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: Kpeltzer@hsrc.ac.za (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

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).

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%.

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.

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.

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)

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

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,

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 Aekplakorn, W., Hogan, M. C., Chongsuvivatwong, V., Tatsanavivat, P., Chariyalertsak, S. & Boonthum, A. (2007). Trends in obesity and associations with education and urban or rural residence in Thailand. Obesity, 15(12), 3113-3121. Aekplakorn, W. & Mo-Suwan, L. (2009). Prevalence of obesity in Thailand. Obesity Reviews, 10(6), 589-92. Cole, T. J., Bellizzi, M. C., Flegal, K. M., & Dietz, W. H. (2000). Establishing a standard definition for child overweight and obesity worldwide: international survey. British Medical Journal, 320 (7244), 1240-1243. Collins, A. E., Pakiz, B. & Rock, C. L. (2008). Factors associated with obesity in Indonesian adolescents. International Journal of Pediatric Obesity, 3(1), 58-64. Centers for Disease Control (CDC) (2009). The Global School and Health Survey background [Online]. Available at http://www.cdc.gov/gshs/background/index, 2009. de Onis, M. & Lobstein, T. (2010). Defining obesity risk status in the general childhood population: which cut-offs should we use? International Journal of Pediatric Obesity, 5(6), 458-560.

Overweight and obesity among school-aged adolescents 457 Dupuy, M., Godeau, E., Vignes, C. & Ahluwalia, N. (2011). Socio-demographic and lifestyle factors associated with overweight in a representative sample of 11-15 year olds in France: results from the WHO-Collaborative Health Behaviour in School-aged Children (HBSC) cross-sectional study. BMC Public Health, 11, 442. Elgar, F.J., Roberts, C., Tudor-Smith, C. & Moore, L. (2005). Validity of self-reported height and weight and predictors of bias in adolescents. Journal of Adolescent Health, 37(5), 371-375. Eisenmann, J. C., Gundersen, C., Lohman, B. J., Garasky, S. & Stewart, S. D. (2011). Is food insecurity related to overweight and obesity in children and adolescents? A summary of studies, 1995-2009. Obesity Reviews, 12(5), e73-83. Goyal, R. K., Shah, V. N., Saboo, B. D., Phatak, S. R., Shah, N. N., Gohel, M. C., Raval, P. B. & Patel, S. S. (2010). Prevalence of overweight and obesity in Indian adolescent school going children: its relationship with socioeconomic status and associated lifestyle factors. Journal of the Association of Physicians in India, 58, 151-158. Haug, E., Rasmussen, M., Samdal, O., Iannotti, R., Kelly, C., Borraccino, A., HBSC Obesity Writing Group (2009). Overweight in school-aged children and its relationship with demographic and lifestyle factors: results from the WHO-Collaborative Health Behaviour in School-aged Children (HBSC) study. International Journal of Public Health, 54(Suppl 2), 167-179. In-Iw, S. & Biro, F. M. (2011). Adolescent women and obesity. Journal of Pediatric and Adolescent Gynecology, 24(2), 58-61. In-Iw, S., Manaboriboon, B. & Chomchai, C. A. (2010). Comparison of body-image perception, health outlook and eating behavior in mildly obese versus moderately-to-severely obese adolescents. Journal of the Medical Association of Thailand, 93(4), 429-345. Janssen, I., Katzmarzyk, P. T., Boyce, W. F., King, M. A. & Pickett, W. (2004a). Overweight and obesity in Canadian adolescents and their associations with dietary habits and physical activity patterns. Journal of Adolescent Health, 35(5), 360-367. Janssen, I., Craig, W. M., Boyce, W. F. & Pickett, W. (2004b). Associations between overweight and obesity with bullying behaviors in school-aged children. Pediatrics, 113(5), 1187-1194. Janssen, I., Katzmarzyk, P.T, Boyce, W. F., Vereecken, C., Mulvihill, C., Roberts, C., et al. (Health Behaviour in School-Aged Children Obesity Working Group) (2005). Comparison of overweight and obesity prevalence in school-aged youth from 34 countries and their relationships with physical activity and dietary patterns. Obesity Review, 6(2), 123-132. Kimani-Murage, E. W., Kahn, K., Pettifor, J. M., Tollman, S. M., Klipstein-Grobusch, K. & Norris, S. A. (2011). Predictors of adolescent weight status and central obesity in rural South Africa. Public Health Nutrition, 14(6), 1114-1122. Lieb, D. C., Snow, R. E. & DeBoer, M. D. (2009). Socioeconomic factors in the development of childhood obesity and diabetes. Clinical Sports Medicine, 28(3), 349-378. Ministry of Public Health Thailand (2008). The Global School-Based Student Health Survey (GSHS) in Thailand. Bangkok, Thailand: Ministry of Public Health Thailand.

458 Pengpid and Peltzer Panamonta, O., Thamsiri, N. & Panamonta, M. (2010). Prevalence of type II diabetes and metabolic syndrome among overweight school children in Khon Kaen, Thailand. Journal of the Medical Association of Thailand, 93(1), 56-60. Pawloski, L. R., Ruchiwit, M. & Pakapong, Y. (2008). A cross-sectional examination of growth indicators from Thai adolescent girls: evidence of obesity among Thai youth? Annals of Human Biology, 35(4), 378-385. Pawloski, L. R., Kitsantas, P. & Ruchiwit, M. (2010). Determinants of overweight and obesity in Thai adolescent girls. International Journal of Medicine, 3(2), 352-356. Rerksuppaphol, S. & Rerksuppaphol, L. (2010). Prevalence of overweight and obesity among school children in suburb Thailand defined by the International Obesity Task Force standard. Journal of the Medical Association of Thailand, 93(Suppl 2), S27-S31. Reilly, J. J. & Kelly, J. (2011). Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. International Journal of Obesity, 35(7), 891-898. Sengmeuanga, P., Kukongviriyapana, U., Pasurivonga, O., Jonesb, C. & Khrisanapanta, W. (2010). Prevalence of obesity among Thai schoolchildren: a survey in Khon Kaen, Northeast Thailand. Asian Biomedicine, 4(6), 965-970. Sirikulchayanonta, C., Ratanopas, W., Temcharoen, P. & Srisorrachatr, S. (2011). Self-discipline and obesity in Bangkok school children. BMC Public Health, 11, 158. Spruijt-Metz, D. (2011). Etiology, treatment and prevention of obesity in childhood and adolescence: A decade in review. Journal of Research in Adolescents, 21(1), 129-152. Vmosi, M., Heitmann, B. L. & Kyvik, K. O. (2010). The relation between an adverse psychological and social environment in childhood and the development of adult obesity: a systematic literature review. Obesity Review, 11(3), 177-184.

Copyright of African Journal for Physical, Health Education, Recreation & Dance is theproperty of African Journal for Physical, Health Education, Recreation & Dance and itscontent may not be copied or emailed to multiple sites or posted to a listserv without thecopyright holder's express written permission. However, users may print, download, or emailarticles for individual use.

65075 - Ajpherd - Vol. 19(2) June 2013 21265075 - Ajpherd - Vol. 19(2) June 2013 21365075 - Ajpherd - Vol. 19(2) June 2013 21465075 - Ajpherd - Vol. 19(2) June 2013 21565075 - Ajpherd - Vol. 19(2) June 2013 21665075 - Ajpherd - Vol. 19(2) June 2013 21765075 - Ajpherd - Vol. 19(2) June 2013 21865075 - Ajpherd - Vol. 19(2) June 2013 21965075 - Ajpherd - Vol. 19(2) June 2013 22065075 - Ajpherd - Vol. 19(2) June 2013 22165075 - Ajpherd - Vol. 19(2) June 2013 222