Comparison of energy expenditure, economy, and pedometer

Comparison of energy expenditure, economy, and pedometer
Eur J Appl Physiol (2009) 106:675-682
DOI 10.1007/s00421-009-1059-9
Comparison of energy expenditure, economy, and pedometer
counts between normal weight and overweight or obese women
during a walking and jogging activity
James D. LeCheminant * Timothy Heden - John Smith -
N. Kay Covington
“Accepted: 6 April 2009 / Published online: 1 May 2009
© Springer-Verlag 2009
Abstract This study compared energy expenditure (EE),
economy of movement, and pedometer counts between
normal weight and overweight or obese women during a
treadmill walking and jogging activity. Participants were 13
normal weight (BMI 22.2 + 2.0kg m7”) and 13 over-
weight or obese (BMI 27.2 + 2.1 kg m7”) women and all
were non-smokers, not regularly active, and able to run
1.609 km continuously at 223 ms~'. Each participant
reported to the laboratory on three separate days within a
I-week period. During the first visit, tests for resting
metabolic rate via indirect calorimetry, anthropometric
measures, and VO,max were completed. On the subsequent
two visits, participants were randomized to perform either
a 1.609-km walk at 1.34 ms”! or a 1.609-km jog at
2.23 m s7', During each physical activity trial, all partici-
pants wore a pedometer to assess steps taken. EE during the
1.609-km walk was 280 + 29 kJ for the normal weight and
356 + 42 kJ for the overweight/obese women and during
the 1.609-km jog was 393 + 46 kJ for the normal weight
J. D. LeCheminant (9)
Brigham Young University, 269 SFH, Provo,
UT 84606, USA
e-mail: [email protected]
T, Heden - N. K. Covington
Southern Illinois University Edwardsville,
Campus Box 1126, Edwardsville, IL 62026, USA
e-mail; [email protected]
N. K. Covington
e-mail; ncovington E siue.edu
J. Smith —
Texas A&M University-Kingsville, San Antonio,
1450 Gillette Blvd, San Antonio, TX 78224, USA
e-mail: [email protected]
and 490 Æ 59 KJ for the overweight/obese women. In both
trials, BE was statistically greater in the overweight/obese
women. Economy of movement was not statistically differ-
ent between the normal weight and overweight/obese
women during the walk or jog. In both groups, pedometer
counts were lower during the jog than the walk (P < 0.05). |
These data indicate significant differences in EE between
normai weight and overweight/obese women during both a
walking and j jogging activity.
Keywords Energy expenditure - Walking - Jogging -
Obesity
Introduction
It is well established that the prevalence of overweight and
obesity has increased worldwide (Filozof et al. 2001; Ford
and Mokdad 2008; Martorell etal. 2000; Ogden etal.
2006; Yoon et al. 2006) and is associated with increased
risk for multiple chronic and metabolic diseases, psycho-
social problems, and orthopedic impairments (Frey and
Zamora 2007; Ogden et al. 2006; Reeves et al. 2007; Stein
and Colditz 2004). According to the National Heart, Lung,
and Blood Institute, modest weight loss results in signifi-
cant health benefits and is desirable for overweight and
obese individuals; however, their minimum recommenda-
tion is to prevent further weight gain (NHLBI 1998). As
there is a general trend for adults to gain weight each year,
prevention of weight gain (i.e., weight maintenance) is
important and may reduce the risk for chronic disease and
assist in keeping lower-risk individuals from becoming
high risk.
Weight maintenance results from balancing energy
intake with energy expenditure (EE). Components of total
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Eur J Appl Physiol (2009) 106:675-682
daily EE include resting metabolic rate (RMR), thermic
— effect of food, and spontaneous and planned physical
activity, which account for -65-75%, 10%, and 15-25%
of total daily EE, respectively (Ravussin and Bogardus
1992). Physical activity (PA) is known to be an important
contributor for weight maintenance (Wing and Phelan
2005) and is the only component of EE that is easily modi-
fiable from day to day. As a result, health professionals
generally focus on the PA component as a means of
increasing EE and to adjust for small imbalances in energy
intake (Hill et al. 2003; Rodearmel et al: 2007). Recent
guidelines have promoted moderate-intensity activities for
five or more days per week or vigorous intensity activities
for three or more days per week and have included sugges-
tions to achieve these recommendations (Haskell et al.
2007). Additionally, there are promising behavioral tools,
such as pedometers, that may enhance the likelihood of
achieving current PA recommendations (Tudor-Locke and
Bassett 2004).
Despite the known benefits of PA and exercise, there is
evidence that EE during a given activity is often overesti-
mated (Buchowski et al. 1999; Walsh et al. 2004) and as a
result, the contribution of PA for weight management may
be exaggerated by some individuals. Prediction equations,
though useful, can be inconsistent tools to determine EE for
walking and jogging activities (Hall et al. 2004) and com-
mon “rules of thumb”, such as 1.609 km of walking equals
418 kJ, may not take into account important variables that
affect EE. It is, therefore, useful to accurately assess the
EE associated with common physical activities and for
individuals to use that information for effective weight
management. |
Walking and jogging are common modes of PA and are
often utilized as part of a weight management program.
Variables such as body mass, intensity, training level, and
gender have been reported in the literature to influence the
energy cost of walking and jogging activities. However,
much of the literature utilizes a lean or trained subject pop-
ulation. In addition, available studies that compare normal
weight and overweight/obese individuals for EE during a
given PA (Browning and Kram 2005; Lafortuna et al. 2008;
Lafortuna etal. 2006; Rutter 1994) rarely include both
walking and jogging to account for the influence of inten-
sity on ÉE.
Therefore, the purpose of this study was to augment
existing literature by determining the extent that EE
differed during a walking (1.609 km at 1.34 m s-') and jog-
ging (1.609 km at 2.23 m s7!) activity between normal
weight and overweight/obese women. In addition, this
study assessed net EE, economy of movement, and pedom-
eter counts for each participant in order to provide objective
and applicable data for women utilizing PA for weight
management.
€) Springer
Materials and methods
Participants
This study received Institutional Review Board approval
and each participant signed an informed consent prior to
initiating the study. Thirteen overweight/obese women
(BMI of >25kg m7") and 13 normal weight women
(BMI < 25 kg m”“) were recruited. Participants were
healthy and free of disease as determined by a physical
activity readiness questionnaire (PAR-Q) and health history
questionnaire, Participants were non-smokers, not'on medi-
cations that affect metabolism (thyroid, hypertensive, anti-
depressant medications, etc.), pre-menopausal, 18-26 years
of age, untrained {vigorous exercise <3 times/week), not
pregnant or lactating, able to walk 1.609 km continuously
at 1.34 m s7! (3 mph), and able to jog 1.609 km continu-
ously at 2.23 m s” (5 mph). Participants were recruited via
campus email, fliers, and word of mouth.
Procedures
Participants reported to the Exercise Physiology Laboratory
on three separate occasions, each separated by at least 24 h,
and within a 7-day period (Tues, Thurs, Sat or Mon, Wed,
Fri) at exactly the same time of morning and under the
same conditions (6-9 a.m., no vigorous exercise for at least
24 h, no caffeine for 12 h; no energy consumption for 8 h).
In addition, participants were asked to wear the exact same
clothes and shoes during each visit and to continue to eat
their regular diet. During each visit the laboratory was kept
at approximately the same temperature and humidity.
During the first visit, participants were asked to void and
were then measured for height using a Seca 214 Portable
Height Rod (Itin Scale Co., Inc, Brooklyn, New York,
USA) and body weight using a portable platform digital
“scale (Befour Inc, Saukville, W1.), both while barefoot and
wearing a standardized hospital gown. Body mass index
(BMI) was then calculated as kg m~2. Abdominal circum-
ference was measured using the umbilicus as a reference
point and hip circumference was measured at the widest
part of the gluteus maximus using a Gulick measuring tape
(Fitness Wholesale, Stow, OH).
Resting metabolic rate (RMR) was then estimated using
indirect calorimetry with a ParvoMedics TrueOne® 2400
metabolic measurement system (Sandy Lake, UT). The sys-
tem was calibrated with 19.52% O, and 1.0% CO, from a
compressed tank‘ and a flow meter calibration was
performed using a 3-L syringe with a flow rate between
40-50 L min! per stroke. During calibration and prior to
RMR testing each participant sat quietly in a chair for
5 min. During RMR testing each participant Hed comfort-
. ably in the supine position on an exam table in a private
677
Eur J Appl Physiol (2009) 106:675—682
room, with a clear-colored ventilated hood fitted comfort-
ably over the neck and head. A flexible plastic canopy
draped over the anterior torso and tucked under the back
was used to prevent unwanted flow in and out of the hood,
which was connected to the metabolic cart with flexible
tubing. In this way, oxygen consumption was captured in
the hood and flowed through the hose to the metabolic cart
for analysis and determination of RMR. Participants were
asked to position themselves in a way that would keep them
from fidgeting and were not allowed to talk or fall asleep
during the test. After positioning the participant, flow was
adjusted so room air (22-26°C) was drawn through the
hood at a rate of 15-30 L min! while keeping expired CO,
around 1.1 + 0.1%, Data collection lasted for 30 min with
the last 25 min averaged into an estimate of RMR.
Subsequently, participants were measured for body com-
position using the BOD POD® (Life Measurements Inc,
Concord, CA). The BOD POD® has been used in other
studies as a valid and reliable body composition assessment
technique (Fields et al. 2002; Levenhagen et al. 1999). Pre-
dicted lung volume was used, which has been shown to be
as accurate as measured lung volume {Collins and McCarthy
2003; Demerath et al. 2002), and the Sir equation was
applied to estimate percent body fat. Participants wore a
tight bathing suit or skin-tight clothing, a skull cap to com-
press the hair, removed jewelry and glasses before mea-
surements, and were asked to sit comfortably still while
breathing normally during measurements.
Lastly, aerobic fitness (VO,max) was assessed using the
TrueOne® 2400 with a Quinton SR 60 motor driven tread-
mill (Bothel, WA, USA). Calibration of the metabolic mea-
surement system for this test and the 1.609-km trials
consisted of using a 16.0% O, and 4.0% CO, concentration
gas, with flow calibrated using a 3-L syringe. Nose clips
and a proper fitting mouthpiece connected to a one-way
valve were used to ensure all expired air flowed into the
metabolic cart. A Polar chest strap was fitted and interfaced
with the metabolic cart for measurement of heart rate. The
Bruce Protocol was used to elicit maximal oxygen con-
sumption with an initial treadmill speed of 0.76 ms”!
(1.7 mph) on a 10% grade. At 3 min, metabolic data, HR,
and RPE (Borg’s 6-20 rating of perceived exertion) were
recorded and the treadmill speed then increased to
1.12ms (2.5 mph) with a simultaneous increase to 12%
grade. The test continued in this manner with increases
in speed to 1.52 m s7! (3.4 mph), 1.83 ms! (4.2 mph),
2.23 т 5! (5.0 mph), and a 0.22m s! (0.5 mph) increase
thereafter with 2% increases in grade every 3 min until vol-
untary exhaustion. A cool-down consisted of walking on
level grade а! 1.12 т 57! (2.5 mph) for 2 min. At least two
of the following criteria were considered achievement of
VO,max: respiratory exchange ratio (RER) over 1.10, a
leveling off in VO, consumption (a change no greater than
150 ml between stages), or +10 beats of estimated maxi-
mum heart rate. At this time, the 1.609-km trials (walk or
jog) were randomized and the second visit was scheduled.
Immediately before the second visit, participants were
asked to void and then a DIGI-WALKERTM SW-701
pedometer (New Lifestyles, Lee’s Summit, MO) was
placed on the right waist along the front of the thigh for step
counts during the 1.609-km trials. This pedometer was
selected because it is frequently used in epidemiological
and intervention studies due to its accuracy (Crouter et al.
2003; Schneider etal. 2004; Speck and Looney 2006).
Participants then sat comfortably in a chair for 10 min at
which time expired air was collected using the metabolic cart.
After 10 min, the mouthpiece was removed and the partici-
pant completed a warm-up that consisted of walking for
5 minat 1.12 ms”! (2.5 mph) on level grade. Upon conclu-
sion of the warm-up, participants straddled the treadmiil,
the mouthpiece was again fitted, and the pedometer reset to
zero. The treadmill was brought up to either 1.34 ms”!
(3 mph) or 2.23 ms”! (5 mph), both on 0% grade, and par-
ticipants began to walk or jog after 1 min of completing the
warm-up. Participants were allowed to use the handrails
only while mounting the treadmill. The walking speed of
1.34 ms! (3 mph) was chosen as it falls within a moder-
ate-intensity walking pace (3-6 METs)(Haskeil et al. 2007)
and the jogging speed of 2.23 m s7! (5 mph} was chosen as
it is considered a vigorous intensity (6 METs or greater)
(Haskell et al. 2007) but not so intense as to decrease the
likelihood that overweight or obese individuals could com-
plete a continuous 1.609-km jog. At exactly 1.609 km, the
participants immediately straddled the treadmill, the
mouthpiece was removed, RPE was recorded, and step
counts from the pedometer were recorded. Oxygen con-
sumption was measured during each of the trials and used
to determine gross EE. The third visit was conducted in the
same manner as the second with only the speed of locomo-
tion changed during the 1.609-km trial.
Statistical analysis
PC-SAS (version 8.2, SAS Institute, Inc., Cary, NC) was
used for all descriptive statistics (mean, standard deviation,
etc.) and unpaired ¢ tests were used to statistically deter-
mine differences between the normal weight and over-
weight/obese women for all outcomes reported. An alpha
level of P < 0.05 was used to determine significance for all
statistical analyses. In order to determine the actual EE cost
of just exercise, net EE (EE above RMR) was determined
by subtracting RMR per minute of exercise (20 min for
walk and 12 min for jog) from the gross EE. Economy of
‘movement {energy requirement of a given velocity of
movement) was reported as the average relative oxygen
consumption (ml kg”! min) during the walk and jog. In
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Eur J Appl Physiol (2009) 106:675-682
order to determine exercise intensity, the average relative
oxygen consumption during the walk or jog was divided by
VO,max (ml kg-! min-1) and multiplied by 100. Pearson
correlation coefficients were used to determine relation-
ships between descriptive characteristics and pedometer
counts. Where appropriate, body mass and fat-free mass
(FFM) were added to the statistical models as control vari-
ables.
Results
Participants were 26 women (13 normal weight and 13
overweight/obese), young, and primarily Caucasian (88%),
while the remaining 12% were 2 African-Americans and !
Asian-American. There was no difference in age or height
between the normal weight and overweight/obese women
(P > 0.05). The overweight/obese participants averaged a
BMI that was 5 kg m™ higher and a body weight that was
15.6 kg heavier than the normal weight participants. In
addition, abdominal and hip circumference were signifi-
cantly higher in the overweight/obese individuals
(P < 0.05). Body fat percentage tended to be higher in the
overweight/obese participants (P = 0.07) and FFM percent-
age tended to be lower in the overweight/obese participants
compared to the normal weight participants (P = 0.07).
However, when expressed in kg, both fat mass and FFM
were higher in the overweight/obese individuals (P < 0.05)
(Table 1). |
Resting metabolic rate was 13% higher in the over-
weight/obese participants compared to the normal weight
participants (P < 0.05). When RMR was adjusted for body
mass and FFM, there was no longer a difference in RMR
(P>0.05). VO,max (mlkg! min”) was significantly
greater in the normal weight women though both groups,
Table 1 Demographic and body composition characteristics
Normal Overweight/ P
weight obese
(n=13) (n=13)
Age (years) 21.2 + 1.5 20.2 +14 - 012
Weight (kg) 59.8 + 6.1 75.4 + 5.7 <0.00
Height (cm) 164.1 + 4.8 166.6 + 5.1 0.23
BMI (kg m”) 222+2.0 27.2+2.1 <0.00
Body fat (%) 27.3 + 7.0 32.3 + 32 0.07
Fat mass (kg) 16.6457 244457 <0.00
Fat-free mass (%) 72770 67.7 + 6,3 0.07
Fat-free mass (kg) 43.2 + 3.8 50.7 + 5.1 <0.00
Abdominal (cm) 76.0 + 5.3 89.4 + 8.0 <0.00
Hip (cm) 93.5 + 4.4 106.9 + 4.0 <0.00
Values are mean + SD
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on average, tended to possess a poor to fair level of fitness
(Heyward 2006). HRmax, RPEmax, and RERmax during
the VO,max test were not statistically different between the
normal weight and overweight/obese participants. Time to
exhaustion (min) during the VO,max test was significantly
shorter in the overweight/obese participants compared to
the normal weight participants (Table 2).
Gross EE was 27% higher in the overweight/obese
participants compared to the normal weight participants
during the 1.609-km walk (356 vs. 280 kJ, respectively)
(P < 0.05). Net EE during the 1.609-km walk was also
higher (31%) in the overweight/obese individuals com-
pared to the normal weight individuals (259 vs. 197 kJ,
respectively) (P < 0.05). Gross EE was 25% higher in the
overweight/obese group compared to the normal weight
group during the 1.609-km jog (490 vs. 393 kJ, respec-
tively) (P < 0.05). Likewise, net EE during the 1.609-km
jog was 28% higher in the overweight/obese individuals
compared to the normal weight individuals (431 vs. 338 kJ,
respectively) (P < 0.05). When expressed per unit of FFM
(kg) or body mass (kg), or when FFM or body mass was
statistically controlled for, there was no difference between
the normal weight and overweight/obese participants for
gross or net EE during the walk or jog (P > 0.05).
‘The overweight/obese participants tended to have higher
HR, RPE, and average RER during both the 1.609-km walk
and jog compared to the normal weight participants; how-
ever, only HR and average RER during the 1.609-km jog
were statistically significant. When intensity was expressed
as a percentage of VO,max (ml kg”! min”!), the over-
weight/obese women worked at a higher relative intensity
than the normal weight women for both the walk and the
Table 2 Resting metabolic rate and maximal oxygen consumption
Normal Overweight/ P
weight obese
(n = 13) {n= 13)
RMR [kJ day 6,113 + 678 6912 + 515 <0.00
(kcal day)] (1,461 £162) (1,652 + 123}
RMRFFM (kg)! 141.7 + 10.2 137.5 + 15.9 0.43
(kJ day)
Resting RER 0.84 + 0.03 0.83 +: 0.04 0.84
VO,max 38.5 + 5.6 31,9 + 3.2 <0.00
(ml kg”! min!)
HRmax (bpm) 181 + 13 186 + 9 0.30
RPEmax 16.8 + 2.9 17.7 + 1.4 0.36
RERmax 1.13 + 0.07 1.15 + 0.06 0.45
Time to Exhaustion 10.7+—12 9.3 + 1.0 0.03
(min)
Values are mean + SD
RMR resting metabolic rate, kJ day kilojoules per day, kcal day kilo-
calories per day, HR heart rate, RPE rating of perceived exertion
(Borg’s 6-20 scale), RER respiratory exchange ratio
Eur } Appl Physiol (2009) 106:675—682
679
jog (P<0.05). Economy of movement, as expressed by
average VO,, during either the walk or jog (Morgan et al.
1989) was not statistically different between BMI groups
(Table 3).
During the 1.609-km walk there was no difference in
pedometer counts between the overweight/obese individu-
als (2,365 + 272) and the normal weight individuals
(2,339 + 85) (P> 0.05). Similarly, during the 1.609-km
. jog, there was no difference in pedometer counts between
the 2 groups (1,902 + 103 vs. 1,862 + 153 for overweight/
obese and normal weight individuals, respectively)
(P > 0.05). However, within each group, the 1.609-km
walk resulted in approximately 25% more pedometer
counts than the 1.609-km jog (P < 0.05) (Fig. 1). Control-
ling for height did not change the difference in pedometer
steps during the walk or jog, between or within groups.
Correlation analysis revealed that height was indirectly
Table 3 Energy expenditure during the 1.609-km walk and 1.609-km
jog
Overweight/ P
Pedometer Counts
Normal
weight obese
(n= 13) (n = 13)
1.609-km walk
Gross EE [kJ (kcal)] 280 + 29 356 + 42 <0.00
(67 + 7) (85 + 10)
Net EE [kJ (kcal)] 197 + 21 259 + 38 0.04
(47 + 5) (62 + 9)
Ending HR (bpm) 100 + 9.0 107 + 12 0.11
Ending RPE 94+19 10.5 + 1.4 0.09
Intensity (%VO,max) 31.2 +47 35,8 + 3.9 0.01
Average RER 0.85 + 0.04 0.86 + 0.02 0.44
EE kg”! min”! 0.24 £0.02 0.24 + 0.01 0.98
EE FFM (kg)! min! 0.33 + 0.03 0.35 + 0.05 0.10
VO, (ml kg”! min 1.8 + 0,9 11.3 + 0.4 0.10
1,609-km jog
Gross EE [kJ (kcal)] 393 + 46 490 + 59 <0.00
(94 + 11) (117 + 14)
Net EE [k] (kcal)] 338 + 46 431 + 59 <0.00
(82 + 11) (103 + 14) |
Ending HR (bpm) 160418 1764205 0.05
Ending RPE 13.0 4 2.2 15.1 + 3.0 0.06
Intensity (%VO,max) — 70.6 +9.1 80.8 + 10.7 0.01
Average RER 0.91 £004 0,96 + 0.06 0.02
EE kg”! min”! 0.55 ++ 0.04 0.54 + 0.04 0.50
EE FFM (kg) ! min”! | 0.77 + 0.09 0.80 = 0.09 0.25
VO, (ml kg”! min!) 26.7+19 25.4 + 1.6 0.08
Values are mean + SD
Gross EE total energy expenditure during the trial, ner EE total
energy expenditure during the trial minus resting metabolic rate,
EE kg" min! energy expenditure (kJ) per kilogram of body weight,
EE FFM(kg) = min~ energy expenditure (kJ) per kilogram of fat-free
mass
3000
2500
2000 -
1500 -
1000 -
500 -
0 i я -
Normal Weight Overweight/Obese
Fig. 1 Pedometer counts during the 1.609-km walk and 1.609-km jog.
Asterisk indicates significant difference between walk and jog within
each group. Walking counts were not different (P = 0.75) nor were jog-
ging counts different (P = 0.44) between the normal weight and over-
weight/obese women
related to pedometer steps during the walk (r= —0.417,
P < 0.05) but not jog (r = —0.17, P > 0.05). When the rela-
tionship between height and pedometer steps was analyzed
by BMI group, height was moderately and negatively asso-
ciated with walking (r= —0.657, P< 0.05) and jogging
(r= —0.554 Р < 0.05) counts in the overweight/obese but
not normal weight participants.
Discussion
This study compared EE in normal weight and overweight/
obese women during a walking and jogging activity to pro-
vide valid and quantitative data for women utilizing PA for
~ weight management, This study supports existing literature
that body mass significantly impacts RMR and EE during a
given PA (Browning et al. 2006; Browning and Kram
2005; Freyschuss and Melcher 1978; Lafortuna et al. 2008),
and the intensity of the PA significantly influences EE
(Greiwe and Kohrt 2000; Hall et al. 2004). While differ-
ences in EE during the walk and jog disappeared for both
BMI groups when adjusting for body mass and FFM, gross
EE remained approximately 25% higher for the over-
weight/obese women during the walk and jog. This study is
unique in that the overweight/obese participants were
untrained but able to run continuously for 1.609 km;
whereas, other studies have typically used trained individu-
als or cycling as the mode of exercise when comparing nor-
mal weight and overweight individuals (Hulens et al. 2001;
Lafortuna et al. 2008). In addition, we quantified EE objec-
tively using indirect calorimetry as opposed to prediction
equations or PA questionnaires. Further, a female popula-
tion was used to control for potential gender differences in
EE (Browning et al. 2006).
The effect of walking and jogging activities has received
considerable attention in the literature. Based upon previous
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Eur J Appl Physiol (2009) 106:675-682
research, the EE of walking versus speed for a given dis-
tance resembles a U-shaped curve (Bastien etal. 2005;
Browning and Kram 2005; Ralston 1958) with the walk-
ing speed that elicits the minimum EE at approximately
1.3-1.4 m s~! (Alexander 2005; Bastien et al. 2005; Martin
et al. 1992; Zarrugh et al. 1974). Slower walking has been
associated with increased EE (Browning and Kram 2005),
while walking at greater speed for a given distance
increases EE in a curvilinear fashion (Bastien et al. 2005:
Browning and Kram 2005). Furthermore, previous studies
have indicated that the walking speed associated with the
minimum EE (1.3-1.4 т 57?) го Бе approximately equal to
preferred speed of walking for norma! weight individuals
(Browning and Kram 2005). While previous reports indi-
cate obese individuals tend to prefer a slower speed of
walking than normal weight adults, Browning and Kram -
recently reported similar preferred speeds of walking
(Browning and Kram 2005). Thus, while variations in
walking speed result in differences in EE for a given dis-
tance, the speed of walking utilized in the present study
(1.34 т 5!) and the associated EE likely generalizes well
to normal weight and overweight/obese individuals as it
may be comparable to their preferred speed of walking
utilized for exercise.
There appears to be a point in which fast walking costs
more energy than jogging at the same speed (Falls and
Humphrey 1976). This crossover point tends to be the
speed in which there is a spontaneous transition from
walking to jogging and is associated with jogging speeds of
2.2-2.5ms”' (McArdle etal. 2007; Menier and Pugh
1968). In addition, EE during jogging and running activities
appears to be independent of speed for a given a distance,
incline, and person. For example, a woman jogging
2.23 m s”! for 1.609 km results in similar EE as running
3.6 ms”! for 1.609 km at the same grade; only the time to
completion differs (McArdle etal. 2007). In the present
study, the speed of 2.23 m s-! was chosen because it repre-
sents “vigorous” intensity activity, it was a feasible jogging
speed for some larger individuals, and it corresponds well
to the speed of spontaneous jogging rather than fast walk-
ing. As a jogging speed of 2.23 т 57! Рог 1.609 Кт is not
likely to be a typical speed for fast walking and also scales
similarly to higher intensity jogging/running speeds, the
data from the present study provides a good estimation of
EE for both normal weight and overweight/obese individu-
als jogging for 1.609 km.
As expected, increasing intensity over 1.609 km resulted
in significantly higher EE in both the normal weight and
overweight/obese women. The role of intensity, therefore,
appears important to consider when utilizing PA for weight
management. Jogging at 2.23 m s~! for 1.609 km equated
to approximately 40% more EE than walking at 1.34 m 5!
over the same distance in both groups of women. In the
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normal weight women, this equated to 113 kJ per 1.609 km
more during jogging than walking and in the overweight/
obese women 134 kJ per 1.609 km more during jogging
than walking. Hypothetically, if these women were to jog
16.09 km per week at 2.23 ms”! instead of walking
16.09 km per week at 1.34 m s”', the difference in EE
would be equivalent to 58,760 kJ per year or almost 2 kg of
body fat for the normal weight women and 69,680 КТ рег
year or 2+ kg of body fat for the overweight/obese women.
We recognize that some individuals have orthopedic
issues or other physical limitations that prevent jogging or
other high impact activities. Fortunately, recent scientific
evidence shows moderate-intensity walking to be associ-
ated with beneficial weight management outcomes in active
individuals (Mougios et al. 2006) as well as in those who
begin an exercise program (Williams and Thompson 2006).
Nevertheless, findings from the present study highlight the
potentially meaningful difference increasing intensity can
have on EE and potentially on body weight over time.
Thus, appropriately adding intensity is worth consideration
when prescribing or beginning an exercise program.
In the present study, economy of movement, typically
defined as the steady-state VO, needed to maintain a given
velocity of movement (Morgan et al. 1989), was not statis-
tically different between BMI groups after normalizing for
body mass (kg). There may be biomechanical and body
mass distribution differences between normal weight and
obese individuals that result in differences in EE (Browning
et al. 2006) and movement economy (Hulens et al. 2001).
- Further, increased recruitment of muscle fibers, increased
power output, high braking forces, and high mediolateral
forces have all been postulated as variables affecting econ-
omy that increase EE during exercise (Kyrolainen et al.
2001). As our study did not assess these variables, we are
unable determine their effect on economy of movement.
Nevertheless, the lack of statistical difference in economy
of movement was not surprising as all participants were
untrained. In addition, our participants were overweight or
class 1 obese. It is possible that more severely obese indi-
viduals would exhibit more distinct characteristics that
result in declining economy of movement compared to
overweight or normal weight individuals and would have
altered the results; however, this is speculative.
When comparing normal weight and overweight/obese
individuals for pedometer counts, there was no difference
while walking or jogging 1.609 km, but jogging resulted in
fewer counts than walking. This finding is in agreement
with other researchers {Welk et al. 2000) and is expected
since the increase in speed during the jog more than likely
elicited a longer stride length that resulted in fewer counts
over the 1.609-km trial. This study did not assess nor factor
in stride length when comparing jogging and walking trials
and this represents a limitation in the interpretation of the
Eur J Appl Physiol (2009) 106:675-682
681
results. However, height was used as an indirect measure of
stride length to determine its effect on pedometer counts
during the walk and jog. It is noteworthy that when ana-
lyzed by BMI group, height was significantly and indirectly
correlated with pedometer counts only in the overweight/
obese individuals during both the walk and jog trials. Inter-
pretation of this finding is difficult without stride length
data to determine if stride length or height is the more
important factor in this association. It has been suggested
that a more sensitive pedometer be used with overweight
and obese adults, such as a piezo-electric pedometer (Mel-
anson et al. 2004), since a spring-levered pedometer may be
affected by its tilt due to increased BMI and waist circum-
ference often seen in overweight and obese adults (Crouter
etal. 2005). Additionally, caution should be used with
spring-levered pedometers since some tend to be less accu-
rate at speeds faster than a brisk walk (Crouter et al. 2003).
Finally, many pedometer models have a function that
allows the user to input his or her stride length to estimate
distance walked. Whether or not this function is used, it is
important for the user to understand that fewer steps will be
taken while jogging compared to running and that this does
not necessarily translate to lower EE.
In summary, this study indicates that women with larger
body mass expend more energy at rest and during walking
and jogging. In addition to the public health guidelines to
regularly obtain moderate-intensity activity for health bene-
fits, progressively adding intensity may be a strategy to
increase EE and prevent small imbalances in energy intake.
While orthopedic considerations may exist for some
heavier individuals preventing intense or high impact tread-
mill exercise, increasing intensity using lower impact
modes should be considered. It is also noteworthy that
moderate-intensity walking may elicit significantly less EE
than the traditional 418 kJ (100 kcal) per 1.609 km (1 mile)
but this “rule of thumb” may more accurately quantify jog-
ging 1.609 km in some normal and overweight women.
Lastly, 2,000 steps may accurately predict 1.609 km
(1 mile) of walking but may significantly under-predict
steps during jogging or running activities and should be
considered when evaluating the health and weight manage-
ment benefits of attaining 10,000 steps per day.
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