Lifestyle Interventions and Weight Control of Adolescents With Abdominal Obesity: A Randomized Controlled Trial Based on Health Belief Model

AUTHORS

Mojgan Nourian 1 , Roya Kelishadi 2 , Arash Najimi 3 , *

1 Department of Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, IR Iran

2 Department of Paediatrics, Child Growth and Development Research Center, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, IR Iran

3 Medical Education Research Center, Isfahan University of Medical Sciences, Isfahan, IR Iran

How to Cite: Nourian M, Kelishadi R, Najimi A. Lifestyle Interventions and Weight Control of Adolescents With Abdominal Obesity: A Randomized Controlled Trial Based on Health Belief Model, Iran Red Crescent Med J. 2017 ; 19(2):e30638. doi: 10.5812/ircmj.30638.

ARTICLE INFORMATION

Iranian Red Crescent Medical Journal: 19 (2); e30638
Published Online: August 7, 2016
Article Type: Research Article
Received: June 8, 2015
Revised: July 13, 2015
Accepted: August 8, 2015
Crossmark

Crossmark

CHEKING

READ FULL TEXT
Abstract

Background: Adolescents are involved in a variety of health risk behaviors like inactivity and unhealthy diet. Furthermore, behaviors learned by adolescents will continue to adulthood.

Objectives: The current study aimed to determine the effects of lifestyle intervention on the anthropometric measurements by the health belief model (HBM) among obese adolescents in Iran.

Methods: In this parallel randomized controlled educational trial, 90 obese adolescents 12 - 18 years were selected (44 in control and 46 in the test group). The participants in the present study were selected by simple random sampling method among adolescents with obesity referred to the Isfahan cardiovascular research center, Iran. Education based on health belief model was conducted. The main components of the program were on nutrition and physical activity as two major factors in the weight control of people with obesity. Subjects in the control and intervention groups completed questionnaires at baseline (T0), end of three months of intervention (T1) and three months after the end of intervention (T2).

Results: The multivariate test results showed significant effects of interaction of time and group for knowledge scores (F = 101.19; P < 0.001), perceived susceptibility (F = 5.01; P = 0.02), self-efficacy (F = 6.18; P = 0.01) and waist circumference (F = 5.643; P = 0.004).

Conclusions: Results of this study showed that the 12-week educational intervention program using the HBM was effective to increase knowledge, perceived susceptibility and self-efficacy of the participants.

Keywords

Lifestyle, Obesity Abdominal Adolescent Health Belief Model Anthropometric Health Behavior

Copyright © 2016, Iranian Red Crescent Medical Journal. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

1. Background

The growing rate of childhood obesity is alarming even in the developing countries. Overweight and obesity in children are associated with many acute and chronic complications and co-morbidities (1). In both children and adults, obesity leads to an increase in the incidence of cardiovascular risk factors such as high blood pressure, hypertriglyceridemia, reduced high density lipoprotein (HDL-C), and impaired glucose metabolism (2, 3). The clustering of these risk factors, related to atherosclerosis and an elevated risk of cardiovascular diseases (CVD) in adults, is referred to as metabolic syndrome (4, 5).

The prevalence of overweight in Iranian adolescents is high, an estimated prevalence of 21% (6). Parallel with the increasing prevalence of obesity in children as an epidemic and an important public health concern, the risk of metabolic syndrome will increase (7, 8). Based on the results of a national study by Kelishadi et al. (2003), prevalence of obesity in the Iranian children and adolescents was 4.5% based on centers for disease control (CDC) cut offs and prevalence of metabolic syndrome in the Iranian adolescents was about 10.3% in boys and 9.9% in girls (9). It is estimated that among the approximately 16 million students in Iran about 320,000 - 2,240,000 children and adolescents have metabolic syndrome (10).

In spite of evidences for the efficacy of educational intervention programs in behavior modifications, a limited number of studies are conducted in Iran on educational interventions among obese adolescents with metabolic syndrome components (11). Green et al. found that since there was not enough information about the knowledge and health beliefs among adolescents and young people with obesity their risks for CVD could not be accurately perceived. Therefore, it seems that adolescents with obesity should first understand the actual risks; then they could make appropriate decision about the lifestyle (12).

Educational programs are good choices to change behaviour in order to change lifestyle of adolescents (13). Theory-based health behavior change programs are also believed to be more efficacious than those which do not employ any theories (14, 15). The health belief model (HBM), as an important model in health education programs, is applied to explain weight control behavior among adolescents and can affect components of metabolic syndrome (16). Based on this model, changes in health behaviors are predicted by perceived susceptibility, severity, benefits and perceived barriers, cues to action and self-efficacy (17).

2. Objectives

This study was conducted to evaluate the effectiveness of a focused lifestyle intervention to reduce the anthropometric measurements by the HBM among adolescents with obesity in Iran.

3. Methods

3.1. Participants

This randomized controlled educational trial was conducted in the childhood obesity research clinic of pediatric preventive cardiology department in 2013. Childhood obesity research clinic is a referral center under the supervision of Isfahan University of Medical Sciences, Isfahan, Iran.

The studied population included adolescents with abdominal obesity aged 12 - 18 years. The participants in the present study were selected by simple random sampling method from three hundred children with obesity referred from health care centers and schools to childhood obesity research clinic. The inclusion criteria were as follows: age between 12 - 18 years, being overweight or obese (body mass index in the 85th - 95th percentile or ≥ 95th percentile for age and gender) (18), abdominal obesity (waist circumference (WC) ≥ 90th percentile for age and gender based on WC cut-offs for Iranian children and adolescents) (19). Those with history of any chronic diseases as diabetes, cardiovascular disease, liver or any endocrine disorders, as well as the ones on any medication use, the ones following any specific diet and/or exercise program in the six months prior to the study were not included in the study. The sample size was calculated by the following formula (alpha = 0.01, test power = 0.80)

For this study, the minimum calculated sample size was 76 participants, 38 in each group. To allow for a 25% drop-out rate during the study, 50 participants were recruited for each group. Therefore, the total number of participants was calculated 100. Oral assent was obtained from participants and written informed consent from their parents/care givers. Then they were randomly assigned to the intervention and control groups (Figure 1). Ethical approval was obtained from medical research ethics committee University Putra Malaysia and Isfahan University of Medical Sciences (UPM/FPSK/PADS/T7-MJKEticaPer/F01).

3.2. Data Collection Instruments

The knowledge instrument consisted of 13 true/false items to assess the knowledge of participants about the obesity, diet and physical activity. For every answer a score = 1 was given to the right answers and a score = 0 was given to the wrong ones. Questions which were not answered by participants were considered as wrong answers. Therefore, the possible total score for knowledge was 0 - 13.

The HBM instrument included: Perceived susceptibility (items 1 -5) to assess perceived susceptibility to obesity related diseases, perceived severity (items 6 - 9) to assess perceived seriousness of obesity- related diseases, perceived benefits (items 10 - 17) to assess perceived benefits of diet and physical activity to prevent obesity related diseases, perceived barriers (items 18 - 22) to assess perceived barriers of diet and physical activity to prevent obesity related diseases, cues to action (items 24 - 27) to assess cues to action to prevent obesity related diseases. Items were measured on 5-point Likert-type scales. A score 1 to 5 was given for each of the questions in these sections.

The self-efficacy scale included eight items (28 - 35) to measure the confidence of the subjects to follow a healthy diet and physical activity. The self-efficacy items were categorized as “No” and “Yes” responses. The choice “No” was considered as “I strongly disagree; I disagree”, the choice “Yes” was “I agree; I strongly agree”.

The knowledge and HBM tools were researcher-made questionnaires. The questionnaires were prepared based on literature search of the similar studies and then some questions were added to it, self-designed (20, 21). The validity of given questionnaires were accomplished by content and face validity methods.

The first draft of questionnaires were assessed by a panel of experts consisting of two nutritionists, two health educators and a paediatrician and then checked by a secondary school teacher for students’ understanding.

Their views were received to assess content validity and some of them were considered in the questionnaire. The questionnaire was assessed by factor analysis in 100 secondary school students who were not included in the main study. Internal consistency was done for reliability of the questionnaire (α = 0.73 and α = 0.80 for knowledge and HBM, respectively).

3.3. Anthropometric Measurements

Standing height was measured using a non-stretchable measuring tape (0.1 cm precision). Body weight was determined to the nearest 100 grams with a weighing scale (SECA 760, SECA, Hamburg, Germany). BMI was calculated as body weight in kilograms divided by the square of height in meters. BMI was categorized into overweight or obese based on the world health organization (WHO) classification. The BMI z-score was calculated using Intro-plus software. WC was measured at the largest circumference of the abdomen below the ribs and participants were classified with abdominal obesity if WC was > 90th percentile of the cut-off point for Iranian children (22).

3.4. Intervention

HBM was completed in twelve sessions and the final session provided a brief review of some important tips and a question-answer session. Each session was 60 minutes including 45 minutes presentation by the lecturer and 15 minutes question-answer. The time of small group discussion lasted to 30 minutes in some sessions based on the contents. Components and the key factors of the intervention programme and follow-up are provided in Appendix 1.

3.5. Educational Materials

The main components of the program were on nutrition and physical activity as two major factors in the weight control of people with obesity. The program focused on behavioral changes to promote changes in dietary habits and increasing the level of physical activity. Strategies used to promote behavioral changes in this program were lectures using PowerPoint presentation, self-study materials (reading materials), role playing, individual counseling to solve the problems and reminding by phone calls. HBM theory provided a framework for program development. The materials were based on the HBM and emphasized on the consequences of obesity, risk factors of obesity, importance of diet and physical activity in weight control. The study materials on obesity risk factors, obesity consequences, healthy eating and physical activity in weight control were prepared as Power Point slides, two booklets and three pamphlets by the researcher. All educational materials and components were prepared based on scientific evidence and outlines of educational intervention studies on children and adolescents with obesity and modified appropriately by the researcher.

Subjects in the control and intervention groups completed all questionnaires at baseline (T0), end of the three months intervention (T1) and three months after the end of intervention (T2), with the exception of the socio-demographic questionnaire completed only at baseline. If the children could not complete all the information in the questionnaires by themselves, they were assisted by their parents. The subjects in the intervention group were informed on the advantages of participation in the educational sessions and of the importance of completing the sessions. Subjects in the control group received information about the times they should attend the clinic for dietary intake. The researcher and assistants also explained how they should complete the dietary questionnaire and provided an example for the subjects.

3.6. Statistical Analysis

Data were analysed using the statistical package for social science (SPSS, Version 18, Chicago. IL, USA). The independent T-test and Chi-square (χ²) were used to compare the two study groups. Normal distribution assumption was tested by the Kolmogorov-Smirnov test. Repeated measure analysis of variance, general linear model (ANOVA, GLM) was used to assess the changes in each parameter during the study; variables that were significantly different at baseline were considered as covariate and repeated measure analysis of covariance (ANCOVA) was done.

4. Results

Mean age of the subjects in the intervention and control groups were 13.7 ± 1.8 and 13.6 ± 1.2 years, respectively (P = 0.97). There were no significant differences between the two groups regarding gender, mother’s education, father’s education and family history of CVD. Family history of type 2 diabetes mellitus (T2DM) in the intervention group was significantly different from that of the control group (

Table 1. Socio-Demographic Characteristics in the Control and Intervention Groupsa
VariableTotal (n = 90)Control (n = 44)Intervention (n = 46)P Value
Age, y13.7 ± 1.513.7 ± 1.813.6 ± 1.20.978
Gender0.300
Male40 (44.4)22 (50)18 (39.1)
Female50 (55.6)22 (50)28 (60.9)
Mother’s education0.300
Illiterate4 (4.4)3 (6.8)1 (2.2)
Primary school16 (17.8)8 (18.2)8 (17.4)
Secondary school35 (38.9)19 (43.2)16 (34.8)
High school29 (32.2)10 (22.7)19 (43.1)
University6 (6.7)4 (9.1)2 (4.3)
Father’s education0.627
Illiterate000
Primary school3 (3.3)2 (4.5)1 (2.2)
Secondary school15 (16.7)8 (18.2)7 (15.2)
High school51 (56.7)22 (50)29 (63.0)
University21 (23.3)12 (27.3)9 (19.6)
Family history of diabetes0.030b
Yes60 (66.7)24 (54.6)36 (78.3)
No30 (33.3)20 (45.4)10 (21.7)
Family history of CVD0.501
Yes45 (50.0)21 (48.0)24 (52.2)
No45 (50.0)23 (52.2)22 (47.8)

Abbreviation: CVD, cardiovascular disease.

aValues are expressed as No. (%) or mean ± SD.

bSignificant differences at P < 0.05.

Kolmogorov-Smirnov tests showed that the data were distributed normally. The means of knowledge score in the control group at baseline, T1 and T2 were 7.3 ± 1.6, 11.0 ± 1.45 and 11.1 ± 1.0, respectively. There was an increase from T0 to T1 (Δ mean = +3.7 ± 0.8) and T0 to T2 (Δ mean = +3.8 ± 0.9) and the differences were significant when T1 and T2 were compared to T0 (P < 0.001). There was an increase in the score of perceived susceptibility and self-efficacy in the intervention group from T0 to T1 and from T0 to T2. The differences were significant when T1 compared to T0 (P < 0.001 and P = 0.001 respectively) and T2 compared to T0 (P = 0.001 and P < 0.001 respectively). Independent t-test also showed that the two groups were significantly different in perceived susceptibility scores at times T1 (P = 0.006) and T2 (P = 0.005). The perceived severity score changes at time T2 were compared to those of T0 and the difference was significant (P = 0.006). In the intervention group, the mean of perceived barriers scores showed an increase from T0 to T1 (Δ mean = +1.1 ± 0.05) and an increase from T0 to T2 (Δ mean = +0.4 ± 0.02) and at time T1 compared to T0 and these changes were significant (P = 0.005). There was a significant difference in perceived barriers between the two groups at time T2 (P = 0.034). For mean changes of perceived benefits and cues to action, there was no significant interaction between the time and group (Table 2).

Table 2. Mean ± SD of Knowledge and Health Belief Model Scores at T0 to T2 in the Two Groups (n = 90)a
VariableT0T1T2P1P2
Knowledge
Control6.8 ± 1.68.2 ± 1.86.9 ± 1.70.005b0.892
Intervention7.3 ± 1.611.0 ± 1.4511.1 ± 1.0< 0.001b< 0.001b
Perceived susceptibility
Control18.2 ± 4.818.5 ± 3.617.8 ± 2.80.6680.642
Intervention17.5 ± 2.320.4 ± 2.319.6 ± 2.8< 0.001b0.001b
P30.3780.006b0.005b--
Perceived severity
Control19.0 ± 3.319.9 ± 2.919.6 ± 2.10.1460.303
Intervention19.2 ± 2.819.9 ± 2.520.5 ± 2.40.2110.006b
P30.7590.8540.061--
Perceived benefits
Control16.0 ± 2.916.1 ± 2.816.2 ± 2.20.8270.591
Intervention16.5 ± 2.116.7 ± 1.816.8 ± 2.50.6280.546
P30.3510.2290.288--
Perceived barriers
Control7.3 ± 2.58.1 ± 2.47.2 ± 2.30.1170.964
Intervention7.8 ± 0.28.9 ± 1.68.2 ± 1.90.005b0.414
P30.2090.0580.034b--
Cues to action
Control9.3 ± 2.59.3 ± 1.88.9 ± 1.90.9990.409
Intervention8.2 ± 1.19.0 ± 2.28.4 ± 2.10.0900.554
P30.02b0.50.5--
Self-efficacy
Control4.6 ± 2.04.4 ± 1.74.2 ± 1.80.4940.278
Intervention3.7 ± 1.54.8 ± 1.74.9 ± 1.60.001b< 0.001b
P30.02b0.40.4--

aT0, baseline; T1, end of three months intervention; T2, three months after end of intervention; P1, paired T-test for T0 and T1; P2, paired T-test for T0 and T2; P3, independent T-test for control vs. intervention group.

bSignificant differences at P < 0.05.

The mean weight at T1 in the control group was 62.2 ± 16.9 kg and in the intervention group was 62.8 ± 13.5 kg. Although the weight of the subjects in both intervention and control groups decreased from T0 to T1, but the mean change was significantly different in the intervention group (P < 0.001). Also the mean weight in the intervention group decreased at T2 compared to T0 and increased in the control group but the mean change was not significantly different (P = 0.131 and P = 0.101, respectively). Mean height of the participants increased significantly at times T1 and T2 in comparison with T0 in the control and intervention groups (P < 0.001). Changes in BMI z-score of the subjects showed a significant decrease in BMI z-score in the two groups three months after intervention (T1) compared to those of the baseline (T0) (P = 0.013 in the intervention and P = 0.031 in control group). There was a significant decrease in BMI z-score after follow-up (T2) compared to that of the baseline (T0) only in the intervention group (P < 0.001). In the intervention group, the mean of WC changes were not significant (P = 0.435; P = 0.990) (Table 3).

Table 3. Mean ± SD of Anthropometric Measurements From T0 to T2 (n = 90)a
VariableT0T1T2P1P2
Weight, kg
Control62.4 ± 17.462.2 ± 16.963.7 ± 16.50.7730.101
Intervention64.1 ± 13.562.8 ± 13.563.3 ± 13.6< 0.001b0.131
P30.6040.8490.886--
Height, cm
Control152.4 ± 11.5153.5 ± 11.2155.4 ± 11.50.012b< 0.001b
Intervention153.8 ± 8.4155.2 ± 8.4156.9 ± 8.6< 0.001b< 0.001b
P30.5130.4270.489--
BMIa z-score
Control2.0 ± 0.61.9 ± 0.71.9 ± 0.80.031b0.112
Intervention1.9 ± 0.41.8 ± 0.71.7 ± 0.60.013b< 0.001b
P30.7520.6530.288--
WCb, cm
Control98.0 ± 11.799.8 ± 11.5101.7 ± 10.30.002b< 0.001b
Intervention101.8 ± 8.3101.4 ± 8.5102.1 ± 8.90.6580.621
P30.0850.4480.820--

Abbreviations: BMI, body mass index; WCb, waist circumference.

aT0, baseline; T1, end of three months intervention; T2, three months after end of intervention; P1, Paired T-test for T0 and T1 p-value; P2, Paired T-test for T0 and T2 p-value; P3, Independent T-test for control vs. intervention group.

bSignificant differences at P < 0.05.

The multivariate test results showed significant effects of interaction of time and group for knowledge scores (F = 101.19; P < 0.001), perceived susceptibility (F = 5.01; P = 0.02), self-efficacy (F = 6.18; P = 0.01) and WC (F = 5.643; P = 0.004) (Table 4).

Table 4. Comparison of Knowledge, Health Belief and Anthropometric Measurement Mean Scores Within and Between the Groups From T0 to T2 (n = 90)
VariableTimeGroupTime × Group
FP ValueFP ValueFP Value
Knowledge94.23< 0.001a39.21< 0.001a101.19< 0.001a
Perceived susceptibility6.530.012a4.730.032a5.010.028a
Perceived severity3.740.028a0.980.3250.860.425
Perceived benefits0.330.7212.650.1070.010.986
Perceived barriers5.160.008a10.540.002a0.150.858
Cues to action2.410.0936.030.016a1.0570.350
Self-efficacy0.320.5700.010.9256.180.015a
Weight (kg)3.3420.0710.3020.5843.1510.080
Height (cm)2.5420.0832.4590.1210.3190.574
BMIa z-score0.2490.7800.1860.6681.3010.275
WC (cm)3.0880.048a1.6880.2005.6430.004a

Abbreviation: BMI, body mass index.

aSignificant differences at P < 0.05.

5. Discussion

The results showed that mean changes of knowledge scores and perceived susceptibility between the groups, over time and the interaction of time and group were significant. It means that the educational program had a positive effect on increasing the knowledge and perceived susceptibility of the intervention subjects. This finding is similar to those of Dunn et al. which showed that an educational program resulted in increasing the knowledge of the subjects (23). On the other hand, the significant increase in knowledge score after the intervention program was also reported by other researchers (16, 24, 25).

By increasing the perceived susceptibility in the intervention group, they may be more motivated to change their lifestyle than the control group. Similarly, Diaz et al. showed changes in the behavior of 76 subjects with obesity aged 9 - 17 years after a lifestyle intervention based on the health belief model (26). Some other studies also found similar results. For example, Shariatjafari, et al. and Eisenmann et al. reported significant changes in the perceptions and beliefs of the subjects after the intervention (25, 27). Smalley et al. found that a majority of young people correctly identified obesity and unhealthy diet as risk factors of CVD (28). Some of the young adults and adolescents believed that heart disease prevention is important for them but they did not consider CVD as a threat (29-31). An explanation for these results may be attributed to inadequate knowledge about obesity consequences.

The current study results showed that the scores for perceived severity in the intervention group significantly increased at time T2 compared to T0, but in the control group the difference was not significant. Similar results are reported by Jagadesan et al. in India which showed that the intervention program increased the awareness of serious consequences of obesity among the adolescents (32). In contrast, other studies showed significant increase in scores of perceived severity after the educational intervention (16, 24). A possible explanation for this difference could be the difference in the age of the subjects and the design of the study.

In the current study, the increase in the scores for perceived benefits in the intervention group was greater compared to the control group but the differences were not significant. The increase in the score of perceived benefits in the control group probably was influenced by other sources of information such as media, friends and family members. The results of the current study were similar to those of the study by Calfas et al. (which showed non-significant increase in scores of perceived benefits and barriers of physical activity after a randomized controlled physical activity intervention among young adults (33). In another study, Nejad et al. reported that perceived benefits was a significant predictor of weight reduction behavior among young females with obesity (34). Scores for perceived barriers in the two groups did not show any significant changes, although there was an increasing trend. This result was consistent with the result of a study by Lovell et al. who reported that the perceived barriers was more than the perceived benefits among female students in UK (35). Abood et al. showed that perceived barriers about exercise and consumption of fruit and vegetables decreased after intervention (36). These differences may be attributed to different sample sizes, different age groups, differences in design and differences in instruments used for data collection.

The results showed no significant difference regarding the mean scores of cues-to-action in the intervention group before and after education. It means that the subjects may not accurately rate the importance of a cue to behavior promotion and the intervention program did not have an effect on cues-to-action of the participants. The findings of the current study were similar to those of the study by Kip et al. which showed that contrary to expectations from HBM, young adults who learned that a family member experienced a heart attack or stroke were not more likely to initiate weight loss or physical activity (37). The mean score of perceived self-efficacy in this study significantly increased in the intervention group. It means that subjects in the intervention group were more confident after the educational program to change their dietary habits and physical activity level to promote a healthy lifestyle. The findings are consistent with those of Shariatjafari et al. which showed that the educational intervention significantly increased the self-efficacy of subjects (25). These findings are also similar to the results of other studies which showed that by increasing the level of knowledge, the self-efficacy of the subjects will also increase (38). In the current study an increase in the self-efficacy score in the intervention group may be attributed to an increase in knowledge of the subjects. This is in contrast to the results of the study by Olander et al. who found that a majority of techniques did not have obvious effects on physical activity self-efficacy (39).

In the current study, the mean weight and BMI z-score significantly decreased in the intervention group at times T1 and T2 compared to those of T0. The increase in WC over time was significantly greater for the control subjects compared with the intervention group. The results of previous intervention studies targeting adolescents show larger effects, although these results may not be comparable because of differences in the sample population (26). The results of the current study were in accordance with the effects of two methods of nutritional intervention on weight loss in children with obesity. The mean value of children’s BMI decreased significantly (10). This finding is also consistent with those of the previous studies showing reductions in weight by a 12-week program in children and their families which promoted healthy lifestyle changes, waist circumference and BMI reductions (40). Furthermore, the current study supports other findings by Waling et al. on the effect of a family-based intervention on anthropometric in children with overweight and obesity (41). In a study by Reinehr et al. the lifestyle intervention was associated with a significant improvement of WC (4). In summary, the changes in the anthropometric data suggest that a more intensive intervention program in nutrition and physical activity might achieve more significant outcomes. Furthermore, the subjects in the intervention group had higher WC compared with the control group at baseline. Therefore, subjects in the intervention group may have persistent weight problems and may face many difficulties to lose weight.

The strengths of the present study include the use of randomized clinical trial as the best method to design an intervention study. Besides, it was the first time that this study was conducted in Iran on adolescents with obesity by HBM framework. Moreover, the study subjects participated in the educational classes designed to improve their ability to change their lifestyle by group discussions, which may provide peer support for behavior changes.

The current study had several limitations. As with most studies of this kind, the duration of the present study was short to induce the significant changes in anthropometric measurements. Another limitation was that all analyses were performed on both genders since there were no significant differences in the proportion of girls and boys between the two groups of the study. Finally, results of the present study suggest that longer duration and more different ways of education are needed to have significant behavioral changes in this age group. These findings are useful for further community based intervention to plan and mange obesity in children and adolescents.

Acknowledgements

Footnote

References

  • 1.

    de Onis M, Blossner M, Borghi E. Global prevalence and trends of overweight and obesity among preschool children. Am J Clin Nutr. 2010; 92(5) : 1257 -64 [DOI][PubMed]

  • 2.

    Reinehr T, Wunsch R, de Sousa G, Toschke AM. Relationship between metabolic syndrome definitions for children and adolescents and intima-media thickness. Atherosclerosis. 2008; 199(1) : 193 -200 [DOI][PubMed]

  • 3.

    Ebbeling CB, Pawlak DB, Ludwig DS. Childhood obesity: public-health crisis, common sense cure. Lancet. 2002; 360(9331) : 473 -82 [DOI][PubMed]

  • 4.

    Reinehr T, Kleber M, Toschke AM. Lifestyle intervention in obese children is associated with a decrease of the metabolic syndrome prevalence. Atherosclerosis. 2009; 207(1) : 174 -80 [DOI][PubMed]

  • 5.

    Crocker MK, Yanovski JA. Pediatric obesity: etiology and treatment. Endocrinol Metab Clin North Am. 2009; 38(3) : 525 -48 [DOI][PubMed]

  • 6.

    Mohammadpour-Ahranjani B, Rashidi A, Karandish M, Eshraghian MR, Kalantari N. Prevalence of overweight and obesity in adolescent Tehrani students, 2000-2001: an epidemic health problem. Public Health Nutr. 2004; 7(5) : 645 -8 [PubMed]

  • 7.

    Fappa E, Yannakoulia M, Pitsavos C, Skoumas I, Valourdou S, Stefanadis C. Lifestyle intervention in the management of metabolic syndrome: could we improve adherence issues? Nutrition. 2008; 24(3) : 286 -91 [DOI][PubMed]

  • 8.

    Sinha R, Fisch G, Teague B, Tamborlane WV, Banyas B, Allen K, et al. Prevalence of impaired glucose tolerance among children and adolescents with marked obesity. N Engl J Med. 2002; 346(11) : 802 -10 [DOI][PubMed]

  • 9.

    Kelishadi R, Pour MH, Sarraf-Zadegan N, Sadry GH, Ansari R, Alikhassy H, et al. Obesity and associated modifiable environmental factors in Iranian adolescents: Isfahan Healthy Heart Program - Heart Health Promotion from Childhood. Pediatr Int. 2003; 45(4) : 435 -42 [PubMed]

  • 10.

    Kelishadi R. Childhood overweight, obesity, and the metabolic syndrome in developing countries. Epidemiol Rev. 2007; 29 : 62 -76 [DOI][PubMed]

  • 11.

    Goldstein MG, Whitlock EP, DePue J, Planning Committee of the Addressing Multiple Behavioral Risk Factors in Primary Care P. Multiple behavioral risk factor interventions in primary care. Summary of research evidence. Am J Prev Med. 2004; 27(2 Suppl) : 61 -79 [DOI][PubMed]

  • 12.

    Green JS, Grant M, Hill KL, Brizzolara J, Belmont B. Heart disease risk perception in college men and women. J Am Coll Health. 2003; 51(5) : 207 -11 [DOI][PubMed]

  • 13.

    Flodmark CE, Marcus C, Britton M. Interventions to prevent obesity in children and adolescents: a systematic literature review. Int J Obes (Lond). 2006; 30(4) : 579 -89 [DOI][PubMed]

  • 14.

    Najimi A, Ghaffari M. Promoting fruit and vegetable consumption among students: a randomized controlled trial based on social cognitive theory. J Pak Med Assoc. 2013; 63(10) : 1235 -40 [PubMed]

  • 15.

    Sharifirad G, Najimi A, Hassanzadeh A, Azadbakht L. Does nutritional education improve the risk factors for cardiovascular diseases among elderly patients with type 2 diabetes? A randomized controlled trial based on an educational model. J Diabetes. 2013; 5(2) : 157 -62 [DOI][PubMed]

  • 16.

    Park DY. Utilizing the Health Belief Model to predicting female middle school students' behavioral intention of weight reduction by weight status. Nutr Res Pract. 2011; 5(4) : 337 -48 [DOI][PubMed]

  • 17.

    Painter JE, Borba CP, Hynes M, Mays D, Glanz K. The use of theory in health behavior research from 2000 to 2005: a systematic review. Ann Behav Med. 2008; 35(3) : 358 -62 [DOI][PubMed]

  • 18.

    Harrington DM, Staiano AE, Broyles ST, Gupta AK, Katzmarzyk PT. BMI percentiles for the identification of abdominal obesity and metabolic risk in children and adolescents: evidence in support of the CDC 95th percentile. Eur J Clin Nutr. 2013; 67(2) : 218 -22 [DOI][PubMed]

  • 19.

    Kelishadi R, Ardalan G, Gheiratmand R, Majdzadeh R, Hosseini M, Gouya MM, et al. Thinness, overweight and obesity in a national sample of Iranian children and adolescents: CASPIAN Study. Child Care Health Dev. 2008; 34(1) : 44 -54 [DOI][PubMed]

  • 20.

    Kartal A, Ozsoy SA. Validity and reliability study of the Turkish version of Health Belief Model Scale in diabetic patients. Int J Nurs Stud. 2007; 44(8) : 1447 -58 [DOI][PubMed]

  • 21.

    Bond GG, Aiken LS, Somerville SC. The health belief model and adolescents with insulin-dependent diabetes mellitus. Health Psychol. 1992; 11(3) : 190 -8 [PubMed]

  • 22.

    Kelishadi R, Cook SR, Motlagh ME, Gouya MM, Ardalan G, Motaghian M, et al. Metabolically obese normal weight and phenotypically obese metabolically normal youths: the CASPIAN Study. J Am Diet Assoc. 2008; 108(1) : 82 -90 [DOI][PubMed]

  • 23.

    Dunn SM, Beeney LJ, Hoskins PL, Turtle JR. Knowledge and attitude change as predictors of metabolic improvement in diabetes education. Soc Sci Med. 1990; 31(10) : 1135 -41 [PubMed]

  • 24.

    Sharifirad G, Entezari M, Kamran A, Azadbakht L. The effectiveness of nutritional education on the knowledge of diabetic patients using the health belief model. J Res Med Sci. 2009; 14(1) : 1 -6

  • 25.

    Shariatjafari S, Omidvar N, Shakibazadeh E, Majdzadeh R, Minaei M, Gholamzade M. Effectiveness of Community-based Intervention to Promote Iran's Food-based Dietary Guidelines. Int J Prev Med. 2012; 3(4) : 249 -61 [PubMed]

  • 26.

    Diaz RG, Esparza-Romero J, Moya-Camarena SY, Robles-Sardin AE, Valencia ME. Lifestyle intervention in primary care settings improves obesity parameters among Mexican youth. J Am Diet Assoc. 2010; 110(2) : 285 -90 [DOI][PubMed]

  • 27.

    Eisenmann JC, Gundersen C, Lohman BJ, Garasky S, Stewart SD. Is food insecurity related to overweight and obesity in children and adolescents? A summary of studies, 1995-2009. Obes Rev. 2011; 12(5) -83 [DOI][PubMed]

  • 28.

    Smalley SE, Wittler RR, Oliverson RH. Adolescent assessment of cardiovascular heart disease risk factor attitudes and habits. J Adolesc Health. 2004; 35(5) : 374 -9 [DOI][PubMed]

  • 29.

    Vanhecke TE, Miller WM, Franklin BA, Weber JE, McCullough PA. Awareness, knowledge, and perception of heart disease among adolescents. Eur J Cardiovasc Prev Rehabil. 2006; 13(5) : 718 -23 [DOI][PubMed]

  • 30.

    Vale A. Heart disease and young adults: is prevention important? J Community Health Nurs. 2000; 17(4) : 225 -33 [DOI][PubMed]

  • 31.

    Collins KM, Dantico M, Shearer NB, Mossman KL. Heart disease awareness among college students. J Community Health. 2004; 29(5) : 405 -20 [PubMed]

  • 32.

    Jagadesan S, Harish R, Miranda P, Unnikrishnan R, Anjana RM, Mohan V. Prevalence of overweight and obesity among school children and adolescents in Chennai. Indian Pediatr. 2014; 51(7) : 544 -9 [PubMed]

  • 33.

    Calfas KJ, Sallis JF, Nichols JF, Sarkin JA, Johnson MF, Caparosa S, et al. Project GRAD: two-year outcomes of a randomized controlled physical activity intervention among young adults. Graduate Ready for Activity Daily. Am J Prev Med. 2000; 18(1) : 28 -37 [PubMed]

  • 34.

    Nejad LM, Wertheim EH, Greenwood K. Comparison of the health belief model and the theory of planned behavior in the prediction of dieting and fasting behavior. Sensoria J Mind Brain Culture. 2005; 1(1) : 63 -74

  • 35.

    Lovell GP, El Ansari W, Parker JK. Perceived exercise benefits and barriers of non-exercising female university students in the United Kingdom. Int J Environ Res Public Health. 2010; 7(3) : 784 -98 [DOI][PubMed]

  • 36.

    Abood DA, Black DR, Feral D. Nutrition education worksite intervention for university staff: application of the health belief model. J Nutr Educ Behav. 2003; 35(5) : 260 -7 [PubMed]

  • 37.

    Kip KE, McCreath HE, Roseman JM, Hulley SB, Schreiner PJ. Absence of risk factor change in young adults after family heart attack or stroke: the CARDIA Study. Am J Prev Med. 2002; 22(4) : 258 -66 [PubMed]

  • 38.

    Choi IS, Ro HK. A comparison study on middle school students of Gwangju and Jeonnam in terms of dietary behavior, body perception and weight control concerns according to BMI. J Korean Soc Food Sci Nutr. 2010; 39(3) : 383 -91

  • 39.

    Olander EK, Fletcher H, Williams S, Atkinson L, Turner A, French DP. What are the most effective techniques in changing obese individuals' physical activity self-efficacy and behaviour: a systematic review and meta-analysis. Int J Behav Nutr Phys Act. 2013; 10 : 29 [DOI][PubMed]

  • 40.

    Joosse L, Stearns M, Anderson H, Hartlaub P, Euclide J. Fit Kids/Fit Families: a report on a countywide effort to promote healthy behaviors. WMJ. 2008; 107(5) : 231 -6 [PubMed]

  • 41.

    Waling M, Backlund C, Lind T, Larsson C. Effects on metabolic health after a 1-year-lifestyle intervention in overweight and obese children: a randomized controlled trial. J Nutr Metab. 2012; 2012 : 913965 [DOI][PubMed]

  • COMMENTS

    LEAVE A COMMENT HERE: