Current Urban Studies
2013. Vol.1, No.4, 166-170
Published Online December 2013 in SciRes (
Open Access
Corner Store and Commuting Patterns of Low-Income,
Urban Elementary School Students
Stephanie S. Vander Veur1, Sandy B. Sherman2, Michelle R. Lent1, Tara A. McCoy1,
Alexis C. Wojtanowski1, Brianna A. Sandoval2, Allison Karpyn2, Gary D. Foster1
1Center for Obesity Research and Education, Temple University, Philadelphia, USA
2The Food Trust, Philadelphia, USA
Received October 14th, 2013; revised November 15th, 2013; accepted November 25th, 2013
Copyright © 2013 Stephanie S. Vander Veur et al. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Background: While there has been considerable focus on the school environment in the context of
childhood obesity, less is known about the environments around the school, particularly in low-income,
urban neighborhoods. Purpose: The purpose of this study was to assess students’ corner store and com-
muting habits before and after school in a low-income, urban environment. Design: This was a
cross-sectional study. Setting/Participants: Participants were 702 4th - 6th graders from 10 K-8 public
schools where 82.1% ± 7.4% of children qualified for free or reduce-priced meals. Methods: Participants
were surveyed about their corner store and commuting habits using a questionnaire. Body mass index was
assessed using measured weight and height, and student’s demographic information was self-reported.
Results: The majority of 4th - 6th grade urban students shopped in corners stores either in the morning
(57.4%) or in the afternoon (58.5%). Nearly half (44.8%) reported shopping and purchasing in both the
morning and the afternoon. Children reported spending approximately $2.00 per corner store visit. Ap-
proximately two-thirds of children reported that they walked to or from school. Children who walked to
school frequented corner stores more than those using other commuting methods. Relative weight status
was not related to corner store or commuting patterns. Conclusion: Many low-income children purchase
food at corner stores before and/or after school making corner stores an important target for public health
nutrition. While many children walk to school, those are more likely to frequent corner stores. Neither
corner store nor commuting pattern was associated with relative weight.
Keywords: Corner Stores; Children; Obesity; Commuting
Nearly a third of children and adolescents in the United
States are at least overweight, and 16.3% are obese (Ogden,
Carroll et al., 2012). Minority and low-income children are dis-
proportionately impacted by obesity (Kaufman, Hirst et al.,
2009; Ogden, Carroll et al., 2012). Childhood obesity often
contributes to the development of metabolic (Freedman, Mei et
al., 2007; Kohler & van den Heuvel 2008; Singh, Foster et al.,
2012) and psychosocial consequences (Puhl, Luedicke et al.,
Schools are often a setting to implement nutrition-based pe-
diatric obesity prevention programs. However, the efficacy of
school-based childhood obesity prevention programs remains
mixed (Ford, Vander Veur et al., 2007; Foster, Sherman et al.,
2008; Katz, O’Connell et al., 2008; Foster, Linder et al., 2010;
Waters, de Silva-Sanigorski et al., 2011; Johnson, Weed et al.,
2012). School-based prevention programs may be compromised
by the local environments around schools, such as urban corner
stores where inexpensive, high-calorie foods are easily accessi-
ble before and after school (Borradaile, Sherman et al., 2009;
Laska, Borradaile et al., 2010; Lucan, Karpyn et al., 2010;
Gittelsohn, Rowan et al., 2012; He, Tucker et al., 2012).
We previously reported that children spent $1.07 and pur-
chased 356 kcal per corner store visit (Borradaile, Sherman et al.,
2009). Little is known, however, about the percentage of chil-
dren who frequent corner stores. One study found that 59% of
low-income urban, Black youth frequented corner stores at least
twice per week (Dennisuk, Coutinho et al., 2011). Even less is
known about the relationship between commuting mode (walk,
car, bus) and the utilization of corner stores or whether relative
weight status is associated with corner store or commuting
patterns. While walking to school provides children the oppor-
tunity to expend energy (Alexander, Inchley et al., 2005;
Davison, Werder et al., 2008; Tucker, Irwin et al., 2009), it may
introduce the unintended consequence of increased energy in-
take through greater exposure to inexpensive, unhealthy, food
environments (Borradaile, Sherman et al., 2009; Gittelsohn,
Rowan et al., 2012). More information about corner store and
commuting patterns of low-income, ethnically diverse, urban
youth can help identify targets for intervention among those
who are at the greatest risk for obesity and its consequences.
Further, such data can inform the considerable work that is
ongoing about corner store interventions.
The purpose of this study was to assess students’ corner store
and commuting patterns before and after school in a low-in-
come, ethnically diverse urban environment. In addition, we
examined the relationship among these factors and relative
Participants were 702 4th - 6th graders from ten, K-8 public
schools where 50% of children qualified for free or reduce-
priced meals. The mean ± SD eligibility for free/reduced meals
across the schools was 82.1% ± 7.4%. Demographic informa-
tion was collected during anthropometric measures. Students
provided sex, date of birth, and race/ethnicity by self-report.
Ethnicity and race were asked as two separate questions. Stu-
dents reported ethnicity as a yes/no (“are you Hispanic?”) and
were asked to choose from a list of provided races: Black/Af-
rican American, White, Asian, American Indian/Alaskan Native,
Native Hawaiian/Pacific Islander, Other. However, we found
that the students themselves did not make such distinctions, and
if identified as Hispanic, did not respond to the question re-
garding race (Hirst, Baranowski et al., 2009). Therefore, we
classified race/ethnicity as five categories: Black, Hispanic,
Asian, White, and Other (Table 1).
Schools were part of a randomized control trial to assess the
effects of a healthy corner store initiative in an urban, low in-
come sample. All data for this study were collected at baseline
before any intervention had occurred. Both parent consent and
child assent were obtained prior to any assessments. The aver-
age consent rate from the ten participating schools was 43.8%.
This study was approved by Temple University’s Institutional
Review Board.
Student Shopping Habits
Information about corner store purchases (yes/no, where,
when, amount spent) and method of commuting (mode) to and
from school were assessed using a 16-item questionnaire de-
veloped by the investigators. The questionnaire was distributed
in the classroom by trained research assistants who instructed
the students on how to complete the questionnaire and assisted
students who needed guidance.
Weight and Height
Weight was measured with a digital scale (SECA Alpha 882
and HD SECA 634) to the nearest 0.1 kg and height was meas-
ured with a portable stadiometer (PE-AIM-101) to the nearest
0.1 cm by trained research assistants using a standardized pro-
tocol. Both height and weight were measured twice and the
average of each was used. Body Mass Index (BMI) (weight in
kg divided by height in m2) as well as BMI z-scores and BMI
percentiles based on age and sex were calculated for each stu-
dent (Dean, Dean et al., 1996).
Statistical Analyses
Primary variables of interest were corner store purchasing
(yes/no), corner store spending (amount), and commuting
(mode). Differences in corner store purchasing, corner store
spending and commuting methods to and from school were
assessed using non-parametric statistics including chi-square
Table 1.
Sample characteristics (N = 702).
Variable Value
Black 43.4
Hispanic 30.6
Asian 7.3
White 6.4
Othera 12.2
Female 56.3
Male 43.7
Weight Status (%)
Underweight 2.0
Normal Weight 53.0
Overweight 17.8
Obese 27.2
Age (yrs) 11.0 ± 1.0
BMI (kg/m2) 21.3 ± 5.6
BMI z-score .8 ± 1.2
BMI percentile 69.4 ± 29.5
Note: Continuous data are reported a mean ± SD. Categorical data are reported as
percentage. aOther = American Indian/Alaska Native, Native Hawaiian/Other
Pacific Islander, more than one race/ethnicity, and unknown.
tests for categorical outcomes. Continuous outcomes that did
not meet assumptions for parametric statistics (due to skewness
and/or kurtosis, K-S tests p < .05) were analyzed using Mann-
Whitney U and Kruskal-Wallis tests. Differences in outcomes
based on categorical demographic variables (i.e., sex, weight
category and race) were also assessed using non-parametric
statistics, and correlations explored relationships between con-
tinuous demographic variables (i.e., age, BMI z-score) and
outcomes. Significance levels were set at p < .05.
Sample characteristics are described in Ta bl e 1. Nearly 75%
of students were Black (43.4%) or Hispanic (30.6%), and near-
ly half of the sample was overweight or obese (45%). Data on
corner store purchasing, corner store spending, and commut-
ing are reported in Table 2.
Corner Store Purchasing
More than half of children reported purchasing food or bev-
erages on the way to school (n = 403, 57.4%) or on the way
home from school (n = 411, 58.5%). Forty-four percent (n =
311) of children reported that they purchase food or beverages
both on the way to and from school, while 27.5% reported that
they never purchase food or beverages on the way to or from
school. One participant did not answer the question regarding
purchasing on the way to school, and 8 participants did
Open Access 167
Table 2.
Corner store purchasing and commuting pattern statistics (N = 702).
Variable Value p Value p
Corner Store Spending
(amount spent per purchase) $2.07 ± 1.5 $1.99 ± 1.7.05a
How much do you usually
spend on food, snac k, or drink
on the way t o/ af t er school?
Commuting (mode) AM PM
How do you usually
get to/leave school?
Walk 57.7 <.001b 66.5 <.001b
Car 26.6 17.2
School Bus 4.0 4.0
Bike 0.3 0.6
Public Transportation 4.0 4.7
Multiple 6.6 4.6
Other .6 1.4
Corner Store Purchasing
(yes/no) by We ight Category
Healthy Weight 56.5 .922c 59.1 .771c
Obese 58.6 57.1
Overweight 57.6 57.6
Underweight 64.3 71.4
Corner Store Purchasing
(yes/no) by Com muti ng
Walk 75.8 .01d 75.3 .2d
Car 61.3 60.0
School Bus 75.0 75.0
Bike 50.0 75.0
Public Transportation 85.7 78.7
Multiple 75.6 67.7
Other 66.7 66.7
Note: Continuous data are reported a mean ± SD. Categorical data are reported as
percentage. aDifference between am and pm spending; bDifference between
walking versus all other modes; cdifference in corner store purchasing by relative
weight status; dDifference in corner store purchasing by commuting method.
not answer the question about purchasing from school.
Corner Store Spending
Among the children who made corner store purchases on the
way to (n = 403) or from (n = 411) school, the average amount
spent was approximately $2.00 per corner store visit, with sim-
ilar amounts in the morning and the afternoon (Table 2).
Approximately two-thirds of children report walking to or
from school (Ta bl e 2 ). Compared to all other modes of trans-
portation, walking was the most common form both to and
from school (both ps < .001). Children who walked had higher
rates of corner store purchasing both before (p = .01) and after
(p = .02) school compared to all other methods of transportation
(Table 2). Approximately, three quarters of the children who
walked to and from school reported usually purchasing food,
snacks or drink at a corner store. There were no differences in
corner store spending (the amount spent per purchase) by me-
thod of commuting to or from school.
Effects of Weight St atus, Age, Sex, and Ra ce
Neither categorical weight status (e.g., obese, overweight,
healthy) nor continuous measures of weight (BMI, BMI z-score
and BMI percentile) were related to corner store purchasing
(yes/no), corner store spending (amount spent per purchase), or
commuting pattern (mode) in the morning or afternoon. Chil-
dren who made corner store purchases on the way to school
were significantly older than children who did not make corner
store purchases on the way to school (Mdn = 11.1 y versus 10.8
y; p = .005) and after school (Mdn = 11.1 y versus 10.8 y; p
= .04). There was no effect of age on the amount spent per cor-
ner store purchase.
There were no sex differences on corner store purchasing
(yes/no) and method of commuting to and from school. Boys
reported spending more money on corner store purchases on the
way to school in the morning than did girls (Mdn = $2.00 ver-
sus $1.50; p = .01), but there were no sex differences in after-
noon spending.
Black students reported making corner store purchases on the
way to school more frequently than children of other races
(68.2% vs 49.1%; p = .001). Black students also reported trav-
eling to (18.7% vs 32.7%) and from (11.8% vs 21.4%) school
via car less frequently (both ps < .001) than children of other
races. There was no race effect for corner store spending
(amount spent per purchase).
More than half of the students in this low-income, ethnically
diverse, urban sample made purchases in corners stores either
in the morning on the way to school (57.4%) or in the afternoon
on their way home from school (58.5%), and nearly 50%
(44.8%) reported shopping and purchasing in both the morning
and the afternoon. Nearly identical rates of corner store shop-
ping (59%) were reported in a smaller sample of low-income,
urban, Black youth (Hirst, Baranowski et al., 2009). Similarly,
65% of children shopped at convenience stores and fast food
outlets twice per week in a Canadian and predominantly Cau-
casian sample (He, Tucker et al., 2012).
Our current data on the amount spent per corner store pur-
chase ($2.07 ± 1.5 in the morning and $1.99 ± 1.7 in the after-
noon) is approximately $1.00 higher than what we previously
reported ($1.07 ± 0.93) (Borradaile, Sherman et al., 2009). This
difference is likely due to the method of direct observations
intercepted after corner store purchases (in our previous study)
rather than self-reported data collected in the classroom (in the
current study), where students may be inclined to inflate their
expenditures. Dennisuk and colleagues (Dennisuk, Coutinho et
Open Access
al., 2011) found that children were spending nearly $4.00 daily
($3.96) on food and beverages at a variety of outlets (Dennisuk,
Coutinho et al., 2011). While data from both studies were col-
lected in an urban sample of predominantly low-income, Black
youth, Dennisuk’s data differ from ours because they used 7-
day food recalls and employed a broader definition of food out-
lets to include convenience stores, fast food restaurants, super-
markets, and corner stores. Further, Dennisuk documented all
daily purchases at these outlets while our data focus on pur-
chases per morning or afternoon visit. While we found statisti-
cally significant differences by age on corner store purchasing
(yes/no) as well as by gender for corner store spending (amount
spent per visit) in the morning, the small median differences are
not likely to be meaningful.
The majority of the 4th - 6th grade students in our low-inco-
me, ethnically diverse urban sample commuted to (58%) and
from (67%) school on foot. Black students reported traveling to
(18.7% vs 32.7%) and from (11.8% vs 21.4%) school via car
less frequently (p < .001) than students of other races. Most
data suggest lower rates of active commuting in elementary
school children with rates from 10% - 13% in the US (Evenson,
Huston et al., 2003; McDonald 2008; Drake, Beach et al., 2012)
and 22% to 65% in other countries (Cooper, Page et al., 2003;
Merom, Tudor-Locke et al., 2006; Arango, Parra et al., 2011;
Chillon, Martinez-Gomez et al., 2012). Similar to our study,
McDonald found that rates of active commuting varied signifi-
cantly by race/ethnic group (9.4% of Whites, 15.5% of Blacks,
27.7% of Hispanics) (McDonald, 2008). McDonald also found
that students living in households earning <$30 K per year were
twice as likely to walk as students living in households making
>$60 K per year. Thus, our higher rates of walking may be due
to a sample that was nearly three quarters Black or Hispanic,
and 82% of whom were eligible for subsidized school meals.
Relative weight was not related to corner store purchasing
(yes/no), corner store spending (amount spent per purchase) or
commuting pattern (mode). To our knowledge, no previous
studies have examined the relationship between corner store
purchases or spending and relative weight. Among studies that
examined corner store location rather than purchases, one study
found that corner store proximity to a school was associated
with a slightly higher prevalence of obesity (1.6%) but the ef-
fect was limited to majority-Latino schools (Langellier, 2012).
Another found that greater access to convenience stores is as-
sociated with higher BMI and higher prevalence of overweight
in adolescents (Powell, Auld et al., 2007). Others, however,
found no relationship between food environment and BMI
(Harris, Blum et al., 2011; An & Sturm, 2012). The lack of a
relationship between corner store purchases and relative weight
in our study may be partially explained by the ubiquity of cor-
ner stores with predominantly nutritionally sparse, energy dense
foods in low-income, urban environments that limited our abil-
ity to detect differences. Alternatively, it may be that energy
intake at other locations (home, school) may differentially con-
tribute to a positive energy balance.
Relative weight was not related to commuting pattern (mode).
This is similar to several other studies (Tudor-Locke, Ainsworth
et al., 2003; Fulton, Shisler et al., 2005; Heelan, Donnelly et al.,
2005; Rosenberg, Sallis et al., 2006). Recently, however, two
studies found a relationship between active commuting and
relative weight among adolescents. Drake et al. found that ac-
tive commuting was associated with a lower risk of obesity but
not with overweight (Drake, Beach et al., 2012), and Arango
found a significant association between active commuting and a
reduced likelihood of overweight and obesity combined
(Arango, Parra et al., 2011). There are several methodological
differences among our study and these two that make the dif-
ferences hard to interpret. While all three studies used self-
reported data on commuting, Drake collected self-reported
height and weight, but Arango and we used measured heights
and weights. Another difference is that our sample had a 45%
prevalence of overweight/obesity combined, while Drake and
Arango’s samples were 29% and 16.1% respectively. Finally,
Drake’s participants were from New Hampshire and Vermont,
Arango’s were from Colombia, and our sample was from
While walking to and from school clearly helps children ex-
pend energy, our data suggest that urban children who walk to
and from school make corner store purchases more frequently
than those using all other forms to commuting. Corner stores
are filled with nutrient poor, high calorie foods and beverages
(Borradaile, Sherman et al., 2009; Laska, Borradaile et al., 2010;
Lucan, Karpyn et al., 2010) and the energy consumed from
purchases at these stores are assumed to be in addition to regu-
lar school meals (i.e., universal free breakfast and lunch pro-
vided at school). Given that most children in our study were
already walking to and from school, future urban pediatric obe-
sity interventions may benefit from targeting reductions in cal-
ories purchased in corner stores in conjunction with targeting
increase in active commuting.
The strengths of this study include individual level data, a
large sample size, a low-income, high-minority sample, sys-
tematically measured weights and heights and the first study to
assess the relationship between corner store purchasing and
relative weight status. Limitations of the study include the use
of self-reported corner store and commuting patterns, and a low
consent rate. Longitudinal research is needed to assess whether
corner store purchasing, corner store spending and commuting
patterns change over time with intervention and to examine
relationships between these changes and changes in relative
weight. Further research should also include a greater range of
age groups to better understand if these patterns vary by age.
This work was supported by the Robert Wood Johnson
Foundation, Healthy Eating Research grant 63052. We would
like to acknowledge the contribution of the following individu-
als to this research:
Kelley E. Borradaile, Ph.D., Ravi Chawla, Teressa Chen,
Bryant Deinhardt, Vikin Lalan, Taya Malone, Swapna Mehta,
MPH, Nomfundo Msomi, Tina Nguyen, MD, and Vishwas
Vanar. In addition, we express our gratitude to the many chil-
dren, parents, teachers, school administrative staff, and store
owners and staff for their assistance in making this research
Alexander, L. M., Inchley, J., et al. (2005). The broader impact of walk-
ing to school among adolescents: Seven day accelerometry based
study. BMJ, 331, 1061-1062.
An, R., & Sturm, R. (2012). School and residential neighborhood food
environment and diet among California youth. American Journal of
Open Access 169
Open Access
Preventive Medicine, 42, 129-135.
Arango, C. M., Parra, D. C., et al. (2011). Walking or bicycling to
school and weight status among adolescents from Monteria, Colom-
bia. Journal of Physical Activity & Health, 8, S171-177.
Borradaile, K. E., Sherman, S., et al. (2009). Snacking in children: The
role of urban corner stores. Pediatrics, 124, 1293-1298.
Chillon, P., Martinez-Gomez, D., et al. (2012). Six-year trend in active
commuting to school in Spanish adolescents: The AVENA and AF-
INOS Studies. Internatio nal Journal of B ehavioral Medicine.
Cooper, A. R., Page, A. S., et al. (2003). Commuting to school: Are
children who walk more physically active? American Journal of
Preventive Medicine, 25, 273-276.
Davison, K. K., Werder, J. L., et al. (2008). Children’s active commut-
ing to school: current knowledge and future directions. Preventing
Chronic Disease, 5, A100.
Dean, A. G., Dean, J. A., et al. (1996). Epi Info™, Version 6.04a, a
Word Processing, Database, and Statistics Program for Public
Health on IBM-Compatible Microcomputers. Atlanta, GA: Centers
for Disease Control and Prevention.
Dennisuk, L. A., Coutinho, A. J., et al. (2011). Food expenditures and
food purchasing among low-income, urban, African-American youth.
American Journal of Preventive Medicine, 40, 625-628.
Drake, K. M., Beach, M. L., et al. (2012). Influence of sports, physical
education, and active commuting to school on adolescent weight sta-
tus. Pediatrics, 130, e296-304.
Evenson, K. R., Huston, S. L., et al. (2003). Statewide prevalence and
correlates of walking and bicycling to school. Archives of Pediatrics
and Adolescent Medicine, 157, 887-892.
Ford, E. G., Vander Veur, S. S., et al. (2007). Obesity prevention in
school and group child care settings. In S. Kumanyika, & R. C.
Brownson (Eds.), Handbook of Obesity Prevention: A Resource for
Health Professionals (pp. 349-376). New York, NY: Spinger Science
+ Business Media.
Foster, G. D., Linder, B., et al. (2010). A school-based intervention for
diabetes risk reduction. The New England Journal of Medicine, 363,
Foster, G. D., Sherman, S., et al. (2008). A policy-based school inter-
vention to prevent overweight and obesity. Pediatrics, 121, e794-802.
Freedman, D. S., Mei, Z., et al. (2007). Cardiovascular risk factors and
excess adiposity among overweight children and adolescents: The
Bogalusa Heart Study. Journal of Pediatrics, 150, 12-17,e12.
Fulton, J. E., Shisler, J. L., et al. (2005). Active transportation to school:
Findings from a national survey. Research Quarterly for Exercise &
Sport, 76, 352-357.
Gittelsohn, J., Rowan, M., et al. (2012). Interventions in small food
stores to change the food environment, improve diet, and reduce risk
of chronic disease. Preventing Chronic Disease, 9, E59.
Harris, D. E., Blum, J. W., et al. (2011). Location of food stores near
schools does not predict the weight status of maine high school stu-
dents. Journal of Nutrition Education and Behavior, 43, 274-278.
He, M., Tucker, P., et al. (2012). The influence of local food environ-
ments on adolescents’ food purchasing behaviors. International Jour-
nal of Environmental Research and Public Health, 9, 1458-1471.
Healthy Corner Stores Network.
Heelan, K. A., Donnelly, J. E., et al. (2005). Active commuting to and
from school and BMI in elementary school children-preliminary data.
Child: Care, Health and Development, 31, 341-349.
Hirst, K., Baranowski, T., et al. (2009). HEALTHY study rationale,
design and methods: Moderating risk of type 2 diabetes in multi-
ethnic middle school students. International Journal of Obesity, 33,
Johnson, T., Weed, L. D., et al. (2012). School-based interventions for
overweight and obesity in minority school children. The Journal of
School Nursing, 28, 116-123.
Katz, D. L., O’Connell, M., et al. (2008). Strategies for the prevention
and control of obesity in the school setting: Systematic review and
meta-analysis. International Journal of Obesity, 32, 1780-1789.
Kaufman, F. R., Hirst, K., et al. (2009). Risk factors for type 2 diabetes
in a sixth-grade multiracial cohort: The HEALTHY study. Diabetes
Care, 32, 953-955.
Kohler, M. J., & van den Heuvel, C. J. (2008). Is there a clear link
between overweight/obesity and sleep disordered breathing in chil-
dren? Sleep Medicine Reviews, 12, 347-361.
Langellier, B. A. (2012). The food environment and student weight
status, Los Angeles County, 2008-2009. Preventing Chronic Disease,
9, E61.
Laska, M. N., Borradaile, K. E., et al. (2010). Healthy food availability
in small urban food stores: A comparison of four US cities. Public
Health Nutrition, 13, 1031-1035.
Lucan, S. C., Karpyn, A., et al. (2010). Storing empty calories and
chronic disease risk: snack-food products, nutritive content, and
manufacturers in Philadelphia corner stores. Journal of Urban Health,
87, 394-409.
McDonald, N. C. (2008). Critical factors for active transportation to
school among low-income and minority students—Evidence from
the 2001 national household travel survey. American Journal of
Preventive Medicine, 34, 341-344.
Merom, D., Tudor-Locke, C., et al. (2006). Active commuting to school
among NSW primary school children: Implications for public health.
Health Place, 12 , 678-687.
Ogden, C. L., Carroll, M. D., et al. (2012). Prevalence of obesity and
trends in body mass index among US children and adolescents, 1999-
2010. JAMA, 307, 483-490.
Powell, L. M., Auld, M. C., et al. (2007). Associations between access
to food stores and adolescent body mass index. American Journal of
Preventive Medicine, 33, S301-307.
Puhl, R. M., Luedicke, J., et al. (2011). Weight-based victimization
toward overweight adolescents: Observations and reactions of peers.
Journal of School Heal th , 81, 696-703.
Rosenberg, D. E., Sallis, J. F., et al. (2006). Active transportation to
school over 2 years in relation to weight status and physical activity.
Obesity, 14, 1771-1776.
Singh, A., Foster, G. D., et al. (2012). Elevated circulating tissue factor
procoagulant activity, factor VII, and plasminogen activator inhibi-
tor-1 in childhood obesity: Evidence of a procoagulant state. British
Journal of Haematology, 1 58 , 523-527.
Tucker, P., Irwin, J. D., et al. (2009). Environmental influences on
physical activity levels in youth. Health Pl a ce , 15, 357-363.
Tudor-Locke, C., Ainsworth, B. E., et al. (2003). Physical activity and
inactivity in Chinese school-aged youth: the China Health and Nutri-
tion Survey. International Journal of Obesity and Related Metabolic
Disorders, 27, 1093-1099.
Waters, E., de Silva-Sanigorski, A., et al. (2011). Interventions for
preventing obesity in children. Cochrane Database Syst Rev, 12,