Objectively Measured Physical Activity in Children

Journal of Physical Activity and Health, 2013, 10, 1145-1152
© 2013 Human Kinetics, Inc.
Official Journal of ISPAH
www.JPAH-Journal.com
ORIGINAL RESEARCH
Objectively Measured Physical Activity in Children
From a Southern Brazilian City: A Population-Based Study
Renata Moraes Bielemann, Andreia Morales Cascaes,
Felipe Fossati Reichert, Marlos R. Domingues, and Denise Petrucci Gigante
Background: The aim of this study was to assess physical activity (PA) patterns (intensity and prevalence) in
children according to demographic, socioeconomic, and familiar characteristics. Methods: In 2010, a crosssectional study of 239 children aged 4–11 was conducted, in Pelotas, Southern Brazil. PA was measured by
accelerometry and classified in different intensities. Insufficient physical activity was defined as less than 60
min/day of moderate-to-vigorous PA. Descriptive analyses of accelerometry-related variables were presented.
Multivariate Poisson regression models were used to estimate the association between physical insufficient PA
and covariates. Results: For both sexes, around 65% of the registered time was spent in sedentary activities
and less than 20 min/day in vigorous activity. Age and economic status were inversely associated to PA in all
categories of PA. Moderate and vigorous activities means were higher in boys than in girls. The prevalence
of insufficient PA was 34.5% in girls and 19.5% in boys. Conclusions: We found important differences in
physical activity patterns according to sex and economic status, as well as a significant decline in time spent in
moderate-to-vigorous PA with increasing age. Understanding the relationship between these sociodemographic
factors is important to tackle low levels of PA.
Keywords: accelerometry, epidemiology, pediatric, youth
Brazil is a middle-income country where population
health profile in recent years has shifted from high rates of
infectious diseases to chronic disorders (ie, cardiovascular diseases and cancer).1,2 Therefore, there is an increased
interest in assessing the frequency and characteristics of
risk factors that contribute to the current load of diseases,
such as physical inactivity.3
Physical activity (PA) engagement in childhood is
extremely important, because some preventable health
problems, such as overweight and dyslipidemia, which
leads to chronic diseases, begin to manifest at this age.4,5
Moreover, inactive behaviors during childhood are more
likely to continue in older ages.6
Studying physical activity in childhood is essential to
understand such behavior and also to establish effective
actions to prevent inactivity and consequently the chance
of diseases into adulthood.7 However, the assessment of
PA in childhood is extremely hard and questionnaires,
widely used in population surveys, have important
limitations when administered to children.8,9 Hence,
Bielemann, Cascaes, and Gigante are with the post-graduate
program in Epidemiology, Federal University of Pelotas, Pelotas, Rio Grande do Sul, Brazil. Reichert is with the Physical
Activity Epidemiology Research Group, Federal University
of Pelotas, Pelotas, Rio Grande do Sul, Brazil. Deomingues is
with the Sports Dept, Federal University of Pelotas, Pelotas,
Rio Grande do Sul, Brazil.
self-reported physical activity is not recommended to be
used in children younger than 10 years.10
Studies that used more sophisticated methods, like
accelerometry, have been conducted in high-income
countries.11,12 In contrast, population-based studies in
children from middle or low-income countries relying
on physical activity measured by accelerometry were
not found in the literature. In Brazil, accelerometry was
used in validation studies8,13 and also among population
subgroups, such as adolescents14 and chronic patients.15,16
Identifying the factors associated with low levels
of PA is important to plan effective interventions and to
measure physical activity secular trends. The importance
in measuring PA behavior in children is supported by the
idea that this age may be a “window of opportunity” for
long-lasting lifestyle changes.
The purpose of this study was to assess different
intensities of physical activity, using accelerometers, and
to describe it according to demographic, socioeconomic
and familiar characteristics in Brazilian children aged
4–11. We also assessed the association between insufficient physical activity and these variables.
Methods
A population-based cross-sectional study was conducted
in Pelotas, a medium-sized city (around 320,000 inhabitants) in Southern Brazil.
1145
1146 Bielemann et al
The selection of children for the study was based
on multiple-stage sampling. Firstly, the 404 city’s census
tracts, as classified by the Brazilian Institute of Geography
and Statistics (IBGE), were sorted according to the average income of household heads. Then, 130 census tracts
were selected with probability proportionate to their size.
All households from each sampled tract were listed, and
systematically visited. On average, 10 households were
sampled from each tract.
All children aged 4–10 years were eligible for the
study. Interviewers underwent 40-hour training and tested
a provisional version of the questionnaires. Respondents
were mainly children’s mother. In case of absence of the
mother, the person in charge of the child responded to the
questionnaire. The interviews were home-based and were
carried out from January 2010 to May 2010.
The variables collected were child’s sex and age,
maternal age, schooling (years of study), employment
(yes/no), insufficient PA (yes/no), type of housing (house
or apartment), and economic status [based on household
assets, having a full-time maid, and head-of-family`s
schooling, according to the Brazilian Association of
Research Institute criterion17 and classified as A (richest),
B, C, D, or E (poorest)]. Maternal PA was estimated by the
leisure-time section of the International Physical Activity
Questionnaire (IPAQ). Mothers were considered insufficiently active if they did not reach at least 150 minutes/
week of at least moderate intensity PA.18
Children’s physical activity was assessed with the
GT1M Actigraph activity monitor (LLC, Fort Walton
Beach, FL, USA) between February and August 2010. The
epoch was set to 5 seconds and the accelerometers were
delivered in the households on Saturdays and collected on
Wednesdays. In an attempt to keep losses and refuses as
low as possible, mothers and children were contacted twice
to receive the devices, as many times as needed. Children
were advised to wear accelerometers at hip for 24 hours/
day, except during shower or swimming. Participants were
instructed to write down on a diary if they did not wear the
device for more than 1 hour. A fieldwork supervisor conducted quality control phone calls to check equipment’s use.
Due to logistics, exposures and children’s PA could
not be measured at the same time, but no more than 60
days have elapsed between 2 data collections. As the main
exposures investigated are not easily changeable in such
a short time gap (eg, economic status or maternal age), it
cannot lead to bias.
Data from the accelerometers were processed in
the Actilife 4.4.1. software and analyzed in MAHUffe
(www.mrc-epid.cam.ac.uk). Analysis excluded the first
(Saturday) and last day (Wednesday) because they did
not constitute valid days. Besides, we did not consider
for analysis those days that accelerometers were worn for
less than 600min/day and in periods above 10 minutes
of consecutive zero counts. Physical activity intensity
was established as follows: sedentary, up to 100 counts
per minute (cpm); light activity, between 100–1999 cpm;
moderate, between 2000–4999 cpm; and vigorous, from
5000 cpm. The lower limit for the moderate activities
threshold corresponds (in children) to a walking pace
of around 3–4 km/h.19 Moderate or vigorous activities
should last at least 10 consecutive minutes.
The variables obtained by accelerometry were mean
daily registered time; mean counts per minute; mean daily
minutes of sedentary, light, moderate, and vigorous activity;
and insufficient physical activity (yes/no). The latter was
defined when children did not reach 60 or more minutes per
day of at least moderate intensity activities. As children’s
PA was not measured for 7 straight days, this variable is
a proxy of current PA guidelines which state that children
should engage in ≥ 60min/day of moderate to vigorous
intensity activities every day of the week.7,18
Descriptive analyses of demographic, economic, and
accelerometry-related variables are presented. The unadjusted analyses were conducted comparing the prevalence
of insufficient PA according to each independent variable by
chi-square and linear trend tests. Analyses of variance were
performed for continuous outcomes, and nonparametric
tests were conducted when necessary. Poisson regression
was used in the adjusted analysis to obtain prevalence ratios
of insufficient PA and to control for potential confounders. The Poisson regression with robust variance provides
proper estimates and is a better alternative for the analysis
of cross-sectional studies than logistic regression.20
The study was approved by the Ethics Committee
of the Medicine School of Federal University of Pelotas.
Written informed consent was obtained from every mother
before the interviews.
Results
From a total of 379 interviewed participants, we
obtained valid accelerometry for 239 children (64.8%).
The only difference between children with or without
accelerometry information was with respect to maternal
age (younger mothers generated more missing data),
while the distribution of sex, children’s age, economic
status, and all others variables was not different. Table
1 presents the sample characteristics for those with
valid information on accelerometry. More than a half of
the children were boys and only 12.1% of the subjects
belonged to high income families. Most participants
lived in a house and the majority was not living with
other 4- to 11-year-olds. Most children’s mothers were
insufficiently active.
The description of physical activity accelerometry
variables is presented in Table 2. The mean of registered
time was more for boys than girls, but this difference
was not statistically significant (P = .2, data not shown).
For both sexes, around 65% of the registered time was
spent with sedentary activities and less than 20 min/day
with vigorous activity. Moderate and vigorous activities
were higher in boys than girls.
Table 3 shows the unadjusted analyses of variance between children’s daily minutes of activities
and the independent variables. Age was the only exposure associated to all different categories of physical
activities, the higher the age, the lower the activity.
Table 1 Description of the Sample of Children Living in the Urban
Area of Pelotas, Brazil, 2010
Sample
Variables
Sex
Boys
Girls
Age (years)
4–5
6–7
8–9
10–11
Economic status
A/B (highest)
C
D/E
Maternal age (years)
< 30
30–39
≥ 40
Maternal paid work
Yes
No
Maternal physical inactivity (< 150min/week)
Yes
No
Housing type
House
Apartment
Other 4- to 11-year-olds at home
Yes
No
n
%
123
116
51.5
48.5
59
62
68
50
24.7
25.9
28.5
20.9
29
113
97
12.1
47.3
40.6
57
108
73
24.0
45.4
30.7
110
125
46.8
53.2
185
47
79.7
20.3
209
30
87.4
12.6
106
133
44.4
55.6
Table 2 Description of Physical Activity Accelerometry Variables; Pelotas, Brazil, 2010
Boys
Girls
Percentiles
Percentiles
Variables
Registered time (min/day)
Mean
923.9
SD
111.1
25
878.3
50
950.1
75
998.9
Mean
906.5
SD
103.6
25
849.4
50
933.5
75
984.6
Mean counts per minute
536.9
167.0
440.4
515.1
633.9
495.1
210.4
381.7
461.0
560.8
Sedentary activity (min/day)
608.3
102.7
565.5
625.1
681.8
602.7
104.5
547.5
617.6
683.0
Light activity (min/day)
231.7
46.3
209.1
232.6
256.8
231.8
44.9
206.2
239.1
263.6
Moderate activity (min/day)
68.5
21.2
53.9
66.9
85.1
60.3
19.6
46.3
60.8
71.7
Vigorous activity (min/day)
15.5
9.0
8.7
13.9
20.4
11.6
7.1
6.5
9.6
16.1
Moderate to vigorous activity
(min/day)
84.0
28.3
65.1
81.8
104.7
72.0
24.7
53.7
70.6
87.1
1147
1148 Bielemann et al
Table 3 Unadjusted Variance Analyses Between Children’s Daily Minutes of Activities and Independent
Variables; Pelotas, Brazil, 2010
Variables
Sex
Male
Female
Age (years)
4–5
6–7
8–9
10–11
Economic status
A/B (highest)
C
D/E
Maternal age (years)
< 30
30–39
≥ 40
Maternal paid work
Yes
No
Maternal physical
inactivity
(< 150min/week)
Yes
No
Housing type
House
Apartment
Other 4- to 11-year-olds
at home
Yes
No
t
k
Sedentary activity
(min/day)
P
Mean (SD)
0.7
608.3 (102.7)
602.7 (104.5)
<0.001t
562.9 (102.2)
599.7 (104.6)
619.6 (97.7)
643.9 (94.1)
0.2t
608.6 (87.1)
614.8 (104.7)
592.0 (106.5)
0.07
589.0 (113.2)
622.5 (622.5)
593.9 (593.9)
1.0
604.9 (104.2)
605.0 (103.5)
0.4
Light activity
(min/day)
Mean (SD)
P
1.0
231.7 (46.3)
231.8 (44.9)
<0.001t
261.9 (37.0)
232.7 (43.1)
218.7 (44.9)
212.9 (40.9)
0.002t
222.2 (38.5)
224.9 (49.4)
243.0 (39.3)
0.09
242.8 (47.6)
226.5 (43.3)
231.3 (46.4)
0.7
230.8 (46.4)
233.0 (43.8)
0.8
Moderate activity
(min/day)
Mean (SD)
P
0.002
68.5 (21.2)
60.3 (19.6)
0.003t
71.3 (19.2)
63.6 (18.9)
64.0 (23.0)
58.4 (20.0)
<0.001t
54.8 (13.1)
61.0 (21.6)
72.0 (19.4)
0.2
69.3 (22.4)
63.8 (22.4)
61.9 (16.4)
0.2
62.8 (20.9)
66.7 (20.5)
0.3
Vigorous activity
(min/day)
Mean (SD)
P
<0.001k
15.5 (9.0)
11.6 (7.1)
0.02t
15.0 (8.7)
13.8 (7.8)
13.6 (8.9)
11.7 (7.9)
0.03t
15.0 (8.6)
13.0 (8.4)
11.9 (7.5)
0.1k
15.0 (8.7)
14.0 (9.3)
11.9 (6.4)
0.7k
13.9 (9.2)
13.4 (7.4)
0.2k
602.1 (104.4)
615.2 (104.1)
230.3 (43.5)
232.2 (48.7)
63.7 (20.0)
67.4 (23.7)
13.1 (7.7)
15.7 (10.7)
0.07
610.1 (101.6)
573.6 (111.5)
0.4
232.6 (46.3)
225.8 (39.6)
0.7
602.5 (105.2)
608.0 (102.3)
0.2
65.2 (21.4)
59.6 (15.8)
0.8
230.7 (47.9)
232.6 (43.7)
0.9
13.6 (8.5)
13.4 (7.4)
0.3
66.2 (22.4)
63.2 (19.4)
0.2k
14.6 (9.3)
12.8 (7.5)
Linear trend test.
Kruskal-Wallis test.
We found that boys’ moderate and vigorous activities
means were higher than girls’ (P = .002; P < .001).
Economic status was associated to mean values of light,
moderate and vigorous activities. While light and moderate physical activities means were lower among children
from the highest economic group, vigorous physical
activities means were higher among richer children. The
opposite was observed in the vigorous activity category:
the richest children were more vigorously active compared with the poorest ones.
The prevalence of insufficient physical activity
and its associated factors are presented in Table 4. The
prevalence of insufficient PA was higher in girls than
boys. Insufficient PA was also found among children
from wealthier families and those aged 10–11. Sex, age,
and economic status were independently associated to
insufficient physical activity. After the adjustment, the
prevalence ratio of insufficient PA was 1.9 (95% CI,
1.24–2.91) higher in girls compared with boys. Children
in the highest economic group were at least twice more
likely to be insufficiently active than poorer children. The
prevalence of insufficient physical activity was 2.5 times
higher in children aged 10–11 compared with those aged
4–5. There was no significant interaction in the effect
of age and economic status on insufficient PA (P = .7).
A potential interaction between age and economic
status on the moderate activity (P = .10) was observed.
Figure 1 illustrates the time spent in moderate and vigorous activities, showing the effect of age according to
different economic status.
Table 4 Bivariate and Multivariable Analyses Between Insufficient Physical Activity (< 60 min/day
of Moderate-to-Vigorous Physical Activity) and Independent Variables in Children From Pelotas,
Brazil, 2010
Inactivity
Variables
Sex
Boys
Girls
Age (years)
4–5
6–7
8–9
10–11
Economic status
A/B (highest)
C
D/E
Maternal age (years)
< 30
30–39
≥ 40
Maternal paid work
Yes
No
Maternal insufficient physical activity (< 150 min/week)
Yes
No
Housing type
House
Apartment
Other 4- to 11-year-olds at home
Yes
No
%
P*
0.009
19.5
34.5
0.01t
11.9
29.0
33.8
32.0
0.003
34.5
33.9
16.0
0.5
22.8
25.9
31.5
0.3
29.6
23.6
0.2
29.2
19.2
0.7
27.3
23.3
0.3
23.6
29.3
Adjusted analyses
PR (95% CI)
P*
0.007
1.00
1.90 (1.24–2.91)
0.01t
1.00
2.49 (1.13–5.52)
2.78 (1.31–5.90)
2.47 (1.12–5.41)
0.006t
2.07 (1.08–3.95)
2.21 (1.34–3.66)
1.00
0.5
1.00
0.88 (0.49–1.53)
1.17 (0.66–2.10)
0.8
1.07 (0.68–1.70)
1.00
0.3
1.39 (0.74–2.63)
1.00
0.3
1.00
0.67 (0.33–1.36)
0.7
1.00
1.09 (0.71–1.68)
Abbreviations: PR, Prevalence Ratios; CI, Confidence Intervals.
t Linear trend test.
Figure 1 — Children’s daily minutes of moderate and vigorous activity’ intensities according to age and economic level; Pelotas,
Brazil, 2010.
1149
1150 Bielemann et al
Discussion
The main strength of this study is the use of accelerometry. To our knowledge, this is the first study with
a population-based sample of children that assessed
physical activity by accelerometry in a middle-income
country. Accelerometry is an objective method to evaluate physical activity, previously validated against other
methods such as calorimeters,21 doubly-labeled water
or direct observations.10 One limitation of the study,
however, is the 25% loss of valid data on accelerometer
information and 10% of refusals. Although this proportion is somewhat high and might be a source of bias, it is
comparable to other studies in richer settings11,12. Besides,
we do not believe that our results are biased as the only
difference between children with or without accelerometry information was maternal age. Another aspect to
be considered is the sample size. We found an association between sociodemographic variables (sex, age and
economic status) and physical activity intensities, as well
as insufficient PA. However, lack of statistical power
impaired our ability to study the associations between
maternal insufficient physical activity and housing type
and the outcome.
In this study, children with valid data on accelerometry wore the devices for at least 600 minutes per day for
3 consecutive days. It is in accordance with the literature,
considering that this period may provide an appropriate
level of reliability to represent physical activity patterns in
children.22 The first and last days were excluded because
they were not considered as valid.
Time spent in in sedentary activities accounted for
around 65% of the registered time. Similar results were
found with 9- to 10-year-olds from the European Youth
Heart Study whose boys and girls spent, respectively, 62%
and 65% of their time on sedentary activities.11
Lately, the understanding that time spent in sedentary activities must be assessed is increasingly evident.
One indication is the inclusion of this subject in the
children and youth’s PA guidelines.23 Nevertheless, the
contributions of sedentary behavior on adverse health
outcomes are still unknown,11,24 in spite of its effects
on obesity that have been shown in youth25,26 and adulthood.27,28 Furthermore, one of the main sedentary behaviors observed among children (increased television time)
has been associated with inadequate dietary behaviors
such as increased fast-foods intake.29
We observed that children aged 4–5 years were
more active than older children. After this age, children
presented a decline in the activity level, particularly in
the moderate and vigorous activities in contrast to the
increase in sedentary activities. The physical activity
level tends to decline during lifespan and this finding is
consistent in the literature,30 even during adolescence.31
Moreover, substantial attention has been paid to the activity levels of children, largely because of the changing
lifestyles that have threatened the opportunity to be active
and also introduced attractive sedentary alternatives such
as playing computer games and watching television.32
The inverse relationship between physical activity and age found in this study could be explained by
the child’s school entry, at the age of 6, as most school
time is devoted to indoor motionless activities. A body
of high-quality evidence is consistent in suggesting that
PA levels within child care centers are typically very low
while levels of sedentary behavior are high.33 Schools
should play a major role in increasing physical activities
in youth.34 In Brazil, at least 90% of young children regularly go to school. However, a significant proportion of
public schools do not promote physical education classes
for young children, or extracurricular physical activities,
like sports, resulting in reduced levels of moderate and
vigorous activities, prevailed by sedentary activities.
Moreover, even in schools where physical education
classes are offered, the classes are not available on a daily
basis and usually include only low-intensity activities,35
against current recommendations.36
In relation to time spent in moderate and vigorous
physical activity there is clear evidence of a positive effect
on children’s body fatness,11,37 obesity and cardiometabolic risk factors,38 independently of sedentary activities.
In our study, and in accordance with other studies, time
spent in moderate and vigorous PA was significantly
higher in boys than in girls,11,12,38 which could lead to
increased risks for the mentioned health disorders in girls.
The mean time spent in moderate to vigorous physical
activity for girls and boys was slightly higher to that found
in European children.38
We found that 26.8% of the sample was classified
as insufficiently active for not achieving the cutoff of
at least 60 min/day of moderate to vigorous physical
activity. This result was similar to the findings in an
European study reporting insufficient PA prevalence of
31% among 9- to 10-year-olds37 and in a case-control
study performed in Belgium reporting 29% insufficient
physical activity prevalence among children 6–10 years
old with normal weight.39
According to current guidelines, children and
young people should accumulate at least 60 min of
moderate-to-vigorous-intensity aerobic activity per
day, including activities that improve bone density and
muscle strength.18 However, by accelerometer we cannot
discriminate the kind of activity practiced.
In our sample, children belonging to the lowest economic group were, in general, more active than others. A
potential explanation for that relationship is that wealthier
families have more electronic assets at home; hence, children in the richest group could spend more time watching
television or playing video games compared with poorer
children. The entertainment activities among poorer children are usually performed outdoors, resulting in higher
levels of activity. On the other hand, richest children were
more vigorously active and this result reflects again the
economic pattern: richer kids in Brazil have more access
to play elite sports and programmed physical activities.
In another cultural context, where economic inequality
is less pronounced, researchers did not find association
between physical activity and economic level.40
Physical Activity in Brazilian Children 1151
Another aspect related to the economic level is commuting to school. In Pelotas, nearly 90% of adolescents
in the lower income group commute to school on foot
or by bicycle, while just over 50% among the richest are
active commuters.41
Our study did not find any association between
mother’s physical activity and child’s physical activity.
However, one should have in mind that we estimated
leisure-time physical activity of the mothers by self report
and overall physical activity in children by accelerometry.
This issue might have hinder the association because it
has been shown that children whose parents are more
active tend to be more active as well.42 However, as this
finding is not consistent in the literature,31 further studies
should address this association.
Consistent with the literature, in our study, girls were
more inactive than boys. Other studies have found the
same association in children.11,37,38 Adolescent and adult
women are also less active than men41,43,44 suggesting that
the pattern begins in childhood and remains unchanged
as people age. Another study carried out in Pelotas city
described potential hypothesis to explain such relationship. According to this study, girls might be less active
because they suffer greater deprivation of liberty than
boys, perhaps related to security, in addition to increased
social and family support for physical activity that happens in boys.45
Conclusion
This was the first study that evaluated the physical activity
by accelerometry and its associated factors in children
from Brazil. The understanding of factors influencing physical activity in children is relevant as it may
determine current and future risk behaviors. We found
important differences in physical activity patterns by sex
and economic status, and a significant decline in time
spent in moderate-to-vigorous PA with increased age.
Our study can contribute to the development of interventions to encourage healthy lifestyles in children and to
attenuate the PA decline throughout lifespan, mainly in
girls. Future studies should address deeply the discussion
on how children become insufficiently active and what
can be done to make them more active, pointing out
guidance on campaigns and interventions focusing on
children and their behavior in terms of physical activity
and sedentary behaviors. We believe that studies like this
should be performed in other South American settings
and in different Brazilian regions.
Acknowledgments
This work was financed by the National Research Council
(CNPQ, Brazil).
References
1. Schmidt MI, Duncan BB, Azevedo e Silva G, et al. Chronic
non-communicable diseases in Brazil: burden and current challenges. Lancet. 2011;377:1949–1961. PubMed
doi:10.1016/S0140-6736(11)60135-9
2. Victora CG, Barreto ML, do Carmo Leal M, et al. Health
conditions and health-policy innovations in Brazil: the
way forward. Lancet. 2011;377:2042–2053. PubMed
doi:10.1016/S0140-6736(11)60055-X
3. Ezzati M, Hoorn SV, Lopez AD, et al. Comparative quantification of mortality and burden of disease attributable to
selected risk factors. In: Lopez AD, Mathers CD, Ezzati
M, Jamison D, Murray CJL, eds. Global burden of disease
and risk factors. Washington, DC: World Bank; 2006.
4. de Assis MA, Rolland-Cachera MF, Grosseman S, et
al. Obesity, overweight and thinness in schoolchildren
of the city of Florianopolis, Southern Brazil. Eur J
Clin Nutr. 2005;59:1015–1021. PubMed doi:10.1038/
sj.ejcn.1602206
5. Silva AA, Barbieri MA, Cardoso VC, et al. Prevalence
of non-communicable diseases in Brazilian children:
follow-up at school age of two Brazilian birth cohorts of
the 1990’s. BMC Public Health. 2011;11:486. PubMed
doi:10.1186/1471-2458-11-486
6. Telama R, Yang X, Viikari J, Valimaki I, Wanne O, Raitakari O. Physical activity from childhood to adulthood: a
21-year tracking study. Am J Prev Med. 2005;28:267–273.
PubMed doi:10.1016/j.amepre.2004.12.003
7. Biddle S, Sallis J, Cavill N. Young and Active? Young
people and health-enhancing physical activity - evidence
and implications. In: Health Education Authority L, ed.
1998.
8. Bielemann RM, Reichert FF, Paniz VM, Gigante DP. Validation of the Netherlands physical activity questionnaire in
Brazilian children. Int J Behav Nutr Phys Act. 2011;8:45.
PubMed doi:10.1186/1479-5868-8-45
9. Welk GJ, Corbin CB, Dale D. Measurement issues in the
assessment of physical activity in children. Res Q Exerc
Sport. 2000;71:S59–S73. PubMed
10. Kohl HI, Fulton J, Caspersen C. Assessment of physical
activity among children and adolescents: a review and
synthesis. Prev Med. 2000;31(2):S54–S76.
11. Ekelund U, Sardinha LB, Anderssen SA, et al. Associations between objectively assessed physical activity and
indicators of body fatness in 9- to 10-y-old European
children: a population-based study from 4 distinct regions
in Europe (the European Youth Heart Study). Am J Clin
Nutr. 2004;80:584–590. PubMed
12. Steele RM, van Sluijs EM, Sharp SJ, Landsbaugh JR,
Ekelund U, Griffin SJ. An investigation of patterns of children’s sedentary and vigorous physical activity throughout
the week. Int J Behav Nutr Phys Act. 2010;7:88. PubMed
doi:10.1186/1479-5868-7-88
13. Hallal PC, Simoes E, Reichert FF, et al. Validity and
reliability of the telephone-administered international
physical activity questionnaire in Brazil. J Phys Act Health.
2010;7:402–409. PubMed
14. Reichert FF, Menezes AM, Kingdom Wells JC, Ekelund
E, Rodrigues FM, Hallal PC. A methodological model for
collecting high-quality data on physical activity in developing settings-the experience of the 1993 Pelotas (Brazil)
Birth Cohort study. J Phys Act Health. 2009;6:360–366.
PubMed
1152 Bielemann et al
15. Hallal PC, Victora CG, Wells JC, Lima RC. Physical
inactivity: prevalence and associated variables in Brazilian adults. Med Sci Sports Exerc. 2003;35:1894–1900.
PubMed doi:10.1249/01.MSS.0000093615.33774.0E
16. Pitta F, Breyer MK, Hernandes NA, et al. Comparison of daily physical activity between COPD patients
from Central Europe and South America. Respir
Med. 2009;103:421–426. PubMed doi:10.1016/j.
rmed.2008.09.019
17. Associação Brasileira de Empresas de Pesquisa. Critério
de Classificação Econômica Brasil; 2010.
18. U. S. Department of Health and Human Services. 2008
Physical Activity Guidelines for Americans. Washington
(DC); 2008.
19. Trost SG, Ward DS, Moorehead SM, Watson PD, Riner W,
Burke JR. Validity of the computer science and applications (CSA) activity monitor in children. Med Sci Sports
Exerc. 1998;30:629–633. PubMed doi:10.1097/00005768199804000-00023
20. Barros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison
of models that directly estimate the prevalence ratio. BMC
Med Res Methodol. 2003;3:21. PubMed doi:10.1186/14712288-3-21
21. Puyau MR, Adolph AL, Vohra FA, Butte NF. Validation and
calibration of physical activity monitors in children. Obes
Res. 2002;10:150–157. PubMed doi:10.1038/oby.2002.24
22. Penpraze V, Reilly JJ, MacLean CM, et al. Monitoring of
physical activity in young children: how much is enough?
Pediatr Exerc Sci. 2006;18:483–491.
23. Tremblay MS, Leblanc AG, Janssen I, Kho ME, Hicks A,
Murumets K, Colley RC, Duggan M. Canadian sedentary
behaviour guidelines for children and youth. Applied
physiology, nutrition, and metabolism = Physiologie
appliquee, nutrition et metabolisme. 2011;36:59–64; 5–71.
24. Treuth MS, Baggett CD, Pratt CA, Going SB, Elder JP,
Charneco EY, Webber LS. A longitudinal study of sedentary behavior and overweight in adolescent girls. Obesity
(Silver Spring, MD). 2009;17:1003–8.
25. Ekelund U, Brage S, Froberg K, et al. TV viewing and
physical activity are independently associated with metabolic risk in children: the European Youth Heart Study.
PLoS Med. 2006;3:e488. PubMed doi:10.1371/journal.
pmed.0030488
26. Berkey CS, Rockett HR, Gillman MW, Colditz GA. Oneyear changes in activity and in inactivity among 10- to
15-year-old boys and girls: relationship to change in
body mass index. Pediatrics. 2003;111:836–843. PubMed
doi:10.1542/peds.111.4.836
27. Bankoski A, Harris TB, McClain JJ, et al. Sedentary
activity associated with metabolic syndrome independent
of physical activity. Diabetes Care. 2011;34:497–503.
PubMed doi:10.2337/dc10-0987
28. Ford ES, Li C, Zhao G, Pearson WS, Tsai J, Churilla JR.
Sedentary behavior, physical activity, and concentrations
of insulin among US adults. Metabolism. 2010;59:1268–
1275. PubMed doi:10.1016/j.metabol.2009.11.020
29. Pearson N, Biddle SJ. Sedentary behavior and dietary
intake in children, adolescents, and adults. A systematic
review. Am J Prev Med. 2011;41:178–188. PubMed
doi:10.1016/j.amepre.2011.05.002
30. Dumith SC, Gigante DP, Domingues MR, Kohl HW,
3rd. Physical activity change during adolescence: a
systematic review and a pooled analysis. Int J Epidemiol.
2011;40:685–698. PubMed doi:10.1093/ije/dyq272
31. Taylor RW, Murdoch L, Carter P, Gerrard DF, Williams
SM, Taylor BJ. Longitudinal study of physical activity
and inactivity in preschoolers: the FLAME study. Med
Sci Sports Exerc. 2009;41:96–102. PubMed
32. Fox KR, Riddoch C. Charting the physical activity patterns of contemporary children and adolescents. Proc
Nutr Soc. 2000;59:497–504. PubMed doi:10.1017/
S0029665100000720
33. Reilly JJ. Low levels of objectively measured physical
activity in preschoolers in child care. Med Sci Sports Exerc.
2010;42:502–507. PubMed
34. Kohl HW, 3rd, Hobbs KE. Development of physical activity behaviors among children and adolescents. Pediatrics.
1998;101:549–554. PubMed
35. Nader PR. Frequency and intensity of activity of thirdgrade children in physical education. Arch Pediatr
Adolesc Med. 2003;157:185–190. PubMed doi:10.1001/
archpedi.157.2.185
36. US Department of Health and Human Services. Healthy
People 2010. 2nd ed. Washington (DC); 2000.
37. Steele RM, van Sluijs EM, Cassidy A, Griffin SJ, Ekelund
U. Targeting sedentary time or moderate- and vigorousintensity activity: independent relations with adiposity in a
population-based sample of 10-y-old British children. Am
J Clin Nutr. 2009;90:1185–1192. PubMed doi:10.3945/
ajcn.2009.28153
38. Owen N, Healy GN, Matthews CE, Dunstan DW. Too
much sitting: the population health science of sedentary
behavior. Exerc Sport Sci Rev. 2010;38:105–113. PubMed
doi:10.1097/JES.0b013e3181e373a2
39. Deforche B, De Bourdeaudhuij I, D’Hondt E, Cardon G.
Objectively measured physical activity, physical activity
related personality and body mass index in 6- to 10-yr-old
children: a cross-sectional study. Int J Behav Nutr Phys
Act. 2009;6:25. PubMed doi:10.1186/1479-5868-6-25
40. Kelly LA, Reilly JJ, Fisher A, et al. Effect of socioeconomic status on objectively measured physical activity.
Arch Dis Child. 2006;91:35–38. PubMed doi:10.1136/
adc.2005.080275
41. Dumith SC, Domingues MR, Gigante DP, Hallal PC,
Menezes AM, Kohl HW. Prevalence and correlates of
physical activity among adolescents from Southern
Brazil. Rev Saude Publica. 2010;44:457–467. PubMed
doi:10.1590/S0034-89102010000300009
42. Moore LL, Lombardi DA, White MJ, Campbell JL,
Oliveria SA, Ellison RC. Influence of parents’ physical
activity levels on activity levels of young children. J
Pediatr. 1991;118:215–219. PubMed doi:10.1016/S00223476(05)80485-8
43. Besson H, Ekelund U, Luan J, et al. A cross-sectional
analysis of physical activity and obesity indicators in
European participants of the EPIC-PANACEA study. Int
J Obes. 2005;2009(33):497–506. PubMed
44. Luke A, Dugas LR, Durazo-Arvizu RA, Cao G, Cooper
RS. Assessing physical activity and its relationship to
cardiovascular risk factors: NHANES 2003-2006. BMC
Public Health. 2011;11:387. PubMed doi:10.1186/14712458-11-387
45. Goncalves H, Hallal PC, Amorim TC, Araujo CL, Menezes
AM. [Sociocultural factors and physical activity level in
early adolescence]. Am J Public Health. 2007;22:246–253.