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Parent Awareness of Young Children’s Physical Activity

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Parents who overestimate their child's physical activity (PA) level may not encourage their children to increase their PA. We assessed parental awareness of child PA, and investigated potential correlates of overestimation. Child PA (accelerometer) and parent-classified child PA ['active' ≥60min/day vs. 'inactive' <60min/day moderate and vigorous PA (MVPA)] were measured over 7days [n=329, 44% male, 39% Latino; mean (SD) 9.1 (0.7)years] in an obesity prevention study in San Diego (Project MOVE). Agreement between date-matched objective MVPA and parent-classified child PA was assessed; % days parental overestimation was the outcome variable. Associations between parental overestimation and potential correlates were investigated using three-level mixed-effects linear regression. Children met the PA guidelines on 43% of days. Parents overestimated their children's PA on 75% of days when children were inactive. Most parents (80%) overestimated their child's PA on ≥1 measurement day. Parental support for child PA (transport, encouragement and participation with child) (p<0.01) was positively associated with higher overestimation. Parents of girls showed more overestimation than parents of boys (p=0.04). Most parents incorrectly classified their child as active when their child was inactive. Strategies addressing parental overestimation may be important in PA promotion.
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Parent awareness of young children's physical activity
Kirsten Corder
a,
, Noe C. Crespo
b
, Esther M.F. van Sluijs
a,d
, Nanette V. Lopez
c
, John P. Elder
c
a
UKCRC Centre for Diet and Activity Research (CEDAR), Institute of Public Health, University of Cambridge, United Kingdom
b
Arizona State University, School of Nutrition and Health Promotion, Exercise and Wellness Program, USA
c
Institute for Behavioral and Community Health, San Diego State University, USA
d
MRC Epidemiology Unit, Cambridge, United Kingdom
abstractarticle info
Available online 2 July 2012
Keywords:
Physical activity
Parental awareness
Children
Child behavior
Overestimation
Objective. Parents who overestimate their child's physical activity (PA) level may not encourage their chil-
dren to increase their PA. We assessed parental awareness of child PA, and investigated potential correlates of
overestimation.
Method. ChildPA (accelerometer) and parent-classied child PA [active 60 min/day vs. inactive b 60 min/
day moderate and vigorous PA (MVPA)] were measured over 7 days [n=329, 44% male, 39% Latino; mean (SD)
9.1 (0.7)years] in an obesity prevention study in San Diego (Project MOVE). Agreement between date-matched
objective MVPA and parent-classied child PA was assessed; % days parental overestimation was the outcome
variable. Associations between parental overestimation and potential correlates were investigated using
three-level mixedeffects linear regression.
Results. Children met the PA guidelines on 43% of days. Parents overestimated their children's PA on 75% of
days when children were inactive. Most parents (80%) overestimated their child's PA on 1measurement
day. Parental support for child PA (transport, encouragement and participation with child) (pb 0.01) was posi-
tively associated with higher overestimation. Parents of girls showed more overestimation than parents of
boys (p=0.04).
Conclusion. Most parents incorrectly classied their child as active when their child was inactive. Strategies
addressing parental overestimation may be important in PA promotion.
© 2012 Elsevier Inc.
Introduction
Insufcient physical activity (PA) is a risk factor for obesity in chil-
dren (Steele et al., 2008; Wareham et al., 2005). Only 42% of US children
aged 611 years meet PA guidelines which are 60 min of moderate
and vigorous PA (MVPA) every day (Troiano et al., 2008). Literature re-
views highlight the limited success of PA interventions in children
(Dobbins et al., 2009; Salmon et al., 2007; van Sluijs et al., 2007b); how-
ever the reasons for this are largely unknown.
One possible explanation for the limited effectiveness of PA interven-
tions is that individuals overestimate their PA level, believing themselves
to be more active than they really are. This misperception is common for
PA (Corder et al., 2010, 2011b; Lechner et al., 2006; Ronda et al., 2001;
van Sluijs et al., 2007a, 2007b; Watkinson et al., 2010), due to unclear
thresholds between healthy and unhealthy PA levels (Ronda et al.,
2001). Someone overestimating their PA level may not be aware that
they are not optimally active and may see no need to increase their PA
level (Ronda et al., 2001). Improving PA awareness by reducing over-
estimation of PA levels may be an important component of PA promo-
tion. Few interventions address this as a key strategy (Ronda et al.,
2001; van Sluijs et al., 2007a, 2007b) although it has been considered
in recent interventions in adults (van Stralen et al., 2010).
Parents strongly inuence the PA of their children, and usually have
primary responsibility for their participation in PA promotion (Giles-
Corti et al., 2009). Investigation of parental awareness of child PA levels
is important as parents may need to be aware that their children are in-
sufcie ntly active in order to facilitate their participation in PA promo-
tion (Corder et al., 2010).
To our knowledge, parental awareness of child PA has not been in-
vestigated among US or ethnically diverse children and parents. Previ-
ous studies have used one habitual PA awareness question to dene
overestimation (Corder et al., 2010, 2011b; Lechner et al., 2006;
Ronda et al., 2001; van Sluijs et al., 2007a, 2007b; Watkinson et al.,
2010). This is the rst study to derive parental overestimation using
daily awareness data, allowing for daily variation in children's PA.
We investigated parental awareness of child PA levels among parents
of 710year-old children, and explored correlates of parental over-
estimation.
Preventive Medicine 55 (2012) 201205
Abbreviations: PA, physical activity; MVPA, moderate and vigorous physical activity.
Corresponding author at: Centre for Diet and Activity Research (CEDAR), Box 296,
Institute of Public Health, University of Cambridge, Forvie Site, Robinson Way, Cambridge,
CB2 0SR, United Kingdom. Fax: +44 1223 330316.
E-mail address: klc29@medschl.cam.ac.uk (K. Corder).
0091-7435 © 2012 Elsevier Inc.
doi:10.1016/j.ypmed.2012.06.021
Contents lists available at SciVerse ScienceDirect
Preventive Medicine
journal homepage: www.elsevier.com/locate/ypmed
Open access under CC BY-NC-ND license.
Open access under CC BY-NC-ND license.
Methods
Study design and setting
Children (58 years old) and their primary caregivers (n=541 dyads) liv-
ing in San Diego County were recruited between November 2006 and May
2008 to participate in Project MOVE, a 2-year obesity prevention study involving
recreation centers. Families were contacted through phone calls, iers and com-
munity information booths. Parentchild dyads lived within 1.75 miles from 1
of 30 participating recreation centers and parents could speak and read English
or Spanish. Parents provided written informed consent and children provided
oral assent. Ethical approval from San Diego State University Institutional Re-
view Board was obtained. Post-intervention data were used here (children
710 years old) as accelerometer data were available for the majority of partic-
ipating children.
At baseline and post-interventionmeasurement sessions,parents completed
a questionnaire,and child and parent anthropometricmeasures were taken. Par-
ents reported demographics for themselves and their child including: age,
gender, Latino ethnicity, family monthly income (b $500$2000, $2001$3500,
$3501$5000 and $5001)and parent education (middle school or lessthrough
post-graduate). Height (Shorr Measuring Height Board) and weight (SECA 880
and876) were assessed using standardproceduresby trained staffto the nearest
0.1 cm and 0.1 kg, respectively. Body mass index (BMI) zscores were calculated
(Center for Disease Control and Prevention, 2000).
Physical activity
At post-intervent ion, PA was assessed using Actigraph accelerometers
(Ekelund et al., 2001, 2003). All children agreeing to wear a monitor (n=370)
were tted with a GT3X or GT1M (recording in 5-s epochs), and asked to wear
the monitors for 7 days while awake and to remove them for water-based activ-
ities. Accelerometry d ata were analyzed using a program available at http://
www.mrc-epid.cam.ac.uk/Research/Programmes/Programme_5/InDepth/
Programme%205_Disclaimer.html to remove: data recorded between 11 pm
and 6 am, periods of 30 min with continuous zero counts and days with
b 540 min of recording (valid day cut-off).
Time (min/day) spent in MVPA was derived using agespeciccut-points
(Trost et al., 2005). Accelerometer data were used to derive a dichotomous
MVPA variable; 60 min/day of MVPA was used to classify children as active or in-
active, according to current PA guidelines (US Department of Health and Human
Services, 2008). Classication error was calculated as daily child MVPA (min)
minus 60 min (current guidelines). Seven categories of time in MVPA were cal-
culated in 15min blocks (from zero to 90 min) to examine the distribution
of PA levels with regard to parental overestimation.
Parental awareness of child PA
Parental awareness of child PA level was assessed through a daily diary, con-
current with accelerometer measurement, asking the parent: was your child
physically active for a total of at least 60 minutes on this day with answer cate-
gories as yes and no.
For each day with valid PA and awareness data, parent
child dyads were categorized into one of four groups using objective and
parent-classied PA (Fig. 1). The outcome variable for this analysis was parental
overestimation, expressed as the percentage of measured days on which par-
ents overestimated their child's PA level (number of days of parental PA over-
estimation divided by the number of days with valid matched data). Only one
child per parent was enrolled in the study and parents were asked to respond
to all surveys for that child only. A sensitivity analysis was done using 45 min
as the threshold between active and inactive.
Potential correlates
Potential correlates of overestimation were parentally reported at follow-up
(except baseline values for sex, ethnicity, income and parental education).
Cronbach's alpha was compute d to determine the internal consistency of items
where appropriate.
Two questions asked parents how many days/week their child plays team
and non-team sports with eight responses options (07 days/week): a sum of
both questions was used to represent sessions/week that the child does sport.
Parents reported the presence of eight PA-related rules, including do not go
places alone (ICC=0.420.74) (Kerr et al., 2008). Responses were yes, no
and sometimes with no and sometimes combined given that if a rule is
only sometimes present it is unlikely to be enforced.
Parents reported how often they provide encouragement and transport for
their child to do PA, and how often they do PA with their child. Response op-
tions were never, b once/week, 12 times/week, 34 times/week and
57 times/week recoded as 0, 1.5, 3.5 and 6 days/week. Parent support for
less sedentary time was derived from two questions to help children think of
ways to be less inactive an
d encouraging less inactive time with responses
as above (α=0.79).
Parents reported electronic media items in the child's bedroom using an
adapted published scale (Rosenberg et al., 2010) (previously reported ICC=
0.90). Parents reported the number of types of PA equipment at home (range
08) using an adapted scale (original reliability ICC=0.80) (Rosenberg et al.,
2010).
Parents selected the frequency of their child's PA participation at 11 loca-
tions (including recreation centers and parks), response categories were
never, b once/week, 12times/week,34 times/week and 57 times/week
(recoded as 0, 1.5, 3.5 and 6 days/week). These have been reported previously
Accelerometer assessed PA level
“Active
60 min/d MVPA
“Inactive”
< 60 min/d MVPA
Yes Realistic Active
37.9 % ( n= 622 )
Mean (SD) MVPA:
93.3 (30.5)
mins/day
Overestimation
42.6 % ( n= 700 )
Mean (SD) MVPA:
37.9 (13.3)
mins/day
Parent classified child PA
level: “Was your child
physically active for a total
of at least 60 minutes on
this day?
No Underestimation
5.3 % ( n= 87 )
Mean (SD ) MVPA:
79.9 (19.5)
mins/day
Realistic Inactive
14.2 % ( n= 233 )
Mean (SD) MVPA:
33.5 (15.5)
mins/day
Fig. 1. Derivation of parental overestimation (n=1642 measurement days) by comparison of parent rated child PA levels and accelerometer assessed PA levels among 329 children
and parents from San Diego County, CA. MVPA, moderate and vigorous PA; min/d, minutes per day.
202 K. Corder et al. / Preventive Medicine 55 (2012) 201205
(original reliability ICC=0.600.89) (Kerr et al., 2008). Two composite vari-
ables were derived: locations used frequently (sum of locations used 12
times/week) and total weekly visits to any location (times/week) (Corder et
al., 2011a).
Statistical analyses
Characteristics of those included and excluded from the analyses
were tested using t-tests or chi-squared tests.
Simple associations between parental overestimation and potential
correlates were assessed using three-level mixedeffects linear regres-
sion with levels as days, children and recreation center recruitment
area. Analyses were additionally adjusted for sex, study condition and
classication error. Classication error was included as a covariate so re-
sults are independent of child MVPA and proximity to the guideline
threshold. This also takes into account that overestimation depends on
PA levels. Study condition was adjusted for but intervention effects
were not assessed. Variables that reached p 0.10inthesimplemodels
were included in a multiple model and subsequently removed if
p 0.05, variables were removed stepwise, starting with the highest
p-value. Stata 12.0 (Statacorp, College Station, TX) was used for analyses.
Results
Of the 541 Project MOVE parentchild dyads, 329 had at least one
matched day of objective and parent-classied PA data (mean (SD)
5.0 (1.9)days); descriptive data are presented in Table 1.Therewere
no signicant differences by sex, parent education, ethnicity, age or
BMI zscore between Project MOVE children excluded and included
from these analyses (all p>0.05).
Fig. 1 shows the grouping of measurement days into four PA aware-
ness categories by objective and parent-classied PA level. In total, 1642
valid measurement days were included. Results primarily focus on over-
estimation as those children did not meet PA guidelines on some mea-
surement days and their parents may therefore not encourage them to
participate in PA promotion.
Parents wrongly classied their child's PA level on 48% of measured
days and overestimated their child's PA on 43% of all measured days. Chil-
dren were not meeting PA guidelines (determined using accelerometry)
on 57% of valid measurement days and parents overestimated their
children's PA level on 75% of these inactive days. Parents overestimated
their child's PA level on mean (SD) 2.1 (1.8)days/week, with 80% over-
estimating on 1 measurement day. Parents who overestimated their
child's PA level did so by a mean (SD) of 22.0 (13.3)min/day.
Table 1 shows a summary of the simple associations between individ-
ual factors and parental overestimation. Table 2 shows the distribution of
parental classication error by categorical objective PA level. Classica -
tion error is similar across the four PA categories of b 60 min/day.
Table 3 shows descriptive data on home and family factors and sim-
ple associations with parental overestimation. Parent encouragement,
transport provision for PA and parents doing PA with their child were
positively associated with parental overestimation. The only variable
remaining in the nal model was parents providing transport for PA
(β (95% CI) 2.3 (0.9, 3.7) pb 0.01).
Sensitivity analyses using 45 min of MVPA as the guideline thresh-
old showed parents overestimating their child's PA on 27% versus 43%
of all days. Sex was no longer signi
ca
ntly associated with % days over-
estimation (B (95% CI) p value as 4.3 ( 0.3, 0.8) p=0.07) but all other
associations were similar.
Discussion
Most parents incorrectly classied their child as meeting PA guide-
lines on days when children were actually inactive (not meeting the
PA guideline). Most parents overestimated their child's PA level at
some point during the measurement period. As this is the rst study ad-
dressing parental awareness in an ethnically diverse population and
using a daily measure, these ndings emphasize the relevance of paren-
tal overestimation in PA promotion.
The parents in the present study had similar levels of overestimation
as a previous British study (Corder et al., 2010). The high prevalence of
overesti mation identied in both studies supports the potential impor-
tance of further research regarding parental awareness. As shown previ-
ously, parental overestimation was higher for parents of girls (Corder et
al., 2010) and may be partly due to the lower PA level of girls versus boys.
The lack of association with BMI contrasts previous results suggesting
that parents who overestimate their child's PA level have children with
lower fat mass (Corder et al., 2010).
Parent overestimation of child PA was higher among parents who
reported more parent support for child PA. Apart from sex, these paren-
tal support variables were the only factors associated with parental
overestimation and providing transport was the only variable to remain
in the nal model. The parental burden of providing support including
transport to PA locations may lead parents to assume that their child
is sufciently active even if the child is not meeting guidelines. Although
parental PA support is positivelyassociated with child PA (vander Horst
et al., 2007), providing more support appears to be associated with
Table 1
Descriptive data for 329 parentchild dyads from San Diego County, CA with data on
parental estimation of child PA and results of simple three-level linear regression for
associations with parental overestimation (% days parental overestimation).
Variable Mean (SD) or % B (95% CI) P value
a
Sex (% boys) 44.1 Reference category
Sex (% girls) 55.9 6.0 (0.3, 11.8) 0.04
Age (years) 9.1 (0.7) 3.8 (0.1, 7.7) 0.06
BMI zscore 0.6 (2.6, 2.8) 1.7 ( 1.2, 4.7) 0.25
Ethnicity (% non-Latino)
b
61.4 Reference category
Ethnicity (% Latino)
b
38.6 2.7 (8.5, 3.2) 0.38
Monthly income (% parents)
b
$0$2000 22.1 Reference category
$2001$3500 20.1 1.7 (10.8, 7.4) 0.72
$3501$5000 22.5 3.8 (12.6, 5.0) 0.39
$5001+ 35.3 0.2 (8.1, 7.8) 0.97
Parental education
(% parents)
b
Middle school or less 15.5 Reference category
High school 13.7 0.1 (10.6, 10.6) 0.99
Some college but
not graduated
26.1 0.3 (9.4, 8.8) 0.95
College graduate 26.8 3.4 (12.4, 5.7) 0.47
Post-graduate work 17.9 4.2 (14.1, 5.7) 0.41
MVPA (min/day) 59.4 (25.8)
Classication error
(MVPA min/day)
0.6 (25.8) 0.4 ( 0.4, 0.3) b 0.01
B; beta estimated regression coefcient from three-level mixedeffects linear regres-
sion and adjusted for study condition, classication error (MVPA min) and sex with
outcome variable as % days of parental overestimation; 95% CI, 95% condence interval;
MVPA, moderate and vigorous physical activity; PA, physical activity.
a
Association with % days of parental overestimation.
b
Baseline data.
Table 2
Descriptive data for 329 parentchild dyads from San Diego County, CA on percentage
days of parental overestimation (n=1642 days) and classication error by category of
moderate and vigorous activity.
Activity category
(MVPA min)
N
(days)
Mean (SD), %
overestimation
Mean (SD) classi cation error
a
(MVPA min)
014.9 73 44.3 (42.6) 44.8 (5.4)
1529.9 227 50.7 (38.6) 29.5 (9.2)
3044.9 308 51.7 (34.4) 16.1 (11.4)
4559.9 325 45.6 (32.2) 5.3 (10.5)
6074.9 239 0 6.1 (9.6)
7589.9 181 0 14.6 (10.9)
90 289 0 38.7 (22.9)
PA, physical activity; MVPA, moderate and vigorous activity.
a
Classication error calculated as difference from 60-min guideline.
203K. Corder et al. / Preventive Medicine 55 (2012) 201205
higher overestimation. Even if parents support their children to engage
in PA, this may still not be sufcient to meet guidelines. A potential strat-
egy might be to encourage parents to consider whether their child's activ-
ities are sufciently active to meet guidelines. This nding also supports
promotion of active travel perhaps as an alternative to parents providing
motorized transport for children to do PA. Findings may be due to reverse
causality as parents who have identied their child as insufcien tly active
may have started providing support. Higher overestimation was positive-
ly associated with parental support which questions our initial hypothe-
sis that parents who wrongly consider their child as active will not
encourage their child to do PA. However, it is possible that inactive chil-
dren still need additional parental support in order to meet guidelines.
A trial is necessary to establish whether parental overestimation can be
reduced, whether this increases parental encouragement and whether
this also increases child PA.
Parental monitoring of child PA in addition to parental education
about adequate PA levels for children may target parental overestimation
of child PA, but this needs investigation in a trial. Other complementary
intervention strategies including goal setting and personalized feedback
to parents about their children may improve parental awareness and in-
crease children's PA (Michie et al., 2009). Self-monitoring step counts
using pedometers has potential in PA promotion among children but
more research is necessary to establish how self-monitoring can be used
most effectively (Lubans et al., 2009) and how best to involve parents.
We are unable to determine causation from this cross-sectional
analysis. Results are from post-intervention measurements from an
obesity prevention intervention. Analyses were adjusted for study con-
dition and the intervention did not specically target PA awareness but
results could still be inuenced by the intervention, possibly due to al-
terations of parental attitudes towards PA or heightened expectations
of children's PA levels. Accelerometryassessed PA is more accurate
than most self-report measures but has limitations including no infor-
mation about activity type (Corder et al., 2007). We could not assess
overestimation continuously due to dichotomous parent-classied
PA. However, the discrepancy between child PA levels and the guideline
was included in analyses, so results are independent of child PA. In fu-
ture, parents could be asked to classify their child's PA in multiple cate-
gories directly comparable to categorized objective data. However,
these results are supported by sensitivity analyses showing similar re-
sults when using 45 min to dene active/inactive. The amount of over-
estimation was also similar across MVPA categories irrespective of PA
level.
Mostparents incorrectly classify their child as meeting PA guidelines
on days when they are actually inactive. Parent support was associated
with greater parental overestimation. Strategies addressing parental
awareness of child PA may be important when designing PA promotion
interventions for children.
Conict of interest statement
The authors declare that there are no conicts of interest.
Acknowledgments
Data used for this study were obtained from Project MOVE/me Muevo
funded by the National Institute of Diabetes and Digestive and Kidney
Diseases (R01 DK072994). Noe C. Crespo was supported by grants
T32HL079891 and F31KD079345 and John P. Elder was supported by
NIDDK grant R01 DK072994 and partially by PRC grant U48 DP000036.
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Table 3
Descriptive data for potential home and family corre lates and results of simple
three-level mixedeffects linear regression with potential home and family correlates
and % days of parental overestimation of child PA among 329 children and parents
from San Diego County, CA.
Potential correlate Mean (SD) or % B (95% CI) P value
a
Sports participation
(sessions/week)
3.2 (2.7) 0.8 (0.3, 1.9) 0.14
Parental encouragement for PA
(days/week)
4.6 (2.2) 1.5 (0.2, 2.8) 0.02
Parent transport provision for PA
(days/week)
3.7 (2.3) 1.9 (0.7, 3.1) b 0.01
Parental PA with child
(days/week)
2.9 (2.0) 1.8 (0.4, 3.3) 0.01
Parental encouragement for
less inactivity (days/week)
4.3 (2.8) 0.8 ( 1.8, 0.2) 0.12
Total PA equipment at home
(n available)
4.2 (2.0) 1.2 (0.3, 2.6) 0.11
Sedentary equipment
in bedroom (n available)
0.7 (0.4) 5.5 (0.9, 11.9) 0.09
Child visits to PA locations
(visits/week)
12.1 (6.0) 0.3 (0.1, 0.8) 0.17
Number of PA locations
usedonce a week
(mean (SD))
4.0 (2.0) 0.3 (1.1, 1.8) 0.66
Rules for PA
Do homework before going
out (% have rule)
70.4 2.8 ( 0.5, 9.1) 0.38
Stay close or within sight
of home (% have rule)
92.7 8.2 ( 2.8, 19.2) 0.14
Do not go into the street
(% have rule)
76.9 0.2 ( 6.9, 6.6) 0.95
Do not go places alone
(% have rule)
92.4 3.4 ( 14.1, 7.4) 0.54
Stay within neighborhood
(% have rule)
93.9 4.1 ( 7.9, 16.2) 0.50
Wear a helmet
(when biking etc.)
(% have rule)
87.8 4.0 ( 12.7, 4.7) 0.37
Wear protective clothing
(e.g., knee pads) (% have rule)
61.6 1.9 ( 7.7, 4.0) 0.53
Avoid strangers (% have rule) 92.4 0.9 ( 9.7, 11.6) 0.86
B, beta estimated regression coefcient from three-level mixedeffects
linear regres-
sion and adjusted for study condition, classication (MVPA min) and sex with outcome
variable as % days of parental overestimation; 95% CI, 95% condence interval; PA,
physical activity.
a
Association with % days of parental overestimation.
204 K. Corder et al. / Preventive Medicine 55 (2012) 201205
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... Several investigations report that adults overestimate their PA level and that of their children [22][23][24][25]. Moreover, in a study, parents with girls were more likely to overestimate their daughters' activity level [26]. The same study showed that parental support for their children's PA (transport, encouragement, and participation with the child) was positively associated with higher overestimation [26]. ...
... Moreover, in a study, parents with girls were more likely to overestimate their daughters' activity level [26]. The same study showed that parental support for their children's PA (transport, encouragement, and participation with the child) was positively associated with higher overestimation [26]. The authors highlight that parental PA support was positively correlated with children's PA. ...
... Zecevic, Tremblay, Lovsin, and Michel [48] find that parents' assessment of their children's level of PA may depend on their perception of their children's level of development (younger children, who typically require more supervision and care, might be perceived as more active), and their perception of their supportive behavior of PA, including their level of PA. This finding is consistent with Corder et al. [26], who highlights that the parental burden of providing support, including transport to PA locations, may lead parents to assume that their child is sufficiently active even if the child does not engage in sufficient PA to meet the PA guidelines. This may constitute a misinterpretation of stress, which leads to an overestimate of the children's activity because parents' stress is included in the interpretation of the children's activity. ...
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This study aimed to investigate parents' estimation of their preschool children's leisure-time physical activity (PA) and the correlation between parents' reported participation in PA with their children in leisure time and their children's PA levels. A total of 244 Norwegian preschool children aged 4-6 and their parents were enrolled in the study. According to standard protocols, the children's PA level was measured with Actigraph GT1M accelerometers. The parents completed a questionnaire that provided information about their estimation of their children's PA and their reported participation in their children's PA. Correlation analyses and scatter plots showed no significant association between parents' estimation of their children's PA level at leisure time and the children's objectively measured PA level. Only 5% of the parents estimated their children's PA level correctly. In general, the parents overestimated their children's PA levels by three times. Furthermore , the results found no significant correlation between children's PA levels at leisure time and parents' reported participation in PA with their children. Our findings indicate that parents' self-estimation of their children's PA is inaccurate, which is problematic. Considering that the PA levels of many children are too low to fulfill internationally established health recommendations, parents' 'wrong' perception about their children's PA urgently needs to be addressed and rectified.
... The research on parents' beliefs of their children's physical activity and motor skills is sparse [27], and the limited findings in this area are mixed [28][29][30][31][32][33][34][35]. Evidence supports that those parents who are knowledgeable about physical activity and motor skills are more likely to support these behaviors in their children [28,29] and that their children are more likely to have greater motor abilities [30]. ...
... Evidence supports that those parents who are knowledgeable about physical activity and motor skills are more likely to support these behaviors in their children [28,29] and that their children are more likely to have greater motor abilities [30]. However, research has found that parents hold inaccurate perceptions about physical activity and motor skills, as they tend to overestimate their children's physical activity [31][32][33] and motor abilities [34,35]. More research is needed to measure parents' beliefs of their child's engagement in motor skills and physical activity in order to determine the extent to which families believe that participating in a physical activity program is essential and would be beneficial. ...
... Responses indicated that at least half (n=125, 50%) of the parents had the motive to buy-in to a SMPA program. Based on research illustrating low levels of physical activity [2] and motor skills [38] in children, and that parents overestimate their children's physical activity levels [31][32][33] and motor skills [34,35], it is likely that some parents perceive their children as more active than they actually are or to have more advanced motor skills than they actually do. Thus, it can be reasonably assumed that the percentage of parents whose children need to increase their physical activity levels or motor skills to meet national recommendations [2] is more significant than this study found. ...
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Background Social media may be a powerful platform to combat parents’ and children’s low physical activity levels. Objective This study surveyed parents’ beliefs about physical activity in order to expand the extant literature concerning the interest in and the design of an effective and feasible social media physical activity (SMPA) program. Methods Primary caregivers (n=250; 215 [86%] mothers, 164 [65.6%] White) of children aged 6-12 years completed an online questionnaire. Interest was examined through responses on the questionnaire; beliefs (ie, perceptions, knowledge, and support) about physical activity were examined using Spearman correlations; and to support the SMPA program design, researchers examined a combination of multiple-choice and free-response questions. For the free-response questions, the researchers performed open coding related to perceived benefits, barriers, and motivators. Results Parent respondents (n=215, 86%) were interested in a SMPA program tailored for families. Regarding beliefs, parents exhibited a monotonic relationship between 2 questions related to perceptions of physical activity levels in their children (rs(250)=.310, P<.001), knowledge about physical activity and motor skills (rs(250)=.328, P<.001), and support of physical activity and motor skills (rs(250)=.385, P<.001). Parents perceived benefits of a SMPA program, highlighting family time and health. Barriers included time constraints, a lack of motivation, and environmental factors. Conclusions Parents are interested in supporting healthy family behaviors using a SMPA program. An effective program should emphasize motor skill activities, be fun and family oriented, and incorporate incentives, goal setting, and advice and tips. SMPA also needs to address identified barriers, such as those regarding time and environment.
... This is demonstrated by the positive association between parents who place a high value on sport and exercise and the subsequent active lifestyle of their children [63], whereas solicitous and overprotective parents inadvertently restrict outdoor activity that yields weaker FMS development in their children [64]. FMS practice is further inhibited by parents who frequently overestimate their children's PA levels, inaccurately perceive their FMS ability, or are simply unaware of FMS and PA guidelines [38,65,66]. Consequently, the children from these families are often not active enough and the parents fail to recognise the need to encourage more active behaviour [67,68]. ...
... Consequently, the children from these families are often not active enough and the parents fail to recognise the need to encourage more active behaviour [67,68]. Therefore, raising the parental awareness of PA guidelines, policies, and FMS may be an important first step in family interventions [65,69]. Equally important may be the education of parents in FMS performance and skill perception to empower them to become role models, which could enhance the FMS proficiency and PA levels of children at home [66,67,70]. ...
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Fundamental movement skills (FMS) are basic movements in children that represent the building blocks for more complex motor skill development and act as a prerequisite for enduring sport and physical activity (PA) engagement and positive health-related behaviours. The FMS proficiency is currently inadequate worldwide, and consequently there are alarming levels of inactivity and childhood obesity. However, parents are role models to their children and possess the power to influence their PA behaviour. This review investigated if parent-focused interventions could improve FMS in 2–7-year-old children and evaluated which setting and method of parent engagement was most impactful. Keyword searches were conducted via Scopus, Web of Science, SPORTDiscus, PubMed, Science Direct, and Google Scholar. Only nine articles met the inclusion criteria. No research originated from the United Kingdom, highlighting the urgent need for further FMS interventions involving parents. The FMS improved in all nine studies, with significant changes in seven of the articles (p < 0.05). Parent–child co-activity, the education and empowerment of parents, and the provision of clear FMS guidance, messaging, and structure can positively influence children’s FMS. Recently, smartphone apps have increased the feasibility and accessibility of FMS practice at home and may be integral to future interventions. Further research with direct parental involvement is clearly warranted.
... These factors contribute to a lower level of energy expenditure resulting in a reduced caloric need and consequently increased risk of inadvertent overfeeding and subsequent weight gain (25). In addition, individuals and parents often overestimate the amount of energy expended through physical and sedentary activity further adding to unintentional excess intake (26)(27)(28)(29)(30). Growth retardation, decreased height velocity and muscle hypoplasia can further exacerbate the high percentage of body fat and can be accentuated with the youth's advancing age (1). ...
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Background The consequences of obesity are ominous, yet healthcare professionals are not adequately preventing or treating obesity in youth with Down syndrome (DS). Total daily energy expenditure (TDEE) is the energy expended in 24 h through physical activity and life-sustaining physiologic processes. An individual's TDEE is essential for determining the daily caloric intake needed to maintain or change body weight. Successful prevention and treatment of obesity in youth with DS is severely compromised by the lack of data on TDEE and information on weight-related behaviors for this high-risk population. This manuscript describes the protocol for the federally funded study that is in process to determine daily energy expenditure in a large cohort of children with DS. Methods This observational cross-sectional study will include a national sample of 230 youth with DS, stratified by age (5–11 and 12–18 years of age) and sex. Doubly Labeled Water analysis will provide the criterion body fat%, fat-free mass, and TDEE. To increase accessibility and decrease the burden on participants, the entire study, including obtaining consent and data collection, is conducted virtually within the participant's home environment on weekdays and weekends. The study team supervises all data collection via a video conferencing platform, e.g., Zoom. This study will (1) examine and determine average TDEE based on age and sex, (2) develop a prediction equation based on measured TDEE to predict energy requirements with a best-fit model based on fat-free mass, sex, age, and height and/or weight, and (3) use 24-hour dietary recalls, a nutrition and physical activity screener, wearable devices, and sleep questionnaire to describe the patterns and quality of dietary intake, sleep, and physical activity status in youth with DS. Discussion The lack of accurate information on energy expenditure and weight-related behaviors in youth with DS significantly impedes the successful prevention and treatment of obesity for this vulnerable population. The findings of this study will provide a further understanding of weight-related behaviors as obesity risk factors, currently not well understood for this population. This study will advance the science of weight management in individuals with disabilities and shift clinical practice paradigms.
... Furthermore, mixed findings on the association between PA and GMS may be partly attributable to measurement error in assessing PA, particularly when PA is assessed using self-or proxy-(parent) reported questionnaires. Indeed, parent-and/or proxy-reported assessments for PA tend to yield overestimates of PA behavior in youth (Corder et al., 2009(Corder et al., , 2012. ...
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The purpose of this study was to determine the associations of device-based assessments of physical activity (PA) and health-related fitness (HRF) with gross motor skills (GMS) in preschool-aged children. Participants were 3- to 5-year-old children (N = 316; 49.6% female) who participated in the 2012 National Youth Fitness Survey. GMS was assessed using the gross motor quotient calculated from the Test for Gross Motor Development—Second Edition. PA was assessed using wrist-worn ActiGraph GT3X accelerometers with raw triaxial acceleration data summarized using monitor-independent movement summary units (MIMS). Analyzed metrics included average MIMS per day and peak 30-min MIMS. HRF assessment consisted of a plank score and a sum of skinfold assessment. Weighted hierarchical regressions tested the associations between PA, HRF, and GMS variables with a secondary weighted mediation analysis that examined whether HRF mediated the association between PA and GMS. Peak 30-min MIMS significantly correlated with GMS (b = 0.17, p = .005). Plank scores had the strongest correlation with GMS (b = 0.23, p = .004), and weighted mediation analyses revealed that plank scores partially mediated the association between peak 30-min MIMS and GMS (indirect effect = 0.03, p = .01, 23.1% mediation). Peak 30-min MIMS significantly associated with GMS in preschool children, an association partially mediated by core muscular endurance.
... Although parents in our study generally considered their children to be more physically active than other children their age, we did not find a relationship between parent perception of children's activity and time spent in MVPA measured by accelerometry. This is consistent with studies from the US [40,41] and the UK [42]. Parents may not focus as much on encouraging their children to be physically active if they do not perceive activity levels to be low. ...
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The purpose of this study was to evaluate family and home/neighborhood characteristics associated with physical activity (PA) and adiposity among young children living in a small rural community. Methods: Participants were 30 parents and their youngest child aged 2-5 years. Children wore accelerometers for 7 days. Parents completed questionnaires about family lifestyle behaviors, parenting practices, and home/neighborhood characteristics. Results: None of the family lifestyle behaviors were associated with child BMI percentile. Backyard size was inversely associated with moderate to vigorous physical activity on weekday afternoons (rho = -0.488, p = 0.006), as was perception of neighborhood dangers (rho = -0.388, p = 0.034). Perceived neighborhood safety (rho = 0.453, p = 0.012), the presence of sidewalks (rho = 0.499, p = 0.012), and public playground use (rho = 0.406, p = 0.026) were each associated with higher weekday afternoon MVPA. Conclusions: Findings suggest neighborhood safety, sidewalks, and use of public playgrounds are positively associated with MVPA among preschoolers, while backyard size and access to play equipment at home are not. These findings have implications for rural communities where space is plentiful but access to community space and sidewalks may be limited.
... For example, existing evidence of PA and sedentary behavior from previous studies in Saudi Arabia relies on the parents' awareness of their child's PA and sedentary behaviors. Parents were found to incorrectly classify their children's PA and sedentary behaviors [21]. In adults, evidence suggests that the self-report method may overestimate PA [22] and underestimate sedentary time [23]. ...
Article
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During the COVID-19 pandemic, a few studies used accelerometers to assess physical activity (PA) and sedentary behavior in the family context. This study aimed to assess children and parents’ moderate and vigorous physical activity (MVPA) and sedentary time, as well as their relationship in MVPA and sedentary time. Data were collected from 30 parent–child dyads during the COVID-pandemic for seven days, using a hip-worn accelerometer. Children and parents engaged in 65.6 and 34.6 min/day in MVPA and 442.2 and 427.9 min/day sedentary, respectively. There was no evidence of gender difference in MVPA and sedentary between boys and girls. Male parent spent more time in MVPA than female parents. A total of 50% of children and 53.3% of parents met the recommended PA. Children’s MVPA and sedentary time were both correlated with that of their parents. Adjusted linear regression showed that only child MVPA was negatively associated with their parents’ MVPA. There is evidence that multi-level interventions involving parents and children are more effective than interventions focusing on a single group. This study also provides evidence to support the link between MVPA and sedentary time between parents and children. Generalization of the findings is difficult due to the bias of self-selection sample.
... Therefore, girls' parents could be more prone to overestimate their daughter's PA due to their frame of reference [43]. Consistent with other studies, this result highlights the importance of taking sex into account in PA research during the early stages of life [43][44][45]. ...
Article
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Validated physical activity (PA) questionnaires are crucial for collecting information in large epidemiological studies during childhood. Thus, this study analyzed the validity of a parent-reported PA questionnaire based on the Children’s Leisure Activities Study Survey by accelerometry in European children aged from 6 to 12 years old. We used data from 230 children of the Human Early-Life Exposome and Infancia y Medio Ambiente projects. Mean differences between moderate-to-vigorous PA (MVPA) reported by the questionnaire and the accelerometer were calculated (min/day), and its associated factors were explored by multiple robust linear regression. The agreement between methods was examined using a Bland–Altman plot. The concurrent validity of assessing MVPA was analyzed by cohort-adjusted Spearman’s partial correlations. ROC curve analysis was also used to explore the questionnaire’s capability to identify active children based on the World Health Organization guidelines. A moderate correlation was found between parent-reported and accelerometer MVPA (rho = 0.41, p < 0.001). The child’s sex (girl) was statistically associated with the mean MVPA difference between methods. However, this questionnaire accurately identified physically active children (area under the curve = 83.8% and 82.7% for boys and girls, cut-points = 68.6 and 45.4 min/day in MVPA, respectively). Consequently, this questionnaire is suitable for classifying active children in order to monitor public health interventions regarding PA.
... According to a study conducted by Piercy et al. (36), it was determined that the level of physical activity awareness increased as the income level of the participants increased. According to a study conducted by Corder et al. (37) who examined parental awareness of physical activities in children, it was determined that individuals with highincome levels have more awareness of physical activity than other income groups. Ergül et al. (27) reported that the awareness levels of the students increased as their income increased. ...
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The Covid-19 pandemic has significantly changed individuals' quality of life. Authorities have taken various measures to protect general public health. These measures, which are taken to fight the virus effectively during the pandemic, have also limited many recreational activities that individuals can do in daily life. In this study, the participants were university students, and the recreational awareness levels of the participants and the effects of the Covid-19 pandemic on the quality of life of the participants were discussed in terms of various variables (n=818). The SPSS package program was used in the analysis of the research data, and Kolmogorov Smirnov test and Shapiro tests were applied to determine the normality of the data distribution. Since the data did not have a normal distribution, that is, non-parametric distribution, besides descriptive statistical models, Mann Whitney U, Kruskal Wallis test, and correlation analysis were applied. A significant positive relationship was found between recreational awareness and the effect of the Covid-19 pandemic on quality of life. As a result, a significant difference was found between the recreational awareness levels of university students and their demographic variables only in the variable of being infected with the Covid-19, and no significant difference was found in other variables. As a result, it was understood that there were significant differences in the variable of being infected with Covid-19. It has been determined that there are significant differences between the effect of the Covid-19 pandemic on the quality of life and gender, age, welfare level and being infected with Covid-19. It has been observed that university students are adversely affected not only psychologically, but also both socially and professionally due to the pandemic.
Article
Introduction: Physical activity has positive health benefits across the lifespan including reduced rates of chronic disease. Despite having ample availability of outdoor space for physical activity in the Appalachian Mountain region, there are low rates of physical activity along with high rates of sedentary time and increased prevalence of overweight individuals across all age groups. Therefore, there is a need to understand the factors that influence family's physical activity and sedentary time. Purpose: To assess whether parental attitudes and behaviors influence children's physical activity and sedentary time. Methods: The current study was a secondary analysis of the baseline data from a pilot study of a pediatrician prescription program for outdoor physical activity. Parents (N = 70) with children aged 5-13 years living in a county served by a single-pediatrician office completed surveys in the pediatrician's office during a well-child visit. The survey included questions related to parental attitudes toward children's physical activity and the physical activity and sedentary time performed by the parent and their child. Results: Parent sedentary time was the only factor that had an impact on child sedentary time, with 18% of the variance in children's sedentary time being explained by parent sedentary time. No factors predicted children's physical activity. Implications: To decrease child sedentary time, interventions should focus on reducing parental and joint parent-child sedentary time.
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EKELUND, U., M. SJÖSTRÖM, A. YNGVE, E. POORTVLIET, A. NILSSON, K. FROBERG, N. WEDDERKOPP, and K. WESTERTERP. Physical activity assessed by activity monitor and doubly labeled water in children. Med. Sci. Sports Exerc., Vol. 33, No. 2, pp. 275-281, 2001. Purpose: To validate the Computer Science and Application's (CSA) activity monitor for assessment of the total amount of physical activity during two school-weeks in 9-yr-old children and to develop equations to predict total energy expenditure (TEE) and activity energy expenditure (AEE) from activity counts and anthropometric variables. Methods: A total of 26 children (15 boys and 11 girls, mean age 9.1 ± 0.3 yr) were monitored for 14 consecutive days. TEE was simultaneously measured by the doubly labeled water method. Averaged activity counts (counts·min-1) were compared with data on: 1) TEE, 2) AEE = TEE minus basal metabolic rate (BMR; estimated from predictive equations), and 3) daily physical activity level (PAL = TEE/BMR). Results: Physical activity determined by activity counts was significantly related to the data on energy expenditures: TEE (r = 0.39;P < 0.05), AEE (r = 0.54;P < 0.01), and PAL (r = 0.58;P < 0.01). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, body composition (body weight or fat free mass), and activity counts (R2 = 0.54-0.60). AEE was significantly influenced by activity counts and gender (R2 = 0.45). There were no significant differences between activity counts and PAL in discriminating among activity levels with low (PAL < 1.56), moderate (1.57 ≤ PAL ≥ 1.81), and high (PAL > 1.81) intensity. Conclusion: Activity counts from the CSA activity monitor seems to be a useful measure of the total amount of physical activity in 9-yr-old children. Activity counts contributed significantly to the explained variation in TEE and was the best predictor of AEE.
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Objective: To assess adolescent PA awareness and investigate associations with biological and psychosocial factors. Design: Cross-sectional from November 2005 to July 2007 (ROOTS study). Setting: Population-based sample recruited via Cambridgeshire and Suffolk schools (UK). Participants: N=799 (44% male, 14.5±0.5 years). Main exposures: Self-rated PA perception, self-reported psychosocial factors, measured anthropometry. Outcome measure: PA measured using accelerometry over five days. 'Inactive' defined as accelerometry-measured <60 min/day of at least moderate PA (MVPA). Associations between awareness (agreement between self-rated and accelerometry-measured active/inactive) and potential correlates investigated using multinomial logistic regression. Results: 70% of adolescents were inactive (81% of girls, 56% of boys, OR(95% CI) 3.41(2.41, 4.82)). 53% of all girls (63% of inactive girls) and 34% of all boys (60% of inactive boys) inaccurately rated themselves as active (over-estimators). Compared to girls accurately describing themselves as inactive (29%), girl over-estimators had lower fat mass (OR(95% CI) 0.84(0.70, 0.99)), higher SES (high vs. low 2.4(1.07, 5.32)), reported more parent-support (1.57(1.12, 2.22)) and better family relationships (0.25(0.09, 0.67)). Amongst boys accurately describing themselves as inactive (22%), over-estimators had lower fat mass (0.86(0.77, 0.96)) reported more peer-support (1.75(1.32, 2.30)) and less teasing (0.75(0.61, 0.92)). Conclusions: A substantial number of adolescents believe themselves to be more physically active than they really are. They maybe unaware of potential health risks, and may be unlikely to participate in PA promotion programs. Increasing information of PA health benefits beyond weight control might help encourage behavior change.
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Poor recognition of physical inactivity may be an important barrier to healthy behaviour change, but little is known about this phenomenon. We aimed to characterize a high-risk population according to the discrepancies between objective and self-rated physical activity (PA), defined as awareness. An exploratory cross-sectional analysis of PA awareness using baseline data collected from 365 ProActive participants between 2001 and 2003 in East Anglia, England. Self-rated PA was defined as 'active' or 'inactive' (assessed via questionnaire). Objective PA was defined according to achievement of guideline activity levels (≥30 minutes or <30 minutes spent at least moderate intensity PA, assessed by heart rate monitoring). Four awareness groups were created: 'Realistic Actives', 'Realistic Inactives', 'Overestimators' and 'Underestimators'. Logistic regression was used to assess associations between awareness group and 17 personal, social and biological correlates. 63.3% of participants (N = 231) were inactive according to objective measurement. Of these, 45.9% rated themselves as active ('Overestimators'). In a multiple logistic regression model adjusted for age and smoking, males (OR = 2.11, 95% CI = 1.12, 3.98), those with lower BMI (OR = 0.89, 95% CI = 0.84, 0.95), younger age at completion of full-time education (OR = 0.83, 95% CI = 0.74, 0.93) and higher general health perception (OR = 1.02 CI = 1.00, 1.04) were more likely to overestimate their PA. Overestimation of PA is associated with favourable indicators of relative slimness and general health. Feedback about PA levels could help reverse misperceptions.
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Important health benefits can be derived when low-cost (e.g., computer-tailored) physical activity interventions for older adults demonstrate sustained effects. The purpose of the study was to conduct in-depth analysis on the long-term efficacy of two tailored physical activity interventions for older adults. A randomized controlled trial (n = 1,971) with two computer-tailored interventions and a no-intervention control group was conducted. The two tailored interventions consisted of three tailored letters, delivered during 4 months. The basic tailored intervention targeted psychosocial determinants alone, while the environmentally tailored intervention additionally targeted environmental determinants, by providing tailored environmental information. Self-reported behaviors (i.e., total physical activity, transport walking and cycling, leisure walking and cycling, and sports) were measured at baseline and 12 months. Additionally, potential personal, health-related, and psychosocial moderators of the intervention effects were examined. The environmentally tailored intervention was effective in changing total physical activity, leisure cycling, and sports compared with the basic intervention and control group. No intervention effects were found for the basic intervention. Moderation analysis revealed that participants with a higher age, lower body mass index, and higher intention were unresponsive to the interventions. Providing environmental information is an effective intervention strategy for increasing physical activity behaviors among older adults, especially among certain "at-risk" subgroups such as lower educated, overweight, or insufficiently active participants. Moderation analysis was perceived as a promising method for identifying meaningful subgroups that are unaffected by an intervention, which should receive special attention in future interventions.
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Sedentary behaviors such as TV viewing are associated with childhood obesity, while physical activity promotes healthy weight. The role of the home environment in shaping these behaviors among youth is poorly understood. The study purpose was to examine the reliability of brief parental proxy-report and adolescent self-report measures of electronic equipment and physical activity equipment in the home and to assess the construct validity of these scales by examining their relationship to physical activity, sedentary behavior, and weight status of children and adolescents. Participants were adolescents (n = 189; mean age = 14.6), parents of adolescents (n = 171; mean age = 45.0), and parents of younger children (n = 116; parents mean age = 39.6; children's mean age = 8.3) who completed two surveys approximately one month apart. Measures included a 21-item electronic equipment scale (to assess sedentary behavior facilitators in the home, in the child or adolescent's bedroom, and portable electronics) and a 14-item home physical activity equipment scale. Home environment factors were examined as correlates of children's and adolescents' physical activity, sedentary behavior, and weight status after adjusting for child age, sex, race/ethnicity, household income, and number of children in the home. Most scales had acceptable test-retest reliability (intraclass correlations were .54 - .92). Parent and adolescent reports were correlated. Electronic equipment in adolescents' bedrooms was positively related to sedentary behavior. Activity equipment in the home was inversely associated with television time in adolescents and children, and positively correlated with adolescents' physical activity. Children's BMI z-score was positively associated with having a television in their bedroom. The measures of home electronic equipment and activity equipment were similarly reliable when reported by parents and by adolescents. Home environment attributes were related to multiple obesity-related behaviors and to child weight status, supporting the construct validity of these scales.
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Meta-analyses of behavior change (BC) interventions typically find large heterogeneity in effectiveness and small effects. This study aimed to assess the effectiveness of active BC interventions designed to promote physical activity and healthy eating and investigate whether theoretically specified BC techniques improve outcome. Interventions, evaluated in experimental or quasi-experimental studies, using behavioral and/or cognitive techniques to increase physical activity and healthy eating in adults, were systematically reviewed. Intervention content was reliably classified into 26 BC techniques and the effects of individual techniques, and of a theoretically derived combination of self-regulation techniques, were assessed using meta-regression. Valid outcomes of physical activity and healthy eating. The 122 evaluations (N = 44,747) produced an overall pooled effect size of 0.31 (95% confidence interval = 0.26 to 0.36, I(2) = 69%). The technique, "self-monitoring," explained the greatest amount of among-study heterogeneity (13%). Interventions that combined self-monitoring with at least one other technique derived from control theory were significantly more effective than the other interventions (0.42 vs. 0.26). Classifying interventions according to component techniques and theoretically derived technique combinations and conducting meta-regression enabled identification of effective components of interventions designed to increase physical activity and healthy eating.
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In the post-World War II era, there have been dramatic changes to the environment that appear to be having a detrimental impact on the lifestyles and incidental physical activities of young people. These changes are not trivial and have the potential to influence not only physical health, but also mental health and child development. However, the evidence of the impact of the built environment on physical activity to date is inconsistent. This review examines the evidence on the association between the built environment and walking for transport as well as physical activity generally, with a focus on methodological issues that may explain inconsistencies in the literature to date. It appears that many studies fail to measure behaviour-specific environmental correlates, and insufficient attention is being given to differences according to the age of study participants. Higher levels of out-of-school-hours physical activity and walking appear to be significantly associated with higher levels of urban density and neighbourhoods with mixed-use planning, especially for older children and adolescents. Proximate recreational facilities also appear to predict young people's level of physical activity. However, there are inconsistencies in the literature involving studies with younger children. Independent mobility increases with age. For younger children, the impact of the built environment is influenced by the decision-making of parents as the gatekeepers of their behaviour. Cross-cultural differences may also be present and are worthy of greater exploration. As children develop and are given more independent mobility, it appears that the way neighbourhoods are designed - particularly in terms of proximity and connectivity to local destinations, including schools and shopping centres, and the presence of footpaths - becomes a determinant of whether children are able, and are permitted by their parents, to walk and use destinations locally. If older children and adolescents are to enjoy health and developmental benefits of independent mobility, a key priority must be in reducing exposure to traffic and in increasing surveillance on streets (i.e. 'eyes-on-the-street') through neighbourhood and building design, by encouraging others to walk locally, and by discouraging motor vehicle use in favour of walking and cycling. Parents need to be assured that the rights and safety of pedestrians (and cyclists) - particularly child pedestrians and cyclists - are paramount if we are to turn around our 'child-free streets', now so prevalent in contemporary Australian and US cities. There remains a need for more age- and sex-specific research using behaviour- and context-specific measures, with a view to building a more consistent evidence base to inform future environmental interventions.
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We examined frequency of use of 11 physical activity (PA) locations among 539 San Diego children (45.0% males, 41.2% Latinos; mean ± SD age: 6.6 ± 0.7 years) and explored associations between location use, PA and potential correlates. Parents reported child's use (visits/week) of 11 locations. Child PA was assessed by accelerometry (subsample n = 178). The most frequently used locations (mean ± SD times/week) were homes (3.2 ± 2.3) and parks/playground (1.6 ± 1.3). Children used 4.0 ± 2.0 locations in a typical week, and made a total of 12.5 ± 6.8 visits/week to all locations. Latinos used fewer locations regularly (3.6 ± 2.1 vs. 4.3 ± 1.9 locations; p < 0.001) and had fewer visits to all locations (11.4 ± 7.4 vs. 13.2 ± 6.4 visits/week; p = 0.003) than non-Latinos. Accelerometry-assessed vigorous PA (VPA) was positively associated with the number of locations regularly used (ß = 0.04, p = 0.03) and total visits to all locations among Latinos (ß = 0.09, p = 0.005). Parental PA support was positively associated with locations used (ß = 0.64, p < 0.001) and visits to all locations (ß = 2.56, p < 0.001). Children using a greater variety of locations did more VPA. Latinos making more total visits to all locations had higher VPA.
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Interventions to increase children's physical activity have had limited success. One reason may be that children and their parents overestimate children's levels of physical activity, although there is a small amount of data on this topic. This study aims to assess awareness of physical activity levels among British school children aged 9-10 years and their parents. Physical activity was measured using an accelerometer in a cross-sectional study of 1892 children (44% male; M age=10.3 years, SD=0.3) from 92 Norfolk schools (Sport, Physical Activity and Eating Behavior: Environmental Determinants in Young People [SPEEDY] study). Data were collected between April and July 2007 and analyzed in 2008. Inactive was defined as <60 minutes/day of moderate and vigorous physical activity. Agreement between physical activity perception (child- and parent-rated) and objective physical activity was assessed. Associations between biological (height, weight, fat mass index); parental (support, BMI, physical activity); and peer factors (support, objective physical activity) and child and parental physical activity awareness were studied using multinomial logistic regression. In all, 39% of girls and 18% of boys were inactive. A total of 80% of parents of inactive children wrongly thought that their child was sufficiently active. In all, 40% of inactive children overestimated their physical activity level. Compared to parents who accurately described their children as inactive, parents who overestimated were more likely to have girls (p=0.005), to have a child with a lower fat mass index (p<0.001), or to report more parental and peer support (p=0.014 and p<0.001, respectively). Most parents of inactive children wrongly consider their children to be sufficiently active; parents of children with a lower fat mass index appear to assume that their children are adequately active. Increasing awareness regarding health benefits of physical activity beyond weight control might help reverse misperceptions of physical activity levels and encourage behavior change.
Article
In the post-World War II era, there have been dramatic changes to the environment that appear to be having a detrimental impact on the lifestyles and incidental physical activities of young people. These changes are not trivial and have the potential to influence not only physical health, but also mental health and child development. However, the evidence of the impact of the built environment on physical activity to date is inconsistent. This review examines the evidence on the association between the built environment and walking for transport as well as physical activity generally, with a focus on methodological issues that may explain inconsistencies in the literature to date. It appears that many studies fail to measure behaviour-specific environmental correlates, and insufficient attention is being given to differences according to the age of study participants. Higher levels of out-of-school-hours physical activity and walking appear to be significantly associated with higher levels of urban density and neighbourhoods with mixed-use planning, especially for older children and adolescents. Proximate recreational facilities also appear to predict young people's level of physical activity. However, there are inconsistencies in the literature involving studies with younger children. Independent mobility increases with age. For younger children, the impact of the built environment is influenced by the decision-making of parents as the gatekeepers of their behaviour. Cross-cultural differences may also be present and are worthy of greater exploration. As children develop and are given more independent mobility, it appears that the way neighbourhoods are designed - particularly in terms of proximity and connectivity to local destinations, including schools and shopping centres, and the presence of footpaths - becomes a determinant of whether children are able, and are permitted by their parents, to walk and use destinations locally. If older children and adolescents are to enjoy health and developmental benefits of independent mobility, a key priority must be in reducing exposure to traffic and in increasing surveillance on streets (i.e. 'eyes-on-the-street') through neighbourhood and building design, by encouraging others to walk locally, and by discouraging motor vehicle use in favour of walking and cycling. Parents need to be assured that the rights and safety of pedestrians (and cyclists) - particularly child pedestrians and cyclists - are paramount if we are to turn around our 'child-free streets', now so prevalent in contemporary Australian and US cities. There remains a need for more age- and sex-specific research using behaviour- and context-specific measures, with a view to building a more consistent evidence base to inform future environmental interventions.