ARTICLE ORIGINAL / ORIGINAL ARTICLE

PUBLIC SCHOOLS ADOLESCENTS’ OBESITY AND GROWTH CURVES IN LEBANON http://www.lebanesemedicaljournal.org/articles/59-2/original5.pdf

Hilda R. CHACAR1, Pascale SALAMEH2

Chacar HR, Salameh P. Public schools adolescents’ obesity and growth curves in Lebanon. J Med Liban 2011 ; 59 (2) : 80-88.

ABSTRACT • OBJECTIVE : Our objective was to draw growth curves and assess obesity prevalence in adolescents of public schools, and to explore selected food consumption frequency and physical activity. METHODS : A cross-sectional study was conducted in Lebanese public schools. From the list of schools provided by the Ministry of Education, a random sample of 20 schools was chosen, distributed in all Lebanese regions. Participants were 2547 adolescents, aged between 11 to 18 years. Anthropometric measures of height and weight were taken, growth curves were drawn. Obesity and at risk of obesity prevalences were also calculated. Selected food intake frequency, physical activity and sedentary behavior were also analyzed. RESULTS : Growth curves were drawn for boys and girls. Overall, 6.6% of adolescents were obese, while 20.5% were at risk of obesity. There were significant differences in obesity prevalence estimates between age groups in girls : increased age was associated with higher obesity (3.8% in those ≤ 13 years of age versus 10.6%in those > 17 y ; p = 0.02) ; this trend was not found in boys (6.5% in those ≤ 13 y and 7.2% in those > 17y ; p = 0.78). As expected, a significant increase in the risk of being overweight was found with increased frequency of eating fried potatoes, chocolate and eating out. In contrast, eating fruits and having physical activity were associated with a lower risk of being overweight. CONCLUSION : In Lebanese public schools, we found high rates of obesity and associated behaviors. Preventing obesity should focus on promoting healthy lifestyles for adolescents of low socioeconomic status. INTRODUCTION

Obesity and risk of obesity have become epidemic in childhood and adolescence, in developing [1] and in developed countries [2-3]. In Lebanon, the prevalence of overweight, including obesity, has been established in some portions of the population [4]. A cross-sectional survey of a sample of 2104 children (3-19 years of age) and adults, showed overall higher prevalence rates of at

Chacar HR, Salameh P. Obésité et courbes de croissance chez les adolescents des écoles publiques au Liban. J Med Liban 2011 ; 59 (2) : 80-88.

RÉSUMÉ • OBJECTIFS : Nos objectifs étaient de tracer les courbes de croissance et d’évaluer l’obésité des adolescents dans les écoles publiques libanaises, en plus de l’exploration de la fréquence de leur consommation de quelques aliments et de leur activité physique. MÉTHODES : Une étude transversale a été menée dans les écoles publiques libanaises. De la liste des écoles pourvue par le ministère de l’Education, un échantillon aléatoire de 20 écoles a été choisi, distribuées dans toutes les régions libanaises. Les participants étaient 2547 adolescents, âgés de 11 à 18 ans. Des mesures anthropométriques de taille et de poids ont été prises, et les courbes de croissance ont été tracées. Les prévalences du risque d’obésité et de l’obésité ont aussi été calculées. La fréquence de quelques aliments, l’activité physique et la sédentarité étaient aussi évaluées. RÉSULTATS : Les courbes de croissance ont été tracées pour les garçons et les filles. 6,6% des adolescents étaient obèses, et 20,5% à risque d’obésité. Des différences significatives ont été retrouvées entre les groupes d’âge chez les filles : un âge plus avancé est associé à une obésité plus élevée (3,8% chez celles ≤ 13 ans versus 10,6% chez celles > 17 ans ; p = 0,02) ; cette tendance n’a pas été retrouvée chez les garçons (6,5% chez ceux ≤ 13 ans et 7,2% chez ceux > 17 ans ; p = 0,78). Tel qu’attendu, une augmentation significative du risque de surpoids a été retrouvée avec l’augmentation de la fréquence de consommation de frites, de chocolat et des repas pris hors de la maison. En contrepartie, la consommation de fruits et l’activité physique étaient associées à un risque inférieur de surpoids. CONCLUSION : Dans les écoles publiques libanaises, nous avons trouvé des prévalences élevées d’obésité et de ses comportements associés d’où l’importance de la prévention chez ces adolescents de bas niveau socioéconomique, en insistant sur l’amélioration du style de vie.

risk of obesity and obesity for boys than girls (22.5% versus 16.1% at risk and 7.5% versus 3.2% obese, respectively) [5]. We had also carried out a study about adolescent obesity in Lebanese private schools: among 12,299 adolescents, we found high obesity (7.5%) and risk of obesity (24.4%).

Departments of Clinical Paediatrics, Faculty of Medicine, University of Balamand, Lebanon ; Epidemiology & Public Health, Faculty of Public Health, Lebanese University. Correspondence : Pascale Salameh, PharmD, MPH, PhD. Jdeidet El Meten, Chalet Suisse St. Ramza Azzam Bldg. Beirut. Lebanon. Tel. : +961 3 385542 Fax : +961 1 691167 e-mail : [email protected] OR [email protected] 1

2

In girls, the risk of obesity and obesity prevalences decreased with increasing age (p < 0.001), while no such change occurred in boys [6]. No such study has been carried out in public schools adolescents, which are known to differ from those of private schools by parents’ socioeconomic status and educational level. The underlying reasons for obesity in Lebanese children and adolescents are still unknown. Social, economic and lifestyle behaviors have contributed to increase the number of obese adolescents with low health related quality of life, and adults with multiple chronic illnesses worldwide [7]. Since lifestyle and behavior choices develop during school-age years, a child food intake and physical activity at school are important determinants of body weight [8]. Having an overweight parent is another risk factor for childhood obesity [9]. As for socioeconomic status, it has been shown to differ in affecting obesity according to countries: in developing countries, obesity is more prevalent in high socioeconomic status populations, while the opposite is observed in developed countries [10-11]. Thus, performing such a study in public schools is expected to give results that differ from those obtained in private schools. The objective of our study was to draw growth curves and assess overweight and obesity prevalences in adolescents of public schools, and explore the frequency of selected food consumption, physical activity and sedentary behavior. MATERIAL AND METHODS

Study design It is a cross-sectional study conducted on a sample of 2547 adolescents in Lebanese public schools, aged 11 to 18 years, between April and June 2007.

Sampling procedure From the list of Lebanon public schools provided by the Ministry of Education, a random sample of 20 schools was chosen, distributed in all Lebanese regions. A permission of the Ministry of Education allowed an easy access to these schools. Directors were contacted to explain the objective of the study and its procedure, and 16 (80%) agreed to participate to the current study: 2 in Beirut, 7 in Mount Lebanon, 5 in North Lebanon, 1 in South Lebanon, and 1 in the Bekaa plain. This population of school students is considered of low to median socioeconomic status. The schools that refused to participate had students with similar socioeconomic background to those which agreed to participate. Data collection Body measures were taken between April and June 2007. A trained researcher was sent to record gender, birth date and measure weight and height of all students in the required age group; these activities were performed in collaboration with the school health professional. One calibrated scale and one stadiometer for height measurement were used; shoes were systematically removed, and mea-

H. CHAKAR, P. R. SALAMEH – Obesity in public schools adolescents

surements were made with light indoor clothing only. In addition, for exploratory purposes only, a self-completed questionnaire was filled in by adolescents on that day. This questionnaire included a limited Food Frequency Questionnaire (chocolate, fried potatoes, traditional Lebanese dishes, salads, and fruits weekly consumption), in addition to frequency of eating out of home, and usual physical and intellectual activity (sports, walking to school, studying, working on the computer or watching television). Although students had the possibility to refuse to participate, none did since it was recommended by the school direction.

Statistical analysis Data entry and analysis were performed on SPSS statistical software, version 11.5. Before analysis, a weighting of cases was performed, according to the latest publication of the Central Administration of Statistics in Lebanon, showing the distribution of Lebanon residents according to age group, sex and district [12], to ensure better representativity of the sample: this maneuver was performed by multiplying every individual’s weight with a weighting index, thus changing the sample structure into one that represents the Lebanese population according to age group, sex and district. Cluster effect was taken into account according to the method suggested by RumeauRouquette and collaborators [13]. Absolute body mass index (BMI) was calculated as mass in kg over height in meters squared; this is a practical, useful and preferred index to assess body fat [14-15]. However, since in children changes in weight may be confounded by linear growth and puberty-related changes in body composition that differ between boys and girls, body mass index relative to age and sex, in the form of percentiles on standardized Z scores are needed to define risk of obesity and obesity in children [16]. If appropriate cutoff points are used, a high body mass index level is a moderately sensitive and a very specific indicator of excess adiposity among children [17-18]. Therefore, obesity and risk of obesity were defined according to cut-off values taken from International Obesity Taskforce for BMI of boys and girls aged 2 to 18 years [19]. We used the term “overweight” to define the subgroup of adolescents above normal BMI, including obese individuals and those at risk of obesity. For every year of rounded age, percentiles were calculated, allowing curves drawing for weight in kg, height in cm and body mass index (BMI) in kg/m2, according to the LMS method described by Cole in 1992 [20], which summarizes the data in terms of three smooth age specific curves called L (lambda), M (mu), and S (sigma). The M and S curves correspond to the median and coefficient of variation of body mass index at each age whereas the L curve allows for the substantial age-dependent skewness in the distribution of body mass index. Further details of the method are explained in Cole paper [20]. Pearson Chi2 and trend tests were used to compare obesity and at risk of obesity prevalence between boys and Lebanese Medical Journal 2011 • Volume 59 (2) 81

girls and within age classes, respectively. Student T-test was used to compare quantitative continuous variables, such as food and activity frequencies between subgroups. A p-value of < 0.05 was considered significant. For weekly frequency variables, classes were created as follows: 0, 1-2 times weekly, 3-4 times weekly, and 5 times weekly or more. For daily frequency variables, frequency classes were created: 0, 0.01-1 hour daily, 1.012 hours daily, and more than 2 hours daily. A stepwise Likelihood Ratio descendent logistic regression for overweight was then performed, taking into account multiple variables: age, gender, geographic distribution, food frequency, physical and other activities. RESULTS

Descriptive results The sample was distributed proportionally to the general Lebanese population distribution across Lebanese regions, due to weighting procedure; it was composed of 1416 females (55.6%) and 1131 males (44.4%). 21.1% of the sample had 13 years of age or less, 32.8% had between 13 and 15 years, 30.9% between 15.1 and 17 years, and 14.8% had 17 years or more (Table I). Chocolate, fried potatoes, fruits and traditional platters were consumed 4 to 5 times per week on average, while salads were consumed 3 to 4 times weekly. These adolescents also declared eating out around 3 times per week. 25% of the adolescents walked to school for a mean time of 11 minutes. They also spent an average of 2 to 3 hours per day studying, watching TV and playing computer, making a total of 6 to 9 hours of extracurricular sedentary activity, compared with around 90 minutes per day of physical activity (Table I).

Obesity and risk of obesity For obesity, 20.5% (95% CI [18.9%-22.1%]) of the sample population were at risk of obesity while 6.6% (95% CI [5.6%-7.6%]) were obese (Table I). Difference in obesity prevalence estimates between regions was not statistically significant (p = 0.09). In addition, obesity prevalence estimates did not differ significantly between boys and girls (p = 0.79), except for the subgroup lower than 13 years of age (p = 0.05) (Table II). In the boys’ subgroup, obesity prevalence estimates did not differ across age groups; however, in girls, a significant difference was found between age groups, with a trend for obesity to be lower in lower age category (p = 0.02) (Table II).

Growth curves for boys and girls Weight, height and BMI curves are presented in figures 1 to 6, for boys and girls separately. At 18 years of age, the 97th percentiles for the BMI of boys and girls were at 30 kg/m2, while the 75th percentiles were at 25 kg/m2 (Fig. 1 to 6). BMI appears to stabilize at 15 years for girls, while it continues to increase for boys beyond 18 years (Fig. 1 & 2). In figures 3 & 4, girls’ weight seems to reach 82 Lebanese Medical Journal 2011 • Volume 59 (2)

TABLE I Variable

DESCRIPTIVE RESULTS OF THE SAMPLE POPULATION

District distribution Beirut Mount Lebanon North Lebanon South Lebanon Bekaa Gender Male Female Age class ≤ 13 years 13.1-15 years 15.1-17 years > 17 years Obesity class Normal weight At risk of obesity Obese Walks to go to school Weight (kg) Height (cm) BMI (kg/m2) Age (years)

Chocolate / week Fried potatoes / week Salad / week Traditional platters / week Eating out / week Fruits / week

Studying hours / day Minutes walking to school / day TV watching hours / day Computer playing hours / day Physical activity hours / day BMI: Body mass index

Frequency n = 2547

% 100

265 1017 523 422 320

10.4 39.9 20.5 16.6 12.6

1131 1416

44.4 55.6

540 834 786 378

21.1 32.8 30.9 14.8

1853 523 167 641 Mean 55.32 158.92 21.70 15.21

72.7 20.5 6.6 25.2 SD 14.02 12.12 4.02 2.09

2.80 11.16 2.87 1.81 1.58

1.71 8.46 2.27 1.96 1.35

5.41 4.34 3.66 5.48 2.96 5.67

4.98 3.63 2.25 2.01 3.50 2.69

SD: Standard deviation

a plateau at 15 years, while that of boys continues to increase up to18 years. A similar plateau appears for girls’ height at 15 years, while boys continue to grow in height up to 18 years and beyond (Fig. 5 & 6).

Food frequency and activity in normal and overweight adolescents As expected, overweight individuals ate chocolate and fried potatoes more frequently than normal BMI individuals; they also ate outside home more frequently (p < 10-4). On the other hand, they performed a lower duration of physical activity per day (p = 0.002) (Table III).

H. CHAKAR, P. R. SALAMEH – Obesity in public schools adolescents

TABLE II OBESITY IN BOYS N = 1126 Normal weight N = 816 (72.5%) At risk of obesity N = 234 (20.8%) Obese N = 76 (6.7%) OBESITY IN GIRLS N = 1409 Normal weight N = 1038 (73.7%) At risk of obesity N = 286 (20.3%) Obese N = 85 (6.0%)

p-value for differences between genders

OBESITY, AGE CLASS AND GENDER DISTRIBUTION ≤ 13 years

13.1-15 years

N = 246 (100%)

AGE

15.1-17 years

> 17 years

N = 328 (100%)

N = 372 (100%)

N = 180 (100%)

183 (74.4%)

246 (75.0%)

260 (69.9%)

127 (70.6%)

47 (19.1%)

61 (18.6%)

86 (23.1%)

40 (22.2%)

16 (6.5%)

21 (6.4%)

26 (7.0%)

13 (7.2%)

N = 293 (100%)

N = 506 (100%)

N = 411 (100%)

N = 199 (100%)

203 (69.3%)

387 (76.5%)

302 (73.5%)

146 (73.4%)

79 (27.0%)

93 (18.4%)

82 (20.0%)

32 (16.1%)

11 (3.8%)

26 (5.1%)

27 (6.6%)

21 (10.6%)

0.05

0.73

Multivariate analysis We performed a stepwise Likelihood Ratio descendent logistic regression for overweight (both obese and at risk of obesity individuals) as a dependent variable, taking multiple variables into account (age, gender, geographic distribution, food frequency, physical and other activities); we found that eating fried potatoes (ORa = 1.28 [1.14-1.44]; p < 10-4) and chocolate (ORa = 1.11 [1.00-1.24]; p = 0.06) were associated with increased risk of overweight, while eating salads (ORa = 0.88 [0.79-0.97]; p = 0.01), fruits consumption (ORa = 0.87 [0.77-0.98]; p = 0.02) and

0.02

0.21

DISCUSSION

TABLE III

Variables frequency M (SD)

Normal BMI

Overweight*

p

Studying hours / day Minutes walking to school / day TV watching hours / day Computer playing hours / day Physical activity hours / day

4.92 (4.42) 3.72 (2.33) 3.65 (2.29) 5.47 (2.11) 2.63 (3.21) 5.72 (2.66)

2.79 (1.67) 10.92 (7.58) 2.84 (2.15) 1.78 (1.95) 1.63 (1.36)

6.72 (6.07) 6.02 (5.48) 3.67 (2.14) 5.52 (2.09) 3.83 (4.04) 5.51 (2.74)

< 10-4 < 10-4 0.88 0.58 < 10-4 0.07

2.83 (1.82) 11.06 (8.31) 2.94 (2.57) 1.89 (2.00) 1.44 (1.31)

0.775

daily physical activity (ORa = 0.81 [0.74-0.90]; p < 10-4) were inversely correlated with overweight. Eating out was also associated with increased risk of overweight (ORa = 1.21 [1.10-1.34]; p 17 y; p = 0.02); this trend was not found in boys (6.5% in those ≤ 13 y and 7.2% in those > 17 y; p = 0.78). These results are opposite to the ones we found for private schools girls, where the risk of obesity and obesity prevalences had decreased with increasing age (p < 10-4), while there is no change in obesity prevalence estimates with age in boys in both studies [6]. Discrepancies between boys’ and girls’ obesity prevalence estimates according to high and low socioeconomic levels remain to be explained. In developed countries, children of public schools have a higher prevalence of obesity during their adolescent years than those with higher socioeconomic status [25]; in these countries, food insecurity, and poverty are clear risk factors for obesity in these children [26]. However, in developing countries, the opposite seems to happen, and high socioeconomic level is associated with higher levels of obesity [10]. We note that the International Obesity Task Force cutoff values have a low sensitivity for detecting obesity [27], and there is a substantial variability of BMI’s accuracy as an indicator of adiposity; thus, caution should be taken in interpreting our results [28], particularly for boys and lower BMI adolescents [29]: sensibly higher results would be expected if BMI measures would be replaced by more sensitive measures, such as fat mass index and fat free mass index [28]; this would put our Lebanese public schools’ adolescents at one of the highest points of the international ladder regarding obesity prevalence and risk of obesity. From a public health point of view, these results are alarming: obesity in adolescents is known to be the cause of several physical, mental and social problems [7]. As expected, a significant increase in the risk of being overweight was found with increased frequency of eating fried potatoes, chocolate and eating out. In contrast, eating fruits and having physical activity were associated with a lower risk of being overweight. These results are similar to those of other researchers in the world. For example, in Puerto Rican children, frequency of fruit juice consumpH. CHAKAR, P. R. SALAMEH – Obesity in public schools adolescents

tion, hours of daily TV viewing, maternal BMI and lower dairy product intake were associated with obesity [30]. Television viewing has been correlated with lower physical activity in girls, and with higher snacking frequency and sweets consumption in boys [30-32]. However, patterns of relationships may differ according to parental weight status. For overweight families, television viewing may provide a context for excessive snack consumption, in addition to inactivity [32]. Moreover, similar to our results, obese adolescents seem less physically active than are normal-weight adolescents, girls in particular [33-36]. The decline in physical activity with age is antithetical to public health goals, so methods of countering the decline need to be developed, based upon an improved understanding of the phenomenon and its causes [35]. Modifiable determinants of decreased physical activity are numerous [37-38], and they should be taken into account when encouraging adolescents to increase they physical activity. Thus, dietary and physical activity guidelines [39-40] could be applied to induce the required changes in adolescents’ behavior, after adaptation to the Lebanese culture and habits. Health education campaigns focusing on healthy eating and physical activity are suggested. However, some environmental influences beyond a child’s control may make dietary and physical activity habits especially resistant to change [41], such as peers and media, with varying effects in boys and girls [42]. Further studies are still needed to thoroughly explain the nutritional behavior of Lebanese adolescents, evaluate the impact of globalization and westernization of social habits on nutrition and physical activity in the Lebanese society, in addition to interactions with genetic, hormonal, biological, psychological, and environmental factors in causing obesity. More adequate nutritional tools (extended food frequency questionnaires, three-day diet history, and 24 hours recalls) would be required to thoroughly evaluate adolescents nutritional habits. An extension of the sample to lower age children would also be needed to have a wider idea about childhood obesity in Lebanon. In conclusion, the growth curves we generated can be used for public schools adolescents in Lebanon; they add to the knowledge about trends in child growth and development and could be useful to monitor prevalent conditions in this specific population such as overweight and obesity. Furthermore, several factors related to school and family environments were associated to overweight among the public schools’ adolescents. Prevention measures should focus on healthy lifestyles and target all adolescents, especially those of a low to median socioeconomic status. REFERENCES

1. World Health Organization. Diet, Nutrition and the Prevention of Chronic Diseases. Geneva, Switzerland : World Health Organization, 2003. 2. Hedley AA, Ogden CL, Johnson CL et al. Prevalence of overweight and obesity among US children, adolescents Lebanese Medical Journal 2011 • Volume 59 (2) 87

and adults, 1999-2002. JAMA 2004 ; 291 : 2847-50. 3. Lobstein T, Frelut ML. Prevalence of overweight among children in Europe. Obes Rev 2003 ; 4 : 195-200. 4. Deeb ME, Awwad J, Yeretzian JS, Kaspar HG. Prevalence of reproductive tract infections, genital prolapse, and obesity in a rural community in Lebanon. Bull World Health Organ 2003 ; 81 (9) : 639-45. 5. Sibai AM, Hwalla N, Adra N, Rahal B. Prevalence and covariates of obesity in Lebanon : findings from the first epidemiological study. Obes Res 2003 ; 11 (11) : 1353-61. 6. Chakar H, Salameh P. Growth and obesity in Lebanese private schools children. Lebanese Medical Journal 2007 ; 55 (2) : 75-82 7. Lavizzo-Mourrey R. Childhood obesity : What it means for physicians. JAMA 2007 ; 298 (8) : 920-2. 8. Colin Carter R. The impact of public schools on childhood obesity. JAMA 2002 ; 288 (17) : 2180. 9. Huerta M, Bibi H, Haviv J et al. Parental smoking and education as determinants of overweight in Israeli children. Prev Chronic Dis 2006 ; 3 : 1-9. 10. Zimmerman R. The obesity epidemic in America. Clinics in Family Practice 2002 ; 4 (2) : 1-8. 11. Majem SL, Barba RL, Bartrina A et al. Childhood and adolescent obesity in Spain. Results of the enKid study (1998-2000). Med Clin (Barc) 2003 ; 121 (19) : 725-32. 12. Central Administration of Statistics. The national study for households living conditions in 2004. Beirut, 7 July 2005. Available at www.cas.org. Consulted 1st August 2007 13. Rumeau-Roquette C, Breart G, Padieu R. Méthodes en Epidémiologie : Echantillonnage, investigations, analyse. Paris : Flammarion, 1985 : 71-82. 14. Magarey AM, Daniels LA, Boulton TJ, Cockington RA. Predicting obesity in early adulthood from childhood and parental obesity. Int J Obes Relat Metab Disord 2003 ; 27 (4) : 505-13. 15. Luciano A, Livieri C, Di Pietro ME, Bergamaschi G, Maffeis C. Definition of obesity in childhood : criteria and limits. Minerva Pediatrics 2003 ; 55 (5) : 453-9. 16. Maynard ML, Wisemandle W, Roche AF, Chumlea WC, Guo SS, Siervogel RM. Childhood body composition in relation to Body Mass Index. Pediatrics 2001 ; 107 : 344-50. 17. Freedmana DS, Ogdenb CL, Berensonc GS, Horlickd M. Body mass index and body fatness in childhood. Curr Opin Clin Nutr Metab Care 2005 ; 8 : 618-23. 18. Mei Z, Grummer-Strawn LM, Pietrobelli A, Goulding A, Goran M, Dietz WH. Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr 2002 ; 75 : 978-85. 19. Cole T, Bellizi M, Flegal K, Dietz W. Establishing a standard definition for children overweight and obesity worldwide : international survey. BMJ 2000 ; 320 : 1240-6. 20. Cole TJ, Green PJ. Smoothing reference centile curves : the LMS method and penalized likelihood. Statistics in Medicine 1992 ; 11 : 1305-19. 21. de Onis M, Onyango AW, Borghi E et al. Development of a WHO growth reference for school-aged children and adolescents. Bulletin of the World Health Organization 2007 ; 85 : 660-67. 22. Rogol A, Clark P, Roemmich J. Growth and pubertal development in children and adolescents : effects of diet and physical activity. Am J Clin Nutr 2000 ; 72 (suppl) : 521S-528S. 23. Center for Disease Control (CDC). Reports and manuals from the first National Health and Nutrition Examination Survey (NHANES I, 1971-75). http://www.cdc.gov/nchs/ 88 Lebanese Medical Journal 2011 • Volume 59 (2)

24.

25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42.

/about/major/nhanes/nh1rrm.htm.2004. Bellizi M, Graham H, Guillaume M, Dietz W. Prevalence of childhood and adolescent overweight and obesity in Asian and European countries. Obesity in childhood and adolescence. Nestlé Nutrition Workshop Series Pediatric Program 2001 ; 49 : 4-6. Edmunds L, Waters E, Elliot EJ. Evidence-based management of childhood obesity. BMJ 2001 ; 323 : 916-19. Casey PH, Simpson PM, Gossett JM et al. The association of child and household food insecurity with childhood overweight status. Pediatrics 2006 ; 118 (5) : e1406-e1413. Cole T, Bellizi M, Flegal K, Dietz W. Establishing a standard definition for children overweight and obesity worldwide : international survey. BMJ 2000 ; 320 : 1240-6. Freedman D, Ogden C, Berenson G, Horlick M. Body mass index and body fatness in childhood. Curr Opin Clin Nutr Metab Care 2005 ; 8 : 618-23. Demerath EW, Schubert CM, Maynard LM et al. Do changes in body mass index percentile reflect changes in body composition in children ? Data from the Fels Longitudinal Study. Pediatrics 2006 ; 117 (3) : e487-e495. Tanasescu M, Ferris AM, Himmelgreen DA, Rodriguez N, Pérez-Escamilla R. Biobehavioral factors are associated with obesity in Puerto Rican children. J Nutr 2000 ; 130 : 1734-42. Hanley AJ, Harris SB, Gittelsohn J, Wolever TM, Saksvig B, Zinman B. Overweight among children and adolescents in a Native Canadian community : prevalence and associated factors. Am J Clin Nutr 2000 ; 71 : 693-700. Francis LA, Lee Y, Birch LL. Parental weight status and girls’ television viewing, snacking, and body mass indexes. Obes Res 2003 ; 11 (1) : 143-52. Ekelund U, Åman J, Yngve A, Renman C, Westerterp K, Sjöström M. Physical activity but not energy expenditure is reduced in obese adolescents : a case-control study. Am J Clin Nutr 2002 ; 76 : 935-41. Trost SG, Pate RR, Sallis JF et al. Age and gender differences in objectively measured physical activity in youth. Med Sci Sports Exer 2002 ; 34 (2) : 350-5. Sallis JF. Age-related decline in physical activity : a synthesis of human and animal studies. Med Sci Sports Exerc 2000 ; 32 (9) : 1598-600. Telama R, Yang X. Decline of physical activity from youth to young adulthood in Finland. Med Sci Sports Exerc 2000 ; 32 (9) : 1617-22. Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc 2000 ; 32 (5) : 963-75. Kimm SY, Glynn NW, Kriska AM et al. Decline in physical activity in black girls and white girls during adolescence. N Engl J Med 2002 ; 347 : 709-15. Johnson RK, Kennedy E. The 2000 Dietary Guidelines for Americans : what are the changes and why were they made ? J Am Diet Assoc 2000 ; 100 : 769-74. Pate RR, Pratt M, Blair SN et al. Physical activity and public health : A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 1995 ; 273 : 402-7. Halford JC, Boyland EJ, Hughes G, Oliveira LP, Dovey TM. Beyond-brand effect of television (TV) food advertisements/commercials on caloric intake and food choice of 5-7-year–old children. Appetite 2007 ; 49 (1) : 263-7. McCabe MP, Ricciardelli LA. A prospective study of pressures from parents, peers, and the media on extreme weight change behaviors among adolescent boys and girls. Behav Res Ther 2005 ; 43 (5) : 653-68.

H. CHAKAR, P. R. SALAMEH – Obesity in public schools adolescents