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ORIGINAL ARTICLE
Year : 2019  |  Volume : 22  |  Issue : 8  |  Page : 1070-1077

Prevalence of obesity among adolescents in Eastern Turkey: A cross-sectional study with a review of the local literature


Department of Public Health, Atatürk University Medical Faculty, Erzurum, Turkey

Date of Acceptance06-Jun-2019
Date of Web Publication14-Aug-2019

Correspondence Address:
Prof. S Yilmaz
Atatürk Üniversitesi, Tıp Fakültesi, Morfoloji Binası, Halk Sağlığı Anabilim Dalı, Yakutiye, Erzurum
Turkey
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/njcp.njcp_418_18

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   Abstract 


Background: The World Health Organization defines obesity as an abnormal or excessive fat accumulation that can damage health. Aims: This study aims to evaluate the prevalence of obesity and risk factors in high school students in Erzurum City Center. Study Design and Methods: A cross-sectional study was conducted. The number of students participating in the study was 845, including 47.6% females and 52.4% males. Data collection was done by surveys filled in under supervision. Anthropometric measurements were performed by the researchers. Predictions of the Extended International Obesity Task Force were used for body mass index. Parents' body mass indexes were calculated by self-report and classified according to cut-off points for adults in the world health community. A systematic review of the local literature published between 2004 and 2013 was drafted. Results: In girls and boys, the frequency of overweight was 26.9% and 25.7%, respectively, while the frequency of obesity was 12.4% and 9.5%. A logistic regression analysis was performed to reveal significant risk factors for overweight/obesity. Weekly exercise status [odds ratio = 3.0, 95% confidence interval CI (1.2–7.8)] and school transfer % CI = (1.1–7.2) were important independent risk factors for obesity. The local literature showed a 4.3-fold increase in the prevalence of obesity within 10 years. Conclusion: The prevalence of obesity and overweight in adolescents requires the implementation of effective programs to fight this epidemic. Health education targeting peers and their parents, peer education, screening of risk groups, and controlling the sale of unhealthy foods can be some interventions.

Keywords: High school students, obesity, overweight, prevalence, risk factors


How to cite this article:
Yilmaz S, Calikoglu E O, Kosan Z. Prevalence of obesity among adolescents in Eastern Turkey: A cross-sectional study with a review of the local literature. Niger J Clin Pract 2019;22:1070-7

How to cite this URL:
Yilmaz S, Calikoglu E O, Kosan Z. Prevalence of obesity among adolescents in Eastern Turkey: A cross-sectional study with a review of the local literature. Niger J Clin Pract [serial online] 2019 [cited 2019 Oct 15];22:1070-7. Available from: http://www.njcponline.com/text.asp?2019/22/8/1070/264414




   Introduction Top


According to the World Health Organization (WHO), obesity is defined as an abnormal or excessive fat accumulation with a body mass index (BMI) of 30 kg/m 2 or higher, while BMI values between 25 and 30 kg/m 2 identify overweight (OW).[1] Between 1980 and 2008, age-standardized mean BMI globally increased by 0.4 kg/m 2 per decade for men and 0.5 kg/m 2 per decade for women.[2] In other words, worldwide over 340 million children and adolescents age 5–19 years were OW or obese in 2016.[1],[3]

According to TEKHARF,[4] the first population-based study in Turkey, the prevalence of obesity was about 19% in 1990 and 22% in 2000 with a 36% increase among women and 75% increase among men over the 10 years. On the other hand, the obesity prevalence calculated as 22% in the TURDEP I study conducted in 1998 increased by 32% after 12 years as to the TURDEP II study.[5]

Although there is no countrywide representative study investigating the prevalence of adolescent obesity in Turkey, studies conducted at local and regional scale report a rise in the frequency of obesity in children during the past 20 years from 7% to 16%.[5] According to the results of the Turkey Demographic and Health Survey conducted in 2013, proportions for OW and obesity among women age 15–49 years were reported as 29% and 27%, respectively.[6]

Given that obesity is a preventable disease, measures for its treatment and avoidance emerge as essential entities. However, of the same importance is the surveillance of the condition, which is crucial for policy planning and mobilization of resources. Besides, inappropriate nutritional behaviors acquired during adolescence can be permanent during the later life and cause complications such as diabetes mellitus and cardiovascular morbidity.[7] Hence, we decided to do a survey to collect reliable and current data for our region. Thus, we expect to have up-to-date figures for the condition in our region. This study aimed to reveal the prevalence of obesity and risk factors among students at the age of high school in the provincial center of Erzurum and make comparisons after reviewing the available recently published local data.


   Methods Top


This study was carried out between September and December 2013 among the high school students in the Erzurum province center. For this descriptive cross-sectional study, written permission was obtained from Atatürk University Medical Faculty Ethics Board (date: 02/09/2013, Ref.: 34) and Erzurum Governorship National Education Directorate (date: 13/11/2013, Ref.: 3351375).

Sampling

As to the information obtained from the Erzurum Provincial National Education Directorate, there were 56 high schools in the city center with 25,552 students studying during the year 2013. Taking the expected prevalence as 15% and margin of error as 3%, a sample size of 745 participants is needed to survey a population of the given size with a confidence level of 98%. Expecting a 15%–20% nonresponse rate, we aimed to reach a sample of 911 participants. Stratified according to the total number of students in each school, the sample was withdrawn from three randomly selected schools. By further stratification according to the study grade and sex, the total number of students to be included from each sex and 9th, 10th, 11th, and 12th grades (age 14–18 years) was determined. Students to be invited were randomly selected using the attendance sheets obtained from the principals. Data for 66 selected students could not be included (32 absent, 29 rejected, 5 inadequate data collection) leading to a response rate of 92.7%.

Study questions

The survey questions were prepared after a vigorous literature review and seeking expert opinions. Data were obtained for the following variables: height, weight, age, sex, education status of parents, parental employment status, monthly family income, number of daily meals, fast food habits, the type of food snacks eaten, time spent with computer or TV, smoking status, weakly exercise status, and type of transport to school. The main study hypothesis was that none of the studied variables was related to the prevalence of obesity.

Data collection

A workshop was organized with the participation of all researchers to standardize data collection. The study questionnaire consisted of 41 items under 14 headings. The questionnaire included 16 items related to the sociodemographic characteristics of the participants and 25 items related to their nutritional habits and physical activity status. Students were invited to a quiet room to fill the questionnaire under supervision. Informed consent forms were distributed with the help of school administrations before data collection and returned at the time of the survey. Together with the consent forms, data on the heights and weights of the parents were obtained by self-report. Each school was visited twice to allow participation of students who were not available in the first instance. Anthropometric measurements were done by the researchers.

Anthropometric measurements

One F. Bosch branded 0.1-kg-precision digital scale and a Seca branded stadiometer were used for measurements. The weights were measured with light clothes, without shoes, each student standing in the center of the scale, which was reset before every measurement. Height measurements were made by a stadiometer lightly pressing on the head, with the feet parallel, heels kept together, and the back of the head and the heels in contact with the wall. The results were recorded on the questionnaires as kilograms and centimeters.

After the measurements, the BMI (expressed as kg/m 2) was calculated for each student. For BMI classification, age- and sex-specific extended International Obesity Task Force (IOTF) BMI cut-offs for low weight (LW), OW, and obesity were used. Students who were below the 5th percentile were categorized as LW, 55th–84th percentile as normal weight (NW), 85th–94th percentile as OW, and those at 95th percentile and above as obese. BMI values of student parents were grouped on the basis of WHO's international obesity classification scheme for adults (BMI 25 kg/m 2 and above as OW and BMI 30 kg/m 2 and above as obese).[8]

Literature review

A systematic literature review was done, aiming to include published research on obesity prevalence among adolescents conducted in Turkey. For this purpose, the Turkish electronic database archives of ULAKBIM, the Turkish Academic Network and Information Center (http://uvt.ulakbim.gov.tr/uvt/index.php), and Google Scholar (https://scholar.google.com/) were searched with the search terms both in Turkish [(obezite, OR obesite OR şişmanlık) AND ergenlik AND (prevalans OR yaygınlık)] and in English [obesity AND adolescence AND prevalence AND Turkey], which revealed 35 articles. The query was limited to the recent 10 years covering 2004–2013 (both inclusive). Studies conducted in Turkey and covering an age group of 5–18 years were included. Of the retrieved articles, three were discarded due to being not relevant and another four not meeting our sample criteria. From the remaining 28 studies, 26 could be accessed and summarized.

Statistical analysis

Data analysis was done by Statistical Package for the Social Sciences (SPSS v20) for Windows. Categorical variables were expressed as numbers and percentage, while numerical variables were presented as mean and standard deviations. Normal distribution of the numerical variables was checked with Kolmogorov–Smirnov test. Due to the few cases in the LW group, the LW and NW groups were merged during the analysis. For the bivariate comparisons, the one-way analysis of variance (ANOVA), Student's t-test, Pearson's correlation, and Chi-square tests were used for numerical and categorical data, respectively. A binary logistic regression analysis was performed to search the effects of the independent variables on OW and obesity. In the regression model, OW and obese students were combined under the same group. The OW and obesity risk factors that met the condition of P < 0.1 were included in the regression model, which was done using the backward elimination method. The level of statistical significance was accepted at P < 0.05.


   Results Top


Data for 845 students were analyzed. Of the participants, 47.6% (n = 402) were female and 52.4% (n = 443) were male. The mean age of the students was 15.9 ± 1.2 years. According to the growth reference values determined by the IOTF for children and adolescents, 4.7% (n = 40) of the students were LW, 26.3% (n = 222) were OW, and 10.8% (n = 91) were obese. The changes in BMI according to age and gender of the students participating in the survey are presented in [Table 1].
Table 1: BMI groups compared to age and sex

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Seventy-four participants (10.0%) were smokers, and 96 participants (37.8%) were exercising at least three times a week. The mean daily time spent with computer and TV was 1.8 ± 1.2 and 2.0 ± 1.1 h, respectively. Compared with smokers, nonsmokers were significantly more OW (26.5%; n = 177 vs. 16.2%; n = 12) and obese (13.6%; n = 91 vs. 8.1%; n = 6) (Chi-square = 7.068; P = 0.029). Compared with less exercisers, those exercising three or more times a week had significantly lower OW (17.7%; n = 17 vs. 24.7%; n = 39) and obesity (5.2%; n = 5 vs. 13.9%; n = 22) (Chi-square = 7.769; P = 0.021). There was a weak but significant correlation between the participants' BMI and daily time spent with computers (Pearson's r = 0.083; P = 0.037). About 29.6% of the students (n = 250) were walking to school, while the rest were using some kind of transfer. The walkers had significantly less OW (21.2%; n = 53 vs. 27.7%; n = 165) and obesity (8.8%; n = 22 vs. 14.1%; n = 84) compared with the others (Chi-square = 10.887; P = 0.004). The majority of participants (78.9%; n = 662) were regular fast food consumers. The difference in the prevalence of OW (26.0%; n = 172 vs. 23.7%; n = 42) and obesity (13.9%; n = 92 vs. 7.3%; n = 13) among students consuming and not consuming fast food was significant (Chi-square = 6.818; P = 0.033).

About 76.3% (n = 621) of the students had three main meals per day, while 23.7% (n = 193) had two main meals. OW (31.1%; n = 60) and obesity (20.7%; n = 40) prevalence was significantly higher in students having two main meals compared with those having three main meals (24.2%; n = 210 and 10.0%; n = 62, respectively) per day (Chi-square = 23.760; P < 0.001). The most frequent type of snack food was potato chips (27.6%; n = 172). OW and obesity prevalence of students consuming daily potato chips, nuts, coffee, pasta, tea, and soda were (34.3%; n = 59) versus (16.3%; n = 28), 32.7% (n = 34) versus 13.5% (n = 14), 21.2% (n = 24) versus 7.1% (n = 8), 26.6% (n = 21) versus 12.7% (n = 10), 16.5% (n = 17) versus 6.8% (n = 7), 28.3% (n = 15) versus 15.1% (n = 8), respectively. Prevalence of OW and obesity was higher among students who ate potato chips as snacks compared with other snack types (Chi-square = 29.161; P = 0.001).

Most of the mothers (46.7%; n = 395) were primary school graduates, while most of the fathers were high school graduates (31.6%; n = 264). There was no statistically significant difference in the obesity status of the participants concerning the educational status of mothers (Chi-square = 8.300; P = 0.405) or fathers (Chi-square = 1.953; P = 0.982). The obesity frequency among the students' mothers and fathers was 26.6% (n = 225) and 19.3% (n = 163), respectively. The BMI of the participants was related to the obesity status of parents [ANOVA, F = 15.997; P < 0.001; [Figure 1].
Figure 1: The relationship between parental obesity and BMI levels

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Of the mothers, 88.3% (n = 746) were housewives and 8% (n = 68) government employees. There was no statistically significant difference in the BMI categories concerning mothers employment (Chi-square = 5.854; P = 0.664). Fathers of most of the students were government officers (32.2%; n = 272). Of the remaining fathers, 18.1% (n = 153) were self-employed, and 24.6% (n = 208) were from other professions. There was no statistically significant difference in the BMI categories concerning fathers' employment (Chi-square = 12.517; P = 0.051). Of the families, 13.9% (n = 116) had a monthly income of 1000 TL or less (around 555 USD), while 24.5% (n = 205) had an income of 3001 TL and more (around 1666 USD). The mean BMI levels were increasing with the income [Figure 2]. There was a statistically significant relationship between the monthly income levels of the families and the BMI levels of the students (ANOVA, F = 2.915; P = 0.034).
Figure 2: The relationship between the monthly income of the family and BMI levels

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To evaluate the independent effects of the studied variables on obesity, a logistic regression analysis using the Enter method was performed. Variables entered into the model were the smoking status of the student (smoker/nonsmoker), exercise status (three or more per week/less than three per week), type of transport to school (walking/some vehicle), fast food habits (yes/no), number of meals per day (two/three), snacks (potato chips/other), obesity status of parents (none/mother/father/both parents), and monthly income of the family (<1000 TL/1001–2000 TL/2001–3000 TL/>3000 TL). Weekly exercise status [odds ratio (OR) =3.0, 95% confidence interval (CI) (1.2–7.8)] and transfer to the school (OR = 2.8, 95% CI = 1.1–7.2) revealed as the only significant independent factors predicting obesity.

The local literature review for Turkey, including the years 2004 and 2013, demonstrated regional differences of OW and obesity within Turkey. Obesity prevalence of as high as 12.7% (Izmir, 2013) or as low as 0.9% (Diyarbakır, 2004) and OW prevalence as high as 26.3% (Erzurum, 2013) or as small as 2.1% (Diyarbakır, 2004) were reported [Table 2], [Figure 3]. More in-depth investigation of [Table 2] and [Figure 3] suggests a combined effect of regional and time differences on obesity. While western and wealthier cities such as Edirne and İzmir show higher percentages, the prevalence also increased 4.3-fold within 10 years from a mean value of 2.7 in 2004 to a mean of 11.8 in 2013 [Figure 4].
Table 2: Review of local literature on OW and obesity published in Turkey

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Figure 3: Distribution of obesity prevalence in different provinces of Turkey. *No data available for the year 2012

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Figure 4: Mean obesity prevalence according to publication years (derived from Table 2)

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   Discussion Top


This study has revealed 26.3% OW and 10.9% obesity prevalence among adolescents age 14–18 years in Erzurum.

Obesity is regarded as a global epidemic by today's international health authorities and poses a significant danger to the future of societies by causing systemic diseases and deaths. Thus, the number of childhood obesity surveys has increased parallel to the importance of the subject. However, there are problems in comparison of the studies conducted among children regarding the dates of the investigations, the age groups they cover, diagnostic methods used, and the differences in the classification criteria.[34]

According to global obesity research on adolescents, the prevalence of OW and obesity varies between 9% and 35.8% and 1.9% and 20.5%, respectively. The OW prevalence in our study was higher than other earlier studies reported from Turkey. Furthermore, our OW frequency was lower than those reported from some countries [34],[35] but higher than others.[36],[37]

When we compare our results with a previous similar study done by Turgut [19] in the same region in 2007 on adolescents age 6–15 years, considering the time and age group differences, we may conclude that there is a rise in obesity prevalence. This increase may be due to regional–cultural factors such as changes in sedentary lifestyles due to improvement in socioeconomic conditions and an increase in unbalanced nutritional behavior, as well as decreased physical activity in the students. Furthermore, differences between the study results may be due to the classification methods used.

There is no consensus in the literature about the gender differences in OW and obesity among adolescents. While reports are stating higher prevalence among males,[38] others reported higher obesity frequency among girls,[36] and even others claimed that there is no difference.[39] Similar disagreement exists for economic status and obesity. The meta-analysis of Wang [7] suggested that high-income American girls had low BMI, while high-income Russian girls and high-income Chinese boys had higher BMIs. On the other hand, according to the study of O'Dea and Dibley [37] in Australia, it was determined that the mean BMI in adolescents decreased as the socioeconomic status (SES) increased. Apparently, the effect of parental education on obesity is sustained between cultures. Studies from the United States,[40] Germany,[41] and South Korea [42] all reported a decrease in the frequency of OW/obesity in children with increased parental education.

The literature on the relationship between parental employment and obesity shows a decrease in the mean BMI of adolescents with parental vocation.[40] Also, Noh et al.[42] reported that OW/obesity prevalence among children with working mothers was lower than those of nonworking mothers, but fathers' working status did not have such an effect. According to the meta-analysis of O'Dea and Dibley [37] in Australia, OW/obesity prevalence was reported as 29.4% among children with low SES, compared with 20.8% in high SES.

The relationship between genetic factors and obesity is well known. Research in twins and high prevalence in some ethnic groups [43] have demonstrated that children have BMI levels similar to their parents. Of course, besides genetics, also cultural factors may be related to these findings. The results of our study are comparable in the sense that the presence of obesity in the parents is a risk factor for adolescent obesity.

According to a study by Davis andCarpenter [44] in the United States in 2009, the frequency of OW/obesity was significantly higher among adolescents with fast food restaurants near their schools. In an international cross-sectional study on adolescents conducted by Braithwaite et al.[45] involving 36 countries, often and very often fast food consumption was associated with increased BMI in children. The relationship between fast food consumption and obesity may be due to its high energy content, refined carbohydrates, exogenously added simple sugars, and high-fat content. The results of our study are similar to national and international studies and indicate that fast food consumption increases the frequency of OW/obesity.

In our study, the frequency of OW/obesity was significantly lower among participants walking to school with a 2.8-times increased risk of OW/obesity among students transported by a vehicle. We also found that exercising three times a week was preventive from OW/obesity. Thibault et al.[46] found no significant difference regarding BMI distributions between those adolescents with less than 1 h of physical activity per day and those who had more physical activity. However, in the same study, there was a significant difference between cases with less than 22 h of weekly sedentary activity and those with more than 22 h per week regarding mean BMI values. Hence, we assume that low-level exercise in adolescents is not a sufficient protection of obesity in adolescents. Public health measures should include more vigorous and sustained exercise programs.

Our study demonstrates that obesity in adolescents is a serious free public health problem. To combat this health epidemic, first, there is a need for health education programs integrated into school health activities that will ensure healthy living in the whole society, especially among adolescents. Families with obesity in the first-degree relatives should be screened by family physicians and parents should be provided with tailored training programs on obesity to establish healthy lifestyle consciousness. Educational programs and practices are needed to warrant that meals are regular and healthy for students spending most of their times outside the home. Also, controlling the sale of carbonated beverages and foods with a high glycemic index or excessive fat in school canteens may be useful in combating obesity. Nowadays, the society should also be conscious about the damages of fast food eating habits spreading at high speed, and necessary measures should be taken by the administrations to keep such businesses away from school environments in particular. Restrictions on fast food advertising can also be useful in preventing adolescent unhealthy eating behaviors.

The literature review for Turkey supports our findings that obesity should be one of the priority public health concerns for this country. If the trend in obesity prevalence continues to increase as it did, obesity-related diseases such as cardiovascular problems, hypertension, and stroke will multiply soon. It is imperative that the changes in the active lifestyles in the prevention and treatment of obesity are passed on to generations. For this reason, parents should be role models, and students should be encouraged to walk to their schools at short distances and encouraged to engage in sports activities. In addition, the reduced public exercise areas because of rapid urbanization should be restored. Finally, yet importantly, the use of peer education primarily to direct adolescents to various social activity programs to use spare time will reduce the exposure to mobile phones, computers, and television, also keeping them away from being exposed to unhealthy food advertisements.

Some limitations of this study can be mentioned as follows: the data on parent BMI values were collected through self-report, which reduces its reliability from this perspective. Also, the long gap between study conduction and publication is a limitation, which resulted from chronic health issues of the primary author.


   Conclusion Top


The prevalence of obesity and overweight in adolescents requires the implementation of effective programs to fight this epidemic. Health education targeting peers and their parents, peer education, screening of risk groups, and controlling the sale of unhealthy foods can be some interventions.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2]



 

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