Anthropometric Indicators As Predictor of Pre-diabetes in Indian Adolescents

Overview

Journal Indian Heart J

Publisher Elsevier

Specialty Cardiology & Vascular Diseases

Date 2017 Aug 21

PMID 28822514

Citations 6

Authors

Umeshwar Pandey

Tanu Midha

Yashwant Kumar Rao

Pravin Katiyar

Pranay Wal

Samarjeet Kaur

Dinesh Singh Martolia

Affiliations

Soon will be listed here.

Abstract

Introduction: In India, there are approximately 41 million diabetics to date. Impaired glucose tolerance or pre-diabetes may occur as early as adolescence.

Objective: To find out the cut-off values of body mass index (BMI) and waist circumference to predict pre-diabetes in adolescents in north India.

Methods: A cross-sectional study was conducted among 526 students aged 17-19 years, in the Institute of Paramedical Sciences, Chatrapati Shahuji Maharaj University, Kanpur. A pre-tested questionnaire was used and the diagnostic criteria of the American Diabetic Association were applied. Receiver operating characteristic(ROC) analysis was used to assess the cut-offs of BMI and waist circumference for predicting prediabetes.

Results: ROC analysis showed that BMI is a good predictor of prediabetes for both boys and girls.Area under the ROC curve was 0.828 for boys and 0.838 for girls, respectively. The cut-off values of BMI for predicting prediabetes were identified as ≥22.8kg/m in boys and ≥20.5kg/m in girls. Upon ROC analysis for waist circumference, it was observed that it was a good predictor of prediabetes both for boys (area under the curve 0.804) and girls (area under the curve 0.795). The cut-offs for waist circumference for predicting prediabetes were found to be ≥82.5cm for boys and ≥80.3cm for girls.

Conclusion: BMI and waist circumference estimation can be done for early detection of prediabetes in adolescents for further diagnostic evaluation and management.

Citing Articles

Accuracy of anthropometric parameters in predicting prediabetes among adolescents in Eastern Sudan: a community-based cross-sectional study.

El-Gendy O, Alsafi W, Al-Shafei K, Hassan A, Adam I BMC Endocr Disord. 2025; 25(1):58.

PMID: 40025528 PMC: 11874620. DOI: 10.1186/s12902-025-01890-8.

Lifestyle practices predisposing adolescents to non communicable diseases in Delhi.

Borle A, Gangadharan N, Basu S Dialogues Health. 2024; 1:100064.

PMID: 38515919 PMC: 10954009. DOI: 10.1016/j.dialog.2022.100064.

A Mediterranean-Diet-Based Nutritional Intervention for Children with Prediabetes in a Rural Town: A Pilot Randomized Controlled Trial.

Blancas-Sanchez I, Del Rosal Jurado M, Aparicio-Martinez P, Quintana Navarro G, Vaquero-Abellan M, Castro Jimenez R Nutrients. 2022; 14(17).

PMID: 36079871 PMC: 9460785. DOI: 10.3390/nu14173614.

Body impedance analyzer and anthropometric indicators; predictors of metabolic syndrome.

Pouragha H, Amiri M, Saraei M, Pouryaghoub G, Mehrdad R J Diabetes Metab Disord. 2021; 20(2):1169-1178.

PMID: 34277496 PMC: 8275900. DOI: 10.1007/s40200-021-00836-w.

Baseline risk factor prevalence among adolescents aged 15-17 years old: findings from National Non-communicable Disease Monitoring Survey (NNMS) of India.

Mathur P, Kulothungan V, Leburu S, Krishnan A, Chaturvedi H, Salve H BMJ Open. 2021; 11(6):e044066.

PMID: 34187814 PMC: 8245441. DOI: 10.1136/bmjopen-2020-044066.

References

. Type 2 diabetes in children and adolescents. American Diabetes Association. Diabetes Care. 2000; 23(3):381-9. DOI: 10.2337/diacare.23.3.381. View

Sinha R, Fisch G, Teague B, Tamborlane W, Banyas B, Allen K . Prevalence of impaired glucose tolerance among children and adolescents with marked obesity. N Engl J Med. 2002; 346(11):802-10. DOI: 10.1056/NEJMoa012578. View

. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2003; 27 Suppl 1:S5-S10. DOI: 10.2337/diacare.27.2007.s5. View

. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157-63. DOI: 10.1016/S0140-6736(03)15268-3. View

Molnar D . The prevalence of the metabolic syndrome and type 2 diabetes mellitus in children and adolescents. Int J Obes Relat Metab Disord. 2004; 28 Suppl 3:S70-4. DOI: 10.1038/sj.ijo.0802811. View

Mathers C, Loncar D . Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006; 3(11):e442. PMC: 1664601. DOI: 10.1371/journal.pmed.0030442. View

Joshi S, Parikh R . India--diabetes capital of the world: now heading towards hypertension. J Assoc Physicians India. 2007; 55:323-4. View

Amutha A, Datta M, Unnikrishnan I, Anjana R, Rema M, Narayan K . Clinical profile of diabetes in the young seen between 1992 and 2009 at a specialist diabetes centre in south India. Prim Care Diabetes. 2011; 5(4):223-9. DOI: 10.1016/j.pcd.2011.04.003. View

Chiu M, Austin P, Manuel D, Shah B, Tu J . Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care. 2011; 34(8):1741-8. PMC: 3142051. DOI: 10.2337/dc10-2300. View

10.

Danaei G, Finucane M, Lu Y, Singh G, Cowan M, Paciorek C . National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health examination surveys and epidemiological studies with 370 country-years and 2·7 million participants. Lancet. 2011; 378(9785):31-40. DOI: 10.1016/S0140-6736(11)60679-X. View

11.

Anjana R, Pradeepa R, Deepa M, Datta M, Sudha V, Unnikrishnan R . Prevalence of diabetes and prediabetes (impaired fasting glucose and/or impaired glucose tolerance) in urban and rural India: phase I results of the Indian Council of Medical Research-INdia DIABetes (ICMR-INDIAB) study. Diabetologia. 2011; 54(12):3022-7. DOI: 10.1007/s00125-011-2291-5. View

12.

Pratyush D, Tiwari S, Singh S, Singh S . Waist circumference cutoff and its importance for diagnosis of metabolic syndrome in Asian Indians: A preliminary study. Indian J Endocrinol Metab. 2012; 16(1):112-5. PMC: 3263178. DOI: 10.4103/2230-8210.91205. View

13.

Amutha A, Datta M, Unnikrishnan R, Anjana R, Mohan V . Clinical profile and complications of childhood- and adolescent-onset type 2 diabetes seen at a diabetes center in south India. Diabetes Technol Ther. 2012; 14(6):497-504. DOI: 10.1089/dia.2011.0283. View

14.

Praveen P, Roy A, Prabhakaran D . Cardiovascular disease risk factors: a childhood perspective. Indian J Pediatr. 2012; 80 Suppl 1:S3-12. DOI: 10.1007/s12098-012-0767-z. View

15.

Mohsin F, Mahbuba S, Begum T, Azad K, Nahar N . Prevalence of impaired glucose tolerance among children and adolescents with obesity. Mymensingh Med J. 2012; 21(4):684-90. View

16.

Roche M, Wang P . Factors associated with a diabetes diagnosis and late diabetes diagnosis for males and females. J Clin Transl Endocrinol. 2017; 1(3):77-84. PMC: 5685052. DOI: 10.1016/j.jcte.2014.07.002. View