Longitudinal Sedentary Behavior Changes in
Adolescents in Ho Chi Minh City
Nguyen H.H.D. Trang, MD, MSc, Tang K. Hong, MD, PhD, Hidde P. van der Ploeg, PhD,
Louise L. Hardy, PhD, Patrick J. Kelly, PhD, Michael J. Dibley, MBBS, MPH
This activity is available for CME credit. See page A4 for information.
Background: Sedentary behavior is associated with increased risk of chronic disease and sedentary
behavior is increasing among adolescents. Data on changes in sedentary behavior in developing
countries are limited.
Purpose: To describe 5-year longitudinal changes in nonschool sedentary hours among urban
adolescents in Ho Chi Minh City, and to identify correlates with this change.
Methods: This is a 5-year longitudinal cohort with systematic random sampling of 759 students
from 18 junior high schools. All measures were taken annually between 2004 and 2009. Sedentary
behavior was assessed by self-report and accelerometry. Generalized linear latent and mixed models
were used to analyze the data in 2011.
Results: Between 2004 and 2009, self-reported time spent in nonschool sedentary behavior
increased from 498 to 603 minutes/day. In the 5th survey year, boys and girls (aged 16 years)
were, respectively, 3.6 times (95% CIϭ2.3, 6.0) and 3.1 times (95% CIϭ 1.8, 5.0) more likely to
spend Ն2 hours/day on screen time compared with baseline (aged 12 years). Accelerometer data
adjusted for wearing time revealed that boys and girls aged 16 years had, respectively,
78 minutes/day (95% CIϭ48, 104) and 69 minutes/day (95% CIϭ34, 95) more nonschool
sedentary time than those at the fırst accelerometer assessment (at age 13 years). Girls in the
highest socioeconomic quartile spent an additional 90 minutes/day in sedentary behavior
compared with girls in the lowest quartile (95% CIϭ52, 128).
Conclusions: Nonschool sedentary behavior increased among Vietnamese adolescents with age.
The largest increase was in recreational screen time (28%), which would be the most obvious target
for preventive health strategies.
(Am J Prev Med 2013;44(3):223–230) © 2013 American Journal of Preventive Medicine
Introduction
S
edentary behaviors increase the risk of obesity
1–3

and the development of a range of chronic dis-
eases.
4–6
In children and adolescents, leisure-time
sedentary behaviors, such as TV viewing, have been
associated with metabolic risk factors, independent of
physical activity levels.
4,7
In recent decades, the oppor-
tunities to be sedentary have increased, and young
people tend to be more sedentary than those in previ-
ous generations.
8,9
Although much is known about correlates of physical
activity,
10
little is known about correlates of sedentary be-
haviors among adolescents, despite the belief that the deter-
minants of sedentary behavior are distinct from those of
physical activity.
11,12
In addition, sedentary behavior ap-
pears to carry over more than physical activity from child-
hood to adolescence,
13
and may even have a greater influ-
ence on the development of overweight and obesity than
physical activity.
14,15
Data on sedentary behaviors are available for devel-

oped countries,
16–20
but they are lacking for develop-
ing nations.
21
Moreover, current studies are mostly
cross-sectional and focused on only screen time (i.e.,
TV, videos/DVDs, recreational computer use), which
has been used widely as a proxy measure of sedentary
behavior among youth.
7,22,23
Few studies have exam-
From the Department of Community Health (Trang, Hong), Pham Ngoc
Thach University of Medicine, Ho Chi Minh City, Vietnam; Sydney School
of Public Health (Trang, Kelly, Dibley), and Prevention Research Collabo-
ration (van der Ploeg, Hardy), The University of Sydney, New South Wales,
Australia; and the Department of Public and Occupational Health (van der
Ploeg), VU University Medical Center Amsterdam, the Netherlands
Address correspondence to: Nguyen H.H.D. Trang, MD, MSc, Pham
Ngoc Thach University of Medicine, 86/2 Thanh Thai Street, District 10,
Ho Chi Minh City, Vietnam. E-mail: nguyenhoang_doantrang@yahoo.
com.
0749-3797/$36.00
/>© 2013 American Journal of Preventive Medicine. All rights reserved. Am J Prev Med 2013;44(3):223–230 223
ined a broad range of sedentary behaviors longitudi-
nally among adolescents.
24
Identifıcation of the correlates of a full range of seden-
tary behaviors in adolescents is needed to develop more-
effıcient preventive action to decrease sedentary behavior

and risk of chronic disease including excess adiposity in
developing countries, such as Vietnam. The purpose of
the current study was to describe the longitudinal
changes in sedentary behavior among adolescents in ur-
ban Vietnam who participated in the Ho Chi Minh City
Youth Cohort study between 2004 and 2009, and to iden-
tify individual, family, and environmental factors associ-
ated with screen time and sedentary behavior over this
5-year period.
Methods
Study Design
The Ho Chi Minh City (Vietnam) Youth Cohort study was a 5-year
longitudinal study that began in 2004 from a multistage cluster
cross-sectional survey. The study examined the weight status and
weight-related behaviors among adolescents in this city. The sur-
vey covered 140 junior high schools from which 31 clusters
(schools) were selected.
Systematic random sampling was used to select 18 junior high
schools, of which 11 were from wealthy districts and seven were
from less-wealthy districts for the cohort.
25
In each school, one
class was taken from two classes (one from Grade 6 and one
from Grade 7) combined. The two classes were selected by
simple random sampling in the cross-sectional study. All stu-
dents in the selected classes were invited to participate in the
study (Nϭ784), and 759 students consented to participate in the
cohort.
Data were collected by trained fıeld staff on fıve occasions, 1 year
apart, on adolescents who consented to take part in the study.

Consent, from both the adolescents and their parents, was required
for participation in the cohort study. The study was approved by
the Research Ethics Committee, Pham Ngoc Thach University of
Medicine, Ho Chi Minh City, and the Human Research Ethics
Committee of the University of Newcastle, Australia.
Data Collection
Information on sedentary behaviors was measured using the Ado-
lescent Sedentary Activity Questionnaire (ASAQ),
26
validated in
Vietnamese adolescents,
27
which asked students to report the time
spent outside of school hours for each day of the week in a range of
sedentary activities. Daily time spent in sedentary behavior was com-
puted as the total of all recorded sedentary activities, categorized by
sedentary domains: screen time (watching TV/video, playing com-
puter games, using computer for fun); educational time (using com-
puter for study, studying at home, studying in afterschool class); other
leisure time (reading books, chatting with friends, talking on phone,
doing hobbies, music or painting lesson/practice); and passive com-
muting to school (i.e., by car, bus, motorbike).
One year after baseline (Year 2005), students’ sedentary behav-
ior also was assessed objectively for 7 days with an Actigraph
accelerometer (model GT1M) worn on the right hip.
28
Sedentary
time was defıned as Ͻ100 counts per minute.
29,30
Nonwear time

was defıned as 10 minutes of consecutive zeroes.
31
Only partici-
pants who wore the accelerometer for Ն8 hours per day on at least
4 days were included in the analysis. Physical activity was assessed
using the Vietnamese Adolescent Physical Activity Recall Ques-
tionnaire (V-APARQ).
32
The Spearman and intraclass correla-
tion coeffıcients showed this questionnaire to be valid and reli-
able, with a weighted kappa of 0.75, indicating that the
V-APARQ is useful for monitoring change in physical activity
among Vietnamese adolescents.
Anthropometric measurements were taken by trained fıeld staff.
Participant weight (in kilograms; without shoes or heavy clothing)
was measured using a Tanita BF 571 electronic scale and recorded
to the nearest 100 g. Standing height (in centimeters) was measured
with a suspended Microtoise tape to the nearest 0.1 cm. BMI was
calculated, and overweight and obesity were defıned using the
International Obesity Task Force cutpoint values.
33
In a confıden-
tial setting, the adolescents self-reported their pubertal status using
Tanners’ fıve stages of pubertal development for pubic hair, and
male genitalia or female breasts; for female students, the date of
menarche also was recorded.
34
The student’s parents also completed a questionnaire provid-
ing information on household SES, and their personal charac-
teristics. SES was assessed through questions on ownership of 14

assets that were used to construct a household wealth index.
Responses were ranked and divided into quartiles of SES. Par-
ents also reported on the availability of computer game stores,
home rules on playing computer games, presence of a TV in the
child’s room, and frequency of the parents’ doing exercises with
their child.
Data Analysis
Analyses were conducted using Stata, version 11. Models were
fıtted using the generalized linear latent and mixed models
(GLLAMM) package in Stata.
35
Multilevel models were used to take
account of the clustering of observations within schools and for
repeated student observations. Data were weighted according to
school size. Screen time was categorized according to recom-
mended guidelines (Ͻ2 and Ն2 hours/day).
36
To determine fac-
tors that could predict the change in the prevalence of Ն2 hours/
day screen time, multilevel multivariable logistic regression models
were used,and multilevelmultivariable linearmodels wereused for
continuous data.
Results were stratifıed by gender because participation in seden-
tary behaviors differed between boys and girls,
37
and an interaction
was found between gender and sedentary time (pϭ0.004). Vari-
ables with a univariate p-value Ͻ0.25 were entered into the multi-
variable model.
38

Stepwise backward elimination was used, and
variables were removed from the model if their adjusted p-value
was Ͼ0.05. Only signifıcant factors were presented.
Results
At baseline, 759 adolescents consented to participate in
the study, and complete data from the 5 survey years were
available for 585 (77%) adolescents. At baseline, the mean
age of the students was 11.8 years (Ϯ0.6). The baseline
characteristics of the students (Table 1) showed that
14.2% of students were overweight or obese. The majority
of students did not have a TV in their bedroom (92%);
224 Trang et al / Am J Prev Med 2013;44(3):223–230
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had a computer game store nearby (95%); and had paren-
tal rules limiting screen time (95%).
Self-reported time spent in various domains of seden-
tary behaviors by survey year is shown in Table 2. Over
the 5-year period, sedentary behavior increased by
21% (pϽ0.001; from an average of 498 minutes/day to
603 minutes/day). At each survey year, the most common
sedentary domain was afterschool educational activities,
Table 1. Baseline characteristics of adolescents, M (SD) or % (95% CI)
Boys
(nϭ364)
Girls
(nϭ395)
Total
(Nϭ759)
Age (years) 11.8 (0.6) 11.9 (0.7) 11.8 (0.6)
Height (cm) 155.7 (9.7) 153.4 (8.1) 154.5 (9)

Weight (kg) 44.6 (9.6) 41 (7.4) 42.7 (8.7)
BMI 20.1 (3.9) 18.1 (3.1) 19.1 (3.7)
BMI status
a
Not overweight/obese 78.2 (73.7, 82.7) 86.5 (82.9, 90.0) 82.5 (79.7, 85.4)
Overweight/obese 21.8 (17.3, 26.3) 13.5 (9.9, 17.1) 17.4 (14.6, 20.3)
Pubertal status
Prepubescent 45.9 (40.6, 51.2) 22.1 (18.0, 26.3) 33.6 (29.9, 36.8)
Pubescent and postpubescent 54.1 (48.8, 59.4) 77.9 (73.7, 82.0) 66.6 (63.2, 70.1)
Maternal education (nϭ329) (nϭ367) (nϭ696)
Did not complete junior high
school
24.6 (19.9, 29.3) 26.7 (22.2, 31.2) 25.7 (22.5, 29.0)
Did not complete high school 21.6 (17.1, 26.0) 22.3 (18.1, 26.6) 22.0 (18.9, 25.1)
Completed high school or higher 53.8 (48.4, 59.2) 50.9 (45.8, 56.1) 52.3 (48.6, 56.0)
Paternal education (nϭ329) (nϭ367) (nϭ696)
Did not complete junior high
school
19.1 (14.9, 23.4) 22.6 (18.3, 26.9) 21.0 (17.9, 24.0)
Did not complete high school 20.1 (15.7, 24.4) 21.0 (16.8, 25.2) 20.5 (17.5, 23.6)
Completed high school or higher 60.8 (55.5, 66.1) 56.4 (51.3, 61.5) 58.5 (54.8, 62.1)
BMI status of parents (nϭ291) (nϭ326) (nϭ617)
Both not overweight/obese 71.1 (65.9, 76.4) 72.1 (67.2, 77.0) 71.6 (68.1, 75.2)
Father overweight/obese 7.6 (4.5, 10.6) 7.1 (4.3, 9.8) 7.3 (5.2, 9.4)
Mother overweight/obese 17.9 (13.4, 22.3) 16.6 (12.5, 20.6) 17.2 (14.2, 20.2)
Both overweight/obese 3.4 (1.3, 5.5) 4.3 (2.1, 6.5) 3.9 (2.3, 5.4)
SES quartile
b
(nϭ364) (nϭ395) (nϭ759)
1st (poorest) 26.1 (21.6, 30.6) 25.3 (21.0, 29.6) 25.7 (22.6, 28.8)

2nd 22.5 (18.2, 26.8) 26.3 (22.0, 30.7) 24.5 (21.4, 27.6)
3rd 25.8 (21.3, 30.3) 27.1 (22.7, 31.5) 26.5 (23.3, 29.6)
4th (richest) 25.5 (21.1, 30.0) 21.3 (17.2, 25.3) 23.3 (20.3, 26.3)
TV in child’s bedroom (nϭ360) (nϭ391) (nϭ751)
No 88.9 (87.4, 90.3) 94.1 (93.1, 95.2) 91.6 (90.7, 92.5)
Easy access to computer game store (nϭ278) (nϭ371) (nϭ649)
Yes 94.4 (91.0, 97.8) 94.7 (91.3, 98.1) 94.5 (92.2, 96.9)
Rules for computer games at home (nϭ337) (nϭ351) (nϭ688)
Yes 95.0 (92.6, 97.3) 94.0 (91.5, 96.5) 94.5 (92.8, 96.2)
a
Defined by using International Obesity Task Force cutpoint
b
Based on household wealth index
Trang et al / Am J Prev Med 2013;44(3):223–230 225
March 2013
accounting for 38%– 40% of total sedentary time,
followed by screen time (30%–34%) and other leisure
activities (17%–20%). Over the 5-year period, screen time
increased by 28% (pϽ0.001); afterschool educational ac-
tivities increased by 27% (pϽ0.001); and other sedentary
leisure-time activities increased by 14% (pϽ0.01). At
baseline, 81.5% students have more than 2 hours of screen
time/day, increasing to 86.4% in 5 years (pϭ0.01).
Figure 1 shows the median time (minutes/day) spent in
three main domains of sedentary behavior outside of
school hours by gender and survey year. For both boys
and girls, time spent in afterschool educational activities
and screen time increased at each survey year. Boys con-
sistently engaged in more screen time than girls across
survey years (pϽ0.001). At baseline, screen time was

160 minutes/day and 144 minutes/day and increasedover
the 5-year period to 215 minutes/day and 190 minutes/
day, for boys and girls respectively. In contrast, girls spent
signifıcantly more time in afterschool educational activi-
ties than boys, especially in the third survey year when
students transitioned into high school, although educa-
tional time did increase in both boys and girls.
The correlates of screen time of Ն2 hours/day by gen-
der show that in the 5th survey year, boys (mean age
16 years) were 3.6 times (ORϭ3.6, 95% CIϭ2.3, 6.0) as
likely to spend Ն2 hours/day on screen time compared
with baseline screen time (mean age 12 years). Similarly,
in the 5th survey year, girls(mean age 16 years) were three
times (ORϭ3.1, 95% CIϭ1.8, 5.0) as likely to spend
Ն2 hours/day on screen time compared with baseline
screen time (mean age 12 years). Girls from the highest
SES quartile were also twice as likely to spend Ն2 hours/
day on screen time than their counterparts from the low-
est SES quartile (ORϭ2.1, 95% CIϭ1.3, 3.4).
The correlates of time in total sedentary behavior
(Table 3) show that in the 5th survey year (mean age
16 years), boys had increased their daily sedentary time
by 121 minutes/day (95% CIϭ98, 160) compared with
baseline, whereas sedentary behavior among girls in-
creased 115 minutes/day (95% CIϭ96, 163) over the
5-year period. Girls in the highest SES quartile had an
additional 90 minutes of daily sedentary time compared
with peers in the lowest SES quartile (95% CIϭ52, 128).
Table 2. Sedentary behavior time (minutes/day) outside of school hours, by categories and survey year
2004/2005

nϭ759
2005/2006
nϭ740
2006/2007
nϭ712
2007/2008
nϭ630
2008/2009
nϭ585
Age (years) 11.8 (0.66) 12.8 (0.65) 13.9 (0.64) 14.8 (0.71) 15.8 (0.61)
Accelerometry time (minutes) — 445 (118) 463 (114) 498 (92) 482 (90)
Wearing time, accelerometry (minutes) — 787 (134) 779 (134) 734 (127) 705 (117)
Self-reported time (ASAQ; minutes) 498 (180) 558 (201) 601 (210) 604 (215) 603 (212)
Screen time 158 (102, 243) 165 (114, 283) 172 (163, 287) 205 (156, 275) 203 (157, 264)
TV 75 (43, 129) 86 (51, 137) 94 (78, 136) 103 (69, 146) 99 (60, 137)
Video 34 (17, 62) 39 (19, 69) 34 (20, 60) 43 (19, 69) 36 (17, 69)
Using computer for fun/games 31 (17, 60) 40 (27, 69) 50 (34, 114) 63 (44, 89) 72 (46, 120)
Ն2 hours screen time/day,
% (95% CI)
81.5 (78.9, 84.2) 82.8 (80.0, 85.1) 83.2 (80.6, 85.8) 85.7 (83.2, 88.4) 86.4 (83.5, 89.2)
Total afterschool educational time 191 (148, 236) 196 (150, 244) 244 (192, 309) 240 (184, 321) 242 (197, 326)
Computer use for education 21 (14, 34) 26 (16, 39) 27 (21, 43) 30 (19, 51) 35 (18, 56)
Noncomputerized study 101 (60, 146) 110 (70, 139) 125 (94, 174) 118 (69, 154) 120 (80, 164)
Afterschool class 62 (41, 95) 64 (39, 90) 96 (57, 132) 92 (71, 137) 98 (64, 133)
Total other leisure-time sedentary
behavior
108 (65, 143) 116 (75, 211) 103 (85, 148) 120 (114, 175) 123 (112, 160)
Sitting chatting with friends/talking
on phone
26 (14, 49) 40 (10, 76) 36 (11, 72) 50 (30, 83) 45 (29, 77)

Reading 25 (13, 43) 26 (13, 43) 21 (10, 39) 25 (16, 43) 30 (17, 51)
Hobbies/music/recreational
practices
56 (34, 90) 51 (29, 84) 45 (28, 88) 50 (29, 95) 52 (43, 105)
Passive travel 41 (22, 80) 60 (47, 137) 70 (34, 116) 45 (30, 98) 40 (30, 103)
Note: Values are M (SD) or median (25th percentile, 75th percentile), unless otherwise noted; — ϭ no observation.
ASAQ, Adolescent Sedentary Activity Questionnaire
226 Trang et al / Am J Prev Med 2013;44(3):223–230
www.ajpmonline.org
Accelerometer data, adjusted for wearing time, showed
that sedentary behavior increased by 78 minutes/day
(95% CIϭ48, 104) among boys and 69 minutes/day
(95% CIϭ34, 95) among girls between the 2nd and 5th
survey year. Physical activity and environmental factors
were not associated with the changes in screen time and
sedentary behavior. Changes in BMI were not associated
with changes in sedentary behavior (data not shown).
Discussion
This is the fırst study to present longitudinal changes
across a broad range of sedentary behaviors and to pro-
vide a better understanding of relevant correlates of
screen time and sedentary behavior among Vietnamese
adolescents. The study fındings are important to the de-
sign of interventions designed to decrease the sedentary
lifestyles that are becoming increasingly common in de-
veloping countries such as Vietnam. This study showed
an increase in nonschool sedentary time in a representa-
tive sample of adolescents aged 12–16 years in urban Ho
Chi Minh City. Afterschool educational sedentary time
and screen time accounted for more than two thirds to

three quarters of total sedentary time, respectively, out-
side school hours. Age, gender, and SES were related to
screen time and total sedentary time.
The increase in screen time with age found in the
present study is similar to increases reported by longi-
tudinal studies in developed countries.
13,39,40
This
fınding may be due to the substantial amount of free-
dom adolescents have in Vietnam to engage in screen
time and the increased access and availability of screen
technologies. Ownership of a TV among those in ur-
ban areas in Vietnam has increased from 77% in 1999
to 91.3% in 2009.
41
Likewise, Internet usage has increased signifıcantly
from 12.8% to 25.7% from 2005 to 2009.
42
Among all
screen behaviors, TV time only increased slightly, a fınd-
ing in accordance with previous studies that reported the
stability of TV time.
43
The median screen time of Viet-
namese adolescents was above the recommended level of
Ͻ2 hours/day in all 5 survey years (2.5–3.5 hours per
day). This is higher than the level found in a study in
urban Chinese adolescents in 2004–2006 that reported
1.2–1.7 hours/day of screen time,
44

and it is more closely
aligned with fındings of adolescents’ screen time in the
U.S. and Canada, where daily screen time exceeds
4 hours/day.
45
The present fınding that Vietnamese youth report a
large amount of time in afterschooleducational sedentary
behaviors is similar to results reported among Chinese
adolescents.
44
This result may be due to the high priority
placed on education in Asian cultures, where academic
pressure is put on the students by their parents and
schools. The time spent in sedentary educational activi-
ties increased steeply after 3 years of follow-up in both
boys and girls, corresponding to the time when students
are preparing for junior high school graduation exams,
followed by entry into high school. During this time,
students often spend more time on extracurricular tutor-
ing in addition to homework, including evening classes in
private institutions and private classes preparing students
for the fınal junior high school examination.
In the present study, time spent hanging out chatting
with friends increased substantially and is also an impor-
tant sedentary leisure-time activity for Vietnamese ado-
lescents. During adolescence, teenagers begin to spend
increasingly more time away from their parents and are
more exposed to schools, peers, and other socialization
agents. Time spent hanging out and socializing therefore
increased correspondingly.

46
Consistent with other studies,
37,44,47,48
boys reported
higher screen time than girls. This may be because girls
take part in more activities other than screen time, such as
housework and extracurricular cultural activities. In
Vietnamese culture, girls are expected to help their moth-
ers with household activities, especially cooking, prepar-
ing the table for dinner, and cleaning; boys may follow
their fathers’ behavioral patterns, which allow for more
screen time.
In the present study, older children were more likely to
have 2 or more hours of daily screen time as well as total
sedentary time. These fındings are in agreement with
other studies that focused on screen time.
13,49,50
The
present study showed that screen time was higher among
0
100
200
300
400
500
600
700
2004/2005 2005/2006 2006/2007 2007/2008 2008/2009
Other leisure time
Afterschool

educational time
Screen time
Minutes/day
Boys
Boys
Boys Boys BoysGirls Girls Girls Girls Girls
Figure 1. Median (minutes/day) self-reported screen time,
afterschool educational time, and other leisure sedentary
time
Trang et al / Am J Prev Med 2013;44(3):223–230 227
March 2013
high-SES adolescents, especially girls, which is in contrast
to that reported among developed countries wherehigher
SES is associated with lower screen time.
51
Similarly, this study also found a negative association
between total nonschool sedentary time and SES,which is
also in contrast with fındings reported by developed
countries.
52–54
Various explanations are possible for the
higher rates of screen time and total sedentary time
among higher-SES adolescents. Higher-SES families may
have greater access to sedentary technologies, their chil-
dren might be more likely to engage in study outside
school hours, and their children might be more likely to
spend time helping with housework.
No association was found between screen time or total
nonschool sedentary behavior and physical activity. This
fınding supports results of a recent review of the corre-

lates of physical activity in children and adolescents,
10
which concluded that there was no relationship between
TV/video games and physical activity among those aged
13–18 years. Similarly, sedentary time and physical activ-
ity have been suggested as being independent behaviors
in school children.
18
Strengths and Limitations
The strength of this study was its longitudinal design with
repeated measures and a good retention rate over the
5-year period (77%). The prospective cohort study design
allowed examination of changes in a large variety of sed-
entary behaviors and relevant sociodemographic factors
during adolescence. Another strength of the study was
the use of accelerometers to objectively measure seden-
tary time. In contrast to self-report, accelerometers pro-
vide very precise information on movement patterns;
Table 3. Correlates of total sedentary behavior (minutes/day) by gender, mean change (95% CI)
Boys Girls
Univariate Adjusted
a
Univariate Adjusted
a
ADOLESCENT SEDENTARY ACTIVITY QUESTIONNAIRE
Year of follow-up (ref: Year 1—baseline)
2 30 (16, 61) 30 (16, 61) 27 (12, 53) 27 (12, 53)
3 70 (35, 106) 70 (35, 106) 66 (39, 110) 66 (39, 110)
4 118 (96, 153) 118 (96, 153) 113 (79, 158) 113 (79, 158)
5 121 (98, 160) 121 (98, 160) 115 (96, 163) 115 (96, 163)

Pubertal status (ref: prepubescent)
Postpubescent 45 (10, 59) — 66 (27, 106) —
Maternal education (ref: did not complete junior high school)
Did not complete high school — — 55 (18, 90) —
High school or higher — — 50 (19, 71) —
SES quartile (ref: 1st—the poorest)
2nd 35 (15, 84) — 72 (32, 119) 69 (31, 109)
3rd 39 (16, 85) — 81 (36, 116) 76 (35, 114)
4th 45 (11, 92) — 97 (48, 125) 90 (52, 128)
ACCELEROMETER
Year of follow-up (ref: Year 2)
3 21 (12, 47) 21 (12, 47) 37 (13, 60) 37 (13, 60)
4 65 (43, 88) 65 (43, 88) 58 (28, 78) 58 (28, 78)
5 78 (48, 104) 78 (48, 104) 69 (34, 95) 69 (34, 95)
Pubertal status (ref: prepubescent)
Postpubescent 37 (16, 58) — 39 (12, 66) —
Note: SES is based on household wealth index.
a
Adjusted for pubertal status, maternal education, SES, and wearing time (from accelerometry data)
228 Trang et al / Am J Prev Med 2013;44(3):223–230
www.ajpmonline.org
however, because accelerometers provide no contextual
information, both methods are required.
The fındings showed that irrespective of the mea-
surement instrument, sedentary behavior among Viet-
namese adolescents has increased over time. The study
design, a multistage cluster, random sampling of urban
adolescents from Ho Chi Minh City, provides strong
external validity of the results. Thus, the results are
likely to be representative of other adolescent popula-

tions in large cities in Vietnam and possibly other
South East Asian cities, which are going through rapid
economic transition.
One of the limitations is the substantial amount of
missing accelerometer data, especially in the later survey
years. The main reason for the missing data was that
many of the participating adolescents did not comply
with wearing instructions. This lack of compliance may
have led to an underestimation of sedentary time mea-
sured by the accelerometer.
Similarly, given the large number of prompts in the
questionnaire for various kinds of sedentary behavior, it
seems that total sedentary time might have been overes-
timated by the questionnaire. This also would help ex-
plain partly the discrepancy between the accelerometer
and questionnaire. However, there is no indication sug-
gesting that such overestimation of sedentary time would
be different across age categories. Accelerometer results
also suggested an increase in sedentary time with age,
although a smaller increase than those reported in the
questionnaire.
Conclusion
The present study showed an increase in daily nonschool
sedentary behavior among Vietnamese youth as they
progress through adolescence. Information on correlates
given can be used to plan evidence-based strategies that
are age-tailored and targeted to differences between gen-
ders, and to high-risk groups, such as students in high-
SES families. Strategies to reduce excessive educational
sitting include more active classes that incorporate stand-

ing time into the educational process, an increase in re-
cess and break times,
55,56
and active homework.
57
Other
promising strategies include encouraging adolescents to
switch from passive to active screen time,
58,59
and to
exchange sitting and chatting during leisure time with
walking and chatting.
Decreasing sedentary behavior has an important
role in prevention strategies aimed at tackling emerg-
ing obesity and chronic diseases in Vietnamese adoles-
cents. Intervention strategies in Ho Chi Minh City will
need to have multidisciplinary approaches and sup-
port from a range of communication channels to in-
crease awareness of the positive effects of decreasing
sedentary time for both adolescents and their parents.
The survey was funded by a grant from the Nestlé Foundation,
Switzerland. Nguyen H.H.D. Trang got the partial PhD schol-
arship (The University of Sydney World Scholars and the Hoc
Mai Foundation).
No fınancial disclosures were reported by the authors of this
paper.
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