|Year : 2015 | Volume
| Issue : 6 | Page : 729-733
Study of clinical parameters and laboratory evaluation of metabolic syndrome in adolescents
Ayesha Imran, Nitin Avinash Yelikar, Sharad Agarkhedkar, Shailaja Mane
Department of Paediatrics, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
|Date of Web Publication||19-Nov-2015|
Department of Paediatrics, Dr. D. Y. Patil Medical College and Hospital, Pimpri, Pune, Maharashtra
Source of Support: None, Conflict of Interest: None
Introduction: Worldwide incidence of obesity is rising. Genetic predisposition, urbanization, sedentary lifestyle, television watching, food habits, and lack of exercise are contributing factors. They result in obesity-related morbidity like metabolic syndrome, stroke in young, coronary artery disease, and diabetes. Materials and Methods: A cross-sectional study was undertaken among 1000 adolescents of both genders, aged 12-19 years in three schools of Pimpri, Pune, after obtaining approval from Institutional Ethical Committee. The criterion used to diagnose metabolic syndrome was International Diabetes Federation definition. The Chi-square test was used to explore the association between metabolic syndrome and various predictors. A P value of 0.05 was accepted as the level of statistical significance. Results: In the study sample, the prevalence of metabolic syndrome was 16/1000. Females were more likely to have metabolic syndrome (male:female = 7:9). Factors associated were body mass index (BMI), waist-hip ratio (WHR), birth weight, skin fold thickness, body fat percentage, faulty dietary habits, and sedentary lifestyles (P < 0.05). Among all, the components of metabolic syndrome, raised triglyceride (75%), and fasting blood sugar level (75%) were more prevalent than high-density lipoprotein-cholesterol (44%) and hypertension (37.5%). Conclusion: Metabolic syndrome was found to be more prevalent in females of age group 16-19 years, among the obese population, associated with birth weight, BMI, and WHR.
Keywords: Adolescents, body mass index, metabolic syndrome, obesity
|How to cite this article:|
Imran A, Yelikar NA, Agarkhedkar S, Mane S. Study of clinical parameters and laboratory evaluation of metabolic syndrome in adolescents. Med J DY Patil Univ 2015;8:729-33
|How to cite this URL:|
Imran A, Yelikar NA, Agarkhedkar S, Mane S. Study of clinical parameters and laboratory evaluation of metabolic syndrome in adolescents. Med J DY Patil Univ [serial online] 2015 [cited 2020 Dec 1];8:729-33. Available from: https://www.mjdrdypu.org/text.asp?2015/8/6/729/167982
| Introduction|| |
Adolescence is the critical period of transition from childhood to adulthood characterized by rapid growth and development. With rapid urbanization, subsequent generations are adopting unhealthy lifestyles. They are more sedentary, lack exercise, and consume energy-rich diet. All these factors predispose to obesity. 
Childhood obesity affects all major organ systems of the body. It is associated with significant morbidity and mortality. Brahmbhatt and Oza  conducted a cross-sectional study among 900 adolescents in Ahmedabad and concluded that the prevalence of overweight was more than obesity. Jan Mohamed et al.  reported a higher prevalence of metabolic syndrome among females. Other workers reported a higher prevalence of metabolic syndrome in males. , Singh et al.  demonstrated metabolic syndrome in overweight, obese, and normal adolescents, Cook et al.  demonstrated it in overweight and obese. Mehairi et al.  found that it was associated with the increased body mass index (BMI). Agirbasli et al.  found that BMI was the only significant predictor for metabolic syndrome among skin fold thickness (SFT), BMI, waist circumference (WC), and waist-hip ratio (WHR). Tandon et al.  observed that most common component was central obesity, followed by hypertriglyceridemia, low high-density lipoprotein-cholesterol (HDL-C), hypertension, and dysglycemia.
These investigators did not include SFT as a measure of obesity. They also did not include family history and dietary questionnaires in their study. Although these are not relevant for making the diagnosis of the metabolic syndrome, we included them in our study.
| Materials and Methods|| |
A cross-sectional study was carried out among selected school going children of both genders who were between 12 and 19 years of age. The study sample included 500 male and 500 female students.
The study protocol was approved by the Institutional Ethical Committee. Permission of the principals of the three schools visited was also obtained.
Screening of adolescents was done in three schools of Pimpri area, an industrial township in Pune District. After screening for overweight and obesity, further investigations were done at a teaching hospital in Pimpri area.
A pretested study instrument was used in the study. Blood pressure (BP), weight, height, SFT, WC, hip circumference, and birth weight (obtained by recall) body mass index (BMI)  of all the adolescents were recorded.
After this initial screening, those found to be overweight and obese were contacted telephonically. They were called at the pediatric out-patient department with their parents after fasting for 10 h for further investigations (blood sugar level [BSL], lipid profile). The family history of diabetes and hypertension was recorded.
SFT measured on triceps muscle with Harpenden Caliper. SFT <5 th percentile was used for defining thinness, and >85 th percentile was used for defining obesity. 
WHR calculated using waist and hip circumference. WHR ≥0.95 in males and ≥0.8 in females was considered as obesity. 
Body fat percentage  >25% in males and >33% in females was classified as obesity.
Data were analyzed by Statistical Package for Social Sciences software (IBM Corp., Armonk, New York, USA). The Chi-square test was used to find correlation. A P value of 0.05 was accepted as the level of statistical significance.
The criterion used to diagnose metabolic syndrome was International Diabetes Federation definition. 
For 10-16 years:
- Obesity (WC) ≥90 th percentile or adult cut-off if lower
- Triglyceride ≥150 mg/dl
- HDL-C ≤40 mg/dl
- Systolic ≥130/diastolic ≥85 mmHg
- Glucose 100 mg/dl
For >16 years:
- Central obesity (WC >94 cm)
- Plus any two of the following four factors:
- Raised triglyceride ≥150 mg/dl
- Reduced HDL-C <40 mg/dl in males and <50 mg/dl in females
- Raised BP: Systolic = 130 or diastolic = 85 mmHg or treatment of previously diagnosed hypertension
- Impaired fasting glucose ≥100 mg/dl, or previously diagnosed type 2 diabetes.
Questionnaire to elicit lifestyle
The questionnaire used to elicit certain lifestyle factors is given in Appendix 1.[Additional file 1]
| Results|| |
Totally, 1000 adolescents were screened for overweight and obesity. Maximum number of adolescents 644 (64.4%) were in the age group of 12-16 years, of which 260 (40.37%) were males and 384 (59.63%) were females. In the age group 16-19 years, 356 adolescents were screened, of which 240 (67.42%) were male and 116 (32.58%) were females.
Mean BMI was found to be 25.23 ± 3.48 in overweight and 30.25 ± 3.52 in obese. The prevalence of overweight and obesity is shown in [Table 1]. Metabolic syndrome was more in adolescents in the older age group [Table 2].
|Table 1: Prevalence of overweight and obese adolescents according to age|
Click here to view
The prevalence of metabolic syndrome was 16 in 1000 (1.6%). It was 7 in 500 (1.4%) males and 9 in 500 (1.8%) females.
Maternal history of diabetes was present in 43 of 1000 (4.3%) adolescents, in which 10 of 16 (62.5%) adolescents had associated metabolic syndrome. Metabolic syndrome was also associated with birth weight more than or equal to 3.5 kg, WHR was raised in 15 (93.75%) out of 16 adolescents with metabolic syndrome which was statistically significant (P < 0.001). In addition to BMI, WHR, body fat percentage, and SFT were associated with metabolic syndrome. High triglyceride and fasting BSL (92.31%) were the most common components, whereas high BP (46.15%) was the least common component of metabolic syndrome.
Lifestyle factors such as television/computer viewing, lack of exercise, sleeping habits, and consumption of fast foods and cold drinks with high sugar content were strongly associated with metabolic syndrome [Table 3].
In the present study, the prevalence of overweight was more than obesity which was comparable to the study of Brahmbhatt and Oza. 
The prevalence of metabolic syndrome was found to be 1.6% as the study population belongs only to three schools of Pimpri area. The prevalence was more in females. A similar observation was reported by Singh et al.  Jan Mohamed et al.  reported the overall prevalence of metabolic syndrome as 37.5% which was higher among females. On the other hand, Cook et al.  and Mehairi et al.  noted that the prevalence of metabolic syndrome was more in males.
Metabolic syndrome was more prevalent in age 16-19 years as compared to 12-16 years, which was similar to study done by Singh et al. 
In this study, metabolic syndrome was found only in the obese population. On the contrary, few studies noted its presence in both overweight and obese adolescents; Singh et al.  demonstrated it in 36.6% of overweight adolescents, 11.5% of at risk for overweight, and 1.9% of the remaining normal weight. Cook et al.  found metabolic syndrome in 28.7% of overweight and 6.8% of at-risk overweight subjects.
The prevalence of metabolic syndrome increased with increase in BMI and was comparable to the study done by Mehairi et al. 
Intrauterine events and factors during early developmental years predispose a child to various diseases like obesity, metabolic syndrome. The presence of family history of diabetes contributes to child's future level of risk.  A study done by Ghosh et al.  showed that people with a moderate family risk of diabetes and people with a high family risk of diabetes were likely to develop metabolic syndrome. Das et al.  also found that a family history of diabetes was more prone to metabolic syndrome.
We found an association of birth weight on the higher side with metabolic syndrome. Similar observations were made by Boney et al.  On the contrary, Silveira and Horta  showed that lower birth weight is a higher risk for metabolic syndrome in young adults.
Besides BMI, we found the relation among the WHR, body fat percentage, and SFT with metabolic syndrome was also found in the present study. Agirbasli et al.  concluded that among SFT, BMI, WC, WHR categories, BMI was the only significant predictor.
When criteria for metabolic syndrome were compared, 18.75% cases of the metabolic syndrome were in the age group 12-16 years. All five criteria of metabolic syndrome (obesity >95 th percentile, triglyceride ≥150 mg/dl, HDL-C ≤40 mg/dl, fasting BSL >100 mg/dl, and BP ≥130/85) were present in them.
Whereas in age group 16-19 years, 92.31% of the cases of metabolic syndrome had triglyceride ≥150 mg/dl and fasting BSL >100 mg/dl, while 53.85% had HDL-C ≤40 mg/dl and 46.15% had BP ≥130/85 mmHg. In our study, high triglyceride and fasting BSL were the most common components in metabolic syndrome and high BP was the least common component. Among adolescents with metabolic syndrome, 92.31% adolescents had at least one and 53.85% had two lipid abnormalities. The observations were comparable to study done by Tandon et al.  who observed that most common component was central obesity, followed by hypertriglyceridemia, low HDL-C, hypertension, and dysglycemia.
Park et al.  found that low HDL-C level was the most common component for the metabolic syndrome, and nearly 20% of adolescents had at least one lipid abnormality. Rizzo et al.  observed that most prevalent risk factors were abdominal circumference ≥90 th percentile, HDL <40 mg/dl, high BP ≥130/85 mm/Hg, triglycerides ≥150 mg/dl, and fasting glycemia ≥100 mg/dl.
Adolescents who used media for more than 4 h, perform physical exercise <4 h and spend more than 10 h a day in sleeping were more likely to have metabolic syndrome. Junk food, sweets, soft were also associated with risk of metabolic syndrome. Mehairi et al.  also observed that boys who were overweight or spend more than 2 h in front of a screen in a day were more likely at the risk. Malik et al.  noted that in addition to weight gain, higher intake of sugar-sweetened beverages is associated with the development of metabolic syndrome.
Screening of all adolescents should be done routinely in the schools to find out adolescents who are at risk of obesity. The detailed medical evaluation must be done in all overweight and obese adolescents for metabolic syndrome. Evaluation of anthropometric indices is crucial for early detection and prevention of metabolic syndrome. We recommend that early intervention must be aimed at managing obesity to reduce the risk of metabolic syndrome. Lifestyle modifications with the help of life skills educations will help adolescents to deal with the global problem of obesity and metabolic syndrome.
Limitation of the study
The present study includes adolescents from Pimpri Chinchwad area only. The sample was selective, and number of cases of metabolic syndrome was very small. Birth weight was recorded on the basis of recall which has the potential for measurement error. Association with socioeconomic status could not be properly ascertained since screening was done only for three schools of Pimpri area and all participants were from the similar socioeconomic background.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Smith JC. Current epidemic of childhood obesity & its implication for future congenital heart disease. Pediatr Clin North Am 2004;51:1679-83.
Brahmbhatt KR, Oza UN. Obesity among adolescents of Ahmedabad City, Gujarat, India - A community based cross-sectional study. Int J Biol Med Res 2012;3:1554-7.
Jan Mohamed HJ, Mitra AK, Zainuddin LR, Leng SK, Wan Muda WM. Women are at a higher risk of metabolic syndrome in rural Malaysia. Women Health 2013;53:335-48.
Cook S, Weitzman M, Auinger P, Nguyen M, Dietz WH. Prevalence of a metabolic syndrome phenotype in adolescents: Findings from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med 2003;157:821-7.
Mehairi AE, Khouri AA, Naqbi MM, Muhairi SJ, Maskari FA, Nagelkerke N, et al.
Metabolic syndrome among Emirati adolescents: A school-based study. PLoS One 2013;8:e56159.
Singh R, Bhansali A, Sialy R, Aggarwal A. Prevalence of metabolic syndrome in adolescents from a North Indian population. Diabet Med 2007;24:195-9.
Agirbasli M, Agaoglu NB, Ergonul O, Yagmur I, Aydogar H, Oneri T, et al.
Comparison of anthropometric indices in predicting metabolic syndrome components in children. Metab Syndr Relat Disord 2011;9:453-9.
Tandon N, Garg MK, Singh Y, Marwaha RK. Prevalence of metabolic syndrome among urban Indian adolescents and its relation with insulin resistance (HOMA-IR). J Pediatr Endocrinol Metab 2013;26:1123-30.
Skeleton JA, Rudolph CD. Overweight and obesity. In: Nelson Textbook of Pediatrics. 18 th
ed. New Delhi: Elsevier Health Sciences; 2008. p. 140.
Agarwal KN, Saxena A, Bansal AK, Agarwal DK. Physical growth assessment in adolescence. Indian Pediatr 2001;38:1217-35.
Available from: http://www.bmi-calculator.net/waist-to-hip-ratio-calculator/waist-to-hip-ratio-chart.php. [Last accessed on 2015 Jun 05].
Aruchamy L. Clinical Paediatrics. History Taking and Case Discussion. 3 rd
ed. New Delhi: Lippincott Williams & Wilkins; 2011. p. 120.
Singh N, Parihar RK, Saini G, Mohan SK, Sharma N, Razaq M. Prevalence of metabolic syndrome in adolescents aged 10-18 years in Jammu, J and K. Indian J Endocrinol Metab 2013;17:133-7.
Pettitt DJ, Nelson RG, Saad MF, Bennett PH, Knowler WC. Diabetes and obesity in the offspring of Pima Indian women with diabetes during pregnancy. Diabetes Care 1993;16:310-4.
Ghosh A, Liu T, Khoury MJ, Valdez R. Family history of diabetes and prevalence of the metabolic syndrome in U.S. adults without diabetes: 6-year results from the National Health and Nutrition Examination Survey (1999-2004). Public Health Genomics 2010;13:353-9.
Das M, Pal S, Ghosh A. Family history of type 2 diabetes and prevalence of metabolic syndrome in adult Asian Indians. J Cardiovasc Dis Res 2012;3:104-8.
Boney CM, Verma A, Tucker R, Vohr BR. Metabolic syndrome in childhood: Association with birth weight, maternal obesity, and gestational diabetes mellitus. Pediatrics 2005;115:e290-6.
Silveira VM, Horta BL. Birth weight and metabolic syndrome in adults: Meta-analysis. Rev Saude Publica 2008;42:10-8.
Park SH, Park JH, Kang JW, Park HY, Park J, Shin KJ. Prevalence of the metabolic syndrome and abnormal lipid levels among Korean adolescents. J Paediatr Child Health 2013;49:582-7.
Rizzo AC, Goldberg TB, Silva CC, Kurokawa CS, Nunes HR, Corrente JE. Metabolic syndrome risk factors in overweight, obese, and extremely obese Brazilian adolescents. Nutr J 2013;12:19.
Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Frank B. Sugar-sweetened beverages and risk of Metabolic Syndrome and type 2 diabetes. A meta-analysis. Am Diabetes Assoc Diabetes Care 2010;33;11:2477-82.
[Table 1], [Table 2], [Table 3]