Physical Activity and 3-Year BMI Change in Overweight
and Obese Children
WHAT’S KNOWN ON THIS SUBJECT: Effective interventions are
still elusive for the large numbers of children affected by
overweight/obesity. The value of targeting physical activity (PA)
remains unclear because its predictive relationship with
improved BMI is still surprisingly poorly quantified.
WHAT THIS STUDY ADDS: In overweight and mildly obese children
presenting to primary care, 3-year changes in PA (especially the
moderate-vigorous component) predicted BMI outcomes.
However, the effect was small, possibly explaining the
disappointing BMI outcomes of brief primary care interventions
targeting PA.
abstract
OBJECTIVES: Targeting physical activity (PA) is a mainstay in obesity
treatment, but its BMI benefits are poorly quantified. We studied longterm predictive PA-BMI relationships in overweight/obese children
presenting to primary care.
METHODS: Three-year follow-up of 182 overweight/obese 5- to 10-yearolds recruited from 45 Melbourne general practices. Predictor: 7-day
accelerometry (counts per minute, cpm). Outcomes: change in BMI
z score, BMI category, and clinically significant BMI improvement
(z score change $0.5). Analysis: Linear and logistic regression.
RESULTS: Mean (SD) baseline and 3-year BMI z scores were 1.8 (0.6)
and 1.8 (0.7), and mean (SD) activity scores 334 (111) and 284 (104)
cpm, respectively. Baseline activity did not predict BMI change. However, for every 100 cpm increase in change in activity over 3 years,
BMI z score fell by 0.11 (95% confidence interval [CI] 0.03–0.20; P =
.006). There were also trends toward greater odds of staying in the
same, versus moving to a higher, BMI category (odds ratio 1.85, 95%
CI 0.99–3.46) and clinically significant BMI improvement (odds ratio
1.96, 95% CI 0.90–4.27; P = .09). Change in percentage time spent in
moderate-vigorous (P = .01), but not sedentary (P = .39) or light (P =
.59), activity predicted reduced BMI z score.
CONCLUSIONS: Sustained increase in moderate-vigorous PA predicts
reducing BMI z score over 3 years in overweight/obese children
presenting to primary care. However, the small BMI change associated
with even the largest activity changes may explain disappointing BMI
outcomes of brief primary care interventions targeting PA. Pediatrics
2013;131:e470–e477
e470
TRINH et al
AUTHORS: Andrew Trinh, MBBS,a,b Michele Campbell, PhD,a,c
Obioha C. Ukoumunne, PhD,d Bibi Gerner, MPsych,a,c and
Melissa Wake, FRACP, MDa,b,c
aCentre
for Community Child Health, Royal Children’s Hospital
Parkville, and cMurdoch Childrens Research Institute, Parkville,
Australia; bDepartment of Paediatrics, University of Melbourne,
Parkville, Australia; and dPenCLAHRC, Peninsula College of
Medicine and Dentistry, University of Exeter, Exeter, United
Kingdom
KEY WORDS
BMI, obesity, child, PA, primary health care, longitudinal studies
ABBREVIATIONS
CI—confidence interval
cpm—counts per minute
LEAP2—Live Eat and Play trial
MVPA—moderate-vigorous PA
OR—odds ratio
PA—physical activity
The project was initiated and supervised by Dr Wake with Dr
Campbell. Dr Wake and Dr Trinh cowrote the paper, with all
authors providing critical contributions to reviewing and
editing, as well as approval of its final version. Ms Gerner was
the project manager for the original 12-month LEAP2 trial, which
was planned and implemented by Dr Wake with the LEAP2 trial
coinvestigators including Dr Ukoumunne. Dr Trinh, Ms Gerner,
and Dr Emily Incledon managed the 3-year follow-up and
collected the outcomes data. Dr Ukoumunne supervised and
finalized Dr Trinh’s analyses. Dr Wake is the guarantor and
accepts full responsibility for the conduct of the study, had
access to the data, and controlled the decision to publish.
www.pediatrics.org/cgi/doi/10.1542/peds.2012-1092
doi:10.1542/peds.2012-1092
Accepted for publication Oct 4, 2012
Address correspondence to Melissa Wake, FRACP, MD, Centre for
Community Child Health, Royal Children’s Hospital, Flemington Rd,
Parkville 3052 AUSTRALIA. E: [email protected]
(Continued on last page)
ARTICLE
Childhood obesity is endemic in many
countries,1–3 and its long-term health
and social consequences urgently demand reduction strategies.4,5 However,
slow progress in learning how to effectively prevent6 and treat7 it may reflect fundamental lack of knowledge as
to what predicts successful long-term
weight loss in children.
Physical activity (PA) has long been
integral to a multifaceted approach to
childhood obesity, but the extent to
which it contributes to changing BMI in
obese children remains surprisingly
poorly quantified. This may reflect the
challenges of PA interventions (the
most robust way to quantify a causal
association8) to modify obesity. In the
most recent Cochrane review7 of childhood obesity trials, only 5 of 12 PA intervention studies satisfied the quality
criteria, that is, randomized controlled
trials for children aged ,18 years followed for at least 6 months; of these,
results were extremely variable, most
had null findings, and no conclusive
associations could be made.
Longitudinal studies analyzing PA and
BMI in obese children could help inform
future PA interventions. However, much
of the existing longitudinal literature
relates to preventing BMI gain across
the whole spectrum rather than BMI
loss in the overweight and obese subgroups. Furthermore, the subjective
methods often used to assess PA impose methodologic heterogeneity and
measurement limitations,9 with 12 of
17 longitudinal studies in a recent metaanalysis studying activity and weight
change assessing children’s PA by
questionnaire only.10 Results also
vary according to nature of activity,11
gender,12 and analytic method.13
Thus, a 2011 meta-analysis suggested
no prospective association between
measured PA and changing fat mass in
children, while acknowledging the
likely role of substantial study heterogeneity despite stringent steps to
PEDIATRICS Volume 131, Number 2, February 2013
minimize impacts of internal and external bias.14
In the face of this conflicting literature,
high-quality longitudinal studies examining the size and nature of associations
between PA and BMI in overweight and
obese children presenting to primary
care could inform future interventions
focusing on long-term weight loss in this
important population. However, we have
not been able to locate any such studies.
To address this gap, we draw here on an
existingcommunitysampleofoverweight/
mildly obese 5- to 10-year-old children15
to determine whether (1) initial PA level
and (2) change in PA over a 3-year period predict BMI outcomes broadly relevant to epidemiologic, public health,
and clinical perspectives, expressed
respectively as
1. reduced BMI z score;
2. increased odds of dropping to
a lower BMI category; and/or
3. increased odds of a clinically significant BMI improvement (ie, loss
of at least 0.5 BMI z score units).
METHODS
Design and Sample
For this longitudinal study, spanning
3 time points over 3 years, participants were drawn from the second
Live Eat and Play randomized trial
(LEAP2, ISRCTN52511065). The trial’s
design and outcomes are reported
elsewhere.15
Briefly, the LEAP2 trial was nested within
a large BMI cross-sectional survey
in 45 family practices in Melbourne,
Australia. From May 2005 to July 2006,
all children aged between 5 years and
their 10th birthday attending these
practices were invited into the BMI
survey and became eligible for the trial if
overweight/obese by International Obesity TaskForce cutpoints.16 Children receiving an ongoing weight-management
program or with BMI z score $3.0
were excluded, on the basis that a brief
secondary prevention approach would
be inappropriate; 3958 children were
surveyed, 781 were eligible, and 258
were recruited to the trial. The trial’s
brief parent-focused behavioral intervention focused on sustainable changes
in nutrition and/or PA but, although acceptable and fully implemented, did not
improve BMI trajectories, dietary intake,
or PA outcomes relative to controls over
the course of a year.15
We report here on the natural history of
PA and BMI over 3 years, combining
intervention and control groups into
a single longitudinal cohort as the
2 groups were similar throughout
(nonetheless, treatment status was
assessed as a potential covariate in the
multivariate model; see Analysis). Objective PA, our key predictor, was
measured for the first time 6 months
after the trial commenced, which thus
comprises the baseline time point for
this article. Additional follow-up occurred 6 months and ∼3 years later (ie,
1 and 3.5 years after trial entry, respectively). As at the earlier follow-up,
the original intervention and control
groups were similar at the end of this
period, with mean (SD) BMI z scores of
1.9 (0.7) and 1.8 (0.6), respectively, and
adjusted mean difference of 0.04 (95%
confidence interval [CI] –0.11 to 0.11,
P = .61).
Procedures
At every time point, researchers blind to
group allocation saw the child at Melbourne’s Royal Children’s Hospital or at
the family home, after a mailed parent
questionnaire. Over 30 minutes, the
researcher administered a questionnaire to the child, recorded child and
parent anthropometric measurements, and fitted an accelerometer
that parents returned via prepaid
registered post.
This study was approved by the hospital’s Ethics in Human Research Committee (EHRC 25006). Parents provided
e471
written consent at the start of the study
and at the 3-year follow-up.
Measures
Outcome
Children were measured by trained
researchers at each time point (and by
trained practice staff at trial entry)
using standard protocols. Weight was
measured once in light clothing to the
nearest 100 g using digital scales
(Tanita ModelTHD-646, Tokyo, Japan),
and height was measured twice to the
nearest 0.1 cm using a portable rigid
stadiometer (Invicta Model IPO955,
Oadby, United Kingdom). Height measurements were averaged unless they
differed by $0.5 cm (∼10% of instances), when a third was taken and the
mean of the closest 2 values used.
$20 minutes of consecutive “0” counts,
or counts .0 that were constant for
$10 minutes. Day 1 data were deleted to
minimize the potential effect of children’s
initial activity being influenced by
awareness of the monitor. We expressed
PA as mean activity in counts per minute
(cpm) and, using Puyau’s thresholds,19
percentage time spent in each of sedentary (,100 cpm), light (100–899 cpm),
and moderate-vigorous ($900 cpm) PA
(MVPA). Change in PA was calculated by
subtracting baseline from outcome PA
in cpm.
Confounders comprised parent BMI
(self-reported; measured if available),
education (did not complete school,
completed school, degree), and country
of birth (born in Australia or not). As
a proxy for neighborhood socioeconomic status, we used the 2001 censusderived Australian SocioEconomic Indexes for Areas disadvantage quintile20
for the child’s postal code.
Analysis
We used regression models to describe
the relationship of (1) PA and (2) change
Change in BMI was quantified by using 3
outcomes, relevant to epidemiologic,
public health and clinical perspectives,
respectively. First, BMI (kg/m2) was converted to age- and gender-standardized
z scores, using the 1990 UK Growth Reference.17 Second, we classified participants as nonoverweight, overweight, or
obese according to International Obesity
TaskForce BMI cutpoints16 and, from this,
derived a multinomial outcome of
change in BMI status with 3 categories:
increased by at least 1 BMI category,
stayed in same category, or decreased
by at least 1 category. Finally, clinically
significant BMI improvement, a binary
outcome, was defined as a $0.5 SD unit
decrease in BMI z score.18
Predictors
PA was measured at all 3 time points by
multiaxial Actical accelerometers (Mini
Mitter, Bend, Oregon), with epoch length
set to 60 seconds. Participants were
asked to wear the accelerometer for 7 full
days. The minimum data requirement for
analysis was $5 “valid days,” with a valid
day having $10 hours of nonmissing
data between 6 AM and 11 PM. Missing
data were defined as segments with
e472
TRINH et al
FIGURE 1
Participant flow through the LEAP trial and 3-year follow-up study.
ARTICLE
in PA (both in cpm) with each of the 3 BMI
change outcomes. Separate models
were fitted to examine change overeach
of 3 periods: baseline to 3 years (main
analysis), and baseline to 6 months and
6 months to 3 years (secondary analyses). In each regression model, the
initial level of PA or change in PA were
used to predict change in BMI in the
same period. Linear, multinomial logistic, and logistic regression were
used for change in BMI z score, change
in BMI category (reference: increasing
BMI category), and the binary outcome
clinically significant reduction in BMI z
score, respectively. All regression coefficients and odds ratios (ORs) presented are the changes in the BMI
outcomes per 100 cpm increase in the
change in activity level during the period of interest (because an increase of
1 cpm is negligible).
Crude analyses used only the activity
variables as predictors. For multivariable analyses, we also adjusted for trial
arm status and the potential confounders, with the exception of the
change in BMI category for which age
was the only included confounder, because ,30 subjects were in the increasing BMI outcome category. A rule
of thumb for multinomial and logistic
regression is that there should be at
least 10 participants per predictor in
the smallest outcome category to obtain
valid estimates of standard error (SE).21
Finally, in post hoc analyses, linear regression was used to examine the relationship of change in BMI z score
outcomes between baseline and 3 years
with percentage of time spent in each of
sedentary, light PA, and MVPA. Both the
initial percentage of time and change in
the percentage of time spent in a particular type of activity were used as
predictors. The regression coefficients
presented are the changes in the BMI
z score (mean increase) corresponding to an absolute increase of 10 percentage points in the specified activity
PEDIATRICS Volume 131, Number 2, February 2013
RESULTS
study, based on the CONSORT flowchart.23 Anthropometry data were collected from 250 of the 258 trial
participants (96.9%) at baseline, 242
(93.8%) at 6 months, and 182 (70.5%) at
3 years, of whom 231, 201, and 126,
respectively, had both BMI and usable
accelerometry data.
Figure 1 shows the participant flow
through the LEAP2 trial and follow-up
Table 1 shows the baseline characteristics of those lost and retained at the
intensity. Again, we rescaled the predictor
in this manner because a difference of
1 percentage point is negligible.
All analyses were carried out by using
Stata 11 software.22
TABLE 1 Baseline Characteristics for Those Retained and Lost to Follow-up at 3 Years for the
Whole Sample and the Accelerometer Subsample
Baseline Variable
Accelerometer Samplea
Whole Sample
Child
Male gender, %
Age (y), mean (SD)
BMI status,b %
Overweight
Obese
BMI z score, mean (SD)
Mother
Age (years), mean (sd)
Born in Australia, %
BMI, mean (sd)
Education, %
Didn’t complete school
Completed high school
Degree
SEIFA disadvantage quintile, %
1 (most disadvantaged)
2
3
4
5 (least disadvantaged)
Retained
n = 182
Not Retained
n = 76
Retained
n = 126
Not Retained
n = 132
40.7
7.4 (1.4)
36.8
7.7 (1.4)
38.9
7.3 (1.4)
40.1
7.7 (1.4)
76.9
23.1
1.9 (0.5)
75.0
25.0
1.9 (0.5)
81.0
19.1
1.8 (0.5)
72.0
28.0
2.0 (0.5)
39.4 (4.9)
72.0
27.3 (5.4)
39.5 (4.6)
65.3
26.1 (5.6)
39.0 (5.0)
71.4
27.0 (5.9)
39.7 (4.7)
68.7
26.9 (5.0)
30.3
33.7
36.0
37.0
34.2
28.8
30.1
35.0
35.0
34.4
32.8
32.8
21.4
15.4
20.9
20.9
21.4
25.0
22.4
23.7
13.2
15.8
23.8
13.5
20.6
20.6
21.4
21.2
21.2
22.7
16.7
18.2
Sample size in retained whole sample group ranges from 170 to 182; in not retained whole sample group, from 73 to 76; in
retained accelerometer sample group, from 119 to 126; and in not retained accelerometer sample group, from 125 to 132.
SEIFA= SocioEconomic Indexes for Area.
a Sample size determined by those children who had valid accelerometry readings at 3-y follow-up.
b Based on cutpoints of International Obesity Taskforce.
TABLE 2 Child PA and Anthropometry Measures at Each Time Point
Measure, All Mean (SD)
Time Points
Baseline (0 mo)
PA
Counts/min
% Time in intensitiesa
Sedentary activity
Light activity
MVPA
Anthropometry
BMI z score
a
6 mo
3y
n
Value
n
Value
n
Value
231
334 (111)
201
339 (134)
126
284 (104)
231
231
231
45.8 (7.3)
38.5 (5.0)
15.7 (5.0)
201
201
201
45.1 (8.8)
39.2 (6.0)
15.7 (5.7)
126
126
126
50.2 (9.0)
36.4 (6.9)
13.4 (4.7)
250
1.8 (0.6)
242
1.8 (0.6)
182
1.8 (0.7)
Intensities based on Puyau’s thresholds19: sedentary (,100 cpm), light PA (100–899 cpm), and MVPA ($900 cpm).
e473
3-year follow-up. Those retained
were broadly similar to those lost to
follow-up, although children retained
in the accelerometer sample were
slightly younger and had lower BMI z
score.
Table 2 summarizes the anthropometric and PA variables for the whole cohort at each follow-up, and Table 3
summarizes the changes in these variables between time points. Among
those providing anthropometric data
at both baseline and 3 years, the mean
PA dropped by 54 cpm. Although mean
BMI z score changed by only 0.006 over
the 3-year period, there was considerable variability across participants,
ranging from a fall in BMI z score of 1.2
to an increase of 1.4; 19% moved to
a lower BMI category, with 10%
achieving a clinically significant BMI z
score improvement of $0.5.
There was little evidence that the initial
level of PA at the start of each period was
associated with subsequent change in
the BMI-related outcomes (data not
presented in tables). For example, between baseline and 3 years, adjusted
analyses demonstrated that baseline PA
did not predict a change in BMI z score
(regression coefficient = 0.02; 95% CI: –
0.04 to 0.09; P = .48), a change in BMI
category (OR = 0.70; 95% CI: 0.43–1.13;
P = .15), or a clinically significant BMI
improvement of $0.5 z score18 (OR =
1.04; 95% CI: 0.63–1.72; P = .87). The
remainder of this section therefore
focuses on the relationship between
change in PA and change in BMI in the
corresponding period.
Table 4 shows evidence that, unlike
baseline PA, change in PA between
baseline and 3 years is associated with
BMI change. The adjusted regression
coefficient indicates that an increase
of 100 cpm in change in PA between
baseline and 3 years corresponds to
a fall of 0.11 (95% CI 0.03–0.20, P = .006)
BMI z score units. Evidence that change
in PA predicted the 2 categorical
e474
TRINH et al
TABLE 3 PA and Anthropometry Outcome Change Between Time Points
Outcome
Change Between Time Points
0 mo–3 y
PA
Counts/min, mean (SD)
% time in intensities,a mean (SD)
Sedentary
Light PA
MVPA
Anthropometry—Child
BMI z score, mean (SD)
BMI category,b %
Increase
Same
Decreased
BMI z score fell $0.5 SD, %
0 mo–6 mo
n
Value
n
125
254 (120)
196
125
125
125
4.9 (9.4)
22.5 (7.3)
22.4 (5.1)
181
181
0.006 (0.46)
14.4
66.3
19.3
9.9
181
6 mo–3 y
Value
n
Value
5 (120)
119
268 (158)
196
196
196
20.9 (8.7)
0.8 (6.2)
0.1 (5.4)
119
119
119
6.6 (11.5)
23.8 (8.6)
22.8 (6.4)
242
242
20.01 (0.29)
179
179
0.04 (0.48)
10.7
77.7
11.6
5.4
242
179
15.1
67.6
17.3
12.3
a
Intensities based on Puyau’s thresholds19: sedentary (,100 cpm), light PA (100–899 cpm), and MVPA ($900 cpm).
b Based on International Obesity TaskForce cutpoints.
outcomes was consistent with these
findings but more marginal. Thus, the OR
for staying in the same, as opposed to
moving to a higher, BMI category with
increasing change in PA was 1.85 (95% CI
0.99–3.46). The OR for achieving a clinically significant BMI improvement18 was
1.96 (95% CI 0.90–4.27, P = .09) for every
TABLE 4 Estimated Coefficients and ORs for the Relationship of BMI Improvement (Outcomes)
With Change in PA (Predictor).
BMI Change Metric for
the Regression on PA
Change (in cpm)
for Each Period
Mean change in BMI z score
Baseline to 3 y
Baseline to 6 mo
6 mo to 3 y
Odds of moving to
lower BMI category
Baseline to 3 y
Increase (reference
category)
Stay the same
Decrease
Baseline to 6 mo
Increase (reference
category)
Stay the same
Decrease
6 mo to 3 y
Increase (reference
category)
Stay the same
Decrease
Odds of clinicallysignificant
BMI z score
improvement
($0.5 SD)
Baseline to 3 y
Baseline to 6 mo
6 mo to 3 y
a
Unadjusted Results
a
n
Coeff/OR
124
196
118
20.08
20.03
20.08
95% CI
Adjusted Results
P
20.16 to –0.005 .04
20.07 to 0.009 .14
20.16 to 0.0004 .05
124
Coeff/ORa
115
184
111
20.11
20.03
20.15
95% CI
P
20.20 to –0.03 .006
20.08 to 0.01 .14
20.24 to –0.06 .001
124
1
1.69
0.99
.07
.05
0.94 to 3.04
0.48 to 2.03
1.85
1.08
196
0.99 to 3.46
0.51 to 2.31
196
1
1.59
1.58
.20
.20
0.96 to 2.65
0.87 to 2.88
1.60
1.60
118
0.96 to 2.67
0.87 to 2.95
118
1
124
196
118
n
.72
1.05
1.27
0.63 to 1.77
0.66 to 2.44
1.51
1.14
2.71
0.81 to 2.84
0.73 to 1.78
1.39 to 5.27
.20 115
.56 184
.003 111
Regression coefficients (Coeff) and OR correspond to 100 cpm increase in activity.
.52
1.18
1.48
0.68 to 2.06
0.74 to 2.98
1.96
1.28
4.37
0.90 to 4.27
0.69 to 2.36
1.82 to 10.5
.09
.44
.001
ARTICLE
additional 100 cpm increase in PA between baseline and 3 years.
Similar trends were seen in the same
direction as over the baseline-to-3-year
period when analyzing change over the
shorter baseline-to-6-month and the 6
month-to-3-year periods for all 3 BMI
change outcomes (Table 4), although
these reached statistical significance
at the 5% level only between 6 months
and 3 years for change in BMI z score
and loss of $0.5 BMI z score units.
Because these findings suggest that an
increase in PA is associated with improved long-term BMI outcomes, we
examined in post hoc analyses the
components of PA intensity in relation to
change between baseline and 3 years in
BMI z score. Table 5 shows that in adjusted analyses, there was evidence
that change in percentage of time
spent in moderate-vigorous PA (P =
.01), but not sedentary (P = .39) or light
(P = .59) activity, predicted change in
BMI z score, with BMI z score decreasing by 0.24 for every 10 percentage points increase in percentage time
spent in MVPA.
DISCUSSION
Principal Findings
We conclude that a long-term increase
in MVPA may improve long-term BMI in
overweight and obese primary schoolage children presenting to primary
care. Although this finding is novel in
children, it is supported by recently
reported adult simulation studies24 and
by both school-based trials25 and observational clinical follow-up26 studies
in which only prolonged intervention
over 1 to 2 years were successful.
However, the long-term reductions in
absolute BMI were small even with the
largest increases in observed PA.
Interpretation in Light of Other
Studies
Given the current research interest in
incidental, light PA, it is also intriguing
that improvements in BMI were most
strongly associated with changes in
MVPA, rather than sedentary or light PA.
This is supported by Kriemler’s recent
yearlong trial of a daily school-based
universal PA program that successfully
reduced BMI gain in Grades 1 and 5
children via an increase in total daily
MVPA, but not light, PA.25 It may also
explain why the Scottish Childhood
Overweight Treatment Trial (SCOTT)
randomized trial targeting obese 5to 11-year-olds did not reduce BMI
gain, despite successfully increasing
total PA via increasing the light (but
not moderate or vigorous) component
of PA.27
There was little evidence that levels of
baseline PA level alone were associated
with subsequent BMI change. We are
confident in this finding, given our objective measurement of PA, the similar
findings for both of the shorter periods,
TABLE 5 Relationship of Change in BMI z Score From Baseline to 3 Years (Outcome) With Change
in % Time Spent in Different PA Intensities (Predictor)
Change in % Time Spent
in Each PA Intensitya
Sedentary
Light
MVPA
Change in BMI z score between baseline and 3yrs
Adjustedb
Unadjusted
Coefficientc
95% CI
P
Coefficientc
95% CI
P
0.005
0.05
20.15
20.09 to 0.10
20.06 to 0.17
20.32 to 0.04
.92
.36
.12
0.04
0.03
20.24
20.05 to 0.14
20.09 to 0.16
20.43 to –0.05
.39
.59
.01
Samples size was 124 in unadjusted analyses and 115 in adjusted analyses.
a Intensities based on Puyau’s thresholds19: sedentary (,100 cpm), light PA (100–899 cpm), and MVPA ($900 cpm).
b Adjusted for initial PA, intervention status, gender, age, SocioEconomic Indexes for Areas disadvantage quintile, maternal
BMI, maternal education.
c Regression coefficient is mean change in BMI z score corresponding to 10 percentage points increase in PA intensity.
PEDIATRICS Volume 131, Number 2, February 2013
and the study’s congruence with
accelerometry-based findings in a population sample of similarly aged children.28 This conclusion seems more
robust than the studies that do report
associations because the latter have
mainly measured PA by questionnaire.11,29,30 Although it has been suggested that lack of associations
between baseline activity and subsequent BMI28,31 could be explained by
reverse causation (ie, it is BMI that
determines PA),28 these null findings
seem predictable to us given the exquisite day-to-day homeostatic balance
between energy input and output32 in
all but the most rapid states of BMI
change. In other words, one would not
expect PA at any 1 time point to predict
weight change.
Similarly, we cannot exclude the possibility that improved BMI led to the
sustained increase in PA, rather than
the other way round. Although it has
been suggested28 that reverse causality
could also explain the reported lack
of efficacy of trials targeting PA to reduce childhood obesity,6,33 it seems
more likely that this inefficacy is due to
the generally short and/or low-intensity
nature of most interventions.34 Nonetheless, weight loss itself may well enhance PA, and bidirectional influences
seem likely.
Strengths of the study include its repeated, prospective, objective measures
of both PA and BMI over a prolonged
period in a community-based overweight sample recruited through primary care, so that our results could be
relevant to policymakers, public health
advocates, and clinicians in many
countries.35–38 The prolonged follow-up
is a particular strength in a field that
systematic reviews show is dominated
by short follow-up and evidence of attenuation of effect by 12 months in virtually all intervention trials.7,34 It
supports, but goes well beyond, a recent
study in obese Hispanic adolescents
e475
showing that BMI improvement is predicted by changes in, but not initial, PA
levels in the short-term (6 months).39
Limitations include our relatively small
sample size, resulting in wide confidence intervals for some ORs because
of the small numbers of children who
were able to decrease a BMI category or
achieve clinically significant weight
loss. Confirming these findings would
require a larger sample size or pooling
data across studies. Nonetheless, with
.100 children, this study compares
favorably to the sample sizes ranging
from 39 to 138 in Wilks’s recent systematic review of associations between PA and adiposity.14 Two possible
threats to internal validity (the original
randomized trial design and attrition)
seem unlikely to have altered our
conclusions because we adjusted in
analyses for the low-intensity intervention
and, despite a slightly greater loss of
obese children and those with lesseducated mothers, those lost to
follow-up generally resembled those
retained. Additionally, we acknowledge
that although accelerometry is vastly
superior to self- reported PA, limitations remain such as interpreting
a zero reading (eg, device removal
vs taking a nap). Finally, examination
of nutrition was beyond the scope of
this study, as were measurements of
total energy expenditure and body
composition.
obese children presenting to primary
care. However, the small BMI change
associated with even the largest
changes in PA may explain why so
many randomized trials of brief primary care interventions targeting PA
have had disappointing BMI outcomes. Multilevel and multisectoral
efforts are likely to be needed to increase children’s endemically low
levels of PA to the point that it can
become a route to a healthier-weight
population.
A sustained increase in PA, especially
the moderate-vigorous component,
predicts reduced BMI z score over a 3year follow-up period in overweight/
ACKNOWLEDGMENTS
We thank our coinvestigators in the
original LEAP2 trial, Dr Emily Incledon,
and all the children, families, and research assistants who participated in
the various phases of the LEAP2 trial
and its follow-up.
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2):194–201
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Must A, Tybor DJ. Physical activity and
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(Continued from first page)
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).
Copyright © 2013 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
FUNDING: The LEAP2 trial was funded by the Australian National Health and Medical Research Council (NHMRC) project grant 334309. Dr Wake was supported by
NHMRC Career Development Award 546405 and Dr Campbell by NHMRC Capacity Building Grant 436914. Murdoch Childrens Research Institute research is
supported by the Victorian Government’s Operational Infrastructure Support Program. The European Centre for the Environment and Human Health (part of the
Peninsula College of Medicine and Dentistry, which is a joint entity of the University of Exeter, the University of Plymouth, and the National Health Service in the
southwest) is supported by investment from the European Regional Development Fund and the European Social Fund Convergence Programme for Cornwall and
the Isles of Scilly.
PEDIATRICS Volume 131, Number 2, February 2013
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