Obesity Research

Open journal

ISSN 2377-8385

Behavioural and Psychological Variables Associated with Overweight and Obesity in Gran Canaria, Spain

Maria Luisa Álvarez-Malé*, Inmaculada Bautista-Castaño and Lluis Serra-Majem

Maria Luisa Álvarez-Malé

Nutrition Research Group IUIBS University of Las Palmas de Gran Canaria, Avda Rafael Cabrera 13, 5ÂșC, Las Palmas de Gran, Canaria, 35002, Spain, Tel. 0034 626 508 838; E-mail: mlalvarezmale@gmail.com

INTRODUCTION

Obesity remains a major public health problem. The potential and serious consequences that can derive from it, as well as its high prevalence in the world, justify the need to find accurate and periodic information about obesity.1

The increase in obesity and overweight in children and adolescents in the past two decades is particularly alarming.2 According to WHO, in 2013 more than 42 million children under five years old were already overweight.3

In Spain, and especially in the Canary Islands, the prevalence of obesity among children and adolescents is very high, particularly among Canarian adolescent girls.4 The enKid studies have shown the prevalence of obesity in Spain to be 13.9% and of overweight 12.4% (of overweight and obesity 26.3%).5 Geographically, the Canary Islands and Andalusia had the highest prevalence of obesity, and La Rioja, Asturias, the Basque Country, Galicia and Madrid had the lowest prevalence of obesity.5,6

Regarding the etiology of obesity, it includes genetic and lifestyle factors. In relation to lifestyle, analyzing eating habits and physical activity in the population is basic. Therefore, in this work we have studied the adherence of the participants to the Mediterranean diet. This concept was proposed and developed by Keys and Grande7 and was defined as a dietary pattern followed in regions around the Mediterranean (mainly Crete, Greece and the south of Italy). The principal aspects of this dietary pattern include high consumption of fruit and vegetables, olive oil as a source of fat, low consumption of meat and dairy products and moderate consumption of wine.8

Its health benefits have been amply demonstrated by numerous epidemiological studies9 and are related to a lower total mortality and a lower incidence of cardiovascular disease, obesity, type 2 diabetes, metabolic syndrome and hypertension.10

In relation to eating habits we also studied the frequency of meals. Breakfast is the meal most related to obesity, and skipping it has been identified as a factor associated with excess weight.1,11 We have also related the morning break, lunch, afternoon break and dinner to the weight status of the participants.

Regarding physical activity, scientific studies have evidenced its association with obesity in adolescents, as well as with metabolic and cardiovascular diseases. Therefore, it is important to pay attention to the amount of physical activity performed by adolescents in order to consider the development of effective obesity prevention and treatment programs.12

Other sociodemographic variables such as educational level of parents have been related to weight status, so we have included them in this study. We also found interesting the assessment of adolescents nutritional knowledge level and its association with their weight status. Children are conditioned by their family dietary practices, while adolescents are cognitively more able to choose what they eat and to think about the dietary habits that they follow.13 There are many studies that have shown the association between variables like eating habits and obesity in childhood and adolescence. However, there is a lack of investigations focused on Spanish adolescents.11,14,15,16 Therefore, the aim of this research was to find overall data of prevalence of overweight and obesity in the Canarian adolescents and associate them with different behavioural variables.

MATERIAL AND METHODS

Participants and Procedure

This study was reviewed and approved by the Ethics Committee of the University of Las Palmas de Gran Canaria. All participants or (in the case of minors) their legal representatives signed an informed consent agreeing to participate in this research.

The sample of this cross-sectional study was representative and consisted of 1336 participants with a mean age of 15.0 (SD = 2.1 years). All adolescents who participated were from compulsory secondary education (aged 12 to 16; known in Spain as EducaciĂłn Secundaria Obligatoria – ESO) to post-compulsory education at high school (aged 16 to 18; known in Spain as Bachillerato) or vocational training enrolled in various schools on the island of Gran Canaria.

The different educational centers and classrooms (one per level) were randomly selected. We contacted the centers and met with heads or school counselors to explain what the work was to consist of, to distribute the informed consent and to coordinate the activity. Once the date was specified, the team moved to the participating centers for the implementation of the different tests. The time required for conducting these tests was approximately 40 minutes, and they were at all times supervised by a team member. Later, the students were weighed and measured without shoes, jackets or heavy coats. The anthropometric study was conducted by experienced professionals.

Instruments

An ad hoc sociodemographic questionnaire was used, which collected information such as gender, age, educational level of parents, family illnesses reported by participants, being on diets, meal frequency and so on.

The Mediterranean Diet Quality Index (KIDMED) questionnaire17 was used to determine the level of adherence to the Mediterranean diet. It consists of 16 items that are related to Mediterranean dietary patterns. Each of the 12 items that denoted positive connotation with respect to the Mediterranean diet were scored as a +1, while questions that had a negative connotation to the Mediterranean diet (there are four) were scored as a -1. Then, all the items were summed to produce a total score. Based on this score, participants’ adherence was classified as high (score ≄ 8), medium (4–7) or low (score ≀ 3).

To assess physical activity habits of adolescents the Krece Plus questionnaire was used.18 This test consisted of two questions that assessed the number of hours per day dedicated to sedentary activities like watching TV or playing video games and the number of hours per week dedicated to physical activity. So, it allowed us to obtain an easy index for screening the level of activity or inactivity of the adolescents.

Each question offered six possible answers and scored ranges from 0 to 5. The maximum total value of the test was 10 and the minimum 0. According to this overall score individuals were classified into three categories corresponding to their level of physical activity:

 

  • Good: score ≄ 9 for boys; ≄ 8 for girls
  • Regular: 6–8 points in boys; 5–7 in girls
  • Bad: score ≀ 5 in boys; ≀ 4 in girls

 

The NKT questionnaire was used to study the nutritional knowledge of participants in a formal way. This test was previously validated in children and adolescents.19,20 The NKT questionnaire was designed for students who had not received any special education on “nutrition”.19 The questionnaire included a total of 23 multiple choice questions categorized in specific scales: knowledge of concepts (e.g. subscales “energy intake and energy metabolism” or “physical activity”), instrumental knowledge (e.g. subscale “nutrient contents”) and knowledge of causal relationships (e.g. subscales “sweeteners” or “oral health”). Each multiple-choice question offered three possible answers and the “don’t know” category, and only one was correct. To calculate the total score, correct answers scored 1 and the rest 0. Finally, all correct answers were summed up and calculated as a percentage of the total.

To weigh students we used a scale ranging from 0 to 150 kg with a precision of 200 g. For the measurement of body height a Holtain stadiometer (Holtain Ltd., Dyfed, UK) with an accuracy of 1 mm was used. Waist circumference was measured with a metal, flexible but inextensible tape (Holtain Ltd., Dyfed, UK) on a 0.1 cm scale.

Growth references from the WHO21,22 were used to establish the weight status of the adolescents, following this criteria:

Weight state Criteria
Overweight

Obesity

Thinness

Severe thinness

IMC > +2 SD

IMC > +1 SD

IMC < -2 SD

IMC < -3 SD

 

Data Analysis

The SPSS statistical package (version 19.0. for Windows) was used throughout for the analysis. Descriptive analyses of the variables used the test of proportions for qualitative variables, measurements of central tendency (mean or median) and measures of dispersion (Standard Deviation – SD) for quantitative variables. Bivariate analyses of the proportionality of distribution of categorical variables were estimated using the χ2 test.

For continuous variables, we used the Kolmogorov-Smirnov test to check that the variables were normally distributed. Normality was accepted as p> 0.05. For comparisons of continuous variables in which the distributions were normal, the comparisons of absolute means between groups were assessed with Student’s t-test. For comparisons of variables in which the distributions were non-normal, the comparisons of absolute means between groups were made with the nonparametric Wilcoxon test of the sum of the ranges.

RESULTS

Obesity Prevalence

The overall prevalence of obesity was 10.4% (n=139), of overweight 22.3% (n=299), of normal weight 65.1% (n=873) and of underweight 1.9% (n=25). Six participants of the total initial sample (N=1342) would not be weighed (because they would not let us to do it), representing a 0.4% of missing subjects. So the final sample was of 1336 adolescents.

Table 1 shows prevalence data of weight status in relation to sociodemographic characteristics. By sex, the prevalence of obesity in boys was of 12.6% (n=76) and in girls it was of 8.6% (n=63). Regarding age groups, we found a higher prevalence among participants of 13 years old or less (16.3%) and of 18 years old or more (11.6%) than in the other groups. Moreover, the prevalence of obesity was higher among adolescents with a father and/or mother with a medium-low level of education, family history of obesity (self-referential) and among those participants who had been on diets in the last year. We did not find significant differences in weight status among participants of public and private schools or among those who reported having relatives with anorexia or bulimia.

 

Table 1: Weight status (WHO) and socio demographic characteristics.

Underweight

n (%)

Normal weight

n (%)

Overweight

n (%)

Obesity

n (%)

Total

n (%)

p

Gender

0.063

Boys

10 (1.7%)

393 (65.3%) 123 (20.4%) 76 (12.6%) 602 (100%)

Girls

15 (2%)

480 (65.4%) 176 (24%) 63 (8.6%) 734 (100%)

Age (years)

<0.001

≀13

7 (2.3%)

161 (52.4%) 89 (29%) 50 (16.3%) 307 (100%)

14-15

7 (1.5%)

319 (67.7%) 102 (21.7%) 43 (9.1%) 471 (100%)

16-17

7 (1.7%)

295 (73.2%) 73 (18.1%) 28 (6.9%) 403 (100%)

≄18

4 (2.6%)

98 (63.2%) 35 (22.6%) 18 (11.6%) 155 (100%)

Center type NS
Public

19 (1.9%)

642 (64.1%) 228 (22.8%) 113 (11.3%)

1002 (100%)

Private

6 (1.8%)

231 (69.2%) 71 (21.3%) 26 (7.8%)

334 (100%)

Father’s educational level

0.027

High 4 (1.5%) 198 (73.1%) 52 (19.2%) 17 (6.3%)

271 (100%)

Medium-Low

17 (2.4%)

448 (63.6%) 162 (23%) 77 (10.9%)

704 (100%)

Mather’s educational level

0.016

High

5 (1.7%)

217 (72.8%) 59 (19.8%) 17 (5.7%)

298 (100%)

Medium-Low

17 (2.2%)

480 (63.4%) 179 (23.6%)  81 (10.7%) 757 (100%)

Family diseases
Alcoholism

NS

YES 1 (1.8%) 36 (65.5%) 13 (23.6%) 5 (9.1%)

55 (100%)

NO

24 (1.9%)

835 (65.3%) 286 (22.4%) 134 (10.5%) 1279 (100%)

Family obesity
YES

0 (0%)

65 (51.2%) 28 (22%) 34 (26.8%)

127 (100%)

NO

25 (2.1%)

806 (66.8%) 271 (22.5%) 105 (8.7%) 1207 (100%)

Family anorexia

NS

YES

0 (0%)

9 (52.9%) 5 (29.4%) 3 (17.6%)

17 (100%)

NO

25 (1.9%)

862 (65.5%) 294 (22.3%) 136 (10.3%)

1317 (100%)

Family bulimia

NS

YES

0 (0%)

7 (50%) 4 (28.6%) 3 (21.4%)

14 (100%)

NO

25 (1.9%)

864 (65.5%) 295 (22.3%) 136 (10.3%) 1320 (100%)

Dieted in past year

<0.001

YES

1 (0.3%)

131 (41.3%) 115 (36.3%) 70 (22.1%)

317 (100%)

NO

24 (2.4%)

740 (72.8%) 184 (18.1%) 68 (6.7%)

1016 (100%)

 

Adherence to the Mediterranean diet

In relation to the questionnaire of adherence to the Mediterranean diet (KIDMED), the mean score of the population was 5.83±2.52. A total of 19.2% of the population belonged to the group of “low adherence”, 53.7% to the group “medium adherence” and the 26.9% belonged to the “high adherence” group. Table 2 shows lower scores in girls (5.56±2.47) than in boys (6.15±2.54) (p< 0.001).

There were no significant differences between weight status and adherence to the Mediterranean diet between the participants (Table 3). However, we observed that participants with normal weight obtained the highest mean score in the KIDMED test and the highest frequency in the “high” group of adhesion.

 

Table 3: Mediterranean diet adherence (KIDMED) and weight status

Normal weight Overweight Obesity

p

Mediterranean diet adherence

NS

 

Total

M (DT)

 

5.89 (2.55)

 

5.76 (2.50)

 

5.64 (2.31)

Groups

n(%)

NS

 

Low 166 (19%) 56 (18.7%) 8 (32%)

Intermediate

463 (53%) 166 (55.5%) 11 (44%)
High 244(27.9%) 77 (25.8%) 6 (24%)

 

Physical Activity

A total of 55.1% of the adolescents belonged to the group of “bad physical activity”, 29.8% to the “regular physical activity” group and 14.8% of the population belonged to the “good physical activity” group. The overall mean of hours of sedentary activities of the population was 2.26±1.26. The mean of hours that the adolescents practice physical activity was 2.77±1.84.

Table 2 shows a higher score in boys (6.05±2.17) than in girls (5.06±2.31) (p< 0 .001) in the Krece Plus (physical activity). Participants with normal weight spent fewer hours in sedentary activities such as watching television or playing video games (p< 0 .05) and more hours of physical activity (p< 0.05) than those with underweight, overweight or obesity (Table 4).

 

Table 2: KIDMED and Krece Plus distributed by gender.

BOYS

Media (DT)

GIRLS

Media (DT)

TOTAL

Media (DT)

p

KIDMED

6.15 (2.54)

5.56 (2.47) 5.83 (2.52)

<0.001

Krece Plus

6.05 (2.17)

5.06 (2.31) 5.51 (2.30)

<0.001

Hours TV, etc.

2.33 (1.27)

2.21 (1.26) 2.26 (1.26)

NS

Hours physical activity

3.37 (1.72)

2.28 (1.77) 2.77 (1.84)

<0.001

 

Table 4: Physical activity (Krece Plus) and weight status.

Normal weight Overweight Obesity p
Physical activity

Total hours
sedentary
activities

M (DT)

2.20 (1.24) 2.33 (1.34)  

2.45 (1.18)

0.007
Total hours
physical activity

M (DT)

2.86 (1.84) 2.64 (1.82) 2.68 (1.81)

0.034

Groups

n (%)

0.008
Poor 457 (52.4) 175 (58.5) 84 (60.4)

Regular

266 (30.5) 87 (29.1) 46 (33.1)
Good 149 (17.1) 37 (12.4) 9 (6.5)

TOTAL

n (%)

873 (100%) 299 (100%) 139 (100%)

 

Nutritional Knowledge

Ten out of twenty-three questions were answered correctly by more than 50% of respondents. The overall percentage of correct answers in the population was 47.2. In the total sample girls had similar scores as boys (respectively, 46.9% and 47.5%). By sex, there were significant differences only in subscale C (sweeteners and oral health; p< 0.000) and subscale E (special terms and definitions; p= 0.01). In both subscales, boys had higher scores. There were no significant differences between nutritional knowledge and weight status.

Meal Frequency

A total of 18.6% of the adolescent population never or almost never had breakfast (11.9% boys, 24.1% girls). There were significant differences between girls and boys in breakfast (p<0.001), afternoon break (p= 0.007), dinner (p<0.001) and snacking between meals (p= 0.005). In all of them, girls never or almost never ate.

Table 5 shows that participants who never or almost never had breakfast, morning break, afternoon break and dinner had a higher prevalence of obesity and overweight (respectively, p= 0.001; p= 0.001; p= 0.001; p= 0.028) than those who had these meals every day or almost every day. The only meal in which there were no significant differences was lunch.

 

Table 5: Frequency of meals and weight status.

Normal weight

Overweight Obesity

Total

Breakfast**

Never/almost never

137 (15.7%) 71 (23.7%) 39 (28.1%) 247 (18.8%)
Always/almost always 736 (84.3%) 228 (76.3%) 100 (71.9%)

1064 (81.2%)

Morning break**

Never/almost never

192 (22%) 93 (31.1%) 48 (34.5%) 333 (25.4%)
Always/almost always 681 (78%) 206 (68.9%) 91 (65.5%)

978 (74.6%)

Lunch

Never/almost never

11 (1.3%) 4 (1.3%) 1 (0.7%) 16 (1.2%)
Always/almost always 862 (98.7%) 295 (98.7%) 138 (99.3%)

1295 (98.8%)

Afternoon break **

Never/almost never

244 (27.9%) 134 (44.8%) 72 (51.8%) 450 (34.3%)
Always/almost always 629 (72.1%) 165 (55.2%) 67 (48.2%)

861 (65.7%)

Dinner*

Never/almost never

58 (6.6%) 34 (11.4%) 13 (9.4%) 105 (8%)
Always/almost always 815 (93.4%) 265 (88.6%) 126 (90.6%)

1206 (92%)

Snacking between meals**

Never/almost never

543 (62.2%) 235 (78.6%) 111 (79.9%) 889 (67.8%)
Always/almost always 330 (37.8%) 64 (21.4%) 28 (20.1%)

422 (32.2%)

**p< 0.001
*p< 0.05
DISCUSSION

The objective of this study was to calculate the prevalence of obesity and overweight in adolescents in Gran Canaria (Canary Islands, Spain) and to analyze the relation between excess weight and different variables. Results showed a prevalence of obesity of 10.4% (12.6% of boys and 8.6% of girls) and of overweight of 22.3% (boys 20.4%, girls 24%). We observed a relation between obesity and the educational level of the parents, having a relative with obesity, hours of sedentary activities and frequency of meals.

The serious physical and psychological consequences resulting from overweight and obesity highlight the importance of addressing these issues from an early age.23 Epidemiological studies have shown that the prevalence of overweight has surpassed the prevalence of malnutrition in all ages and social and demographic strata. This represents a short and long term risk factor for the increase of Non-communicable chronic diseases (NCCD).24,25,26

The prevalence rates of overweight and obesity vary depending on the geographical area where the studies were conducted, as well as age groups, tables or classification systems used, etc. However, there is a consensus that marks a worldwide increase of child and adolescent obesity, which constitutes an important public health problem.1

The enKid study 5, conducted in Spain with children and youths, found a prevalence of obesity (13.9%) higher than in our work (10.4%). However, in our study, the data of the prevalence of overweight were much higher (22.3%) than in the enKid study (12.4%). The National Health Survey 2006-2007 6 obtained a prevalence of obesity in Spanish children of 10.3% and of overweight of 18.8%. Another work in Castilla y LeĂłn (Spain) showed a prevalence of obesity of 5.8% and of 16.7% of overweight.27 These data are much lower than ours.

We observed similar results in other studies such as the one of Garcia-Continente et al.11 In this work they found a lower prevalence than in our study. However, they also found more obese boys (6.2%) than obese girls (3.7%) and more overweight boys (19.9%) than overweight girls (17%). The prevalence of overweight boys was similar to ours. The AVENA study28 obtained similar data of prevalence to the study of Garcia-Continente.11 In boys they found 5.7% obese and 20% overweight. In girls obesity and overweight prevalence were lower than ours: 3.8% and 16%, respectively. These works found higher rates of obesity prevalence among boys than among girls. However, HenrĂ­quez et al.2 found higher obesity prevalence among girls than boys in Gran Canaria. They obtained a prevalence of 14.8%: 17.6% of girls and 12% of boys. In a more recent study, SĂĄnchez-Cruz29 found a prevalence of obesity of 12.9% among boys and of 12.3% among girls, and a prevalence of overweight of 28.6% and 23.5% among boys and girls, respectively. Obesity prevalence of boys and overweight prevalence of girls were similar to ours. Comparing age groups, as in the enKid study 5, we found the highest prevalence of obesity in participant’s ≀ 13 years old.

There is some controversy among studies that examine the relationship between weight and the Mediterranean diet. Numerous prospective studies that investigate the relationship between diet quality and the risk of obesity found that the Mediterranean diet was inversely associated with the risk of obesity or weight gain.30 However, other studies such as the SUN cohort study, found no such relationship, observing that participants increased their average weight during the follow-up period.31 In our study, the highest average KIDMED score was observed in adolescents with normal weight. Nevertheless, there were no significant differences in the level of adherence to the Mediterranean diet and the weight status.

According to the scientific literature, breakfast represents a clear protector factor of obesity.32 Other specific eating habits have also been related to the increase of weight such as the frequency of meals or the intake of snacks. However, the results of the studies in relation to eating habits are inconsistent.33 In our research we found significant differences in meal frequency and weight status. We observed that skipping meals (breakfast, morning break, afternoon break and dinner) was associated to obesity.

However, most interventions focused on obesity prevention consider not only a dietary change component but also a physical activity component or a combination of both. A number of interventions are focused on increasing frequency and duration of physical exercise, while others on decreasing time devoted to sedentary activity.34 In our research, we observed that participants with normal weight had the lowest number of hours of sedentary activities and the most hours of physical activity.

Another variable studied in this research was the nutritional knowledge level, using the validated test NKT. As in the HELENA study (Healthy Lifestyle in Europe by Nutrition in Adolescence), in our study there was no correlation between BMI values and total NKT score. However, they found gender differences that we did not find. Their results showed a higher knowledge level among girls than among boys. Obesity and overweight have also been linked with lower educational levels.1,35 This paper also found a higher prevalence in adolescents whose fathers and/or mothers had low-medium educational level versus those with a higher educational level.

Overall prevalence of overweight and obesity continue to be very high, especially in the Canary Islands. Therefore it is necessary to search for more effective prevention programs and treatments specifically for adolescents, which might consider the variables analyzed in this research.

CONFLICTS OF INTEREST: None.

1. Ortega RM, LĂłpez-Sobaler AM, Aparicio, A, et al. Surveillance Study of Growth, Diet, Physical Activity, and Obesity Child Development in 2013. Spain Spanish Agency of Consumer Affairs, Food Safety and Nutrition. Ministry of Health. Madrid. 2014.

2. HenrĂ­quez P, Doreste J, LaĂ­nez P, et al. Prevalence of obesity and overweight in adolescents from Canary Islands, Spain. Relationship with breakfast and physical activity. Med Clin (Barc). 2008; 130(16): 606-610. doi: 10.1157/13120339

3. World Health Organization. Obesity and overweight. Available from: http://www.who.int/mediacentre/factsheets/fs311/en/ Accessed January 21, 2015.

4. Aranceta Bartrinaa J, PĂ©rez Rodrigoa C, Ribas Barbab L, Serra Majem L. Epidemiology and determinants of child and adolescent obesity in Spain. Rev Pediatr Aten Primaria. 2005; 7(Suppl 1): S13-S20.

5. Serra L, Ribas L, Aranceta J, Pérez C, Saavedra P, Peña L. Child and adolescent obesity in Spain. Study Results enKid (1998-2000). Med Clin. 2003; 121(19): 725-732.

6. Valdes J, Royo-Bordonada MA. Prevalence of childhood obesity in Spain; National Health Survey 2006-2007. Nutr Hosp. 2012; 27(1): 154-160. doi: 10.1590/S0212-16112012000100018

7. Keys A, Grande F. Dietary fat and serum cholesterol. Am J Public Health. 1957; 47: 1520-1530.

8. GarcĂ­a-Meseguer MJ, Cervera F, Vico C, Serrano-Urrea R. Adeherence to Mediterranean diet in a Spanish university population. Appetite. 2014; 78: 156-164. doi: 10.1016/j.appet.2014.03.020

9. Serra-Majem L, Bes-Rastrollo M, Roman-Viñas B, et al. Dietary patterns and nutritional adequacy in a Mediterranean country. Br J Nutr. 2009; 101: 21-28. doi: 10.1017/S0007114509990559

10. Widmer RJ, Flammer AJ, Lerman LO, et al. The Mediterranean Diet, its Components, and Cardiovascular Disease. Am J Med. 2015; 128(3): 229-238. doi: http://dx.doi.org/10.1016/j.amjmed.2014.10.014

11. García-Continente X, Allué N, Pérez-Giménez A, et al. Eating habits, sendentarias behaviors and overweight and obesity in adolescents in Barcelona. An Pediatr (Barc). 2014. doi: 10.1016/j.anpedi.2014.07.006

12. MartĂ­nez-GĂłmez D, MartĂ­nez-De-Haro V, Del-Campo J, et al. Validity of four questionnaires to assess physical activity in Spanish adolescents. Gac Sanit. 2009; 23(6): 512-517. doi: 10.1016/j.gaceta.2009.02.013

13. Sichert-Hellert W, Beghin L, De Henauw S, et al. Nutritional knowledge in European adolescents: results from the HELENA (Healty Lifestyle in Europe by Nutrition in Adolescence) study. Public Health Nutrition. 2011; 14(12): 2083-2091. doi: 10.1017/S1368980011001352

14. Bueno M, Bueno G, Moreno LA, SarrĂ­a A, Bueno O. Epidemiology of obesity in developed countries. In: Serra L, Aranceta J, eds. Child and Adolescent Obesity: Study enKid. Masson: Barcelona, Spain. 2001; 2: 55-62.

15. Serra Majem L, Ribas Barba L, Aranceta Bartrina J, et al. Childhood and adolescent obesity in Spain. Results of the enKid study (1998-2000). Med Clin (Barc). 2003; 121(19): 725-732. doi: 10.1016/s0025-7753(03)74077-9

16. Zurriaga O, PĂ©rez-Panades J, Quiles Izquierdo J, et al. Factors associated with childhood obesity in Spain The OBICE study: A case-control study based on sentinel networks. Public Health Nutr. 2011; 14: 1105-1113. doi: 10.1017/S1368980010003770

17. Serra-Majem L, Ribas L, Ngo J, et al. Food, youth and the Mediterranean diet in Spain: Development of Kidmed, Mediterranean diet quality index in children and adolescents. Public Health Nutr. 2004; 7: 931-935. doi: http://dx.doi.org/10.1079/PHN2004556

18. Serra Majem L, Aranceta Bartrina J, Santos R. Growth and development. Study enKid. Krece Plus. Masson: Barcelona. 2003.

19. Diehl JM. Nutritional knowledge of children and adolescents. Consumer Services. 1999; 44: 282-287.

20. Kersting M, Sichert-Hellert W, Vereecken CA, et al. Food and nutrient intake, nutritional knowledge and diet- related attitudes in European adolescents. Int J Obes (Lond). 2008; 32, Suppl 5: 35-41. doi: 10.1038/ijo.2008.181

21. World Health Organization. Simplified field tables. BMI for-age GIRLS, 2007. Available from: http://www.who.int/growthref/sft_bmifa_girls_z_5_19years.pdf Accessed January 29, 2015.

22. World Health Organization. Simplified field tables. BMI for-age BOYS, 2007. Available from: http://www.who.int/growthref/sft_bmifa_boys_z_5_19years.pdf Accessed January 29, 2015.

23. Villarejo C, Fernåndez-Aranda F, Jiménez-Murcia S, et al. Lifetime obesity in patients with eating disorders: increasing prevalence, clinical and personality correlates. Eur Eat Disord Rev. 2012; 20(3): 250-254. doi:10.1002/erv.2166

24. Mendonça EKN, De Menezes CE, Souza J, et al. Nutritional status of children and adolescents from a town in the semiarid Northeastern Brazil. Rev Paul Pediatr. 2014; 32(3): 200-207. doi: 10.1590/0103-0582201432309

25. Leal VS, Lira PI, Oliveira JS, Menezes RC, Sequeira LA, Arruda MA, Neto, et al. Overweight in children and adolescents in Pernambuco state, Brazil: prevalence and determinants. Cad Saude Publica. 2012; 28: 1175-1182. doi: http://dx.doi.org/10.1590/S0102-311X2012000600016

26. Menezes RC, Lira PI, Oliveira JS, et al. Prevalence and determinants of overweight in preschool children. J Pediatr (Rio J). 2011; 87: 231-237. doi: 10.2223/jped.2092

27. GulĂ­as-GonzĂĄlez R, MartĂ­nez-VizcaĂ­no V, GarcĂ­a-Prieto JC, DĂ­ez-FernĂĄndez A, Olivas-Bravo A, SĂĄnchez-LĂłpez M. Excess of weight, but not underweight, is associated with poor physical fitness in children and adolescents from Castilla-La Mancha, Spain. Eur J Pediatr. 2014; 173: 727-735. doi: 10.1007/s00431-013-2233-y

28. Moreno LA, Mesana MI, Fleta J, et al. Overweight, obesity and body fat composition in spanish adolescents. The AVENA study. Ann Nutr Metab. 2005; 49: 71-76. doi: 10.1159/000084738

29. Sånchez-Cruz JJ, Jiménez-Moleón JJ, Fernåndez-Quesada F, Sånchez MJ. Prevalence of child and adolescent obesity in Spain in 2012. Rev Esp Cardiol. 2013; 66: 371-376. doi: 10.1016/j.rec.2012.10.012

30. MartĂ­nez-GonzĂĄlez MA, GarcĂ­a-Arellano A, Toledo E, Salas-Salvado J, Cosiales, Corella D. A 14-Item Mediterranean Diet Assessment Tool and Obesity Indexes among High-Risk Subjects: The PREDIMED Trial. PLoS ONE. 2012; 7(8): e43134. doi: 10.1371/journal.pone.0043134

31. SĂĄnchez-Villegas A, Bes-Rastrollo M, MartĂ­nez-GonzĂĄlez MA, Serra-Majem L. Adherence to a Mediterranean dietary pattern and weight gain in a follow-up study: the SUN cohort. International Journal of Obesity. 2006; 30: 350-358. doi: 10.1038/sj.ijo.0803118

32. Merten MJ, Williams AL, Shriver LH. Breakfast consumption in adolescence and young adulthood: parental presence, community context, and obesity. J Am Diet Assoc. 2009; 109(8): 1384-1391. doi: 10.1016/j.jada.2009.05.008

33. Mesas AE, Munoz-Pareja M, Lopez-Garcia E, Rodriguez-Artalejo F. Selected eating behaviours and excess body weight: a systematic review. Obes Rev. 2012; 13(2): 106-135. doi: 10.1111/j.1467-789X.2011.00936.x

34. Roman B, Serra-Majem L, PĂ©rez-Rodrigo C, Drobnic F, Segura R. Physical activity in children and youth in Spain: future actions for obesity prevention. Nutrition Reviews. 2009; 67(Suppl 1): S94-S98. doi: 10.1111/j.1753-4887.2009.00168.x

35. Aranceta J, Perez-Rodrigo C, Serra-Majem L, et al. Influence of sociodemographic factors in the prevalence of obesity in Spain. The SEEDOÂŽ97 Study. European Journal of Clinical Nutrition. 2001; 55: 430-435. doi: 10.1038/sj.ejcn.1601189

LATEST ARTICLES

Practical Pointers for Drug Development and Medical Affairs

Gerald L. Klein*, Roger E. Morgan, Shabnam Vaezzadeh, Burak Pakkal and Pavle Vukojevic

doi.

10.17140/CTPOJ-7-125

Prevalence and Risk Factors of Subclinical Mastitis of Goats in Banadir Region, Somalia

Omar M. Salah*, Yasin H. Sh-Hassan, Moktar O. S. Mohamed, Mohamed A. Yusuf and Abas S. A. Jimale

doi.10.17140/VMOJ-9-184

Use of Black Soldier Fly (Hermetia illucens) Prepupae Reared on Organic Waste

Maggot Debridement Therapy: A Natural Solution for Wound Healing

Isayas A. Kebede*, Haben F. Gebremeskel and Gelan D. Dahesa,

doi.10.17140/VMOJ-9-183

The Impact of Family Dynamics on Palliative Care at the End-of-Life

Neil A. Nijhawan*, Rasha Mustafa and Aqeela Sheikh

doi.10.17140/PMHCOJ-10-154

Long-Term Follow-Up After Laparoscopic Radical Prostatectomy for Localized and Locally Advanced Prostate Cancer

Shrenik J. Shah*, Abhishek Jha, Chirag Davara, Rushi Mistry and Kapil Kachhadiya

doi.

10.17140/UAOJ-7-147

LATEST ARTICLES

Pie Chart Showing Overall Proportions of Diagnostic Category of FNAC, JUMC

Retrospective Study

2024 Apr

Abel Tefera*, Lemlem Terefe and Kitesa Biresa
Prevalence (%) of Types of Anthropometric Failure among Previous and Present Studied Tribal Children

Original Research, peer reviewed

2024 Apr

Biswajit Mahapatra and Kaushik Bose*

Opinion

2024 Apr

Gerald L. Klein*, Roger E. Morgan, Shabnam Vaezzadeh, Burak Pakkal and Pavle Vukojevic