Order 932343: Does exercise and fitness affect cognitive health

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An abstract is a paragraph (150-300 words) that summarizes the main aspects of the paper in a prescribed sequence that includes 1) the overall purpose of the study and the research problem(s) you investigated; 2) the basic design of the study; 3) major findings or trends found as a result of your analysis; and, 4) a brief summary of your interpretations and conclusions.

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Runninghead:

DOES EXERCISE AND FITNESS HELP WITH COGNITIVE HEALTH

Does exercise and fitness help with cognitive health

Sekinah Walls

Mississippi College

Abstract

Older adults are experiencing the deterioration of physical functions and also suffering from declining brain and cognitive functions. Normal aging includes the degradation of cognitive processes, including memory, reasoning, and information processing speed. Older adults are at risk for osteoporosis and they are at high risk for falling. It is a huge problem when an older adult falls because the body does not heal as fast and easy like and young adult. Older adults need to be active and continue to be active to help increase the blood flow throughout their bodies and promote a healthy life physically and mentally. Living a healthy lifestyle helps cognitive skills for both young and old adults. Childhood obesity, cardiovascular disease, diabetes type 2, and certain cancers can possibly be prevented with exercise and fitness. Regular physical activity has been shown to be productive against the development of these diseases and many others. Not all children have adequate and effective brain development throughout childhood, therefore leading them to having health conditions that have causes. Exercise and fitness is suggested to indirectly improve cognitive and brain health by reducing the risks for many disease processes. Exercise and fitness in the adolescence and adults will help with physical as well as cognitive and brain health Comment by User: This sentence is wordy, consider revising.

Statement of the Problem

Purpose of the Study

This research purpose is to review studies and examine the cross sectional and experimental relationship between exercise and fitness and executive control function. Since the brain does not fully develop until one has reached their twenties, exercise and fitness maybe an important guiding principle to have for children early on and young adults. A proper and healthy exercise and fitness lifestyle affects the whole body, mind, and soul. This study is to see if exercise and fitness affects the cognitive functions positively. Medically thinking, exercise and fitness is naturally good for the body physically and cognitively, because it promotes good blood flow throughout the body. Having good flow throughout the body is necessary when relating it to cognitive functions. The body has to have proper blood flow in order to receive an adequate

amount of oxygen that the body requires to function properly and effectively. In this study I will review researches and based off of those and the results from the studies will determine and prove that exercise and fitness does have a positive effect on cognitive function. Comment by User: Try not to use first person here. This section is meant to be very clear and concise, but I’m not sure what you are wanting to do. You can start this section by saying: The purpose of this study is…and tell me.

Research Question/Hypothesis Comment by User: I need this section to be set up with a numbered list of questions.

What exercises and fitness regimens are recommended to help with cognitive function in both children, young adults, middle age adults, and older adults. Exercise and fitness helps the blood to flow better in the body. Therefore, people’s brains are getting well oxygenated and people are able to make smarter decisions more effectively. Does exercise and fitness have an effect of the cognitive function in older adults? What different cognitive functions are measured, implying that the cognition type plays a moderating role in the relationship between acute exercise and cognition? Whether the effects of acute exercise have general or specific effects on the different cognition types and whether fitness status moderates the magnitude of favorable acute exercise effects on these cognitive performances, particularly in older adults. This research study will investigate how cardiovascular fitness moderates two type of cognitive function assessed by the Stroop test, following an acute bout of moderate aerobic exercise in an older population. Acute exercise not only reduced the response times for both Stroop test conditions but also diminished the interface, suggesting that acute exercise led to both general and specific improvements in cognitive functions. How does exercise and fitness affect the cognitive functions?

Review of Literature

Klan and Hillman reviewed the brain development mental trajectory and evaluated observational and interventional studies examining relationship between physical activity and fitness with cognitive performance and brain health in childhood. The relationship between physical activity, fitness, and academic achievement has received attention in recent years due to increased prevalence of children who overweight and not active. Studies in humans suggest that physical activity may be protective against age related brain tissue loss and may be positively associated with brain health and cognitive functions in children. Further research is needed to determine to what extent genetics, motivation, personality characteristics, nutrition, and intellectual stimulation plays a role in mediating the fitness brain relationship observed in cross sectional studies. Longitudinal studies are needed to better examine the association between changes in fitness, physical activity, brain, and cognition. According to Klan and Hillman, evidence from MRI studies suggest that physical activity may influence the modulation of neural activity supporting executive control in pre-puberty children, but also suggests that further work is needed to better determine the differential patterns of activation across various cognitive tasks. Childhood physical activity and aerobic fitness helps brain function and cognition. Despite the fact that the brain achieves 95% of its maximum size by the age of six, the processes underling functional connectivity continues throughout life which is why physical activity helps brain function and cognition. The purpose of this research was to find out whether exercise and fitness has an effect on the cognitive function in older adults. The examination of whether the positive effects of acute exercise extend to older adults has been limited, with unclear findings. This study examined the effects of acute exercise on two types of cognitive process derived from the Stroop test, where the Stroop incongruent condition is believed to engage a greater amount of executive control than does the Stroop congruent condition, which reflects more basic information processing. A Stroop test is when you compare congruent conditions with incongruent conditions. Acute exercise not only reduced the response times for both Stroop conditions, but also diminished the interference, suggesting that acute exercise led to both general and specific improvements in cognitive functions.

Reference

Boa Sorte Silva, N. C., Gregory, M. A., Gill, D. P., & Petrella, R. J. (2017). Multiple-modality exercise and mind-motor training to improve cardiovascular health and fitness in older adults at risk for cognitive impairment: A randomized controlled trial. Archives Of Gerontology And Geriatrics, 68149-160. doi:10.1016/j.archger.2016.10.009

Chiu, C., Ko, M., Wu, L., Yeh, D., Kan, N., Lee, P., & … Ho, C. (2017). Benefits of different intensity of aerobic exercise in modulating body composition among obese young adults: a pilot randomized controlled trial. Health And Quality Of Life Outcomes, 15(1), 168. doi:10.1186/s12955-017-0743-4

Chu, C., Chen, A., Hung, T., Wang, C., & Chang, Y. (2015). Exercise and fitness modulate cognitive function in older adults. Psychology And Aging, 30(4), 842-848. doi:10.1037/pag0000047

Khan, N. A., & Hillman, C. H. (2014). The relation of childhood physical activity and aerobic fitness to brain function and cognition: a review. Pediatric Exercise Science, 26(2), 138-146. doi:10.1123/pes.2013-0125

Lowe, B. D., Swanson, N. G., Hudock, S. D., & Lotz, W. G. (2015). Unstable sitting in the workplace–are there physical activity benefits? American Journal Of Health Promotion: AJHP, 29(4), 207-209. doi:10.4278/ajhp.140331-CIT-127

Ludyga, S., Gerber, M., Brand, S., Holsboer-Trachsler, E., & Pühse, U. (2016). Acute effects of moderate aerobic exercise on specific aspects of executive function in different age and fitness groups: A meta-analysis. Psychophysiology, 53(11), 1611-1626. doi:10.1111/psyp.12736

Runninghead:

DOES EXERCISE AND FITNESS HELP WITH COGNITIVE HEALTH

1
DOES EXERCISE AND FITNESS HELP WITH COGNITIVE HEALTH

Does exercise and fitness help with cognitive health

Sekinah Walls

Mississippi College

Abstract

Older adults are experiencing the deterioration of physical functions and also suffering from declining brain and cognitive functions. Normal aging includes the degradation of cognitive processes, including memory, reasoning, and information processing speed. Older adults are at risk for osteoporosis and they are at high risk for falling. It is a huge problem when and older adults falls because the body does not heal as fast and easy like and young adult. Older adults need to be active and continue to be active to help increase the blood flow throughout their bodies and promote a healthy life physically and mentally. Living a healthy lifestyle helps cognitive skills for both young and old adults. Childhood obesity, cardiovascular disease, diabetes type 2, and certain cancers can possibly be prevented with exercise and fitness. Regular physical activity has been shown to be productive against the development of these diseases and many others. Not all children have adequate and effective brain development throughout childhood, therefore leading them to having health conditions that have causes. Exercise and fitness is suggested to indirectly improve cognitive and brain health by reducing the risks for many disease processes. Exercise and fitness in the adolescence and adults will help with physical as well as cognitive and brain health

Statement of the Problem

Purpose of the Study

This research purpose is to review studies and examine the cross sectional and experimental relationship between exercise and fitness and executive control function. Since the brain does not fully develop until one has reached their twenties, exercise and fitness maybe an important guiding principle to have for children early on and young adults. A proper and healthy exercise and fitness lifestyle affects the whole body, mind, and soul. This study is to see if exercise and fitness affects the cognitive functions positively. Medically thinking exercise and fitness is naturally good the body physically and cognitively, because it promotes good blood flow throughout the body. Having good flow throughout the body is necessary when relating it to cognitive functions. The body has to have proper blood flow in order to receive an adequate

Research Question/Hypothesis

Review of Literature

Reference

Chu, C., Chen, A., Hung, T., Wang, C., & Chang, Y. (2015). Exercise and fitness modulate cognitive function in older adults. Psychology And Aging, 30(4), 842-848. doi:10.1037/pag0000047

©Journal of Sports Science and Medicine (2015) 14, 716-722

http://www.jssm.org

Influence of Two Different Exercise Programs on Physical Fitness and Cognitive
Performance in Active Older Adults: Functional Resistance-Band Exercises vs.
Recreational Oriented Exercises

Hernán Ponce-Bravo 1,2, Christian Ponce 1, Belén Feriche 1 and Paulino Padial 1
1 Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain
2 Faculty of Health Sciences, School of Physical Culture, National University of Chimborazo, Ecuador

Abstract
This study examines the impact of a resistance-band functional
exercise program, compared with a recreational exercise pro-
gram, on physical fitness and reaction times in persons older
than 60 years. Fifty-four community-dwelling volunteers (71.76
± 6.02 years) were assigned to a specific exercise program:
Functional activity program (focused on resistance-band multi-
joint activities; experimental group, EG), or recreational physi-
cal activity program (with gross motor activities of ludic con-
tent; control group, CG). Before and after the intervention, we
determined cognitive capacity in terms of simple reaction time
(S-RT), choice reaction time (C-RT) and fitness. In both groups
physical performance improved, though this improvement was
more marked in the EG for grip strength, arm strength and gross
motor abilities (p < 0.05). Reaction times were better only in EG (S-RT = 10.70%, C-RT = 14.34%; p < 0.05) after the corre- sponding physical training intervention. The training period showed no effect on the moderate relationship between both RT and gross motor abilities in the CG, whereas the EG displayed an enhanced relationship between S-RT and grip-strength as well as the C-RT with arm strength and aerobic capacity (r ~ 0.457; p < 0.05). Our findings indicate that a functional exercise program using a resistance band improves fitness and cognitive performance in healthy older adults. Key words: Aging, reaction time, physical activity program, cognitive capacity.

Introduction

According to estimates by the World Health Organization,
elderly persons make up the most rapidly growing section
of the population worldwide. It is forecast that by 2050,
around 2000 million people –or one in four– will be older
than 60 years of age.

The physical and cognitive decline that occurs dur-
ing aging translates to an inability to carry out daily living
tasks with consequent impacts on social relationships and
quality of life. This has prompted the design of programs
for this population sector targeted at improving functional
health and promoting the independence of the elderly in
their environment. In this context, routine physical exer-
cise plays a major role in the life quality and expectancy
of older adults (Blain et al., 2000; Katula et al., 2008;
Poon and Fung, 2008; Vogel et al. 2009).

A lack of agility and dynamic balance (gross mo-
tor abilities) is a significant risk factor for loss of inde-
pendence and increases the risk of falls. Balance also

affects daily living activities such as standing, bending,
climbing stairs, walking or responding to external stimuli
(Sturnieks et al., 2008). The reason for this is the
progressive deterioration in neurophysical skills that
occurs with age, impairing sensory-motor functions and
producing deficiencies in perception, muscle and
cognitive function, and thus affecting balance and the risk
of falling (Sturnieks et al., 2008). Regularly practicing
some form of physical exercise reduces the risk of falls
(Howe et al., 2007), essentially because of improved
muscular strength, agility, dynamic balance and coordina-
tion (Blain et al., 2000; Karinkanta et al., 2009; Orr et al.,
2008) and also helps preserve cognitive skills (Angevaren
et al., 2008; Blain et al., 2000; Brisswalter et al., 2002;
Colcombe and Kramer, 2003; Liu-Ambrose and Don-
aldson., 2009; Williamson et al. 2009). Indeed, different
exercise programs seem to achieve proportional changes
in physical condition and cognition in older adults (Ber-
ryman et al, 2014). However, the physiological pathway
of these results displays a large variety of mechanisms
liked with their cognitive impact, which nowadays should
be clarified (Berryman et al., 2014; Voelcker-Rehage et
al., 2010).

The available data indicates a direct link between
improved cognitive performance and training programs
designed to improve cardiovascular fitness (Colcombe &
Kramer, 2003), strength and balance (Araya, 2011). How-
ever, there is no general consensus regarding the details of
the most appropriate fitness training program (including
the best intervention type, length of exercise program,
session duration, etc.) or of its effects on indicators of
cognitive function. Some of these indicators are simple
reaction time (S-RT) (Dustman et al. 1984), choice reac-
tion time (C-RT) (Van Boxtel et al., 1997), or visual-
spatial tasks (Shay and Roth, 1992), which are considered
as key markers of the functional independence of the
elderly (Colcombe and Kramer, 2003). Training programs
for older adults have been mostly based on exercises
designed to improve cardiovascular fitness and muscular
strength (de Vreede et al., 2005; Kalapotarakos et al.,
2006; Katula, et al. 2008; Liu-Ambrose and Donaldson,
2009; Van Boxtel et al., 1997). However, it has not al-
ways been possible to correlate such improvements with a
capacity to better carry out daily living tasks. Some au-
thors propose the inclusion of functional exercises (multi-
joint motor tasks that involve several body parts) in inter-
ventions planned for older adults (de Bruin and Murer,
2007; de Vreede et al. 2005) though their effects on cog-

Research article

Received: 10 June 2015 / Accepted: 29 July 2015 / Published (online): 24 November 2015

Ponce-Bravo et al.

717

nitive performance and general fitness have not yet been
established.

This study was designed to determine the impact
of a program of functional exercises using elastic bands
versus a recreational activity program on fitness and cog-
nitive performance in active elderly participants older
than 60 years of age.

Methods

Participants
Fifty-four participants were recruited from the community
among older adults attending regular physical activity
classes organized by the town hall (age 70.57 ± 5.46
years; weight 72.96 ± 10.54 kg; height 1.56 ± 0.09 m; 6
men, 48 women). Exclusion criteria were: A diagnosis of
a progressive somatic or psychiatric disease, or any illness
preventing participation in physical activities. The study
protocol adhered to the tenets of the Declaration of Hel-
sinki and received institutional review board approval.
Written informed consent was obtained from each partici-
pant.

The participants enrolled were assigned to two
groups matched in terms of their baseline reaction times
and physical fitness, as well as the compatibility training
schedule : an experimental group (EG; n = 22) and a con-
trol group (CG; n = 32). Participants in each group com-
pleted a 4-week training program consisting of 5 weekly
sessions of 50 min each. Before and after the training
intervention, fitness and cognitive performance were
assessed in each participant.

Study design
In a longitudinal-experimental study, pre- and post-
intervention data were compared in an experimental
(functional training with resistance elastic-bands; EG) and
control (recreational training; CG) group. The effects of
both training programs on physical fitness and cognitive
performance (simple and choice reaction times) were
determined by intra- and intergroup comparisons of
means. Sampling was performed via an intentional non-
probabilistic convenience procedure.

Both types of training included a multidimensional
activity program (endurance, strength, balance, gross
motor, and flexibility training), which is considered opti-
mal for health and functional benefits in older people
(Cress et al., 2005). Differences between training groups
came from the nature of the exercises (multi-joint vs ana-
lytical) and the focus towards which they were directed
(physical condition improvement or ludic orientation): 1)
Resistance-band functional training sessions combined
several objectives simultaneously by means of exercise
that incorporated multi-joint motor tasks that involved
several body parts (functional exercises; de Bruin and
Murer, 2007; de Vreede et al., 2005). These exercises
were executed with low-resistance elastic-bands in order
to highlight the strength content in each session (Cress et
al., 2005); 2) Recreational training also combined several
objectives simultaneously but used more analytical low-
load exercises applied in a ludic form.

The variables used as indicators of physical fitness
were: leg strength (LS) using the Chair-stand test;
right/left arm strength (R/L AS) using the Arm curl test;
and gross motor abilities (AG; 8-Foot up-and-go). For all
tests, we followed the procedures and recommendations
described for the Senior Fitness Test (SFT) battery (Rikli
and Jones, 2001). The aerobic endurance test was reduced
to 2 min, and performance subsequently estimated in the 6
min-test according to the procedure of Butland et al,
(1982). Finally, expected aerobic performance (EAP) was
calculated as the difference between aerobic performance
and the expected minimum distance (Jones and Rikli,
2002).

Additionally, handgrip strength was determined in
a maximum dynamometry test (dynamometer T.K.K.
5401 Grip-D, Tokyo Japan). From a standing position
with arms extended on both sides and hands facing the
thighs, participants were instructed to exert as much pres-
sure as possible for 3-5 s on the grip adapted to hand-
breadth. After 3 attempts with each hand, lower values
were eliminated. Performance was calculated as the sum
of the kg generated using both hands (HGS).

Cognitive performance was assessed by recording
reaction times (RT) in the simple reaction (S-RT) and
choice (C-RT) tests using the system Whole Body Reac-
tion Measuring Equipment (FT-3130, TKK Takei &
Company, LTD, Tokyo, Japan). This system comprises a
table with three buttons and three light bulbs (red, yellow
and blue). To determine S-RT, the participants sit at the
table with hands on each side of the buttons. The tests
consist of pressing any button with either hand as quickly
as possible after a bulb lights up. When participant is
ready, the evaluator presses a button and a random time
between 1 and 3 s is set automatically by the system be-
fore the light turns on. The test result is recorded in milli-
seconds. To determine C-RT, participants respond to the
three possible colored bulbs by pressing a different button
(left, middle, right) for each color. Three attempts were
allowed per test and the lowest value recorded as the
result.

Testing procedure
Before and after the training interventions, all measure-
ments were taken and tests performed on a single day.
Each testing session commenced with the measurements:
height (Holtain, Dyffed, UK), weight (Tanita TBF-300a,
IL, USA) and waist/hip measurements. Body mass index
(BMI) was determined using the Quetelet procedure as
the ratio between weight (kg) and height squared (m2).
The waist-hip ratio was recorded using the corresponding
measurements in cm. Anthropometric measurements were
followed by the RT tests and then by the physical fitness
tests in the order: strength tests (legs, arms and handgrip),
gross motor and aerobic performance test.

Intervention programs
The intensity and difficulty of the experimental and con-
trol programs were increased as the participants adapted
to each level of exercise. Sessions were always supervised
by a sports expert.

Functional training and cognitive performance

718

In the experimental group, each training session
commenced with 5 min of introduction, organization and
warm-up (functional and stretching exercises). In the
main part of the session (40 min), participants performed
the functional exercises with elastic bands: aerobic (8
min), gross motor activities, action/reaction speed (7 min)
and floor exercises (25 min). Each session finished with 5
min of active relaxation exercises. Training loads were
adjusted according to the recommendations of Chodzko-
Zajko et al. (2009). In weeks 1 and 4, loads were 8 repeti-
tions of each exercise performed at an intensity of 5-6 on
a scale of 0-10. This intensity was recorded and pre-
scribed according to the expert’s perception of each train-
ing session. In weeks 2 and 3, the load was increased to
12 repetitions and intensity to 7-8.

Training sessions for participants in the control
group commenced with a warm up (10 min) of games and
mixed exercises. The main part of each session (30 min)
consisted of traditional aerobic exercises (20 min) and
recreational (10 min) activities. All sessions ended with
10 min of relaxation exercises. Training loads were ad-
justed as in EG. In weeks 1 and 4, the load was 6 repeti-
tions per exercise at an intensity of 3-4 on a scale of 0-10.
In weeks 2 and 3, this volume was increased to 8 repeti-
tions at an intensity of 5-6 (Chodzko-Zajko et al., 2009).

Statistical analysis
Data are provided as the mean and standard deviation
(SD). The Shapiro-Wilk test was used to determine the
distribution of data. To assess the effect of treatment on
the measures of physical fitness, body composition and
cognitive capacity in each group, we used a comparison
of means test for paired data (pre vs. post intervention), or
the Wilcoxon test for variables not normally distributed.
The Student t-test for independent samples or Mann-
Whitney U test were used to compare the difference pro-
duced in each variable (post-intervention value minus pre-
intervention value) between CG and EG. The homogenei-
ty of groups was determined using the Levene test. For
non-homogeneous comparisons, the Welch test was em-
ployed. Correlations between physical condition variables
and reaction times (S-TR and C-RT) were quantified
through Pearson’s product-moment correlation coefficient
(r). Qualitative interpretations of the r coefficients as

defined by Hopkins (2002) (0–0.09 trivial; 0.1–0.29
small; 0.3–0.49 moderate; 0.5–0.69 large; 0.7–0.89 very
large; 0.9–0.99 nearly perfect; 1 perfect) were provided
for all significant correlations. Statistical tests were per-
formed using the software SPSS version 20.0 (SPSS,
Chicago, IL, USA) and Microsoft Excel 2007. The confi-
dence interval was set at 95%.

Results

Before the physical activity program, the experimental
and control groups were homogenous in terms of body
composition and indicators of fitness and cognitive per-
formance (p > 0.05).

The pre-post comparisons of the variables recorded
in each group may be seen in Table 1. Intragroup compar-
isons revealed increases in leg and arm strength and im-
proved aerobic performance in both groups (p < 0.05). The CG participants also showed a slight reduction in BWI (p < 0.05). Additionally, in EG, handgrip strength and gross motor abilities also improved (p < 0.01) and significant enhancements were detected in reaction times in response to the training program (S-RT: -1.06 ± 14.99% vs. 10.70 ± 15.38%; C-RT: 3.63 ± 15.48% vs. 14.34 ± 15.58% for CG and EG respectively; p < 0.01) (Table 1).

The comparison of the two training programs for
the variables examined is detailed in Table 2. Compared
to CG, the EG showed greater improvements in response
to training in handgrip strength (16.31%; p < 0.01), arm strength (R-AS: 14.37%; L-AS: 16.17%; p < 0.05), and gross motor abilities (15.96%; p < 0.001). On average, functional training led to an 11% improvement in cogni- tive performance over recreational training (S-RT: 11.76%; C-RT: 10.71%; p < 0.05) (Table 2).

Tables 3 and 4 show the relationship between the
S-RT or C-RT and the fitness variables before and after
the training period. In pre- intervention, Pearson´s prod-
uct-moment correlation coefficients showed a wake-
moderate relationship between S-RT and C-RT and gross
motor abilities in the control group, there were however
no relationships of significance detected for experimental
group. In post- intervention, while no changes in correla-
tions were observed in the control group with respect to

Table 1. Response to the training program recorded in the experimental and control groups. Data expressed as mean (SD).

CG EG
PRE POST P-value PRE POST P-value
BMI (kg∙m-2) 30.31 (4.65) 30.12 (4.56) .300 30.10 (4.61) 30.0 (4.71) .254
WH-r (%) .91 (.09) .89 (.06) .116 .91 (.06) .90 .05) .129
S-RT (ms) .51 (.08) .52 (.08) .874 .47 (.09) .41 (.08) .006
C-RT (ms) .58 (.11) .55 (.11) .119 .56 (.14) .48 (.12) .001
HGS (kg) 39.91 (11.94) 41.59 (13.86) .207 44.42 (12.41) 52.25 (14.68) <.001 LS (rep) 11.75 (2.13) 14.31 (2.15) <.001 12.00 (2.56) 14.86 (2.77) <.001 R-AS(rep) 15.39 (2.64) 18.48 (2.84) <.001 14.68 (2.34) 19.55 (3.20) <.001 L-AS (rep) 16.13 (2.75) 19.13 (3.00) <.001 15.09 (2.37) 20.27 (3.33) <.001 AG (s) 6.13 (1.20) 6.27 (.97) .210 5.91 (.98) 5.11 (.72) .001 EAP (m) -9.10 (62.26) 30.54 (51.82) .001 5.66 (65.26) 29.36 (73.92) .046

CG = control group; EG = experimental group; PRE = pre-intervention; POST = post-intervention; BMI = body mass index;
WH-r = waist-hip ratio; S-RT = simple reaction time; C-RT = choice reaction time; HGS = handgrip strength; LS = leg
strength; R-AS = right arm strength; L-AS = left arm strength; AG = gross motor abilities; EAP = expected aerobic perfor-
mance; P-value = statistical significance at 95% CI (values in bold indicate a significant difference).

Ponce-Bravo et al.

719

Table 3. Correlation between reaction time (Simple and Choice) and physical performance variables in the control group.

PRE POST
S-RT C-RT S-RT C-RT

r P-value r P-value r P-value r P-value
HGS (kg) -.21 .239 -.20 .273 -.27 .128 -.27 .138
LS (rep) -.23 .204 -.08 .679 -.16 .368 -.29 .106
R-AS (rep) -.24 .181 -.13 .469 -.24 .200 -.21 .260
L-AS (rep) -.32 .075 -.18 .316 -.27 .149 -.21 .265
AG (s) .57 .001 .36 .041 .54 .001 .44 .013
EAP (m) -.21 .245 -.08 .646 -.23 .280 -.24 .255

r = Pearson’s linear correlation coefficient; HGS = handgrip strength; LS = leg strength; R-AS = right arm
strength; L-AS = left arm strength; AG = gross motor abilities; EAP = expected aerobic performance; P-value =
statistical significance at the 95% CI (values in bold indicate a significant difference).

Table 4. Correlation between reaction time (Simple and Choice) and physical performance variables in the ex-
perimental group.

PRE POST
S-RT C-RT S-RT C-RT

r P-value r P-value r P-value r P-value
HGS (kg) -.03 .905 -.32 .144 -.53 .012 -.29 .182
LS (rep) .04 .868 -.07 .744 -.04 .865 -.02 .923
R-AS (rep) .19 .378 -.24 .275 -.37 .085 -.43 .047
L-AS (rep) .33 .135 -.09 .693 -.41 .058 -.46 .033
AG (s) -.20 .359 -.12 .600 .32 .146 .37 .094
EAP (m) -.08 .747 -.25 .256 -.41 .058 -.50 .021

pre-intervention results, the experimental group displayed
a moderate correlation between S-RT and handgrip
strength and between C-RT and arms strength and the
expected aerobic performance (p < 0.05). Table 2. Comparison of training programs outcome. Data expressed as mean (SD).

Diff CG Diff EG p-value
BMI (kg∙m-2) -.19 (.49) -.10 (.42) .485
WH-r (%) -.02 (.08) -.01 (.03) .515
S-RT (ms) .00 (.08) -.06 (.09) .036
C-RT (ms) -.03 (.09) -.09 (.10) .030
HGS (kg) 1.68 (7.03) 7.84 (8.50) .005

LS (rep) 2.56 (1.78) 2.86 (2.10) .572
R-AS (rep) 2.56 (3.79) 4.86 (3.33) .025
L-AS (rep) 1.78 (5.47) 5.18 (3.25) .005
AG (s) 014 (.77) -.79 (.89) <.001 EAP (m) 39.64 (48.27) 23.70 (52.33) .288

CG = control group; EG = experimental group; Diff CG = post-
pre training difference recorded in CG; Diff EG = post-pre
training difference recorded in EG; BMI = body mass index;
WH-r = waist-hip ratio; S-RT = simple reaction time; C-RT =
choice reaction time; HGS = handgrip strength; LS = leg
strength; R-AS = right arm strength; L-AS = left arm strength;
AG = gross motor abilities; EAP = expected aerobic perfor-
mance; P-value = statistical significance at the 95% CI (values
in bold indicate a significant difference).

Discussion

This study sought to compare the effects of two physical
exercise programs (functional with elastic bands vs. rec-
reational) on the cognitive performance of adults older
than 60 years measured in terms of reaction times (S-RT
and C-RT). Our main finding was that 20 sessions of

either training mode, despite considerable content and
workload differences, showed beneficial effects on over-
all leg/arm strength and aerobic capacity (p < 0.05), though no appreciable impacts were produced on body composition. However, a functional exercise program using an elastic exercise band led to additional improve- ments over those produced in the control group in arm strength (Δ 15.27%; p < 0.05), handgrip strength (~ 16.32%; p < 0.001), gross motor abilities (~ 15.95%; p < 0.01), and cognitive performance (S-RT: 10.70%, C-RT: 14.34%; p < 0.01). Additionally, only the EG improved the relationship between reaction times and fitness varia- bles, confirming that better cognitive processes can be achieved as physical condition improves. However, the design used in this study did not allow us to determine if the mechanism responsible for this result is due to a min- imum level of change in physical performance, or if it is inherent in the training method employed in this study (combination of functional exercises and elastic bands).

The available literature is replete with reports of
training programs for individuals older than 60 years
targeted at improving both physical (Blain et al., 2000;
Karinkanta et al., 2009; Orr et al., 2008) and cognitive
skills (Angevaren et al., 2008; Berryman et al., 2014;
Brisswalter et al., 2002; Colcombe and Kramer 2003;
Forte et al., 2013; Liu-Ambrose and Donaldson, 2009;
Williamson et al., 2009). Baseline physical fitness and
reaction time data for our study population is consistent
with those reported for the same age group in similar
studies (Jones and Rikli, 2002; Van Boxtel et al., 1997).
In the present study, the control program was designed to
represent the more traditional interventions with a high
recreational component and low workload. In contrast, the
experimental program consisted of combined objective

Functional training and cognitive performance

720

sessions incorporating motor tasks simultaneously involv-
ing several body parts (functional exercises) (de Bruin
and Murer, 2007; de Vreede et al., 2005). These compo-
nents address in a single session a large number of com-
ponents implicated in cognitive decline (Voelcker-Rehage
et al., 2010). The use of elastic bands increases strength
gains as reflected by the improved effects of the experi-
mental intervention over the control intervention on
handgrip strength (16.31%; p < 0.01) and arm strength (R-AS = 14.37%; L-AS = 16.17%; p < 0.05). The shorter simple reaction time recorded in the EG and lack of change in this variable observed in the control group intervention concurs with the recommendation by Col- combe & Kramer (2003) that cardiovascular and re- sistance training should be combined in order to benefit cognitive skills (Tables 1 and 2). Our findings indicate that 20 sessions of recrea- tional physical training produced fitness but not cognitive benefits (Table 1). In contrast, a similar program involv- ing 20 sessions of resistance-band functional training induced a greater impact on fitness and a mean 11% im- provement in reaction times (simple and choice) (Tables 1 and 2). After 3 months (2 sessions/week) of multicompo- nent (neuromuscular coordination, balance, agility, and cognitive executive control) or progressive resistance training for strength gains, Forte et al (2013) observed that the beneficial effects of a resistance program on cog- nitive function were mediated by gains in muscular strength. However, the benefits of multicomponent train- ing displayed a direct cognitive stimulation by a direct influence on neuromuscular coordination and perceptual motor adaptations. Reports in the current literature have described both beneficial (Kalapotharakos et al., 2006) and inappreciable (Paas et al., 1994; Powell, 1983) effects of physical activity programs on reaction times. Reaction time decreases with age (Sturnieks, et al., 2008; Van Boxtel et al., 1997) independently of gender (Silverman, 2006; Wellmon, 2012) and moderately dependently on changes in aerobic capacity (Colcombe and Kraemer, 2003; Van Boxtel et al., 1997). The participants of our study, with a mean age of 70, showed no impairment in cognitive function and their aerobic performance was just at the lower expected limit. In contrast with other reports (Barella et al., 2010; Kalapotharacos et al., 2006), a bene- ficial effect was detected on aerobic capacity in response to both training interventions (p < 0.05), although only the experimental intervention led to improved reaction times (p < 0.01). Contrary with the findings of Van Boxtel et al. (1997), a positive change in correlation was detected between the C-RT and aerobic performance in EG (Table 4).

Other authors have reported cognitive function im-
provements ranging from 13.4% to 9.6% in response to a
12-week recreational activity program of 2 and 3 sessions
per week respectively in participants with a mean age of
79 years (p < 0.001) (Gálvez, 2012; Pereira, 2011). De- spite the similarity with our control intervention, the dif- ferent findings of these studies may be attributed to the mild cognitive impairment described for the participants of the studies by Gálvez and Pereira (scores of ~19 out of 30 in the Minimental test; MSSE; Folstein et al., 1975),

and the 9-year difference in age with our study partici-
pants. These differences along with the different training
regimens (20 vs. 24 vs. 36 sessions), could in part explain
the different physical performance gains recorded in the
different studies and our control group. Studies that have
linked improved cognitive function to gains in cardiovas-
cular capacity seem to suggest greater dedifferentiation in
neuron activation pathways in younger adults (Colcombe
and Kramer, 2003). Thus, recreational type activity ses-
sions do not seem to offer a stimulus that is able to im-
prove both the physical and cognitive capacities of older
persons with no cognitive impairment.

Other studies have shown a direct relationship be-
tween improved cognitive performance and cardiovascu-
lar fitness, strength or balance training (Araya, 2011;
Colcombe and Kramer, 2003). Araya et al. (2012), in
response to a 12-week physical training program (3 ses-
sions per week) completed by 33 women with a mean age
of 72 years and with mild cognitive decline (MSSE = 24
out of 30), noted the improved fitness of the participants
along with a cognitive capacity improvement of 7.4% (p
< 0.05). In agreement with these findings, we observed improvements in the fitness (strength and gross motor abilities; p < 0.05) and cognitive skills (11% in RT, p < 0.05) of participants in the functional training group com- pared to the recreational intervention group (Table 2). Hence, in only 20 sessions, it seems that a functional resistance-band exercise program is able to improve both physical fitness and cognitive function in elderly partici- pants with no cognitive deficiency. Such improvements are likely to play a role in preventing cognitive decline and maintaining independence. Finally, despite the apparent contribution of physical activity programs in ameliorating cognitive skills (Colcombe and Kramer, 2003; Forte et al, 2013; Voelcker-Rehage et al., 2010), only a moderate correla- tion was observed between handgrip-strength and the S- RT and between arm-strength and endurance and the C- RT (p < 0.05) in EG. No such correlation was found in the CG despite the improvements in leg and arm strength and aerobic performance. Considering the greater im- provements in strength and coordination following re- sistance band exercises when compared to recreational exercises, our results concur with other studies which reveal that the combination of physical and cognitive training maximizes cognitive benefits in the elderly (Fos- ter et al., 2013; Oswal et al, 2006). Other studies have also described the correlation between C-RT and aerobic capacity (Rikli and Edwards, 1991). However, in our study the combination of functional exercises with an elastic band in the EG did not allow us to determine if the mechanism responsible for these findings results from a minimum change in physical performance, or if this bene- fit is inherent to the experimental training method used. Indeed, the mechanisms that cause the cortical changes linked to cognitive performance seem to differ depending on the intervention (Berryman et al., 2014; Voelcker- Rehage et al., 2010). Our results indicate a need for gains greater than 20-23% in handgrip, arm and leg strength for the neurophysiological mechanisms that regulate sensory- motor function to produce a beneficial impact on percep-

Ponce-Bravo et al.

721

tion and reaction time, improving the gross motor abilities
(such as agility and balance), and thus reducing the risk of
falls (Sturnieks et al., 2008).

Conclusion

In summary, our findings indicate that 20 sessions of
functional resistance or recreational training lead to gen-
eral upper and lower body strength and aerobic capacity
gains in adults older than 60 years. However, the im-
proved cognitive function observed, as assessed through
reaction times, seems more linked to the workload and
resistance component of the training program. Thus, pro-
grams involving functional exercises with an elastic band
improve both simple and choice reaction times and lead to
greater gains in gross motor abilities, handgrip and arm
strength over the improvement achieved by a more recre-
ational type program. In turn, these latter gains correlate
to improved C-RT. Collectively our findings indicate that
exercise sessions of more recreational type contents do
not seem to constitute a stimulus that is able to improve
both physical and cognitive performance in healthy active
older adults. We therefore recommend the incorporation
of functional elastic-band exercises in physical activity
programs designed for this population group.

Acknowledgements
The authors thank the elderly of the village of Maracena (Granada,
Spain) and the Maracena Town Hall for their enthusiasm and willing-
ness to participate in this study. The study was financed by Research
group SEJ-438 of the Junta de Andalucía.

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Key points

• Better cognitive processes can be achieved as phys-

ical condition improves

• Exercise sessions of a more recreational type do not
seem to constitute a stimulus able to improve both
physical and cognitive performance in healthy ac-
tive older adults

• The improvement of cognitive function, as assessed
through reaction times, seems more linked to the
workload and strength component of the training
program.

AUTHOR BIOGRAPHY

Hernán PONCE-BRAVO
Employment
Lecturer in Sports Training, Swimming
Training. Department of Physical Education
and Sport Training, National University of
Chimborazo- Ecuador. PhD student. De-
partment of Physical Education and Sport,
University of Granada. Spain.
Degree
MSc
Research interests
Physical activity and health.
E-mail: herpobraunach@hotmail.com

Christian PONCE
Employment
PhD student. Department of Physical Edu-
cation and Sport, Faculty of Sport Sciences,
University of Granada, Granada, Spain.
Degree
MSc
Research interests
Physical Activity and health.
E-mail: christian.natacion@gmail.com

Belén FERICHE Employment
Lecturer in Sport Training. Department of
Physical Education and Sport, University of
Granada, Spain.
Degree
PhD
Research interests
Sport training, training assessment, altitude
training.
E-mail: mbelen@ugr.es

Paulino PADIAL
Employment
Lecturer in Sport Training. Department of
Physical Education and Sport, University of
Granada, Spain.
Degree
PhD
Research interests
Strength training, sport performance and
training in combat sports.
E-mail: ppadial@ugr.es

 Paulino Padial
Department of Physical Education and Sport, Faculty of Sport
Sciences, University of Granada, Granada, Spain

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RESEARCH ARTICLE

The Association of Childhood Fitness to
Proactive and Reactive Action Monitoring
Keita Kamijo1*, Seongryu Bae2, Hiroaki Masaki2

1 Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan, 2 Department of Functioning
Activation, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan

* k-kamijo@aoni.waseda.jp

Abstract
Several studies have claimed that the positive association between childhood fitness and

cognitive control is attributable to differences in the child’s cognitive control strategy, which

can involve either proactive or reactive control. The present study tested this hypothesis by

manipulating the probability of trial types during a modified flanker task. Preadolescent chil-

dren performed mostly congruent and mostly incongruent conditions of the flanker task, with

post-error task performance and error negativity/error-related negativity (Ne/ERN) being

assessed. Results indicated that greater aerobic fitness was related to greater post-error accu-

racy and larger Ne/ERN amplitudes in the mostly congruent condition. These findings suggest

that higher-fit children might be able to transiently upregulate cognitive control by recruiting

reactive control in the mostly congruent condition. Further, greater fitness was related to

greater modulation of Ne/ERN amplitude between conditions, suggesting that higher-fit chil-

dren engaged in more proactive control in the mostly incongruent condition. This study sup-

ports the hypothesis that greater childhood fitness is associated with a more flexible shift

between reactive and proactive modes of cognitive control to adapt to varying task demands.

Introduction
For over a decade and a half, it has become increasingly clear that regular physical activity can
promote brain health and improve cognitive function in adult populations [1–3]. More
recently, research has started to examine this relationship in child populations, demonstrating
that greater physical activity levels and greater aerobic fitness are positively associated with
cognitive functioning (see [4, 5] for reviews). Although most previous studies have employed
cross-sectional designs that compared cognitive performance across lower-fit and higher-fit
children, recent longitudinal randomized controlled intervention studies have provided evi-
dence of a causal link between physical activity and changes in cognitive function [6–8]. Specif-
ically, these longitudinal studies indicated that a physical activity intervention leading to
increases in aerobic fitness improves higher-order cognitive function, also known as cognitive
control, in preadolescent children. These findings emphasize the importance of physical activ-
ity, not only for prevention of metabolic syndrome but also for cognitive development and
brain health. In light of the worldwide epidemic of childhood inactivity [9, 10], the link
between childhood fitness and cognitive control should be further clarified.

PLOS ONE | DOI:10.1371/journal.pone.0150691 March 3, 2016 1 / 13

OPEN ACCESS

Citation: Kamijo K, Bae S, Masaki H (2016) The
Association of Childhood Fitness to Proactive and
Reactive Action Monitoring. PLoS ONE 11(3):
e0150691. doi:10.1371/journal.pone.0150691

Editor: Francesco Di Russo, University of Rome,
ITALY

Received: October 27, 2015

Accepted: February 18, 2016

Published: March 3, 2016

Copyright: © 2016 Kamijo et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.

Data Availability Statement: All relevant data are
within the paper and its Supporting Information files.

Funding: This work was supported by a Grant-in-Aid
to KK for Research Activity Start-up (24800066) from
the Japan Society for the Promotion of Science and
the MEXT-Supported Program for the Strategic
Research Foundation at Private Universities, 2015–
2019, from the Ministry of Education, Culture, Sports,
Science and Technology (S1511017). The funders
had no role in study design, data collection and
analysis, decision to publish, or preparation of the
manuscript.

http://crossmark.crossref.org/dialog/?doi=10.1371/journal.pone.0150691&domain=pdf

http://creativecommons.org/licenses/by/4.0/

Cognitive control refers to the ability to coordinate thought and action to execute goal-
directed behaviors [11]. It has been well documented that the prefrontal cortex (PFC), which
shows protracted maturation [12], plays a critical role in the effective regulation of cognitive
control [11]. Although the underlying mechanisms for the beneficial effects of aerobic fitness
are still controversial, nonhuman animal models have suggested that aerobic exercise increases
nerve growth factors such as brain-derived neurotrophin factor [13], which promotes synaptic
plasticity and neurogenesis [14, 15]. It is likely that exercise-induced increases in aerobic fitness
are specifically associated with the development of higher-order cognitive function (i.e., cogni-
tive control), which is supported by one of the last brain regions to mature (i.e., the PFC).
Stated differently, aerobic fitness may be essential for development of the cognitive control net-
work, including the PFC, during childhood. The present study was designed to provide addi-
tional insight into the association between childhood fitness and cognitive development by
focusing on cognitive control strategy use, which is linked to PFC activity [16, 17].

Action monitoring has been considered one of the key aspects of cognitive control, since
individuals need to monitor and correct their actions during subsequent environmental inter-
action to optimize goal-directed behaviors. Several neuroelectric studies using error negativity
(Ne) [18] or error-related negativity (ERN) [19] have indicated that aerobic fitness is associated
with action monitoring system efficiency in preadolescent children [20, 21]. The Ne/ERN is a
negative-going component of the response-locked event-related brain potential (ERP) which is
elicited following commission errors during a cognitive task. The Ne/ERN has a fronto-central
scalp distribution, and is thought to reflect activity of the anterior cingulate cortex (ACC) [22–
24], which plays a crucial role in action monitoring [22, 25]. Hillman and his colleagues have
indicated that higher-fit children exhibit smaller Ne/ERN amplitude with superior task perfor-
mance relative to their lower-fit counterparts [20, 21]. These results suggest that greater child-
hood fitness is associated with less ACC activation, which is thought to reflect more efficient
action monitoring (i.e., superior cognitive control).

Several researchers have proposed a possible explanation for the association between child-
hood fitness and cognitive control [8, 21, 26, 27], which is based on the dual mechanisms of con-
trol (DMC) theory [16, 17]. They propose that the association can be attributed to differences in
the child’s cognitive control strategy, which can involve either proactive or reactive control. Pro-
active control is associated with sustained lateral PFC activation, which is linked to decreased
transient ACC activation, to anticipate and prevent interference before it occurs. By contrast,
reactive control is associated with transient activation of the lateral PFC and a wider brain net-
work including the ACC to detect and resolve interference on an as-needed basis. Based on this
theory, smaller Ne/ERN amplitude (i.e., less ACC activation) for higher-fit children is hypothe-
sized to reflect more efficient action monitoring due to their utilization of a proactive control
strategy. Using a cue-probe task (i.e., an AX-continuous performance task), Chatham, Frank [28]
indicated that young children (3 years) used more probe-driven reactive control, whereas older
children (8years) engaged in more cue-driven proactive control. An fMRI study that compared
Stroop task related brain activity across adolescents (14–17 years) and young adults (18–25
years) indicated that the neural systems underlying proactive control are still underdeveloped in
adolescents [29]. Thus, these developmental studies suggest that proactive control mechanisms
show protracted maturation relative to reactive control mechanisms, and that they continue to
mature through childhood and into early adulthood. As mentioned earlier, the findings of longi-
tudinal studies [6–8] imply that childhood fitness is associated with development of the cognitive
control network involving the PFC. In accordance with these findings, a hypothesized association
between childhood fitness and cognitive control strategy use appears to be reasonable.

To test this hypothesis, the present study examined the association between childhood fit-
ness and action monitoring by manipulating the probability of trial types during a modified

Fitness and Action Monitoring Strategy

PLOS ONE | DOI:10.1371/journal.pone.0150691 March 3, 2016 2 / 13

Competing Interests: The authors have declared
that no competing interests exist.

flanker task. In neuroelectric studies which reported a difference in Ne/ERN amplitude
between lower-fit and higher-fit children [20, 21], congruent and incongruent trials were pre-
sented equally during the flanker task. An fMRI study [30] manipulated the probability of trial
types during the Stroop task and indicated that young adult participants exhibited a smaller
interference effect on reaction time (RT; i.e., incongruent RT minus neutral RT) in the mostly
incongruent (MI; 70% of trials were incongruent) condition, relative to the mostly congruent
(MC; 70% of trials were congruent) condition, with increased sustained lateral PFC activation
and decreased transient ACC activation. Such a pattern of results suggests that participants are
biased toward adoption of a proactive control strategy in the MI condition. In the MC condi-
tion, by contrast, there was decreased sustained activity in the lateral PFC and increased tran-
sient activity in the PFC and ACC (De Pisapia & Braver, 2006), which is thought to reflect a
greater utilization of reactive control. In line with this, it has been suggested that interference
expectancy can influence reliance on proactive versus reactive modes of cognitive control [31].
Specifically, young adult participants should engage in more proactive control when interfer-
ence is frequent and expected, whereas reactive control should be dominant when interference
is infrequent and unexpected. Thus, it is likely that young adults change cognitive control strat-
egy based on the probability of trial types, in order to adapt to varying task demands. If child-
hood fitness is associated with cognitive development, higher-fit children should show a
pattern more similar to that observed in young adults relative to lower-fit children, based on
trial type probabilities.

An fMRI study compared brain activity between lower-fit and higher-fit children during the
MC and MI conditions of a modified flanker task [26]. This study found greater ACC activity
for higher-fit children, relative to lower-fit children, in the MC condition, whereas no such
group difference was observed in the MI condition. This pattern of results, coupled with a
smaller interference effect on accuracy for higher-fit children, suggests that higher-fit children
engaged in more reactive control strategies in the MC condition relative to lower-fit children
and flexibly changed cognitive control strategies to adapt to the increased task demands in the
MI condition. However, higher-fit children also exhibited an increased sustained PFC activa-
tion relative to lower-fit children in the MC condition [26], which contradicts the DMC theory.
One possible source of this discrepancy is that this fMRI study used a block design, which
could not dissociate transient from sustained brain activation.

The current study further examined the association of childhood fitness to cognitive control
strategy using the Ne/ERN, which is thought to be suitable to assess transient brain activation
due to its high temporal resolution. We predicted that greater aerobic fitness would be related
to smaller Ne/ERN amplitudes in the MI condition, reflecting a greater utilization of a proac-
tive control strategy, whereas such a relationship should be attenuated or even reversed in the
MC condition. Additionally, we used post-error accuracy and post-error slowing as behavioral
indices of action monitoring. It is well known that individuals show reduced response speed
following an error of commission [32], possibly to prevent subsequent errors during cognitive
tasks. That is, greater post-error behavioral adjustments are considered to reflect greater utili-
zation of a reactive control strategy. Accordingly, we predicted that greater aerobic fitness
would be related to greater post-error behavioral adjustments in the MC condition, whereas
such a relationship should be attenuated in the MI condition.

Methods

Participants
Fifty preadolescent children participated in this study. The participants also performed an AX-
continuous performance task in order to investigate a different cognitive process (i.e., task

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preparation), and as such, we will report these results elsewhere. Given that weight status has
been associated with cognitive control during childhood [33], data from three obese children
and one underweight child, as defined by the national cutoff points [34], were excluded from
the analyses. Additionally, data from four participants were discarded due to an insufficient
number of error trials to compute Ne/ERN averages (< 6 trials) [35, 36]. Thus, analyses were conducted for 42 participants (mean age = 10.5 years, SD = 1.1). Table 1 summarizes demo- graphic and fitness information for this sample. Prior to testing, legal guardians reported that their children were free of neurological diseases or physical disabilities and had normal or cor- rected-to-normal vision. All participants provided written assent and their legal guardians pro- vided written informed consent in accordance with the Ethics Committee on Human Research of Waseda University.

Laboratory Procedure
After providing informed consent, participants had their height and weight measured using a
Tanita WB-3000 digital scale (Tanita Corp., Tokyo, Japan). Participants’ legal guardians com-
pleted the Attention Deficit Hyperactivity Disorder Rating Scale IV [37] and the Physical
Activity Readiness Questionnaire [38] to screen for any previous health issues that might be
exacerbated by exercise. Additionally, given that socioeconomic status has been associated with
cognitive control [39] and fitness [40], maternal educational attainment was assessed as a
proxy for socioeconomic status. Maternal education was assessed using a five-point scale rang-
ing from 1, indicating that they did not complete high-school, to 5, indicating an advanced
degree. Participants were then fitted with a 64-channel headcap with Ag/AgCl active electrodes
(BioSemi ActiveTwo system, Amsterdam, the Netherlands) and seated in a sound-attenuated
room where the flanker task took place. Participants were then given instructions, afforded the
opportunity to ask questions, and practiced the task prior to the start of testing. The 20-m shut-
tle run test was conducted on a different day.

Flanker Task
A modified flanker task consisting of five left- or right-oriented fish was used. This task asked
participants to press a button with their index fingers as accurately and quickly as possible cor-
responding to the direction of a centrally presented target fish and to ignore the flanking fish.
The target fish was surrounded by flanking fish that either pointed in the same direction (con-
gruent trials) or the opposite direction (incongruent trials). The flanker task was performed
under two conditions in which the probability of congruent and incongruent trials was

Table 1. Mean (SD) values for participant demographics and fitness data.

Measure All participants Girls Boys

No. of participants 42 19 23

Mean age (years) 10.5 (1.1) 10.2 (0.9) 10.7 (1.1)

20-m shuttle run (#laps) 51.3 (22.0) 42.9 (19.5) 58.2 (21.9)

20-m shuttle run (percentile) 53.3 (32.3) 54.1 (32.9) 52.7 (32.6)

Body mass index (kg/m2) 16.8 (1.6) 16.5 (1.2) 17.0 (1.9)

Maternal education 2.8 (0.9) 2.8 (0.8) 2.8 (1.0)

ADHDa 7.8 (6.3) 7.1 (6.9) 8.4 (5.8)

aRaw scores on the Attention Deficit Hyperactivity Disorder Rating Scale IV.

doi:10.1371/journal.pone.0150691.t001

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manipulated. In the MC condition, 70% of trials were congruent and 30% were incongruent,
whereas in the MI condition, 30% of trials were congruent and 70% were incongruent. The
order of conditions was counterbalanced across the participants. After 40 practice trials, partic-
ipants completed 320 experimental trials (160 trials × 2 blocks) in each condition. The viewing
distance was 1 m and the stimuli subtended a horizontal visual angle between the two outside
positions of 9.7° and a vertical visual angle of 1.2°. Stimulus duration was 200 ms, with a ran-
domized stimulus onset asynchrony (SOA) between 1500 and 1900 ms (mean = 1700 ms).

Task Performance
Post-error accuracy was defined as the percentage of correct responses following trials with
errors of commission. Post-error slowing was defined as the mean RT for correct trials follow-
ing an error of commission trial minus the mean RT for correct trials following a correct trial.
Post-error task performance was calculated across congruency due to an insufficient number
of errors of commission for the congruent trials.

ERP Recording
EEG activity was measured from 64 electrode sites arranged in an extended montage based on
the International 10–10 system [41], as well as two electrodes placed on the right and left mas-
toids. Electrooculographic activity was collected from electrodes placed above and below the
right orbit and on the outer canthus of each eye to record bipolar eye movements. Continuous
data were recorded with a bandwidth of DC to 208 Hz (–3 dB/octave), using the BioSemi
Active Two system and sampled at 1024 Hz. Offline EEG processing, which was performed
using Brain Vision Analyzer 2 software (Brain Products, Gilching, Germany), included eye
movement correction using the procedure described by Gratton, Coles [42], re-referencing to
average mastoids, creation of response-locked epochs (–450 to 650 ms relative to response
onset), baseline correction (−100 to 0 ms relative to response onset), bandpass filtering (1–12
Hz, 24 dB⁄octave), and artifact rejection (epochs with signals that exceeded ± 100 μV were
rejected). Average ERP waveforms were created for error of commission trials (i.e., Ne/ERN)
and correct trials (i.e., correct negativity/correct response negativity: Nc/CRN) [43]. Trials with
an error of omission were rejected and the waveforms were averaged across congruency. Across
conditions, a mean of 31 and 278 trials were averaged for Ne/ERN and Nc/CRN, respectively.
Ne/ERN amplitude was assessed at the FCz electrode site, where it reached its topographic
maximum (see Fig 1B), and was quantified as the mean voltage within a 20 to 80 ms latency
window relative to response onset.

Fitness Assessment
Participants’ fitness was assessed using the multistage 20-m shuttle run test (also known as the
Progressive Aerobic Cardiovascular Endurance Run: PACER). The 20-m shuttle run test was
performed according to Leger, Mercier [44]. Participants were required to run back and forth
between two lines 20 m apart paced by a tone on a CD player signaling when they should reach
the opposite line. The initial speed was set at 8.5 km/h, with the speed increasing by 0.5 km/h
every minute. The test was continued until the participant stopped due to fatigue or could not
reach the end lines concurrent with the audio signals on two consecutive occasions. The fin-
ished lap number was recorded. To exclude age- and sex-related differences, in this study the
age- and sex-specific percentile score was calculated as an index of aerobic fitness based on nor-
mative data provided by the Japanese Ministry of Education, Culture, Sports, Science and
Technology [45].

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Statistical Analysis
Initial Pearson product-moment correlations were computed between demographic factors
and dependent variables (i.e., post-error task performance and Ne/ERN amplitude). Hierarchi-
cal linear regression analyses were then performed for each dependent variable. Age, sex
(dummy coded, 0 = girls, 1 = boys), and maternal education were included in step 1 as control
variables, and aerobic fitness (20-m shuttle run test percentile score) was then added to step 2
of the analysis. The significance of the change in the R2 value between the two steps was used

Fig 1. A: Grand averaged response-locked ERP waveforms for error trials (Ne/ERN) and correct trials (Nc/CRN) for each condition at FCz electrode site. B:
Topographical maps of the Ne/ERN amplitudes for each condition.

doi:10.1371/journal.pone.0150691.g001

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to judge the independent contribution of the fitness measure for explaining variance in the
dependent variables. All statistical analyses were conducted using a significance level of p = .05.

Results

Task Performance
Results of the correlational analysis for post-error task performance and Ne/ERN amplitude
are provided in Table 2. The correlation analysis revealed that greater fitness was related to
greater post-error accuracy for the MC condition, r = .28, p = .035 (one-tailed), whereas no
such relationship was observed for the MI condition, r = .12, p = .23. The regression analysis
yielded no significant relationship between fitness and post-error accuracy for both MC and
MI conditions. The correlation and regression analyses of post-error slowing revealed no sig-
nificant relationship with fitness for either the MC or MI condition.

Ne/ERN
Fig 1A illustrates grand averaged response-locked ERP waveforms for error trials (Ne/ERN)
and correct trials (Nc/CRN) for each condition at the FCz electrode site, on which a median
split was performed on the 20-m shuttle run test percentile scores within each sex to visualize
the association between fitness and Ne/ERN amplitude. Preliminary Bonferroni-corrected t-
tests were conducted within each condition comparing Ne/ERN amplitude with Nc/CRN
amplitude. Results indicated larger Ne/ERN amplitude relative to Nc/CRN amplitude across
conditions, ts(42) � 7.0, ps � .001, confirming the expected accuracy effect.

A median split was performed on the 20-m shuttle run test percentile scores within each sex
to visualize the association between fitness and Ne/ERN amplitude.

The correlation analysis revealed that greater fitness was related to larger Ne/ERN ampli-
tude for the MC condition, r = –.43, p = .004, whereas no such relationship was observed for
the MI condition, r = –.18, p = .27 (Table 2). A summary of the regression analyses for Ne/ERN
amplitude for each condition is provided in Table 3. The regression analysis for the MC condi-
tion yielded a significant change in R2 at step 2, F(1, 37) = 13.3, p = .001, indicating that greater
fitness was associated with larger Ne/ERN amplitude. For the MI condition, no significant

Table 2. Pearson product-moment correlation coefficients between variables.

Variable 1 2 3 4 5 6 7 8 9 10

1. Fitness —

2. Age –.20 —

3. Sexa –.02 .26 —

4. Maternal education .10 –.45* –.04 —

5. MC. Post-error accuracy .28† –.26† –.24 .31* —

6. MI. Post-error accuracy .12 –.13 –.24 .16 .66* —

7. MC. Post-error slowing .05 –.16 –.21 .08 .01 –.07 —

8. MI. Post-error slowing .19 .00 –.34* –.19 .17 .42* .25 —

9. MC. Ne/ERN amplitude –.43* –.24 –.19 .24 –.06 .05 .24 –.04 —

10. MI. Ne/ERN amplitude –.18 –.27† –.16 .18 .15 .01 .25 –.16 .64* —

aSex was dummy coded, 0 = girls, 1 = boys.

*Two-tailed p � .05.
†One-tailed p � .05.

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fitness influence was present at step 2, F(1, 37) = 2.3, p = .14. An additional multiple hierarchi-
cal regression analysis was conducted to examine the difference in Ne/ERN amplitude between
the MC and MI conditions (i.e., MC–MI). This analysis tested for a possible relationship
between fitness and differences in ACC activity, which is thought to reflect the flexibility to
change cognitive control strategy use based on the probability of trial types. This analysis
yielded a significant change in the R2 at step 2, F(1, 37) = 4.0, p = .05, indicating that greater fit-
ness was associated with greater modulation of Ne/ERN amplitude between the MC and MI
conditions.

Discussion
The main findings here were that greater aerobic fitness was related to larger Ne/ERN ampli-
tude, which reflects increased transient ACC activation, in the MC condition. Additionally,
although the regression analysis revealed no relationship between fitness and post-error task
performance, correlation analyses implied that greater aerobic fitness was associated with
greater post-error accuracy in the MC condition. Based on the DMC theory [16, 17, 30], these
findings suggest that higher-fit children might be able to maintain greater post-error accuracy
in the MC condition relative to lower-fit children by recruiting reactive control, as denoted by
larger Ne/ERN amplitude. This interpretation can also be accounted for by conflict monitoring
theory [46]. This theory proposes that the ACC monitors response conflict on error trials and
provides a signal to the dorsolateral PFC to upregulate cognitive control in support of behav-
ioral adjustments on subsequent trials [25, 46]. Accordingly, we suggest that the observed
larger Ne/ERN amplitude and greater post-error accuracy in the MC condition for higher-fit
children represent transient intensification of cognitive control due to greater utilization of
reactive control.

More importantly, greater fitness was associated with greater modulation of Ne/ERN ampli-
tude between the MC and MI conditions. Stated differently, higher-fit children had smaller Ne/
ERN amplitude in the MI condition relative to the MC condition, whereas such a relationship
was attenuated for lower-fit children. Based on the DMC theory [16, 17, 30], it is plausible that
the decreased Ne/ERN amplitude (i.e., less ACC activation) in the MI condition for higher-fit
children is due to increased sustained PFC activation, reflecting a greater utilization of proac-
tive control. Thus, these findings suggest that greater childhood fitness is associated with a
more flexible shift between reactive and proactive modes of cognitive control based on the
probability of trial types.

However, it is noteworthy that, contrary to our hypothesis, aerobic fitness was not related to
Ne/ERN amplitude in the MI condition. Pontifex, Raine [21] manipulated stimulus-response

Table 3. Summary of regression analyses for variables predicting Ne/ERN amplitude.

MC MI MC–MIa

ΔR2 β ΔR2 β ΔR2 β

Step1 .10 .09 .02

Age –.12 –.21 .11

Sex –.16 –.10 –.07

Maternal education .18 .08 .13

Step 2 .24* .05 .10*

Fitness –.50* –.24 –.32*

aA difference in Ne/ERN amplitude between the MC and MI conditions.

*p � .05.

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compatibility during a modified flanker task, and observed smaller Ne/ERN amplitude and
superior task performance, which may reflect recruitment of proactive control by higher-fit
children, relative to lower-fit children, in the stimulus-response compatible condition. Higher-
fit children also exhibited superior task performance in the stimulus-response incompatible
condition, but had increased Ne/ERN amplitude that did not differ from lower-fit children.
These findings imply that higher-fit children engaged more in reactive control in the more
effortful condition (i.e., incompatible condition) to meet the increased task demands. Although
it remains unclear whether proactive control and reactive control are fully independent, they
may be able to be engaged simultaneously [16, 17]. Taken together, in the present study, we
speculate that higher-fit children might engage in both proactive and reactive control simulta-
neously in the more demanding condition (i.e., MI condition), and therefore aerobic fitness
was not related to Ne/ERN amplitude. Given that this is merely speculation, further studies are
required to confirm this interpretation using fMRI techniques to assess both transient and sus-
tained brain activation.

Given the cross-sectional design used here, this study does not demonstrate a causal rela-
tionship between changes in childhood fitness and cognitive control strategy use. A random-
ized controlled intervention study [8] showed that a physical activity program, one that lead to
increases in aerobic fitness, improved working memory performance on a modified Sternberg
task. Further, the program improved the effectiveness of task preparation, as assessed by con-
tingent negative variation (CNV). The CNV is a negative slow potential that develops during
the foreperiod between warning and imperative stimuli, and is composed of at least two differ-
ent components, the early and late CNVs [47, 48]. Kamijo, Pontifex [8] indicated that the phys-
ical activity program selectively enhanced early but not late CNV amplitude. An fMRI study
manipulated participants’ cognitive control strategy (i.e., proactive or reactive) during the
Sternberg task, and observed increased sustained PFC activation during the foreperiod with
superior task performance when participants engaged in proactive control, relative to reactive
control [49]. Based on this study, it is plausible that the selective effect of the physical activity
program on the early CNV, which was accompanied by improvement in task performance,
indicates a strategy shift from reactive control to proactive control due to increased fitness.
Thus, although this longitudinal study did not manipulate cognitive control strategies [8],
these findings imply a causal relationship between fitness and cognitive control strategy use
during childhood.

A cross-sectional study has supported the association between childhood fitness and cogni-
tive control strategy by focusing on the effectiveness of task preparation [27]. Berchicci, Ponti-
fex [27] assessed the Bereitschaftspotential (BP) and the prefrontal negativity (pN) during a
modified flanker task. The BP and pN are negative slow potentials that develop around 1.5 to 1
s before movement onset, and believed to reflect responses [50] and cognitive preparation [27,
51], respectively. Berchicci, Pontifex [27] indicated that higher-fit children exhibited larger pN
relative to their lower-fit counterparts, whereas no such difference was observed for the BP.
The larger pN observed in higher-fit children might reflect more effective cognitive preparation
by their utilization of a proactive control strategy, which is consistent with the above described
CNV study [8]. Note that although we also assessed the BP and pN in the present study, no
association between fitness and pN/BP amplitude was observed (S1 Text). The implication of
this discrepancy might be related to the difference in SOA used for the flanker task. The SOA
was randomized in the present study, whereas it was fixed in the previous study [27]. A ran-
domized SOA might make it more difficult to prepare for upcoming stimuli. We believe that in
the present study fitness was not associated with cognitive preparation processes (i.e., pN
amplitude) for this reason.

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As stated in the introduction, animal studies suggest that exercise induced increases in
nerve growth factors relate to increases in the number of synaptic connections and the develop-
ment of new neurons that support learning and memory [14, 15]. If these changes were to
occur in the human brain, it is no wonder that cognitive control strategies are susceptible to the
effect of aerobic fitness, given that the neural networks underlying cognitive control strategies
are still underdeveloped during childhood [29]. It is reasonable to suggest that the present
results for neuroelectric (i.e., Ne/ERN) and behavioral (i.e., post-error accuracy) measures of
action monitoring indicate differences in children’s cognitive control strategies based on their
fitness level. Nonetheless, additional longitudinal studies are needed to examine how changes
in physical activity and fitness influence cognitive control strategies during childhood.

Another limitation is that findings of previous neuroelectric studies [20, 21] that observed
smaller Ne/ERN amplitudes for higher-fit relative to lower-fit children would appear to be
inconsistent with the present results. In the previous studies’ flanker task, congruent and
incongruent trials were presented equally often. Given that we did not employ a 50/50 condi-
tion in this present study and did find that the association between childhood fitness and action
monitoring differed based on the probability of trial types, it is difficult to compare and con-
trast study outcomes among these neuroelectric studies.

Conclusion
On the basis of results from neuroelectric and behavioral measures of action monitoring, we
suggest that higher-fit children showed a strategic shift from use of reactive control in the MC
condition to increasing use of proactive control in the MI condition. The shift in the cognitive
control mode based on the probability of trial types for higher-fit children is similar to that
observed in young adults in a previous study [30]. Thus, the current findings suggest that child-
hood fitness may be associated with development of the neural network underlying cognitive
control strategies. In conclusion, this study suggests that greater childhood fitness is associated
with a more flexible shift between reactive and proactive modes of cognitive control to adapt to
varying task demands.

Supporting Information
S1 Dataset. Demographic, fitness, behavioral, and neuroelectric data for the 42 partici-
pants.
(XLSX)

S1 Fig. A: Grand averaged stimulus-locked ERP waveforms for each condition at Fpz (pN)
and Cz (BP) electrode site. B: Topographical maps of the pN/BP amplitudes for each condi-
tion.
(PDF)

S1 Text. pN/BP analysis and results.
(DOCX)

Author Contributions
Conceived and designed the experiments: KK HM. Performed the experiments: KK SB. Ana-
lyzed the data: KK. Contributed reagents/materials/analysis tools: KK HM. Wrote the paper:
KK HM SB.

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PLOS ONE | DOI:10.1371/journal.pone.0150691 March 3, 2016 10 / 13

http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0150691.s001

http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0150691.s002

http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0150691.s003

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138

The authors are with the Dept. of Kinesiology and Community
Health, University of Illinois at Urbana-Champaign, Urbana,
IL. Address author correspondence to Naiman A. Khan at
nakhan2@illinois.edu.

Pediatric Exercise Science, 2014, 26, 138-146
http://dx.doi.org/10.1123/pes.2013-0125
© 2014 Human Kinetics, Inc.

The Relation of Childhood Physical Activity and Aerobic
Fitness to Brain Function and Cognition: A Review

Naiman A. Khan and Charles H. Hillman
University of Illinois at Urbana-Champaign

Physical inactivity has been shown to increase the risk for several chronic diseases across the lifespan. How-
ever, the impact of physical activity and aerobic fitness on childhood cognitive and brain health has only
recently gained attention. The purposes of this article are to: 1) highlight the recent emphasis for increasing
physical activity and aerobic fitness in children’s lives for cognitive and brain health; 2) present aspects of
brain development and cognitive function that are susceptible to physical activity intervention; 3) review neu-
roimaging studies examining the cross-sectional and experimental relationships between aerobic fitness and
executive control function; and 4) make recommendations for future research. Given that the human brain is
not fully developed until the third decade of life, preadolescence is characterized by changes in brain structure
and function underlying aspects of cognition including executive control and relational memory. Achieving
adequate physical activity and maintaining aerobic fitness in childhood may be a critical guideline to follow
for physical as well as cognitive and brain health.

Keywords: executive function, relational memory, pediatrics

Regular physical activity has been shown to be pro-
tective against the development of several diseases includ-
ing obesity, cardiovascular disease, certain cancers, and
Type II diabetes (73). Given that these diseases have also
been associated with reduced cognitive and brain health
among older adults (21,35), physical activity is suggested
to indirectly improve cognition and brain health by
attenuating the risk for disease. However, research from
rodent models demonstrates that physical activity is a
potent stimulator of processes underlying neurogenesis,
synaptogenesis, as well as brain vasculature (53,72). In
addition, physical activity training has been shown to
counter age-related hippocampal tissue loss and improve
spatial memory function among older adults (31). Taken
together, the findings from both rodent and older human
studies suggest that physical activity may indirectly or
directly modulate cognitive function and brain health.

Converging lines of research indicate that regular
physical activity and enhanced aerobic fitness may
improve cognitive function and brain health in childhood
as well. Higher-fit preadolescent children exhibit greater
attention (42), faster information processing speed (43),
and achieve higher scores on standardized achievement
tests (11,27), relative to their lower-fit counterparts.

These benefits were highlighted by a recent Institute
of Medicine (48) committee charged with examining
the status of physical activity and physical education in
schools, how physical activity and fitness affect health
outcomes, and ways to help schools get students to
become more active. While acknowledging the fiscal and
policy challenges involved, the final committee report
recognized that attaining over 60 min of moderate to
vigorous physical activity (MVPA) during the school
day is necessary for optimal learning in the classroom.
To represent the full scope of the positive contribution of
regular physical activity to overall health and function,
a team of kinesiologists validated the Human Capital
Model (HCM) of physical activity (3). The HCM is sup-
ported by a growing community of public, private, and
civil sector organizations. It considers physical activity
an investment and consolidates the evidence for physi-
cal activity benefits into six domains including physical,
emotional, individual, social, intellectual, and financial.
Taken together, the Institute of Medicine report and the
HCM place an emphasis on childhood health and provide
a platform for implementing physical education and other
physical activity opportunities in schools along with
a holistic conceptual model that incorporates physical
activity benefits for cognitive function and brain health.

However, much remains to be learned regarding
the influence of physical activity on specific cognitive
processes and their neural substrates. Knowledge from
the developmental literature is largely based on observa-
tional/cross-sectional studies. Thus, information on the

Official Journal of NASPEM and the
European Group of PWP

www.PES-Journal.com
REVIEWS

Brain and Cognition 139

efficacy of improving physical activity and/or aerobic
fitness for cognitive function and brain health in child-
hood remains limited. It is of particular importance to
examine how the protracted development of specific
brain structures provides opportunities for environmental
modulation by health behaviors including physical activ-
ity. Keeping this in mind, our laboratory and colleagues
have focused efforts on examining physical activity
effects on the cognitive processes of executive control
and relational/associative memory because the key neural
structures subserving these processes—the prefrontal
cortex and hippocampus—continue to develop through-
out childhood. Furthermore, these cognitive processes
and their neural substrates provide the foundation for
successful learning and scholastic achievement, thereby
influencing overall health and well-being throughout life.

In this article, we review the brain developmental
trajectory and evaluate observational and intervention
studies examining relationships between physical activity
and fitness with cognitive performance and brain health
in childhood.

Brain Development
The human brain undergoes a fourfold increase in volume
from birth to adolescence resulting in an adult brain that
is highly structured and functionally specialized (49).
Gestation represents a period of rapid brain development
involving several synchronized processes including neu-
rogenesis, migration, programmed cell death, myelina-
tion, and synaptogenesis (56). In addition, sulci and gyri
formation is nearly complete by birth (57) and by 2 years
the brain achieves 80% of its adult weight (25).

Despite the fact that the brain achieves 95% of its
maximum size by 6 years, the processes underlying
functional connectivity—including competitive elimina-
tion of synapses, myelination, and dendritic and axonal
arborization—continues throughout life (56). The early
rapid increase in synaptic density is followed by a period
during which synaptic connections that are not used are
eliminated or pruned (58). This elimination increases both
computational capacity and speed of information process-
ing and serves as a functional mechanism for plasticity,
which supports the hypothesis that the immature brain is
sculpted to fit the individual’s environment (2). Further,
synaptic pruning occurs at varying velocities in different
parts of the brain with sensory regions—such as the visual
cortex—achieving maturity by 7 years while the middle
frontal gyrus—a region involved in executive function—
not maturing until 20 years (47). One of the implications
of this hierarchical growth model is that development of
executive control—which consists of inhibition (resisting
distractions or habits to maintain focus), working memory
(mentally holding and manipulating information), and
cognitive flexibility (multitasking)—is guided by the late
maturation of the prefrontal cortex (10). Furthermore,
protracted myelination throughout the cortices supports
the position that childhood and adolescence are periods

of modification in connectivity between distant brain
circuitries as well as prefrontal specialization (38).

In addition to modifications in connectivity, different
regions of the cortices display varying growth trajecto-
ries. Gray matter volume, which consists of neuronal
cell bodies, dendrites, and unmyelinated axons, peaks
between 10 and 12 years in the frontal and parietal lobes
while temporal lobe gray matter volume does not peak
until 16–17 years of age (37). Indeed, the dorsolateral
prefrontal cortex—a cortical area subserving control of
impulses, judgment, and decision-making—reaches adult
levels of cortical thickness last (56).

The relatively delayed rate of maturation of the
human brain, compared with other mammals, may pro-
vide opportunity for postnatal environmental modulation.
The discovery that the dentate gyrus of the hippocampus
in the adult brain continues to undergo neurogenesis—
previously assumed to be complete at birth—may provide
additional support to this theory (1). Thus, the protracted
development of the prefrontal cortex and neurogenic
capacity of the dentate gyrus offer the possibility of excit-
ing mechanisms by which physical activity may affect
cognitive function and brain health. Rodent models have
been particularly useful in examining the role of physical
activity in neurogenesis, and older human studies have
provided further empirical support for this relationship
(19,20,31).

Mechanisms Underlying Physical
Activity-Brain Relationships

Although brain development is complete by the third
decade of life, it is now well accepted that that the adult
human brain has the capacity to form new neurons
throughout life. The two brain regions that exhibit adult
neurogenesis are the subventricular zone of the lateral
ventricle and the dentate gyrus in the hippocampus
(59). Evidence from rodent studies has revealed that
several factors affect neurogenesis including stress,
aging, environmental enrichment, and physical activity
(40,50,54,68). However, physical activity has been identi-
fied as a critical neurogenic component of environmental
enrichment (29,67). Indeed, wheel running in rodents
enhances performance on hippocampal-dependent tasks
including spatial memory and novel object recognition
(61,69). Subsequent studies established that the neu-
rogenic effects of exercise are localized to the dentate
gyrus of the hippocampus and not the subventricular
zone/olfactory bulb; thus, providing a model to explain
the enhanced hippocampal function observed following
exercise (6). This is further supported by the observation
that long-term potentiation (LTP)—a persistent increase
in synaptic strength that may underpin certain forms of
learning or memory—is enhanced in the dentate gyrus
of running mice compared with controls (72). However,
the granule cells in the dentate gyrus can be influenced
by a variety of factors including neurotransmitters, neural
peptides, and growth factors.

140 Khan and Hillman

Although several neurotrophins are involved in the
maintenance of neural function and plasticity, brain-
derived neurotrophic factor (BDNF) is proposed to be
one of the key mediators of exercise effects on the brain
(22). BDNF is expressed in several tissues including the
brain, muscle, and adipose tissue and plays an important
role in various aspects of developmental and adult brain
plasticity, including proliferation, differentiation, and
survival of neurons (46). Studies in animals have shown
that exercise-induced increases in BDNF mRNA are
specific to the dentate gyrus (34), an area vital for learn-
ing and memory. Among humans, circulating BDNF has
been related to hippocampal volume, with aerobic fitness
related to the upregulation of BDNF serum levels and
greater hippocampal volume among older adults (31,55).
Although differences in hippocampal volume as a func-
tion of fitness have been recently observed in children
as well (discussed below), additional studies are needed
to determine exercise effects on neurochemical factors
that mediate the effects of physical activity on cognition
in childhood. A complete review of possible mechanisms
for the effects of physical activity on brain and cognition
is beyond the scope of this article, but several informative
reviews on the topic exist in the literature (39,70).

Aerobic Fitness and
Hippocampal-Dependent Memory

The hippocampus is essential for relational/associative
memory, which refers to the ability to form and use rep-
resentations among the constituent elements of an event
or scene (18,23). This form of memory is particularly
important because it is critical for binding arbitrary
associations between pieces of information and their
flexible expression (30), thus representing a continuous
cognitive process that is integral to learning in school
and everyday life. Therefore, elucidating whether factors
such as physical activity or fitness can enhance relational
memory could be crucial for achieving optimal learning
and cognitive development, potentially influencing life
outcomes beyond childhood.

Given that wheel running increases neurogenesis in
the hippocampus and enhances hippocampal-dependent
memory in rodents (51), the impact of physical activity
and aerobic fitness on hippocampal structure and function
has received much attention in recent years. Among older
adults, Erikson et al. (32) found that higher aerobic fitness
was associated with increased hippocampal volumes,
which translated to superior performance on a spatial
memory task. Recent evidence has emerged indicating
that differences in hippocampal structure and function
may extend to children as well.

Specifically, Chaddock et al. (12) examined differ-
ences in hippocampal volumes and performance on a
relational memory task between higher- (≥70th VO2max
percentile) and lower- (≤30th VO2max percentile) fit 9- to
10-year-olds. Higher-fit children exhibited larger bilat-
eral hippocampal volumes and greater accuracy on the

relational memory task. Furthermore, the hippocampal
volume mediated the positive association observed
between fitness and relational memory performance.
No differences were observed—across fitness levels—
for item memory performance and nucleus accumbens
volume (assessed as a control region), demonstrating
the selectivity of fitness to specific aspects of memory
and their neural substrates. In a subsequent study, the
behavioral findings were extended to a different rela-
tional memory task among a unique sample, as selective
associations with fitness were only observed for the rela-
tional task (15). To test whether the provision of physi-
cal activity would enhance relational memory, Monti et
al. (60) used eye-movements—an implicit measure of
hippocampal activity—to demonstrate that 8- to 9-year-
olds who participated in a 9-month physical activity
intervention showed eye movement patterns indicative
of superior relational memory without any difference in
the item condition (an aspect of memory subserved by
regions outside the hippocampus). Although pretest eye-
movement data were not collected, the observation that
there was a significant group difference on eye-movement
measures specific to the relational memory condition at
posttest provided additional support for the selective link
between the hippocampus, relational memory, and fitness.

Aerobic Fitness and Executive
Control: Evidence From Structural

and Functional MRI
Unlike the study of physical activity and aerobic fitness
effects on hippocampal plasticity—which has predomi-
nantly been studied using animal models—the relation-
ship between physical activity and aerobic fitness and the
prefrontal cortex has been illuminated by several studies
among humans. Of particular interest has been the influ-
ence of fitness on executive control; goal-directed cogni-
tive processes underlying perception, memory, and action.
Indeed, much of the currently available evidence suggests
disproportionately larger effects of fitness on executive
control processes—relative to controlled, visuospatial,
and speed tasks—among adult populations (21,45).

Subcortical structures subserving the fronto-striatal
connection are also suggested to modulate efficient
recruitment of executive control and these structures may
be influenced by fitness. Chaddock et al. (13) investigated
the relationships between aerobic fitness, performance on
a modified flanker task, and volume of the basal ganglia,
a group of structures located at the base of the forebrain
and implicated in action selection and execution (41).
The flanker task is an executive control task that specifi-
cally requires variable amounts of inhibitory control. It
consists of arrays of congruent and incongruent stimuli,
with the instruction to respond to the directionality of
the central (i.e., target) stimulus and ignore flanking
stimuli. Higher-fit children exhibited larger volumes of
dorsal striatum (eg, left caudate nucleus, bilateral puta-
men, globus pallidus), which was negatively associated

Brain and Cognition 141

with behavioral interference attributed to the incongruent
flanking stimuli, providing a behavioral sequelae for the
observed structural differences between groups. Indeed,
lower-fit children exhibited over a twofold higher inter-
ference effect indicating less efficient management of
conflicting cues compared with higher-fit children.

Beyond MRI measures of brain structure, the avail-
ability of functional MRI (fMRI) allows for a proxy
measure (eg, blood flow) of underlying brain activation
during task performance, thereby detecting regional
locations and networks that are associated with higher
aerobic fitness. Although research is limited, a handful
of studies have used fMRI to assess how physical activ-
ity or aerobic fitness changes patterns of brain activation
(14,17,24,52,71). Specifically, Chaddock et al. (14) com-
pared performance on early and later blocks of a flanker
task between higher and lower fit 9- and 10-year-olds
using fMRI. During congruent trials requiring lower
amounts of executive control, both groups showed greater
activation in the prefrontal and parietal cortex (eg., left
middle frontal gyrus, supplementary motor area, anterior
cingulate cortex [ACC], left superior parietal lobe) during
the early blocks when the paradigm was more novel, fol-
lowed by a decrease in activity during the later blocks.
However, during incongruent trials requiring the upregu-
lation of executive control, higher-fit children maintained
accuracy across blocks and exhibited increased activa-
tion in the left middle frontal gyrus, right middle frontal
gyrus, supplementary motor area, ACC, and the left
superior parietal lobe during the early task block and
reduced activity in the later block. In contrast, the lower-
fit children declined in accuracy across blocks without
displaying any changes in brain activity. These findings
are consistent with studies that have used event-related
brain potentials (ERPs, discussed later) to indicate that
higher-fit children may have greater ability to upregulate
neural processes involved in executive control to meet
task demands and maintain performance.

Differences in underlying brain activity have also
been found as a function of physical activity interven-
tions. Davis et al. (24) tested the effect of 3 months of
physical activity training on executive function in over-
weight children using cognitive assessments, achieve-
ment measures, and fMRI. Participants were randomized
into high (40 min) and low-dose (20-min) exercise and
control groups. Exercise selectively enhanced executive
control tasks and math achievement in a dose-dependent
manner. The improvement in math achievement was
particularly important because no educational instruction
was given. Relative to the fMRI data, the exercise group
(high and low-dose exercise groups were collapsed for
fMRI analyses) exhibited increased bilateral prefrontal
cortex activity and decreased activity in the posterior
parietal cortex. Similarly, Chaddock et al. (17) observed
differences in brain activity between children participat-
ing in a 9-month physical activity intervention, relative
to children assigned to a wait-list control. In addition to
improved performance on an attentional task of inhibi-
tory control, intervention participants exhibited decreased

activation in the right prefrontal cortex while the control
group showed no changes in brain function from baseline
to posttest. Furthermore, posttest brain activity among
the intervention group showed similar anterior frontal
brain patterns and incongruent accuracy performance to
a group of college-aged adults while the control group
children failed to show such a pattern.

A third physical activity intervention study exam-
ined changes in accuracy and brain function among
8- to 11-year-old overweight children using flanker and
antisaccade tasks (52). Relative to the control group,
intervention participants exhibited decreased activity in
several areas subserving the antisaccade performance,
including the precentral gyrus and posterior parietal
cortex. However, increased activity was observed in
regions involved in flanker accuracy including the ACC
and superior frontal gyrus. This observation for ACC
activation was in contrast with Chaddock et al. (17) who
did not observe any changes in ACC activation using the
flanker task. Nevertheless, evidence from fMRI studies
suggests that that physical activity may influence the
modulation of neural circuitry supporting executive
control in prepubertal children, but also suggests that
further work is needed to better determine the differential
patterns of activation across various cognitive tasks.

Aerobic Fitness and Executive
Control: Evidence From
Neuroelectric Studies

In addition to fMRI, other neuroimaging tools have been
used to study the relation of physical activity to brain
function. Findings from our laboratory have indicated
that fitness has a positive relationship with performance
on cognitive tasks requiring variable levels of executive
control in children (7). Several subsequent studies have
assessed ERPs during stimulus engagement and response
production to determine which aspects of cognition are
influenced by fitness. ERPs refer to patterns of neuroelec-
tric activation that occur in response to, or in preparation
for, a stimulus or response. Although ERPs have low
spatial resolution, they have high temporal resolution;
therefore, reflecting specific neural operations that occur
between stimulus encoding and response execution.
The P3 (P300 or P3b) is a positive-going component
observed in the stimulus-locked ERP waveform that
has captured considerable attention in the literature and
is believed to represent the updating of memory once
sensory information has been analyzed (26). P3 ampli-
tude and latency are thought to be directly proportional
to the amount of attentional resources allocated during
stimulus engagement and information processing speed
during stimulus evaluation, respectively (28,63). Thus,
this endogenous component provides rich information
regarding brain function underlying behavior within the
stimulus environment.

Several studies in our laboratory have demonstrated
differences in the P3 component between higher- and

142 Khan and Hillman

lower-fit children. Hillman et al. (42) assessed neuroelec-
tric differences between higher and lower-fit 9- to 10-year-
olds on a modified flanker task. Higher-fit children not
only out-performed lower-fit children, they also exhibited
larger P3 amplitude, indicating greater attentional resource
allocation during stimulus evaluation. Interestingly though,
the findings were observed across both flanker condi-
tions requiring variable (ie, lower and higher) amounts
of inhibition. In a subsequent study among another group
of children (mean = 10.1 years) the flanker task was
manipulated by adding an incompatible stimulus-response
condition during which participants were instructed to
press a button that opposed the direction of the central
stimulus (64), necessitating greater inhibitory control
and cognitive flexibility. Higher-fit children maintained
their response accuracy (which was higher than lower-fit
children) regardless of the stimulus-response compatibility
condition. However, lower-fit children exhibited reduced
accuracy with increases in task difficulty. Inspection of the
underlying ERPs showed that higher-fit children exhibited
larger P3 amplitude relative to lower-fit children, but also
for incompatible compared with compatible conditions;
modulation that was not evidenced in the lower-fit group.
Furthermore, higher-fit children had shorter P3 latencies
than their lower-fit counterparts. These results indicated
that higher-fit children have greater attentional resource
allocation and enhanced cognitive flexibility during tasks
that modulate cognitive control demands. Given that cog-
nitive processing speed was also faster, the data suggest
that higher amounts of fitness are related to better acqui-
sition of information within the stimulus environment. In
summary, our initial findings suggested that fitness had a
general relationship with cognition across tasks requiring
variable amounts of executive control. Subsequent studies
in our laboratory modified the flanker paradigm to extend
the literature further by demonstrating selective effects of
fitness on inhibitory control, suggesting a need for sensitive
assays to bore out the selective or disproportionate nature
of the fitness-cognition relationship.

In addition to improved cognitive function during
stimulus acquisition, higher-fit children also exhibit
enhanced action monitoring during response execution;
another important aspect of executive control. To carry
out goal-directed behavior, individuals must continuously
monitor interactions between intended and executed
actions. The error-related negatively (ERN)—localized
to the dorsal portion of the ACC—is a negative-going
component observed during a response and is suggested
to index the action monitoring system (33,36). Findings
from both Hillman et al. (42) and Pontifex et al. (64)
indicated that when instructed to respond as quickly
as possible, higher-fit children exhibited smaller ERN
amplitudes and higher response accuracy following com-
mission errors, relative to their lower-fit counterparts.
Interpreting these findings in the context of the conflict
monitoring theory—which posits that the ACC detects
response conflicts and transmits signals to several regions
of the brain, including the dorsolateral prefrontal cortex,
which in turn regulate executive control in support of
ongoing environmental interaction (5,9)—suggests

that higher-fit children exhibit lower response conflict
during task execution. Furthermore, similar to findings
for the P3, Pontifex et al. (64) observed that the ERN
was significantly larger for the incompatible condition
compared with the compatible condition of a modified
flanker task among the higher-fit children; an effect that
was not observed among lower-fit children. Although
the ERN in the incompatible condition did not differ
across fitness groups, the lower-fit group did not exhibit
significant changes in ERN. Therefore, higher-fit children
not only exhibit less conflict, but they also appear to flex-
ibly modulate action monitoring processes depending
on executive control demands to optimize behavioral
interactions within the task environment (44).

Therefore, cross-sectional studies indicate that
higher-fit children allocate greater attentional resources
during stimulus engagement (P3 amplitude) and have
greater capability to flexibly regulate executive control,
relative to their lower-fit counterparts. This difference in
strategy may account for some of the variability observed
in task performance across fitness levels. Furthermore,
a recently concluded randomized controlled trial in our
laboratory demonstrated that 8- and 9-year-olds receiv-
ing 9 months of physical activity (5 days/week) exhib-
ited greater improvements in attentional inhibition and
cognitive flexibility coupled with increased attentional
resources (eg, increased P3 amplitude) during tasks
requiring the upregulation of attentional inhibition and
cognitive flexibility; an effect not observed for the waitlist
control (Hillman et al., submitted for publication).

Considering both the hippocampal and prefrontal
cortex literature, fitness has selectively positive effects on
volumes of particular structures that subserve relational
memory and executive control. In addition, the positive
associations between fitness and brain structure were
only found for performance on hippocampal-dependent/
relational memory tasks and not item memory tasks,
further reinforcing the fitness-brain relationship to the
hippocampus. These findings are consistent with those
from animal studies indicating that the hippocampus
is positively influenced by physical activity. Emerg-
ing evidence from neuroimaging studies suggests that
higher-fit children demonstrate differential patterns in
brain activity while performing executive control tasks,
relative to their lower-fit counterparts. Furthermore, the
provision of physical activity appears to alter efficiency
and flexible modulation of neural circuitry that supports
executive control in children.

Translational Applications of
Physical Activity to Academics,
Learning and Real-World Tasks

The relationship between physical activity, fitness, and
academic achievement has received attention in recent
years due to the increased prevalence of children who
are lower-fit and overweight. Several publications on the
topic indicate that regular physical activity and higher
levels of aerobic fitness have weak but positive effects

Brain and Cognition 143

on academic achievement (4,11). Given that much of this
evidence is based on cross-sectional studies (however, see
Donnelly et al. (27) for an exception), the magnitude of
the effect of physical activity on academic achievement
remains an issue of debate. However, there is no empirical
data in the literature that suggests that increasing time
spent in physical activity in schools has a detrimental
effect on academic achievement.

In addition, the literature thus far has focused pre-
dominantly on the ability to perform cognitive tasks.
That is, human physical activity studies have focused on
differences in task performance as a function of fitness or
engagement in a physical activity program, rather than the
ability to acquire or learn new information per se. Demon-
strating that learning is positively influenced by physical
activity or aerobic fitness would provide an important
link between physical activity and cognitive and brain
health that is directed toward the everyday acquisition
of information with implications for lifelong cognitive
wellbeing. A recent study in our laboratory examined
the influence of fitness on learning and memory among
9- to 10-year-olds (65). Higher- and lower-fit children
performed a task requiring them to learn the names of
specific regions on a fictitious map, under a condition
in which they only studied the maps and names versus
a condition in which they were tested during studying
process. Testing during studying has been previously
shown to enhance accuracy for retrieval and assists learn-
ing through the provision of a strategy (8). The retention
day occurred one day after initial learning and involved
two different recall conditions: free recall and cued recall.
No differences in performance at initial learning were
observed between higher-fit and lower-fit participants.
However, during the retention session higher-fit children
outperformed lower-fit children, particularly when the
material was learned without an explicit strategy (ie, the
study only condition). Therefore, fitness appears to be
associated with enhanced learning, particularly during
conditions in which learning is more challenging. Given
the greater retrieval among higher-fit children and the
lack of interaction between fitness and the cued condi-
tion, the beneficial influence of fitness may primarily
occur via enhancements during initial encoding for novel
information, rather than through the enhancement of
retrieval processes. These findings extend the literature
by showing that differences in learning are evident among
prepubertal children as a function of fitness.

A last example of how fitness influences aspects of
children’s everyday life examined the role of fitness in
successful street crossing among 8- to 10-year-olds (16).
Higher- and lower-fit children were asked to navigate
trafficked roads—while walking on a manually driven
treadmill –within a modeled virtual environment. Child
pedestrians crossed the street while undistracted, listening
to music, or conversing on a hands-free cellular phone.
There was an interaction between fitness and street cross-
ing condition such that higher-fit children maintained
street crossing rates across all conditions, regardless of
the amount of distraction. In contrast, lower-fit children
exhibited decreases in street crossing success rates when

on the phone, compared with the undistracted and music
condition. Therefore, higher levels of aerobic fitness may
attenuate impairment typically observed with multitask-
ing during street crossing. These findings are particularly
important considering that pedestrian accidents are the
second leading cause of injury and mortality in children
between the ages of 5 and 14 in the U.S. (66).

Research Needs

Additional longitudinal studies are needed to better exam-
ine the association between changes in fitness, physical
activity, brain, and cognition. It should be noted that
neuroimaging evidence is limited in its generalizability
because of the typically lower sample sizes and variability
in subject characteristics. Therefore, additional random-
ized controlled trials are needed to elucidate how changes
in physical activity and fitness predict changes in brain
structure and function in children. Further research is
needed to determine to what extent genetics, motivation,
personality characteristics, nutrition, and intellectual
stimulation play roles in mediating the fitness-brain
relationship observed in cross-sectional studies. Critically
missing from the literature is the examination of the rela-
tionship between chronic physical activity, independent
of aerobic fitness, and cognitive function in childhood.
Thus, future studies should objectively assess physical
activity in addition to aerobic fitness. Given that much
of the current knowledge is based on studies among nor-
mally developing and healthy children, additional studies
among children with autism, ADHD, and other disorders
are needed to enhance the generalizability of findings.

General Conclusions
Evidence from rodent models strongly indicates that
physical activity is a potent stimulator of molecular and
cellular components underlying brain structure and func-
tion. Furthermore, studies in humans suggest that physical
activity may be protective against age-related brain tissue
loss and may be positively associated with brain health
and cognitive function in children as well. Childhood
presents a critical period in brain growth characterized by
prolonged maturation of structures involved in executive
function and relational memory as well as fine-tuning of
the brain circuitry intended to support operations of the
adult brain (58). Therefore, this protracted development
may provide opportunity for physical activity to optimize
cognitive function and brain health during childhood.
However, longitudinal studies are needed to examine
how changes in physical activity affect the physical and
functional developmental trajectory of the brain.

Considering the rise in physical inactivity and obe-
sity in the U.S. and other industrialized nations, the results
from the studies reviewed in this article have significant
public health and educational implications (62). Although
additional experimental studies are warranted, the current
evidence points to the benefits of physical activity and
aerobic fitness for cognitive and brain health in childhood.

144 Khan and Hillman

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BRIEF REPORT

Exercise and Fitness Modulate Cognitive Function in Older Adults

Chien-Heng Chu
National Taiwan Sport University

Ai-Guo Chen
Yangzhou University

Tsung-Min Hung
National Taiwan Normal University

Chun-Chih Wang and Yu-Kai Chang
National Taiwan Sport University

This study investigated the effects of acute exercise on cognitive function and the modulatory role of
fitness in the relationship between exercise and cognition. Forty-six healthy older adults, categorized into
higher or lower fitness groups, completed the Stroop test after both 30 min of aerobic exercise and a
reading control with a counterbalanced order. Our findings demonstrated that acute exercise leads to
general improvements in 2 types of cognitive functions and to specific improvements in executive
function. Additionally, older adults with initially higher fitness levels experienced greater beneficial
effects from acute exercise.

Keywords: aerobic exercise, cognition, executive function, inhibition, Stroop test

The population over 60 years old has rapidly grown and
changed the worldwide demographic landscape (Gorman, 2002).
This aging population not only experiences the deterioration of
physical functions but also suffers from declining brain and cog-
nitive functions. Indeed, normal aging is associated with brain
volume atrophy of approximately 15% to 25% (Jernigan et al.,
2001) and with it the degradation of cognitive processes, including
memory, reasoning, and information processing speed (Salthouse,
2004). The influence of acute exercise, defined as a single bout of
exercise, on cognitive performance has received substantial atten-
tion within younger populations, demonstrating positive changes
with small to moderate effects on various types of cognitive
performance (Chang & Etnier, 2015; Chang, Labban, Gapin, &
Etnier, 2012; Chu, Alderman, Wei, & Chang, 2015; Lambourne &
Tomporowski, 2010; McMorris, Sproule, Turner, & Hale, 2011).
However, examination of whether the positive effects of acute

exercise extend to older adults has been limited, with ambiguous
findings.

Pesce and Audiffren (2011) found that switch performance
improved following acute exercise at moderate intensity in both
younger and older adult groups. Given that switching is one of the
primary executive function aspects, these results suggested that the
beneficial effects of acute exercise could extend to higher order
cognitive function, regardless of age. In contrast, research that
used a similar paradigm (i.e., Alternate Uses test) found partially
conflicting findings wherein the positive effects of acute exercise
in older adults only partially benefited switching (Netz, Tomer,
Axelrad, Argov, & Inbar, 2007). Another study found changes in
only basic cognition levels in older adults following acute exercise
(i.e., Stroop color condition) and failed to demonstrate an effect on
the inhibition- and interference-related executive function aspects
(i.e., Stroop inhibition and interference conditions; Barella, Etnier,
& Chang, 2010). Notably, these studies measured different cogni-
tive functions, implying that the cognition type plays a moderating
role in the relationship between acute exercise and cognition.
Indeed, Etnier and Chang (2009) proposed that acute exercise
effects might differ depending on the specific type of cognitive
function and further studies are required that utilize assessments
that not only are widely used but also posit multiple cognition
subtypes with similar features, such as the Stroop test. Therefore,
future research should examine the effects of acute exercise on
different cognitive functions derived from similar task character-
istics to explore these relationships.

Another potential moderator that must be considered is the
participant’s cardiovascular fitness status (Brisswalter, Collardeau,
& René, 2002; Chang et al., 2012). Longitudinal studies have
indicated that, along with the positive association between cardio-
vascular fitness and cognitive function (Etgen et al., 2010), exer-

Chien-Heng Chu, Graduate Institute of Athletics and Coaching Science,
National Taiwan Sport University, Taoyuan, Taiwan, Republic of China;
Ai-Guo Chen, College of Physical Education, Yangzhou University, Ji-
angsu, People’s Republic of China; Tsung-Min Hung, Department of
Physical Education, National Taiwan Normal University, Taipei, Taiwan,
Republic of China; Chun-Chih Wang and Yu-Kai Chang, Graduate Insti-
tute of Athletics and Coaching Science, National Taiwan Sport Universit

This research was supported by a portion of Grants NSC 101-2628-H-
179-002 and NSC 102-2420-H-179-001-MY3 from the Ministry of Sci-
ence and Technology, Taiwan, to Yu-Kai Chang.

Correspondence concerning this article should be addressed to Yu-
Kai Chang, Graduate Institute of Athletics and Coaching Science,
National Taiwan Sport University, No. 250, Wenhua 1st Road, Guishan
Township, Taoyuan County 333, Taiwan, Republic of China. E-mail:
yukaichangnew@gmail.com

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Psychology and Aging © 2015 American Psychological Association
2015, Vol. 30, No. 4,

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– 848 0882-7974/15/$12.00 http://dx.doi.org/10.1037/pag0000047

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mailto:yukaichangnew@gmail.com

http://dx.doi.org/10.1037/pag0000047

cise interventions that induced fitness improved specific cognitive
function types (Angevaren, Aufdemkampe, Verhaar, Aleman, &
Vanhees, 2008; Smith et al., 2010). These superior cognitive-
related foundations associated with high cardiovascular fitness
may result in larger improvements following acute exercise. A
meta-analysis conducted by Chang et al. (2012) indicated that
individuals with higher fitness levels received the largest acute
exercise benefit effects compared with individuals with low or
moderate fitness levels, both immediately and following a delay
after exercise. Notably, this viewpoint is primarily based upon
studies performed with younger adults. Furthermore, only a few
studies have investigated these differences among individuals with
different fitness levels (individuals with high fitness levels, but not
moderate or low fitness, were typically evaluated; Chang, Chi, et
al., 2014; Chang et al., 2012).

Recently, the modulatory role of fitness in acute exercise and
cognition in older adults has been preliminarily explored. Pesce,
Cereatti, Forte, Crova, and Casella (2011) indicated that road
cyclists had better visual attention control and performance in
attentional tasks involving executive control compared with a
sedentary group during an acute bout of aerobic exercise. Similar
fitness-moderated effects of acute exercise on cognitive flexibility
were observed (Netz, Argov, & Inbar, 2009). However, these
studies focused on highly trained individuals and cognitive per-
formance assessed during acute exercise or utilized assessments
that examined a single construct.

Whether the effects of acute exercise have general or specific
effects on the different cognition types and whether fitness status
moderates the magnitude of favorable acute exercise effects on
these cognitive performances, particularly in older adults, remain
undetermined. The present study examined the effects of acute
exercise on two types of cognitive processes derived from the
Stroop test (i.e., Stroop congruent and incongruent conditions),
where the Stroop incongruent condition is believed to engage a
greater amount of executive control than does the Stroop congru-
ent condition, which reflects more-basic information processing
(e.g., perceptual-motor level; Liotti, Woldorff, Perez, & Mayberg,
2000; Miyake et al., 2000; West & Alain, 1999). Additionally, the
acute effects on these cognitive functions were compared between
older adults with higher and lower fitness levels to explore the
modulatory role of fitness. Acute effects were expected to induce
favorable effects on multiple cognition types, and older adults with
higher fitness were expected to receive larger acute exercise ben-
efits than were older adults with lower fitness.

Method

Participants

Seventy healthy older adults, ages 60 to 70 years, were
initially recruited in Taoyuan County, Taiwan. The participants
were screened using physical activity readiness and health
screening questionnaires and were required to meet the follow-
ing criteria: (a) right-hand dominant, (b) no history of neuro-
logical or major psychiatric disorders, (c) normal or corrected-
to-normal vision, and (d) no color-blindness to minimize the
confounders between acute exercise and cognition. Eligible
participants completed the Digit Span test (Wechsler, 1997).
Then, the participants were categorized into a higher or a lower

fitness group on the basis of a VO2peak that fell above or below
the 55th percentile (�35.0 ml/kg/min for men and �29.4 ml/
kg/min for women; American College of Sports Medicine,
2013), resulting in 46 participants, with 22 in the higher fitness
group and 24 in the lower fitness group. This study was ap-
proved by the university Institutional Review Board, and all
participants provided informed consent.

Cardiovascular Fitness Test

Cardiovascular fitness was assessed via a submaximal exercise
test according to the YMCA cycle ergometry protocol (Golding,
1989). The protocol was appropriate for adults with a Class A risk
stratification (Fletcher et al., 2001). The YMCA protocol includes
two to four consecutive 3-min circuits, which have specific work-
loads designed to raise the steady-state heart rate between 110
beats/min and 85% of the age-predicted maximal heart rate (e.g.,
220-age). To begin, the participant rode a cycle ergometer (Er-
goselect 100/200, Ergoline GmbH, Germany) with a workload of
150 kpm/min (25 W) and a 50-rpm pedaling rate. The average
heart rate during the last 15–30 s of the final second and third
minutes determined the subsequent workloads (e.g., 750 kpm/min,
600 kpm/min, or 300 kpm/min). When the target steady-state heart
rate was observed for two consecutive circuits, the VO2peak was
calculated on the basis of the slope regarding heart rates, workload,
and body mass.

The Stroop test

The Stroop test (Stroop, 1935) is a widely used neuropsycho-
logical assessment recommended for adaptation in exercise–
cognition research. The computerized Stroop test consists of two
types of conditions— congruent and incongruent—and was pre-
sented using Stim2 (Neurosoft Labs, Inc., Sterling, VA). In the
congruent condition, Chinese words (i.e., 紅 [red], 藍 [blue], and
綠 [green]) were presented in the same color as the meaning of the
words. In the incongruent condition, the name of the color word
was printed in a different font color. Each stimulus word was
presented in equal proportions in the congruent (i.e., 33.3% each
for red, blue, and green words) and incongruent (e.g., the word
“red” printed in either blue or green color) conditions to minimize
specific word facilitation. Each block had 60 target stimuli con-
sisting of 38 congruent and 22 incongruent stimuli with mixed
presentation. Each 2-cm stimulus was displayed in the center of a
21-in. (53.3 cm) computer screen. Each trial began with the pre-
sentation of a fixed cross for 500 ms. Then, either a target-
congruent or -incongruent stimulus was presented for 506 ms; the
interval between the fixed cross and the target stimulus was 383,
583, or 783 ms in a random order to minimize anticipation.
Participants were instructed to respond as quickly and accurately
as possible to the color of the presented stimulus by pressing their
thumb on one of three buttons on a response pane. Each trial was
completed once the target stimulus response was made within
1,000 ms. Response time and accuracy were identified as primary
indices. Each participant was required to complete six blocks with
a 2-min rest between each block, resulting in a total testing period
of approximately 25 min.

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843ACUTE EXERCISE, FITNESS, COGNITION, OLDER ADULT

Experimental Procedures

The participants attended the laboratory individually on three
separate days, with at least a 3-day interval between each day
and within a 2-week period. On Day 1, participants meeting the
inclusion criteria were fit with a Polar HR monitor (Sport Tester
PE 3000, Kempele, Finland) and completed a submaximal
exercise test with a YMCA cycle ergometry protocol. The
participants were then assigned to either the high- or low-fitness
group on the basis of their VO2peak (categorized as good or
poor, respectively).

The experimental conditions for Days 2 and 3 (i.e., exercise
and control days) were performed in a counterbalanced order to
control for potential practice and order effects. Each participant
was tested at a similar time of day on the 2 days to control
confounding due to time of testing (Hasher, Chung, May, &
Foong, 2002). On the exercise day, the resting heart rate (HR)
was measured by having the participants sit quietly in a chair
for 10 –15 min. Then, participants completed practice trials to
become familiarized with the test procedure; once an 85%
correct rate was achieved, they started the experimental trials.
Next, participants were instructed to complete a modified acute
cycling ergometer protocol on the basis of Chang et al. (2011).
The protocol consisted of three stages: a 5-min warm-up, a
20-min primary exercising stage at 65% heart rate reserve
(HRR; the difference between maximal and resting heart rates),
and a 5-min cool-down. The peddling rate was set at 70 rpm,
and the workload began with 15 W and then increased or
decreased gradually until a steady state at the required HR was
reached. The participants performed the Stroop test within 5
min of exercise cessation. On the control day, participants
completed procedures similar to those on the exercise day,
except that participants read a book related to exercise and
cognition during treatment. The control condition was intended
to maintain a low arousal level compared to the exercise con-
dition.

A Polar HR monitor and the Rating of Perceived Exertion (RPE)
scale (Borg, 1982) were used to objectively and subjectively
confirm the intensity manipulation, respectively. The RPE scale
ranges from 6 (no exertion at all) to 20 (maximum exertion). The
experimental session lasted approximately one and a half hours
each day. Participants were informed about the purpose of the
study and compensated with US$15 after completing the overall
experimental session.

Statistical Analyses

This study was a randomized control group posttest design. A
mixed three-way analysis of variance (ANOVA), with a between-
subjects (i.e., group: lower vs. higher fitness) and two within-
subject (i.e., treatment: control vs. exercise; Stroop condition:
congruent vs. incongruent) were used to analyze response time and
accuracy. Multiple comparisons were performed using t tests with
Bonferroni adjustments when appropriate. The effect size of the
partial eta-square was reported for significant effects derived from
the ANOVA. An alpha of 0.05 was set as significant for all
analyses.

Results

Participant Characteristics and Exercise
Intensity Check

Higher scores in the higher fitness group were observed for only
fitness-related variables (see Table 1). The HR values (beats per
minute [bpm]) for the lower and higher fitness groups during the
primary exercise were 124.8 � 7.2 bpm and 119.5 � 8.8 bpm,
respectively, representing 60% to 65% of HRR. Along with the
RPE range of 12 to 14, these values suggest that the exercise
intensity was appropriate.

Stroop Test Performances

A preliminary analysis was conducted to test the effects of
session order. Neither a main effect of session order nor any
interaction with session order was observed for any dependent
variable, Fs(1, 21) � 1.81, p � .19.

A main effect of the treatment condition revealed a shorter
response time for the exercise compared with that for the control
condition, F(1, 44) � 169.75, p � .001, partial �2 � 0.79, and a
main effect of the Stroop condition revealed a longer response time
for the incongruent compared with the congruent condition,(F(1,
44) � 123.91, p � .001, partial �2 � 0.73 (see Table 2).

An interaction between the treatment and fitness was observed,
F(1, 44) � 10.17, p � .03, partial �2 � 0.18. The follow-up
comparisons revealed that the exercise condition had a shorter
response time compared to that of the control condition in both the
higher (p � .001) and lower (p � .001) fitness groups. Addition-
ally, the higher fitness group demonstrated a shorter response time
relative to the lower fitness group in the exercise condition (p �
.04) but not the control condition (see Figure 1a).

An interaction between treatment and Stroop condition was also
observed, F(1, 44) � 10.17, p � .001, partial �2 � 0.24. The
follow-up comparisons revealed that the response time for the
incongruent condition was longer than that for the congruent
condition in both the exercise (632 � 102 vs. 587 � 83, respec-
tively, p � .001) and control (695 � 99 vs. 632 � 82, respectively,

Table 1
Participant Demographics for the Higher and Lower
Fitness Groups

Variable

Higher
fitnessa

Lower
fitnessb

p ESM SD M SD

Age (years) 63.8 2.3 64.9 4.0 .29
Education (years) 9.3 3.5 10.0 4.1 .57
Height (cm) 161.7 8.6 158.2 6.7 .13
Weight (kg) 63.8 8.6 61.8 9.4 .45
BMI (kg.m�2) 24.2 2.5 24.3 3.1 .95
Digit Span Forward 11.5 2.4 11.2 2.5 .69
Digit Span Backward 6.0 2.4 6.7 2.4 .32
VO2peak (mL.kg

�1.min�1) 36.0 1.2 23.5 2.8 .01 5.80�

Resting heart rate (bpm) 65.5 8.7 70.0 6.6 .05 0.58�

Note. ES � effect size with the value of Cohen’s d; BMI � body mass
index; bpm � beats per minute.
a Sample size � 22 (12 female). b Sample size � 24 (10 female).
� p � .05.

844 CHU, CHEN, HUNG, WANG, AND CHANG

p � .001) conditions. The exercise condition resulted in shorter
response times compared to those for the control condition with
both the congruent and incongruent conditions (p � .001). An
additional paired t test revealed a smaller difference between the
congruent and incongruent conditions in the exercise condition
relative to the control condition, t(45) � 3.83, p � .001 (see Figure
1b). No three-way interaction was observed.

Regarding accuracy, main effects of treatment and Stroop con-
dition were revealed. Higher accuracy for the exercise condition
compared to the control condition, F(1, 44) � 5.12, p � .03,
partial �2 � 0.11, and lower accuracy for the incongruent condi-
tion compared to the congruent condition, F � 28.23, p � .001,
partial �2 � 0.41, were observed. Neither the main effect of fitness
nor any interaction was significant.

Discussion

This study investigated how cardiovascular fitness moderates
two types of cognitive function assessed by the Stroop test, fol-
lowing an acute bout of moderate aerobic exercise in an older
population. Although participants had a shorter response time and
an increased accuracy rate in both conditions of the Stroop test
following exercise, reflecting general improvements, acute exer-
cise led to additional benefits for executive function by demon-
strating a smaller difference between the congruent and incongru-

ent conditions after acute exercise compared to results for the
control condition. Moreover, older adults with a higher fitness
level performed significantly better following acute exercise than
did those with a lower fitness level, suggesting that the level of
fitness modulates the relationship between acute exercise and
cognition. Thus, older adults with a higher fitness level received
disproportionally more benefits from acute exercise than did those
with a lower fitness level.

The longer response time and lower accuracy rate in the Stroop
incongruent condition relative to the Stroop congruent condition,
regardless of treatment conditions, demonstrate the typical Stroop
effect (Cohen, Dunbar, & McClelland, 1990). Specifically, com-
pared with the congruent condition, in which colors of the char-
acters were named in the absence of interference (i.e., presenting
automatic activation), greater attentional demand was required to
resolve the conflicts between the stimulus meaning and color in the
incongruent condition to inhibit the automatic nature of word-
reading tendency (Cohen et al., 1990; Milham et al., 2002). Fur-
thermore, the initiating response to inhibit the bias toward word
reading is also believed to reflect an inhibitory aspect of executive
function (Bugg, Jacoby, & Toth, 2008; Nigg, 2000).

Acute exercise not only reduced the response times for both
Stroop test conditions but also diminished the interference, sug-
gesting that acute exercise led to both general and specific im-
provements in cognitive functions. Our findings that these im-
provements are associated with acute exercise agree with the
findings of many previous studies and confirm that an acute bout
of moderate exercise increases cognitive performance requiring
different amounts of executive control (Chang, Tsai, Huang,
Wang, & Chu, 2014; Hyodo et al., 2012; Sibley, Etnier, & Le
Masurier, 2006; Tam, 2013; Yanagisawa et al., 2010). For exam-
ple, Tam (2013) reported that, compared with a response time
reduction of 10.2% in the congruent condition, a 20.6% reduction
was found in the incongruent condition after acute exercise.
Chang, Tsai, et al. (2014) also reported that acute exercise im-
proved performances in five conditions of the Stroop test (i.e.,
Stroop congruent, word, neutral, square, and incongruent), in
which the largest increase was observed in the incongruent con-
dition.

Table 2
Stroop Test Performances of Fitness Groups and
Treatment Conditions

Variable

Higher fitness Lower fitness

Control Exercise Control Exercise

M SD M SD M SD M SD

Response time (ms)
Congruent 622 67 567 61 642 96 608 99
Incongruent 679 86 602 83 711 109 664 110

Accuracy rate (%)
Congruent 92 7 94 5 94 7 95 7
Incongruent 80 15 84 21 86 9 93 6

Figure 1. (a) The response time of the Stroop test is a function of treatment condition and fitness. (b) Stroop
differences during the congruent and incongruent conditions between the exercise and control conditions. Error
bars represent standard error of the means. � Represents a significant difference between treatments. # Represents
a significant difference between fitness group (p � .05).

845ACUTE EXERCISE, FITNESS, COGNITION, OLDER ADULT

General improvement may be attributed to exercise-induced
increases in cerebral blood flow (Heo et al., 2010; Ide & Secher,
2000). That is, brain neuronal activity and metabolism increase
during exercise (Ide & Secher, 2000), resulting in elevated cerebral
blood flow (Ogoh & Ainslie, 2009). In contrast, specific improve-
ments may be interpreted by neuroelectric studies. Acute exercise
enlarges the P3 amplitude only in tasks reflecting executive func-
tion (Chu et al., 2015; Hillman, Snook, & Jerome, 2003; Kamijo,
Nishihira, Higashiura, & Kuroiwa, 2007). These findings from
neuroelectric perspectives suggest that acute exercise may benefit
cognition through increased attentional resource allocation for
tasks requiring greater executive control processes. Taken to-
gether, increased cerebral blood flow and attention alterations
suggest possible general and specific functional roles in exercise-
induced cognitive enhancement.

Another novel finding from the current study was an interaction
between treatment and fitness level, namely, the more-fit older
adults had superior improvements in the Stroop test than did their
less-fit counterparts. This finding is consistent with a previous
meta-analysis (Chang et al., 2012) and extends the current knowl-
edge regarding older adults with extreme higher fitness status (e.g.,
highly trained) to those with moderate to high fitness status (Netz
et al., 2009; Pesce & Audiffren, 2011). Although the underlying
mechanisms remain unknown, potential interpretations based on
studies indirectly examining this issue have been proposed. Older
adults with higher fitness may maintain better brain structures and
functions, providing the foundation for superior benefits from
acute exercise. Studies associated with structural and functional
magnetic resonance imaging (MRI) have indicated that older
adults with higher fitness or long-term exercise training demon-
strate larger volumes of several brain regions that are the core of
cognitive functions, such as white and gray matter in the ventro-
lateral and dorsolateral prefrontal cortexes (Colcombe et al., 2003)
and the hippocampus (Erickson et al., 2009), as well as greater
activations in similar brain regions during cognitive task perfor-
mance (Colcombe et al., 2004). Using an electroencephalogram,
Hogan et al. (2013) found that adolescents with high fitness levels
experienced greater lower upper alpha and beta coherence after
acute exercise, whereas no beneficial acute effect was observed for
those with lower fitness levels, implying that the individuals with
higher fitness posited better cortical efficiency.

The present study was restricted by several factors. First, a
causal relationship between fitness and cognitive performance
could not be established because of the cross-sectional design.
Additionally, the Stroop test reflected only the interference aspect
of inhibition rather than inhibition related to motor suppression
(Aron et al., 2007). Therefore, caution should be taken with the
generalization of the results. Moreover, Boot, Simons, Stothart,
and Stutts (2013) indicated that different expectancy track benefit
performances were observed when conducting computer-based
games, reflecting that the treatment effect may be confounded by
expectancy individual posited. Expectancy has yet to be consid-
ered in acute exercise– cognition studies, and future research that
considers this confounder is suggested. The disproportionate num-
ber of congruent and incongruent trials may also lead to potential
bias regarding inhibitory processes. Specifically, more incongruent
trials than congruent trials may increase the Stroop effect. Al-
though such bias was limited in the present study because the
number of trials was constant across groups and conditions, the

percentage of each trial type is worth considering in future study
designs.

In conclusion, acute exercise leads to general and specific im-
provements for two types of cognitive functions derived from the
Stroop test, and the beneficial effects of acute exercise are greater
for older adults with higher fitness. These findings are important
for older adults and suggest that performing a single bout of
exercise can improve cognitive performance. These results also
indicate that good fitness levels can maximize these beneficial
cognitive effects (i.e., processing speed of cognitive performance)
induced by acute exercise.

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Received September 22, 2014
Revision received July 5, 2015

Accepted July 8, 2015 �

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ORIGINAL PAPER

The Effect of a Community-Based

Exercise Program

on Inflammation, Metabolic Risk, and Fitness Levels
Among Persons Living with HIV/AIDS

Stacy E. Cutrono1,2 • John E. Lewis3 • Arlette Perry1 • Joseph Signorile1 •

Eduard Tiozzo3 • Kevin A. Jacobs1

Published online: 25 November 201

� Springer Science+Business Media New York 20

Abstract The human immunodeficiency virus (HIV)

pandemic remains a top national health priority. Chronic

inflammation may be a critical component in the disease

course of HIV as C-reactive protein (CRP) is elevated and

associated with increased mortality. This study examined

the effect of 3 months of combined aerobic and resistance

exercise training among a diverse cohort of HIV-infected

men and women. The fixed effect of time for CRP was

found to be non-significant (F[1,57.3] = 1.7, p = 0.19).

There was a significant fixed effect for time for upper body

(F[1,51.6] = 18.1, p \ 0.05) and lower body strength
(F[1,48.0] = 15.7, p \ 0.05) and significant declines in
diastolic blood pressure (p = 0.002) and waist circumfer-

ence (p = 0.027). Though levels of CRP were not impac-

ted after 3 months training, participants demonstrated a

significant increase in muscular strength as well as bene-

ficial changes in metabolic risk factors. Future studies

should focus on determining the optimal exercise inter-

vention length and mode to reduce inflammation among

individuals living with HIV.

Keywords Human immunodeficiency virus � Aerobic
exercise � Resistance training � C-reactive protein �
Inflammation � Metabolic risk

Introduction

Globally, the rate of new human immunodeficiency virus

(HIV) infections has fallen by 33 % since 2001 [1], but has

held steady in the United States (U.S.) at an estimated

50,000 new cases per year [2]. As such, the HIV/acquired

immune deficiency syndrome (AIDS) pandemic continues

to affect millions worldwide and remains a top health

priority in the U.S. Recent reports indicate that the state of

Florida has one of the highest rates of newly reported HIV

infections and newly reported AIDS cases in the country

[3]. Furthermore, the burden of HIV/AIDS continues to

disproportionately affect individuals of minority race/eth-

nicity, such as African Americans and Hispanics who

represent 44 and 20 % of new HIV infections, respectively,

as well as individuals with lower socioeconomic status

(SES) and reduced access to quality health care [2].

The use of combination antiretroviral therapy (ART) has

significantly reduced the risk of mortality and morbidity in

persons living with HIV (PLWH) since its introduction in

the mid-1990s [4–7]. However, the extensive use of ART

has given rise to serious and adverse side effects including

hyperlipidemia, insulin resistance, and lipodystrophy thus

increasing the risk for non-AIDS events such as cardio-

vascular disease and the development of metabolic syn-

drome (MetS) [8, 9]. The pathogenic mechanism for

metabolic changes secondary to combination ART have yet

to be fully elucidated, however, current investigations

indicate a greater risk of negative side effects are associ-

ated with use of drug combinations containing protease

& Stacy E. Cutrono
scutrono@med.miami.edu

1
Department of Kinesiology and Sports Sciences, School of

Education and Human Development, University of Miami,

Coral Gables, FL, USA

2
Sylvester Comprehensive Cancer, University of Miami,

Miller School of Medicine, 1475 NW 12th Avenue, Suite

C-021, Miami, FL 33136, USA

3
Department of Psychiatry & Behavioral Sciences, University

of Miami, Miller School of Medicine, Miami, FL, USA

123

AIDS Behav (2016) 20:1123–1131

DOI 10.1007/s10461-015-1245-1

http://crossmark.crossref.org/dialog/?doi=10.1007/s10461-015-1245-1&domain=pdf

inhibitors or nucleoside reverse transcriptase inhibitors

[10]. The risks associated with widespread and prolonged

use of ART may be managed through effective lifestyle

interventions incorporating exercise and weight

management.

Current research suggests that chronic inflammation

may be a critical component in the course of disease states.

The American Heart Association and the Centers for Dis-

ease Control and Prevention support the use of C-reactive

protein (CRP), an acute, non-specific inflammatory bio-

marker, as an independent predictor of increased coronary

risk and recommends using 3.0 mg/L as the minimum

threshold for high risk classification [11]. In healthy young

adults the median level of CRP is 0.8 mg/L [12]. However,

among PLWH, CRP levels are elevated [9, 13] with

reported ranges of 1.94–4.80 mg/L [14–16] and are asso-

ciated with opportunistic infections, progression to AIDS,

and mortality. Individuals enrolled in the Multicenter AIDS

Cohort Study with CRP levels B1.2 mg/L were found to

have a 47 % reduction in time to AIDS progression com-

pared to those with [2.3 mg/L [17]. Individuals in the
Strategies for Management of Anti-Retroviral Therapy trial

with CRP levels C5 mg/L had 7.6-fold higher odds of

developing an opportunistic infection than those with

CRP B 1.0 mg/L [18]. Thus, interventions that reduce

CRP levels may improve the cardiovascular risk profiles

and disease prognosis among PLWH.

The physiological and psychological benefits of regular

exercise are numerous and well established. The available

literature supports the therapeutic use of aerobic and

resistance exercise for improving health and fitness out-

comes among PLWH [19, 20]. For this reason, the Amer-

ican College of Sports Medicine (ACSM) recommends that

PLWH engage in a regular exercise program consisting of

aerobic exercise and resistance exercise on most days of

the week [21]. A reduction in systemic inflammation may

be one of the mechanisms driving the protective effects of

regular exercise for chronic disease risk [22], though the

specific mechanisms by which exercise training may

reduce systemic inflammation has not yet been established.

Recent research examining the effects of exercise inter-

ventions on circulating inflammatory biomarkers has pro-

duced inconsistent results. The third National Health and

Nutrition Examination Survey found that 21 % of seden-

tary individuals had elevated CRP levels compared to 13 %

of moderately active individuals [23]. Several other studies

have reported significant declines in CRP levels after aer-

obic exercise interventions among older individuals [24],

obese women [25] and breast cancer survivors [22]. Yet, a

recent meta-analysis of randomized controlled trials

reported a non-significant decrease in CRP levels among

subjects in aerobic exercise interventions [26]. The pro-

inflammatory changes secondary to treatment with ART

are accepted as a necessary risk in an effort to reduce

progression to AIDS and AIDS mortality, yet inflammatory

changes measured by elevated CRP increase the risk of

non-AIDS events, cardiovascular mortality, as well as

progression to AIDS. Interventions with potential to man-

age treatment side effects and reduce inflammation are

necessary among PLWH. The effect of exercise on CRP

levels has not been well examined among PLWH, how-

ever, given the severity of treatment side effects its

potential beneficial impact warrants further investigation.

The purpose of this study was to determine the effect of

combined aerobic and resistance exercise training

(CARET) on inflammation, metabolic risk profile, and

aerobic and muscular fitness among PLWH after 3 months

of training using data collected from the Healthy Living for

Better Days program. We hypothesized that 3 months of

CARET would significantly improve aerobic and muscular

fitness, and metabolic risk profile and to a lesser extent

systemic

inflammation.

Methods

Study Design

The Healthy Living for Better Days was a 12-month,

community exercise program conducted by research staff

at the University of Miami to improve the health of low

SES individuals with HIV residing in Miami-Dade. This

study specifically analyzed baseline and 3-month data.

Program outcome variables measured at baseline and 3

months included: (1) physical characteristics (body weight,

body mass index, waist and hip circumferences, blood

pressure), (2) non-lipid blood markers (high sensitivity

CRP, fasting blood glucose, and insulin), (3) blood lipid

profile (total cholesterol, low-density lipoprotein choles-

terol, high-density lipoprotein cholesterol, and total

triglycerides), and (4) physical fitness variables (estimated

VO2max and one-repetition maximum for upper and lower

body strength).

Participants

Ninety male and female participants were enrolled in

Healthy Living for Better Days through referrals from the

Adult HIV clinic at the University of Miami/Jackson

Health System and other local HIV clinics. Program eli-

gibility criteria included: [1] confirmed HIV infection as

established by external laboratory reports, [2] men or

women C18 years of age, [3] currently receiving

antiretroviral treatment, and [4] ability to attend weekly

exercise sessions at the UHealth Fitness and Wellness

Center. Program exclusion criteria included any medical

1124 AIDS Behav (2016) 20:1123–1131

123

condition or situation for which unsupervised exercise

would be contraindicated. The Institutional Review Board

of the University of Miami approved Healthy Living for

Better Days and all participants gave written informed

consent.

Exercise Program

All exercise sessions for Healthy Living for Better Days

were held at the UHealth Fitness and Wellness Center at

the University of Miami Medical campus. Each participant

was required to swipe an electronic badge to gain admit-

tance to the wellness center allowing attendance to be

recorded and tracked electronically. Participants were

encouraged to attend the supervised exercise sessions held

four times a week, but were also given open access to the

wellness center. Study personnel directed each supervised

session and were available to advise participants on their

exercise intensity and progression. Each supervised exer-

cise session was 40–60 min in length and consisted of at

least 30 min of aerobic exercise completed on a treadmill,

elliptical machine, or stationary bike and resistance exer-

cises completed on stacked weight machines (bench press,

shoulder press, biceps curl, triceps extension, leg extension,

leg curls, leg press, squat, lateral raises, lat pull downs,

back extension, and abdominal crunches). Aerobic exercise

was performed at 60–80 % of each individual’s age-pre-

dicted maximum heart rate (HRmax). The duration of

exercise sessions progressed from 40 to 60 min over the

first 2 weeks of the program. Two to four sets of 8 to 15

repetitions were performed for each upper and lower body

exercise.

Physical Characteristics

Research staff used standard techniques to obtain anthro-

pometric measurements. Weight and height were recorded

to the nearest 0.1 kg and 0.1 cm, respectively, to calculate

body mass index (BMI). Waist circumference was mea-

sured in inches at the narrowest portion between the lowest

rib and the iliac crest. Systolic blood pressure (SBP) and

diastolic blood pressure (DBP) were measured by use of

the automatic oscillometric device (Omron HEM-712CN2,

Omron Healthcare, Inc., Bannockburn, Illinois).

Blood Sampling and Analyses

Blood samples were drawn from participants in the

morning in a fasted condition and processed by the Dia-

betes Research Institute Clinical Laboratory. Chemistry

and immunoassays were performed by automated analyzer

(Roche Cobas-6000; Roche Diagnostics, Indianapolis, IN)

utilizing the manufacturer’s reagents and following the

manufacturer’s instructions. High sensitivity CRP (hsCRP)

was quantified in serum by a high sensitivity latex-particle

enhanced immunoturbidimetric assay with a detection limit

of 0.1 mg/L with an intra- and inter-assay coefficients of

variation (CV) of 1.1 and 2.2 %, respectively. Fasting

glucose (FG) was measured by the hexokinase method with

intra- and inter-assay CVs of 1.9 and 2.7 %, respectively.

Total cholesterol and triglycerides were determined in

serum or plasma by enzymatic, colorimetric assay with

intra- and inter-assay CVs are 0.7 and 1.8 %, respectively

for total cholesterol and 0.9 and 2.3 %, respectively for

triglycerides. High density lipoprotein cholesterol (HDL-

C) was measured using a third generation homogenous

enzymatic colorimetric assay with intra- and inter-assay

CVs of 0.6 and 1.9 %, respectively. Low density lipopro-

tein cholesterol (LDL-C) was calculated using the Friede-

wald equation.

Physical Fitness

Cardiorespiratory fitness was measured using a Rockport

One-Mile Fitness Walking Test [21], which has been val-

idated in healthy adults aged 30–69 years [27] and been

used in other clinical populations [28]. The test was

modified for use indoors with participants performing the

one-mile walk on a treadmill rather than on an outdoor

track. Participants were instructed to walk for one mile on

the treadmill as quickly as possible and were allowed to

modify speed at their discretion throughout the test. Heart

rate was measured for 10 s immediately upon completion

by palpating the radial artery. Age, gender, body weight,

and walk time were also recorded and used in a regression

equation to predict maximal oxygen consumption

(VO2max).

Muscular strength was measured using the ACSM pro-

tocol for one-repetition maximum (1-RM) testing [21].

Program participants completed a maximum of four trials

of 10, 8, 6, and 3 repetitions with rest periods between 2

and 4 min between trials. The initial weight was selected

within the subject’s perceived capacity (50–70 % of

capacity) and resistance was progressively increased until

the participants reached their maximum. The final maxi-

mum weight lifted successfully one time for bench press

and leg press was recorded as the 1-RM.

Metabolic syndrome was defined using ATPIII criteria

[29]. Three or more criteria had to be met to be classified as

having MetS: (1) high fasting serum triglycerides(C150 mg/

dL), (2) abnormal waist circumference ([102 cm for men
and[88 cm for women), (3) low HDL-C level (\40 mg/dL
for men and\50 mg/dL for women), (4) high blood pressure
(BP) (C130/85 mmHg), and (5) high FG level (C110 mg/

dL). Participants who self-reported being diagnosed with

diabetes or who were receiving treatment for diabetes were

AIDS Behav (2016) 20:1123–1131 11

123

classified as having a high FG level. The same criteria were

used for high BP.

Statistical Analysis

Statistical analyses were performed with the Statistical

Package for Social Sciences (SPSS) version 22 for Win-

dows (IBM Inc., Chicago, IL, USA). Statistical analyses

included descriptive statistics and frequencies for each

variable. Linear Mixed Modeling (LMM) was used to

assess the fixed effect of time on changes in the outcome

variables (hsCRP, estimated VO2max, 1-RM bench press,

and 1-RM leg press) from baseline to 3-months follow

up. The significance level of all analyses was a \ 0.05.
LMM with heterogeneous compound symmetry covariance

allowed us to account for missing values, subject attrition,

inter-correlated responses between time points, and non-

constant variability. Changes in hsCRP from baseline to

3-months follow up were further examined controlling for

potential confounders, specifically body mass index, waist

circumference, aerobic fitness, and individuals with

hsCRP [ 3 mg/L classified as high risk at baseline. Paired
t tests were used to assess changes in metabolic risk factors

(BP, BMI, FG, HDL-C, LDL-C, waist circumference and

triglycerides) from baseline to 3-months follow up. Chi

square analysis was used to assess the change in MetS

prevalence from baseline to 3-months follow up.

Given that the exercise program consisted of four ses-

sions per week, participants were stratified into exercise

compliance groups based on average exercise sessions

attended as follows: (a) Non-compliant (average of \19/
week for 3 months), (b) Somewhat compliant (average

1–29/week for 3 months), and (c) Compliant (C29/week

for 3 months), where compliant individuals completed at

least 50 % of the prescribed exercise. Comparisons

between groups from baseline to 3 months were analyzed

using LMM for outcome variables.

Results

Demographic data are presented in Table 1. Ninety PLWH

were enrolled in Healthy Living for Better Days. The

majority of participants were women (53.9 %), Black/

African American (65.2 %), and unemployed or disabled at

the time of participation (83.1 %). Nearly one-third of

participants were classified as having MetS at baseline.

Fifty-five percent of total participants were non-compliant

(49/89), 20.2 % were somewhat compliant (18/89), and

24.7 % were compliant (22/89) with the prescribed exer-

cise. After 3 months participation in Healthy Living for

Better Days, nearly one-quarter (24.7 %) of our partici-

pants were meeting physical activity recommendations

defined as a combination of moderate- and vigorous-in-

tensity aerobic exercise at least 75 min/week and resistance

training twice per week.

The fixed effect of time for hsCRP was found to be non-

significant (F[1,57.3] = 1.7, p = 0.19) (Fig. 1). Mean

hsCRP at baseline was 5.75 ± 7.62 mg/L (median 2.30)

and 7.54 ± 14.19 mg/L (median 2.95) at 3-months follow

up. Comparing hsCRP across categories of exercise com-

pliance groups (see Fig. 1) revealed non-significant fixed

effects for time (F[1,55.5] = 2.4, p = 0.13), exercise

compliance (F[2,62.1] = 0.06, p = 0.94) and exercise

compliance 9 time (F[2,55.5] = 0.99, p = 0.38). When

examining the effect of the exercise intervention on

changes in hsCRP from baseline to 3-months follow up

only among individuals classified as high risk

(hsCRP [ 3 mg/dL) at baseline, the fixed effect for time
was still found to be non-significant (F[1,30.3] = 0.2

p = 0.657). Comparing hsCRP levels by gender group

revealed a significant fixed effect for gender

(F[1,68.6] = 4.08, p \ 0.05]), with women displaying an
overall higher mean hsCRP (8.50 ± 12.69 mg/L) than men

(4.46 ± 13.65 mg/L). The fixed effect for time

(F[1,57.4] = 1.75, p = 0.19]) and gender 9 time was non-

significant (F[1,57.4] = 0.06, p = 0.80]). The fixed effect

of time on changes in CRP from baseline to 3-months

follow up controlling for the use of protease inhibitors

(F[1,55.6] = 1.7, p = 0.200), BMI (F[1,53.2] = 1.7,

p = 0.199), aerobic fitness (F[1,50.1] = 1.1, p = 0.304),

and sleep duration (F[1,56.1] = 2.4, p = 0.129) was found

to be non-significant.

Changes in participant’s metabolic risk profile can be

found in Table 2. Diastolic BP (t(52) = 3.247, 95 % CI

1.55–6.58, p = 0.002) and waist circumference

(t(58) = 2.268, 95 % CI 0.06–1.02, p = 0.027) signifi-

cantly decreased from baseline to 3 months. There were no

significant changes from baseline to 3 months for body

weight (t(58) = 0.405, 95 % CI -1.24 to 1.86, p = 0.687),

SBP (t(52) = 1.796, 95 % CI -0.41 to 7.31, p = 0.078),

BMI (t(58) = 0.196, 95 % CI -0.24 to 0.29, p = 0.845),

triglycerides (t(61) = 0.806, 95 % CI -9.69 to 22.79,

p = 0.423), total cholesterol (t(61) = 0.065, 95 % CI

-7.22 to 7.70, p = 0.948), HDL-C (t(61) = 1.875, 95 %

CI -0.17 to 5.37, p = 0.066), VLDL-C (t(61) = 0.845,

95 % CI -1.87 to 4.62, p = 0.401), LDL-C

(t(61) = -1.186, 95 % CI -10.01 to 2.55, p = 0.240), or

FG (t(61) = 1.226, 95 % CI -3.49 to 14.56, p = 0.225).

There was a non-significant decline in individuals with

MetS from baseline to 3 months (32 vs. 19 %, v2(1,
Nbaseline = 89, N3months = 63) = 3.43, p = 0.06).

The fixed effect of time for changes in VO2max was

found to be non-significant (F[1,36.3] = 3.5, p = 0.07)

(Table 3). For upper body 1-RM, a significant fixed

effect was found for time (F[1,51.6] = 18.1, p \ 0.05)

1126 AIDS Behav (2016) 20:1123–1131

123

and the parameter estimate between baseline and 3

months follow up was also significant (t[51.6] = -4.3,

p \ 0.05). Likewise, for lower body 1-RM a significant
fixed effect was found for time (F[1,48.0] = 15.7,

p \ 0.05) and the parameter estimate between baseline
and 3 month follow up was also significant

(t[48.0] = -4.0, p \ 0.05).

Discussion

Among our participants, changes in hsCRP were not

impacted by 3 months of CARET, even among individuals

with high hsCRP levels at baseline. The number of indi-

viduals classified as having MetS declined from baseline to

3-months, however these results were found to be non-

Table 1 Demographic and
baseline population

characteristics by gender

Overall (n = 89) Men (n = 41) Women (n = 48)

Age (years) 48 ± 7 48.7 ± 7 47.8 ± 7.6

Body mass index (kg/m
2
) 31.2 ± 7.8 28.7 ± 5.2 33.4 ± 8.9

Duration of HIV (years) 17.6 ± 12.7 15.3 ± 7.6 19.5 ± 15.7

Ethnic, n (%)

Non-Hispanic White 9 (10.1) 7 (17.1) 2 (4.2)

African-American 58 (65.2) 21 (51.2) 37 (77.1)

Hispanic 20 (22.5) 12 (29.3) 8 (16.7)

Current smoker, n (%) 32 (36.0) 16 (39.0) 16 (33.3)

Antiretroviral therapy, n (%)

Protease inhibitors 46 (51.7) 22 (53.7) 24 (50.0)

Non-protease inhibitors 36 (40.4) 16 (39.0) 20 (41.7)

Employment, n (%)

Unemployed 74 (83.1) 30 (73.2) 44 (91.7)

Employed (part or full time) 14 (15.7) 11 (26.8) 3 (6.3)

Yearly household income, n (%)

\$5000 27 (30.3) 11 (26.8) 16 (33.3)
$5000–$14,999 38 (42.7) 20 (48.7) 18 (37.6)

$15,000–$39,999 12 (13.4) 6 (14.7) 6 (12.5)

Data are mean ± SD or n (%)

0
5

Baseline 3-Months

M
ea

n
CR

P
(m

g/
L)

Non-compliant Somewhat Compliant Compliant

Fig. 1 Changes in levels of
C-reactive protein across

exercise compliance groups.

Data are mean ± SD. Non-

compliant, average exercise

session of \19/week for
3 months; Somewhat

Compliant, average exercise

session of 1–29/week for

3 months; Compliant, average

exercise session of C29/week

for 3 months; hsCRP, high

sensitivity C-reactive protein

AIDS Behav (2016) 20:1123–1131 1127

123

significant. Participants did significantly increase muscular

strength of the upper and lower body and displayed a trend

for improved aerobic capacity.

Disappointingly, a majority of participants (55 %) were

not compliant with the prescribed exercise regime. Previ-

ous literature has documented barriers and challenges to

appointment adherence or research participation among

PLWH [31, 32]. Though few studies have specifically

assessed challenges to participating in exercise programs,

there have been reports of moderate withdrawals (range

3–44 %) and low compliance (range 24–82 %) in other

exercise interventions [19]. Macarthur et al. [33], reported

transportation and difficulty exercising as challenges to

completing exercise testing and training. Similarly, Neidig

et al. [34], reported changes in employment, unreliable

transportation, and family responsibilities as contributors to

withdrawal from an aerobic exercise trial. Nevertheless,

Healthy Living for Better Days was designed as a com-

munity-based exercise program in an effort to expand

access to a variety of participants. The program was well

received by most participants (data not reported); however,

the low compliance highlights the challenge of engaging

this population in exercise programs.

Mean levels of hsCRP were elevated at baseline

(5.75 ± 0.82 mg/L, Fig. 1) and 40 % of our participants

had hsCRP values that would be classified as high coronary

risk ([3 mg/L) under AHA and CDC guidelines [11].
Median levels of hsCRP at baseline and 3-months follow

up were greater than values previously reported in the lit-

erature among PLWH (1.20–2.83 mg/L) [14, 17]. Elevated

CRP has been associated with metabolic risk factors such

as obesity, hypertension, and dyslipidemia [35]. Among

our participants BMI and waist circumference were ele-

vated at baseline and additionally a few of our participants

displayed very high CRP values perhaps reflective of the

disease course of the HIV infection. Thus, it is possible that

our cohort had more severe inflammation than the general

population of PLWH. Women in our sample were found to

have significantly higher hsCRP levels than men. This is

consistent with data from the third National Health and

Nutrition Examination Survey that found that the odds of

having elevated CRP levels is twofold higher among

women than men [35].

Participants showed a trend for an increase in VO2max of

2.2 mL/kg/min with 3 months of training (Table 3).

Although this trend was not significant, our results were

consistent with previously reported changes in VO2max
(range ?2.6 to ?4.7 mL/kg/min) after 3 months of training

among PLWH [8, 36]. Exercise adherence did not appear

to be a contributing factor as even the compliant cohort of

subjects showed no significant improvement in hsCRP. In

contrast to our 3-month program consisting of CARET,

Lindegaard et al. [37] found that hsCRP levels declined in

a small sample (n = 18) of HIV-positive men who per-

formed 35 min of endurance training 39/week for

16 weeks (baseline hsCRP, 2.42 mg/L [1.01–5.80],

16-week hsCRP, 1.82 mg/L [0.76–4.36]; p \ 0.0001).
However, the effect of exercise on inflammatory

biomarkers was not the primary variable studied by Lin-

degaard et al. [37]. Nonetheless, we cannot rule out the

possibility that a longer intervention or higher sustained

intensity of aerobic exercise is needed to impact systemic

inflammation.

Table 2 Changes in metabolic risk profile after 3-months of CARET

Baseline 3 months p value

Total body weight (lbs) 191.9 ± 46.5 191.6 ± 46.6 0.687

Systolic BP (mmHg) 127 ± 12 124 ± 11 0.078

Diastolic BP (mmHg) 82 ± 9 78 ± 8 0.002*

Body mass index (kg/m
2
) 30.7 ± 7.4 30.7 ± 7.4 0.845

Waist circumference (inch) 41.2 ± 7.0 40.7 ± 7.4 0.027*

Total triglycerides (mg/dL) 125.4 ± 72.6 118.8 ± 55.7 0.423

Total cholesterol (mg/dL) 186.7 ± 35.0 186.5 ± 42.0 0.948

HDL cholesterol (mg/dL) 52.3 ± 16.1 49.7 ± 13.7 0.066

VLDL cholesterol (mg/dL) 25.1 ± 14.5 23.7.1 ± 11.2 0.401

LDL cholesterol (mg/dL) 109.4 ± 30.2 113.1 ± 38.1 0.240

Fasting glucose (mg/dL) 95.7 ± 35.1 90.2 ± 16.5 0.225

Data are mean ± SD

CARET combined aerobic and resistance exercise training, BP blood

pressure, VLDL very low density lipoprotein, LDL low density

lipoprotein, HDL high density lipoprotein

* Significant difference from baseline to 3 months (p \ 0.05, paired
t test)

Table 3 Changes in
cardiorespiratory fitness and

muscular strength

Baseline 3 months Statistic

VO2max (mL/kg/min) 27.2 ± 8.9 29.4 ± 10.0 F[1,36.3] = 3.5, p = 0.07

Upper body 1-RM (lbs) 114 ± 51 125 ± 46 F[1,51.6] = 18.1, *p \ 0.001
Lower body 1-RM (lbs) 225 ± 81 250 ± 96 F[1,48.0] = 15.7, *p \ 0.001

Data are mean ± SD

VO2max maximal volume of oxygen consumed, 1-RM one-repetition maximum

* Significant fixed effect on time (p \ 0.05)

1128 AIDS Behav (2016) 20:1123–1131

123

Participants significantly increased both upper and lower

body strength after 3 months of CARET as has been shown

in other studies that involved resistance training among

PLWH [20, 38, 39]. The improvements in strength in our

study, however, were not associated with a significant

improvement in hsCRP levels from baseline to the 3-month

follow up (Fig. 1). Likewise, Lindegaard et al., [37] found

that despite a 30 % improvement in strength after

16 weeks of resistance training, there was no significant

change in CRP levels (baseline CRP: 1.54 mg/L

[1.0–2.37], 16-week CRP: 1.65 mg/L [1.07–2.54];

p = 0.44) among HIV-positive men. Similarly, among

older adults assigned to 10-months of strength and flexi-

bility training serum CRP levels were not improved com-

pared to those in an aerobic exercise arm [24]. These

results may indicate that aerobic exercise rather than

resistance training may be the primary mode of exercise by

which systemic inflammation is impacted.

It has been suggested that reduction in systemic

inflammation may be the mechanism driving the pro-

tective effects of regular physical activity and exercise

for chronic disease risk [22]. Yet, a meta-analysis by

Kelley et al., [26] of randomized controlled trials among

adult subjects reported a non-significant 3 % decrease in

CRP levels in aerobic exercise interventions ranging

from 8 weeks to 6 years. On the other hand, CRP levels

were reported to significantly decline in aerobic exercise

trials among older adults [24] and postmenopausal obese

women [25] after 10- and 12-months of training,

respectively. Thus, greater gains in aerobic fitness as

measured by VO2max may be necessary to affect hsCRP

levels in PLWH. Future studies examining the role of

exercise interventions on systemic inflammation should

incorporate randomization to an aerobic-only comparison

arm.

The presence of one or more cardiovascular risk fac-

tors, specifically those which contribute to the classifica-

tion of MetS, are associated with a pro-inflammatory

state. Data from the third National Health and Nutrition

Examination Survey indicated that the presence of at least

one abnormal cardiovascular risk factor was associated

with a threefold higher prevalence of elevated CRP [35].

Among PLWH metabolic changes secondary to the

extensive use of ART, such as insulin resistance, adiposity

and poor lipid profiles, has contributed to an elevated

cardiovascular risk profile [40–42]. In our cohort nearly

one-third of participants had MetS at baseline. After 3

months of CARET we observed a significant decrease in

DBP and waist circumference. Loss of abdominal sub-

cutaneous fat and therefore reduced central obesity could

have been indicative of HIV-associated lipoatrophy [43].

Further investigation of body composition and body fat

distribution may be warranted to fully understand the

relationship between metabolic risk factors and inflam-

mation. Though not significant, we observed a trend

towards decreased SBP, total triglycerides, FG, and the

number of individuals with MetS. We did not observe

changes in total body weight or BMI. Several studies have

reported a rapid progression to MetS after initiation of

ART [44–47]. Given the deleterious impact of ART on

metabolic risk factors and the rate of change reported in

previous studies among PLWH, it appears that our pro-

gram may have been effective in delaying a worsening of

these side effects. A longer intervention, in combination

with changes in total body weight, may be necessary to

reduce metabolic risk factors and potentially impact

hsCRP levels.

A strength of the Health Living for Better Days pro-

gram was its enrollment of a sample of participants

comprised mainly of minorities ([85 %). African Amer-
icans and Hispanics continue to bear a disproportionate

burden of new HIV cases despite only representing 13.1

and 16.9 % of the general U.S. population, respectively

[30]. For this reason our results may be more generaliz-

able to the larger population of PLWH. A majority of

participants were of low SES as evidenced by high rates

of unemployment (83.1 %) and low household income

(73 %), defined as earning less than $15,000 annually.

Over half of the sample was comprised of women, who

according to the CDC accounted for one in four new HIV

infections in 2010 [2]. Our program included a compre-

hensive assessment of fitness and obtained extensive

information on metabolic risk factors. Furthermore, while

several other protocols have utilized a 6–8 h fast for

blood sampling, we utilized a 12-h fast, thus avoiding

exaggerated triglycerides and eliminating serum chy-

lomicrons which could overestimate triglyceride and

MetS rates.

In addition to the strengths of our study, several limi-

tations were present. Our study design was not a ran-

domized controlled trial and did not include a non-

exercise control arm, though all analyses were conducted

as intent-to-treat. We did not obtain HIV ribonucleic acid

(RNA) levels or information pertaining to secondary

infections, which limits our ability to examine the effect

of CARET on systemic inflammation independent of

changes in the disease course. Similarly, while we did

ascertain the type of ART used among our participants we

did not obtain the total duration of exposure to combi-

nation ART. Extended exposure to combination ART

regimes has been found to increase the risk of myocardial

infarction [48, 49] and thus has the potential to impact

both metabolic risk profile and

systemic inflammation.

Further, we cannot rule out the impact of diet and overall

nutritional status on cardiovascular risk reduction and

systemic inflammation.

AIDS Behav (2016) 20:1123–1131 1129

123

Conclusion

In conclusion, our study enrolled a diverse cohort of HIV-

infected individuals receiving ART, who were of pre-

dominantly low SES. Overall mean levels of hsCRP were

elevated in our cohort of HIV-infected individuals receiv-

ing ART. Though levels of hsCRP were not impacted after

3 months of CARET, participants demonstrated a signifi-

cant increase in upper and lower body muscular strength as

well as beneficial changes in waist circumference and

diastolic blood pressure. Although low compliance to the

prescribed exercise limits our ability to make definitive

conclusions about the impact of exercise on systemic

inflammation, it is possible that a longer intervention or

greater intensity is necessary to induce improvements in

aerobic fitness and metabolic profiles and thus impact

systemic inflammation. Future studies should focus on

effective ways of engaging and retaining HIV-infected

minorities in structured exercise interventions and dis-

cerning the optimal dose and duration of exercise to reduce

inflammation.

Acknowledgments This material is based on work supported by
AstraZeneca HealthCare Foundation’s Connections for Cardiovas-

cular HealthSM (CCH) program. The CCH program funds charita-

ble work, not research that addresses cardiovascular health issues

within the United States and its territories. Any opinions, findings,

and conclusions or recommendations expressed in this material are

those of the authors and have not been reviewed for approval by the

AstraZeneca HealthCare Foundation.

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http://dx.doi.org/10.1186/s13098-015-0008-5

The Effect of a Community-Based Exercise Program on Inflammation, Metabolic Risk, and Fitness Levels Among Persons Living with HIV/AIDS

Abstract
Introduction
Methods
Study Design
Participants
Exercise Program
Physical Characteristics
Blood Sampling and Analyses
Physical Fitness
Statistical Analysis
Results
Discussion
Conclusion
Acknowledgments
References

Multiple Sclerosis Journal
2014, Vol. 20(3) 382 –390
© The Author(s) 2013
Reprints and permissions:
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DOI: 10.1177/1352458513507358
msj.sagepub.com

MULTIPLE
SCLEROSIS MSJ
JOURNAL

Introduction

Currently approved disease-modifying therapies (DMTs)
for multiple sclerosis (MS) have limited impact on the neu-
rodegenerative component of the disease. Therapeutic
effects on cognition, which might be the best clinical cor-
relate of widespread neurodegeneration, are modest at
best.1, 2 One review shows that attempts to develop pharma-
cological therapies for cognitive impairment have been
unsuccessful in MS.3 Evidence for the effectiveness of
rehabilitation strategies to ameliorate cognitive deficits in
MS is limited, as well.4 Therefore, therapeutic approaches
that target neuroprotective mechanisms and may improve
cognition and motor function are urgently needed.5

Intriguingly, exercise is shown to promote neuroregen-
eration and plasticity and to improve learning and memory,
in rodents.6 Several randomized controlled trials (RCTs) of

Effects of exercise on fitness and cognition
in progressive MS: a randomized,
controlled pilot trial

S Briken1,2, SM Gold1, S Patra3, E Vettorazzi4, D Harbs3,
A Tallner5, G Ketels6, KH Schulz3,7 and C Heesen1,2

Abstract
Background: Exercise may have beneficial effects on both well-being and walking ability in multiple sclerosis (MS). Exer-
cise is shown to be neuroprotective in rodents and may also enhance cognitive function in humans. It may, therefore, be
particularly useful for MS patients with pronounced neurodegeneration.
Objective: To investigate the potential of standardized exercise as a therapeutic intervention for progressive MS, in a
randomized-controlled pilot trial.
Methods: Patients with progressive MS and moderate disability (Expanded Disability Status Scale (EDSS) of 4–6) were
randomized to one of three exercise interventions (arm ergometry, rowing, bicycle ergometry) for 8–10 weeks or a
waitlist control group. We analyzed the drop-out rate as a measure of feasibility. The primary endpoint of the study was
aerobic fitness. Secondary endpoints were walking ability, cognitive function as measured by a neuropsychological test
battery, depression and fatigue.
Results: A total of 42 patients completed the trial (10.6% drop-out rate). Significant improvements were seen in aero-
bic fitness. In addition, exercise improved walking ability, depressive symptoms, fatigue and several domains of cognitive
function.
Conclusion: This study indicated that aerobic training is feasible and could be beneficial for patients with progressive
MS. Larger exercise studies are needed to confirm the effect on cognition.
Trial Registration: ISRCTN (trial number 76467492) http://isrctn.org

Keywords
Aerobic exercise, clinical trial, cognition, depression, fatigue, fitness, motor function, multiple sclerosis, progressive
multiple sclerosis, rehabilitation, walking ability

Date received: 15 July 2013; accepted: 8 September 2013

1 Institute for Neuroimmunology and Clinical Multiple Sclerosis Research
(inims), University Hospital Eppendorf, Hamburg, Germany.

2 Department of Neurology, University Hospital Eppendorf, Hamburg,
Germany.

3 Competence Center for Sports and Exercise Medicine (Athleticum),
University Hospital Eppendorf, Hamburg, Germany.

4 Department of Medical Biometry and Epidemiology, University Medical
Center Hamburg-Eppendorf, Germany.

5 Institute of Sport Science, University of Erlangen-Nürnberg, Germany.
6 Department of Physiotherapy, University Medical Center Hamburg-
Eppendorf, Germany.

7 Institute for Medical Psychology, Hamburg, Germany.
Authors Briken, Gold, Schulz and Heesen contributed equally.

Corresponding author:
Christoph Heesen, Institute for Neuroimmunology and Clinical MS
Research (inims), University Medical Center Eppendorf, Martinistrasse,
Hamburg, Germany.
Email: heesen@uke.de

507358MSJ20310.1177/1352458513507358Multiple Sclerosis JournalBriken et al.
2013

Research Paper

Briken et al. 383

aerobic exercise in both young healthy and aging adults
demonstrate improved cognitive function.7 Exercise may
therefore have therapeutic potential for improving cogni-
tive function in MS, but empirical evidence from rand-
omized controlled trials is lacking.8

Since the first RCT of exercise in MS by Petajan et al.9,
both improved quality of life and walking ability in MS
after exercise training were confirmed by several RCTs.10,
11 In addition to improving well-being, recent experimental
evidence suggests that exercise might directly affect pathol-
ogy, by showing neuronal protection during experimental
autoimmune encephalomyelitis (EAE).12

Exercise therapy might be a particularly useful approach
for MS patients with progressive disease, as treatment
options are very limited.13 On the other hand, the more
advanced motor impairment in secondary progressive MS
(SPMS) might interfere with the ability of the patients to
perform aerobic exercise training programs. Therefore,
there is a need to rigorously test the feasibility and effec-
tiveness of exercise in progressive MS.

In the present pilot-RCT, we aimed to compare three
endurance-training interventions in progressive MS
patients. We expected exercise to improve their physical
fitness, walking ability and cognitive function. Based on a
meta-analysis in non-MS populations7, we expected
improved performance in learning/memory, attention and
executive function.

Materials and methods

Study design, overview and patient recruitment

Our study was a RCT of three different exercise training
tools (arm ergometry, rowing and bicycle ergometry) and a
waitlist control group with progressive MS patients with
moderate disability (see Supplemental Figure). The training
programs consisted of 8–10 weeks of standardized exercise
with 2–3 sessions per week. This time frame was chosen as a
pragmatic approach, to also allow short interruptions of the
training with the aim of obtaining about 20 training sessions.
The training program was tailored to the individual level of
fitness of the participants, as determined by standard ergom-
etry at baseline. The feasibility measure of the study was the
percentage of subjects completing the trial.

Our main hypothesis was that the training program
would increase fitness, as measured by increased peak oxy-
gen consumption (VO2), and would improve walking abil-
ity, as measured by gait tests. The primary endpoint was
aerobic fitness (as defined by peak oxygen consumption
during an exhaustion test). Secondary endpoints were:
walking ability (as defined by the 6-Minute Walk Test
(6MWT)), cognitive function (as measured by a neuropsy-
chological battery), depressive symptoms and fatigue. All
endpoints were assessed at baseline, as well as at the end of
the 8–10 week intervention (unblinded to the group).
Patients were recruited through the MS outpatient clinic at

the University Medical Center Hamburg Eppendorf, as
well as through advertisements on the website of the
German MS Society and leaflets left in neurologists’
offices. We also contacted patients from our database who
had agreed to be informed about new studies.

Standard protocol approvals and patient consent

The trial was approved by the ethics committee of the
Chamber of Physicians, City of Hamburg, Germany
(Registration Number PV3689). Participants provided
written informed consent prior to enrollment.

Participant inclusion and exclusion criteria

Patients had to meet diagnostic criteria for clinically defi-
nite MS14 with a secondary-progressive disease course15
and moderate disability (EDSS 4–6). To enhance recruit-
ment, we later also allowed patients with primary-
progressive MS (PPMS) to enter the trial, as long as they
met the EDSS inclusion criterion.

Patients were excluded if they had any medical contrain-
dications for exercise therapy (cardiovascular or major
orthopedic disease, general medical contraindications for
increased aerobic activity) as assessed by self-report using
the revised Physical Activity Readiness Questionnaire
(rPAR-Q).16 We excluded patients if they had started immu-
nomodulatory therapy within the last 6 months, undergone
steroid therapy within the last 4 weeks, documented
relapses within the last 12 months, abnormal liver or kidney
function, immunodeficiency, diagnosis of other serious
medical illnesses, or if they had severe developmental, psy-
chiatric and neurological disorders other than MS.
Eligibility was determined by an experienced senior neu-
rologist. As no previous studies were available to power the
exercise trial, its sample size was based on patient availa-
bility, with a recruitment goal of n = 40 (at least n = 10 in
each group).

Randomization

Patients were consecutively randomized to one of the four
groups, using an automated biased coin algorithm.17 This
approach used the a priori defined variables age, sex, EDSS
and previous group size. To ensure a concealed allocation,
we performed randomization after determining eligibility.

Individually-tailored training intervention

The training schedule for each participant was tailored to
the individual results from a bicycle ergometry perfor-
mance test that assessed aerobic fitness levels.18 Since MS
patients might not be able to reach their maximum perfor-
mance in a stepwise exhaustion test, we used a submaximal
performance index (aerobic threshold (AT)) for the adjust-
ment of the training intervention.

384 Multiple Sclerosis Journal 20(3)

The training was then performed with the modalities the
participants were randomized to. We used the following
equipment for training: First Degree Fitness® E-920 Upper
Body arm ergometer, the Ergofit® 3000 bicycle ergometer
and the Waterrower®.

We determined the training levels using a performance
test (ramp test) on the specific selected training tool (see
Supplemental Figure). We used the performance in Watts
(W) recorded at the individual AT as an anchor for the fol-
lowing training intensity categories: AT, 120% of AT and
130% of AT. The length of each training interval and the
target performance were steadily increased with every
training session (including regeneration sessions), accord-
ing to a predefined training plan. The performance as well
as subjective work load ratings (Borg scale) were recorded
during each training session.19 The length of the training
sessions steadily increased from 15 to 45 minutes (see
Supplemental Table 1). All training sessions were per-
formed at the Department of Physiotherapy, University
Medical Center Hamburg-Eppendorf, under the supervi-
sion of a licensed physiotherapist.

Outcome measures

Aerobic fitness. Participants started cycling at 25 W and
resistance was steadily increased with an incline of 12.5 W/
min. We obtained VO2 and heart rate continuously and
recorded maximum power. We measured lactate every 2
minutes. As some patients (n = 14) were unable to perform
this standard ergometry, for these participants, an easier
protocol was used starting at 8W with incremental increases
of 8W/min. These tests were conducted at the Competence
Center for Sports and Exercise Medicine in Hamburg, Ger-
many by an experienced sports scientist.

Motor function. We assessed walking ability before and
after the training program, using the 6MWT.20

Neuropsychological function. Cognitive impairment in MS
affects domains including attention, processing speed,
long-term memory and executive function.21 Therefore, we
administered a battery of standardized neuropsychological
tests that covered these domains.

The “Symbol Digit Modalities Test” (SDMT)22 was
utilized to measure processing speed. The “Verbal
Learning and Memory Test” (VLMT) was used to evalu-
ate declarative memory and learning abilities.23 Here, a
word list of 15 unrelated words is presented 5 times. The
test provides a measure of learning (sum of correctly
recalled words during the 5 trials), plus delayed recall
after 30 minutes. To assess attention, we used the “alert-
ness” and “shift of attention” subtests of the computerized
“Test Battery of Attention” (TAP).24 The “alertness” TAP
subtest consists of a simple reaction time test, with and
without cue (for “tonic alertness” and “phasic alertness”,
respectively). In the TAP subtest “shift of attention”, a

Posner paradigm with valid and invalid cues is used: After
valid cues, the stimulus is presented in the area, as indi-
cated by the arrow. After invalid cues, the stimulus is pre-
sented on the side opposite to that indicated by the arrow.
We quantified executive function with subtest 3 of the
“Achievement Testing System” (Leistungsprüfsystem
(LPS)).25 In this test, subjects select a symbol that does
not fit a sequence, i.e. they identify the rule behind the
sequence. The LPS was employed as a measure of logical
reasoning. In addition, we assessed verbal fluency using
the “Regensburg Verbal Fluency Test” (RWT), specifi-
cally subtest “letters G-R”.26 In a previous study, we dem-
onstrated that the VLMT, RWT and TAP are sensitive for
detecting cognitive impairment in MS.27

Patient-based outcome measures. We assessed depression
using the self-reported version of the 30-item “Inventory of
Depressive Symptoms” (IDS-SR30).

28 We measured fatigue
with the “Modified Fatigue Impact Scale” (MFIS). 29

Statistical analyses

We tested the feasibility of the different exercise modali-
ties by analyses of drop-out rates, using Fisher’s exact
test. Based on visual inspection of Quantile-Quantile
(Q-Q) plots, we conducted statistical analyses using para-
metric tests. According to guidelines for statistical analy-
sis of clinical trials, published by The European Agency
for the Evaluation of Medicinal Products (CPMP/
ICH/363/96 and CPMP/EWP/2863/99), we computed the
primary statistical analysis for all outcomes using
ANCOVA (Analysis of covariance) models adjusting for
baseline measurement of the respective outcome variable,
to evaluate treatment effects (measured as change from
baseline). No other covariates were included in this pri-
mary analysis. As recommended, this model also did not
include treatment by covariate interactions. In the case of
significant F values in the ANCOVA model, we conducted
planned pairwise comparisons for each intervention group
(bicycle, arm ergometry and rowing) compared to the
waitlist control group.

A total of 14 ANCOVAs were computed: One for the
primary endpoint (VO2 peak), and one for each of the sec-
ondary endpoints walking ability (6MWT), depressive
symptoms (IDS) and fatigue (MFIS) – for the multidimen-
sional assessment of cognitive function, we computed 10
ANCOVAs, of which four assessed attention. In accord-
ance with European Medicines Agency (EMA) guidelines,
we also computed sensitivity analyses using ANCOVA
models, adjusting for baseline as well as sex, age, EDSS
and patient MS type (SPMS or PPMS), in addition to the
primary analysis. For the ANCOVA models, we used avail-
able data from all our subjects who completed the pre- and
post-intervention assessments (n = 42).

Finally, we also computed non-parametric intention-
to-treat (ITT) analyses, using Kruskal-Wallis tests

Briken et al. 385

where the patients who dropped out were assigned the
lowest rank. In the results section, we report p values
from the primary analysis (ANCOVA, adjusted for
baseline). The p values from sensitivity analyses can be
found in Supplemental Table 2. Pre- and post mean
scores, standard deviations as well as confidence inter-
vals are indicated in Supplemental Table 3 and Spearman
correlation coefficients of change scores are indicated
in Supplemental Table 4. We performed statistical anal-
yses and conducted 2-tailed testing, using the statistics
package R 2.15.2.30 A value of p < .05 was considered statistically significant.

Results

Patient sample

We sent out 423 letters advertising the study. Patients who
indicated interest in participating (n = 80) were contacted
by phone for further screening. We examined 50 MS
patients in person at the MS clinic. After screening, 47
patients met our inclusion criteria and were randomized to
one of the four treatment arms: arm ergometry, rowing,
bicycle ergometry, waitlist control (see flow chart in Figure
1 and Table 1).

Feasibility

As a measure of feasibility, we analyzed MS patient drop-
out rates in the four groups. Of the 47 study participants, 42
finished the trial, while five dropped out. The drop-out rate
did not differ between the groups (p = .892; Table 1), indi-
cating that exercise intervention is feasible in progressive
MS with moderate disability (EDSS 4–6). Reasons for not
completing the trial included logistic and mobility difficul-
ties (n = 3), fatigue (n = 1) and injury unrelated to the study
(n = 1). Baseline characteristics for the four groups are
shown in Table 1. On average, the subjects exercised 22 ses-
sions. The average Borg rating during the sessions was 4.6.

Effects of exercise on fitness

Exercise induced significant improvements in aerobic fitness,
as measured by VO2 peak during the bicycle ergometry test
(Figure 2, p = .029). Only the bicycle ergometry group dif-
fered significantly from the control group (p = .003).

Effects of exercise on motor function

Exercise significantly improved distance walked by
patients during the 6MWT (Figure 3; p = .012). Significant

Figure 1. Participant flow chart.

386 Multiple Sclerosis Journal 20(3)

improvements were seen for both the arm ergometry (p =
.003) and bicycle ergometry groups (p = .005), in com-
parison to the control group.

Effects of exercise on neuropsychological function

Exercise improved 4 out of 10 neuropsychological
measures. Exercise significantly improved verbal
learning, as measured by the VLMT (p = .011, Figure

4(a)). Improvements were significant for the arm
ergometry (p = .007), the rowing group (p = .001) and
the bicycle group (p = .009), as compared to the waitlist
control group. In addition, a significant effect was found
for VLMT delayed recall (p = .002, Figure 4(b)). Again,
all exercise groups showed significant improvement,
when compared to the waitlist control group (arm
ergometry p = .004; rowing p < .001; bicycle ergometry p < .001).

Figure 2. Effects of standardized exercise therapy on
aerobic fitness of MS patients. A significant training effect was
observed in VO2 peak consumption during the step-wise bicycle
ergometry exhaustion test, the primary endpoint of the study.
Each dot represents one patient. Asterisks indicate significant
pairwise comparisons (* < .05; ** < .01). ml: milliliter; min: minutes; MS: multiple sclerosis;VO2 peak: peak oxygen consumption.

Figure 3. Effects of standardized exercise therapy on walking
ability in MS patients. Exercise therapy significantly improved
walking ability, as measured by the 6MWT. Each dot represents
one patient. Asterisks indicate significant pairwise comparisons
(* < .05; ** < .01). ergo: ergometry; MS: multiple sclerosis; 6MWT: 6-Minute Walking Test.

Table 1. Clinical baseline characteristics and training intensity.

Arm Rowing Bicycle Control

Drop-outs (n, %) 2 (16.6%) 1 (8.3%) 1 (8.3%) 1 (10%)
Subjects completing 10 11 11 10
Age (years) 49.1±8.5 50.9±9.2 48.8±6.8 50.4±7.6
Sex (m/f) 5/5 4/7 5/6 4/6
Education (years) 13.7±2.7 12.8±3.7 13.2±3.3 12.9±3.7
Disease duration (years) 17.1±7.2 14.1±6.1 13.3±5.4 18.9±9.8
EDSS (score) 5.2±0.9 4.7±0.8 5.0±0.8 4.9±0.9
MS type (SPMS/PPMS) 8/2 7 / 4 8/3 8/ 2
Number of sessions 21.1±0.5 21.7±0.4 22.6±0.9 N/A
Average Borg rating 4.3±0.5 5.3±0.3 4.3±0.1 N/A

EDSS: Expanded Disability Status Scale, SPMS: secondary progressive multiple sclerosis, PPMS: primary progressive multiple sclerosis. Data given as
mean+standard deviation.

Briken et al. 387

Significant group differences were observed for the
TAP subtest “tonic alertness” (p < .001; Figure 4(c)). The bicycle ergometry group showed significant improve- ments, compared to waitlist controls (p = .005). Furthermore, we saw significant effects in the TAP sub- test “shift of attention” (valid cue p = .007; Figure 4(d)). Again, the arm ergometry (p = .026), as well as the bicy- cle ergometry group (p = .002), showed significant improvements, compared to waitlist controls. No effects

of exercise were seen for the two other TAP subtests,
RWT, LPS and SDMT.

Effects of exercise on mood and fatigue

At baseline, 23 patients (49%) had IDS scores of 18 or
higher (indicating moderate to severe clinical depression).
Moreover, 27 patients (64%) had a MFIS score of 38 or
higher at baseline, indicative for substantial fatigue. Exercise

Figure 4. Effects of standardized exercise therapy on neuropsychological function. (a) Exercise resulted in significantly
more words remembered in the learning trials 1–5 of the VLMT. (b) Moreover, significant differences in delayed recall trial 7 were
seen. (c) Exercise significantly improved mean reaction times in the TAP alertness and (d) TAP shift of attention subtests. Each dot
represents one patient. Asterisks indicate significant pairwise comparisons (* < .05; ** < .01). TAP: Test Battery of Attention; VLMT: Verbal Learning of Memory Test.

388 Multiple Sclerosis Journal 20(3)

significantly decreased depressive symptoms as per IDS
(p < .001), with arm ergometry (p = .001) and bicycle ergometry (p = .035) showing significant improvements, compared to the waitlist control group. Finally, exercise also significantly improved fatigue, as per MFIS total score (p = .019), but only the arm ergometry group was signifi- cantly better than waitlist control (p = .013).

Associations between physical fitness,
walking ability and cognition

We saw significant, albeit small-to-moderate correlations
between improvements in the VO2 peak and the VLMT, as well
as walking ability (as measured by the 6MWT) and measures
of attention, fatigue and depression (Supplementary Table 4).

Discussion

In this study, we obtained the first evidence for beneficial
effects of exercise on physical measures (aerobic fitness
and walking ability), as well as neuropsychiatric symptoms
(cognitive impairment, depressive symptoms and fatigue)
in progressive MS.

In MS, exercise studies mostly focused on endpoints,
such as walking ability10 and quality of life11. Given the
high prevalence of neuropsychiatric symptoms such as
depression, fatigue and cognitive impairment in MS31, our
preliminary results obtained in this pilot study indicate
that exercise might have therapeutic potential for these
important symptom domains. Despite the evidence for the
beneficial effects of exercise on brain function provided
by animal models and RCTs in older healthy adults, only
one study to date explored the effects of exercise on cog-
nitive function in MS.32 This trial used a 6 months training
intervention with aerobic exercise at a low intensity (2–3
on the Borg scale), with one class per week plus home
exercise, and found no significant effects on neuropsy-
chological tests, compared to yoga delivered at the same
frequency. In contrast, herein we report significant
improvements in learning, memory and attention after
exercise training at a higher intensity (mean Borg scaling
4.6). Furthermore, for most of our endpoints, namely VO2
peak, depression, fatigue and measures of attention, the
strongest effects were seen in the bicycle group. Therefore,
further studies are needed to determine optimal exercise
intensity, as well as to verify the most effective training
modalities required to gain beneficial effects on neuropsy-
chiatric symptoms in MS.

Importantly, we found better performance in aspects of
verbal learning and delayed memory (VLMT), as well as
alertness and shift of attention (TAP), but not in working
memory (SDMT) or executive function (RWT and LPS).
Memory and attention were also shown to be consistently
improved by exercise training in a recent meta-analysis of
RCTs in healthy aging adults.7 On the other hand, this meta-

analysis also reported beneficial effects on executive function
and processing speed, which we did not find in our sample.
Whether this is due to chance, limited statistical power in our
study or whether there might be domain-specific differences
in the effects of exercise, depending on the patient population
and exercise conditions, remains to be elucidated.

Higher levels of fitness in MS patients are found to be
correlated cross-sectionally with higher structural connec-
tivity33 and higher gray matter density34, using neuroimag-
ing. Together, these data suggested that physical fitness
may be related to less severe CNS damage and higher struc-
tural integrity of brain networks that are important for cog-
nitive function, such as learning and memory in MS.

Our study suggested that exercise may improve walk-
ing ability in progressive MS. This corroborates and
expands the evidence from one recent uncontrolled trial
resulting in increased walking ability after 8 weeks of
mixed aerobic, resistance, and balance training in pro-
gressive patients with EDSS 4–6.35 Intriguingly, we found
improved walking ability, not only in the bicycle ergom-
etry group, but also for the arm ergometry training. The
underlying mechanisms for improved walking ability
after upper limb training in MS are unclear and warrant
further investigation. One possibility is that the increased
walking ability may be due to contributions of improved
cardiorespiratory function toward walking, as was previ-
ously shown for patients with peripheral arterial disease36,
37; however, since in our study the arm ergometry group
did not show significant improvement in the VO2 peak,
this explanation seems less likely. Another possibility is
that better core stability, through the training of abdomi-
nal and back muscles by arm ergometry, could help to sta-
bilize the body during movement, thereby improve
walking ability. Alternatively, improved walking ability
could be a non-specific result of the frequent trips to the
training facility, which may have provided some walking
training, but the rowing group had the same frequence of
trips without these significant improvements. This should
be investigated in future studies.

Some other limitations of our study need to be consid-
ered: First, the study sample was small and the findings,
particularly on cognitive function, require replication in
larger samples. The significant increase in fitness might
have, at least in part, been due to the decreased VO2 peak
in the control group; however, other outcomes remained
stable (6MWT) or slightly improved in controls (VLMT).
Therefore, we believe that the intervention effects are not
in general based on a worsening of the control group.

Secondly, our control condition consisted of a waitlist
group, rather than a non-exercise control condition deliv-
ered at the same frequency. Therefore, we cannot entirely
rule out that some of the effects, particularly those seen
in patient self-reporting measures such as the IDS and
MFIS, may be contributed by non-specific factors, such as
attention from the therapist or social support from other

Briken et al. 389

patients. However, the three different intervention groups
received the same frequency of visits, yet they did not
show the same pattern of therapeutic effects in the objec-
tive tests of aerobic fitness, walking ability and neuropsy-
chological function. This makes such non-specific effects
unlikely to explain our findings.

A related limitation might be that we had multiple sec-
ondary endpoints, particularly in the neuropsychological
domain. This was because of the lack of previous data
regarding the question which MS-related cognitive impair-
ments might be most likely to be affected by exercise.

Our study should therefore be considered a pilot trial;
however, the consistent pattern of improvements across
endpoints (with strongest improvements always in the
bicycle group) would argue against a chance finding
based on multiple testing.

While the short-term effects of our exercise training
study are encouraging, it remains unknown whether these
effects can be sustained over longer periods of time.
Maintenance of exercise in MS remains a major issue38 and
a better understanding of the barriers involved, as well as
development of effective strategies to overcome these, are
needed.39 Moreover, our findings were obtained in a sample
of progressive MS patients with moderate disability (EDSS
4–6). It therefore remains to be seen if our results can be
extended to higher disability ranges.

In summary, this trial provided the first evidence for ben-
eficial effects of standardized exercise training on aerobic fit-
ness, walking ability, cognitive function and neuropsychiatric
symptoms in patients with progressive MS and moderate-to-
advanced disability. Given the limited pharmacological treat-
ment options for progressive MS, further investigation of
exercise interventions in progressive MS is clearly warranted.

Conflict of interest

The authors declare that there are no conflicts of interest.

Funding

This work was supported by the “Bundesministerium für Bildung
und Forschung” (within the Consortium “Neu2” for the develop-
ment of new therapeutic approaches in MS) and a generous dona-
tion from Birgit Nollmeyer. SM Gold is supported by the German
Research Society (Heisenberg Fellowship number GO1357/4–1).

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