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'A Review of Correlates of Physical Activity of Children and Adolescents'



Understanding the factors that influence physical activity can aid the design of more effective interventions. Previous reviews of correlates of youth physical activity have produced conflicting results. A comprehensive review of correlates of physical activity was conducted, and semiquantitative results were summarized separately for children (ages 3-12) and adolescents (ages 13-18). The 108 studies evaluated 40 variables for children and 48 variables for adolescents. About 60% of all reported associations with physical activity were statistically significant. Variables that were consistently associated with children's physical activity were sex (male), parental overweight status, physical activity preferences, intention to be active, perceived barriers (inverse), previous physical activity, healthy diet, program/facility access, and time spent outdoors. Variables that were consistently associated with adolescents' physical activity were sex (male), ethnicity (white), age (inverse), perceived activity competence, intentions, depression (inverse), previous physical activity, community sports, sensation seeking, sedentary after school and on weekends (inverse), parent support, support from others, sibling physical activity, direct help from parents, and opportunities to exercise. These consistently related variables should be confirmed in prospective studies, and interventions to improve the modifiable variables should be developed and evaluated.
A review of correlates of physical activity
of children and adolescents
Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA;
and University of Texas-Houston Health Science Center, Houston, TX
SALLIS, J. F., J. J. PROCHASKA, and W. C. TAYLOR. A review of correlates of physical activity of children and adolescents. Med.
Sci. Sports Exerc., Vol. 32, No. 5, pp. 963–975, 2000. Background: Understanding the factors that influence physical activity can aid
the design of more effective interventions. Previous reviews of correlates of youth physical activity have produced conflicting results.
Methods: A comprehensive review of correlates of physical activity was conducted, and semiquantitative results were summarized
separately for children (ages 3–12) and adolescents (ages 13–18). The 108 studies evaluated 40 variables for children and 48 variables
for adolescents. Results: About 60% of all reported associations with physical activity were statistically significant. Variables that were
consistently associated with children’s physical activity were sex (male), parental overweight status, physical activity preferences,
intention to be active, perceived barriers (inverse), previous physical activity, healthy diet, program/facility access, and time spent
outdoors. Variables that were consistently associated with adolescents’ physical activity were sex (male), ethnicity (white), age
(inverse), perceived activity competence, intentions, depression (inverse), previous physical activity, community sports, sensation
seeking, sedentary after school and on weekends (inverse), parent support, support from others, sibling physical activity, direct help
from parents, and opportunities to exercise. Conclusion: These consistently related variables should be confirmed in prospective
studies, and interventions to improve the modifiable variables should be developed and evaluated. Key Words: PSYCHOLOGY,
Important favorable health effects of physical activity for
adults are extensively documented and well accepted by
health professionals (8,11,13,22). The benefits of phys-
ical activity in youth are less well documented (14). How-
ever, reviewers have identified at least modest positive
effects in the population or subsamples of youth on such
health outcomes as aerobic fitness, blood lipids, blood pres-
sure, body composition, glucose metabolism, skeletal
health, and psychological health (14,16).
Three groups have issued guidelines specifically for
youth physical activity, and there is continuing debate over
the amount and types of activity needed for health benefits.
Recommendations tend to emphasize daily physical activity
and encourage young people to accumulate 30 to 60 mind
(3,5,16) ranging up to several hours per day (5). Because
sustained moderate to vigorous physical activity has been
associated with specific health benefits, this pattern of ac-
tivity has also been recommended (5,16). Other recommen-
dations have included activities to promote strength, flexi-
bility, bone health (3), and avoidance of extended periods of
inactivity (5).
Population surveys show that many young people are not
meeting the guidelines. Although about 80% of adolescents
are estimated to spend at least 30 mind
being active,
probably less than half are active at least 60 mind
About two-thirds of adolescent boys and one-quarter of
adolescent girls report doing 20 min of sustained moderate
to vigorous physical activity three times per week (12).
Studies using self-report measures usually find more phys-
ical activity than those using objective measures (12). Be-
cause physical activity has important health benefits in
youth and many young people are not meeting established
guidelines, improving the physical activity levels of youth is
an important public health challenge.
To develop effective physical activity interventions in
youth, influences on, and determinants of, activity levels
need to be well understood. Data from cross-sectional stud-
ies of association can help identify potential mediators of
physical activity that can be targeted for change in inter-
ventions. Baranowski et al. (1) argue interventions that
target strong and consistent modifiable correlates of behav-
ior should be more effective in changing behavior. There
have been several reviews of the correlates of youth physical
activity (6,15,19–21,23). However, these reviews were not
Copyright © 2000 by the American College of Sports Medicine
Submitted for publication May 1999.
Accepted for publication August 1999.
comprehensive, relied on narrative evaluations of the liter-
ature (except (21)), and restricted either the age of young
people or the categories of variables included in the reviews.
The present review evaluates comprehensively the pub-
lished studies of correlates of youth physical activity, in-
cludes the entire range of potential correlates, encompasses
young people aged 3–18 yr, makes a semiquantitative eval-
uation of the results, and compares results for young people
of primary school and secondary school ages. In addition to
summarizing methods and results of studies, gaps in the
literature are identified and directions for future research are
Computer searches (MEDLINE and PsychInfo) and man-
ual searches were conducted of articles in the English lan-
guage literature from 1970 to 1998. Inclusion criteria were
as follows: (a) subjects were in the age range of 3–18 yr, or
the mean age was in this range; (b) the dependent variable
was a measure of overall physical activity; and (c) variables
were tested for their association with physical activity. Ar-
ticles were excluded that had a primary focus on sports
participation, physical activity in controlled settings, labo-
ratory studies, case reports, expert opinion, unpublished
studies, and dissertations. The studies reviewed consisted of
school or community samples, used a variety of physical
activity measures reflecting a range of intensities, and in-
cluded both cross-sectional and prospective designs.
Detailed tables were created for coding selected study
characteristics and to record results for child (3–12 yr) and
adolescent (13–18 yr) studies, respectively. Some studies
had multiple dependent measures or reported multiple sub-
groups of subjects. In these cases, the most objective or most
inclusive measure of physical activity was chosen, the vig-
orous physical activity measure was selected (because va-
lidity was presumed to be higher than for other types of
activity), or specific findings were recorded separately. A
few studies reported results for both children and adoles-
cents, so age-specific results were reported for both age
In the detailed background table, the sample was de-
scribed by sex, age, and ethnicity, and the design was coded
as cross-sectional or prospective. The following categories
were used to code quality of the physical activity measure:
(a) self-report of poor or unknown reliability/validity, (b)
self-report with acceptable reliability/validity, and (c) ac-
ceptable objective measure. Finally, the variables were clas-
sified as “related” or “not related” to physical activity based
on statistical significance, and the direction of association
for related variables was coded. The full data tables are
available upon request from the authors, and all studies that
met review criteria are listed in the Bibliography.
The detailed data tables were further analyzed to create
tables that summarized the state of the literature for different
variables. The following coding rules were used to create
the summary tables.
Selection and categorization of variables. Vari-
ables are not shown in the summary tables unless three or
more comparisons were available. Some variables that were
conceptually similar were combined if there were not
enough studies to examine the variables individually. For
example, a “benefits” variable was created that includes
variables such as having fun and feeling healthy. For studies
that examined multiple benefits, multiple associations were
recorded and summarized under the general “benefits”
heading. Consistent with previous reviews of the adult de-
terminants literature, potential determinants were classified
into six categories: demographic/biological; psychological/
cognitive/emotional; behavioral attributes/skills; social/cul-
tural factors; physical environment.
Coding associations with physical activity. A va-
riety of statistical techniques were used to evaluate associ-
ations, most commonly correlations, t-tests, and ANOVAs.
Sometimes only multivariate analyses were reported, in-
cluding linear regression, logistic regression, and structural
equation modeling. The column “Related to physical activ-
ity” indicates which studies reported significant associations
between the variable and physical activity. Direction of
association is indicated with a “”or“.” The column
“Unrelated to physical activity” indicates which studies
reported nonsignificant associations between the variable
and physical activity. For the most part, articles reported
univariate tests assessing the significance of associations.
Thus, even if multivariate tests were conducted, univariate
tests were reported for consistency across studies.
Coding of analyses. Numbers in the columns refer to
numbers in the Bibliography. If analyses were conducted
separately for male and female subjects, “M” or “F” is
indicated. If analyses were conducted for different age sub-
groups or different time periods (baseline, follow-up), “I”
and “II” are used to indicate separate subgroup analyses.
Due to the small number of studies reporting analyses spe-
cific to ethnic or socioeconomic groups, these subgroup
analyses were not included in the summary tables.
Summary codes. The “Summary code” column con-
tains a code to summarize the state of the literature for that
variable. The percentages in parentheses refer to the number
of associations supporting the expected association divided
by the total number of associations for the variable. Based
on the percent of findings supporting the association, the
variable was classified as: no association, indeterminate/
inconsistent, positive association, or negative association
(see Table 1).
TABLE 1. Rules for classifying variables regarding strength of evidence of associa-
tion with physical activity.
% of Studies Supporting
Association Summary Code Meaning of Code
0–33 0 No association
34–59 ? Indeterminate, inconsistent
60–100 Positive association
Negative association
When four or more studies supported an association or no association, it was coded as
00, ⫹⫹,or⫺⫺. The ?? code indicated a variable that has been frequently studied with
considerable lack of consistency in the findings.
Official Journal of the American College of Sports Medicine
Tallies were also calculated to summarize characteristics
of the youth physical activity determinants literature, in-
cluding: mean sample size, number of studies reporting
sex-specific results, number of cross-sectional versus pro-
spective designs, and quality of physical activity measures.
Correlates of children’s physical activity. From
102 published papers, 54 studies of children were reviewed.
The child papers were published between 1976 and 1999,
with 76% of the studies published in the 1990s. Sample
sizes ranged from 20 to 1681, with a mean of 321 (SD
367). A cross-sectional design was used by 76%. Between
one and 31 variables were tested in each study, with a mean
of 5.9 (SD 6.1) variables. About 60% of reported asso-
ciations were statistically significant. Results were reported
for combined genders by 65%, separately by gender for
28%, and for female subjects only by 7%. Thirty percent of
studies had subjects from one race, and 26% did not report
the race or ethnicity of the subject sample. Only one study
reported racial/ethnic differences in associations (18). Over
80% of the studies were conducted in the United States.
Concerning the quality of the physical activity measure,
24% were unvalidated self-reports, 28% were empirically
supported self-reports, and 48% were objective measures.
Table 2 presents the studies reviewed categorized by sample
size and quality of physical activity assessment. Studies
with prospective designs are also identified; remaining stud-
ies are cross-sectional.
Table 3 summarizes associations between potential cor-
relates and physical activity that were examined in at least
three studies of children aged 4–12 yr. The review identified
11 demographic and biological variables, and seven were
studied three or more times. The most often studied variable
in the table was sex, and in 81% of comparisons, boys were
more active than girls. Body weight/adiposity and age were
frequently studied, but findings of negative associations
with physical activity were inconsistent for both variables.
Age was inconsistently related to physical activity within
this narrow age range. Indicators of socioeconomic status
were not related to children’s physical activity. Most studies
found ethnic minority children were as active as non-His-
panic whites. Surprisingly, overweight parents tended to
have more active children.
Fifteen psychological variables were reported, with 12
appearing in three or more studies. The most consistent
negative correlate was perceived barriers. Intention to be
physically active and preference for physical activity had
consistent positive associations. Several frequently studied
variables had no association: body image, self-esteem, per-
ceived benefits, attitudes toward sweating, and after school
activity. Self-efficacy, perceived competence, and atti-
tudes had indeterminate relations with children’s physical
Eighteen behavioral variables were studied, and six of
them appeared three times or more. Time in sedentary
pursuits, such as television viewing, was the most frequently
studied behavior, and its relation to physical activity was
indeterminate. Only healthy diet and previous physical ac-
tivity had consistent positive associations with physical ac-
tivity. Smoking, alcohol use, and calorie intake were unre-
lated to children’s physical activity.
Twenty-one social variables, mainly related to parent
influences, were studied, with nine appearing three or more
times. Parental physical activity was the most frequently
studied variable in this category, and 38% of 29 studies
showed a positive association with children’s physical ac-
tivity, resulting in an indeterminate summary code. Parent
participation in child physical activity was also indetermi-
nate. All of the other social variables were classified as no
Eleven physical environment variables were studied, with
six reported at least three times. Access to facilities and
programs and time spent outdoors were positively and con-
sistently related to children’s physical activity. Season and
milieu (rural/urban) were classified as indeterminate. Rated
TABLE 2. Child and adolescent studies categorized by sample size and quality of physical activity assessment.
Child Studies (Biblio. No.) Adolescent Studies (Biblio. No.)
Total sample size (
100 9, 22, 23, 24, 32, 34, 43, 45, 48, 49, 55, 58, 68, 84,
98, 100, 104
4, 11, 20, 53
100–199 10, 15, 17, 19, 30, 31, 38, 52, 62, 83, 96, 105 12, 19, 26, 28, 42, 65, 66, 67, 97, 103
200–299 37, 54, 64, 76, 78, 81, 87, 89 7, 8, 20, 20, 25, 57, 92, 93, 102
300–399 21, 59, 70, 82, 101 13, 39
400–499 47, 85, 91
500–999 46, 63, 73, 78, 80, 90, 95 6, 14, 16, 33, 35, 36, 40, 41, 72, 74, 77, 96, 107
1000–2999 60, 86, 94 2, 3, 14, 27, 44, 50, 51, 75, 79, 99, 108
3000–4999 1, 5, 61, 69, 106
500056, 71, 88
Physical activity measure
Self-report of poor or unknown reliability/validity 17, 21, 43, 46, 73, 76, 86, 87, 90, 91, 94, 95, 96, 98 1, 2, 4, 5, 6, 12, 13, 16, 18, 25, 27, 28, 33, 35,
36, 39, 44, 50, 51, 53, 56, 57, 61, 65, 66, 67,
69, 71, 74, 75, 79, 88, 92, 93, 96, 97, 99, 106
Self-report with acceptable reliability/validity 15, 19, 24, 37, 38, 60, 63, 70, 78, 78, 80, 83, 89, 101,
3, 14, 19, 20, 20, 20, 26, 40, 41, 42, 72, 77, 102,
103, 107, 108
Acceptable objective measure 9, 10, 22, 23, 30, 31, 32, 34, 45, 47, 48, 49, 52, 54,
55, 58, 59, 62, 64, 68, 81, 82, 84, 85, 100, 104
7, 8, 11
Prospective design 15, 17, 30, 38, 43, 58, 64, 68, 78, 80, 85, 87, 94 4, 13, 20, 26, 36, 74, 77
CORRELATES OF YOUTH PHYSICAL ACTIVITY Medicine & Science in Sports & Exercise
TABLE 3. Summary of studies of determinants of physical activity in children: based on studies including children aged 4–12.
Determinant Variable
Related to Physical Activity Unrelated to Physical Activity
(Biblio. No.)
Summary Code
Biblio. No. Assoc. (/) Assoc. % Studies
Demographic and biological factors
Age 9, 17, 43(F), 48(M, F), 64, 80, 90(M, F) 10, 19(F), 37, 43(M), 49, 63 ?? 9/19
19(M), 46, 70, 85 47%
Ethnicity (EuroAm) 59, 81(M, F), 82 10, 37, 68, 70, 80(I-M, F) ?? 4/11
Sex (Male) 9, 10, 15(II), 30, 37, 38, 43, 46, 47, 49,
52, 55, 59, 63, 70, 73, 80(I, II), 82, 85,
86, 87, 90, 91, 101
15(I), 19, 31, 48, 54, 68 ⫹⫹ 25/31
Socioeconomic status 32, 46(M, F), 47(M) 17, 47(F), 80(I-M, F), 81(M), 82, 90 00 4/13
52, 81(F)
Single parent status 81(M) 81(F) 0 1/4
80(I-M, F)
Body mass index 21, 22, 23, 47(M), 47(M), 48(M, F), 55,
81(M), 86(M, F), 95(M), 95(M), 105,
105, 105
46(M, F), 47(F), 47(F), 58, 82, 83, 85, 91, 95(F), 95(F),
100, 101
?? 16/31
54, 81(F)
Parent overweight/obesity 45, 54, 83 (dad) 31, 83(mom) 3/5
Psychological, cognitive, and
emotional factors
Self-esteem 17, 37, 80(I-M, F), 80(II-M, F) 00 0/6
Perceived competence (physical,
24, 32, 80(II-M, F) 37, 80(I-M, F) ?? 4/7
Self-efficacy 15(I), 70, 70, 101 15(II), 37, 70, 89(M, F) ?? 4/9
Body image 80(I-M, F), 80(II-M, F) 00 0/4
Attitudes, outcome expectation 15(I, II), 24, 38, 70, 80(I-M), 89(M, F) 70, 80(I-F), 80(II-M, F), 96(I), 98 ?? 8/14
Sweat attitudes 80(I-M, F), 80(II-M, F) 00 0/4
After school activity attitudes 80(I-M, F), 80(II-M, F) 00 0/4
Dislikes PE 96(I) 80(I-M, F), 80(II-M, F) 00 1/5
PA intention 80(I-M), 80(II-F), 98 80(II-M), 80(I-F) 3/5
PA preference 17, 80(I-M), 80(II-F) 80(I-F), 80(II-M) 3/5
Perceived benefits 37 17, 17, 17, 17, 17, 98 00 1/7
General barriers 37, 89(M, F) ⫺⫺3/3
Behavioral attributes and skills
Cigarette use 21 76, 96(I) 0 1/3
Alcohol use 21, 76, 96(I) 0 0/3
Healthy Diet 21, 96(I), 96(I) ⫹⫹3/3
Caloric intake 104 46, 85 0 1/3
Previous PA 38, 68, 94(M, F), 98 37 ⫹⫹ 5/6
Sedentary time (TV, video
10, 30, 70, 78(I-F), 80(I-M), 101 37, 46, 78(II-F), 80(I-F), 80(II-M), 82, 89(M, F) ?? 6/15
Social and cultural factors
Parent PA 17, 32, 34, 47(M), 62(M, F), 62(M, F), 73,
83, 84
34, 37, 47(F), 57(M, F), 70, 70, 80(I-M, F), 80(II-M, F),
81(M, F),
?? 11/29
89(F) 82, 89(M, F), 89(M)38%
Parent PA participation with
47(F), 80(I-M, F), 80(II-M), 89(M) 47(M), 80(II-F), 81(M, F), 89(F) ?? 5/10
Parent benefits of PA 57, 89(M, F) 0 0/3
Parent barriers to PA 57, 89(M, F) 0 0/3
Parental encouragement,
17, 55, 58, 80(II-M) 47(M, F), 54, 80(I-M, F), 80(II-F), 81(M, F), 98 00 4/13
Parent transports child 80(II-M), 81(M) 47(M, F), 80(II-F), 80(I-M, F), 82(F) 00 2/8
Official Journal of the American College of Sports Medicine
neighborhood safety and parents providing transportation to
a physical activity place were unrelated to activity level.
Correlates of adolescents’ physical activity. A to-
tal of 54 studies of potential correlates of physical activity
among adolescents aged 13–18 yr were reviewed. These
studies were published between 1970 and 1998, with 76% of
studies published in the 1990s. Sample sizes ranged from 51
to 7302, with a mean of 1286 (SD 1645). Eighty-three
percent of studies used a cross-sectional design. Studies
evaluated a range of 1 to 28 variables, with a mean of 7.4
(SD 6.1) variables. Sixty-two percent of variables had
statistically significant associations. Results were reported
for combined genders by 52% of studies, 43% of studies
reported associations separately by sex, and 6% had female-
only samples. Of the adolescent studies, 57% had samples of
one race only, 9% did not report race or ethnicity, and 7%
reported associations separately by race or ethnic group.
Sixty-eight percent of studies were conducted in the United
States. In the classification of physical activity measures,
69% were unvalidated self-reports, 28% were empirically
supported self-reports, and 4% were objective measures.
Table 2 presents the studies reviewed categorized by sample
size and quality of physical activity assessment. Studies
with prospective designs are also identified; remaining stud-
ies are cross-sectional.
Table 4 summarizes associations between potential cor-
relates and physical activity that were examined in at least
three studies of adolescents aged 13–18 yr. The review
identified nine demographic and biological variables, and
five were studied three or more times. The most consistently
supported finding in this group was that boys were more
active than girls, and 27 of 28 comparisons supported this
conclusion. A negative association between age and physi-
cal activity was found in 70% of the 27 comparisons. Eth-
nicity was consistently related, with non-Hispanic whites
being more active than other ethnic groups. Findings re-
garding adolescent body weight and adiposity were indeter-
minate, and socioeconomic status was unrelated to youth
physical activity.
Thirty-five psychological variables were reported, after
combining similar constructs, with 17 appearing three or
more times. Several types of perceived benefits were
grouped together, and of these 29 comparisons, only 38%
were significant and positive, making this association inde-
terminate. Barriers was the next most commonly studied
category of variables. Of the 15 comparisons, 33% were
significant, so barriers was classified as unrelated. Self-
efficacy was categorized as indeterminate, as were body
image, attitudes, knowledge, and enjoyment of physical
education. Variables found to have no association were talks
loudly, external locus of control, self-esteem, self-motiva-
tion, enjoys exercise, and perceived stress. Of the 17 psy-
chological variables, the only ones with consistent and pos-
itive associations with physical activity were achievement
orientation, perceived competence, and intention to be ac-
tive. Depression was the only psychological variable nega-
tively correlated with adolescent physical activity.
Of the 30 behavioral variables, 13 were reported three or
more times. The only consistently positive associations were
found for sensation seeking, previous physical activity, and
participation in community sports. Among the frequently
studied variables, cigarette smoking was indeterminate, al-
cohol use was unrelated, healthy diet was unrelated, and
sedentary time was unrelated. In contrast, sedentary behav-
ior after school and on weekends was consistently and
inversely related to adolescent physical activity.
Twenty-three social variables were assessed, with 10
reported three or more times. Parent physical activity levels
were reported most frequently, with 27 comparisons, but
results showed no association. However, measures of pa-
rental support, direct help from parents, and support from
“significant others” were consistently related to adolescent
TABLE 3. Continued.
Determinant Variable
Related to Physical Activity
Unrelated to Physical Activity
(Biblio. No.)
Biblio. No. Assoc. (/) Assoc.
Parent pays PA fees 80(II-M) 80(I-M, F), 80(II-F) 0 1/4
Subjective norms 70 37, 98 0 1/3
Peer influence 89(M) 70, 89(F) 0 1/3
Physical environment factors
Access to facilities/programs 37, 82, 89(F) 89 (M) 3/4
Parent provides transportation to PA 81(M) 47(M, F), 81(F) 0 1/4
Season (Summer/Spring) 38, 73 90 ? 2/4
Milieu (rural) 46(M), 87 46(F), 90 ? 2/4
Neighborhood safety 80(I-M, F), 80(II-M, F) 00 0/4
Time outdoors 10, 54, 82 ⫹⫹3/3
Ref. No., reference number; Assoc., association; , negative, , positive; 0, no relation; ?, indeterminate; EuroAm, European American; PA, physical activity; PE, physical education;
M, male; F, female; I, sample 1; II, sample 2.
CORRELATES OF YOUTH PHYSICAL ACTIVITY Medicine & Science in Sports & Exercise
TABLE 4. Summary of studies of determinants of physical activity in adolescents: based on studies including adolescents aged 13–18.
Determinant Variable
Related to Physical Activity Unrelated to
Physical Activity
(Biblio. No.)
Summary Code
Biblio. No.
(/) Assoc.
Demographic and biological factors
Age 3(F), 4(M, F), 5(F), 8(F), 14, 16, 19(M, F),
20(III), 36(M, F), 56, 69, 96, 103(M),
107(F), 108(M, F)
3(M), 8(M), 18, 41, 97, 103(F) ⫺⫺ 19/27 70%
5(M), 42
Ethnicity (EuroAm) 3(M, F), 5(M, F), 14, 44, 56, 69, 102(F),
97, 102(M), 108(M, F) ⫹⫹ 10/14 77%
Sex (Male) 3, 4, 5, 6, 7, 18, 19, 20(I, II, III), 33, 36,
40, 41, 42, 44, 50, 56, 69, 72, 74, 75,
88, 97, 102, 106, 108
103 ⫹⫹ 27/28 96%
Body mass
74(M, F), 75(M), 75(M, F), 107(F)
5(M), 108(F)
5(M, F), 5(F), 7, 14, 74(M, F), 75(F),
77(I-M, F), 77(II-M, F), 108(M)
00 6/21 29%
Socioeconomic status 44, 56, 56 3(M, F), 14, 36(F), 97 00 3/9 33%
Psychological, cognitive,
and emotional factors
Achievement orientation 27, 27, 69, 96(II, III) 96(I) ⫹⫹ 5/6 83%
Talks loudly 96(III) 96(I, II) 0 1/3 33%
External locus of control 35 35, 93(M) 00 1/4 25%
Self-esteem 33, 65(III) 11(M, F), 16, 28(M), 65(II) 00 2/9 22%
28(F), 65(I)
Perceived physical
28(F), 108(M, F) 11(M, F), 28(M), 69 ?? 3/7 43%
Self-efficacy 77(I-M, F), 77(II-M, F), 102(M), 108(M, F) 14, 26(M, F), 102(F), 102(M, F) ?? 7/13 53%
Attitudes, outcome
14, 16, 102(M) 65(I, II, III), 102(F) ?? 3/7 43%
Perceived competence 11(M), 33 11(F) 2/3 66%
Intention 35, 41, 77(I-M, F), 77(II-M, F) 12, 14 ⫹⫹ 6/8 75%
Self-motivation 93(F) 28(M, F) 0 1/3 33%
Likes PE 96(III), 102(F), 108(M, F) 16, 33, 96(I, II), 102(M) ?? 4/9 44%
Benefits of PA 33, 39(M, F), 39(M, F), 39(M, F), 39(F),
93(F), 97, 108(F)
14, 39(M), 39(M, F), 39(M, F), 39(M, F),
39(M, F), 39(M, F), 67, 93(F), 93(F),
93(M), 93(F), 108(M)
?? 11/29 38%
Enjoy exercise 14, 26(M, F), 39(M, F) 00 0/5 0%
Stress 66 13, 13, 77(II-M, F), 77(I-M, F) 00 1/7 14%
Depression 13, 57, 66 35 3/4 75%
General barriers 39(F), 92, 93(M), 102(M, F) 14, 13, 39(M), 67, 92, 92, 92, 92, 108(M, F) 00 5/15 33%
Knowledge of exercise/
12, 26(M, F), 44 14, 33, 67 ?? 4/7 57%
Behavioral attributes and
Sensation seeking 2, 79, 97 ⫹⫹3/3 100%
Fighting 69, 96(I, II, III) 00 0/4 0%
Cigarette use 2, 69, 74(M, F), 79, 99 14, 39(M, F), 96(I, II, III), 106(F), 108(M, F) ?? 6/15 40%
Chewing tobacco 96(II) 96(I, III) 0 1/3 33%
Alcohol use 69(F), 79
2, 39(M, F), 69(M), 92, 96(I, II, III),
108(M, F)
00 2/13 15%
Healthy diet 2, 74(M), 79, 96(I) 2, 74(M, F), 74(M), 96(I, II, III), 96(II, III),
96(I, II, III)
00 4/16 25%
Meal regularity 96(I, II) 2, 96(III) ? 2/4 50%
Previous PA 26(M), 41, 50(M, F), 74, 77(I-M, F), 77(II-
M, F), 103(M, F)
26(F) ⫹⫹ 11/12 92%
Community sports 14, 33, 96(I, II, III), 102(M, F) ⫹⫹7/7 100%
On school sports teams 69 102(M, F) 0 1/3 33%
Sedentary time (TV,
video games)
5(M), 14, 26(M(dad report)) 5(F), 26(M(mom)report)), 26(F(mom
report)), 26(F(dad report)), 102(M, F),
107(F), 108(M, F)
00 3/12 25%
Sedentary after school 96(I, II, III) ⫺⫺3/3 100%
Sedentary on weekend 96(I, II, III) ⫺⫺3/3 100%
Social and cultural factors
Parent activity/modeling 1(F), 41, 41, 42, 44, 71, 71, 71, 72 1(M, F), 1(M), 12, 14, 26(M, F), 26(M, F),
26(M, F), 42, 102(M, F), 102(M, F),
108(M, F)
00 9/27 33%
Sibling PA 1(M, F), 71, 72 ⫹⫹4/4 100%
Peer modeling 14, 102(M, F), 108(M, F) 00 0/5 0%
Direct parental help in
6(M, F), 108(F) 108(M) 3/4 75%
Parents support 16, 72 53 2/3 67%
Teacher support or
12, 39(M, F), 40, 108(M, F) 00 0/6 0%
Official Journal of the American College of Sports Medicine
physical activity. Sibling physical activity was consistently
related. Peer modeling of physical activity was unrelated,
and perceived support from peers was indeterminate. Sub-
jective norms, or perceived attitudes of significant others,
were often studied, but this variable was classified as inde-
terminate. There was no association with teacher or coach
support or modeling.
Seven variables in the physical environment category
were reported, and three had three or more comparisons.
Opportunities to exercise had consistently positive associa-
tions. Other variables were unrelated to adolescent physical
Comparison of children’s and adolescents’ find-
ings. Table 5 summarizes the number of variables studied
for each category and lists the variables with the strongest
evidence of association with children’s and adolescents’
physical activity. There was very little overlap in consis-
tently correlated variables for both age groups. The only
variables listed for both were sex (male), intention to be
active, and previous physical activity. In the physical envi-
ronment category, the variables of access to programs/fa-
cilities for children and opportunities to exercise for ado-
lescents appeared to be similar. Table 2 shows that
methodology differed across studies of children and adoles-
cents. Studies of adolescents had larger sample sizes
(F(1,107) 18.19, P0.001) and were more likely to use
self-report physical activity measures (
32.1, P
0.001). By contrast, almost half of the studies of children
used objective physical activity measures.
Additional analyses were conducted to examine relations
between methodological variables and proportion of signif-
icant associations in studies. The correlation between sig-
nificant associations and sample size was not significant for
children (r ⫽⫺0.06), but it was significant for adolescent
studies (r 0.29, P0.05). Quality of physical activity
measure was not related to proportion of significant asso-
ciations for either the child or adolescent studies. Of 40
variables studied with children, 23% were classified as
“consistently related,” which was not significantly different
from the 35% “consistently related” variables out of 48
studied in adolescents.
Identifying correlates of youth physical activity is con-
sidered to be of public health significance (22), because
such information could inform efforts that seek to increase
the proportion of young people who meet health-related
physical activity guidelines (17). Past narrative reviews
have been selective and have come to discrepant conclu-
sions (19,22). The most recent review that dealt with both
children and adolescents was the 1996 Surgeon General’s
Report on physical activity (22), and the conclusions are
somewhat different from those drawn from the present
semiquantitative review.
In the 1996 review the most consistent modifiable corre-
lates, as opposed to demographic factors, were identified as
self-efficacy, physical or sports competence, perceived ben-
efits, perceived barriers, intention, enjoyment, physical ed-
ucation attitudes, parental encouragement, direct help from
parents, peer and sibling support, access to play spaces and
equipment, and time spent outdoors. Multiple studies were
cited in support of each variable, and inconsistent associa-
tions between parent and child physical activity were also
noted (22). Of the 12 variables identified in the Surgeon
General’s Report, nine were confirmed as consistently as-
sociated with physical activity of children or adolescents in
the present review: perceived physical competence, inten-
tion, barriers, parent support, direct help from parents, sup-
port from significant others, program/facility access, oppor-
tunities to be active, and time outdoors.
As in previous reviews, significant variables were found
in all categories of correlates (19), supporting an interpre-
tation that youth physical activity is a complex behavior
determined by many factors. This result also supports eco-
logical models of behavior that posit behavioral influences
from personal (biological, psychological, behavioral), so-
cial, and physical environmental factors (17). The implica-
tion is that interventions must target changes in variables
from all categories to achieve substantial behavior change
(1). However, it was surprising that social correlates of
children’s physical activity was the only instance of a cat-
egory with no consistent correlates. Previous reviews have
concluded that social, especially parental, influences on
TABLE 4. Continued
Determinant Variable
Related to Physical Activity Unrelated to
Physical Activity
(Biblio. No.)
Summary Code
Biblio. No.
(/) Assoc.
Support from significant
6(M, F), 12, 16 ⫹⫹4/4 100%
Support from peers 39(F), 108(M) 14, 39(M), 108(F) ? 2/5 40%
Coach support/modeling 39(M), 108(F) 39(F), 108(M), 108(M, F) 00 2/6 33%
Subjective norms/Social
41, 77(I-M, F), 77(II-M, F), 102(M) 14, 67, 102(F), 108(M, F) ?? 6/11 55%
Physical environment
16 26(M, F), 92, 102(M, F), 108(M, F) 00 1/8 13%
Opportunities to exercise 39(M, F) 14 2/3 66%
Sports media influence 26(M) 14, 26(F) 0 1/3 33%
Ref. No., reference number; Assoc., association; , negative, , positive; 0, no relation; ?, indeterminate; EuroAm, European American; PA, physical activity; PE, physical education;
M, male; F, female; I, sample 1; II, sample 2; III, sample 3.
CORRELATES OF YOUTH PHYSICAL ACTIVITY Medicine & Science in Sports & Exercise
children’s activity are strong (19–21), but this more com-
prehensive review demonstrated a lack of consistency for
associations with social variables.
One of the most notable results may be the lack of
consistency across studies. Only about one-quarter to one-
third of variables examined more than three times met the
current definition of consistently related to child or adoles-
cent physical activity. Very few of these variables were
significant in all comparisons. Between 40 and 50% of
variables were found to have no association, although stud-
ies were rarely unanimous in reporting null findings. It may
be premature to dismiss all the variables in the no associa-
tion group, because methodological problems may be af-
fecting the results. About 20–28% of variables were placed
in the indeterminate category. It is particularly difficult to
draw conclusions about these variables, because approxi-
mately half the studies found an association and half did not.
The lack of consistency in findings could be due to differ-
ences in measurement or sample. There may be confounding
or moderating variables that need to be accounted for in
It is useful to consider some of the possible explanations
for the substantial inconsistencies. A possible explanation is
measurement error. It is challenging to measure physical
activity in young people, and all available measures have
substantial error and known limitations (10). Fewer signif-
icant associations would be expected in studies that relied on
unvalidated self-report measures. However, no association
was found between the quality of the physical activity
measure and the proportion of significant associations in the
studies of either children or adolescents.
Sample size has a direct bearing on likelihood of declar-
ing a statistically significant result. The expected moderate
correlation between sample size and proportion of signifi-
cant associations was documented in the adolescent studies,
but sample size did not appear to impact results of the child
Another reason for the inconsistent findings may be sam-
ple characteristics. Two studies could use the same mea-
sures and protocols on samples of the same size, but if one
sample is from a high-income population and the other
sample is low-income, then different findings could be
obtained. The effect of sample characteristics on correlates
of youth physical activity is an important question, but it has
not been explored systematically. It would be valuable for
studies to report on subgroups within the same study that
differ on ethnicity, socioeconomic status, and environmental
characteristics (e.g., urban vs rural). There may be different
correlates of physical activity for boys and girls. Although
sex-specific analyses are sometimes reported, there are too
few studies using the same variables to permit sex compar-
isons in the present review.
Different analysis strategies can also affect results. Most
studies reported bivariate associations using correlations,
t-tests, or ANOVAs. Thus, bivariate results were used when
available to construct the summary tables. Some studies
used multivariate techniques such as linear regression, lo-
gistic regression, or LISREL. A typical finding is that fewer
variables are significant in multivariate analyses than in
bivariate analyses, so there is a bias toward null findings
from studies that reported only multivariate results.
Measurement error, variation in sample size, differences
in sample characteristics, and different analysis strategies all
increase the likelihood of inconsistent findings across stud-
ies. Thus, the variables whose associations with physical
activity were supported by multiple studies should be inter-
TABLE 5. Comparison of variables consistently associated with child and adolescent physical activity.
Category of Variable Child Results Adolescent Results
Demographic, biological
No. of variables 3 comparisons 7 5
Variables consistently related to PA Sex (male) ⫹⫹ Sex (male) ⫹⫹
Parent overweight Ethnicity (white) ⫹⫹
Age ⫺⫺
Psychological, cognitive, emotional
No. of variables 3 comparisons 12 17
Variables consistently related to PA PA preference Achievement orient. ⫹⫹
Intention Intention ⫹⫹
Barriers Perceived physical competence
Behavioral attributes and skills
No. of variables 3 comparisons 6 13
Variables consistently related to PA Previous PA Previous PA ⫹⫹
Healthy diet Community sports ⫹⫹
Sensation seeking
Sedentary after school
Sedentary on weekends
Social and cultural
No. of variables 3 comparisons 9 10
Variables consistently related to PA None Parent support ⫹⫹
Support from significant others ⫹⫹
Sibling PA ⫹⫹
Direct help from parents
Physical environment
No. of variables 3 comparisons 6 3
Variables consistently related to PA Program/facility access Opportunities to exercise
Time outdoors
PA, physical activity; ,⫹⫹, positive association; ,⫺⫺, negative association.
Official Journal of the American College of Sports Medicine
preted carefully. The most frequent and most consistent
finding was that boys are more active than girls. This result
supports data from population studies (12,22) and implies
that special efforts are needed to increase physical activity in
girls. For adolescents only, non-Hispanic whites were more
active than other ethnic groups, and this has also been found
in epidemiologic studies (22). There is continuing debate
over the extent to which ethnic differences in health out-
comes and health behaviors are due to the confounding
effect of socioeconomic status. In this review, socioeco-
nomic indicators were not related to physical activity, but
this complex variable was not included in many studies. Age
was expected to be a strong correlate of physical activity
(22), but this was only found for adolescents. The lack of
consistent findings in children may be due to the tendency
for the children’s studies to include a narrower age range in
the sample, which would suppress any association.
Present findings confirm the complex and inconsistent
relation between physical activity and body weight-related
variables in young people (2). There were a total of 55
comparisons for this variable, and results were indetermi-
nate for children and adolescents.
Relatively few psychological variables were assessed
with children, likely due to their limited cognitive abilities
to self-report these variables. Four of 17 psychological vari-
ables were consistently supported for adolescents. The pos-
itive association with achievement orientation, primarily
related to academics, is interesting and may reassure edu-
cators that being physically active does not reduce adoles-
cents’ interest in academics. Lack of consistency for knowl-
edge is consistent with findings that knowledge of physical
activity or health is rarely related to physical activity in
adults (17). The consistent results regarding intention to be
active are also similar to findings for adults (17).
Previous physical activity is one of the few variables
consistently related to physical activity in both age groups.
This is indirect evidence of tracking of activity levels over
time, supporting prospective studies that show moderate
levels of tracking over periods of several years (9). Com-
munity sports participation was related to adolescent phys-
ical activity, whereas participation in school sports was not.
This supports recommendations from the Centers for Dis-
ease Control and Prevention (4) to increase the number of
community activity programs and encourage more young
people to participate. Although time spent watching televi-
sion is generally unrelated to activity levels, use of after-
school and weekend time for sedentary pursuits was a con-
sistent correlate for adolescents. This identifies sedentary
behaviors as competitors for adolescents’ time during these
critical periods and may help explain why interventions to
decrease sedentary time result in increased activity (7).
The strong relation of social support from parents and
others with adolescent physical activity was expected and
suggests that parents still play important roles in their teen-
agers’ lives. Thus, parents can be encouraged to support
their teens’ physical activity verbally and with direct assis-
tance such as paying fees. Parental physical activity was the
most frequently studied social variable, but it was unrelated
or indeterminate for both age groups. There may be some
situations in which parent modeling is an important influ-
ence, but those situations have not been identified. It may be
that parents need to provide more direct assistance to sup-
port their children’s physical activity. There was little evi-
dence in the present review that mother’s or father’s phys-
ical activity was more likely to be related to the child’s
behavior. As mentioned above, the lack of consistent social
correlates of children’s physical activity was surprising.
Few physical environmental variables were studied, but
there were consistent variables identified for both children
and adolescents. Two of six frequently studied variables
were consistently related for the younger group. Although it
is obvious that young people must be active in some place,
the findings regarding access to programs, facilities, and
opportunities empirically validate the need for appropriate
physical environment supports for youth physical activity.
Providing these resources should become a policy goal for
those interested in promoting youth physical activity. Re-
sults of studies assessing environmental variables also imply
that it is important to get young children outdoors where
they can be active.
There are numerous limitations to this review. The diver-
sity of variables, measures, subject samples, and analysis
strategies prevented a true meta-analysis. The present semi-
quantitative review required the establishment of definitions
for consistency of association that are debatable, as are any
arbitrary classifications. The categories of evidence and
summary codes do provide, however, a relative assessment
of the consistency of associations with physical activity. The
present review focused on the consistency of reported as-
sociations and was not able to assess the strength of asso-
ciations. To reduce the number of variables, similar con-
structs or specific measures of aspects of a general construct
were combined into a single category. Only published pa-
pers in the English language were included. Although over
100 studies were reviewed, it is possible articles were
missed in the retrieval process. The bias against publishing
negative findings may have also affected the present results.
Strengths of the review include the systematic summary
of over 100 published studies, the clear definitions of con-
sistency of evidence, and the clear rules used in the coding
of studies. This is the first review of correlates of youth
physical activity that compared results for children and
Conclusion and Recommendations
There are different recommendations for further research
and action for each category of variables. The priority for
variables classified as consistently associated with physical
activity should be to apply these findings to improving
interventions. The nonmodifiable demographic variables
suggest subgroups of relatively inactive young people that
need to be targeted for special intervention programs. Sub-
groups at risk for being inactive include girls, older adoles-
cents, and those in minority ethnic groups. Modifiable vari-
ables identified in this review may be considered potential
CORRELATES OF YOUTH PHYSICAL ACTIVITY Medicine & Science in Sports & Exercise
mediators of youth physical activity, and interventions
should be developed to change these variables through ed-
ucation, family programs, or environmental and policy
change (1).
The variables whose associations with physical activity
were classified as indeterminate should be subjected to more
detailed study. This substantial group includes frequently
studied variables such as child body weight and parent
physical activity. Reasons for the inconsistent findings need
to be explored. For example, there may be some subgroups
of young people for whom parent physical activity is an
important correlate, or there may be other variables that
moderate the association.
Variables that have already been shown to be consistently
unrelated to youth physical activity should be de-empha-
sized in future studies. These variables should not be tar-
geted for change in interventions until additional research
warrants it. Variables such as benefits, peer modeling, and
socioeconomic status may show different results if better
quality measures are used. For these variables especially, it
is essential to use measures that are shown to be psycho-
metrically adequate. It is likely that many variables are
found to be unrelated to physical activity because of mea-
surement error.
Some variables have been studied too few times to draw any
conclusions, so more studies are needed to test variables that
are understudied. Other possible correlates derived from theo-
ries, models, and creative thinking need to be evaluated for the
ability to improve the explanation of youth physical activity.
The purpose of this area of research should be to identify
correlates of youth physical activity, further test promising
variables in prospective studies, and then use the results to
develop improved interventions that are rigorously evaluated.
Readers are encouraged to send the first author copies of ap-
propriate papers that could be included in updates of this review.
Address for correspondence: James F. Sallis, Ph.D., FACSM, De-
partment of Psychology, San Diego State University, 6363 Alvarado
Court, #103, San Diego, CA 92120; E-mail:
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CORRELATES OF YOUTH PHYSICAL ACTIVITY Medicine & Science in Sports & Exercise
... Durante a infância e adolescência, a escola é um contexto social particularmente relevante no desenvolvimento dos indivíduos, possibilitando o acesso a oportunidades de melhoria da saúde e o acesso a uma educação de qualidade de forma equitativa. Em paralelo, sabemos também que a infância é um período de desenvolvimento particularmente relevante para educar e influenciar a adopção e manutenção de estilos de vida ativos ao longo da vida (Sallis et al., 2000;Telama et al., 1997;Telama et al., 2014;Telama et al., 2005;WHO, 2018). É neste quadro que identificamos a escola como contexto impar para a promoção de hábitos de vida ativos e saudáveis (whole-school aproach), destacando o papel da Educação Física (EF), nomeadamente, pelo seu potencial para promover justiça social no acesso à educação e a oportunidades de proteção da saúde. ...
... A aplicação de modelos ecológicos tem-se tornado uma referência no desenvolvimento de intervenções de base comunitária para a promoção da AF (Sallis & Owen, 2015;Sallis, Cervero, Ascher, Henderson, Kraft & Kerr, 2006). Os estudos sobre as determinantes de AF apontam para que o conjunto único de experiências de AF de um individuo (Pot, Whitehead, Durden-Myers, 2018;Whitehead, , 2019 seja condicionado por fatores sociais (interpessoais) e ambientais, para além dos individuais amplamente estudados (Bauman et al., 2012;Sallis et al., 2000;Van Der Horst, Paw, Twisk, & Van Mechelen, 2007;Yen & Li, 2019). É neste sentido que a natureza multidimensional da promoção da adesão e manutenção de comportamentos de AF ao longo da vida direciona a nossa reflexão para o possível lugar dos modelos ecológicos na operacionalização de programas de intervenção que visem o apoio ao desenvolvimento da Literacia Física (c.f. ...
... O desenvolvimento da Literacia Física não se esgota na participação em AF escolar e na fase da infância, pelo contrário, é relevante ao longo da vida e tão importante para as crianças em idade pré-escolar e para a população adulta ou idosa como é para as crianças e jovens em idade escolar (Whitehead, 2013). No entanto, deveremos reconhecer que a infância é um período de desenvolvimento particularmente relevante para educar e influenciar a adopção e manutenção de estilos de vida ativos a longo prazo (Sallis et al., 2000;Telama et al., 1997;Telama et al., 2014;Telama et al., 2005;WHO, 2018). Nesta fase do desenvolvimento humano, a escola é um contexto privilegiado para promover uma oferta equitativa de oportunidades de desenvolvimento da Literacia Física, uma vez que é gratuita e o local onde a generalidade das crianças e jovens se encontram durante parte considerável do dia. ...
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A escola é um contexto social particularmente relevante no desenvolvimento dos indivíduos, possibilitando o acesso a oportunidades de melhoria da saúde e o acesso a uma educação de qualidade de forma equitativa. Por ser a única disciplina do currículo escolar cujo foco combina o corpo e a competência física com aprendizagens baseadas em valores e na comunicação, a Educação Física é reconhecida pela UNESCO um meio privilegiado onde as crianças e jovens podem desenvolver as competências requeridas para serem bem-sucedidos enquanto parte ativa das sociedades do século XXI. A participação de qualidade na Educação Física é uma das vias mais importantes para assegurar o exercício de uma cidadania ativa e saudável, onde se inclui a tomada de responsabilidade e valorização da participação inclusiva em atividade física ao longo da vida. A Literacia Física, definida como o desenvolvimento integrado da motivação, confiança, competência física, conhecimento e compreensão para praticar atividade física ao longo da vida, é considerada o resultado último da Educação Física de Qualidade. Este capítulo pretendeu dar um contributo para a sistematização de estratégias de intervenção pedagógica que visem o desenvolvimento da Literacia Física no contexto da Educação Física.
... These studies used several strategies in the intervention to enhance self-efficacy such as improving children's self-regulation capabilities related to physical activity (e.g., critical thinking and problem-solving skills) [27] and social support (e.g., small groups/pairs and positive feedback and encouragement) [47]. According to other researchers, the characteristics identified in these intervention studies, such as self-regulation [58,59] and social support [60,61] could enhance physical activity self-efficacy in children. Self-efficacy can play a major role in children's motivation to participate in physical activity [62]. ...
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Background This systematic review examined the effectiveness of experiential learning interventions for improving children’s physical activity knowledge, attitudes, and behaviours. It also aimed to identify intervention characteristics that resulted in the greatest impact. Methods Four databases: Education Research Complete, Scopus, Web of Science and PsychINFO were searched from database inception to January 2023. Eligible studies: (1) included children 0–12 years; (2) assessed the effect of physical activity outcomes on children’s physical activity knowledge, attitudes or behaviour and (3) were randomised controlled trials conducted in any setting. Study risk of bias was assessed by two independent reviewers using the Cochrane risk of bias tool. Intervention approaches were categorised, and effect sizes were compared across studies for each outcome. Results Twelve studies were included in the review: ten in school age and two in below five years. For behavioural outcomes, six of eight studies showed medium to large effects (effects size (ES) range: 0.3–0.9), two of the three studies that assessed attitudinal outcomes displayed medium effects (ES range: 0.4–0.5) and both studies that assessed knowledge outcomes displayed medium to large effects (ES range: 0.4–1.3). The two experiential learning interventions among children < 5 years demonstrated small to medium effects on behaviour change (ES range: 0.2–0.5). Effective interventions combined enjoyable practical activities (fitness activities, games and challenges), with behaviour change techniques (goal setting, and self-monitoring), were underpinned by a behaviour change theory, and were often of short duration (< 4 months) but intense (several sessions/week). Moderate to high statistical heterogeneity was observed for behaviour outcomes and risk of bias across studies was generally high. Conclusions This review provides some evidence supporting the effectiveness of experiential learning interventions in improving physical activity outcomes in school-aged children. Additional evidence is needed in children <5 years old. Future experiential learning interventions need to strengthen the evidence with rigorous methodological quality and clear reporting of the experiential learning components.
... Relationships between determinants and PA were summarized using vote counting (i.e., comparing the number of effects favouring each direction), a synthesis method in the Cochrane handbook [32], and followed the methods outlined by Sallis et al. [33] and adapted by Choi et al. [14] for use in umbrella reviews. The number of primary studies that found a statistically significant positive, negative, or null relationship were summed for each relationship present across each review (i.e., determinant-PA combination). ...
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Introduction Physical activity (PA) is critical for disease prevention and maintaining functional ability with aging. Despite this, as many as 50% of older adults in populations worldwide are considered insufficiently active. There is a recognized need to mobilize policies targeted toward modifiable determinants of healthy aging like PA. This umbrella review aimed to summarize the evidence for determinants of PA in community-dwelling older adults. Methods A research librarian searched six databases. Systematic and scoping reviews were included if they investigated community-dwelling people with a mean age of 60 + years and examined a relationship between a determinant and any type of PA. Two independent reviewers screened and extracted data from all reviews. JBI methodology and Critical Appraisal Checklist for Systematic Reviews and Research Syntheses were followed and information on the quality of the evidence was extracted. Results From 17,277 records screened,11 reviews representing > 300 unique primary papers were ultimately included. Only 6% of studies included in all reviews had longitudinal designs. Included studies used a large variety of PA measures, with 76% using only self-report, 15% using only direct measures (e.g., accelerometry), 3% using both types, and 6% with no outcome measure reported. Only four reviews provided a definition of PA and there was substantial inconsistency in the way PA was categorised. Community level influences, which only included the physical environment, were the most commonly assessed (6/11) with more than 70% of the summarized relationships demonstrating null associations. Three out of four reviews reported a positive relationship between walkability and PA in general community-dwelling older adults. There was also evidence supporting relationships between presence of social support for PA, younger age, and men having higher PA from a single systematic review. None of the included reviews assessed the quality of evidence but over 60% performed a risk of bias assessment. Conclusions Walkability, age, gender, and social support for PA were the most supported PA determinants identified. Further research should focus on interpersonal and intrapersonal influences and incorporate direct measures of PA with clear operational definitions. There is a need for longitudinal study designs to further understand determinants of PA behaviour trajectories.
... Students in their classes can engage in developmentally appropriate physical activities designed specifically for them to develop their fitness, motor skills, and health (Robinson & Goodway, 2009;Sallis et al., 2000). In addition, students in their classes are more likely to develop positive attitudes toward physical education and physical activity. ...
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The world in the 21st century is a world of technology and revolution in different aspects of life. The increasing desire of young people to use technology (van Laarhoven & van Laarhoven-Myers, 2006) at home, at work, and during leisure time has made industry come up with a variety of tools to be used. In such a scenario, the video recording analysis method has become a helpful tool in researchers’ and educators’ hands, allowing them to observe and assess a class, conduct pedagogy research, and so forth. For some time, video has been used to record and analyze human movement for health issues. Physical education professionals and coaches took advantage of technology to improve their athletes’ performance using video capture. The video gave them the opportunity to analyze and inform their athletes for better performance during competition. Video-based observation has been used in several studies conducted in schools, for different disciplines and for different reasons, such as to compare different teaching styles, to compare teaching behaviors of teachers, to compare student participation in class, or teaching effectiveness (Constantinides et al., 2013). In physical education, there is a growing interest among physical educators to incorporate digital technology in their teaching (Pyle & Esslinger, 2014; Thomas & Stratton, 2006). In this paper, however, the focus of the discussion is on how this technology may help the teacher develop and provide more effective lessons to the students. Therefore, the process of video recording is analyzed, the value-based observation is thoroughly discussed, as well as the value for the teacher who wants to develop his teaching. Furthermore, suggestions are made for physical education teachers who may use this method in the future for their own development in teaching physical education.
... The level of physical activity between genders (SDG5) has been the most common demographic variable that has been investigated within school recess periods across the international literature (Hyndman et al., 2016;Ridgers et al., 2012). A review of 31 recess studies from over a decade (Ridgers et al., 2012) revealed that girls were consistently less active than boys and this further reinforced previous international reviews across age groups (Hinkley et al., 2008;Sallis et al., 2000;Van Der Horst et al., 2007). Researchers have suggested that girls can often view school playgrounds more as a place to socialise (Pellegrini & Bohn, 2005), an important consideration within schools better to accommodate girls' play behaviour (SDG5). ...
Over recent decades, the importance of encouraging physical activity participation for both children and adults has emerged as a major international public health objective. The United Nations (Transforming our world: The 2030 agenda for sustainable development., 2015) stated that people need to develop lifelong physical activity habits for the benefit of all of society. Physical activity is defined as “any bodily movement produced by skeletal muscles that results in energy expenditure”.
... In this context, school PE courses are a unique opportunity that provides direct access to the children and young population and have facilities, teachers, and curricula to achieve social and educational physical activity and healthy lifestyle objectives (Dobbins et al., 2013;Hills, Dengel, & Lubans, 2015). On the other hand, PE classes are unique places for many children to increase their physical fitness, play sports, and exercise (Sallis, Prochaska, & Taylor, 2000;Biddle & Mutrie, 2007). In addition to these, it is known that physical education lessons have psychosocial benefits such as body self-perception and general well-being (Bailey, 2006). ...
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Background. School-based physical activity interventions contribute positively to children’s general health, wellness, and quality of life. The present study aims to investigate the effect of a 12-week handball training intervention on the ingredients of physical fitness and physical performances of primary school children. Materials and methods. In this quasi-experimental study, students participating in school-based handball training constitute the intervention group (IG) (n=15, aged 12.3 ± 0.96) and those who do not participate (n=17, aged 12.1 ± 0.83) constitute the comparison group. The linear speed (T30m), change of direction speed (T-test time), lower extremity power (standing long jump (SLJ)), muscular strength and endurance (30-sec curl-ups and push-ups), and estimated maximum oxygen uptake (VO2 max) (YYIRTL-1) were measured at the beginning and end of the handball training session. Independent samples t-test was conducted to test the significant differences in pretests between groups. Paired samples t-test was carried out to analyze statistically significant differences within groups. Results. The results revealed that, except for SLJ test scores, the pre-tests IG performed statistically significantly higher than the CG. In post-test scores, the IG performed statistically significantly higher than the CG in all test scores. In addition, physical fitness performance levels of the IG significantly changed between pre- and post-test (p<0.05) but not in the control group (p>0.05). Conclusions. In conclusion, school-based handball intervention can positively affect students’ physical fitness and performance characteristics.
The purpose of this systematic literature review was to systematically compile the state of knowledge on correlates of physical activity enjoyment in children and adolescents to influence the perspective of future physical activity promotion approaches especially for children and adolescents affected by overweight or obesity. The electronic database search was executed in the five databases PubMed, PsychINFO, SPORTDiscus, Web of Science, and BISp-SURF, from inception to December 6, 2021. A semi-quantitative method was used for summarizing the resulted correlates. For final analysis, 85 studies comprising 48,144 children and adolescents were included. Fifty-seven variables could be coded for their relationship with physical activity enjoyment. Of these, 12 psychological variables, for example, the basic psychological needs, task orientation, or self-efficacy; six interpersonal variables, for example, peer/group acceptance, parental support, and autonomy support; and one behavioral variable, the higher self-reported physical activity, are consistent positively associated to physical activity enjoyment. A scientifically based overview could be extracted for the promotion of physical activity enjoyment in children and adolescents. There is a gap in literature focusing the perception of physical activity enjoyment in the subgroup of children and adolescents affected by overweight or obesity. Therefore, recommendations were made to enable the development of further innovative research approaches in this population.
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Martial arts (MA) and combat sports (CS) are physical activities that may be associated with health-related outcomes. The aim of this systematic review was to synthesize and evaluate the available evidence on the relationship between MA and CS training and mental health of adult practitioners (≥18 years). CochraneLibrary, EBSCOhost, Web-of-Science, and Scopus databases were searched up to September 2022 for measures of self-related constructs, ill-being and well-being, cognition and brain structure/function, in adult MA/CS practitioners. Seventy cross-sectional and two longitudinal studies were retained and submitted to risk of bias assessments through an adapted version of the Cochrane Collaboration’s Tool. Associations between MA/CS practice and self-related constructs were inconclusive for both consistency and strength of evidence. Limited evidence of significant associations emerged for sub-domains of ill-being (i.e., externalizing and internalizing emotion regulation), and well-being. In regard to cognitive and brain structural/functional variables, evidence of positive association with MA/CS practice was consistent with respect to perceptual and inhibition abilities but limited with respect to attention and memory. Evidence on negative associations of boxing with changes of brain structure integrity due to concussions was also inconclusive. Functional imaging techniques could shed light onto brain activation mechanisms underlying complex cognitive performance. In relation to moderators, mixed results were found for activity exposure, expertise, level of competitive engagement (which often covary with the length of training) and sex and type of MA/CS. The MA/CS’ multifaceted nature may produce different, sometimes conflicting outcomes on mental health. Studies on MA/CS represent a flourishing research area needing extensive improvement in theoretical and practical approaches.
Context Although the nutritional composition of organic food has been thoroughly researched, there is a dearth of published data relating to its impact on human health. Objective This systematic review aimed to examine the association between organic food intake and health effects, including changes in in vivo biomarkers, disease prevalence, and functional changes. Data Sources PubMed, EMBASE, Web of Science, the Cochrane Library, and were searched from inception through Nov 13, 2022. Data Extraction Both observational and interventional studies conducted in human populations were included, and association between level of organic food intake and each outcome was quantified as “no association,” “inconsistent,” “beneficial correlation/harmful correlation,” or “insufficient”. For outcomes with sufficient data reported by at least 3 studies, meta-analyses were conducted, using random-effects models to calculate standardized mean differences. Data Analysis Based on the included 23 observational and 27 interventional studies, the association between levels of organic food intake and (i) pesticide exposure biomarker was assessed as “beneficial correlation,” (ii) toxic metals and carotenoids in the plasma was assessed as “no association,” (iii) fatty acids in human milk was assessed as “insufficient,” (iv) phenolics was assessed as “beneficial”, and serum parameters and antioxidant status was assessed as “inconsistent”. For diseases and functional changes, there was an overall “beneficial” association with organic food intake, and there were similar findings for obesity and body mass index. However, evidence for association of organic food intake with other single diseases was assessed as “insufficient” due to the limited number and extent of studies. Conclusion Organic food intake was found to have a beneficial impact in terms of reducing pesticide exposure, and the general effect on disease and functional changes (body mass index, male sperm quality) was appreciable. More long-term studies are required, especially for single diseases. Systematic Review Registration PROSPERO registration no. CRD42022350175.
Compilación de investigaciones realizadas por el Observatorio del Deporte, la Recreación y la Actividad Física. INDER Alcaldía de Medellín, 2015 Medellín - Colombia
Purpose. Television watching has been reported to be associated with obesity, resting energy expenditure, and lower daily physical activity among both children and adolescents. However, most of these studies were based on self report or data collected in laboratory settings. This study examined the relationship among observed time of television watching, observed physical activity level and body composition among 3- or 4-year-old children. Methods. African-American (41.4%), Mexican-American (23%), and Anglo-American (35.6%) children (N = 191, males = 90) from the Texas site of the Studies of Child Activity and Nutrition program were observed from 6 to 12 hours per day up to 4 days over 1 year. Activity level each minute of the day was measured with the Children's Activity Rating Scale (interobserver reliability = .84 ± .001). The interobserver reliability of time of television watching was .96 ± .08. Results. The median of the longest number of consecutive minutes of television watching was 15 (range = 1 to 79). The median percent of minutes of television watching of total observed minutes was 14.8% (0% to 58%) and the median percent of minutes of inside minutes was 17.9% (0% to 80.9%). There were no gender or ethnic differences in time watching television or physical activity during television watching. Physical activity during television watching was lowest during the longest bout of television watching (\l=x_\ = 1.48 ± .28) compared to outside minutes (\l=x_\ = 2.38 ± .21), inside non-television minutes (\l=x_\ = 1.96 ± .13) and inside television minutes (\l=x_\ = 1.65 ± .18). The level of physical activity during television-watching times was highest (P <.0031) during October and November and lowest during March, April, June, and July. Longest bout of television watching and percent of minutes watching television to total observed minutes were inversely associated with mean physical activity, percent of minutes of physical activity levels 3, 4, or 5, and percent of physical activity levels 4 or 5. Percent of television watching to inside minutes was negatively correlated with physical activity levels 4 or 5. Television-watching behavior was not associated with body composition. Conclusions. Television watching was weakly negatively correlated with physical activity levels, and physical activity was lower during television-watching than non-television-watching time in this sample of children. Television viewing behavior was not associated with body composition.
In order to quantify genetic and environmental determinants of physical activity level, 1,610 subjects from 375 families who lived in the greater Québec city area completed a three-day activity record in 1978–1981. Level of habitual physical activity, which includes all the usual activities of life, and exercise participation, which includes activities requiring at least five times the resting oxygen consumption and more, were derived from this record. Familial correlations were computed in several pairs of biologic relatives and relatives by adoption after adjustment for the effects of age, sex, physical fitness, body mass index, and socioeconomic status, and analyzed with a model of path analysis that allows the separation of the transmissible effect between generations (t²) into genetic (h²) and cultural (b²) components of inheritance. The transmission was found to be statistically significant, but was accounted for by genetic factors for level of habitual physical activity (t² = h² = 29%), and by cultural factors for exercise participation (t² = b² = 12%). Although non-transmissible environmental factors remain the major determinants of these two physical activity indicators in this population, the results suggest that children can acquire from their parents certain customs regarding exercise behavior and that the propensity toward being spontaneously active could be partly influenced by the genotype.
Gender and ethnic trends were examined in 351 Mexican American and Anglo American children between the ages of four and seven. Four physiologic variables, seven observed and reported variables related to diet, and eight observed and reported variables related to physical activity were periodically assessed. Children were observed at home at meal times and at school (or a day care center) at lunch and recess. A linear regression model was used. Of the four physiologic variables, two variables (height and total skinfolds) showed significant ethnic differences, with Mexican American children showing greater skinfolds over time and the tendency to be shorter than Anglo American children. Of the variables related to diet, five of the seven variables showed gender or ethnic differences; percent of calories from fat and food preparation behaviors tended to place Mexican American children at greater risk. When examining physical activity, four of the eight variables showed gender and/or ethnic differences in trend. As children age, they get less active at home and more active at school. Anglo boys are the most active and are prompted more often to be active. They also participate in more organized physical activities as they get older.
This paper reviews the descriptive epidemiology of physical activity in adolescents. Large population-based studies were reviewed, along with smaller studies using objective monitoring of physical activity. Estimates showed that adolescents engage in physical activity of any intensity for a mean of one hour per day. Approximately two thirds of males and one quarter of females participate in moderate to vigorous activity for 20 min 3 or more days per week. Activity levels decline with increasing age across adolescence, and this decrease is more marked in females than in males. Comparison of these data to physical activity guidelines for adolescents suggests the vast majority are meeting the guideline of accumulating physical activity. However, a substantial number of males, and the majority of females, are not meeting the guideline for moderate to vigorous physical activity.
This review examines the evidence that the level of physical activity (PA) or total energy expenditure during adolescence affects body adiposity in the obese and nonobese adolescent population. Several cross-sectional studies suggested that obese children were less physically active than their nonobese peers, but there was no consistent difference in the total energy expenditure. The likelihood that infants of obese mothers become obese at age 1 year is greater if their total energy expenditure (using the doubly labeled water technique) is lower at age 3 months. Many interventional studies in the general adolescent population show a small (1-3% body fat) reduction in adiposity as a result of physical training. It appears, though, that programs longer than one year are more efficacious than shorter programs. Lifestyle activities (e.g., walking to and from school) appear to have a more lasting effect than regimented activities (e.g., calisthenics or jogging).
This investigation examined parental influence on children’s moderate to vigorous physical activity (MVPA) participation via an expectancy-value model that included parents’ behavior, parents’ beliefs about their children’s MVPA, and children’s beliefs about their MVPA. The influence of parents on their children’s MVPA was investigated via questionnaires tapping the belief systems of fourth- and fifth-grade children (n=71) and their parents (n=69). Self-reported MVPA was assessed for parents and children. Correlational analyses demonstrated a number of significant relationships between parents’ belief systems and children’s MVPA behavior and children’s belief systems and their physical activity participation. Based on hierarchical regression analyses, there was no evidence of a positive relationship between parents’ physical activity behavior (role modeling) and children’s physical activity behavior. Parents’ perceptions of their children’s MVPA competence was the only parent belief system variable relate...