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African Journal for Physical, Health Education, Recreation and
Dance (AJPHERD), Volume 19(2), June 2013, pp. 448-458. Overweight
and obesity and associated factors among school-aged adolescents in
Thailand SUPA PENGPID1,2 AND KARL PELTZER1,2,3 1ASEAN Institute for
Health Development, Madidol University, Salaya, Phutthamonthon,
Nakhonpathom, Thailand, 73170 2University of Limpopo, Turfloop
Campus, Private Bag X1106, Sovenga 0727, South Africa
3HIV/AIDS/SIT/and TB (HAST), Human Sciences Research Council,
Private Bag X41, Pretoria 0001, South Africa; E-Mail:
[email protected] (Received: 18 November 2012 ; Revision
Accepted: 11 February 2013 ) Abstract The aim of this study was to
assess overweight and obesity and associated factors in
school-going adolescents in Thailand. Using data from the Thailand
Global School-Based Student Health Survey (GSHS) 2008, we assessed
the prevalence of overweight and obesity and its associated factors
among adolescents (N=2758). Bivariate and multivariate analyses
were applied to assess the relationship between dietary behaviour,
substance use, physical activity, psychosocial factors, overweight
and obesity. The prevalence of overweight and obesity was
determined based on self-reported height and weight and the
international child body mass index standards. Results indicate an
overall prevalence of overweight and obesity of 10.0% and 4.4%,
respectively, overweight 12.7% among boys and 7.6% among girls, and
obesity 5.0% and 3.9% among girls and boys, respectively. Among
boys younger age (12 years and younger), being physically inactive,
sedentary behaviour and no history of illicit drug use were
associated with obesity using bivariate and multivariate analysis,
and among girls none of the variables (dietary behaviour, substance
use, physical activity and psychosocial factors) was found to be
associated with obesity. Moderate prevalence rates of overweight or
obesity were found among adolescents in Thailand. Increasing
physical activity participation should be the focus of strategies
aimed at preventing and treating overweight and obesity in male
youth. Keywords: Overweight, obesity, global school-based health
survey, dietary behaviour, substance use, physical activity,
sedentary behaviour, psychosocial factors, Thailand. How to cite
this article: Pengpid, S. & Peltzer, K. (2013). Overweight and
obesity and associated factors among school-aged adolescents in
Thailand. African Journal for Physical, Health Education,
Recreation and Dance, 19(2), 448-458. Introduction The prevalence
of overweight and obesity in children has increased worldwide
during the past 20 years (de Onis & Lobstein, 2010). Obesity in
childhood and adolescence has been found to be associated with
premature mortality and physical morbidity (In-Iw & Biro, 2011;
Reilly & Kelly, 2011) as well as impaired health during
childhood itself including an increase in the prevalence of type 2
diabetes mellitus and metabolic syndrome among children in Thailand
(Panamonta, Thamsiri
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Overweight and obesity among school-aged adolescents 449 &
Panamonta, 2010; Reilly & Kelly, 2011). Once obesity is
established in children (as in adults) it is hard to reverse (de
Onis & Lobstein, 2010). Monitoring the prevalence of obesity in
order to plan services for the provision of care and to access the
impact of policy initiatives is essential (de Onis & Lobstein,
2010). A number of local studies in Thailand found increases and
moderate rates of overweight and obesity among adolescents and
adults. Aekplakorn and Mo-Suwan (2009) note significant increases
in the prevalence of obesity in adults: from 13.0% in men and 23.2%
in women in 1991 to 18.6% and 29.5% in 1997 and 22.4% and 34.3% in
2004 respectively. Obesity prevalence in children increased from
5.8% in 1997 to 7.9% in 2001 for the 2-5-year-olds and from 5.8% to
6.7% for the 6-12-year-olds (Aekplakorn & Mo-Suwann, 2009). The
prevalence of overweight and obesity among school children in
suburb Thailand was 12.8% and 9.4% (Rerksuppaphol &
Rerksuppaphol, 2010), 12.6% among grade 7-12 who attended two
metropolitan Bangkok schools (In-Iw, Manaboriboon, & Chomchai,
2010), 27.6% overweight school children (aged 10-15 years) in Khon
Kaen province (Panamonta et al., 2010), 18.4% among girls (11-17
years) overweight or obese in suburban Thailand (Pawloski, Ruchiwit
& Pakapong, 2008), and overall 4.9% obese and 9.5% overweight
(4.8% obesity and 9.4% overweight among boys and 4.9% obesity and
9.9% overweight among girls) among 12- to 18-years-olds attending
the secondary school in the municipality of Khon Kaen
(Sengmeuangpa, Kukongviriyapana, Pasurivonga, Jonesb &
Khrisanapanta, 2010). Although differences exist between urban and
rural men, the odds of being overweight or obese were similar in
urban and rural women (Aekplakorn, Hogan, Chongsuvivatwong,
Tatsanavivat, Chariyalertsak & Boonthum, 2007). Studies found
that factors associated with childhood overweight or obesity
include lower physical activity levels (Janssen, Katzmarzyk, Boyce,
King, & Pickett, 2004a; Janssen et al. 2005), higher sedentary
behaviour (such as television viewing times) (Janssen et al.,
2004a; Collins, Pakiz, & Rock, 2008), dietary behaviour such as
frequency of sweets intake (Janssen et al., 2005), psychosocial
factors (Vmosi, Heitmann & Kyvik, 2010; Spruijt-Metz, 2011)
female gender (Kimani-Murage, Kahn, Pettifor, Tollman,
Klipstein-Grobusch, & Norris, 2011), victims and perpetrators
of bullying behaviours (Janssen, Craig, Boyce & Pickett,
2004b), inaccurate perceptions of the need to diet, poorer
self-perceived health status and potential social isolation
(Pawloski, Kitsantas, & Ruchiwit, 2010), and poorer self-image
(In-Iw et al., 2010). Overweight status has not been found to be
associated with the intake of fruits and vegetables (Janssen et
al., 2005; Pawloski et al., 2010). Risk factors such as dietary
behaviour, life style factors (substance use), physical activity
and psychosocial factors for obesity in low-income countries are
not well-known and might differ from those in other countries.
Therefore, the aim of this study was to assess overweight and
obesity and associated factors in school-going adolescents in an
Asian low income country (Thailand).
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450 Pengpid and Peltzer Methodology Participants and procedures
The study involved the secondary analysis of existing data from the
2008 Thailand Global School-Based Health Survey (GSHS) (Centers for
Disease Control, 2009). The aim of the GSHS is to collect data from
students of age 13 to 15 years. The Thailand GSHS was a
school-based survey of students in Grades 7, 8, 9, and 10. A
two-stage cluster sample design was used to collect data to
represent all students in Grades 7, 8, 9, and 10 in the country. At
the first stage of sampling, schools were selected with probability
proportional to their reported enrollment size. In the second
stage, classes in the selected schools were randomly selected and
all students in selected classes were eligible to participate
irrespective of their actual ages. The school response rate was
100%, the student response rate was 93%, and the overall response
rate was 93%. Students self-completed the questionnaires to record
their responses to each question on a computer scan able answer
sheet. A total of 2,767 students participated in the Thailand GSHS
(Ministry of Public Health, 2008). The GSHS 10 core questionnaire
modules address the leading causes of morbidity and mortality among
children and adults worldwide: tobacco, alcohol and other drug use;
dietary behaviors; hygiene; mental health; physical activity;
sexual behaviors that contribute to HIV infection, other sexually
transmitted infections, and unintended pregnancy; unintentional
injuries and violence; protective factors and respondent
demographics (Centers for Disease Control, 2009; Ministry of Public
Health Thailand, 2008). Measures Body Mass Index (BMI) measurement
and overweight classification Height and body weight were based on
self-reports. BMI was calculated as weight/height2 (kg/m2). The
international age- and gender-specific child BMI cut-points were
used to define underweight, overweight and obesity (Cole, Bellizzi,
Flegal & Dietz, 2000). These cut-points were derived from a
large international sample using regression techniques by passing a
line through the health-related adult cut-points at 18 years. Youth
with BMI values corresponding to an adult BMI of < 25.0 kg/m2
were classified as normal weight and youth with BMI values
corresponding to an adult BMI of 25.0 kg/m2 were classified as
overweight. Thus, in this study overweight youth included those who
were obese. The overweight youth was further subdivided into
pre-obese (BMI corresponds to adult values of 25.029.9 kg/m2) and
obese (BMI is corresponding to an adult value of 30.0 kg/m2)
groups. The response rate on the BMI was for Thailand 97%.
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Overweight and obesity among school-aged adolescents 451 Fruits
and vegetables consumption and hunger Fruits: During the past 30
days, how many times per day did you usually eat fruit, such as
country specific examples? Response options were 1 = I did not eat
fruit during the past 30 days, 2 = less than one time per day, 3 =
1 time per day to 7 = 5 or more times per day. Vegetables: During
the past 30 days, how many times per day did you usually eat
vegetables, such as country specific examples? Response options
were 1 = I did not eat vegetables during the past 30 days, 2 = less
than one time per day, 3 = 1 time per day to 7 = 5 or more times
per day. Adolescents indicated that they were consuming fruits (or
vegetables) less than once a day was coded as having inadequate
consumption patterns. The inadequate fruits and vegetables
consumption variables were re-coded separately into two categories:
inadequate fruits consumption (less than once = 1) and adequate
fruits consumption (once or more a day = 0) and inadequate
vegetable consumption (less than once = 1) and adequate vegetable
consumption (once or more a day = 0). Hunger: A measure of hunger
was derived from a question reporting the frequency that a young
person went hungry because there was not enough food at home in the
past 30 days (response options were from 1 = never to 5 = always)
(coded 1 = most of the time or always and 0 = never, rarely or
sometimes). Substance use variables: Smoking cigarettes (current
smoking) was assessed with the question, During the past 30 days,
on how many days did you smoke cigarettes? Response options
included 1=0 days to 7=all 30 days. Alcohol use was assessed with
the question, During the past 30 days, on how many days did you
have at least one drink containing alcohol? Response options
included 1=0 days to 7=all 30 days. Drug use: During your life, how
many times have you used drugs, such as methamphetamines (Yaba),
ecstasy, 4x100, or marijuana? (ever drugs). Physical Activity.
Leisure time physical activity was assessed by asking participants:
"During the past 7 days, on how many days were you physically
active for a total of at least 60 minutes per day?" and "During a
typical or usual week, on how many days are you physically active
for a total of at least 60 minutes per day?" Physical activity was
defined as any activity that increases heart rate and makes one get
out of breath some of the time. Physical activity can be done in
sports, playing with friends, or walking to school. Some examples
of physical activity are running, fast walking, biking, dancing,
and football. Physical education or gym classes were not supposed
to be included. According to the scoring protocol of the
PACE+Adolescent Physical Activity Measure, physical activity was
defined as obtaining at least 60 min of physical activity per day
on at least five days per week. For analysis, the number of active
days "during the past week" and the number of active days "during a
typical week" were averaged.
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452 Pengpid and Peltzer Leisure time sedentary behaviour was
assessed by asking participants about the time they spend mostly
sitting when not in school or doing homework: How much time do you
spend during a typical or usual day sitting and watching
television, playing computer games, talking with friends, or doing
other sitting activities (3 hours of more per day). Psychosocial
distress variables. Loneliness During the past 12 months, how often
have you felt lonely? (Response options were from 1 = never to 5 =
always) (Coded 1 = most of the time or always and 0 = never, rarely
or sometimes). Anxiety or worried. During the past 12 months, how
often have you been so worried about something that you could not
sleep at night? (Response options were from 1 = never to 5 =
always) (Coded 1 = most of the time or always and 0 = never, rarely
or sometimes). Sadness. During the past 12 months, did you ever
feel so sad or hopeless almost every day for 2 weeks or more in a
row that you stopped doing your usual activities? (Response option
1 = yes and 2 = no) (Coded 1 = 1, 2 = 0). Suicide plan. During the
past 12 months, did you make a plan about how you would attempt
suicide? (Response option was 1 = yes and 2 = no, coded 1 = 1, 2 =
0). Bullied: The variable ever being bullied was defined as those
who reported they were bullied at least once in the preceding 30
days, by any form of bullying. Data analysis Data analysis was
performed using STATA software version 10.0 (Stata Corporation,
College Station, TX, USA). This software has the advantage of
directly including robust standard errors that account for the
sampling design, i.e. cluster sampling owing to the sampling of
school classes. Psychosocial distress was assessed across the 4
mental health measures when a students response was indicative of
distress: loneliness, anxiety or worried, sadness and suicide plan.
The number of psychosocial distress indicators was calculated by
determining if students had 0, 1, 2-4 indicators. Associations
between dietary behavior and substance use, physical activity and
psychosocial distress and overweight or obesity among school
children were evaluated calculating odds ratios (OR). Unconditional
logistic regression was used for evaluation of the impact of
explanatory variables for overweight or obesity for boys and girls
(binary dependent variables). All variables statistically
significant at the P < .05 levels in bivariate analyses were
included in the multivariable models. In the analysis, weighted
percentages are reported. The reported sample size refers to the
sample that was asked the target question. The two-sided 95%
confidence intervals are reported. The P values less or equal to 5%
is used to indicate statistical significance. Both the reported 95%
confidence intervals and the P value are adjusted for the
multi-stage stratified cluster sample design of the study.
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Overweight and obesity among school-aged adolescents 453 Results
Sample characteristics Table 1 gives the sample characteristics of
2758 participants, mainly between 12 to 15 years old and 53.2%
females and 46.8% males. The study found an overall prevalence of
overweight and obesity of 10.0% and 4.4%, respectively, overweight
12.7% among boys and 7.6% among girls, and obesity 5.0% and 3.9%
among girls and boys, respectively. In terms of dietary behavior,
more boys as opposed to girls had fruits or vegetables less than
once a day, and 3.4% indicated that mostly or always they felt
hungry. More than three quarters of students indicated physical
inactivity, almost half that they would not walk to school and more
than one quarter engaged in three or more hours sedentary behaviour
per day. Regarding psychosocial factors, being bullied was the most
frequent one, followed by sadness, having a suicide plan and having
no close friends; females scored significantly higher than boys on
no close friends, suicide plan and anxiety (Table 1). Table 1:
Sample characteristics among adolescents in Thailand, 2008, N=2758
Total
N (%) Males N (%)
Females N (%)
Age (years) 12 13 14 15
466 (17.0) 840 (29.5) 870 (28.7) 582 (24.9)
201 (15.6) 407 (30.9) 443 (30.3) 313 (23.2)
265 (18.2) 433 (28.1) 427 (27.2) 269 (26.5)
Gender Female Male
1394 (53.2) 1364 (46.8)
Hunger 94 (3.4) 63 (4.7) 31 (2.1) Weight Overweight Obese
269 (10.0) 118 (4.4)
164 (12.7) 67 (5.0)
105 (7.6) 51 (3.9)
Dietary behaviour Fruits less than once a day Vegetables less
than once a day Most of the time or always hunger
638 (23.2) 358 (12.8) 94 (3.4)
373 (27.1) 195 (14.0) 63 (4.7)
265 (19.6) 163 (11.7) 31 (2.1)
Substance use Current smoking Current alcohol use Lifetime
illicit drug use
220 (8.2) 368 (14.8) 167 (6.0)
190 (15.0) 247 (21.2) 147 (11.1)
30 (2.2) 121 (9.3) 20 (1.3)
Physical activity Physical activity less than 60 min per day on
at least five days per week
2073 (76.3) 914 (67.5) 1159 (84.6)
Sedentary behavior (3 hours of more per day) 1039 (37.5) 518
(37.4) 521 (37.7) Psychosocial factors Psychosocial distress 0 1939
(73.4) 935 (73.3) 1004 (73.4) 1 445 (16.9) 239 (16.6) 206 (17.3)
2-4 257 (9.7) 128 (10.1) 129 (9.3) Being bullied 679 (27.8) 383
(32.9) 296 (23.2)
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454 Pengpid and Peltzer Association with overweight or obesity
Among boys younger age, being physically inactive, sedentary
behaviour and no history of illicit drug use were associated with
obesity in bivariate and multivariable analysis, and among girls
none of the study variables (dietary behaviour, substance use,
physical activity and psychosocial factors) were found to be
associated with obesity (Table 2). Table 2: Bivariate and
multivariable logistic regression analysis of factors that are
associated with obesity among adolescents in Thailand, 2008
Variables Male Female OR1 (95% CI) AOR2 (95% CI) OR1 (95% CI) Age
12 years 13 14 15 years
1.00 0.27 (0.12-0.58)** 0.46 (0.21-1.01) 0.27 (0.11-0.64)**
1.00 0.25 (0.11-0.53)*** 0.42 (0.19-0.95)* 0.23
(0.09-0.57)**
1.00 0.76 (0.28-2.08) 0.93 (0.44-1.96) 1.37 (0.74-2.52)
Dietary behaviour and substance use
Fruits less than once a day
1.11 (0.62-1.99) --- 1.02 (0.29-3.54)
Vegetables less than once a day
0.58 (0.16-2.22) --- 0.23 (0.04-1.40)
Most of the time or always hunger
1.02 (0.23-4.40) --- 0.79 (0.08-7.87)
Substance use Current alcohol use 0.73 (0.36-1.46) --- 0.91
(0.27-3.01) Current smoking 0.83 (0.45-1.54) --- --- Ever illicit
drug use 0.23 (0.06-0.93)* 0.20 (0.05-0.80)* --- Physical activity
Physical activity less than 60 min per day on at least five days
per week
2.12 (1.25-3.58)** 2.26 (1.38-3.71)** 0.83 (0.34-2.04)
Sedentary behaviour (3 hours of more per day)
1.74 (1.08-2.79)* 1.75 (1.09-2.81)* 0.97 (0.53-1.79)
Psychosocial factors Psychosocial distress 0 1.00 --- 1.00 1
1.42 (0.63-3.21) 1.06 (0.36-3.13) 2-4 1.13 (0.47-2.72) 1.07
(0.26-4.43) Being bullied 1.33 (0.85-2.08) --- 1.75 (0.93-3.29) 1
OR=Odds Ratio; 2 AOR=Adjusted Odds Ratio. ***P
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Overweight and obesity among school-aged adolescents 455 2008;
Rerksuppaphol & Rerksuppaphol, 2010; Sengmeuangpa et al.,
2010). This study did not find significant gender differences
between male and female adolescents regarding body weight, which is
conformed to other studies in Thailand (Rerksuppaphol &
Rerksuppaphol, 2010). Further the study found that among boys
younger age, being physically inactive, sedentary behaviour and no
history of illicit drug use were associated with obesity, and among
girls none of the study variables (dietary behaviour, substance
use, physical activity and psychosocial factors) were found to be
associated with obesity. In a study among 12 to 18 year-olds in
Thailand the prevalence did also not increase with age
(Sengmeuangpa et al., 2010). The effect of physical inactivity and
sedentary behaviour in this study among boys is conforming to a
number of other studies (Janssen et al., 2004b; Haug et al., 2009;
Sirikulchayanonta et al., 2011). Overweight status was in this
study also not associated with the intake of fruits, vegetables, as
found in other studies (Janssen et al., 2005; Spruijt-Metz, 2011;
Pawloski et al., 2010). Further, the study found that being most of
the time or always hungry was not associated with overweight. In a
review of studies on food insecurity related to overweight and
obesity in children and adolescents in the USA, Eisenmann,
Gundersen, Lohman Garasky and Stewart (2011) found no associations
between food insecurity and overweight among more recent studies
with larger samples and that food insecurity and overweight
co-exist. We studied health-risk behaviours that could influence
energy metabolism such as alcohol and tobacco use (Dupuy, Godeau,
Vignes & Ahluwalia, 2011). Substance use (illicit drug use
among boys) was in this study significantly inversely associated
with overweight or obesity, which needs further investigation.
Study limitations This study had several limitations. Firstly, the
GSHS only enrolls adolescents who are in school. School-going
adolescents may not be representative of all adolescents in a
country as the occurrence of obesity may differ between the two
groups. Also we did not assess regional and urban-rural differences
in obesity. Furthermore, this study was based on data collected in
a cross-sectional survey. We cannot, therefore, ascribe causality
to any of the associated factors in the study. The cut-offs used
with self-reported BMI may lead to underestimation or overweight
and obesity (Elgar, Roberts, Tudor-Smith, & Moore, 2005). The
BMI was assessed by self-reported weight and height and could have
included anthropometry to evaluate weight status and body fat
content. In addition, a number of factors known to be associated
with weight status were not assessed including dietary intake, low
quality diet, skipping breakfast, environmental,
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456 Pengpid and Peltzer family variables including parental
weight status, socioeconomic status (Goyal et al., 2010; Lieb, Snow
& DeBoer, 2009; Spruijt-Metz, 2011), age at menarche and order
of birth (Pawloski et al., 2008; Pawloski et al., 2010),
dissatisfaction with body weight (In-Iw et al., 2010) and
self-discipline (Sirikulchayanonta, Ratanopas, Temcharoen &
Srisorrachatr, 2011). Conclusions Moderate prevalence rates of
overweight or obesity were found among adolescents in Thailand.
Increasing physical activity participation should be the focus of
strategies aimed at preventing and treating overweight and obesity
in male youth. Acknowledgements We are grateful to the World Health
Organisation (Geneva) for making the data available to us for
analysis. We also thank the Ministries of Education and Health and
the study participants for making the Thailand Global School Health
Survey 2008 possible, and the country survey coordinator, Dr.
Pensri Kramomtong, Chief Department of Health, Ministry of Public
Health. The government of Thailand and the World Health
Organization did not influence the analysis, nor did they have
influence on decision to publish these findings. References
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