVCISO Age Free T Constant Cognitive speed Overall MAPISO Age Free T Constant Cognitive speed Overall MAPREST Age Free T Constant Cognitive speed Overall CVCISO Age Free T Constant Cognitive speed Overall CVCREST Age Free T Constant

r

r2

p-value

B

0.613

0.375

0.002 0.013 0.005 0.037 0.001

−0.433 −0.693 −0.358 83.303

0.059 0.175 0.119 0.081 0.354

17.434 −0.426 −0.349 19.206

0.000 0.001 0.001 0.007 0.000

−0.137 −0.192 −0.112 24.682

0.004 0.141 0.038 0.015 0.003

−0.061 −0.143 −0.118 15.251

0.008 0.028 0.079 0.040 0.453

7.157 −0.119 −0.102 3.819

0.020 0.056 0.088 0.043 0.391

5.569 −0.136 −0.116 5.260

0.496

0.697

0.585

0.599

0.585

0.246

0.486

0.343

0.359

0.342

S.E. of estimate

95% confidence interval lower-bound

95% confidence interval upper-bound

−0.769 −1.158 −0.691 39.022

−0.097 −0.229 −0.024 127.585

−8.259 −0.971 −0.743 −22.584

43.127 0.118 0.046 60.996

−0.218 −0.303 −0.192 14.085

−0.057 −0.081 −0.033 35.278

−0.144 −0.279 −0.213 5.686

0.021 −0.008 −0.024 24.817

0.819 −0.254 −0.199 −6.489

13.494 0.015 −0.005 14.126

−0.156 −0.293 −0.229 −7.172

11.294 0.022 −0.004 17.692

9.60173

10.27665

2.29767

2.62434

2.53477

2.67570

Results from regression analyses indicating that vascular health is a predictor of cognition. Cognitive function is known to decrease with age (See Kramer et al., 2006) and free testosterone is also known to be correlated with cognitive abilities (see Thilers et al., 2006).Our own pilot study shows that fitness is a predictor of vascular health (i.e., Table 1). A statistical model (multiple linear regression) was developed in which an index of vascular health, age and free testosterone where used to predict cognitive function. Equations with similar statistical outcomes were developed for verbal memory and attention (not shown here). Mathematical equations are below: overall cognitive function = MAPISO × (−0.433) + age × (−0.693) + Free T × (−0.358) + 83.303; overall cognitive function = CVCISO × (17.434) + age × (−0.426) + Free T × (−0.349) + 19.206; cognitive speed = MAPISO × (−0.137) + age × (−0.192) + Free T × (−0.112) + 24.682; cognitive speed = MAPREST × (−0.061) + age × (−0.143) + Free T × (−0.118) + 15.251; cognitive speed = CVCISO × (7.157) + age × (−0.119) + Free T × (−0.102) + 3.819; cognitive speed = CVCREST × (5.569) + age × (−0.136) + Free T × (−0.116) + 5.260. Abbreviations: MAPISO , resting mean arterial blood pressure (mmHg) when end-tidal PCO2 and PO2 are regulated near resting values (i.e., isocapnia and euoxia); CVCISO , resting cerebrovascular conductance (cm s−1 mmHg−1 ) when end-tidal PCO2 and PO2 are regulated near resting values; Age, age in years; Free T, free testosterone (pmol l−1 ); r, correlation coefficient; r2 , coefficient of determination; B, regression coefficients; S.E., standard error.

4.2. Biological mechanisms The negative relations between the various indices of cognition and both MAP and CVC are remarkable. It has been shown that hypertensive subjects have impaired cognition compared to normal controls (Mazzucchi et al., 1986) and that this finding persists in treated hypertensives medically maintained in a normotensive range (Sacktor et al., 1999). Hypertension also leads to increased risk of both vas-

cular dementia and mixed vascular-Alzheimer’s dementia (Birkenhager and Staessen, 2006). Despite the strong relations between hypertension and cognitive function it has not been previously demonstrated that higher blood pressure in a normotensive population is associated with poorer cognitive function. However, blood pressure and hypertension have previously been found to be related to cerebral white matter lesions, which in turn are associated with lower scores on cognitive function tests (Breteler et al., 1994), lower cogni-


tive reserve (Burns et al., 2005), and particular declines in the cognitive domains of processing speed, immediate and delayed memory, executive function, and overall cognitive function (Gunning-Dixon and Raz, 2000). Taken together, these findings suggest common lesion patterns with aging. There are a number of ways by which physical activity may be acting through vascular mechanisms to either benefit or impair cognitive function. It has been shown that regular exercise is associated with a chronic increase in vascular perfusion in the rat brain (Swain et al., 2003). This study also suggested that exercise may lead to recruitment of capillaries from either a ‘brain capillary reserve’ or from new capillaries formed as a direct result of exercise (Swain et al., 2003). Recently, neurogenesis and enhanced survival of existing neurons, particularly in the hippocampus, have been implicated as potential mechanisms. For instance, it has been found that a number of neurotrophins such as brain-derived neurotrophic factor (BDNF) and vascular endothelial growth factor (VEGF) are elevated with exercise (Churchill et al., 2002). Exercise also results in the stimulation of angiogenesis, primarily the growth of new capillaries from vessels in the brain (Black et al., 1990; Churchill et al., 2002). These data suggest that the brain’s vascularity is highly plastic throughout the lifespan, and manipulations that may increase brain vascularization may be effective strategies in reducing or delaying age-related cognitive impairments (Churchill et al., 2002).

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are subject to problems of reverse causality. A prospective intervention study would allow a definitive understanding of the magnitude and direction of effect on cognitive function. Another limitation of our study was the inclusion of a volunteer sample. The selection of subjects is biased in favor of those with higher VO2 max because a lower VO2 max is associated with loss of independence later in life (Paterson et al., 2004), and hence a reduced likelihood of volunteering for such a study. Third, our study sample was predominantly Caucasians of European descent and our findings cannot be readily generalized to different ethnic or racial groups. However, we do not think that these limitations are likely to have substantially altered our study outcomes, and believe that our findings remain broadly pertinent to the vast majority of postmenopausal women in North America. 4.5. Summary In conclusion, this study provides novel evidence that aerobic fitness contributes to the maintenance of healthy brain function throughout the aging process. The implications of this research are considerable and warrant future investigation given the aging population and the magnitude of the burden that this segment of the population has, and will increasingly have, on health care systems.

Conﬂict of interest 4.3. Clinical relevance No conflicts of interests for this study. A major strength of this study is the precision of physiological measurements in our human physiology laboratory, including accurate and continuous control of the end-tidal (i.e., arterial) PO2 and PCO2 , the ability to assess VO2 max and cerebrovascular health outcomes with high temporal resolution, and a comprehensive battery of cognitive function. Our findings indicate that physically active women are more likely to maintain better cognitive function with age than their sedentary counterparts. The large effect sizes in this study underscore the fact that the results are not only statistically significant but also clinically relevant. Furthermore, the larger effect sizes for vascular health (i.e., MAPISO , CVCISO ) compare to those for fitness (i.e., VO2 max) and age emphasize important underlying relations between vascular health and cognition. Currently, exercise rehabilitation programs are popular in clinical practice as part of comprehensive therapy for the treatment of many chronic diseases (COPD, cardiopulmonary and renal diseases, diabetes, etc.), and this study provides compelling evidence of an additional benefit from being physically active or physically fit. 4.4. Limitations Our study has several limitations. First, because of the cross-sectional design, we cannot establish causal relations between exercise, fitness and cognition. Further, such designs

Acknowledgements We are grateful to all the volunteers for their cheerful and dedicated participation to this study. We also thank Dr. Todd Anderson, Mr. Michael Kimm and Mr. Andrew Beaudin for assistance with data collection and analysis, and Ms. Linda Brigan for administrative support. We also thank Dr. Tak Fung, Dr. Bradley Goodyear and Dr. David Hogan for helpful discussions. This study was supported by an Establishment Grant from the Alberta Heritage Foundation for Medical Research (AHFMR; Dr. Poulin); by a Grant-in-Aid from the Heart and Stroke Foundation of Alberta, NWT & Nunavut (Dr. Poulin); by a New Opportunities Funding Award from the Canadian Foundation for Innovation (Dr. Poulin); by fulltime studentships from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the AHFMR (Ms. Brown); by the Calgary Health Region (Dr. Longman); by a CIHR Clinician-Scientist (Phase 2) Award, an AHFMR Clinician Investigator Award and a Glaxo-Smith-Kline-CIHR Professorship in Inflammatory Lung Disease (Dr. Leigh); by an AHFMR Health Scholar Award and a Heart and Stroke Foundation of Alberta, Northwest Territories and Nunavut Research Scholarship (Dr. Hill); by a CIHR New Investigator

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Award and an AHFMR Health Scholar Award (Dr. Friedenreich); and by a CIHR New Investigator Award, an AHFMR Senior Medical Scholar Award and the Strafford Foundation (Dr. Poulin). Author Contributions: Study concept: Poulin. Study Design: Brown, McMorris, Longman, Friedenreich and Poulin. Acquisition of data: Brown, McMorris, Leigh and Poulin. Analysis and interpretation of data: Brown, McMorris, Longman, Hill, Friedenreich and Poulin. Drafting of the manuscript: Brown and Poulin. Critical revision of the manuscript for important intellectual content: Brown, McMorris, Longman, Leigh, Hill, Friedenreich and Poulin. Statistical analysis: Brown, Longman, Hill, Friedenreich and Poulin. Obtained funding: Poulin. Administrative, technical and material support: Leigh and Poulin. Study supervision: Friedenreich, Longman, Leigh and Poulin.

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