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American Journal of Health Education

ISSN: 1932-5037 (Print) 2168-3751 (Online) Journal homepage: http://www.tandfonline.com/loi/ujhe20

Physical Activity and Self-efficacy in Physical Activity and Healthy Eating in an Urban Elementary Setting

Tracey D. Matthews, Elizabeth O'Neill, Kimberly T. Kostelis, Daniel Jaffe, Steven Vitti, Melissa Quinlan & Michelle Boland

To cite this article: Tracey D. Matthews, Elizabeth O'Neill, Kimberly T. Kostelis, Daniel Jaffe, Steven Vitti, Melissa Quinlan & Michelle Boland (2015) Physical Activity and Self-efficacy in Physical Activity and Healthy Eating in an Urban Elementary Setting, American Journal of Health Education, 46:3, 132-137, DOI: 10.1080/19325037.2015.1023476

To link to this article: http://dx.doi.org/10.1080/19325037.2015.1023476

Published online: 08 May 2015.

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Physical Activity and Self-efficacy in Physical Activity and Healthy Eating in an Urban Elementary Setting

Tracey D. Matthews and Elizabeth O’Neill Springfield College

Kimberly T. Kostelis Central Connecticut State University

Daniel Jaffe, Steven Vitti, Melissa Quinlan, and Michelle Boland Springfield College

Background: Identifying lifestyle factors such as physical activity (PA) patterns and eating

behaviors of children may be beneficial in implementing interventions in urban elementary

schools. Purpose: To examine PA levels and self-efficacy (SE) in PA and health eating (HE)

of third, fourth, and fifth graders in 3 low economic elementary schools in an urban setting.

Method: Students (N ¼ 295) were administered SE in PA and HE inventories and given Omron HJ7201TC pedometers. Results: Girls had significantly (P , .05) higher goal setting for healthy food choices (4.34 ^ 0.75) and decision making for healthy food choices

(3.85 ^ 0.89) than boys (goal setting: 4.11 ^ 0.87; decision making: 3.20 ^ 1.05). For step

counts per weekday (SWKD), boys (7354.88 ^ 2631.44 steps/day) had significantly

(P , .05) higher steps than girls (6273.87 ^ 2259.00 steps/day). Third and fifth graders (third: 7112.48 ^ 2564.13 steps/day; fifth: 7189.35 ^ 2470.57 steps/day) had significantly

(P , .05) higher steps than fourth graders (6172.21 ^ 2350.32 steps/day). For step counts per

weekend (SWKEND), no significant (P . .05) differences existed for gender (girls: 5732.38 ^ 3267.16 steps/day; boys: 6050.59 ^ 3564.21 steps/day) or grade level (third:

6486.23 ^ 3282.34 steps/day; fourth: 5605.74 ^ 3381.45 steps/day; fifth:

5617.51 ^ 3513.54 steps/day). A significant positive relationship was found for goal setting

for PA and SWKEND (r ¼ 20.178, P ¼ .033). In addition, significant relationships existed for transport questions, specifically, goal setting for PAwas positively related to the number of

times walking to school (r ¼ 0.142, P ¼ .036) and decision making for PA was negatively related to the number of times a student took the bus per week (r ¼ 20.139, P ¼ 0.33). Translation to Health Education Practice: An urban setting may influence the amount of

PA due to accessibility and opportunities to engage in PA.

BACKGROUND

Childhood lifestyle factors, such as a poor diet and physical

inactivity, have been recognizedas risk factorsfora multitude

of chronic health conditions that may have ramifications in

adulthood. 1 Both diet and physical activity are critical

components to the energy balance equation. Though

controversy may exist regarding which aspect plays a more

dominant role, proper management of both components can

assist one in achieving a healthy body weight and reduce the

onset of chronic diseases. 2 More recently, a lack of physical

activity associated with compromised health and well-being

has been termed exercise deficit disorder (EDD). 1 Only 42%

of children aged 6-11 years and 8% of adolescents (aged 12-

19 years) meet the current physical activity recommendations

by the Centers for Disease Control and Prevention for

Submitted October 3, 2014; accepted December 22, 2014.

Correspondence should be addressed to Tracey D. Matthews, School

Health, Physical Education, and Recreation, Springfield College, Wellness

108, 263 Alden Street, Springfield, MA 01109. E-mail: tmatthews

@springfieldcollege.edu

American Journal of Health Education, 46, 132–137, 2015

Copyright q SHAPE America

ISSN: 1932-5037 print/ 2168-3751 online

DOI: 10.1080/19325037.2015.1023476

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children to accrue daily a minimum of 60 minutes of

moderate to vigorous physical activity. 3,4

The prevailing concern regarding physical inactivity and

dietary behaviors of children is the increased risk for

obesity. Childhood obesity has the potential for devastating

health consequences. Obesity has been well established as a

risk factor for a wide array of chronic hypokinetic diseases

including coronary heart disease, type II diabetes,

hypertension, and certain cancers. Obese children are

twice as likely to be obese as adults compared to nonobese

children. 5 Thus, it is critical to examine factors such as

physical activity and perceived confidence to make

decisions about healthy eating and physical activity with

the elementary school population, which can provide

important information to aid in obesity prevention.

In addition, minority children are at a higher risk for

being overweight or obese. Racial and ethnic disparities do

exist for prevalence of obesity. There are significant racial

and ethnic disparities in obesity prevalence among U.S.

children and adolescents. From National Health and

Nutrition Examination Survey 2007-2008 data, Hispanic

boys were significantly more likely to be obese than non-

Hispanic white boys, and non-Hispanic black girls were

significantly more likely to be obese than non-Hispanic

white girls. 6 Previous research demonstrated that minority

girls obtained less steps/day than their Caucasian grade-

level counterparts. 7 Understanding activity patterns and

decision-making perceptions of children may help to

understand reasons why these disparities exist.

A multidisciplinary approach is most appropriate for

tackling EDD, including involvement of schools (physical

educators and health educators), community health

specialists, health care providers, and parents to identify

children who do not meet physical activity recommen-

dations. 1

Identifying children who do not meet such

recommendations is considered an important initial step in

the battle against EDD; however, just as important is

understanding why recommendations are not being met.

Exploring children’s efficacy toward physical activity and

healthy eating behaviors may provide additional infor-

mation that could assist with intervention strategies. Using

social cognitive theory (SCT), the behavior, environment,

and individual were examined in urban Latino fourth and

fifth graders. 8,9

Physical activity (PA) was measured using

acclerometers, and self-efficacy, outcome expectancy,

social support, and physical/social environmental factors

were measured as variables of SCT. Gao found that self-

efficacy and social support were positive predictors for PA. 9

In addition, Bean et al. examined SCT during a PA

intervention in elementary school girls. 10

They found that

self-efficacy and PA were improved after a PA intervention

and concluded that structured PA programs can aid in

improving self-efficacy in elementary school girls.

The current study collaborated with elementary school

physical education teachers in an urban setting to examine

physical activity levels through the use of pedometers. Step

counting using pedometers is widely accepted by research-

ers and practitioners for assessing physical activity and

establish comparisons of step counts per day by gender of

children 6-12 years. 11,12

Daily step counts of 15 000 for

males and 12 000 for females were optimal in relation to

physical activity levels to establish a healthy body weight. 13

Steps per day from previous researchers were reported from

children grades 5-7 as 12 513 steps/day on weekdays (boys

13 523 ^ 3815; girls 11 737 ^ 2997) and 8820 steps/day on

weekends (boys 9431 ^ 4934; girls 8389 ^ 3943). 11

Current research suggests that mode of transportation to

and from school influences step-defined physical activity in

youth, in which nonactive commuters (car or bus) had fewer

weekday steps than active commuters. 7,14

Active transport

to schools has been reduced. In 1969, approximately half of

elementary and middle school children in the United States

walked or biked to school. By 2009, only about 13% of this

same age group walked or biked to school. 15

Additionally,

activity rates are reportedly lower in at-risk children, which

can be defined as children who come from economically

challenged backgrounds and can include minority groups

and single-parent families. 16-18

Purpose

The purpose of the current study was to examine the PA

levels among urban children living in a low economic

setting, as well as efficacy toward physical activity and

eating habits.

METHODS

Participants and Setting

Participants (N ¼ 295) were third, fourth, and fifth graders at 3 elementary schools in Springfield, Massachusetts. The 3

elementary schools were identified as low economic

schools. Total enrollment for grades 3-5 at School A was

134 and 59 students participated in the study (44%). Total

enrollment for grades 3-5 at School B was 227 with 96

students participating in the study (42%). For School C,

there were 146 total students in grades 3 to 5 and 94 students

participated in the study (64%). Please refer to Tables 1 and

2 for demographic data for each school as well as data for

the district and state. Data were collected during the 2012-

2013 year.

Permission to collect data was received by the

Institutional Review Board at the first author’s institution

and the Assessment, Research and Accountability Office of

Springfield Public Schools. Parental permission was

obtained; letters were sent home with students written in

the first language (English, Spanish, or Vietnamese) of the

parents/guardians.

PHYSICAL ACTIVITY AND HEALTHY EATING 133

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Inventories and Instruments

The Physical Activity and Healthy Food Efficacy Scale for

Children (PAHFE) 19

was used to assess children’s goal-

setting and decision-making efficacy for physical activity

and healthy food choices. Construct validity evidence for

four subscales: Goal-Setting for Physical Activity (GSPA),

Goal Setting for Healthy Food Choices (GSHF), Decision

Making for Physical Activity (DMPA), and Decision

Making for Healthy Food Choices (DMHF) has been

established. 19

In addition, internal consistency ranged from

0.59 to 0.87 for the 4 subscales. 19

Data were collected that provided information on how

many days participants walked to school, took the bus,

brought their lunch, and ate school lunches and/or break-

fasts. OMRON HJ-720 ITC Pedometers (Omron Healthcare,

Lake Forest, IL) were used to assess PA. Omron HJ-720ITC

Pedometers display aerobic steps in minutes during aerobic

activity and total number of steps during the day. Advanced

Omron Health Management Software allows tracking of

daily, weekly, monthly, and yearly progress. Validity

evidence has been reported during treadmill use and over-

ground walking for the HJ-720ITC. 20,21

Procedures

Upon approval from the Institutional Review Board and

Assessment, Research and Accountability Office of the

Public School system, the principals and physical education

teachers at each school were contacted to receive

permission to collect data. Once approval was granted,

permission letters were sent home with each child in the

third, fourth, and fifth grades at each elementary school.

Permission slips were collected in each child’s physical

education class. Data collection occurred in physical

education classes for all students at all schools from

October 2012 to April 2013. School A’s data collection

period was from March to April 2013. School B’s data

collection was from January to February 2013, and school

C’s was from October 2012 to January 2013. For each grade

level, children take physical education biweekly.

In addition, for each grade level, there were 2 to 3

classrooms per grade level. At each school, we collected

data from one class in each grade level at a time. During the

first day of physical education for the week, students were

divided into 3 to 4 stations depending on class size. The first

station was used to complete the PAHFE and demographic

information. At the station, a researcher explained how to

fill out the inventory and stayed with students in the event

that they had any questions. At the second station,

pedometers were calibrated by having students walk 10

normal steps alongside a tape measure. The distance to walk

10 steps was recorded in inches and this information was

inputted into the assigned pedometer. Pedometers were

given to each student after calibration. Students were

instructed to wear the pedometer on the right side of their

body for 7 days. At the completion of 7 days, pedometers

were returned and data were downloaded from each

pedometer. Daily step counts were recorded per weekday

and per weekend from each student. Once one class at each

TABLE 1

Demographic Data by School—Percentage Enrollment by

Race/Ethnicitya

Race School A School B School C District State

African American 17.3 17.7 35.8 20.2 8.6

Asian 7.1 2.5 1.3 2.4 5.9

Hispanic 37.8 54.7 38.1 60.9 16.4

White 35.8 22.4 21.1 13.5 66.0

Multirace, non-Hispanic 2.0 2.5 3.7 2.8 2.7

a All data reported as percentages.

TABLE 2

School Profiles for Selected Populationsa

Title School A School B School C District State

First language not

English

7.9 21.8 6.4 26.1 17.3

English language learner 4.3 16.6 1.3 16.9 7.7

Low-income 78.0 83.0 85.6 87.5 37.0

Free lunch 70.1 78.4 81.9 82.5 32.1

Reduced lunch 7.9 4.6 3.7 5.0 4.9

a All data reported as percentages.

TABLE 3

Descriptive Statistics for Step Counts Per Weekday (N ¼ 243) and Weekend (N ¼ 162) Across Grade Levels

Step Counts Mean SD

Weekday

3rd Grade 7112.48 ^ 2564.13

4th Grade 6172.21* ^ 2350.32

5th Grade 7189.35 ^ 2470.57

Weekend

3rd Grade 6486.23 ^ 3282.34

4th Grade 5605.74 ^ 3381.45

5th Grade 5617.51 ^ 3513.54

*Significantly (p , .05) less steps than 3 rd and 5

th grade.

TABLE 4

Descriptive Statistics for Step Counts Per Weekday (N ¼ 243) and Weekend (N ¼ 162) Across Gender

Step Counts Mean SD

Weekday Total 6767.66 ^ 2490.68

Girls 6273.87 ^ 2259.00

Boys 7354.88* ^ 2631.44

Weekend Total 5875.77 ^ 3397.17

Girls 5732.38 ^ 3267.16

Boys 6050.59 ^ 3564.21

*Significantly (p , .05) greater than girls.

134 T. D. MATTHEWS ET AL.

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grade level had completed their 7 days, we collected data on

the next class and this continued until data collection was

complete at each school. As part of their physical education

classes, students were already exposed to wearing

pedometers before the start of the study. At each school,

students had worn pedometers as part of their physical

education class before. Therefore, an accommodation phase

was not included as part of the study.

Statistical Analysis

Differences among grade level (third, fourth, and fifth) and

gender were examined for weekday and weekend step

counts and subscale scores on the PAHFE. The subscales

included physical activity self-efficacy (SE) and healthy

eating SE. A total of two 2 £ 3 independent groups factorial analyses of variance were computed for weekday and

weekend step counts. The 2 independent variables included

gender (male and female) and grade level (third, fourth,

and fifth grade). For PAHFE subscale scores, a 2 £ 3 independent groups factorial multiple analysis of variance

was computed. Pearson’s product moment correlation

analyses were performed to examine the relationship

between PAHFE subscale scores and weekday and weekend

step counts. In addition, we examined the relationship

between PAHFE subscales, PA, and transport questions.

The number of times a student walked, took the bus, or was

driven by car to school was correlated with PAHFE

subscales and PA. All statistical analyses were conducted

using IBM-SPSS version 21. Alpha levels were set at

P ¼ .05.

RESULTS

Approximately 81% of the participants took the bus or were

brought by car 5 days per week, whereas only 12% walked

to school 5 days per week. Approximately 65% of

participants had school lunch at school 5 days per week

and 47% had the school breakfast. Initially, a total of 295

students participated in the study. The individual infor-

mation–centered approach was utilized to recover step

count missing data. 22 Only students with 2 or fewer missing

days were used to recover missing data for weekday steps

and students who had at least one weekend day were used to

recover missing data. In addition, only days in which

participants wore their pedometer for 6 or more hours were

included for analysis. Across grade level, a total of 243 data

points were used for weekday steps and 162 data points

were used for weekend steps. Step counts per weekday

(SWKD) and step counts per weekend (SWKEND) were

averaged.

No significant interaction (P . .05) existed for the subscales of the PAHFE for gender or grade level. There

was, however, a significant main effect for gender

(l ¼ 0.92, P ¼ .003). Univariate F tests were used to determine which subscales were significantly different for

gender. GSHF and DMHF were found to be significant, F(1,

194) ¼ 4.00, P ¼ .02; F(1, 194) ¼ 4.88, P ¼ .03. For both subscales, girls had higher subscales scores (GSHF:

4.34 ^ 0.75; DMHF: 3.85 ^ 0.89) than boys (GSHF:

4.11 ^ 0.87; DMHF: 3.20 ^ 1.05). No significant inter-

actions were found for SWKD or SWKEND step counts For

SWKD, boys (7354.88 ^ 2631.44 steps/day) had signifi-

cantly (P , .05) higher step counts than girls (6273.87 ^ 2259.00 steps/day). In addition, third and fifth

graders (third: 7112.48 ^ 2564.13 steps/day; fifth:

7189.35 ^ 2470.57 steps/day) had significantly (P , .05) higher step counts than fourth graders (6172.21 ^ 2350.32

steps/day). For SWKEND, no significant (P . .05) differences existed for gender (girls: 5732.38 ^ 3267.16

steps/day; boys: 6050.59 ^ 3564.21 steps/day) or grade

level (third: 6486.23 ^ 3282.34 steps/day; fourth:

5605.74 ^ 3381.45 steps/day; fifth: 5617.51 ^ 3513.54

steps/day). SWKEND step counts was significantly related

to GSPA (r ¼ 20.178, P ¼ .033). In terms of transport responses and PAHFE subscale scores, significant relation-

ships were found for number of times walking to school and

GSPA (r ¼ 0.142, P ¼ .036) and number of times taking the bus and DMPA (r ¼ 20.139, P ¼ .033). In addition, for the questions regarding food, the number of times bringing

lunch and GSHE were significantly related (r ¼ 20.149, P ¼ .030).

DISCUSSION

The current study examined the physical activity levels and

efficacy of physical activity and healthy eating of third,

fourth, and fifth graders from 3 urban elementary schools.

For the subscales on the PAHFE, differences were found

between boys and girls for the subscales for healthy eating.

For GSHF and DMHF, girls had higher self-efficacy scores

than boys. Differences in SWKD steps existed among grade

level and gender. Boys had higher step counts than girls and

third and fifth graders had higher step counts than fourth

graders. SWKD and SWKEND were less than reported by

previous researchers. 14 Average weekday and weekend step

counts for the participants were below the average values

reported from previous studies with similar age groups 21,23

and recommended levels for boys (15 000/day) and girls (12

000/day). 12

Lower average step counts may be linked to

more time spent in sedentary behavior. 11

In addition,

relationships among PAHFE subscales and PA as well as

PAHFE subscales and transport data were examined.

A relationship was found for SWKEND steps and GSPA.

As GSPA scores increased, the number of steps on the

weekend decreased. For transport data, relationships were

found for GSPA and number of times walking to school.

As the number of times a child walked to school increased,

PHYSICAL ACTIVITY AND HEALTHY EATING 135

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so did the scores for GSPA, indicating greater self-efficacy

in children with more times they walked to school per week.

DMPA was found to negatively relate to the number of

times a child took the bus. Therefore, students who had

higher DMPA scores regarding how sure they can be to be

physically active was related to fewer times per week taking

the bus. Finally, GSHF was found to negatively relate to the

number of times students brought their lunch. The higher

the goal-setting score, the fewer number of times a student

brought his or he lunch. One should approach these

significant relationships with caution, however. Given the

number of correlations that were run (20) and the relatively

low correlations found, one may assume that this was due to

the sample size and may not be meaningful. 24

Though SE has been found to improve with higher PA,

this was not the case in the present study. 9,10

Gao utilized

accelerometers and, like this study, examined PA for

7 days. 9 Only Latino schoolchildren were studied. For the

current study, ethnicity was not collected by each

participant. Examining differences among ethnic groups

may be a more accurate way to examine PA patterns in

children. Bean et al. also found improved SE among African

American girls; however, their study utilized a self-report

of PA, namely the Youth Risk Behavior Survey. 10,25

The

self-report data may have been influenced by social

desirability bias.

The current study determined that only 12% of the

participants walked to school 5 days per week, which may

explain, in part, the lower average step counts. Minority

youth who actively commute are more likely to meet

physical activity recommendations than nonactive commu-

ters. 7 Youth who actively commuted to school were found

to average 1700 to 2300 more steps/day. 26

Total steps per

day may influence body composition (percentage body fat,

body mass index, and waist circumference), systolic blood

pressure, and VO2 max. 27,28

Even when accounting for the potential reduction in steps

per day due to transportation mode, the sample studied still

had substantially lower step counts. Additional contributing

factors may be climate during the data collection periods

and the physical environment of the schools. As noted

earlier, data were collected in the northeast region during

the months of October–April during the 2012-2103 school

year. Typically colder temperatures during these months

may have been a factor. Lower average step counts may also

be attributed in part to the urban setting, in which low levels

of step-defined physical activity (,5000 steps/day) is linked to a lower household income.

11 The Centers for

Disease Control and Prevention identifies physical environ-

ment as a potential factor reducing the likelihood that

physical activity guidelines will be met. 3 The lack of safe

locations for activity, parents’ perceptions of environment

safety, and lack of equipment were identified as barriers to

physical activity, which are often a concern with urban

environments. Additionally, the cost associated with

physical activities may account for low step counts in the

current study. On average, 82% of the students at the

elementary schools were from low-income families.

Though we did not specifically examine the physical

environment of the specific school locations, one may infer

that given the urban and low economic environment that

these children lived in that these barriers may play a role in

the lack of physical activity. The low physical activity

trends observed in this urban population stress the

importance of continued research in urban schools to help

fully understand the barriers involved with such negative

health conditions.

Though the information that was gleaned from this study

is telling, there were a number of limitations. Firstly, body

mass index data were not collected because 2 of the 3

schools did not agree to access the student data on height

and weight. Having body mass index data of the children

may have provided further evidence of the relationship of

PA and body composition in at-risk youth. Based on the

inactivity of our participants, we can only speculate that

these children are also at a higher risk for being identified

as being obese. Secondly, though children were very

compliant with wearing pedometers for 7 days, some data

were not usable because students did not wear their

pedometers long enough to meet the threshold of usable data

(at least 6 hours), especially for weekend steps. Finding

ways in which to remind or encourage students to wear the

pedometers for the requested time period is suggested.

TRANSLATION TO HEALTH EDUCATION PRACTICE

Step-defined physical activity using pedometers may be an

effective manner to determine lifestyle habits during

childhood, which may influence eating habits and physical

activity in adulthood. Low-income households, an urban

setting, and environmental factors may impact upon

attaining physical activity requirements. Mode of commut-

ing to school for youth and school-supplied meals may be

barriers to attaining physical activity recommendations and

avenues for intervention. Continued research in identifying

less active populations, environmental barriers, and

attitudes toward behaviors will dictate prevention measures

needed to impact upon the childhood obesity epidemic. The

low physical activity observed in this study underlines the

importance of continued research in urban schools to help

fully understand the factors involved with such negative

health conditions.

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