|Cognition; C-Reactive Protein (CRP); Cardiorespiratory
fitness; Arterial stiffness
|Although there is robust evidence supporting the relationship
between physical activity and cognition [1-4], most research has
focused on older adult [5-8] and child populations [9-12]. However,
given that individuals within the emerging adult population have
an increased prevalence of health risk factors , it is critical that
attention be directed toward identifying the potential contributors to
such early declines in overall health.
|Emerging adulthood is classified as a developmental stage between
adolescence and adulthood, including individuals in their late teens
and mid-twenties . Individuals in this age range typically exhibit
the most efficient behavioral responses when presented with cognitive
stimuli of any age range population as the brain is developmentally
mature and age-related loss of cognition has not commenced .
Traditionally, cardiorespiratory fitness is high and health risk relatively
low during the second and third decade of life; however, this status is
changing, as incidence of morbidity is increasing among young people
. Because diseases previously common in older adults have become
prevalent in younger populations, it is important to understand how
cognitive health may be impacted.
|Young adults with low fitness who were studied over a 15-year
period were found to have developed diabetes, hypertension, and
metabolic syndrome . Furthermore, the emerging adults of
today have high blood pressures, high cholesterol levels, high BMIs,
and increased risks for artery calcification [18,19]. The prevalence of
risk factors within emerging adults is especially troubling when one
considers that individuals within this age group are thought to be at
their peak cardiorespiratory and cognitive abilities. As such, the current
study explores how health indices, such as levels of C-Reactive Protein (CRP), relate to performance on congruent and incongruent cognitive
tasks in an emerging adult population.
|CRP is a protein produced by the liver and serves as an indicator
of one’s risk for developing coronary heart disease because of its rapid
response to inflammation . Elevated CRP levels are indicative
of inflammation and often result from such factors as obesity and
metabolic syndrome . In addition to the health consequences
associated with CRP, cognitive performance has also been linked to this
protein such that a significant relationship was found to exist between
cognitive dysfunction and elevated CRP levels, among overweight
and obese individuals . Asystematic review of CRP and cognitive
disorders found that six, cross-sectional- or cohort-designed studies
among older adults, confirmed that high levels of CRP were associated
cognitive decline and risk for dementia .
|Other health indices of consideration in populations at risk include,
but are not limited to, arterial stiffness and blood pressure. Arterial
stiffness, or a loss of elastic fibers within the arterial wall, is an indicator
of risk for cardiovascular disease. Recently, arterial stiffness has been
identified as an independent predictor of loss of cognitive function in older adults . The age of onset of arterial stiffness is declining.
Adiposity, body weight, and a clustering of risk factors culminating
in metabolic syndrome have also been linked to a decline in cognitive
function in later life . During midlife or the ages of 25-74, the
health of cardiorespiratory system has been associated with executive
function and memory, while inflammation was only related to memory
. Accordingly, it was hypothesized that individuals with at least
one of the health risk factors measured in this study (e.g., elevated CRP
levels, elevated blood pressure, and poor cardiorespiratory fitness)
would have slower and less accurate cognitive responses than emerging
adults with fewer risk factors.
|Upon receiving Institutional Review Board approval, fifteen
emerging adults (n=8 females) with a mean age of 23.00 (SD=3.64) and
a mean Body Mass Index (BMI) of 22.60 (SD=2.65) were recruited to
participate in this study. The participants were solicited from various
advertisements offered on a large university campus in the southern
United States. All participants were involved in campus life as an
employee or student.
|Instruments and techniques
|Three cognitive instruments, one blood assay, and various
physiological techniques were used in this study. The cognitive
measurements included the Kaufman Brief Intelligence Test (KBIT),
Stroop Color-Word Test (Stroop), and Trail Making Test (Trail
Making). The KBIT  provides an estimation of verbal (crystallized)
and nonverbal (fluid) intelligence and has a reliability range from .88
to .94. The Stroop test  provides participants with 45 seconds to
read words displayed on the page in columns. In the first task, Word,
color names are written in black ink. In the second task, Color, “words”
are composed of Xs in different colors of ink, requiring participants to
identify ink color. For the final task, Color-Word, color names appear
in contrasting colors of ink, requiring participants to identify ink
color rather than reading the word. Trail Making A and B29 measures
the time it takes for a participant to draw lines that connect ordered numbers as quickly as possible. The first test, Trail Making A, includes
numbers, while the second test, Trail Making B, adds letters such
that the connection is made from 1 to A to 2 to B. If an error was not immediately addressed by the participant (e.g., realizing that they had
drawn a line to an incorrect number), the researchers prompted the
participant to correct this action.
|Using blood drawn through a venipuncture, serum levels of CRP
were determined with an Enzyme-Linked Immunosorbent Assay
(ELISA) method (High Sensitivity Enzyme Immunoassay, BioCheck,
Inc., USA). According to the manufacturer’s instructions (Schultz &
Arnold, 1990), 96-well polystyrene microplates were coated with a
mouse monoclonal-CRP antibody. After absorbance was read at 450
nm on a microplate reader and CRP concentrations were determined
automatically according to the CRP standard curve.
|Other techniques included in this research study centered on the
collection of resting blood pressure, BMI as a measure of standing
height and weight, and arterial stiffness. Arterial stiffness and pulse wave
velocity were measured both manually and using an automatic device.
The manual method consisted of using two identical transcutaneous
Doppler flowmeters (810-A, Parks Medical, Aloha, OR) to obtain the
velocity of pulse waves (PWV) between the following: the aortic arch and the femoral artery (aortic PWV), the brachial and the radial artery
(arm PWV), the femoral and the posterior tibial artery (leg PWV),
the aortic arch and the posterior tibial artery (whole-body PWV),
and between the brachial and the posterior tibial artery (baPWV) as previously described. Arterial pressure waves were digitized for offline
analysis with signal processing software (Biopac System, Santa Barbara, CA). Pulse wave velocity was calculated from distance divided
by transit time. Transit time was determined from the time delay
between the proximal and distal “foot” waveforms. The foot of the wave
was identified as the commencement of the sharp systolic upstroke. Distance traveled by the pulse wave was assessed in duplicate with a random zero length measurement over the surface of the body with a
non-elastic tape measure.
|After a twelve hour overnight fasting state, a resting blood draw
was conducted to measure baseline CRP in the morning, which was
analyzed using commercially available hsCRP Enzyme Immunoassay
kit (BioCheck). Because one individual was not available for the
blood draw, the corresponding analysis was conducted using fourteen
subjects. If a CRP value was two standard deviations away from the
group mean, an additional assay was run to confirm the accuracy
of the level of risk. After the blood draw the participant was offered
a snack, completed a health screening questionnaire, and height and
weight were measured. Arterial stiffness measures and blood pressure
measures were collected from the participant in a supine position,
while resting comfortably. Participants were initially positioned on the
cycle ergometer (Velotron Dynafit Pro, Seattle WA). Cardiorespiratory
fitness was determined through four incremental five minute stages of
submaximal cycling for the determination of oxygen consumption VO2
versus work rate relationship followed by a ergometry test to determine
maximal oxygen consumption (VO2 max), using indirect calorimetry
via continuous gas-exchange measurements, which also provided
measurement of RER and METs (True-Max; ParvoMedics, Sandy,
UT). On a second day of testing, participants completed baseline
cognitive testing and an acute bout of physical activity. The cognitive
test administration sequence was KBIT, Stroop, and Trail Making,
which was followed post exercise by repeating the Stroop and Trail
Making assessments. The results of the baseline cognitive assessments
are described here, while the acute responses to physical activity are
reported in another manuscript.
|All data were confirmed and reduced from a single database in
IBM SPSS v19. Descriptive statistics and Pearson correlations were
calculated to identify significant characteristics and associations
between the variables in this database. Multiple Analysis of Variance
(MANOVA) was calculated to determine differences in health indices,
cognition and gender. Multiple regressions were calculated with the
individual health indices of CRP, BMI, and cardiorespiratory fitness,
and arterial stiffness, being regressed on to the dependent cognitive
|Table 1 contains the fitness and demographic characteristics of this
sample. An ANOVA revealed significant gender differences for BMI
[F (3, 11) 0.06; p=.01] and cardiorespiratory fitness (ml/Kg/min) [F
(3,11)=0.36; p=.01]. There were no significant differences in age, KBIT
(IQ), RER, systematic levels of CRP, arterial stiffness, blood pressure,
and cognitive function tests by gender. Pearson correlations revealed
that the only health marker that was significantly associated with all
conditions of the Stroop cognitive assessments and the Trail Making A
condition, was CRP (Table 2 and Figure 1). Among the other variables,
BMI was not significantly correlated with other health indices and
cognitive function tests, but was negatively correlated with KBIT (r
=-0.71, p<.01). Age was significantly correlated with arterial stiffness
(r=0.67, p<0.001). Cardiorespiratory fitness has a significant, negative
with Trail Making Test B (r=-0.57, p=.027). There were no significant
correlations found between arterial stiffness, pulse wave velocity, and
|When IQ and BMI were controlled, CRP negatively predicted
Word (ß=-0.69, p<0.05), Color (ß=-0.72, p<0.02), and Color-Word
(ß=-0.83, p<0.01) and accounted for 59%, 73%, and 77% of the variance,
respectively. CRP was not a significant predictor of performance on the
Trail Making test of cognitive testing in either the congruent or noncongruent
conditions (ß=0.58, p=.09 and ß=0.41, p=0.33, respectively).
Arterial stiffness and pulse wave velocity did not significantly predict
cognitive performance and did not contribute to the regression model.
Cardiorespiratory fitness negatively predicted the condition of Trail
Making B (ß=-0.62, p<0.03) and approached negative significance for
Trail Making A (ß=-0.71, p<0.09).
|Previous research suggests that the prevalence of negative health
indices is increasing among emerging adults. The purpose of this
study was to examine the relationship of health indices with cognitive
performance on both congruent and non-congruent cognitive tasks.
Although it was hypothesized that a clustering effect (the idea that
multiple health indices would have a collective effect that was greater
than any single health marker) would be significantly associated with
and a predictor of cognitive performance, the findings in this study
suggest that CRP was the only major contributor over other health
markers. CRP exhibited predictive systematic levels on cognitive
performance, under some, but not all task conditions, when controlling
for BMI and IQ. Previous research has identified CRP as a direct
neurotoxin resulting in immunoreactivity in the brains of individual’s
with Alzheimer’s . Because instances of highly elevated CRP
create this neurotoxicity, it likely affects cognitive tasks under varied
conditions; whereas, lower levels of CRP may be related to some
cognitive tasks, but not others.
|This finding is important among emerging adults, because it supports the employment of preventive strategies, such as engagement
in habitual physical activity within this population and may prioritize
this health marker for preventive screening.
|In accordance with previous research cardiorespiratory fitness was
significantly related to cognitive performance on the Trail Making
test . However, surprisingly, in this population cardiorespiratory
fitness was not a predictor of performance on the Stroop task. The
strength of previously documented associations between aerobic
fitness and cognition, in emerging adults, has been weak to moderate
and accordingly, these findings could be impacted by the small size of
this sample or could be an indicator of complex correlates that subserve
cognitive function. These findings should be applied with caution.
|Another surprise finding was that BMI was not significantly
associated with CRP, as we had hypothesized. This was perhaps affected
by the proportion of study participants who were considered to be at
minimal risk for cardiorespiratory fitness, whereby some participants
were considered “fit and fat”. Possibly a larger, more targeted sample
that classifies individuals into categories of fitness and risk (e.g., high
fit and high risk) may help to further decompose this relationship
between body composition, CRP, and cognitive function.
|Future research should employ experimental designs to elucidate
the potential clustering effects of metabolic syndrome risk factors as
they relate to a decline in cognitive performance. Given the strength
of the association and predictive qualities of CRP within this study,
the effects of preventive strategies, such as regularly participating in
physical activity and early screenings should be comprehensively
- Barnes DE, Santos-Modesitt W, Poelke G, Kramer AF, Castro C, et al. (2013) The Mental Activity and eXercise (MAX) trial: a randomized controlled trial to enhance cognitive function in older adults. JAMA Intern Med 173: 797-804.
- Chaddock-Heyman L, Erickson KI, Voss MW, Knecht AM, Pontifex MB, et al. (2013) The effects of physical activity on functional MRI activation associated with cognitive control in children: a randomized controlled intervention. Front Hum Neurosci 7: 72.
- Hillman CH, Erickson KI, Kramer AF (2008) Be smart, exercise your heart: exercise effects on brain and cognition. Nat Rev Neurosci 9: 58-65.
- Hillman CH, Pontifex MB, Motl RW, O'Leary KC, Johnson CR, et al. (2012) From ERPs to Academics. Dev Cogn Neurosci 2: S90-90S98.
- Laurin D, Verreault R, Lindsay J, MacPherson K, Rockwood K (2001) Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch Neurol 58: 498-504.
- Voss MW, Erickson KI, Prakash RS, Chaddock L, Malkowski E, et al. (2010) Functional connectivity: a source of variance in the association between cardiorespiratory fitness and cognition? Neuropsychologia 48: 1394-1406.
- Weuve J, Kang JH, Manson JE, Breteler MM, Ware JH, et al. (2004) Physical activity, including walking, and cognitive function in older women. JAMA 292: 1454-1461.
- Yaffe K, Barnes D, Nevitt M, Lui LY, Covinsky K (2001) A prospective study of physical activity and cognitive decline in elderly women: women who walk. Arch Intern Med 161: 1703-1708.
- Kamijo K, Khan NA, Pontifex MB, Scudder MR, Drollette ES, et al. (2012) The relation of adiposity to cognitive control and scholastic achievement in preadolescent children. Obesity (Silver Spring) 20: 2406-2411.
- Kamijo K, Pontifex MB, Khan NA, Raine LB, Scudder MR, et al. (2012) The association of childhood obesity to neuroelectric indices of inhibition. Psychophysiology 49: 1361-1371.
- Kamijo K, Pontifex MB, O'Leary KC, Scudder MR, Wu CT, et al. (2011) The effects of an afterschool physical activity program on working memory in preadolescent children. Dev Sci 14: 1046-1058.
- Sibley BA, Etnier JL (2003) The relationship between physical activity and cognition in children: A meta-analysis. Pediatric Exercise Science 15: 243-256.
- Kuklina EV, Yoon PW, Keenan NL (2010) Prevalence of coronary heart disease risk factors and screening for high cholesterol levels among young adults, United States, 1999-2006. Ann Fam Med 8: 327-333.
- Jensen Arnett, J (2004) Emerging Adulthood: The Winding Road from the Late Teens through the Twenties. Oxford: Oxford University Press.
- Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, et al. (2003) Mapping cortical change across the human life span. Nat Neurosci 6: 309-315.
- Centers for Disease Control and Prevention [CDC] (2013) Surveillance for certain health behaviors among states and selected local areas – United States, 2010. Morbidity and Mortality Weekly Report 62: 1-250.
- Carnethon MR, Gidding SS, Nehgme R, Sidney S, Jacobs DR Jr, et al. (2003) Cardiorespiratory fitness in young adulthood and the development of cardiovascular disease risk factors. JAMA 290: 3092-3100.
- Carnethon MR, Gulati M, Greenland P (2005) Prevalence and cardiovascular disease correlates of low cardiorespiratory fitness in adolescents and adults. JAMA 294: 2981-2988.
- Mahoney LT, Burns TL, Stanford W, Thompson BH, Witt JD, et al. (1996) Coronary risk factors measured in childhood and young adult life are associated with coronary artery calcification in young adults: the Muscatine Study. J Am Coll Cardiol 27: 277-284.
- Du Clos TW (2000) Function of C-reactive protein. Ann Med 32: 274-278.
- Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C, et al. (2004) Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation 109: 433-438.
- Sweat V, Starr V, Bruehl H, Arentoft A, Tirsi A, et al. (2008) C-reactive protein is linked to lower cognitive performance in overweight and obese women. Inflammation 31: 198-207.
- Kuo HK, Yen CJ, Chang CH, Kuo CK, Chen JH, et al. (2005) Relation of C-reactive protein to stroke, cognitive disorders, and depression in the general population: systematic review and meta-analysis. Lancet Neurol 4: 371-380.
- Scuteri A, Tesauro M, Appolloni S, Preziosi F, Brancati AM, et al. (2007) Arterial stiffness as an independent predictor of longitudinal changes in cognitive function in the older individual. J Hypertens 25: 1035-1040.
- Cavalieri M, Ropele S, Petrovic K, Pluta-Fuerst A, Homayoon N, et al. (2010) Metabolic syndrome, brain magnetic resonance imaging, and cognition. Diabetes Care 33: 2489-2495.
- Karlamangla AS, Miller-Martinez D, Lachman ME, Tun PA, Koretz BK, et al. (2014) Biological correlates of adult cognition: Midlife in the United States (MIDUS). Neurobiol Aging 35: 387-394.
- Kaufman AS, Kaufman NL (1990) Kaufman Brief Intelligence Test: American Guidance, Circles Pines, MN.
- Golden C (1978) Stroop Color and Word Test. A Manual for Clinical and Experimental Uses. Stoelting, Chicago, Illinois.
- Reynolds CR (2002) Comprehensive Trail Making Test: Examiner's manual. Pro-Ed, Austin, Texas.
- Ganio MS, Brothers RM, Shibata S, Hastings JL, Crandall CG (2011) Effect of passive heat stress on arterial stiffness. Exp Physiol 96: 919-926.
- Duong T, Nikolaeva M, Acton PJ (1997) C-reactive protein-like immunoreactivity in the neurofibrillary tangles of Alzheimer's disease. Brain Res 749: 152-156.
- Hillman CH, Castelli DM, Buck SM (2005) Aerobic fitness and neurocognitive function in healthy preadolescent children. Med Sci Sports Exerc 37: 1967-1974.