Distribution of cardiac output to the brain across the adult lifespan

Abstract

A widely accepted dogma is that about 15–20% of cardiac output is received by the brain in healthy adults under resting conditions. However, it is unclear if the distribution of cardiac output directed to the brain alters across the adult lifespan and is modulated by sex or other hemodynamic variables. We measured cerebral blood flow/cardiac output ratio index in 139 subjects (88 women, age 21–80 years) using phase-contrast magnetic resonance imaging and echocardiography. Body mass index, cardiac systolic function (eject fraction), central arterial stiffness (carotid-femoral pulse wave velocity), arterial pressure, heart rate, physical fitness (VO₂ max), and total brain volume were measured to assess their effects on the cardiac output–cerebral blood flow relationship. Cerebral blood flow/cardiac output ratio index decreased by 1.3% per decade associated with decreases in cerebral blood flow (P < 0.001), while cardiac output remained unchanged. Women had higher cerebral blood flow, lower cardiac output, and thus higher cerebral blood flow/cardiac output ratio index than men across the adult lifespan. Age, body mass index, carotid-femoral pulse wave velocity, and arterial pressure all had negative correlations with cerebral blood flow and cerebral blood flow/cardiac output ratio index (P < 0.05). Multivariable analysis adjusted for sex, age showed that only body mass index was negatively associated with cerebral blood flow/cardiac output ratio index (β = −0.33, P < 0.001). These findings demonstrated that cardiac output distributed to the brain has sex differences and decreases across the adult lifespan and is inversely associated with body mass index.

Introduction

The brain is the most energy-demanding organ in the body with a high metabolic rate for oxygen and glucose utilization. The structural and functional integrity of the brain relies on a delicate balance of neurovascular coupling between the substrate delivery through brain perfusion and the energy demand imposed by sustained neural activity.¹ A widely accepted dogma has been that approximately 15–20% of the cardiac output (CO) is distributed to the brain in healthy adults under resting conditions²; however, few studies have been conducted to determine whether the distribution of CO directed to the brain alters across the adult lifespan and is influenced by systemic and/or cerebral hemodynamic factors such as physical fitness level, cardiac function, and arterial stiffness.

Previous studies have documented that cerebral blood flow (CBF) decreases with aging, which has been attributed to a decrease in brain metabolic rate and/or increase in cerebrovascular resistance (CVR).^3–5 However, whether CO changes with aging is unclear; and the presence or absence of cardiovascular disease or other confounding factors such as individual variability of physical activity or body mass index (BMI) may have contributed to the inconsistent observations of age-related changes in CO.^6–9 In addition, most studies have been focused on the effects of aging on CO or CBF separately and did not measure them concurrently in the same subjects^10,11; therefore, the influences of age or other potential covariates on the CO-CBF relationship remain unknown.

Sex differences in both CO and CBF have been observed^5,12–14; recent studies also showed that obesity is negatively associated with brain perfusion and function.^15–17 Conversely, physical activity may attenuate age-related CBF decline as indicated by a positive association between maximal oxygen uptake (VO₂ max) and CBF.^18–20 Finally, cardiac contractility, central arterial stiffness, and arterial blood pressure all may affect the CO-CBF relationship through either cardiovascular or neurovascular coupling.^21–23

The purpose of this study was to determine the impact of age and sex as well as systemic and cerebral hemodynamic variables on the distribution of CO directed to the brain as measured by the CBF/CO ratio index (CCRI) in healthy subjects across the adult lifespan.

Methods

Participants

One hundred and thirty-nine healthy participants aged between 21 and 80 years (88 women; 85% Caucasian, 9% African American, 6% Asian) were recruited through study flyers and newspaper advertisements from the Dallas-Fort Worth metroplex. Exclusion criteria included pathophysiological conditions, which may have significant impact on the CO-CBF relationship: the presence of ischemic or structural heart disease (screened using 12-lead electrocardiogram and echocardiography), high blood pressure > 140/90 mmHg (measured using 24-h ambulatory blood pressure), carotid artery atherosclerotic plaque or stenosis (occlusion of the common and/or internal carotid artery by > 50% by ultrasound),²⁴ diabetes (screened by the presence of symptoms, using antidiabetic drugs or fasting glucose > 126 mg/dL), BMI > 35 kg/m², smoking, and the presence or history of cerebrovascular (e.g. stroke), neurologic, psychiatric, or inflammatory diseases, brain damage or trauma, hypothyroidism, active alcohol, or drug abuse. Pregnant or breast-feeding women and individuals who participated in regular exercise training were also excluded. This study was approved by the Institutional Review Board of the University of Texas Southwestern Medical Center and Texas Health Presbyterian Hospital Dallas and was performed in accordance with the guidelines of the Declaration of Helsinki and Belmont Report. A written informed consent was signed by all subjects for study participation.

Data collection

Measurement of CO and CBF

Subjects abstained from caffeinated beverages, alcohol, and vigorous exercise at least 12 h before the study and rested in the supine position for ≥ 10 min before data collection. All subjects were examined using two-dimensional transthoracic echocardiography (CX-50, Phillips Healthcare) by an experienced sonographer. Cardiac ejection fraction (EF) was calculated as: (end-diastolic volume − end-systolic volume)/(end-diastolic volume). Left ventricular volumes were determined using the modified Simpson’s rule according to the recommended guidelines.¹² CO was calculated as: (end-diastolic volume − end-systolic volume) × heart rate.

Phase-contrast magnetic resonance imaging (PC-MRI) was used to measure blood flow from the bilateral internal carotid arteries (ICA) and vertebral arteries (VA) using a 3 T scanner (Philips Medical Systems, Best, The Netherlands) with an eight-channel transmit/receive head coil. PC-MRI data were analyzed using the region of interest method.²⁵ Total brain volume (TBV) was obtained as a sum of the cerebrum, cerebellum, and brain stem volume using FreeSurfer based on T1-weighted magnetization-prepared rapid gradient-echo images.⁵ The imaging protocols and the data analysis methods used for PC-MRI and brain volume calculation have been described in detail previously.^5,25 CBF was obtained as a sum of the blood flow from the four arteries of the ICA and VA. CCRI was calculated as the percentage of CBF to CO.

Measurement of arterial stiffness, systemic hemodynamics, and physical fitness

Carotid-femoral pulse wave velocity (cfPWV) was measured using applanation tonometry (SphygmoCor 8.0, AtCor Medical) to assess central arterial stiffness.²⁶ Intermittent brachial blood pressure was measured using an ECG-gated electrosphygmomanometer (Suntech, Morrisville, NC, USA), averaged from at least three measurements to obtain systolic (SBP), diastolic (DBP), and mean blood pressures (MAP). Heart rate was monitored using a three-lead ECG (Hewlett-Packard, Palo Alto, CA, USA). CVR was estimated as MAP divided by CBF. Ambulatory blood pressure was measured on the nondominant arm for ≥ 24 h using a noninvasive oscillometric blood pressure monitor (SunTech Medical Instruments, Morrisville, NC) and data were reported as the average blood pressure over 24 h. A modified Astrand-Saltin incremental treadmill protocol was used to measure VO₂ max to determine physical fitness according to the ACSM guidelines.^27,28

Statistical analysis

We first compared three age groups separated by sex: young (21–45 years), middle age (46–65 years), and old (66–80 years). Two-way analysis of variance (ANOVA) was used to examine the main and interaction effects of age and sex on demographic and physiologic variables. Chi-squared test was used to test group differences in categorical variables. Next, the Pearson’s product moment correlation was used to examine simple correlations between the measured variables. Multiple linear regression was further used to determine the relationship between age and CCRI after adjustment for covariates. In the model, sex and age were first included sequentially. Curve linear effect of age was examined by entering age-squared (age²), which was excluded later because it did not have a significant impact on CCRI over the linear effect of age. Stepwise method was subsequently used to identify significant covariate(s) of CCRI. Age- and sex-adjusted partial correlation plot of CCRI was created using standardized residuals (Z score). A two-tailed P < 0.05 was considered statistically significant. All data were reported as mean ± standard deviation unless otherwise stated. Data were analyzed with SPSS 20.0 (SPSS, Inc, Chicago, IL).

Results

Participant characteristics

Table 1 summarizes subject demographic and physiologic characteristics grouped in age and sex. Compared with men, women had lower BMI, CO, SBP, DBP, VO₂ max, TBV, and CVR; but higher CBF and EF. BMI, cfPWV, SBP, PP, and CVR all increased with age, while VO₂ max and TBV decreased with age (Tables 1 and 2).

Table 1.

Subject characteristics.

	Young (21–45 years)		Middle age (46–65 years)		Old (66–80 years)		P-value
	Men	Women	Men	Women	Men	Women	Age Group	Sex	Interaction
N	17	24	19	40	15	24		0.617
Age (years)	33 ± 7	32 ± 7	54 ± 6	60 ± 5	70 ± 3	72 ± 4	<0.001	0.055	0.019
Height (cm)	176 ± 7	162 ± 7	177 ± 7	164 ± 10	176 ± 5	161 ± 4	0.398	<0.001	0.821
Weight (kg)	81.3 ± 8.9	60.6 ± 8.6	88.1 ± 14.1	70.2 ± 10.0	85.6 ± 9.0	66.1 ± 7.5	0.001	<0.001	0.802
BMI (kg/m2)	26.2 ± 3.1	23.1 ± 3.2	28.0 ± 3.2	26.2 ± 4.3	27.8 ± 3.2	25.5 ± 3.1	0.004	<0.001	0.676
CO (L/min)	3.94 ± 0.81	3.51 ± 0.63	3.93 ± 0.72	3.66 ± 0.62	4.13 ± 0.97	3.50 ± 0.59	0.829	0.001	0.485
CBF (mL/min)	551 ± 111	724 ± 112	495 ± 114	580 ± 160	475 ± 130	496 ± 118	<0.001	<0.001	0.040
CCRI (%)	14.8 ± 5.3	21.3 ± 5.6	13.0 ± 3.7	16.4 ± 5.5	11.7 ± 2.9	14.8 ± 5.5	<0.001	<0.001	0.264
EF (%)	57 ± 7	61 ± 6	59 ± 8	61 ± 7	59 ± 6	63 ± 8	0.480	0.004	0.663
cfPWV (m/s)	7.8 ± 0.8	6.7 ± 0.8	9.3 ± 1.5	9.4 ± 1.6	10.9 ± 2.2	11.0 ± 2.1	<0.001	0.287	0.166
Brachial SBP (mmHg)	115 ± 8	103 ± 8	114 ± 14	113 ± 9	118 ± 12	118 ±  13	0.001	0.038	0.033
Brachial MAP (mmHg)	87 ± 8	79 ± 7	89 ± 11	87 ± 8	89 ± 7	89 ± 10	0.005	0.013	0.079
Brachial DBP (mmHg)	72 ± 8	63 ± 6	74 ± 9	69 ± 8	71 ± 6	68 ± 8	0.068	<0.001	0.276
Brachial PP (mmHg)	43 ± 8	40 ± 7	40 ± 8	44 ± 9	47 ± 11	50 ± 10	0.001	0.375	0.199
HR (bpm)	64 ± 8	67 ± 10	63 ± 9	63 ± 7	59 ± 9	65 ± 8	0.199	0.046	0.281
24 h SBP (mmHg)	127 ± 6	115 ± 5	128 ± 9	126 ± 8	129 ± 10	123 ± 10	0.002	<0.001	0.026
24 h DBP (mmHg)	74 ± 5	68 ± 5	78 ± 7	73 ± 7	74 ± 6	67 ± 6	<0.001	<0.001	0.720
24 h HR (bpm)	73 ± 7	74 ± 9	73 ± 8	76 ± 6	66 ± 8	73 ± 7	0.006	0.007	0.195
VO2 (mL·kg−1·min−1)	35.4 ± 7.1	32.9 ± 6.0	29.8 ± 4.0	23.6 ± 4.5	25.1 ± 5.1	20.3 ± 2.8	<0.001	<0.001	0.197
TBV (mL)	1445 ± 117	1356 ± 119	1446 ± 114	1263 ± 102	1383 ± 109	1209 ± 75	<0.001	<0.001	0.083
CVR (mmHg·min/mL)	0.17 ± 0.04	0.11 ± 0.02	0.19 ± 0.06	0.17 ± 0.07	0.20 ± 0.05	0.19 ± 0.05	<0.001	0.004	0.217

Data are mean ± standard deviation. Comparisons of demographic and physiologic variables were made using a two-way analysis of variance. Chi-square test was used to examine the difference in sex distribution. Bold values represent P < 0.05.

BMI: body mass index; CO: cardiac output; CBF: cerebral blood flow; CCRI: (cerebral blood flow)/(cardiac output) ratio index; EF: eject fraction; cfPWV: carotid-femoral pulse wave velocity; SBP: systolic blood pressure; MAP: mean arterial pressure; DBP: diastolic blood pressure; PP: pulse pressure; HR: heart rate; VO₂ max: maximum oxygen uptake; TBV: total brain volume; CVR: cerebrovascular resistance.

Table 2.

The Pearson correlation matrix of CCRI, age, and covariates.

	CO	CBF	CCRI	Age	BMI	EF	cfPWV	VO2 max	Brachial SBP	Brachial MBP	Brachial DBP	Brachial PP	HR	TBV	CVR
CO		−0.143	−0.623	0.053	0.298	0.111	0.183	0.095	0.201	0.172	0.153	0.113	0.264	0.132	0.180
CBF	(0.093)		0.825	−0.413	−0.423	0.137	−0.457	0.242	−0.217	−0.268	−0.254	−0.044	0.078	0.174	−0.881
CCRI	(<0.001)	(<0.001)		−0.357	−0.475	0.025	−0.450	0.133	−0.289	−0.297	−0.262	−0.126	−0.065	0.047	−0.739
Age	(0.538)	(<0.001)	(<0.001)		0.212	0.162	0.688	−0.712	0.350	0.318	0.161	0.290	−0.141	−0.368	0.395
BMI	(<0.001)	(<0.001)	(<0.001)	(0.012)		−0.117	0.421	−0.240	0.158	0.190	0.199	0.021	−0.060	0.053	0.445
EF	(0.191)	(0.107)	(0.774)	(0.057)	(0.170)		0.068	−0.173	0.100	0.044	−0.060	0.176	0.169	−0.176	−0.110
cfPWV	(0.031)	(<0.001)	(<0.001)	(<0.001)	(<0.001)	(0.429)		−0.560	0.554	0.492	0.314	0.408	0.043	−0.184	0.503
VO2 max	(0.268)	(0.004)	(0.118)	(<0.001)	(0.004)	(0.042)	(<0.001)		−0.253	−0.224	−0.067	−0.253	−0.038	0.507	−0.269
Brachial SBP	(0.018)	(0.010)	(0.001)	(<0.001)	(0.063)	(0.241)	(<0.001)	(0.003)		0.857	0.593	0.712	0.028	−0.094	0.350
Brachial MAP	(0.043)	(0.001)	(<0.001)	(<0.001)	(0.025)	(0.609)	(<0.001)	(0.008)	(<0.001)		0.897	0.271	0.032	−0.078	0.452
Brachial DBP	(0.072)	(0.003)	(0.002)	(0.058)	(0.019)	(0.480)	(<0.001)	(0.435)	(<0.001)	(<0.001)		−0.143	0.006	0.033	0.423
Brachial PP	(0.184)	(0.604)	(0.139)	(0.001)	(0.809)	(0.039)	(<0.001)	(0.003)	(<0.001)	(0.001)	(0.092)		0.029	−0.144	0.061
HR	(0.002)	(0.362)	(0.444)	(0.099)	(0.485)	(0.046)	(0.614)	(0.659)	(0.748)	(0.712)	(0.945)	(0.737)		−0.061	−0.029
TBV	(0.122)	(0.040)	(0.587)	(<0.001)	(0.536)	(0.038)	(0.030)	(<0.001)	(0.274)	(0.359)	(0.701)	(0.092)	(0.478)		−0.151
CVR	(0.034)	(<0.001)	(<0.001)	(<0.001)	(<0.001)	(0.196)	(<0.001)	(0.001)	(<0.001)	(<0.001)	(<0.001)	(0.474)	(0.733)	(0.076)

Data were reported as correlation coefficients and (P values).

BMI: body mass index; CO: cardiac output; CBF: cerebral blood flow; CCRI: (cerebral blood flow)/(cardiac output) ratio index; EF: eject fraction; cfPWV: carotid-femoral pulse wave velocity; SBP: systolic blood pressure; MAP: mean arterial pressure; DBP: diastolic blood pressure; PP: pulse pressure; HR: heart rate; VO₂ max: maximum oxygen uptake; TBV: total brain volume; CVR: cerebrovascular resistance. Bold values represent P < 0.05.

Age- and sex-related differences in CCRI

CBF was associated negatively with age, BMI, cfPWV, and arterial pressure (P < 0.05), while CO did not differ across the age groups (P = 0.538) (Tables 1 and 2). Consequently, CCRI was negatively correlated with age (P < 0.001) (Figure 1(a)). Women had a higher CCRI than men in all age groups (P < 0.05) (Figure 1(b)). There was no significant difference in the slopes of the linear regressions between age and CCRI for men (−0.093 ± 0.035%/year) and women (−0.169 ± 0.036%/year) (P = 0.132). Altogether, CCRI decreased at a rate of 1.3% per decade for both men and women in the study population.

Figure 1.

Age- and sex-related differences in CCRI. (a) The regression equation was: CCRI = −0.127% × age + 22.72%, with a standard error of the slope equal to 0.035%/year (R²= 0.13, P < 0.001). (b) Solid lines inside the box represent median values, the cross (+) represents the mean value; P < 0.001 for the age group; P < 0.001 for sex; and P = 0.264 for age and sex interaction. The differences in CCRI between men and women in each age group were as follows: Young, 21.3 ± 5.6% vs. 14.8 ± 5.3%, P < 0.05; Middle age, 16.4 ± 5.5% vs. 13.0 ± 3.7%, P < 0.05; 14.8 ± 5.5% vs. 11.7 ± 2.9%, P < 0.05. CCRI: (cerebral blood flow)/(cardiac output) ratio index.

Association between CCRI and BMI

Table 2 presents the simple correlations between CCRI and potential covariates. Age, BMI, cfPWV, and arterial pressure all were negatively correlated with CBF and CCRI (P < 0.05). However, in multiple linear regression analysis, only BMI was associated negatively with CCRI after adjustments for age and sex (β = −0.33, P < 0.001) (Table 3). The relationship between BMI and CCRI was further confirmed by partial correlation analysis after adjustment of age and sex (R²= 0.13, P < 0.001) (Figure 2).

Table 3.

Multiple linear regression analysis of CCRI and covariates.

Model	Variable	β	95% CI		P value	Overall model	Model improvement
			Lower	Upper		R2 (P value)	ΔR2 (P value)
1	Sex	−0.34	−0.50	−0.19	<0.001	0.12 (<0.001)	0.12 (<0.001)
2	Sex	−0.39	−0.53	−0.24	<0.001	0.27 (<0.001)	0.16 (<0.001)
	Age	−0.40	−0.54	−0.25	<0.001
3	Sex	−0.29	−0.43	−0.14	<0.001	0.37 (<0.001)	0.09 (<0.001)
	Age	−0.32	−0.46	−0.18	<0.001
	BMI	−0.33	−0.48	−0.18	<0.001

Dependent variable: CCRI: (cerebral blood flow)/(cardiac output) ratio index. Sex and age were forced to enter sequentially in model 1 and model 2. In model 3, the stepwise method was used to enter significant correlates of CCRI according to Table 2.

β: standardized beta coefficients; CI: confidence interval; R²: coefficient of determination.

Figure 2.

Age- and sex-adjusted partial correlation between CCRI and BMI. Standardized residuals of BMI and CCRI were calculated by regressing out the effect of age and sex. CCRI: (cerebral blood flow)/(cardiac output) ratio index; BMI: body mass index.

Discussion

The major findings from the present study are threefold. First, CO distribution directed to the brain, as measured by CCRI, decreased linearly with age. Second, women had lower CO and higher CBF; therefore, a higher CCRI than men across the all age groups. Third, higher BMI is associated with lower CCRI independent of age and sex.

Age-related decrease in CCRI

Since Kety and Schmidt first used an invasive nitrous oxide inhalation method to quantify CBF,²⁹ the proportion of CO distributed to the brain in human subjects has been reported in several studies. A comprehensive review of blood flow to the organs under resting conditions concluded that the ratio of CBF to CO was relatively constant within a range of about 15–20%.² The limitations of these previous studies were relatively small sample sizes, conducted mostly in men, and did not address specifically the influences of sex or age on the CO-CBF relationship.² In this study, the average CCRI obtained from all subjects was 15.8 ± 5.7%, which overall is in agreement with the findings from previous studies.

To our knowledge, this is the first study to show a linear age-related CCRI decrease in healthy subjects. It has been well known that CBF decreases in older adults.^3–5 However, whether or not CO changes with age is less established.^6–9 Some studies showed a reduction of CO with advancing age at rest.^6,9 This is partially because these studies were done in a population with a high incidence of latent or subclinical cardiovascular disease. Our results demonstrated that there are no differences in CO across the adult lifespan in healthy subjects. This observation is consistent with the findings from studies, which excluded subjects with potential cardiovascular diseases by using rigorous screening criteria.^7,8 Thus, CO at rest may be preserved until late life in healthy individuals despite an overall reduction of resting metabolic rate.^30,31

An age-related decrease in CCRI suggests that a smaller proportion of CO is directed to the brain as one ages. The underlying mechanism(s) for this phenomenon as well as a potential redistribution of CO to other organs are unknown. In association with a decrease in brain metabolic rate with aging, there may exist less demand for CBF.^32–34 Alternatively, age-related increase in CVR and/or arterial stiffness may result in decreases in CBF and thus CCRI despite increases in arterial perfusion pressure (Table 1).³⁵ Further investigation of the impact of aging on the CO-CBF relationship may shed light on the role of cardiovascular health in maintaining cognitive vitality in older adults.

Sex-related differences in CCRI

A higher CBF, lower CO, and hence a higher CCRI observed in women in the present study are consistent with previous reports.^5,36 A higher CBF and CCRI despite a smaller total brain tissue volume observed in women (TBV, Table 1) suggest the presence of a higher cerebral metabolic rate in women than men.^37,38 Interestingly, there were no significant differences in the slopes of CCRI decrease with age between men and women. Thus, the sex differences in CBF as well as the proportion of CO distributed to the brain are likely to be preserved across the adult lifespan. The remaining questions are whether these sex-related differences in CBF and CCRI are also related to the sex differences in brain structure and function.³⁹

Effects of BMI on CCRI

One aim of this study was to identify systemic and/or cerebral variables, besides age and sex, which may influence the CO-CBF relationship. We observed that CCRI was correlated negatively with BMI, cfPWV, and SBP, which is consistent with earlier brain perfusion studies.^5,16 However, in the multiple linear regression analysis, only BMI was associated with CCRI after adjustments for age and sex. The inverse relationship between BMI and CCRI was reflected partially in the increase of CO with BMI and a concomitant decrease in CBF.^16,40 As BMI increases, CO increases to provide more blood to meet the metabolic demand of the increased body mass, which may compete with the brain for blood flow from the systemic circulation. However, it is also possible that increases in BMI, particularly fat tissue, may impair cerebral vascular function resulting in increases in cerebrovascular resistance and thus decreases in CBF.¹⁶ Regardless of the specific underlying mechanisms, these findings are consistent with the accumulating evidence, which indicates a higher BMI or obesity in mid to late life is an important risk factor for cognitive impairment and dementia.⁴¹

Mounting evidence suggests that physical activity may attenuate age-related CBF decline as indicated by a positive association between VO₂ max and CBF.^18,42 In the present study, we found that VO₂ max was associated positively with CBF across the age groups in all subjects (Table 2). However, no significant relationship between VO₂ max and CBF was observed after adjustments of age and BMI. Exclusion of the individuals who participated in regular exercise training and the cross-sectional data collected in the present study may have confounded the relationships between VO₂ max and CBF.

Strengths and limitations

Strength of this study is a comprehensive assessment of systemic and cerebral hemodynamics, which may influence the CO-CBF relationship. In addition, the subject population was stringently screened to exclude overt cerebral and cardiovascular disease, which may affect CO or CBF.

Study limitations include the cross-sectional nature of the study, which limits the understanding of the causality between CO and CBF across the adult lifespan, which we and others have demonstrated only in physiological studies during acute changes in CO.^43,44 However, the novel observation of the sex differences in CCRI and its decline across the adult lifespan challenges the dogma that the distribution of CO directed to the brain is a fixed value within the range of about 15–20% in healthy adults.² Second, we observed that BMI is an important covariate, which influences the CO-CBF relationship independent of age and sex. However, we did not measure body composition, and thus, cannot dissect specifically the contribution of increases in body fat on the CO-CBF relationship, which is likely to be related more closely to cerebrovascular function.⁴⁵ Nevertheless, the individuals in this study were relatively sedentary, thus, a higher BMI most likely reflects increased body fat.⁴⁶ Future studies that include obese subjects with BMI > 35 and measurement of body composition may extend the findings of the present study. Third, this study was focused on healthy subjects with normal aging; thus, further study of the CO-CBF relationship in those who have heart or brain disease may provide deeper understanding on how improvement in cardiovascular health may contribute to cognitive vitality in older adults.⁴⁷

Conclusion

The proportion of CO distributed to the brain, as measured by CCRI, has sex differences and declines across the adult lifespan. In addition, BMI is inversely associated with CCRI independent of age and sex. These findings provide new insights into the understanding of the CO-CBF relationship, which may have clinical significance for developing cardiovascular-based approaches to improve brain health in older adults.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: NIH grants of RC1AG036003 and R01HL102457. CX was supported by the China Scholarship Council Fund. TT was supported by the AHA’s Postdoctoral Fellowship (14POST20140013).

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Authors' contributions

CX performed experiments, conducted data analysis, and wrote the manuscript. TT performed experiments, conducted data analysis, and manuscript revision. JL, MT, JR, and CDT performed experiments and discussed results and commented on the data acquisition, analysis, and interpretation. YZ and LY discussed results and revised manuscript. RZ designed the study, discussed results, and revised manuscript. All authors edited and revised the manuscript and approved final submission.