EFFECTS OF OBESITY ON SYMMETRY AND SPATIO-TEMPORAL CHARACTERISTICS OF ADOLESCENT GAIT

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Effects of overweight and obesity on walkingcharacteristics in adolescents

Janet S. Dufek a,⇑, Rayland L. Currie a,1, Philana-Lee Gouws a,1, Lori Candela b,2,Antonio P. Gutierrez b,2, John A. Mercer a,1, LeAnn G. Putney c,3

aBiomechanics Laboratory, Department of Kinesiology and Nutrition Sciences, 4505 South Maryland Parkway, Box 3034,

University of Nevada, Las Vegas, Las Vegas, NV 89154-3034, United StatesbDepartment of Psychosocial Nursing, 4505 South Maryland Parkway, Box 3018, University of Nevada, Las Vegas, Las Vegas,

NV 89154-3018, United StatescDepartment of Educational Psychology, 4505 South Maryland Parkway, Box 3303, University of Nevada, Las Vegas, Las Vegas,

NV 89154-3303, United States

a r t i c l e i n f o

Article history:

Available online 9 December 2011

PsychINFO classification:

2330

Keywords:

Body mass index

Children

Gait

Locomotion

Spatio-temporal parameters

a b s t r a c t

Child and adolescent obesity is growing at a staggering rate. Associ-

ated potential health risks have been acknowledged in the adult

population, and similar concerns have been raised for children and

adolescents. However, distinguishing locomotor characteristics

related to obesity have yet to be clearly identified for adolescents.

The aimsof the studywere to examine the effects ofwalking velocity

and gender on spatio-temporal characteristics of gait between nor-

mal weight (NW) and overweight and obese (OWO) adolescents. In

addition,we sought to identify characteristics of gait that are related

to bodymass index percentile (BMI%). Adolescent students in grades

7–10 (N = 111) from a charter school participated in the study. All

participants walked at two speeds (preferred, fast) over an instru-

mented walkway (120 Hz). Spatio-temporal characteristics of gait

were extracted from four walkway passes and evaluated. Results

identified significant (p < .05) differences in velocity, percent double

support, percent swing phase, and stance width between groups.

Only stance width was different (p < .05) between genders. Models

to predict BMI% from kinematicwalking parameters were ofmoder-

ate strength (averaging 43.5% explained variance) and were gener-

ally stronger for females versus males. Percent double support was

the primary predictor variable of BMI% across speed and gender. It

0167-9457/$ - see front matter � 2011 Elsevier B.V. All rights reserved.

doi:10.1016/j.humov.2011.10.003

⇑ Corresponding author. Tel.: +1 702 895 0702.

E-mail address: [email protected] (J.S. Dufek).1 Tel.: +1 702 895 0702.2 Tel.: +1 702 895 2443.3 Tel.: +1 702 895 4879.

Human Movement Science 31 (2012) 897–906

Contents lists available at SciVerse ScienceDirect

Human Movement Science

journal homepage: www.elsevier .com/locate/humov


is suggested that OWO adolescents may be challenged with control

of movement of the center of mass during the support phase of

walking.

� 2011 Elsevier B.V. All rights reserved.

1. Introduction

Pediatric obesity is emerging as a 21st century global epidemic. It is currently estimated that 155

million children worldwide, or 1 out of 10, are obese or overweight (Aschemeier, Lange, Kordonouri, &

Danne, 2008). In the United States, childhood obesity has tripled in the last 20 years with 1 in 5 chil-

dren now considered overweight (Daniels et al., 2005; Dehghan, Akhtar-Danesh, & Merchant, 2005;

Whitaker, Davis, & Lauer, 2004). Ethnicity also appears to influence child obesity statistics with the

greatest number of overweight and obese children found disproportionately among Native American,

African American, and Hispanic populations (Caprio et al., 2008). In addition, up to 70% of obese chil-

dren mature to become obese adults (Dehghan et al., 2005). Furthermore, other obesity-related health

concerns include type 2 diabetes, cardiovascular disease, and respiratory challenges (Lawrence &

Kopelman, 2004), while the combination of adulthood and obesity has also been shown to be strongly

associated with the onset of bilateral knee joint osteoarthritis (Anderson & Felson, 1988; Stürmer,

Günther, & Brenner, 2000).

In adults, reported effects of obesity on gait characteristics and potential joint pathology have been

equivocal. Devita and Hortobágyi (2003) reported greater knee and ankle joint moments for obese par-

ticipants walking at a standard speed (1.50 m/s) versus a preferred speed (1.29 m/s). Despite the dif-

ferences in body mass and assumed increases in joint loads for obese individuals, hip and knee joint

moments were not different for obese versus non-obese adults at the matched walking speed. In con-

trast, Browning and Kram (2007) identified peak extensor knee moments to be 51% greater in obese

versus non-obese adults walking at 1.50 m/s. Of note is the fact that as walking speed decreased,

the magnitude of the joint moment differences between groups became less and were eventually

non-existent, suggesting obese individuals can modulate joint loads by self-selecting walking speed.

The contrasting joint kinetic profiles between groups were previously suggested by Devita and

Hortobágyi (2003) to be the result of altered kinematics observed for the obese subjects. This finding

was subsequently suggested to be a conscious effort to increase dynamic balance to reduce knee joint

loads (Wearing, Hennig, Byrne, Steele, & Hills, 2006).

However, Browning and Kram (2007) identified no differences in kinematics; alternatively, their

results showed increased ground reaction forces leading to increased joint kinetics for obese adults.

Malatesta et al. (2009) extended this body of work to examine mechanical work optimization for

obese adults walking at a preferred speed. The authors reported greater external mechanical work

for obese versus normal weight individuals, attributable to the mass differential. Furthermore, results

did not suggest that obese adults modify kinematics to improve energy transfer, but rather choose a

slower walking speed to minimize mechanical work associated with walking.

It is not known if obese children display similar kinematic or kinetic profiles as obese adults, and as

such, locomotor characteristics of obese children are now receiving research attention. Hills and

Parker (1992) examined kinematic differences between obese (n = 10) and normal weight (n = 4) chil-

dren and found lesser velocities, increased instability, and limb asymmetry for obese children across

their small study sample. McMillan, Auman, Collier, and Williams (2009) reported that overweight

boys (n = 7) displayed greater knee valgus and hip adduction during support than healthy weight boys

(n = 7), and suggested such frontal plane excursions in the overweight individuals will lead to lower

extremity injuries and performance deviations. Paralleling the queries into walking speed reported

for obese adults, Shultz, Sitler, Tierney, and Hillstrom (2009) reported no kinematic differences during

stance or swing between normal weight (n = 10) and overweight (n = 10) children with selected differ-

ences identified across walking speed. Lower extremity joint moment values were greater in the over-

weight group, with no differences in percent increase with increased walking speed. In contrast,

898 J.S. Dufek et al. / Human Movement Science 31 (2012) 897–906


McMillan, Pulver, Collier, and Williams (2010) did find differences in velocity-matched healthy weight

(n = 18) and obese (n = 18) adolescents, suggesting that obese participants adopted a kinematic strat-

egy to minimize hip and knee joint moments.

The effects of gender on performance of locomotor skills in children have resulted in equivocal

findings. Haubenstricker, Wisner, Seefeldt, and Branta (1997) identified differences in running perfor-

mance between boys and girls. In contrast, Barnett, Beurden, Morgan, Brooks, and Beard (2010) found

no gender differences in locomotor skills in adolescents. It has been suggested that locomotor skill

development may be more directly related to other factors, including weight (Oakley, Booth, & Chey,

2004). Peyrot et al. (2010) reported no gender differences in obese adolescents before a weight loss

program for a small sample (n = 16), yet little data exists examining gender differences and adiposity

relative to potential differences in developed locomotor skills, including walking, for adolescents for a

larger sample size. It is also unknown if there are gender differences relative to walking performance

relative to body composition for this age group.

While the potential health challenges related to obesity are recognized (Lawrence & Kopelman,

2004), there are conflicting bodies of evidence being presented in the literature relative to obesity

and locomotion. Such results are likely influenced by experimental protocols, measurement proce-

dures, data reduction techniques, participant selection and study sample size. We sought to address

some of these potential limitations and possible sources of conflicting information by identifying a

large sample of ethnically diverse children who would participate in the study by virtue of the aca-

demic curriculum offered at their school versus selection or voluntary participation. We also sought

to explore potential relationships between gender and obesity relative to adolescent gait.

Therefore, the specific aims of the study were to: (1) evaluate spatio-temporal characteristics of

locomotion between normal weight (NW) and overweight and obese (OWO) adolescents walking at

different speeds, (2) evaluate spatio-temporal characteristics of locomotion between NW and OWO

adolescents across gender walking at different speeds, and (3) predict body mass index percentile

(BMI%) from spatio-temporal locomotion characteristics of adolescents. The significance of achieving

the study aims includes understanding the potential long-term effects of overweight/obesity for ado-

lescents as they move into adulthood, with an eye toward long-term overuse injury prevention. We

hypothesized that adiposity and walking speed would influence spatio-temporal parameters of gait;

however, there would be no gender-adiposity effects. We further hypothesized that spatio-temporal

parameters of gait would strongly predict level of adiposity for adolescents.

2. Methods

2.1. Participants

The entire body of students (N = 154) enrolled in grades 7–10 inclusive at an ethnically diverse

charter school participated in data collection as a part of the curriculum at the school. Of this group,

institutionally approved parental permission and child assent were obtained from 111 participants,

constituting the entire study sample. Participants were between the ages of 12 to 17 years

(14.2 ± 1.4 yrs) and enrolled in grades 7 (15 male, 15 female), 8 (21 male, 15 female), 9 (13 male, 9

female) and 10 (15 male, 8 female). The self-reported ethnicity of this study sample is presented

graphically in Fig. 1.

2.2. Data acquisition

All children performed walking gait assessment as part of a special curricular program (instruc-

tional modules focusing on a modification to the Diabetes Prevention Program). During a regularly

scheduled academic physical activity period, height recorded to the nearest 1/8 inch (0.32 cm) and

weight recorded to the nearest 1/4 pound (1.1 N) of each participant was obtained in a private screen-

ing room. A trained registered nurse conducted all anthropometric measurement sessions using a dig-

ital medical beam scale (HealthOMeter, 500 KL).

J.S. Dufek et al. / Human Movement Science 31 (2012) 897–906 899


Each participant then walked twice at their preferred pace over a 4.27 m instrumented walkway

(CIR Systems, Haverhill, PA; 120 Hz), which was centered in a 10 m hallway. Reliability of the walkway

system (GAITRite) has been shown to be high to excellent (ICC(1,1) = .73 to .95) when used to evaluate

a clinical population (Sorsdahl, Moe-Nilssen, & Strand, 2008). The walkway had an imperceptible

thickness of 4 mm which created no perturbation in the case where one’s foot made only partial con-

tact with the mat. All participants started at the same position, walked through the hallway (over the

walkway), stopped, turned around, and walked back to the start position. This was followed by two

trials over the walkway at a fast pace, after receiving the following verbal instruction: ‘‘Walk as fast

as you can.’’ There was no attempt to control footwear, velocity, or attire that the children wore while

walking in order to more closely replicate typical movement patterns. A minimum of one full walking

stride was completed before and after contact with the walkway to minimize the effects of initial

acceleration and terminal deceleration.

2.3. Data reduction

Body mass index (BMI) was calculated for each participant based upon height, weight, age, and

gender, following the procedures established by the Centers for Disease Control and Prevention

(CDC & Prevention, 2009). Participants were then grouped (post-hoc) based upon their BMI percentile

(BMI%), again following the recommendations of the CDC which has established <85th percentile as

not overweight or obese, P85th percentile as overweight, and P95th percentile as obese. All partic-

ipants with BMI% <85th percentile were assigned to the NW group (n = 56) and those with BMI%

P85th percentile were assigned to the OWO group (n = 55).

Custom walkway software (GAITRite, version 4.0, 59) was used to visually inspect each walking

trial performed for completeness. If any part of initial or terminal foot contact was not complete

(the entire foot did not contact the walkway), that step was eliminated from the walking trial. This

process resulted in a variable number of steps for each participant-condition-trial that was influenced

by foot placement on the walkway and walking velocity. The range of steps was between 4 and 7

across all trials and participants. The two walking trials at each speed were then concatenated, result-

ing in 8–14 steps (4–7 complete strides) of data per participant-speed.

All spatio-temporal measurements describing walking were extracted from the walkway data

using custom walkway software, and selected variables were identified for subsequent analysis. Four

specific dependent variables, identified relative to previous literature findings, (velocity, Vel; swing

Fig. 1. Ethnicity of study participants as self-reported. Note: Af-Am = African American, As-Am = Asian American, Cauc = Cau-

casian, Hisp = Hispanic, DNR = did not report.



phase percent of cycle, SW%; double support percent of cycle, DS%; heel to heel stance width, StW)

were selected to address Aims 1 and 2, while 14 measures were identified as independent variables

for the predictive portion, Aim 3, of the study. Bilateral descriptors were retained for the predictive

portion of the analysis owing to reported relationships between gait asymmetry and obesity (Hills

& Parker, 1992). Variables used for the respective analyses are specified in Table 1.

2.4. Statistical analysis

An independent t-test was used to test BMI% between groups (NW vs OWO) to determine whether

group membership was unique. Two-way mixed model Group � Speed analyses of variance (ANO-

VAs), with speed as the repeated factor, were used to address study Aim 1. Group � Gender at levels

of Speed ANOVAs were used to address Aim 2. All analyses were conducted for each of the four depen-

dent variables (Table 1). Level of significance was set at a = .05.

A stepwise multiple regression procedure was used to predict BMI% from a 14-independent vari-

able set (Table 1). Variable entry was set at a = .15 with the overall model significance set at

a = .05. This approach of liberal variable entry with stringent overall model significance has been

shown to address the potential confounding multicollinearity issue that can arise from related inde-

pendent variables (Dufek & Bates, 1992; Dufek, Mercer, & Griffin, 2009) and eliminates the need of

arbitrary selection between potentially related variables. Three prediction model procedures were

conducted: (1) by speed, (2) by gender, and (3) by gender at levels of speed. All statistical analyses

were conducted using Statistical Analysis Software (Version 9.1; SAS Institute, Inc., Cary, NC).

3. Results

3.1. Participant grouping

Results of the post hoc participant grouping based uponBMI% resulted in 56members in theNWgroup

(14.7 ± 1.5 yrs; 51.2 ± 9.4 kg; 159.6 ± 10.2 cm) and 55 members in the OWO group (14.9 ± 1.2 yrs;

79.8 ± 17.7 kg; 164.8 ± 8.2 cm). There was a significant difference between groups (t(109) =�13.83,

p < .001) for BMI% with the NW average (57.9%) less than OWO average (95.5%). There was a near equal

Table 1

Variables by study aims.

Dependent/independent variable Text abbreviation

Study Aims 1 and 2

Velocity (m/s) Vel

Stance width (cm) StW

Double support (% gait cycle) DS%

Swing phase (% gait cycle) SW%

Study Aim 3

Left step time (s) LStp

Right step time (s) RStp

Left step length (cm) LStL

Right step length (cm) RStL

Stride length (cm) SL

Stance width (cm) StW

Left swing (% gait cycle) LSW%

Right swing (% gait cycle) RSW%

Left stance (% gait cycle) LSt%

Right stance (% gait cycle) RSt%

Left single support (% gait cycle) LSS%

Right single support (% gait cycle) RSS%

Left double support (% gait cycle) LDS%

Right double support (% gait cycle) RDS%



proportion of group membership by gender for the NW (male = 33, female = 23) and OWO (male = 31,

female = 24) groups.

3.2. Effects of overweight–obesity and speed (Aim 1)

Descriptive results for both groups at levels of speed are presented in Table 2.

The Group � Speed ANOVA results identified a significant, F(1,104) = 4.65, p = .0334, ordinal inter-

action for SW%, with both groups demonstrating increased SW% with increased speed. There were no

significant Group � Speed interactions observed for Vel (p = .2567), DS% (p = .0565), or StW (p = .2051).

As anticipated per study design, a significant speed effect was observed for Vel (F(1,104) = 629.2,

p < .0001), DS% (F(1,104) = 273.4, p < .0001), and SW% (F(1,104) = 239.7, p < .0001). There was no sig-

nificant speed effect for StW (p = .3467). Velocity was 0.37 m/s greater for fast versus preferred speeds,

while DS% was 3.3% longer during preferred speed walking and SW% was 1.7% longer during fast speed

walking. There was a significant group difference for Vel (F(1,104) = 4.55, p = .0352), DS% (F(1,104) =

59.13, p < .0001), SW% (F(1,104) = 20.49, p < .0001), and StW (F(1,104) = 20.49, p < .0001). Walking Vel

was 0.07 m/s faster and SW% 2.1% longer for NW, while DS% was 4.2% longer and StW 0.025 m greater

for OWO.

3.3. Effects of overweight–obesity and gender (Aim 2)

Descriptive results for both groups at levels gender arepresented in Table 2. Therewereno significant

Group � Gender interactions observed for any of the dependent variables (p > .05). The only gender dif-

ference identifiedwas a significantly greater StW formales,with an average difference = 0.25 cm.Group

differences reflected results presented for Aim 1, with all variables significantly different between NW

and OWO.

Table 2

Mean and standard deviation values for Aims 1 and 2.

NW OWO Total

Female Male Female Male NW OWO

(n = 23) (n = 33) (n = 24) (n = 31) (n = 56) (n = 55)

Pref.

Vel (m/s) 1.28 1.25 1.18 1.17⁄ 1.25⁄ 1.17#

sd 0.15 0.19 0.16 0.16 0.17 0.16

DS% 22.71 23.34 27.37 27.95⁄ 23.80⁄ 8.03#

sd 2.43 3.25 3.50 2.51 3.13 3.19

SW% 38.57 38.48 36.37 36.00⁄ 38.16⁄ 35.96�#

sd 1.31 1.75 2.06 1.35 1.71 1.74

StW (cm) 7.73 8.40^ 10.14 11.54^⁄ 8.59⁄ 11.09

sd 3.40 2.67 2.85 4.10 3.35 2.99

Fast

Vel (m/s) 1.57 1.64 1.53 1.57 1.60⁄ 1.55#

sd 0.17 0.24 0.20 0.22 0.21 0.21

DS% 20.28 20.16 23.86 24.02⁄ 20.69⁄ 24.47#

sd 2.43 3.28 3.78 3.07 2.99 3.54

SW% 40.03 39.88 38.09 38.11⁄ 39.71⁄ 37.82�#

sd 1.23 1.66 2.03 1.85 1.61 1.91

StW (cm) 8.15 8.75^ 10.20 11.21^⁄ 8.80⁄ 11.08

sd 2.87 2.59 3.28 3.47 2.94 3.32

Note: sd = standard deviation; a = .05; � = significant Group � Speed interaction; # = significant speed main effect; � = signifi-

cant group main effect; ^ = significant gender main effect; Vel = velocity; DS% = double support percent of cycle; SW% = swing

phase percent of cycle; StW = heel to heel stance width.



Table 3

Summary of prediction of BMI% by speed, gender and gender at levels of speed.

Independent variable Explained variance Graphic representation

By speed: preferred

RDS% 41.6

RStL 4.8

StW 2.3

Total EV 48.7

By speed: fast

RDS% 26.9

LStp 3.7

SL 4.5

Total EV 35.1

By gender: female

RDS% 28.4

SL 10.7

RStp 4.6

Total EV 43.7

By gender: male

LSW% 30.7

SL 5.8

StW 2.8

LDS% 2.6

LStp 2.5

Total EV 44.4

By speed and gender: preferred – female

RDS% 40.8

LDS% 11.1

LStp 4.4

Total EV 56.3

By speed and gender: preferred – male

RDS% 26.3

Total EV 26.3

By speed and gender: fast – female

LSt% 46.2

StW 3.4

RSt% 2.2

RStL 4.3

Total EV 56.1

By speed and gender: fast – male

RDS% 27.3

LStp 4.8

SL 5.1

Total EV 37.2

Note: Refer to Table 1 for variable abbreviations.



3.4. Predictors of BMI% (Aim 3)

Prediction of the continuous measure of BMI% from spatio-temporal characteristics of walking pro-

duced models of weak to moderate strength ranging from 26.3% to 56.3% explained variance (EV)

across all models. The prediction results are summarized in Table 3 by variable contribution at each

level of contrast. The strongest models (averaging 56.2% EV) were exhibited for females by speed, with

DS% being the primary distinguishing characteristic across all models (Table 3).

4. Discussion

The overall purpose of the study, under which the three specific aims fell, was to examine the ef-

fects that conditions of overweight and obesity have on gait characteristics of adolescents. This broad

purpose was examined using a variety of approaches in order to more thoroughly expose any relation-

ships that may exist. As well, the study was carried out using a large number of participants. A post hoc

power analysis indicated statistical power values ranging from 87.7% to 99.9% for the dependent vari-

ables assessed in Aims 1 and 2. It is also important to note that while national statistics suggest that

20% to 36% of children in the U.S. are OWO (Daniels et al., 2005; Dehghan et al., 2005; Whitaker et al.,

2004), the present study sample consisted of nearly 50% membership in the OWO group.

McMillan et al. (2010) performed a kinematic analysis of walking for the same age range popula-

tion (12–17 yrs) as in the current study. Due to protocol differences including matching participants in

healthy weight and obese groups based upon preferred walking velocity, direct study comparisons

cannot be made. As a result of reported differences in sagittal and frontal plane lower extremity kine-

matics and kinetics between groups, the researchers suggested that muscle weakness may be a cause

of observed differences. The present study results, which identified longer DS% time for OWO, may be

due to the inability of these individuals to control and accelerate the center of mass over the base of

support during the stance phase, perhaps due to lack of strength (Granacher, Gollhofer, & Kriemler,

2010). Such conjecture deserves further research attention.

In contrast, Peyrot et al. (2010) found few differences in spatio-temporal characteristics of walking

for obese adolescents following a weight loss program. Their protocol was unique in that each partic-

ipant served as their own baseline/control. It is likely that inherent movement patterns would require

some time, likely greater than the 12 week period of assessment in this study, to effect change in gross

locomotor function. Despite this limitation, significant differences in stride length were observed. Sin-

gle support (%) did not change, and DS% was not reported.

While not specifically focusing on obesity, Granacher et al. (2010) reported that balance training

significantly improved postural control and performance in jump height and leg extensor force devel-

opment rate (implied lower extremity strength improvement) in adolescents. The particular focus of

this work was on potential to reduce lower extremity injury prevalence, which is also an objective in

obesity prevention. Whether balance training is appropriate to reduce DS% time during normal walk-

ing for OWO adolescents, with the intent of reducing long-term injury potential, is not known. Exam-

ination of center of pressure patterns as a measure of dynamic balance and determination of

differences between NW and OWO individuals may provide insight into any possible potential bene-

fits that balance training might provide for OWO adolescents.

Due to the unbalanced gender demographics in the McMillan et al. (2010) study, the researchers

were unable to assess gender differences; however, it was suggested that future studies explore this

factor. The present study consisted of 47 females and 64 males. Of these, 24 females and 31 males

were members of the OWO group. The only gender difference observed between NW and OWO was

StW, with males exhibiting slightly greater (2.5 cm) values. This result may be attributable to the fact

that the males were larger physically (height: 1.65 ± 0.09 m, mass: 67.1 ± 19.5 kg) than the females

(height: 1.57 ± 0.07 m, mass: 62.6 ± 20.7 kg). Confounding this outcome was the observed gender dif-

ference in prediction of BMI% with stronger models generated for females versus males. This outcome

may suggest that males produced a less consistent walking pattern than females, indicating that there

may be a gender difference in walking characteristics of adolescents in general, without regard for adi-

posity. Gender differences may also become more pronounced with maturation as this population is



growing to the status of young adults. The 5-year age range among participants (12–17 yrs) resulted in

a wide range of physical maturation among participants, allowing only speculation as to this

argument.

The prediction portion of this study was conducted in an attempt to identify any common locomo-

tor characteristics that may be related to increased BMI%. Results consistently identified longer DS% as

being both a salient characteristic of OWO gait as well a strong predictive measure of BMI%. Increasing

DS% may be a compensatory adaptation displayed by OWO adolescents to control inertial character-

istics of adipose tissue as it is moved over the base of support during stance. We suggest this may also

be an adaptive strategy to reduce joint loads as increased DS% is accompanied by a shorter period of

single support during walking. In addition, preferred speed walking produced a stronger predictive

model than fast walking, perhaps because OWO individuals tend to adopt a slower walking velocity.

Browning and Kram (2007) found that joint loads became similar between normal weight and obese

adults when participants were allowed to self-select walking speed. Perhaps OWO adolescents seek to

accomplish this same outcome by maximizing DS%. As an extension of this idea, perhaps OWO ado-

lescents who seek to lose weight through activity including walking should be coached not to focus

on walking faster, but rather to walk longer, thus minimizing acute lower extremity joint loading.

The school setting in which data were obtained for this study provided a familiar environment for

the adolescent participants. At the same time, the non-laboratory setting limited the scope of data

which could be obtained. Given the differences observed in the present study, it would be helpful

to add to this base of information in the form of joint kinetics and/or three dimensional gait analysis

to better understand why OWO adolescents walk differently than their NW peers. Furthermore, such

analyses may provide insight as to the potential long-term health risks associated with adolescent

obesity and locomotion.

5. Conclusion

Child obesity is recognized as an important issue with potential long-term health implications, and

therefore, activity is typically encouraged to reduce BMI in OWO individuals. The biomechanical

implications of obesity on activities including walking have received some attention in the adult pop-

ulation. However, less is known about any relationships between OWO in adolescents and locomotor

characteristics. Results of this investigation have identified differences in walking Vel, DS%, SW%, and

StW for OWO adolescents versus their NW peers, with DS% being most highly predictive of BMI%. A

possibility that such differences in walking patterns at a young age may precipitate to lower extremity

joint dysfunction in adulthood deserves research attention.

Acknowledgments

Funding provided by a University of Nevada, Las Vegas School of Nursing/School of Allied Health

Sciences Obesity-RelatedAward. The study sponsor had no role in the conception or completion of this

research. The authors wish to thank Mr. Jeff Kurrus for his editorial comments during manuscript

preparation.

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EFFECTS OF OBESITY ON SYMMETRY AND SPATIO-TEMPORAL CHARACTERISTICS OF ADOLESCENT GAIT

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