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REVIEW ARTICLEPEDIATRICS Volume 139 , number 4 , April 2017 :e 20162266
Children’s Physical Activity and Depression: A Meta-analysisDaphne J. Korczak, MD, MSc, a, b Sheri Madigan, PhD, c Marlena Colasanto, MSca
abstractCONTEXT: Research regarding the protective effects of early physical activity on depression has
yielded conflicting results.
OBJECTIVE: Our objective was to synthesize observational studies examining the association of
physical activity in childhood and adolescence with depression.
DATA SOURCES: Studies (from 2005 to 2015) were identified by using a comprehensive search
strategy.
STUDY SELECTION: The included studies measured physical activity in childhood or adolescence
and examined its association with depression.
DATA EXTRACTION: Data were extracted by 2 independent coders. Estimates were examined by
using random-effects meta-analysis.
RESULTS: Fifty independent samples (89 894 participants) were included, and the mean effect
size was significant (r = –0.14; 95% confidence interval [CI] = –0.19 to –0.10). Moderator
analyses revealed stronger effect sizes in studies with cross-sectional versus longitudinal
designs (k = 36, r = –0.17; 95% CI = –0.23 to –0.10 vs k = 14, r = –0.07; 95% CI = –0.10 to
–0.04); using depression self-report versus interview (k = 46, r = –0.15; 95% CI = –0.20
to –0.10 vs k = 4, r = –0.05; 95% CI = –0.09 to –0.01); using validated versus nonvalidated
physical activity measures (k = 29, r = –0.18; 95% CI = –0.26 to –0.09 vs k = 21, r = –0.08;
95% CI = –0.11 to –0.05); and using measures of frequency and intensity of physical activity
versus intensity alone (k = 27, r = –0.17; 95% CI = –0.25 to –0.09 vs k = 7, r = –0.05; 95% CI =
–0.09 to –0.01).
LIMITATIONS: Limitations included a lack of standardized measures of physical activity; use of
self-report of depression in majority of studies; and a small number of longitudinal studies.
CONCLUSIONS: Physical activity is associated with decreased concurrent depressive symptoms;
the association with future depressive symptoms is weak.
aDepartment of Psychiatry, Hospital for Sick Children, Toronto, Ontario, Canada; bDepartment of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; and cDepartment of Psychology, Aberta Children's Research Institute, Calgary, Alberta, Canada
Dr Korczak conceptualized and designed the study, assisted in data collection, and drafted the initial manuscript; Dr Madigan assisted in data collection, carried
out the initial analyses, contributed to, and reviewed and revised the manuscript; Ms Colasanto coordinated and assisted in data collection and contributed to and
critically reviewed the manuscript; and all authors approved the fi nal manuscript as submitted.
DOI: 10.1542/peds.2016-2266
Accepted for publication Jan 6, 2017
Address correspondence to Daphne J. Korczak, MD, MSc, Department of Psychiatry, The Hospital for Sick Children, 555 University Ave, Toronto, ON M5G1X8, Canada.
E-mail: [email protected]
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).
To cite: Korczak DJ, Madigan S, Colasanto M. Children’s Physical Activity and Depression: A Meta-analysis. Pediatrics. 2017;139(4):e20162266
by guest on May 24, 2020www.aappublications.org/newsDownloaded from
KORCZAK et al
Research interest in the health and
psychological benefits of exercise
has grown exponentially over
recent years. Evidence suggests that
physical activity may ameliorate
depressive symptoms, supporting
the use of exercise as part of a
comprehensive treatment plan for
major depressive disorder (MDD). 1, 2
The reverse association has also
been demonstrated: decreased
physical activity (PA), as well as
increased sedentary behaviors,
confers vulnerability for developing
depressive symptoms. 3 –5 To date,
studies have investigated whether
increased PA may also protect
individuals against the development
of MDD, and findings from
observational studies are
promising. 3, 6 – 8 However, the age
range of participants in these
studies has been wide, research
has been conducted principally in
adult populations, and results have
been conflicting.9 – 11 Thus, using the
current state of the literature for the
purpose of clinical decision-making
is challenging. A meta-analysis is
warranted to resolve discrepancies
in the literature and to examine the
suggestion that the largest magnitude
of protective effect may be found
at younger ages, 12 which would in
turn provide support for a potential
preventative role of physical activity
in the development of depression.
Two recent systematic reviews 13, 14
have reported that increased PA is
associated with fewer depressive
symptoms. However, only 1 review
focused on the child and adolescent
age group, 13 and neither review
conducted a meta-analytic synthesis
of the data, which can provide a
powerful estimate of the mean
effect size across studies. Compared
with adult participants, in which
the investigation of risk factors is
confounded by years of the allostatic
load of depression (exposure to
depressive symptoms and their
associated physiologic strain) 15
and comorbid cardiometabolic
disease, 16 studies of children and
adolescents enable the examination
of the relationship between PA and
depressive symptoms at their most
nascent. To our knowledge, this is
the first study to conduct a meta-
analytic review of the protective
effect of PA on depression and, as
such, is the first to describe the
magnitude of this association. Also,
previous systematic reviews have not
explored the potential moderating
role of sex in the association between
PA and MDD, although a stronger
effect for females has been suggested
in several independent studies. 4, 17, 18
Understanding if the association
between PA and MDD is sex-specific
is relevant for the elucidation of
potential underlying mechanisms of
association.
The objective of this meta-analysis
was to investigate the potential
preventative effect of child and
adolescent PA on depression.
Several variables have been linked
to differences in effects size; thus,
we will examine whether between-
study differences were observed for
child age, sex, and social risk. 19 – 21 We
will also examine if heterogeneity
in effect sizes can be explained by
variation in study methodology
(eg, methods of assessing physical
activity and depression), as well
as study quality (eg, longitudinal
versus cross-sectional). Clarification
on the role of these factors for
understanding systematic differences
in effect sizes are important for
the design and implementation of
targeted and effective public health
prevention programs.
METHODS
Search Strategy
Published studies on PA and
depression in children and
adolescents were identified by
searching Social Sciences Abstracts,
International Bibliography of the
Social Sciences, Scopus, SportDiscus,
CBA Abstracts, Physical Education
Index, Sociological Abstracts, and
PsycINFO electronic databases for
potential articles through October
2015. The search was limited to
English language articles published
between 2005 and 2015 using the
keywords (“child*, ” or “teen*, ” or
“adolesc*, ” or “youth*, ” or “infant, ”
or “infancy, ” or “baby, ” or “babies”)
AND (“depress*”), AND (“sedentary
behavio*” or “recreation” or “physical
activity” or “leisure activity” or
“exercise” or “fitness” or “sport*”).
This search strategy yielded 3147
nonduplicate articles.
Study Inclusion and Exclusion Criteria
Titles and abstracts of the articles
were reviewed to identify studies
that met the inclusion criteria.
Articles selected for the current
study were based on the following
criteria. (1) Cross-sectional study
of PA and depression collected
during childhood or adolescence
(<18 years). (2) Longitudinal study
of PA collected during childhood or
adolescence (<18 years); (3) The
constructs measured were PA (eg,
energy expenditure) and depressive
symptoms. Studies that measured
broader, nonspecific constructs
of either PA (eg, participation
in extracurricular activities) or
of depression (eg, psychological
distress) were excluded. Because
numerous standardized, validated
and accessible measures of
depression among youth are widely
available, studies that assessed the
outcome of depression by using
a nonvalidated measure were
excluded. Only 1 study 22 needed
to be excluded because it assessed
depression by using a single self-
report item with no demonstrated
psychometric properties. In contrast
to the depression literature,
fewer standardized and validated
measures exist for assessing physical
activity. Thus, no validity criterion
was applied to the measure of
PA. However, a validated versus
nonvalidated PA measure was
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PEDIATRICS Volume 139 , number 4 , April 2017
examined as a moderator to
determine if this measurement
characteristic explained between
study heterogeneity. (4) The study
statistic could be transformed into
an effect size (eg, correlations, odds
ratios, means/SDs, and/or P values).
(5) The full-text article was available
and written in English. Studies in
which PA was used as an intervention
were not included in the current
study.
Multiple results often emerge
from a single dataset. If the same
participants were used across
multiple publications, only 1 study
was included in the meta-analysis
to ensure independence of effect
sizes. A protocol was developed so
that each sample of participants was
only represented once in the meta-
analysis. First, if a single dataset
presented both cross-sectional and
longitudinal analyses, we selected
the study with longitudinal data
because this study design was
underrepresented in our analyses.
Second, if multiple publications
emerged from a single cross-sectional
dataset, we selected the publication
with the largest sample size and
most comprehensive data extraction
information.
Multiple samples or groups often
exist within a particular study. For
example, some studies present
results separately for boys and girls
within a sample. In such cases, effects
sizes for both these nonoverlapping
samples were calculated and entered
into the meta-analysis separately.
Data Extraction
All articles that met inclusion
criteria were coded by using a
standard coding form to collect
information on study and sample
characteristics. Several moderator
variables were collected to explain
effect size variability across studies.
Moderator variables were divided
into categorical moderators (sex,
social risk [ie, low income, minority,
or involved in child protective
services], PA type, PA validated
measure, depression measure
type, study design, and country)
and continuous moderators (age
at PA/depression, time between
assessments, and publication
year). Some studies reported data
stratified by level of PA. In such
cases, data for the group with
the greatest PA were used in the
analysis. This was done to remain
consistent with our primary
objective. Data extraction was
performed by 2 independent coders
(DK and MC). Discrepancies were
resolved through discussion, and
consensus scores were entered into
the final dataset.
Data Analysis
Effect sizes were calculated and
analyzed by using Comprehensive
Meta-Analysis version 3.0
software. 23 Effect sizes were
calculated directly from
information provided in each
study. When provided, adjusted
effect sizes were included. All
effect sizes were transformed
into correlations for the purpose
of reporting mean effect sizes.
Pooled effect size estimates were
based on random effects model. We
assessed for overall heterogeneity
of the mean effect size using the
Q statistic and by calculating the
I2 statistic. The Q statistic is a
test of the null hypothesis that all
studies share a common effect size,
and the I2 statistic examines the
proportion of the variation across
studies that is due to heterogeneity
rather than chance, expressed as
a percentage. General guidelines
for the interpretation of the I2 are
as follows: 25%, 50%, and 75%
indicate low, moderate, and high
heterogeneity, respectively. 24
Categorical moderator analyses
were conducted by using Q
statistics, 25, 26 whereas the
significance of each continuous
moderator was assessed by using
meta-regressions.27 Finally, we
examined publication bias using
funnel plots and Egger’s test.
Study Quality
To assess the quality of studies,
a 7-point quality assessment
tool was created based on those
implemented in previous meta-
analyses of observational
studies. 28, 29 The tool evaluated
the articles based on the following
7 criteria: (1) having a defined
sample, (2) having a representative
sample, (3) rater blinding, (4)
report of relevant MDD and PA
data, (5) adequate sample size,
(6) statistical adjustment for
covariates, and (7) a validated PA
measure. Articles were given a
score of 0 (“No”) or 1 (“Yes”) for
each of the abovementioned criteria
and summed to give a total score
out of 7.
RESULTS
Our electronic search of 7 databases
yielded 3147 nonduplicate articles.
On review of the titles and abstracts,
87 articles met inclusion criteria and
full articles were retrieved. A total
of 40 studies with 50 independent
samples (89 894 participants) met
the inclusion criteria and were
included in analyses. Figure 1
presents a flowchart of the review
process.
Study and Sample Characteristics
Study Characteristics
As detailed in Table 1, 14 studies
were longitudinal and 36 studies
were cross-sectional. Sample sizes
ranged from 55 to 14 594. Child
age at the time of the assessment
of PA ranged from 8 to 19 years.
With respect to PA measures, 15
studies examined the frequency of
activity only, 7 studies examined
the intensity of the activity, and 27
examined a combination of frequency
and intensity. With respect to the
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KORCZAK et al
assessment of depression, 4 studies
measured depressive symptoms
by using interview methodology,
whereas 46 studies used self-report
questionnaires. The overall burden
of depressive symptoms in studies
that used a depression self-report
measure was low (see Table 1).
A clinical diagnosis of MDD was
reported at follow-up for the 4
longitudinal samples that measured
depressive symptoms by using a
standardized interview. An MDD
diagnosis was made in 5% to 13%
of participants across these studies
at follow-up. 6, 30, 31 Although several
studies specifically noted the absence
of antidepressant medication
use among participants, the large
majority of studies did not include
information regarding the use of
medications.
Study Quality
Validated measures of PA were used
in 19 out of 36 (53%) cross-sectional
studies and in 10 out of 14 (71%)
longitudinal studies, as indicated in
Table 1. The mean study quality score
was 4.9 (SD = 0.9) out of 7. For cross-
sectional studies, the mean percentage
of participants with complete data
were 96.6% (range: 68%–100%).
For longitudinal studies, the mean
rate of attrition between time points
was 13.8% (range: 0.04%–30%).
Additional detail regarding individual
study- and item-level quality
assessment scoring is summarized in
Supplemental Table 6.
Overall Measure of Effect Size
A significant mean effect size for
the association between PA and
depression was found: (r = –0.14;
95% confidence interval [CI] = –0.19
to –0.10) ( Fig 2), suggesting that
children’s PA is negatively associated
with depressive symptoms. The
funnel plot revealed asymmetry ( Fig
3) and Egger’s test suggested that the
asymmetry was significant (P < .01).
Using the trim and fill analysis, the
adjusted pooled effect size estimate
was r = 0.06 (95% CI = –0.11 to
–0.01). Statistically significant
heterogeneity between the studies
was found (Q = 1767.95; P < .0001;
I2 = 95.23) and potential moderator
analyses were explored, including
demographic, measurement, and
study design factors. The results of
all moderator analyses are presented
in Tables 2 and 3, and significant
moderators are discussed in detail
below.
Effect sizes were stronger in
samples using cross-sectional
designs (k = 36, r = –0.17; 95%
CI = –0.23 to –0.10) compared with
those using longitudinal designs
(k = 14, r = –0.07; 95% CI = –0.10
to –0.04), in which a weak inverse
relationship between physical
activity and future depressive
symptoms was found. Similarly,
studies that used interview-based
MDD measures demonstrated
weaker effect sizes compared with
those that used questionnaires (k =
4, r = –0.05; 95% CI = –0.09 to –0.01
vs k = 46, r = –0.15; 95% CI = –0.20
to –0.10). Stronger effect sizes were
also observed in samples with no
known risks (k = 44; r = –0.15; 95%
CI = –0.21 to –0.10) compared with
samples with social risk (eg, low
income) (k = 6; r = –0.05; 95%
4
FIGURE 1PRISMA fl ow diagram of the literature search used to identify studies for analysis of physical activity and depression.
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PEDIATRICS Volume 139 , number 4 , April 2017 5
TABL
E 1
Ind
epen
den
t S
amp
les
Incl
ud
ed in
th
e M
eta-
anal
ysis
of
Ph
ysic
al A
ctiv
ity
and
Dep
ress
ion
Stu
dy
Cou
ntr
yN
% B
oys
Mea
n A
gea
(Ran
ge)
PA
Mea
sure
[F/
I]D
epre
ssio
n M
easu
re [
Q/I
NT]
(Ran
ge)
Dep
ress
ion
Mea
nb (
SD
)
QA
Sco
re
(Ou
t of
7)
Tim
e La
pse
(T2
– T
1)
Cro
ss-s
ecti
onal
stu
die
s
Ad
eniy
i et
al 32
Nig
eria
1100
48.9
15.2
(12
–17
)P
AQ-A
[F/
I]C
DI [
Q]
(0–
54)
Boy
s: 8
.8 (
3.9)
;
girl
s: 1
3.5
(6.7
)
6—
Am
mou
ri e
t al
33U
nit
ed S
tate
s18
60
— (
10–
19)
Mod
ifi ed
SAP
AC [
F]6-
item
sca
le [
Q]
(0–
18)
14.7
(3.
8)6
—
Am
mou
ri e
t al
33U
nit
ed S
tate
s98
100
— (
10–
19)
Mod
ifi ed
SAP
AC [
F]6-
item
sca
le [
Q]
(0–
18)
13.2
5 (4
.08)
6—
As
are
and
Dan
qu
ah 34
Gh
ana
296
50.7
14.9
(13
–18
)P
AQ-A
[F/
I]C
DI [
Q]
(0–
100)
T sc
ores
c : p
riva
te
sch
ool:
56.5
3
(13.
9); p
ub
lic
sch
ool:
44.0
7
(10.
8)
6—
B
abis
s an
d G
angw
isch
35U
nit
ed S
tate
s14
594
4916
(11
–21
)N
o. d
pla
yed
sp
orts
in p
ast
wkd
[F]
CES
-D [
Q]
—5
—
C
ao e
t al
36C
hin
a50
0352
13.2
(11
–16
)P
ast-
wee
k P
Ad [
F/I]
DS
RS
C [
Q]
—5
—
C
asti
llo e
t al
37U
nit
ed S
tate
s79
70
13.9
(11
–18
)M
VPA
pas
t 2
wk
(1-it
em)
[F/I
]
6-it
em s
cree
n [
Q]
(0–
18)
11.3
(3.
0)6
—
C
asti
llo e
t al
37U
nit
ed S
tate
s71
110
013
.9 (
11–
18)
MVP
A p
ast
2 w
k (1
-item
)
[F/I
]
6-it
em s
cree
n [
Q]
(0–
18)
10.4
(2.
9)6
—
D
esh
a et
al 38
Un
ited
Sta
tes
371
015
.3 (
13–
18)
24h
r d
iari
es, m
etab
olic
equ
ival
ents
, tot
al M
VPAd
[F/I
]
CD
I-SF
[Q]
—5
—
D
esh
a et
al 38
Un
ited
Sta
tes
356
100
15.3
(13
–18
)24
-h d
iari
es, m
etab
olic
equ
ival
ents
, tot
al M
VPAd
[F/I
]
CD
I-SF
[Q]
—5
—
D
ockr
ay e
t al
39, e
Un
ited
Sta
tes
550
10.5
(8–
13)
Par
ent-
rep
ort
of 6
-item
s
from
CH
IPd [
F/I]
CB
CL
– a
nx/
dep
[Q
]2.
25 (
2.1)
4—
D
ockr
ay e
t al
39, e
Un
ited
Sta
tes
5610
011
.4 (
8–13
)P
aren
t-re
por
t of
6-it
ems
from
CH
IPd [
F/I]
CB
CL
– a
nx/
dep
[Q
]2.
11 (
2.2)
4—
Es
mae
ilzad
eh 40
Iran
265
100
9.7
(8–
11)
PAQ
-C a
nd
ph
ysic
al fi
tnes
s
test
[F/
I]
CD
I [Q
]—
6—
Fa
tire
gun
an
d K
um
apay
i 41N
iger
ia17
1345
14 (
10–
19)
Par
tici
pat
ion
in s
por
tsd
, fP
HQ
-9 [
Q]
—5
—
G
ray
et a
l 42U
nit
ed S
tate
s95
4612
.8 (
8–17
)1-
item
, am
oun
t of
PA
[F]
CD
I-SF
[Q]
(0–
20)
13.6
(3.
9)3
—
H
oare
et
al 43
Aust
ralia
440
013
.1 (
11–
14)
ABAK
Q [
I]M
FQ-S
F [Q
] (0
–26
)13
.1 (
0.6)
5—
H
oare
et
al 43
Aust
ralia
360
100
13.1
(11
–14
)AB
AKQ
[I]
MFQ
-SF
[Q]
(0–
26)
13.1
(0.
6)5
—
H
ong
et a
l 44C
hin
a12
640
13.9
(–
)m
in. o
f P
A/w
eekd
ay (
end
)d [
F]
CD
I [Q
] (0
–54
)11
.22
(7.3
)4
—
H
ong
et a
l 44C
hin
a11
8010
013
.9 (
–)
min
. of
PA/
wee
kday
(en
d)
d [
F]
CD
I [Q
] [0
–54
]12
(7.
7)4
—
Ji
n e
t al
45C
anad
a36
48—
—S
HAP
ES P
A, P
ASC
Q, K
KD
[F/I
]
CES
-D [
Q]
—5
—
Jo
hn
son
et
al 46
Un
ited
Sta
tes
1397
012
(11
–13
)3-
d P
A re
call
and
acce
lero
met
ry [
F/I]
CES
-D [
Q]
(0–
60)
14.7
(9.
3)5
—
Kr
emer
et
al 47
Aust
ralia
8029
4811
.5 (
10–
16)
d a
nd
min
/d p
arti
cip
ated
in P
Ad [
F]
MFQ
-SF
[Q]
(0–
26)
6.4
(5.9
)4
—
M
aras
et
al 48
Can
ada
2482
4214
.1 (
11–
20)
GO
DIN
[F/
I]C
DI [
Q]
(0–
54)
7.8
(7.0
)5
—
M
ata
et a
l 49U
nit
ed S
tate
s82
014
(10
–16
)P
AQ-C
A [F
/I]
CD
I [Q
] (0
–54
)1.
6 (2
.0)
4—
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KORCZAK et al 6
Stu
dy
Cou
ntr
yN
% B
oys
Mea
n A
gea
(Ran
ge)
PA
Mea
sure
[F/
I]D
epre
ssio
n M
easu
re [
Q/I
NT]
(Ran
ge)
Dep
ress
ion
Mea
nb (
SD
)
QA
Sco
re
(Ou
t of
7)
Tim
e La
pse
(T2
– T
1)
M
oljo
rd e
t al
50N
orw
ay56
00
15.6
(13
–18
)1-
item
pas
t m
o P
Ad [
F/I]
ASQ
(d
ep s
cale
) [Q
] (0
–60
)2.
5 (0
.8)
4—
M
oljo
rd e
t al
50N
orw
ay53
610
015
.6 (
13–
18)
1-it
em p
ast
mo
PAd
[F/
I]AS
Q (
dep
sca
le)
[Q]
(0–
60)
2.05
(0.
7)4
—
P
iko
and
Ker
eszt
es 51
Hu
nga
ry11
0939
16.5
(14
–21
)N
o. t
imes
exe
rcis
ed p
ast
3
mod
[F]
CD
I-SF
[Q]
(0–
20)
Less
act
ive:
11.
1
(2.7
); r
egu
lar
acti
ve: 1
0.6
(2.4
)
3—
P
rasa
d e
t al
52U
nit
ed S
tate
s85
243
14.8
(–
)4-
item
s fr
om C
DC
YR
BS
[F/I
]
CD
I-SF
[Q]
(0–
20)
2.8
(0.1
)6
—
S
alah
et
al 53
Egyp
t54
653
— (
12–
20)
1-it
em P
A m
easu
red [
F]C
ES-D
C [
Q]
(0–
60)
16.4
(9.
3)5
—
S
hep
her
d e
t al
54N
ew Z
eala
nd
148
0—
(16
–18
)N
ZPAQ
-SF
[F]
DAS
S-4
2 (d
ep it
em)
[Q]
(0-4
2)In
acti
ve: 2
.4 (
1.5)
;
acti
ve: 1
.7
(1.1
); h
igh
ly
acti
ve: 1
.6
(1.4
)
4—
S
igfu
sdot
tir
et a
l 55Ic
elan
d72
3250
—5-
item
PA
scal
ed [
F/I]
10-it
em s
cale
[Q
] (0
–30
)N
o fa
mily
con
fl ic
t: b
oys,
4.2
(4.8
); g
irls
,
6.7
(6.3
).
Fam
ily c
onfl
ict:
boy
s, 7
.0 (
6.0)
;
girl
s, 1
1.4
(7.6
)
4—
S
olta
nia
n e
t al
56Ir
an73
554
— (
15–
19)
IPAQ
[F/
I]G
HQ
(d
ep it
em)
[Q]
—5
—
S
un
et
al 57
Ch
ina
5453
0—
(8–
18)
YRB
S [
F/I]
CD
I [Q
] (0
–54
)12
.2 (
7.7)
6—
S
un
et
al 57
Ch
ina
3789
100
— (
8–18
)YR
BS
[F/
I]C
DI [
Q]
(0–
54)
12.4
(6.
8)6
—
Ta
o et
al 58
Ch
ina
5141
5215
(–
)2-
qu
esti
ons
and
com
pu
ted
MVP
Ad [
F/I]
SC
L-90
[Q
]—
4—
W
iles
et a
l 59U
nit
ed K
ingd
om32
9847
13.8
(–
)Ac
cele
rom
etry
[F/
I]M
FQ [
Q]
—6
—
Lon
gitu
din
al s
tud
ies
B
irke
lan
d e
t al
60N
orw
ay91
255
13N
o. t
imes
per
wk
did
acti
viti
es t
hat
mad
e
you
th s
wea
t/b
reat
hle
ss
[F/I
]
7-it
em s
cale
[Q
]1.
89(0
.96)
512
0 m
o
B
run
et e
t al
61C
anad
a86
047
12.7
MVP
A, o
rgan
ized
sp
ort,
IPAQ
[F/
I]
MD
I [Q
] (0
–50
)9.
34 (
7.5)
596
mo
C
olm
an e
t al
30C
anad
a11
3750
16–
17En
ergy
ind
exd [
F/I]
CID
I-SF
[IN
T]—
316
8 m
o
H
um
e et
al 62
Aust
ralia
155
4014
.5M
odifi
ed A
PAR
Qd a
nd
acce
lero
met
ry [
I]
CES
-DC
[Q
]—
548
mo
Je
rsta
d e
t al
6U
nit
ed S
tate
s49
60
13M
odifi
ed P
YAS
[F]
SC
ID-IV
[IN
T]—
472
mo
M
cKer
cher
et
al 31
Aust
ralia
871
015
min
/wk
leis
ure
PA
[F]
CID
I (se
lf-a
dm
in.)
[IN
T]—
6∼2
40 m
o
M
cKer
cher
et
al 31
Aust
ralia
759
100
15m
in/w
k le
isu
re P
A [F
]C
IDI (
self
-ad
min
.) [
INT]
—6
∼240
mo
M
cPh
ie a
nd
Raw
ana 63
Un
ited
Sta
tes
3676
4915
Mod
ifi ed
PA
scal
e [F
]C
ES-D
(m
odifi
ed)
[Q]
(0–
27)
6.04
(4.
3)6
156–
168
y
N
eiss
aar
and
Rau
dse
pp
64Es
ton
ia18
10
11.4
3DP
AR [
F/I]
CES
-D [
Q]
(0–
60)
20.4
(3.
2)5
24 m
o
R
oth
on e
t al
11U
nit
ed K
ingd
om86
30
11.5
PA
qu
esti
on f
rom
HEA
d [
I]M
FQ-S
F [Q
]—
424
mo
R
oth
on e
t al
11U
nit
ed K
ingd
om81
210
011
–12
PA
qu
esti
on f
rom
HEA
d [
I]M
FQ-S
F [Q
]—
424
mo
TABL
E 1
Con
tin
ued
by guest on May 24, 2020www.aappublications.org/newsDownloaded from
PEDIATRICS Volume 139 , number 4 , April 2017
CI = –0.09 to –0.01). Effect sizes
were stronger in samples examining
a combination of PA frequency and
intensity (k = 27; r = –0.17; 95%
CI = –0.25 to –0.09) compared with
intensity alone (k = 7; r = –0.05;
95% CI = –0.09 to –0.01). Finally,
stronger effect sizes were found in
studies that used validated (k = 29,
r = –0.18; 95% CI = –0.26 to –0.09)
versus nonvalidated PA measures
(k = 21, r = –0.08; 95% CI = –0.11 to
–0.05).
Longitudinal Studies
Because there were significant
differences in effect sizes between
cross-sectional and longitudinal
studies, and because longitudinal
associations may provide
insight into the directionality of
associations, we performed a set
of subanalyses with longitudinal
studies only to more explicitly
examine the magnitude of the
association, as well as the between-
study variability, for studies
assessing a baseline metric of
physical activity and its association
with later depressive symptoms.
There were 14 studies involving
15 926 participants that reported
on longitudinal associations
between PA and depression. Five
studies 6, 8, 30, 64, 66 reported on
depression-related covariates,
including baseline depressive
symptoms, number of weeks
depressed during the preceding
year, body dissatisfaction, social
support, self-efficacy, history of
childhood trauma or stressful
life events, and medication status
( Table 1).
The mean effect size for the
longitudinal association between PA
and depression was r = –0.07 (95%
CI = –0.10 to –0.04). Statistically
significant heterogeneity between
studies was found (Q = 59.25;
P < .0001; I2 = 77.52) and potential
moderator analyses were explored
( Tables 4 and 5). However, because
7
Stu
dy
Cou
ntr
yN
% B
oys
Mea
n A
gea
(Ran
ge)
PA
Mea
sure
[F/
I]D
epre
ssio
n M
easu
re [
Q/I
NT]
(Ran
ge)
Dep
ress
ion
Mea
nb (
SD
)
QA
Sco
re
(Ou
t of
7)
Tim
e La
pse
(T2
– T
1)
S
tavr
akak
is e
t al
65N
eth
erla
nd
s22
3049
11.1
Amou
nt
of P
A/w
kd [
F]Af
fect
ive
pro
ble
ms
from
YS
R
and
CB
CL
[Q]
0.31
(0.
29)
448
–84
mo
S
un
d e
t al
8N
orw
ay23
6049
.513
.74-
qu
esti
ons
abou
t P
A,
vigo
rou
s ex
erci
se,
non
vigo
rou
s P
A,
sed
enta
ry a
ctiv
ity
[I]
MFQ
[Q
] (0
–68
)10
.6 (
11.8
)5
12–
24 m
o
To
seeb
et
al 66
Un
ited
Kin
gdom
614
4314
.5H
eart
rat
e an
d m
ovem
ent
sen
sin
g [I
]
MFQ
[Q
] (0
–68
)13
.7 (
10.6
)5
36 m
o
ABAK
Q,
Adol
esce
nt
Beh
avio
rs,
Atti
tud
es,
and
Kn
owle
dge
Qu
esti
onn
aire
; an
x, a
nxi
ety;
AP
ARQ
, Ad
oles
cen
t P
hys
ical
Act
ivit
y R
ecal
l Q
ues
tion
nai
re;
ASQ
, Ad
oles
cen
t S
tres
s Q
ues
tion
nai
re;
CB
CL,
Ch
ild B
ehav
ior
Ch
eckl
ist:
An
xiou
s/D
epre
ssed
su
bsc
ale;
CD
C Y
RB
S, C
ente
rs f
or D
isea
se C
ontr
ol a
nd
Pre
ven
tion
You
th R
isk
Beh
avio
r S
urv
ey; C
DI/
-SF,
Ch
ildre
n’s
Dep
ress
ion
Inve
nto
ry (
-Sh
ort
Form
); C
ESD
/-C
, Cen
tre
for
Epid
emio
logi
c S
tud
ies
Dep
ress
ion
(-f
or C
hild
ren
); C
HIP
, Ch
ild H
ealt
h a
nd
Illn
ess
Pro
fi le
;
CID
I/-S
F, C
omp
osit
e In
tern
atio
nal
Dia
gnos
tic
Inte
rvie
w (
-Sh
ort
Form
); D
ASS
-42,
Dep
ress
ion
, An
xiet
y, S
tres
s S
cale
-42;
dep
, dep
ress
ion
; 3D
PAR
, 3-d
ay p
hys
ical
act
ivit
y re
call;
DS
RS
C, D
epre
ssio
n S
elf
Rat
ing
Sca
le f
or C
hild
ren
; F, f
req
uen
cy; G
HQ
, Gen
eral
Hea
lth
Qu
esti
ons;
GO
DIN
, God
in L
eisu
re-T
ime
Exer
cise
Qu
esti
onn
aire
; HEA
, hea
lth
ed
uca
tion
au
thor
ity;
I, i
nte
nsi
ty; I
NT,
in
terv
iew
; IP
AQ, I
nte
rnat
ion
al P
hys
ical
Act
ivit
y Q
ues
tion
nai
re; K
KD, k
iloca
lori
es e
xpan
ded
per
kilo
gram
of
bod
y w
eigh
t p
er d
ay;
L, l
ongi
tud
inal
; M
DI,
Maj
or D
epre
ssio
n I
nve
nto
ry;
MFQ
/-S
F, M
ood
an
d F
eelin
gs Q
ues
tion
nai
re (
-Sh
ort
Form
); M
VPA,
mod
erat
e to
vig
orou
s p
hys
ical
act
ivit
y; N
ZPAQ
-SF,
New
Zea
lan
d P
hys
ical
Act
ivit
y Q
ues
tion
nai
re (
-Sh
ort
Form
); P
AQ/-
A/-C
A, P
hys
ical
Acti
vity
Qu
esti
onn
aire
(-f
or A
dol
esce
nts
/-fo
r O
lder
Ch
ildre
n a
nd
Ad
oles
cen
ts);
PAS
CQ
, Ph
ysic
al A
ctiv
ity
Sta
ges
Qu
esti
onn
aire
; PH
Q-9
, Pat
ien
t H
ealt
h Q
ues
tion
nai
re; P
YAS
, Pas
t Ye
ar A
ctiv
ity
Sca
le; Q
, qu
esti
onn
aire
; QA,
qu
alit
y as
sess
men
t; S
APAC
, Sel
f-
Adm
inis
tere
d P
hys
ical
Act
ivit
y C
hec
klis
t; S
CID
-IV =
Str
uct
ure
d C
linic
al In
terv
iew
for
DS
M-IV
; SC
L-90
, Sym
pto
m C
hec
klis
t-90
; sel
f-ad
min
, sel
f-ad
min
iste
red
; SH
APES
, Sch
ool H
ealt
h A
ctio
n P
lan
nin
g an
d E
valu
atio
n S
yste
m; T
1, t
ime
1; T
2, t
ime
2; X
S, c
ross
-
sect
ion
al; Y
SR
, you
th s
elf-
rep
ort;
—, i
nsu
ffi c
ien
t in
form
atio
n a
vaila
ble
in t
he
arti
cle.
a Ag
e lis
ted
is a
t ti
me
1 fo
r lo
ngi
tud
inal
stu
die
s. W
her
e av
aila
ble
, th
e ag
e ra
nge
is r
epor
ted
for
stu
die
s th
at d
o n
ot r
epor
t th
e m
ean
age
.b M
ean
dep
ress
ion
sco
re is
at
tim
e 2
for
lon
gitu
din
al s
tud
ies.
c T
scor
es >
70 a
re r
ecom
men
ded
to
det
erm
ine
clin
ical
sig
nifi
can
ce.
d N
onva
lidat
ed m
easu
re.
e S
pec
ifi ca
lly n
oted
th
at p
arti
cip
ants
wer
e n
ot o
n m
edic
atio
n t
hat
cou
ld in
terf
ere
wit
h h
orm
one
leve
l or
wei
ght
gain
.f N
ot s
pec
ifi ed
; ask
ed a
bou
t p
arti
cip
atio
n in
sp
orti
ng
acti
viti
es.
TABL
E 1
Con
tin
ued
by guest on May 24, 2020www.aappublications.org/newsDownloaded from
KORCZAK et al
the number of studies for several
subgroups was small (eg, there were
only 2 studies with social risk), the
results of these moderator analyses
should be interpreted with caution
( Table 5).
DISCUSSION
This systematic review and meta-
analysis of 50 samples involving
89 894 participants found that a
greater PA level was associated
with fewer depressive symptoms,
although not with decreased
diagnoses of MDD. This association
was stronger for cross-sectional
studies than for longitudinal studies,
in which the mean effect size was
8
FIGURE 2Forest plot of the overall mean effect size, as well as the effect size for each study included in the analysis. Observed effect sizes (r) and 95% CIs are indicated for each study included in the meta-analysis. The black diamond, located at the bottom of the forest plot, indicates the overall mean effect size. Inserting an average effect size across all stratifi ed groups for studies that categorized PA into strata had no effect on the overall mean effect size (r = –0.14; 95% CI: 0.18 to 0.10).
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PEDIATRICS Volume 139 , number 4 , April 2017
significant, but weak. The nature of
the PA was also associated with the
presence of depressive symptoms,
in that PA of increased frequency
and intensity was more strongly
associated with decreased depressive
symptoms compared with PA that
was defined by intensity of activity
alone.
Significant effect sizes were
observed for studies that examined
depressive symptomatology by
using questionnaire measures and
were considerably stronger than
those of studies assessing MDD by
using interview measures. Indeed,
the majority of studies in this meta-
analysis employed self-report
inventories to assess depressive
symptoms (n = 46) rather than
diagnostic interviews (n = 4),
which are considered to be the
gold-standard measure for MDD.
Self-report measures are frequently
used in research studies due to their
ease of administration, low cost,
minimal time requirement, and low
patient response burden. These
measures are useful screening tools;
however, self-report instruments
are limited by their inability to
confirm the presence or absence of
an MDD diagnosis. That increased
PA was more highly associated with
decreased depressive symptoms
in this meta-analysis, as compared
9
FIGURE 3Funnel plot of the meta-analysis of included studies. The y-axis on the funnel plot represents the SE, and the x-axis is the effect size. Observed studies are indicated by open circles. The white diamond represents the observed mean effect size, and the black diamond represents the adjusted mean effect size.
TABLE 2 Examination of Potential Effect Modifi ers in the Association of Physical Activity and Depression: Categorical Variables
Categorical Moderators k N R 95% CI Q Contrast P
Sex 2.13 .15
Girls 15 13 864 –0.11** –0.15 to –0.06
Boys 11 8931 –0.07** –0.10 to –0.03
Social Risk 9.62 .01
No 44 85 440 –0.15*** –0.21 to –0.10
Yes 6 4464 –0.05* –0.09 to –0.01
Physical activity type 9.94 .01
Frequency only 15 35 283 –0.11*** –0.14 to –0.08
Intensity only 7 5604 –0.05* –0.09 to –0.01
Frequency/intensity 27 47 294 –0.17*** –0.25 to –0.09
Physical activity measure 4.71 .03
Nonvalidated 21 53 589 –0.08*** –0.11 to –0.05
Validated 29 36 305 –0.18*** –0.26 to –0.09
Depression measure type 1.38 .24
Interview 4 3263 –0.05* –0.09 to –0.01
Questionnaire 46 86 631 –0.15*** –0.20 to –0.10
Study Design 7.32 .01
Cross-sectional 36 73 978 –0.17*** –0.23 to –0.10
Longitudinal 14 15 926 –0.07*** –0.10 to –0.04
Continent 3.28 .51
North America 19 31 938 –0.08*** –0.11 to –0.04
Europe 8 20 707 –0.09*** –0.13 to –0.05
Australia 12 10 762 –0.09*** –0.12 to –0.05
Asia 7 22 830 –0.08*** –0.08 to –0.11
Africa 4 3655 –0.55* –0.84 to –0.01
* P < .05.** P < .01.*** P < .001.
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KORCZAK et al
with an MDD diagnosis, is a critical
finding. This finding suggests that
individuals who are at risk for more
severe, syndromal-level symptom
burden, impairment, and associated
poor health outcomes may not
respond to the potential preventative
effects of PA. Although it is possible
that these results may also reflect the
relative methodological limitations
associated with the examination of
a dichotomous versus a continuous
variable, our findings are consistent
with previous data reporting that
MDD severity is distinguished from
subsyndromal depressive symptoms
by its decreased sensitivity to
prevention strategies, greater
association with cardiovascular risk
factors and health outcomes, and
greater treatment resistance. 67 – 70
Increased PA was more strongly
associated with decreased depressive
symptoms in cross-sectional studies
compared with longitudinal studies,
where the effect size was small.
Cross-sectional studies are limited
in their ability to probe causality,
because the temporal relationship
between variables cannot be
determined. Thus, it is possible
that the cross-sectional studies
included in this meta-analysis are
actually indicative of the reverse
association of PA and depression:
that children and adolescents with
increased depressive symptoms
are less likely to participate in PA.
Indeed, amotivation, pessimism,
and anhedonia associated with the
depressed state have been reported
to lead to decreased PA among
adult populations. 71 In contrast,
longitudinal studies provide insight
into the direction of the association
and, in the present meta-analysis,
demonstrated a weak inverse
10
TABLE 3 Examination of Potential Effect Modifi ers in the Association of Physical Activity and Depression: Continuous Variables
Continuous Moderators k N Slope SE z Score P
Age at PA assessment 50 89 894 –0.009 0.014 −0.65 .52
Age at depression assessment 50 89 894 0.005 0.005 1.03 .30
Time between assessments 50 89 894 0.008 0.003 1.46 .15
Publication year 50 89 894 0.002 0.009 0.17 .87
TABLE 4 Examination of Potential Categorical Effect Modifi ers in Studies With Longitudinal Associations Between Physical Activity and Depression
Categorical Moderators k N R 95% CI Q Contrast P
Sex 1.16 .28
Girls 4 812 –0.10* –0.20 to –0.00
Boys 2 2411 –0.03 –0.11 to –0.04
Social Risk 12.13 .0001
No 12 14 251 –0.09*** –0.12 to –0.05
Yes 2 1675 –0.01 –0.03 to 0.01
Physical activity type 2.44 .30
Frequency only 5 8032 –0.06** –0.08 to –0.03
Intensity only 5 3090 –0.04+ –0.09 to 0.01
Frequency/intensity 4 4804 –0.14* –0.25 to –0.02
Physical activity measure 11.66 .01
Nonvalidated 4 5042 –0.01+ –0.03 to 0.00
Validated 10 10 884 –0.10*** –0.14 to –0.05
Depression measure type 1.12 .29
Interview 4 3263 –0.05* –0.09 to –0.01
Questionnaire 10 12 663 –0.08*** –0.12 to –0.04
Continent 1.31 .52
North America 4 6169 –0.06*** –0.08 to –0.03
Europe 7 7972 –0.09** –0.15 to –0.04
Australia 3 1785 –0.05* –0.10 to –0.01
+ P < .10.* P < .05.** P < .01.*** P < .001.
TABLE 5 Examination of Continuous Moderators in Studies With Longitudinal Associations Between Physical Activity and Depression
Continuous Moderators k N Slope SE z Score P
Age at physical activity 14 15 926 0.004 0.009 0.45 .66
Age at depression 14 15 926 0.001 0.002 0.47 .64
Time between assessments 14 15 926 0.001 0.003 0.45 .65
Publication year 14 15 926 0.009 0.009 1.03 .30
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PEDIATRICS Volume 139 , number 4 , April 2017
relationship between PA and future
depressive symptoms measured 2 to
17 years later, suggesting that PA has
a weak but positive association with
future mood.
Studies that included a measure of
both increased PA frequency and
intensity demonstrated stronger
associations with depressive
symptoms than those that used
measures of intensity alone. This
finding is consistent with other
systematic reviews examining the
role of PA as an intervention for
depressed adults. 1 Currently, some
clinical guidelines recommend
the inclusion of 45 minutes of
moderately intense exercise
at least 3 days per week in the
treatment of MDD among adults. 72
In contrast, guidelines for general
health promotion by the Canadian
Pediatric Society 73 and American
Academy of Pediatrics 74 recommend
that children and adolescents get
at least 60 minutes of moderate
to vigorous PA daily to maintain
general health. As such, the findings
from the current study support the
inclusion of both the PA frequency
and intensity components in the
Canadian Pediatric Society and
American Academy of Pediatrics
recommendations with respect
to the benefit to depressed mood.
Many hypotheses regarding the
mechanism by which PA may
lead to improved mood have
been theorized, including via
antiinflammatory effects, increased
growth factors leading to neural
plasticity, neuroendocrine effects
on the hypothalamic-pituitary-
adrenal axis and insulin sensitivity,
and improvements in self-
efficacy.75 – 77 However, neither
the pathophysiological pathways
themselves nor whether they are
specific to mood state are known.
These factors are important for
determining rational prevention
versus treatment strategies,
gaining insight into the etiology of
depression, and for research into
novel treatments for depression for
medically ill populations and those
unable to participate in PA.
Studies that examined the
association of PA with depression
in samples of higher social risk (eg,
low income, minority, or involved in
child protective services) reported
weaker effect sizes than those of
lower-risk groups. Socioeconomic
status and its associated risk factors
(eg, disadvantaged neighborhoods)
explain a significant proportion
of the variance in childhood
psychopathology, including
depression. 78 Because children
in high–social risk environments
may be exposed to many more
risk factors for depression,
including lower socioeconomic
status, 79 increased PA may have
relatively less influence with
respect to the proportion of the
variance in depression it explains
when compared with children of
lower social risk. 80 Also, because
measures of depression and PA
have traditionally been developed
in samples of low social risk, they
may be less well calibrated to
capture the variation in depression
or PA seen in high–social risk
children. 81, 82 These results should
be interpreted with caution,
however, because few studies
have examined the association of
PA with depression in high–social
risk samples. Given the increased
prevalence of both depression and
obesity in populations of high social
risk, however, additional research
examining potential targets for
prevention among this vulnerable
group of children is needed.
As the first study to conduct a meta-
analytic review of the potential
protective association of childhood
PA with depression, this study
has many strengths, including
the analysis of a large number of
studies to increase the precision of
effect size estimates, subanalysis of
cross-sectional versus longitudinal
associations, and examination
of PA frequency and intensity as
potentially contributing effect
modifiers. However, our findings
must be interpreted within the
context of the limitations of this
study. The measurement of PA in
the majority of studies relied on
self-report measures of frequency,
intensity, and type of activity,
which were not correlated with
objective measures of activity (eg,
accelerometry). This also reflects
a limitation of the PA literature
more broadly, in that the use of
standardized instruments that
have demonstrated reliability and
validity was not consistent across
studies. The current meta-analysis
demonstrated that studies with
validated measures of PA had
stronger effect sizes than those
that used nonvalidated measures.
Thus, future PA research should
focus on the methodology for PA
measurement in children and
adolescents to increase confidence
in the study results. In addition,
the majority of the literature relies
on the self-report of depressive
symptoms, with few studies able to
confirm a diagnosis of depression,
leading to wide precision estimates
of the magnitude of the effect of
PA on clinical depression. Finally,
we only included studies that were
published in English, and this
inclusion criterion may limit the
generalizability of our findings to
predominantly English-speaking
countries.
CONCLUSIONS
This systematic review and meta-
analysis finds that increased PA
in childhood and adolescence is
associated with decreased depressive
symptoms. Substantive moderators
of this association include (1) study
design, with the strongest association
found in cross-sectional studies;
(2) type of PA, with a combination
of PA frequency and intensity
resulting in the greatest effect on
11 by guest on May 24, 2020www.aappublications.org/newsDownloaded from
KORCZAK et al
depressive symptoms; and (3)
depression measure, with a stronger
protective effect of increased PA
for depressive symptoms than for
a clinical diagnosis of MDD. Taken
together, this study suggests that
PA in childhood and adolescence is
associated with improved concurrent
symptoms of depression, particularly
when undertaken regularly and with
vigor, and has weak but significant
effects on future depressive
symptoms. Future research is
needed to advance the knowledge
of PA measurement, elucidate the
mechanism of association between
PA and depression, and examine the
longitudinal relationships between
PA, depression, and health outcomes
to determine the critical periods in
which preventative efforts may be
most effective.
ACKNOWLEDGMENT
We thank Ms Qi Fang (University
of Toronto) for assistance in the
literature search.
12
ABBREVIATIONS
CI: confidence interval
MDD: major depressive disorder
PA: physical activity
Copyright © 2017 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE: The authors have indicated they have no fi nancial relationships relevant to this article to disclose.
FUNDING: Research support was provided to Dr Madigan by the Alberta Children’s Hospital Foundation and the Canada Research Chairs program.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential confl icts of interest to disclose.
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