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DOI: 10.1542/peds.105.6.e83
2000;105;e83 Pediatrics
Penny Gordon-Larsen, Robert G. McMurray and Barry M. Popkin
Determinants of Adolescent Physical Activity and Inactivity Patterns
http://www.pediatrics.org/cgi/content/full/105/6/e83
located on the World Wide Web at:
The online version of this article, along with updated information and services, is
rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.
Grove Village, Illinois, 60007. Copyright © 2000 by the American Academy of Pediatrics. All
and trademarked by the American Academy of Pediatrics, 141 Northwest Point Boulevard, Elk
publication, it has been published continuously since 1948. PEDIATRICS is owned, published,
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Determinants of Adolescent Physical Activity and Inactivity Patterns
Penny Gordon-Larsen, PhD*; Robert G. McMurray, PhD‡; and Barry M. Popkin, PhD*§
ABSTRACT. Objectives. Despite recognition of the
important influence of environmental determinants on
physical activity patterns, minimal empirical research
has been done to assess the impact of environmental/
contextual determinants of physical activity. This article
aims to investigate environmental and sociodemographic
determinants of physical activity and inactivity patterns
among subpopulations of US adolescents. We define en-
vironmental determinants as modifiable factors in the
physical environment that impose a direct influence
on the opportunity to engage in physical activity. The
present research examines environmental and sociode-
mographic determinants of physical activity and inactiv-
ity with the implication that these findings can point
toward societal-level intervention strategies for increas-
ing physical activity and decreasing inactivity among
adolescents.
Study Design and Methodology. The study popula-
tion consists of nationally representative data from the
1996 National Longitudinal Study of Adolescent Health
on 17 766 US adolescents enrolled in US middle and high
schools (including 3933 non-Hispanic blacks, 3148 His-
panics, and 1337 Asians). Hours/week of inactivity (TV/
video viewing and video/computer games) and times/
week of moderate to vigorous physical activity were
collected by questionnaire. Outcome variables were
moderate to vigorous physical activity and inactivity,
which were broken into categories (physical activity: 0 –2
times/week, 3–4 times/week, and >5 times/week; inactiv-
ity: 0–10 hours/week, 11–24 hours/week, and >25 hours/
week). Sociodemographic and environmental correlates
of physical activity and inactivity were used as exposure
and control variables and included sex, age, urban resi-
dence, participation in school physical education pro-
gram, use of community recreation center, total reported
incidents of serious crime in neighborhood, socioeco-
nomic status, ethnicity, generation of residence in the
United States, presence of mother/father in household,
pregnancy status, work status, in-school status, region,
and month of interview.
Logistic regression models of high versus low and me-
dium physical activity and inactivity were used to investi-
gate sex and ethnic interactions in relation to environmen-
tal and sociodemographic factors to examine evidence for
the potential impact of physical education and recreation
programs and sociodemographic factors on physical activ-
ity and inactivity patterns.
Results. Moderate to vigorous physical activity was
lower and inactivity higher for non-Hispanic black and
Hispanic adolescents. Participation in school physical
education programs was considerably low for these ado-
lescents and decreased with age. Participation in daily
school physical education (PE) program classes (adjusted
odds ratio [AOR]: 2.21; confidence interval [CI]: 1.82–
2.68) and use of a community recreation center (AOR:
1.75; CI: 1.56–1.96) were associated with an increased
likelihood of engaging in high level moderate to vigor-
ous physical activity. Maternal education was inversely
associated with high inactivity patterns; for example,
having a mother with a graduate or professional degree
was associated with an AOR of .61 (CI: .48-.76) for high
inactivity. High family income was associated with in-
creased moderate to vigorous physical activity (AOR:
1.43; CI: 1.22–1.67) and decreased inactivity (AOR: .70; CI:
.59–.82). High neighborhood serious crime level was as-
sociated with a decreased likelihood of falling in the
highest category of moderate to vigorous physical activ-
ity (AOR: .77; CI: .66–.91).
Conclusions. These results show important associa-
tions between modifiable environmental factors, such as
participation in school PE and community recreation pro-
grams, with activity patterns of adolescents. Despite the
marked and significant impact of participation in school
PE programs on physical activity patterns of US adoles-
cents, few adolescents participated in such school PE
programs; only 21.3% of all adolescents participated in 1
or more days per week of PE in their schools. In addition
to the more readily modifiable factors, high crime level
was significantly associated with a decrease in weekly
moderate to vigorous physical activity.
The key modifiable factors that had an impact on phys-
ical activity did not affect inactivity. Thus, it is clear that
physical activity and inactivity were associated with very
different determinants. Although physical activity was
most associated with environmental factors, inactivity
was most associated with sociodemographic factors.
The data presented here confirm what researchers and
pediatricians have known intuitively; however, these re-
lationships have not been tested empirically, nor have
they been studied in any nationally representative sur-
vey of US school-aged children. These findings show
that patterns in inactivity cannot be explained using the
environmental factors studied here and, thus, it is clearly
important that researchers search for other environmen-
tal determinants likely to impact inactivity.
National-level strategies must include attention to
school PE and community recreation programs, particu-
larly for segments of the US population without access to
resources and opportunities that allow participation in
physical activity. Research to measure and explore the
effects of other environmental determinants of activity
and to ascertain whether there are any environmental
determinants of inactivity are important future research
directions. Pediatrics 2000;105(6). URL: http://www.
pediatrics.org/cgi/content/full/105/6/e83; physical educa-
From the *Carolina Population Center, ‡Department of Exercise Physiology,
and §Department of Nutrition, School of Public Health, University of North
Carolina, Chapel Hill, North Carolina.
Received for publication Sep 14, 1999; accepted Jan 12, 2000.
Reprint requests to (P.G.-L.) University of North Carolina at Chapel Hill,
Carolina Population Center, CB 8120 University Square, 123 W Franklin St,
Chapel Hill, NC 27516-3997. E-mail: gordon_larsen@unc.edu
PEDIATRICS (ISSN 0031 4005). Copyright © 2000 by the American Acad-
emy of Pediatrics.
http://www.pediatrics.org/cgi/content/full/105/6/e83 PEDIATRICS Vol. 105 No. 6 June 2000 1of8
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tion, community recreation center, US adolescents, crime,
socioeconomic factors, National Longitudinal Study of
Adolescent Health.
ABBREVIATIONS. PE, physical education; Add Health, National
Longitudinal Study of Adolescent Health; MET, metabolic equiv-
alent; AOR, adjusted odds ratio; CI, confidence interval.
A
dolescent overweight is a major US public
health problem, with prevalence rates in-
creasing for children and adolescents,
1
partic-
ularly for minority ethnic groups.
1,2
Minority adoles-
cents have consistently high levels of inactivity and
low levels of physical activity; these trends are exag-
gerated for females.
3–5
Inactivity and activity are important biological de-
terminants of obesity and represent major avenues
for treating and preventing obesity.
6–8
Physical activ-
ity has been associated with a wide range of benefi-
cial health outcomes in adults, including bone and
cardiovascular health and reduction of selected can-
cers.
9
Inactivity, in particular, TV viewing, has been
associated with obesity in cross-sectional studies of
children, adolescents, and adults.
10
Physical activity
habits, and, specifically, inactivity, track significantly
from adolescence to young adulthood.
11
The physical activity literature has examined en-
vironmental determinants such as school and com-
munity sports and home access to fitness equip-
ment,
12,13
perceived physical environments,
14
outdoor
play spaces,
15
time spent outdoors,
16,17
exercise op-
portunity,
18
and “an environment that promotes ex-
cessive food intake and discourages physical activi-
ty.”
19
A review of this topic concludes that little
attention has been given to ecological determinants
(eg, availability of facilities for activity and physical
safety) and broader sociocultural determinants, in-
cluding the influence of ethnicity on activity inde-
pendent of confounding sociocultural factors.
20
Sev-
eral researchers have suggested that school physical
education (PE) programs and community recreation
facilities are needed; however, little empirical re-
search has been done to determine the impact of such
facilities and programs on physical activity and in-
activity levels of American adolescents.
21
Furthermore, a literature review suggests that re-
searchers often focus on univariate (as opposed to
multivariate) relationships between single determi-
nants and physical activity,
22
despite the fact that
physical activity has been shown to be influenced by
the interaction among several factors.
21,23
In the present article, we define environmental
determinants as modifiable factors in the physical
environment that impose a direct influence on the
opportunity to engage in physical activity. The
present research examines environmental and socio-
demographic determinants of physical activity and
inactivity with the implication that these findings can
point toward societal-level intervention strategies for
increasing physical activity and decreasing inactivity
among US adolescents.
METHODS
Survey Design
The study population consists of over 20 000 adolescents en-
rolled in the National Longitunital Study of Adolescent Health
(Add Health), a longitudinal, nationally representative, school-
based sample of adolescents in grades 7 through 12 (ages: 11–21
years) in the United States. The Add Health study included a core
sample and additional subsamples of selected ethnic and other
groupings collected following informed consent procedures estab-
lished by the institutional review board of the University of North
Carolina at Chapel Hill. We used the wave I sample (20 747
eligible adolescents measured between April 1995 and December
1995), excluding adolescents who used a walking aid device (eg,
cane, crutches, and wheelchair) and Native Americans (n ⫽ 178)
because of small sample size. Our final sample totaled 17 766 for
prevalence estimates and logistic regression analysis. The survey
design and sampling frame have been described elsewhere.
2,3
In-school and in-home surveys of adolescents provided the
activity data and components of the determinants data. In-home
surveys of parents provided income, education, and other key
sociodemographic data. Community data were collected from
many sources, including 1993 Uniform Crime Reports, US Federal
Bureau of Investigation. Race and ethnicity were determined us-
ing data from a combination of all the surveys.
Physical Activity/Inactivity
Moderate to vigorous physical activity (5–8 metabolic equiva-
lents [METs]) and inactivity were assessed using standard 7-day
recall (times/week) questionnaire methodology relevant for epi-
demiologic studies.
4,5,24–26
The assessment employed an array of
questions similar to those used and validated in many other
smaller studies to categorize adolescents into high, medium, and
low activity and inactivity patterns with reasonable reliability and
validity. The Add Health adolescents were asked about the times/
week spent in various physical activities (eg, “During the past
week, how many times did you go roller-blading, roller-skating,
skate-boarding, or bicycling?”). Each activity grouping was as-
signed a MET value (1 MET ⫽ 3.5 mL O
2
/kg body weight/minute
or resting metabolic rate) based on the Compendium of Physical
Activity
27
developed for adults to categorize activity as low, mod-
erate, or vigorous. It is realized that the energy cost of activities is
⬃10% higher in children; however, at the present time no norms
exist for children. Higher intensity activities, such as skating,
cycling, dance, martial arts activities, and active sports, were
assigned 5 to 8 METs and are, thus, considered moderate to
vigorous physical activity.
Physical inactivity was assessed using standard 7-day recall
questionnaire methodology relevant for epidemiologic studies
4,5
used to categorize adolescents into high, medium, and low inac-
tivity patterns. The inactivity questions follow the same structure
as those validated for physical activity. The quantification of in-
activity has received far less attention than physical activity
28
and
there is little published in the literature regarding reliability and
validity of inactivity. In addition to the standard TV-viewing
question used in other studies (eg, number of hours of TV viewing
per week), Add Health elicited information on the number of
hours and minutes of video viewing and video/computer game
use during the past week. The quantification of inactivity is more
straightforward than that of physical activity, because there is no
concern with intensity and most sedentary activities have the
same relative energy cost. In this study, all 3 inactivity variables
were assigned 1 MET each. A composite inactivity score was
calculated using the number of hours and minutes that each
adolescent spent engaged in TV and video viewing and playing
video/computer games. This strategy ignores potential differ-
ences in METs for computer/video games versus TV and video
viewing, as well as differences attributable to advertisements seen
on TV but not in video viewing.
Study Variables
Outcome variables were moderate to vigorous physical activity
and inactivity, which were broken into categories (physical activ-
ity: 0–2 times/week, 3–4 times/week, and ⱖ5 times/week; inac-
tivity: 0–10 hours/week, 11–24 hours/week, and ⱖ25 hours/
week) for comparability to published data. Sociodemographic and
environmental correlates of physical activity and inactivity were
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used as exposure and control variables. These correlates included
gender, age (11–21 years), total household income (0-$26 200,
$26 200-$50 000, and ⱖ$50 000), maternal education (⬍high
school, high school/GED, some college, and college/professional
degree), ethnic group (non-Hispanic white, non-Hispanic black,
Hispanic [Cuban, Puerto Rican, Central/South American, Mexi-
can/Chicano, and other Hispanic], and Asian [Chinese, Filipino,
and other Asians]; ethnicity/race categorized from self-reports of
adolescents and their parents), ethnicity and sex interaction, gen-
eration of residence in United States (1st, 2nd, or 3rd generation),
urban residence, total reported incidents of serious crime per
100 000, (0–4796, 4800–7 139, and 7170–16 855), use of neighbor-
hood recreation center, number of days in an average week that
respondents attend PE classes at school (none, 1–4 days/week,
and 5 days/week), whether respondent works for pay, region
(Northeast, South, West, and Midwest), and month of interview.
Control variables included pregnancy status, whether respondent
was in school at time of interview, mother in household, father in
household, family income predicted (n ⫽ 3401; 19.1%), maternal
education predicted (n ⫽ 258; 1.5%). Data on family income and
maternal education were compiled using adolescent reports when
parent reports were missing. A predication equation was used to
estimate family income and maternal education when both parent
and adolescent information were missing. Major correlates of
interest are shown in Table 1.
Statistical Analysis
Statistical analyses were conducted using STATA (STATA, Chi-
cago, IL).
29
Poststratification sample weights were used in all
analyses to allow these results to be comparable with adolescents
attending schools in the United States. Survey design effects of
multiple stages of cluster sampling were also controlled for in all
analyses. Logistic regression models of physical activity and inac-
tivity were used to investigate sex and ethnic interactions in
relation to environmental and sociodemographic correlates of
physical activity and inactivity to examine evidence for the poten-
tial impact of these correlates (eg, PE programs and community
recreation facilities) on physical activity and inactivity patterns.
Models compare high activity (or inactivity) versus low and me-
dium activity (or inactivity), with non-Hispanic whites as the
reference category. Regression models were used to investigate
the association of environmental correlates of physical activity
with age, sex, and ethnicity.
RESULTS
Ethnicity and Gender
Table 2 presents the proportion of adolescents who
participated in low, moderate, and high categories of
physical activity. Among males, the proportion of
adolescents to participate in the highest category of
moderate to vigorous physical activity varied little
by ethnicity. In contrast, among females, a greater
percentage of non-Hispanic whites and Asians par-
ticipated in the highest category moderate to vigor-
ous physical activity, whereas the proportion was
smaller for non-Hispanic blacks and Hispanics.
Results for physical inactivity show greater ethnic
variability than for activity. Table 2 presents the pro-
portion of adolescents to participate in low, medium,
and high categories of weekly inactivity (TV/video
viewing and video/computer game use). The pro-
portion of adolescents to participate in the highest
category of inactivity was greatest for non-Hispanic
black males and females and Hispanic males and
females and was lowest for Asian and non-Hispanic
white females.
Environmental Determinants of Physical Activity
Table 3 shows the distribution of sociodemo-
graphic and environmental determinants of physical
activity and inactivity by ethnicity. Most adolescents
were not enrolled in PE courses at the time of survey
(78.7%) and only a fraction (14.6%) had PE classes on
5 or more days. Results varied by ethnicity; fewer
non-Hispanic whites had PE classes and a greater
proportion of Asians had PE. A small percentage of
adolescents used a neighborhood community recre-
ation center (19.6%) with the greatest percentage
seen for non-Hispanic blacks (23.6%). Results for PE
and recreation center use did vary by sex; more
males were enrolled in PE classes and used commu-
nity recreation centers than females. Results show
that the highest percentage of non-Hispanic whites
(46.9%) lived in low crime areas, whereas the highest
percentage of non-Hispanic blacks (58.1%) and His-
panics (41.5%) lived in high crime areas. Maternal
education was lowest for Hispanics (44.7% had less
than a high school degree) and highest for Asians
(11.1%) and non-Hispanic whites (8.5%) with given
percentages of mothers with graduate or profes-
sional degrees. The greatest percentage of non-
Hispanic whites (38.1%) and Asians (34.8%) had high
family incomes, whereas the greatest percentage of
non-Hispanic black (58%) and Hispanic (52.5%) had
low family incomes.
School PE
Participation in school PE programs was substan-
tially associated with likelihood of engaging in mod-
erate to vigorous physical activity (Table 4). Having
PE 1 to 4 times per week was associated with an
increase of 44% in falling in the highest category of
moderate to vigorous physical activity (adjusted
TABLE 1. Sample Characteristics*
Correlate Proportion Number
Sex
Male 50.8% 8727
Female 49.2% 9039
Age
Mean age 15.5 ⫹⫺.12 11–21 y
Ethnicity/race
Non-Hispanic white 66.7% 9348
Non-Hispanic black 16.7% 3933
Hispanic 12.7% 3148
Asian 4.0% 1337
Maternal education
⬍ High school 16.2% 2993
High school/general education
development
32.4% 5297
Some college 25.8% 4512
College degree 13.3% 2623
Graduate/professional degree 7.6% 1496
Family income
Low ($0–$26 200) 32.3% 5798
Middle ($26.2–$50 000) 37.0% 6642
High ($50 000⫹) 30.6% 5326
Recreation center use
Use center 80.4% 14 083
Don’t use center 19.6% 3683
Weekly PE
0 times/wk 78.7% 13 962
1–4 times/wk 6.7% 1276
5 times/wk 14.6% 2528
Crime level (total crime/100 000)
Low (0–4 796) 37.4% 6189
Medium (4800–7139) 33.2% 6503
High (7170–16 855) 29.4% 5074
* Figures are weighted to be nationally representative.
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odds ratio [AOR]: 1.44; 95% confidence interval [CI]:
1.09–1.92; P ⱕ .01) and having PE 5 times per week
was associated with a substantial increase in likeli-
hood of falling in the highest category of moderate-
vigorous physical activity (AOR: 2.21; CI: 1.82–2.68;
P ⱕ .00001). Participation in PE was not significantly
associated with likelihood of engaging in high levels
of inactivity (Table 4).
We found marked differences in the patterns of PE
program participation by age and gender (Fig 1). For
example, 12-year-olds (24.7%) had a higher fre-
quency of PE, but this number decreased with age, so
that by 17 years of age, only 8.3% of adolescents had
PE 1 or more times per week. Males (15.3%) were
more likely than females (13.7%) to participate in PE
at least once per week. Regression analyses modeling
use of PE programs, using ethnicity, sex, age, and a
sex–ethnicity interaction, show that age (P ⱕ .00001);
sex (P ⱕ .012); and Non-Hispanic black (P ⱕ .010),
Asian (P ⱕ .005), and Hispanic (P ⱕ .014) ethnicity
(but not sex–ethnicity interactions) were important
factors in PE use.
Neighborhood Community Recreation Centers
Use of a community recreation center also had a
marked association with likelihood of engaging in
moderate to vigorous physical activity (Table 4). Us-
ing a recreation center was associated with a 75%
increase in the likelihood of falling in the highest
category of moderate to vigorous physical activity
(AOR: 1.75; CI: 1.56–1.96; P ⱕ .00001). As with school
PE, inactivity did not vary with use of a community
recreation center (Table 4). Recreation center use was
modeled similarly to that described above for PE use.
Results show that sex (P ⱕ .021), non-Hispanic black
ethnicity (P ⱕ .006) and its sex interaction (P ⱕ .005),
and the interaction between Hispanic ethnicity and
sex (P ⱕ .018) were important factors in recreation
center use.
Total Reported Incidents of Serious Crime
High crime levels were associated with a decrease
in the likelihood of falling in the highest category of
moderate to vigorous physical activity (AOR: .77; CI:
.66-.91; P ⱕ .002), although the magnitude of this
association was not as great as that seen for school
TABLE 2. Weighted Proportion of Adolescents Participating in Given Categories of Physical Activity and Inactivity*
Activity Level Non-Hispanic
Whites
Non-Hispanic
Blacks
Hispanics Asians
Males Females Males Females Males Females Males Females
Moderate to vigorous physical activity
Low 26.5 37.3 24.9 46.8 24.9 42.6 21.1 37.6
Medium 30.1 34.2 34.1 34.3 31.6 35.9 31.0 34.3
High 43.4 28.5 41.0 18.9 43.4 21.4 47.9 28.0
Composite inactivity
Low 29.5 42.0 22.0 28.5 27.7 36.2 27.2 40.1
Medium 34.9 35.2 26.4 26.8 32.9 29.7 36.9 30.9
High 35.6 22.8 51.6 44.7 39.4 34.0 35.9 28.9
* Results are weighted to be nationally representative and standard error terms are adjusted for complex survey design effects.
TABLE 3. Sociodemographic and Environmental Determinants of Physical Activity and Inactivity*
Variable Non-Hispanic Whites
n ⫽ 9348
% (SE)
Non-Hispanic Blacks
n ⫽ 3933
% (SE)
Hispanic
n ⫽ 3148
% (SE)
Asian
n ⫽ 1337
% (SE)
PE d/wk
0 d/wk 80.9 (1.4) 75.2 (3.1) 74.5 (2.4) 70.6 (3.1)
1–4 d/wk 6.4 (1.1) 6.5 (1.4) 7.8 (1.7) 8.6 (3.4)
5 d/wk 12.6 (1.2) 18.3 (2.9) 17.7 (2.2) 20.8 (4.0)
Recreation center use
Use center 18.9 (1.3) 23.6 (2.1) 18.5 (1.0) 18.2 (2.2)
Don’t use center 81.1 (1.3) 76.4 (2.1) 81.5 (1.0) 81.8 (2.2)
Total incidents serious
Crime/100 000
0–4795 46.9 (5.7) 14.3 (4.0) 19.7 (5.7) 32.0 (11.7)
4800–7139 32.7 (5.0) 27.5 (6.7) 38.8 (8.1) 47.2 (11.8)
7170–16 855 20.4 (4.1) 58.1 (7.3) 41.5 (8.5) 20.8 (6.7)
Maternal education
Less than high school 10.1 (.9) 19.0 (2.1) 44.7 (3.5) 20.6 (4.2)
High school/general education development 34.1 (1.3) 35.4 (1.8) 23.1 (1.9) 20.6 (2.0)
Some college 28.2 (.9) 24.5 (1.5) 17.7 (1.3) 16.6 (2.6)
College degree 14.7 (.9) 10.0 (.9) 6.2 (.8) 26.6 (3.1)
Graduate professional degree 8.5 (.9) 6.4 (1.3) 3.5 (.8) 11.1 (1.7)
Family income
$0–$26 200 22.6 (1.8) 58.0 (2.9) 52.5 (3.1) 24.5 (3.1)
$26 200–$50 000 39.3 (1.1) 29.3 (1.8) 33.8 (1.9) 40.7 (3.2)
$50 000 38.1 (2.2) 12.7 (1.6) 13.7 (1.8) 34.8 (3.0)
SE indicates standard error.
* Results are weighted to be nationally representative and standard error terms are adjusted for complex survey design effects.
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PE or community recreation center use (Table 4).
High crime was associated with an increase in the
likelihood of engaging in high levels of inactivity;
however, this association was not significant (Table
4). Again, crime was modeled similarly to that de-
scribed above for PE use and was very clearly asso-
ciated with non-Hispanic black (P ⱕ .00001) and
Hispanic (P ⱕ .00001) ethnicity, but there were no
significant age, sex, and sex–ethnicity interactions.
Seasonality and Region
Classic work on environmental determinants of
physical activity has focused on season and region of
residence. Our results do not show major effects of
seasonality and region. For physical activity, there
was no relationship with month during which activ-
ity patterns were measured, and, thus, no evidence
of a seasonality effect. However, there was a signif-
icant association with residence in the Northeast re-
gion (AOR: 1.27; CI: 1.05–1.56; P ⱕ .015). For com-
posite inactivity, there was no region effect. There
was a significant association with inactivity mea-
sured during July (AOR: 1.32; CI: 1.09–1.68; P ⱕ .006)
with inactivity.
Sociodemographic Determinants of Physical Activity
Maternal Education
High level of maternal education (adolescents with
mothers who had graduate or professional degrees)
was significantly associated with increased likeli-
hood of having high levels of moderate to vigorous
physical activity (AOR: 1.27; CI: 1.01–1.60; P ⱕ .045).
At other levels, maternal education was not signifi-
cantly associated with high category of moderate to
vigorous physical activity, although likelihood of
falling in the highest category of moderate to vigor-
ous physical activity increased with maternal educa-
tion (Table 5). Conversely, having a mother with
some college education (AOR: .84; CI: .72-.99; P ⱕ
.044), a college degree (AOR: .80; CI: .66–.98; P ⱕ
.028), or having a graduate or professional degree
(AOR: .61; CI: .48-.76; P ⱕ .00001) was associated
with decreased likelihood of engaging in high levels
of inactivity (Table 5).
Family Income
Family income was associated with both physical
activity and inactivity (Table 5). Adolescents from
households with highest family income had an in-
creased likelihood of falling in the highest category
of moderate to vigorous physical activity (AOR: 1.43;
CI: 1.22–1.67; P ⱕ .00001) and decreased likelihood of
falling in the highest category of inactivity (AOR: .70;
CI: .59–.82; P ⱕ .00001). In addition, adolescents of
Fig 1. Weighted percentage of US adolescents who participate in
school PE programs. Weighted to be nationally representative
with the error terms corrected for design effects.
TABLE 4. AORs for Risk of High Levels of Physical Activity and Inactivity Among Given Environmental Contexts*†
Context AOR 95% CI P Value
Highest category of moderate to vigorous physical activity
PE times/wk
0 times/wk 1.00 — —
1–4 times/wk 1.44 1.09–1.92 .01
5 times/wk 2.21 1.82–2.68 .00001
Recreation center use
Don’t use center 1.00 — —
Use center 1.75 1.56–1.96 .00001
Total crime/100 000
Low 1.00 — —
Medium .89 .78–1.02 NS
High .77 .66–.91 .002
Highest category of inactivity
PE times/wk
0 times/wk 1.00 — —
1–4 times/wk .92 .75–1.13 NS
5 times/wk .96 .82–1.14 NS
Recreation center use
Don’t use center 1.00 — —
Use center 1.01 .89–1.13 NS
Total crime/100 000
Low 1.00 — —
Medium 1.11 .94–1.32 NS
High 1.13 .98–1.60 NS
NS indicates not significant.
* Adjusted using logistic regression models controlling for sex, age, urban residence, socioeconomic status, ethnicity, generation of
residence in the United States, presence of mother/father in household, pregnancy status, in-school status, work status, region, and month
of interview.
† Results are weighted to be nationally representative and standard error terms are adjusted for complex survey design effects.
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medium family income were at increased likelihood
of falling in the highest category of moderate to
vigorous physical activity (AOR: 1.19; CI: 1.04–1.36;
P ⱕ .013).
Interactions Between Ethnicity and Sex and Determinants
Logistic regression models were used to test sex
and ethnicity interactions with each set of environ-
mental determinants (PE participation, recreation
center use, and neighborhood crime). Differential ef-
fects were seen only for inactivity for neighborhood
crime and sex and recreation center and race. Fe-
males living in high crime areas were at increased
likelihood of falling in the highest category of inac-
tivity (AOR: 1.29; CI: 1.03–1.62; P ⱕ .027). Non-
Hispanic black ethnicity and recreation center use
were associated with an increase in likelihood of
inactivity (AOR: 1.61; CI: 1.22–2.11; P ⱕ .001).
Effect of Determinants on Physical Activity and Inactivity
Among Subpopulations
The above analysis, repeated using the subpopu-
lation groups of Hispanics (Cuban, Puerto Rican,
Central/South American, Mexican/Chicano, and
other Hispanics) and Asians (Chinese, Filipino, and
other Asians) showed small and nonsignificant dif-
ferences for physical activity. Adjusted odds ratios
for inactivity were significant for Filipino (AOR: 1.71;
CI: 1.05–2.80; P ⱕ .032), non-Hispanic black (AOR:
1.86; CI: 1.54–2.24; P ⱕ .0001), and Puerto Rican
(AOR: 1.46; CI: 1.10–1.95; P ⱕ .009) adolescents.
DISCUSSION
Add Health, a unique survey with its rich sample
of ethnic subpopulations and detailed activity and
inactivity, sociodemographic, and environmental
data, investigates modifiable physical activity deter-
minants vitally important to current efforts to in-
crease physical activity among our nation’s adoles-
cents. The high levels of obesity and inactivity and
low levels of physical activity illustrate the public
health importance of this analysis.
3
The results fit well with US teen obesity patterns.
2
Inactivity was highest and physical activity lowest
for non-Hispanic black and Hispanic adolescents.
These trends were exaggerated for females and older
adolescents.
PE Matters but Few Participate
The national push away from comprehensive PE
in US schools is remarkable.
8
Although our results
show important associations between participation
in PE and activity patterns, particularly on a daily
basis, few teens receive PE. Our results indicate that
PE classes may represent the only opportunity for
many adolescents to engage in weekly physical ac-
tivity. Conversely, the number of PE classes per
week was not associated with level of inactivity of
these adolescents. As shown, age, sex, and ethnicity
were important factors in PE use. Clearly, these are
modifiable relationships. Indeed, the Child and Ad-
olescent Trial for Cardiovascular Health has shown
that a program aimed at improving school PE has
been successful in increasing moderate to vigorous
physical activity in PE classes.
30
Logistic regression results show a strong impact of
PE programs on physical activity patterns. To place
these results in context of potential program out-
come, simulations run from the logistic regression
models (Tables 4 and 5) show increases in adjusted
proportion of adolescents participating in the highest
category of moderate to vigorous physical activity by
number of days of PE per week. For example, the
adjusted proportion of adolescents to fall in the high-
est category of moderate to vigorous physical activ-
ity increases from 30.3% for those adolescents with
no weekly PE to 37.6% for those having PE 1 to 4
times per week and to 46.8% for those having PE 5
times per week. This represents a marked increase in
the percentage of adolescents who would be partic-
ipating in substantial levels of weekly moderate to
vigorous physical activity.
Community Recreation Facilities Might Offer a Key
Intervention
Adolescents who used a community recreation
center (as with those in PE) reported markedly
higher levels of moderate to vigorous physical activ-
ity than those who did not. As indicated, sex, non-
Hispanic black ethnicity (with a strong ethnicity-sex
interaction) and Hispanic female ethnicity were im-
portant factors in community recreation center use.
TABLE 5. AORs for Risk of High Levels of Physical Activity
and Inactivity Among Given Sociodemographic Contexts*†
Context AOR 95% CI P Value
Highest category of moderate
to vigorous physical
activity
Maternal education
Less than high school 1.00 — —
High school/general
education development
.93 .79–1.12 NS
Some college 1.05 .88–1.25 NS
College degree 1.12 .90–1.38 NS
Graduate/professional
degree
1.27 1.01–1.60 .045
Family income
Low 1.00 — —
Medium 1.19 1.04–1.36 .013
High 1.43 1.22–1.67 .00001
Highest category of inactivity
Maternal education
Less than high school 1.00 — —
High school/general
education development
1.00 .87–1.45 NS
Some college .84 .72–.99 .044
College degree .80 .66–.98 .028
Graduate/professional
degree
.61 .48–.76 .00001
Family income
Low 1.00 — —
Medium .93 .82–1.05 NS
High .70 .59–0.82 .00001
NS indicates not significant.
* Adjusted using logistic regression models controlling for sex,
age, urban residence, socioeconomic status, ethnicity, presence of
mother/father in household, pregnancy status, in-school status,
work status, region, and month of interview.
† Results are weighted to be nationally representative and stan-
dard error terms are adjusted for complex survey design effects.
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Crime Reduces Physical Activity
Total number of incidents of serious crime in the
adolescents’ neighborhood was significantly associ-
ated with a decrease in physical activity. Crime was
also associated with an increase in inactivity, al-
though this relationship was not significant. Crime
was very clearly associated with ethnicity, but there
were no significant age, sex, and sex–ethnicity inter-
actions. However, logistic regression results showed
a differential association between high neighborhood
crime and increased inactivity (AOR: 1.29; CI: 1.03–
1.62; P ⱕ .027) for females relative to males.
Key Environmental Factors Do Not Reduce Inactivity
The key modifiable factors that had an impact on
activity did not affect inactivity. Thus, it is clear that
physical activity and inactivity were influenced by
very different determinants. Although physical ac-
tivity was most influenced by environmental factors,
inactivity was much more influenced by sociodemo-
graphic factors. Higher socioeconomic status mea-
sured by maternal education and family income had
a substantial impact on likelihood of engaging in
inactivity. Advanced education and high income
were associated with lower levels of inactivity.
Related Research
Other scholars have found that participation in
community sports is an important predictor of phys-
ical activity and have suggested the need for improv-
ing access to community-based physical activity op-
portunities,
13
health-oriented improvements in PE
programs,
31
daily PE programs that are fun and
stress lifelong physical activity habits,
19
and a possi-
ble role for clinicians in educating parents about
appropriate community play places.
15
This study has 1 limitation. The data on commu-
nity recreation centers were based on actual use, not
availability. Data on availability are unavailable in
any national database. This actual use response may
produce misleading results because physically active
people may be more likely to use recreation centers.
Additional research is needed to determine the types
of facilities that might offset the impact of crime on
physical activity and inactivity.
The data presented here confirm what researchers
and pediatricians have known intuitively; however,
these relationships have not been tested empirically,
nor have they been studied in any national dataset.
These findings show that patterns in inactivity can-
not be explained using the environmental factors
studied here and, thus, it is clearly important that
researchers search for other environmental determi-
nants likely to impact inactivity. This further dem-
onstrates the difficulty that researchers and pediatri-
cians face in developing public health efforts to
decrease inactivity.
The results of this study show the importance of
PE classes and recreation centers in increasing phys-
ical activity and give powerful evidence supporting
the importance of increasing opportunities for phys-
ical activity and the potential impact of PE programs
and community recreation programs on physical ac-
tivity of US adolescents. In addition, it is imperative
that we provide safe and accessible places for exer-
cise for our nation’s youth. In many communities,
the only such place may be the school.
Clearly our national public health initiatives
should consider these options. More research is
needed on the role of these factors in affecting activ-
ity and inactivity and on ways to most effectively
change them. PE and community recreation pro-
grams should receive attention at a national level,
particularly for segments of the population without
resources to locate and pay for extracurricular and
extracommunity physical activity opportunities.
Availability of such resources will increase success
for pediatricians in recommendations to patients to
increase physical activity and decrease inactivity.
This research also suggests that with increased op-
portunities for physical activity, adolescents may opt
to selectively engage in these activities instead of
more inactive behaviors.
ACKNOWLEDGMENTS
This work was supported in part by National Institute of Child
Health and Human Development Grant P01-HD31921 and the
Dannon Institute Postdoctoral Fellowship in Interdisciplinary Nu-
trition Science.
We thank Frances Dancy for her helpful administrative assis-
tance and Tom Swasey for assistance with the graphics.
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DOI: 10.1542/peds.105.6.e83
2000;105;e83 Pediatrics
Penny Gordon-Larsen, Robert G. McMurray and Barry M. Popkin
Determinants of Adolescent Physical Activity and Inactivity Patterns
& Services
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