Anthropometric markers as correlates of metabolically unhealthy phenotype of children in North Asia

Introduction. Stratification of anthropometric indices to identify metabolically unhealthy phenotype in Mongoloid adolescents with different weight status carried out.

The aim. To identify anthropometric parameters that differentiate between metabolically healthy phenotype (MHP) and metabolically unhealthy phenotype (MUHP) in adolescent northern mongoloid populations.

Materials and methods. A single-center cross-sectional study conducted in 02.2015–10.2016 in the territory of the Republic of Buryatia and Irkutsk region: anthropometric examination and determination of blood glycemia level, lipidogram analysis, calipometry and measurement of girth parameters. In total 227 children were selected for the study: 137 boys and 90 girls.

Results. All adolescents with metabolically unhealthy phenotype had abnormal HDL levels. Comparison of anthropometric parameters and indices in samples of boys with metabolicdisordersshowedstatisticallysignifi antdiff encesinWC,HC,WC/HC,subcutaneous fat thickness in all measured locations and roundness index in overweight boys. Comparative analysis of anthropometric parameters and indices in girls of the studied groups did not reveal statistically signifi ant diff ences between girls with MHP and MUHP. The most informative parameters of metabolically unhealthy phenotype in Asian boys are visceral obesity index (AUC = 0.92), SDS BMI (AUC = 0.73), abdominal subcutaneous fat thickness (AUC = 0.73) and on the anterior surface of the upper arm (AUC = 0.74). The optimal SDS BMI cutoff value for predicting metabolic disorders is 2.29 c.u; abdominal subcutaneous fat thickness more than 3.5 cm and on the anterior surface of the upper arm more than 1.0 cm Northern Mongoloid girls had the largest areas under the curve for visceral obesity index (AUC = 0.84), hip circumference (AUC = 0.7) and taper index (AUC = 0.7).

Conclusion. Visceral adiposity index in adolescents of both sexes is the most informative indicator of metabolic abnormalities. For North Asian boys SDS BMI is a good indicator for verification of metabolically unhealthy phenotype. For girls, hip circumference and taper index can used to screen metabolically unhealthy phenotype.

1. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. Lancet. 2017; 390(10113): 2627-2642. doi: 10.1016/S0140-6736(17)32129-3

2. Kapoor N, Furler J, Paul TV, Thomas N, Oldenburg B. Normal Weight Obesity: An underrecognized problem in individuals of South Asian Descent. Clinical therapeutics. 2019; 41(8): 1638–1642. doi: 10.1016/j.clinthera.2019.05.016

3. Kapoor N. Thin Fat Obesity: The Tropical Phenotype of obesity. In: Feingold KR, Anawalt B, Blackman MR, et al. Endotext. South Dartmouth (MA): MDText.com, Inc.; March 14, 2021.

4. Kapoor N, Lotfaliany M, Sathish T, Thankappan KR, Thomas N, Furler J, et al. Prevalence of normal weight obesity and its associated cardio-metabolic risk factors – Results from the baseline data of the Kerala Diabetes Prevention Program (KDPP). PloS one. 2020; 15: e0237974. doi: 10.1371/journal.pone.0237974

5. Osorio Manyari AA, Armas Alvarez AL, Osorio Manyari JD, Caballero FG, Pouwels S. “Metabolic surgery in Asian patients with type 2 diabetes mellitus and body mass index less than 30 kg/m2: а systematic review”. Obes Pillars. 2024; 12: 100145. doi: 10.1016/j.obpill.2024.100145

6. Sivasubramanian R, Malhotra S, Fitch AK, Singhal V. Obesity and metabolic care of children of South Asian Ethnicity in Western Society. Children (Basel). 2021; 8(6): 447. doi: 10.3390/children8060447

7. Wijayatunga NN, Dhurandhar EJ. Normal weight obesity and unaddressed cardiometabolic health risk-a narrative review. Int J Obes (Lond). 2021; 45(10): 21412155. doi: 10.1038/s41366-021-00858-7

8. Zhao Y, He L, Marthias T, Ishida M, Anindya K, Desloge A, D’Souza M, et al. Out-Of-Pocket Expenditure associated with physical inactivity, excessive weight, and obesity in China: Quantile regression approach. Obes Facts. 2022; 15(3): 416-427. doi: 10.1159/000522433

9. Wang L, Hui SS. Diagnostic accuracy of different body weight and height-based definitions of childhood obesity in identifying overfat among Chinese children and adolescents: a cross-sectional study. BMCPublic Health. 2015; 15: 802. doi: 10.1186/s12889-015-2152-0

10. Bairova TA, Dolgikh VV, Kolesnikova LI, Pervushina OA. Nutritciogenetics and risk factors of cardiovascular disease: associated research in eastern Siberia populations. Acta Biomedica Scientifica. 2013; 4(92): 87-92.

11. Piqueras P, Ballester A, Durá-Gil JV, et al. Anthropometric Indicators as a tool for diagnosis of obesity and other health risk factors: A Literature Review. Front Psychol. 2021; 12: 631179. doi: 10.3389/fpsyg.2021.631179

12. Vizzuso S, Del Torto A, Dilillo D, Calcaterra V, Di Profio E, Leone A, et al. Visceral Adiposity Index (VAI) in Children and Adolescents with obesity: no association with daily energy intake but promising tool to Identify Metabolic Syndrome (MetS). Nutrients. 2021; 13(2): 413. doi: 10.3390/nu13020413

13. Leone A, Vizzuso S, Brambilla P, Mameli C, Ravella S, De Amicis R, et al. Evaluation of different adiposity indices and association with Metabolic Syndrome Risk in obese Children: Is there a Winner? Int J Mol Sci. 2020; 21(11): 4083. doi: 10.3390/ijms21114083

14. Zhang J, Olsen A, Halkjær J, Petersen KE, Tjønneland A, Overvad K, et al. Self-reported and measured anthropometric variables in association with cardiometabolic markers: A Danish cohort study. PLoS One. 2023; 18(7): e0279795. doi: 10.1371/journal.pone.0279795

15. Choi DH, Hur YI, Kang JH, Kim K, Cho YG, Hong SM, et al. Usefulness of the Waist Circumference-to-Height Ratio in screening for obesity and Metabolic Syndrome among Korean Children and Adolescents: Korea National Health and Nutrition Examination Survey, 2010-2014. Nutrients. 2017; 9(3): 256. doi: 10.3390/nu9030256

16. Misra A, Khurana L. Obesity-related non-communicable diseases: South Asians vs. White Caucasians. Int J Obes (Lond). 2011; 35(2): 167-87. doi: 10.1038/ijo.2010.135

17. Nazare JA, Smith JD, Borel AL, Haffner SM, Balkau B, Ross R, et al. Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardio metabolic risk profile: the International Study of Prediction of Intra-Abdominal Adiposity and Its Relation-ship with Cardiometabolic Risk/Intra-Abdominal Adiposity. Am J Clin Nutr. 2012; 96(4): 714–26. doi: 10.3945/ajcn.112.035758

18. Lear SA, Humphries KH, Kohli S, Chockalingam A, Frohlich JJ, Birmingham CL. Visceral adipose tissue accumulation differs according to ethnic back-ground: results of the Multicultural Community Health Assessment Trial (M-CHAT). Am J Clin Nutr. 2007; 86: 353–359. doi: 10.1093/ajcn/86.2.353

19. Ogarkov MYu, Barbarash OL, Kazachek YAV, Kvitkova LV, Policutina AL, Barbarash LS. The metabolic syndrome main components prevalence of aboriginal and non-aboriginal population of Gornaya Shoria. Bulletin SO RAMN. 2004; 1(111): 105-108.

20. Xi B, Zong X, Kelishadi R, Litwin M, Hong YM, Poh BK, et al. International waist circumference percentile cutoffs for central obesity in Children and Adolescents Aged 6 to 18 Years. J Clin Endocrinol Metab. 2020; 105(4): e1569–83. doi: 10.1210/clinem/dgz195

21. Flegal KM, Ogden CL. Childhood Obesity: are we all speaking the same language? Adv. Nutr. 2011; 2: 159S–166S. doi: 10.3945/an.111.000307

22. Chen G, Yan H, Hao Y, Shrestha S, Wang J, Li Y, et al. Comparison of various anthropometric indices in predicting abdominal obesity in Chinese children: a cross-sectional study. BMC Pediatr. 2019; 19(1): 127. doi: 10.1186/s12887-019-1501-z

23. Choi D-H, Hur Y-I, Kang J-H, et al. Usefulness of the Waist Circumference-to-Height Ratio in Screening for Obesity and Metabolic Syndrome among Korean Children and Adolescents: Korea National Health and Nutrition Examination Survey, 2010–2014. Nutrients. 2017; 9: 256. doi: 10.3390/nu9030256

24. Perona JS, Rio-Valle JS, Ramírez-Vélez R, et al. Waist circumference and abdominal volume index are the strongest anthropometric discriminators of metabolic syndrome in Spanish adolescents. Eur. J. Clin. Invest. 2019; 49(3): e13060. doi: 10.1111/eci.13060

25. Lee J, Kang SC, Kwon O, Hwang SS, Moon JS, Kim J. Reference values for waist circumference and Waist-Height Ratio in Korean Children and Adolescents. J Obes Metab Syndr. 2022; 31(3): 263-271. doi: 10.7570/jomes22033

26. Widjaja NA, Arifani R, Irawan R. Value of waist-tohip ratio as a predictor of metabolic syndrome in adolescents with obesity. Acta Biomed. 2023; 94(3): e2023076. doi: 10.23750/abm.v94i3.13755

27. Soylu M, Şensoy N, Doğan İ, Doğan N, Mazıcıoğlu MM, Öztürk A. Four-site skinfolds thickness percentiles of schoolchildren and adolescents in Turkey. Public Health Nutr. 2021; 24(16): 5414-5425. doi: 10.1017/S1368980021003323

28. Hastuti J, Rahmawati NT, Suriyanto RA, Wibowo T, Nurani N, Julia M. Patterns of body mass index, percentage body fat, and skinfold thicknesses in 7to 18-year-old Children and Adolescents from Indonesia. Int J Prev Med. 2020; 11: 129. doi: 10.4103/ijpvm.IJPVM_388_19

29. Ramírez-Vélez R, López-Cifuentes MF, Correa-Bautista JE, González-Ruíz K, González-Jiménez E, Córdoba-Rodríguez DP, et al. Triceps and subscapular skinfold thickness percentiles and cut-offs for overweight and obesity in a population-based sample of schoolchildren and adolescents in Bogota, Colombia. Nutrients. 2016; 8(10): 595. doi: 10.3390/nu8100595

30. Štěpánek L, Horáková D, Cibičková Ľ, Vaverková H, Karásek D, Nakládalová M, et al. Can Visceral Adiposity Index Serve as a Simple Tool for Identifying Individuals with Insulin Resistance in Daily Clinical Practice? Medicina (Kaunas). 2019; 55(9): 545. doi: 10.3390/medicina55090545

31. Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. Visceral adiposity index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care. 2010; 33(4): 920-2. doi: 10.2337/dc09-1825

32. Ejtahed H-S, Kelishadi R, Hasani-Ranjbar S, Angoorani P, Motlagh ME, Shafiee G, et al. discriminatory ability of visceral adiposity index as an indicator for modeling cardio-metabolic risk factors in pediatric population: The CASPIAN-V Study. J. Cardiovasc. Thorac. Res. 2019; 11: 280–286. doi: 10.15171/jcvtr.2019.46

33. Dong Y, Bai L, Cai R, Zhou J, Ding W. Visceral adiposity index performed better than traditional adiposity indicators in predicting unhealthy metabolic phenotype among Chinese children and adolescents. Sci Rep. 2021; 11(1): 23850. doi: 10.1038/s41598-021-03311-x