Diet and Physical Activity Patterns of School-Aged Children
Childhood provides an opportunity for establishing healthful lifestyle habits, yet little is known about diet and physical activity patterns of elementary school-aged children. A cohort of 35 boys and girls in grades 3 through 5 (mean age=9.5 years) was studied during the course of the 2004-2005 school year, providing seasonal assessments of diet and physical activity. Objectively measured data included height, weight, and pedometer step counts. Subjective data included seasonal 3-day diet diaries, a food frequency questionnaire, and a physical activity questionnaire. Participants were white, well-nourished, and within the healthy range for body mass index for age. Only three students (9%) were overweight and another three were "at risk" for overweight. Food intake patterns fell far below MyPyramid guidelines for average daily servings of fruits and vegetables. High intakes of saturated fat (average of 12% of calories) and sodium were noted, along with inadequate fiber intakes. Snacks, desserts, and entrees that contributed most to calorie and saturated fat intake were identified. Self-reported physical activity appears in line with recommendations, but step counts fall short, particularly for girls and during winter months. These findings identify targets for behavioral and environmental interventions to reduce childhood obesity risks. Additional research involving more diverse populations is warranted.
Research and Professional Briefs
Diet and Physical Activity Patterns of
MAYA VADIVELOO, MS; LEI ZHU, MS; PAULA A. QUATROMONI, DSc, MS, RD
Childhood provides an opportunity for establishing
healthful lifestyle habits, yet little is known about diet
and physical activity patterns of elementary school-aged
children. A cohort of 35 boys and girls in grades 3 through
5 (mean age⫽9.5 years) was studied during the course of
the 2004-2005 school year, providing seasonal assess-
ments of diet and physical activity. Objectively measured
data included height, weight, and pedometer step counts.
Subjective data included seasonal 3-day diet diaries, a
food frequency questionnaire, and a physical activity
questionnaire. Participants were white, well-nourished,
and within the healthy range for body mass index for age.
Only three students (9%) were overweight and another
three were “at risk” for overweight. Food intake patterns
fell far below MyPyramid guidelines for average daily
servings of fruits and vegetables. High intakes of satu-
rated fat (average of 12% of calories) and sodium were
noted, along with inadequate ﬁber intakes. Snacks, des-
serts, and entrees that contributed most to calorie and
saturated fat intake were identiﬁed. Self-reported physi-
cal activity appears in line with recommendations, but
step counts fall short, particularly for girls and during
winter months. These ﬁndings identify targets for behav-
ioral and environmental interventions to reduce child-
hood obesity risks. Additional research involving more
diverse populations is warranted.
J Am Diet Assoc. 2009;109:145-151.
revalence of childhood obesity has risen dramati-
cally in the United States, and is recognized as an
important public health threat. Since the 1970s, obe-
sity prevalence has more than doubled among preschool-
aged children and adolescents, and has more than tripled
among children ages 6 to 11 years (1-3). Approximately 9
million children older than age 6 years are classiﬁed as
overweight according to age- and sex-speciﬁc body mass
index (BMI; calculated as kg/m
) cut-points (1-3). Unfor-
tunately, youth does not spare children from the physical,
social, and emotional consequences of obesity, including
diabetes, dyslipidemia, hypertension, and metabolic syn-
There are many contributors to childhood obesity, man-
ifested by notable shifts in population demographics, life-
style behaviors, and environments at home, in the com-
munity, and in schools. Multiple forces contribute to the
imbalance between energy intake and energy expendi-
ture that inﬂuences weight gain (4). The importance of
establishing healthful nutritional practices in young chil-
dren is underscored by the fact that eating habits are
typically molded during early childhood (5). Only 2% of
school-aged children meet all of the recommendations of
the Food Guide Pyramid (6) and 16% do not meet any of
the guidelines (7). Some 20% of children and adolescents
meet the recommendation for fruit and vegetable intake
and even fewer drink at least 3 cups of milk daily (8).
Children also fall short of physical activity recommenda-
tions, with roughly one third of students active for at
least 60 minutes per day at least 5 days a week (8).
Moreover, 58% of students are exceeding the American
Academy of Pediatrics (AAP) guidelines (9) by spending
more than 2 hours a day watching television or playing
computer/video games (8).
Efforts to address childhood obesity include public
health goals to increase daily physical activity, decrease
sedentary behaviors, and establish healthful eating hab-
its (4). To inform effective interventions, a better under-
standing of the behaviors of school-aged children is
needed, yet relatively little research includes elementary
school students. Research examining this population
comes predominantly from large surveys (10-12) using
short-term, self-reported assessments methods that can
contribute to measurement error and imprecise estimates
of both diet and physical activity. While these data are
useful for generating new research hypotheses, more
comprehensive objective data are needed. Because ⬎20%
of US children who are either overweight or “at-risk”
have achieved that status by the time they enter middle
school (2,3,13), the elementary school years represent an
appropriate time to introduce behavioral interventions
M. Vadiveloo is a research assistant and P. A. Quatro-
moni is an assistant professor, Department of Health
Sciences, Sargent College of Health and Rehabilitation
Sciences, Boston, MA. L. Zhu is a research assistant
and doctoral student, Department of Mathematics and
Statistics, Statistics and Consulting Unit, Boston Uni-
versity, Boston, MA.
Address correspondence to: Paula A. Quatromoni,
DSc, MS, RD, Department of Health Sciences, Sargent
College of Health and Rehabilitation Sciences, Boston
University, 635 Commonwealth Ave, Boston, MA 02215.
Manuscript accepted: July 25, 2008.
Copyright © 2009 by the American Dietetic
© 2009 by the American Dietetic Association Journal of the AMERICAN DIETETIC ASSOCIATION 145
(4). The purpose of this pilot study (KidSTEPS) is to use
a combination of age-appropriate objective and self-re-
ported assessment tools to describe the eating patterns
and physical activity habits of elementary school-aged
Children in grades 3 through 5 were recruited from two
partnering elementary schools in a single suburb of Bos-
ton, MA. Fliers were distributed in school in September
2004 and eligibility required only parental consent. Par-
ents contacted study personnel via e-mail and informed
consent was obtained by telephone with follow-up mail-
ings to obtain signed parental consent and student assent
forms. Study protocols were approved by the Boston Uni-
versity Institutional Review Board. Enrollment occurred
between September and November. Data collection was
initiated upon enrollment and continued through June
2005. Study materials were user-friendly, low-burden,
completed at home by children and their parents, and
exchanged by mail. Stamped envelopes were provided for
return of completed forms and small prize incentives (eg,
keychains, t-shirts) were given as rewards.
Children were assessed in three seasons: fall (October/
November), winter (January/February), and spring (May/
June). Parents completed a brief demographic question-
naire at baseline. All other information was collected in
each season, with the exception of the food frequency and
physical activity questionnaires as noted here. Each sea-
son, students were given a personalized KidSTEPS diary
that facilitated collection of information by integrating
assessment forms into a single booklet.
Height (in inches) and weight (in pounds) were mea-
sured by certiﬁed school nurses using district-wide clini-
cal protocols that comply with state regulations (14).
Nurses used existing equipment in their schools that is
calibrated annually (Detecto physician beam balance
scales, Webb City, MO; and Seca wall-mounted stadiom-
eters, Hanover, MD). Single measures were taken and
recorded to the nearest one-quarter inch for height and
one-half pound for weight. Anthropometric data were re-
corded by nurses in the KidSTEPS diary. BMI was com-
puted (15) and BMI-for-age was plotted on sex-speciﬁc
growth charts (16). Overweight was deﬁned as BMI-for-
age ⱖ95th percentile, and “at risk” was deﬁned as values
ⱖ85th percentile but ⬍95th percentile (17).
A validated 152-item semi-quantitative youth food fre-
quency questionnaire (FFQ) (18,19) was completed at
home by children with their parents. FFQs were collected
in fall and spring seasons to assess long-term intake
patterns. Children reported how often they ate speciﬁc
foods during the past year. Response categories ranged
from “never/less than once per month” up to “5 or more
times per day.” Questionnaires were used to generate
estimates of food group intake and to identify foods that
were top contributors to key macronutrients in students’
diets. Questionnaires were reviewed for completeness,
open-ended responses were coded by trained research
assistants according to standard procedures of Channing
Laboratory (Boston, MA), and forms were optically
scanned to produce electronic data sets. All question-
naires were sufﬁciently complete for analysis; none were
excluded and no outliers were detected with respect to
reported food group intake.
There are many contributors to
childhood obesity, manifested by
notable shifts in population
demographics, lifestyle behaviors,
and environments at home, in the
community, and in schools.
Three-day food records were collected from participants
in each of three seasons for the purpose of estimating
daily nutrient intake. Children and their parents were
instructed to record the child’s food and beverage intake
on 2 weekdays and 1 weekend day in the KidSTEPS
diary. Days of the week speciﬁed for record-keeping were
randomly assigned across cohort members and were
guaranteed to be nonconsecutive. Portion sizes were es-
timated using household measures, food-speciﬁc portion
size information from food packages, and serving size
information obtained from the school foodservice man-
ager. Completed diaries were returned by mail and re-
viewed by trained staff. Parents were contacted and
probed for missing information, food preparation details,
or missing portion details. The foodservice manager pro-
vided recipe, ingredient, and serving size details for
school lunch items. Food records were coded by trained
university-based research staff using the Nutrition Data
System for Research (NDS-r version 5.0, database 35,
2004) developed by the Nutrition Coordinating Center at
the University of Minnesota (20) to generate nutrient
intake estimates exclusive of micronutrients from multi-
vitamin/mineral supplements. Data ﬁles were reviewed
by investigating the top 10% and bottom 10% of daily
intake estimates for total calories and macronutrients to
correct or verify any extreme nutrient outliers.
Physical activity was assessed by self-report using a val-
idated, youth seasonal activity questionnaire (21,22) com-
pleted in fall and spring seasons. Like the FFQ, this
instrument was scanned by Channing Laboratory (Bos-
ton, MA) to generate a data set that was devoid of outli-
ers. The questionnaire lists 18 physical activities, 8 inac-
tive pursuits like reading and doing homework, and
queries participation in team sports. This instrument
minimizes the overestimation of highly seasonal activi-
ties by asking respondents to report their frequency of
participation in each season of the previous year (23).
Children also wore pedometers for 7 consecutive days in
each season. A 7-day monitoring protocol was shown to
provide reliable estimates of usual physical activity in
children (24). Students entered daily pedometer counts
into activity logs in the KidSTEPS diaries, with parental
assistance as needed.
146 January 2009 Volume 109 Number 1
Nutrient estimates represent an average of 9 days of food
record data (3 days/season). Food group intake was de-
rived from the spring FFQ to coincide with nutrient esti-
mates from food records kept during the same time frame
(the 2004-2005 school year). Foods that contributed the
most to total energy and saturated fat intakes in the
cohort were determined from FFQ data. Pedometer, an-
thropometric, demographic, and behavioral data (such as
multivitamin/mineral supplement use) were keyed and
veriﬁed using duplicate entry procedures. The Statistical
Analysis System (SAS/STAT Software, version 8.2, 2001,
SAS System for Windows, SAS Institute Inc, Cary, NC)
was used to generate descriptive statistics and two-sam-
ple t-tests compared data across sexes.
RESULTS AND DISCUSSION
Thirty-ﬁve children enrolled and completed baseline data
collection. The cohort was almost exclusively white
(n⫽34), with one minority participant who was Asian
American. At the close of data collection, 32 children
(91%) remained in the study, with reasons for drop-out
related to burden of the diet assessment protocols. Chil-
dren who dropped out of the study were no different from
those who completed the study with respect to demo-
graphic characteristics, BMI, or baseline physical activ-
ity. Participants were between the ages of 8 and 10 years
with a mean age of 9.5 years. Most students (n⫽15) were
in the fourth grade. The study group was predominantly
female (n⫽24) and most were within the healthy range
for weight. In this sample, 26 students (82%) had a BMI-
for-age in the desired range, three (9%) were at risk for
overweight, and three others were overweight. About half
of participants (n⫽17) took a multivitamin/mineral sup-
plement, with only 10 reporting daily use.
The dietary proﬁles of elementary school-aged children in
this sample (Table 1) were relatively consistent with rec-
ommendations of the Dietary Guidelines for Americans
2005 (25). Children consumed 54% of calories from car-
bohydrate, 15% from protein, and 33% from fat, on aver-
age. According to Institute of Medicine recommendations
(26-30), diets appeared adequate in folic acid, iron, and
vitamins C and D from food sources (exclusive of multi-
vitamin/mineral supplements). However, diets fell short
of target intakes for ﬁber and calcium with children meet-
ing only 50% and 70% of the recommendations, respec-
tively. Both boys and girls consumed more saturated fat
and sodium in their diets than what is recommended by
the Institute of Medicine (30,31). The difference in mean
energy intake between sexes approached statistical sig-
niﬁcance, and boys consumed more ﬁber, iron, calcium,
folic acid, and sodium than girls (P⬍0.05).
Average daily intakes of fruits and vegetables were
markedly low; children consumed half or less of the
amount recommended by the US Department of Agricul-
ture’s MyPyramid (32). In contrast, intake of milk, yo-
gurt, and cheese approached recommended levels, yet
only boys’ average intakes met the guideline. While it is
promising that children in this cohort were close to meet-
ing the milk equivalent recommendation, it is important
to promote consumption of these foods wisely. In this
school-aged sample, milk was the biggest contributor to
both total calories and saturated fat intake, suggesting
that availability and promotion of low-fat and nonfat milk
deserves extra effort. In fact, many items commonly of-
fered in school cafeterias as either lunch entrees or snack
foods were found to be important contributors to calorie
and saturated fat intake in this cohort, namely ice cream
treats; chips; macaroni and cheese; fried foods, including
chicken nuggets; meatballs; and other entrees made with
cheese. This observation was made previously in a high
school population (33) and substantiates the need for
healthier menu offerings in school foodservice beginning
at the elementary level.
Sex differences in dietary intake in this cohort were
relatively few. According to the Institute of Medicine
guidelines, active boys and girls between the ages of 9
and 13 should consume 2,000 to 2,600 and 1,800 to 2,200
calories, respectively (30). Reported energy intakes in our
cohort are slightly lower than these targets, but are not
likely the result of substantial measurement error, given
the 9 days of food records collected during the year. None-
theless, our estimates of intake are comparable with the
limited body of research among this age group showing
that boys tend to consume more calories than girls (10)
and children between the ages of 6 and 11 years eat, on
average, 2,100 kcal/day, with 33% of calories from fat and
11.5% of calories from saturated fat (10). Research sug-
gests that children’s diets are also high in sodium (10,11).
Finally, low fruit and vegetable intake in school-aged
children may represent an important precursor to adoles-
cent behavior, because only one in ﬁve high school stu-
dents reportedly eats ﬁve or more servings of fruits and
vegetables daily (8). Without diligent efforts, these unde-
sirable food and nutrient intake patterns that begin as
early as elementary school will likely persist throughout
Physical Activity Patterns
According to self-reports from the activity questionnaires,
elementary school-aged students in this cohort met the
AAP guidelines for physical activity (34) by engaging in a
mean of 1.8 hours of daily activity (Table 2). They accu-
mulated, on average, almost 11,000 steps per day. Simul-
taneously, both boys and girls were spending an average
of 4 hours per day engaging in inactive pursuits including
television, video games, computer media, and recre-
ational reading. While television viewing and video, com-
puter, and handheld games were not distinguished from
inactivity associated with pleasure reading and home-
work in this analysis, it is possible that the proportion
that was screen time exceeded AAP recommendation of
fewer than 2 hours per day (9).
While children in this sample appear reasonably active
based on self-reported activity data, objectively measured
pedometer counts fall short of public health recommen-
dations for children. Whereas 10,000 steps per day is
advocated as a target for health promotion among adults
(35), the 2001-2002 President’s Challenge Physical Activ-
ity and Fitness Awards Program (36) recommends that
children accumulate more; speciﬁcally 11,000 steps (for
January 2009 ● Journal of the AMERICAN DIETETIC ASSOCIATION 147
girls) to 13,000 steps (for boys) at least 5 days a week.
More recently, targets ranging from 12,000 up to 16,000
steps per day have been suggested for girls and boys,
respectively (37,38). KidSTEPS participants were chal-
lenged to meet these goals, with boys logging an annual
average of 12,839 steps and girls accumulating only 9,822
steps on average. In fact, boys logged considerably more
steps than girls in each season. The sex discrepancy was
least pronounced during the spring season, when both
groups appeared to be the most active. In general, step
counts were notably higher during the fall and spring
seasons, whereas levels dropped to below recommended
targets in the winter among both sexes. Sustaining phys-
ical activity during winter months and inclement weather
requires special efforts and creative innovation.
The observation that boys were more active than girls
is consistent with other research (39-42) and suggests the
importance of targeting activity interventions differently
to girls to achieve high rates of participation. In addition,
research suggests that interventions should encourage
speciﬁcally more vigorous physical activity. In fact, the
majority of youth participate in moderate physical activ-
ity, whereas ⬍3% engage in vigorous activity three or
more times per week (39,43).
While the activity ﬁndings are promising, observations
about the average time spent inactive warrant attention.
Research suggests that physical activity declines through-
out adolescence and is often replaced with less-active pur-
suits (44). Inactivity, particularly inactivity associated
with television-watching and video or computer games,
may be related to development of unhealthful eating and
snacking patterns (45,46), including excess fat consump-
Table 1. Dietary intakes of elementary school-aged participants in KidSTEPS compared to recommended intake levels, with food sources of
key macronutrients identiﬁed
at the 2,000-calorie
Boys (nⴝ8) Girls (nⴝ24)
4™™™™™™™™™™™™™™™ mean⫾standard deviation ™™™™™™™™™™™3
Energy (kcal) 2,000 1,766⫾325 1,949⫾401† 1,702⫾275
Carbohydrate (%) 45-65 54.0⫾5.0 54.6⫾5.9 53.8⫾4.8
Protein (%) 10-35 15.0⫾2.1 15.7⫾2.1 14.8⫾2.0
Total fat (%) 25-35 32.6⫾4.1 31.7⫾4.8 32.9⫾3.9
Saturated fat (%) ⬍10 11.9⫾1.9 12.2⫾2.4 11.8⫾1.7
Trans fat (g) — 4.6⫾1.4 4.5⫾1.6 4.6⫾1.4
Cholesterol (mg) ⬍300 193⫾75 203⫾91 190⫾70
Fiber (g) 28 13.6⫾4.1 16.4⫾5.6* 12.6⫾3.0
Sodium (mg) ⬍2,300 2,627⫾549 3,009⫾673* 2,495⫾440
Calcium (mg) 1,300 900⫾314 1,165⫾339* 809⫾252
Iron (mg) 8 14.2⫾4.3 17.7⫾4.9* 12.9⫾3.4
Folic acid (DFE)
300 382⫾136 472⫾184* 352⫾102
Fruits (cups/day) 2 0.96⫾0.50 0.83⫾0.25 1.01⫾0.06
Vegetables (cups/day) 2.5 1.06⫾0.49 1.30⫾0.22 0.98⫾0.50
(cups/day) 3 2.42⫾1.18 3.06⫾1.15 2.21⫾1.13
Top contributors to calories and saturated fat in children’s diets
Total calories Milk, peanut butter sandwich, poultry, ice cream, beef, yogurt, cold cereal, spaghetti w/sauce, pasta,
Calories from mixed dishes Peanut butter sandwich, spaghetti w/ sauce, pizza, macaroni and cheese, turkey sandwich, tacos,
bologna sandwich, cheeseburger, French toast, grilled cheese sandwich
Calories from snack foods Potato chips, corn chips, crackers, nuts, pretzels, popcorn, nachos, chicken noodle soup
Calories from desserts and
Ice cream, fruit punch, chocolate chip cookies, frozen yogurt, popsicles, chocolate, soda, cake, other
candy, graham crackers
Saturated fat Milk, ice cream, beef, cheese, butter, poultry, peanut butter sandwich, macaroni and cheese, fried
foods eaten away from home, meatballs
Recommended intake levels for energy and food groups were estimated for the average KidSTEPS participant who was 9.5 years old, based on the US Department of Agriculture Food
Guide amount at the 2,000 calorie-level for a moderately-active to active boy or girl ages 9-13 (25); for micronutrients, Dietary Reference Intakes are shown for males and females
ages 9-13 years (26-31). Recommended ﬁber intake is 14 g/1,000 kcal, representing 28 g/day at a 2,000-calorie intake level (30). There is no speciﬁc recommendation for trans-fat
intake other than to keep intake as low as possible (25).
Nutrient intake estimated from a series of 3-day food records collected in each of three seasons (fall, winter and spring), for a total of nine dietary records per child.
DFE⫽dietary folate equivalent. 1 DFE⫽1
g food folate (26).
Derived from the Youth/Adolescent Questionnaire (18,19).
Milk equivalents include milk, yogurt and cheese.
*P⬍0.05 for differences in intake between sexes.
148 January 2009 Volume 109 Number 1
tion (47) and low fruit and vegetable intake (48). Because
elementary school-aged children in this sample may al-
ready exceed AAP recommendations (9) for screen time,
this trend may become problematic as adolescence ap-
proaches. In fact, some of the observed dietary traits may
already reﬂect the unhealthful patterns that can develop
with excess screen time.
The hypothesis that obesity risk behaviors cluster to-
gether is well-supported in the literature. In a recent
study, nearly 80% of 11- to 15-year-olds had more than
one risk factor related to poor diet and physical activity
(49). Moreover, children who are the most sedentary are
reportedly less likely to undertake physical activity and
consume adequate servings of fruits and vegetables (50).
Unhealthful dietary patterns appear to proliferate during
the years between elementary and high school, with far
fewer high school students consuming enough daily serv-
ings of fruits and vegetables (12). In a nationwide survey
of ⬎4,000 students, the proportion who fell short of phys-
ical activity guidelines increased dramatically by 28 per-
centage points between elementary and high school, with
63% of high school students not meeting the criteria for
physical activity (12). While behavioral research demon-
strates that unhealthful behaviors travel together, it also
suggests that healthier behaviors are similarly correlated
(51,52). This evidence underscores the need for integrated
intervention strategies and environmental changes to effec-
tively moderate obesity-related risk behaviors.
This descriptive research is preliminary and is limited by
the cohort’s small sample size, unequal sex distribution
with few male participants, and relative homogeneity
with respect to demographic characteristics. Yet the com-
bination of multiple self-reported, seasonal, and objective
measures of diet and physical activity reduces measure-
ment error and strengthens our behavioral assessments.
It should be noted that for apparent differences between
boys and girls that do not reach statistical signiﬁcance,
one explanation may be lack of analytical power given the
small sample size. Self-selection bias is possible because
children who participated may have had activity and
dietary patterns that were different, and possibly health-
ier, than those who did not enroll. This source of bias may
explain why most participants were within the healthy
BMI range, which limits the generalizability of ﬁndings
to overweight children. Nonetheless, areas for improve-
ments in diet and physical activity were clearly identiﬁed
even within this selective cohort, suggesting that sub-
stantial risk may remain undeﬁned in the general popu-
Elementary school–aged children have diet and physical
activity patterns that warrant attention, additional
study, and targeted intervention in order to impact child-
hood obesity risks. Food and nutrition professionals and
educators should work to foster healthful eating behav-
iors in elementary schools and facilitate physical activity
opportunities that effectively involve girls and students
in general who are challenging to engage. Speciﬁc efforts
to increase intakes of fruits, vegetables, dietary ﬁber, and
calcium appear important, as are efforts to reduce con-
sumption of saturated fat and sodium in home, school,
and snack environments. Continued emphasis on the pro-
motion of daily physical activity is appropriate, and cre-
ative strategies that sustain activity during winter
months are needed.
This work was supported by funds from the Dudley Allen
Sargent Research Fund, Sargent College of Health and
Rehabilitation Sciences at Boston University.
The authors gratefully acknowledge the contributions
of the school nurses, school administrators, teachers, par-
ents, and children who participated in the KidSTEPS
Table 2. Mean daily pedometer step counts and self-reported physical activity of elementary school-aged participants in KidSTEPS, compared
to recommendations for physical activity
Recommended Overall (nⴝ32)
Boys (nⴝ8) Girls (nⴝ24)
4™™™™™™™™™™™™™ mean⫾standard deviation ™™™™™™™™™™™™™3
Fall (steps/day) 13,000 for boys
10,955⫾3,273 13,354⫾1,884** 10,124⫾3,262
Winter (steps/day) 9,236⫾2,554 11,495⫾2,416** 8,513⫾2,179
Spring (steps/day) 11,000 for girls
11,625⫾3,600 13,795⫾3,676* 10,902⫾3,342
(steps/day) 10,576⫾2,760 12,839⫾2,548** 9,822⫾2,432
Time spent in physical activity
(h/day) ⱖ1 1.80⫾0.91 1.97⫾1.05 1.75⫾0.99
Time spent in inactivity
4.05⫾1.92 4.45⫾1.24 3.93⫾2.09
Average of pedometer step counts logged over 7 consecutive days per season.
Recommendations for children, set by the 2001-2002 President’s Challenge Physical Activity and Fitness Awards Program (36).
Average of pedometer step counts logged over 7 consecutive days in each of three seasons (21 days total).
Self-reported time spent in various physical activities and sports, from the Seasonal Youth/Adolescent Activity Questionnaire (21-23).
Self-reported time spent doing inactive tasks like playing computer games, reading, or watching television; from the Seasonal Youth/Adolescent Activity Questionnaire (21-23).
Recommendation is to limit “screen time” speciﬁcally to no more than 2 hours per day (9). This makes the comparison with the estimate of time spent in inactivity as deﬁned by the
Seasonal Youth/Adolescent Activity Questionnaire (21-23) less direct because reading is included in that tool’s estimate of inactive time.
January 2009 ● Journal of the AMERICAN DIETETIC ASSOCIATION 149
project. Special thanks to Research Assistants Danielle
Duggan, Katie Kirkpatrick, Annie Paquette, Eva Mallis,
Helen Wei, and Mimi Borkan. Thanks to Winning Moves
Games, Inc of Danvers, MA and the Barnes & Noble
Bookstore at Boston University for the games and prizes
donated as incentive gifts for study participants.
1. Focus on childhood obesity. Institute of Medicine, The National Acad-
emies. http://www.iom.edu/CMS/22593.aspx. Accessed June 22, 2007.
2. Institute of Medicine, Committee on Progress in Preventing Child-
hood Obesity. Progress in Preventing Childhood Obesity: How Do
We Measure Up? Washington, DC: National Academies Press; 2007.
3. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal
KM. Prevalence of overweight and obesity in the United States, 1999-
2004. JAMA. 2006;295:1549-1555.
4. Daniels S, Arnett D, Eckel R, Gidding S, Hayman L, Kumanyika S.
Overweight in children and adolescents: Pathophysiology, conse-
quences, prevention, and treatment. Circulation. 2005;111:1999-
5. Birch L, Fisher J. Development of eating behavior in children and
adolescents. Pediatrics. 1998;101:539-549.
6. US Department of Agriculture. The Food Guide Pyramid. Home and
Garden Bulletin No. 252. Hyattsville, MD: Human Nutrition Infor-
mation Service, August 1992.
7. US Department of Agriculture. The school environment: Helping stu-
dents learn to eat healthy. Washington, DC: USDA Food and Nutrition
Service, 2000. http://www.fns.usda.gov/tn/resources/helpingstudents.
html. Accessed June 1, 2008.
8. Eaton D, Kann L, Kinchen S, Ross J, Hawkins J, Harris W, Lowry R,
McManus T, Chyen D, Shanklin S, Lim C, Grunbaum J, Wechsler H.
Youth risk behavior surveillance—United States, 2005. J Sch Health.
9. American Academy of Pediatrics. Children, adolescents, and T.V.
10. US Department of Agriculture. Nutrient intakes from food: Mean
amounts and percentages of calories from protein, carbohydrate, fat,
and alcohol, one day, 2003-2004. Beltsville, MD: Agricultural Re-
search Service; 2007. Available at www.ars.usda.gov/ba/bhnrc/fsrg.
Accessed June 1, 2008.
11. Devaney B, Gordon A, Burghardt J. Dietary intakes of students. Am J
Clin Nutr. 1995;61(suppl):205S-212S.
12. Driskell MM, Dyment S, Mauriello L, Castle P, Sherman K. Relation-
ships among multiple behaviors for childhood and adolescent obesity
prevention. Prev Med. 2008;46:209-215.
13. Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal
KM. Prevalence of overweight and obesity among US children, ado-
lescents and adults, 1999-2002. JAMA. 2004;291:2847-2850.
14. Commonwealth of Massachusetts, Ofﬁce of Health and Human Ser-
vices. Physical Examination of School Children. Massachusetts Gen-
eral Laws (MGL) c71, s57 (Regulations) 105 CMR 200.500: Annual
Assessment of Physical Growth and Development. http://www.mass.
gov. Accessed June 1, 2008.
15. Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran MI,
Dietz WH. Validity of body mass index compared with other body-
composition screening indexes for the assessment of body fatness in
children and adolescents. Am J Clin Nutr. 2002;75:978-985.
16. National Center for Health Statistics. 2000 CDC Growth Charts:
United States. http://www.cdc.gov/growthcharts. Accessed August 23,
17. Institute of Medicine. Preventing Childhood Obesity: Health in the
Balance. Washington, DC: National Academies Press; 2005.
18. Rockett HR, Wolf AM, Colditz GA. Development and reproducibility
of a food frequency questionnaire to assess diets of older children and
adolescents. J Am Diet Assoc. 1995;95:336-340.
19. Rockett HR, Breitenbach M, Frazier AL, Witschi J, Wolf AM, Field
AE, Colditz GA. Validation of a youth/adolescent food frequency ques-
tionnaire. Prev Med. 1997;26:808-816.
20. Schakel SF, Sievert YA, Buzzard IM. Sources of data for developing
and maintaining a nutrient database. J Am Diet Assoc. 1988;88:1268-
21. Wolf AM, Hunter DJ, Colditz GA, Manson JE, Stampfer MJ, Corsano
KA, Rosner B, Kriska A, Willett WC. Reproducibility and validity of a
self-administered physical activity questionnaire. Int J Epidemiol.
22. Peterson KE, Field AE, Fox MK, Black B, Simon DS, Bosch RB.
Validation of the Youth Risk Behavior Surveillance Survey (YRBSS)
Questions on Dietary Intake and Physical Activity among Adolescents
in Grades 9 Through 12. Boston, MA: Harvard School of Public Health
to the Division of School and Adolescent Health at the Centers for
Disease Control and Prevention; 1996.
23. Rifas-Shiman SL, Gillman MW, Field AE, Frazier AL, Berkey CS,
Tomeo CA, Colditz GA. Comparing physical activity questionnaires
for youth. Seasonal vs annual format. Am J Prev Med. 2001;20:282-
24. Trost SG, Pate RR, Freedson PS, Sallis JF, Taylor WC. Using objec-
tive physical activity measures with youth: How many days of moni-
toring are needed? Med Sci Sports Exerc. 2000;32:426-431.
25. US Department of Health and Human Services. Dietary Guidelines
for Americans. Washington, DC: US Government Printing Ofﬁce;
2005. http://www.health.gov/DietaryGuidelines. Accessed June 1,
26. Institute of Medicine, National Academies. Dietary Reference Intakes
for Thiamin, Riboﬂavin, Niacin, Vitamin B6, Folate, Vitamin B12,
Pantothenic Acid, Biotin, and Choline. Washington, DC: National
Academies Press; 1998. http://www.nap.edu/catalog.php?record_
id⫽6015. Accessed June 1, 2008.
27. Institute of Medicine of the National Academy of Sciences. Dietary
Reference Intakes for Vitamin A, Vitamin K, Arsenic, Boron, Chro-
mium, Copper, Iodine, Iron, Manganese, Molybdenum, Nickel, Sili-
con, Vanadium, and Zinc. Washington, DC: National Academies
Press; 2001. http://www.nap.edu/catalog.php?record_id⫽10026. Ac-
cessed June 1, 2008.
28. Institute of Medicine of the National Academy of Sciences. Dietary
Reference Intakes for Vitamin C, Vitamin E, Selenium and Carote-
noids. Washington, DC: National Academies Press; 2000. http://www.
nap.edu/catalog.php?record_id⫽9810. Accessed June 1, 2008.
29. Institute of Medicine of the National Academy of Sciences. Dietary
Reference Intakes for Calcium, Phosphorus, Magnesium, Vitamin D
and Fluoride. Washington, DC: National Academies Press; 1997.
http://www.nap.edu/catalog.php?record_id⫽5776. Accessed June 1,
30. Institute of Medicine of the National Academy of Sciences. Dietary
Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids,
Cholesterol, Protein, and Amino Acids (Macronutrients). Washington,
DC: National Academies Press; 2005. http://www.nap.edu/catalog.
php?record_id⫽10490. Accessed June 1, 2008.
31. Institute of Medicine of the National Academy of Sciences. Dietary
Reference Intakes for Water, Potassium, Sodium, Chloride, and Sul-
fate. Washington, DC: National Academies Press; 2004. http://www.
nap.edu/catalog.php?record_id⫽10925. Accessed June 1, 2008.
32. US Department of Agriculture. MyPyramid. www.mypyramid.gov.
Accessed February 15, 2008.
33. Probart C, McDonnell E, Weirich J, Hartman T, Bailey-Davis L,
Prabhakher V. Competitive foods available in Pennsylvania public
high schools. J Am Diet Assoc. 2005;105:1243-1249.
34. American Academy of Pediatrics. Active healthy living: Prevention of
childhood obesity through increased physical activity. Pediatrics.
35. Choi BC, Pak AW, Choi JC, Choi EC. Daily step goal of 10,000 steps:
A literature review. Clin Invest Med. 2007;30:E146-E151.
36. President’s Council on Physical Fitness and Sports. The President’s
Challenge Physical Activity and Fitness Awards Program. Bloom-
ington, IN: President’s Council on Physical Fitness and Sports, US
Department of Health and Human Services; 2001. http://www.
presidentschallenge.org. Accessed June 1, 2008.
37. Tudor-Locke C, Pangrazi RP, Corbin CB, Rutherford WJ, Vincent SD,
Raustorp A, Tomson LM, Cuddihy TF. BMI-referenced standards for
recommended pedometer-determined steps/day in children. Prev Med.
38. Duncan JS, Schoﬁeld G, Duncan EK. Step count recommendations for
children based on body fat. Prev Med. 2007;44:42-44.
39. Pate R, Freedson P, Sallis J, Taylor W, Sirard J, Trost S, Dowda M.
Compliance with physical activity guidelines: Prevalence in a pop-
ulation of children and youth. Ann Epidemiol. 2002;12:303-308.
40. US Department of Health and Human Services. Physical Activity and
Health: A Report of the Surgeon General. Atlanta, GA: US Depart-
ment of Health and Human Services, Centers for Disease Control and
Prevention, National Center for Chronic Disease Prevention and
Health Promotion; 1999. http://www.cdc.gov/nccdphp/sgr/sgr.htm. Ac-
cessed June 1, 2008.
41. Centers for Disease Control and Prevention. Youth Risk Behavior
Surveillance—United States, 1999. MMWR. 2000;49(SS-5):1-95.
42. Sallis JF. Epidemiology of physical activity in children and adoles-
cents. Crit Rev Food Sci Nutr. 1993;33:403-408.
150 January 2009 Volume 109 Number 1
43. US Department of Health and Human Services. Healthy People 2010.
Washington, DC:US Government Printing Ofﬁce; 2000. http://www.
healthypeople.gov. Accessed June 1, 2008.
44. Nelson M, Neumark-Stzainer D, Hannan P, Sirard J, Story M. Lon-
gitudinal and secular trends in physical activity and sedentary be-
havior during adolescence. Pediatrics. 2006;118:e1627-e1634.
45. Francis L, Lee Y, Birch L. Parental weight status and girls’ television
viewing, snacking, and body mass indexes. Obes Res. 2003;11:143-
46. Gore S, Foster J, DiLillo V, Kirk K, Smith West D. Television viewing
and snacking. Eating Behav. 2003;4:399-405.
47. Robinson T, Killen J. Ethnic and gender differences in the relation-
ships between television viewing and obesity, physical activity, and
dietary fat intake. J Health Educ. 1995;26(suppl):S91-S98.
48. Lowry R, Wechsler H, Galuska D, Fulton J, Kann L. Television
viewing and its associations with overweight, sedentary lifestyle, and
insufﬁcient consumption of fruits and vegetables among US high
school students. J Sch Health. 2002;72:413-421.
49. Sanchez A, Norman G, Sallis J, Calfas K, Cella J, Patrick K. Patterns
and correlates of physical activity and nutrition behaviors in adoles-
cents. Am J Prev Med. 2007;32:124-130.
50. Zabinski M, Norman G, Sallis J, Calfas K, Patrick K. Patterns of seden-
tary behavior among adolescents. Health Psychol. 2007;26:113-120.
51. Motl R, McAuley E, Birnbaum A, Lytle L. Naturally occurring
changes in time spent watching television are inversely related to
frequency of physical activity during adolescence. J Adolesc. 2006;29:
52. Kremers S, De Bruijn G, Schaalma H, Brug J. Clustering of energy
balance-related behaviors and their intrapersonal determinants. Psy-
chol Health. 2004;19:595-606.
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