Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

The range of non-traditional anthropometric parameters to define obesity and obesity-related disease in children: a systematic review

Abstract

Obesity is defined as an abnormal/excessive accumulation of body fat, associated with health consequences. Although overall obesity does confer a significant threat to the health of individuals, the distribution of body fat, especially abdominal/central obesity is of greater importance. For practical reasons, proxy anthropometric measurements have been developed to identify central obesity, however, major limitations are noted in these traditional measurements. The present study aims to evaluate the literature, to identify and describe non-traditional anthropometric measurements of overweight and obesity in children. The current systematic review was conducted in accordance with the PRISMA guidelines, and the search was undertaken in the PubMed® database, using MeSH (Medical Subject Headings) terms. Data extracted from each study were: (a) details of the study, (b) anthropometric parameter(s) evaluated in the study and its details, (c) study methods, (d) objectives of the study and/or comparisons, and (e) main findings/conclusions of the study. The search yielded a total of 3697 articles, of which 31 studies were deemed eligible to be included. The literature search identified 13 non-traditional anthropometric parameters. Data on non-traditional anthropometric parameters were derived from 24 countries. Majority were descriptive cross-sectional studies (n = 29), while sample size varied from 65 to 23,043. Non-traditional anthropometric parameters showed variable correlation with obesity and/or related metabolic risk factors. Some parameters involved complex calculations, while others were based on a single anthropometric measurement or derived from traditional measures. Most studies lacked comparison with a ‘gold standard’ assessment of body fat, hence further research is required to determine their accuracy and precision.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1

Similar content being viewed by others

References

  1. World Health Organization. Obesity and overweight: fact sheet. Geneva: World Health Organization; 2016.

  2. Djalalinia S, Qorbani M, Peykari N, Kelishadi R. Health impacts of obesity. Pak J Med Sci. 2015;31:239–42.

    PubMed  PubMed Central  Google Scholar 

  3. Katulanda P, Jayawardena MA, Sheriff MH, Constantine GR, Matthews DR. Prevalence of overweight and obesity in Sri Lankan adults. Obes Rev: Off J Int Assoc Study Obes. 2010;11:751–6.

    CAS  Google Scholar 

  4. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metab: Clin Exp. 2019;92:6–10.

    CAS  Google Scholar 

  5. GBDO Collaborators, Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K, et al. Health effects of overweight and obesity in 195 countries over 25 years. N. Engl J Med. 2017;377:13–27.

    Google Scholar 

  6. Katzmarzyk PT, Chaput J-P, Fogelholm M, Hu G, Maher C, Maia J, et al. International study of childhood obesity, lifestyle and the environment (ISCOLE): contributions to understanding the global obesity epidemic. Nutrients. 2019;11:848.

    PubMed Central  Google Scholar 

  7. Krauss R, Winston M, Fletcher B, Grundy S. Obesity: impact on cardiovascular disease. Circulation. 1998;98:1472–6.

    PubMed  Google Scholar 

  8. Editorial. Curbing the obesity epidemic. Lancet. 2006;367:P1549.

  9. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX, et al. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss. Circulation. 2006;113:898–918.

    PubMed  Google Scholar 

  10. Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Investig. 2004;114:1752–61.

    CAS  PubMed  Google Scholar 

  11. Spalding KL, Arner E, Westermark PO, Bernard S, Buchholz BA, Bergmann O, et al. Dynamics of fat cell turnover in humans. Nature. 2008;453:783–7.

    CAS  PubMed  Google Scholar 

  12. Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA, et al. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N. Engl J Med. 2011;365:1876–85.

    CAS  PubMed  Google Scholar 

  13. Okorodudu DO, Jumean MF, Montori VM, Romero-Corral A, Somers VK, Erwin PJ, et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. Int J Obes (2005). 2010;34:791–9.

    CAS  Google Scholar 

  14. Ho-Pham LT, Campbell LV, Nguyen TV. More on body fat cutoff points. Mayo Clinic Proc. 2011;86:584.

  15. Sanyal D, Mukhopadhyay P, Pandit K, Mukhopadhyay S, Chowdhury S. Central obesity but not generalised obesity (body mass index) predicts high prevalence of fatty liver (NRFLD), in recently detected untreated, IGT and type 2 diabetes Indian subjects. J Indian Med Assoc. 2009;107:755–8.

    PubMed  Google Scholar 

  16. Carmienke S, Freitag MH, Pischon T, Schlattmann P, Fankhaenel T, Goebel H, et al. General and abdominal obesity parameters and their combination in relation to mortality: a systematic review and meta-regression analysis. Eur J Clin Nutr. 2013;67:573–85.

    CAS  PubMed  Google Scholar 

  17. Song X, Jousilahti P, Stehouwer CD, Soderberg S, Onat A, Laatikainen T, et al. Comparison of various surrogate obesity indicators as predictors of cardiovascular mortality in four European populations. Eur J Clin Nutr. 2013;67:1298–302.

    CAS  PubMed  Google Scholar 

  18. Bila WC, Freitas AE, Galdino AS, Ferriolli E, Pfrimer K, Lamounier JA. Deuterium oxide dilution and body composition in overweight and obese schoolchildren aged 6–9 years. J de Pediatr. 2016;92:46–52.

    Google Scholar 

  19. Smith-Ryan AE, Mock MG, Ryan ED, Gerstner GR, Trexler ET, Hirsch KR. Validity and reliability of a 4-compartment body composition model using dual energy x-ray absorptiometry-derived body volume. Clin Nutr (Edinb, Scotl). 2017;36:825–30.

    Google Scholar 

  20. Smalley KJ, Knerr AN, Kendrick ZV, Colliver JA, Owen OE. Reassessment of body mass indices. Am J Clin Nutr. 1990;52:405–8.

    CAS  PubMed  Google Scholar 

  21. Must A, Anderson SE. Body mass index in children and adolescents: considerations for population-based applications. Int J Obes (2005). 2006;30:590–4.

    CAS  Google Scholar 

  22. Owolabi EO, Ter Goon D, Adeniyi OV. Central obesity and normal-weight central obesity among adults attending healthcare facilities in Buffalo City Metropolitan Municipality, South Africa: a cross-sectional study. J health, Popul, Nutr. 2017;36:54.

    Google Scholar 

  23. Purnell JQ. Definitions, classification, and epidemiology of obesity. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, et al., eds. Endotext. South Dartmouth (MA): MDText.com, Inc; 2000.

  24. CAS AlvesJunior, Mocellin MC, ECA Gonçalves, DAS Silva, EBSM Trindade. Anthropometric indicators as body fat discriminators in children and adolescents: a systematic review and meta-analysis. Adv Nutr. 2017;8:718–27.

    Google Scholar 

  25. Kelishadi R, Mirmoghtadaee P, Najafi H, Keikha M. Systematic review on the association of abdominal obesity in children and adolescents with cardio-metabolic risk factors. J Res Med Sci. 2015;20:294–307.

    PubMed  PubMed Central  Google Scholar 

  26. Martin-Calvo N, Moreno-Galarraga L, Martinez-Gonzalez MA. Association between body mass index, waist-to-height ratio and adiposity in children: a systematic review and meta-analysis. Nutrients. 2016;8:512.

    PubMed Central  Google Scholar 

  27. Freedman DS, Sherry B. The validity of BMI as an indicator of body fatness and risk among children. Pediatrics. 2009;124Suppl 1:S23–34.

    PubMed  Google Scholar 

  28. Vanderwall C, Randall Clark R, Eickhoff J, Carrel AL. BMI is a poor predictor of adiposity in young overweight and obese children. BMC Pediatr. 2017;17:135.

    PubMed  PubMed Central  Google Scholar 

  29. Goh VH, Tain C, Tong TY, Mok HP, Wong M. Are BMI and other anthropometric measures appropriate as indices for obesity? A study in an Asian population. J lipid Res. 2004;45:1892–8.

    CAS  PubMed  Google Scholar 

  30. Burniat W, Cole T, Lissau I, Poskitt E,. Child and adolescent obesity: causes and consequences, prevention and management. Cambridge: Cambridge University Press; 2002.

  31. Romero-Corral A, Somers VK, Sierra-Johnson J, Thomas RJ, Collazo-Clavell M, Korinek J, et al. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes. 2008;32:959–66.

    CAS  Google Scholar 

  32. Jayawardena R, Ranasinghe P, Ranathunga T, Mathangasinghe Y, Wasalathanththri S, Hills AP. Novel anthropometric parameters to define obesity and obesity-related disease in adults: a systematic review. Nutr Rev. 2019;78:498–513.

    Google Scholar 

  33. Moher D, Liberati A, Tetzlaff J, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.

    PubMed  PubMed Central  Google Scholar 

  34. Akaboshi I, Kitano A, Kan H, Haraguchi Y, Mizumoto Y. Chest circumference in infancy predicts obesity in 3-year-old children. Asia Pac J Clin Nutr. 2012;21:495–501.

    PubMed  Google Scholar 

  35. Dumith SC, Muraro MFR, Monteiro AR, Machado KP, Dias M, Oliz MM, et al. Diagnostic properties and cutoff points for overweight prediction through anthropometric indicators in adolescents from Caracol, Piaui, Brazil, 2011. Epidemiologia e servicos de Saude: Rev do Sist Unico de Saude do Bras. 2018;27:e201715013.

    Google Scholar 

  36. Chaput JP, Katzmarzyk PT, Barnes JD, Fogelholm M, Hu G, Kuriyan R, et al. Mid-upper arm circumference as a screening tool for identifying children with obesity: a 12-country study. Pediatr Obes. 2017;12:439–45.

    PubMed  Google Scholar 

  37. Craig E, Bland R, Ndirangu J, Reilly JJ. Use of mid-upper arm circumference for determining overweight and overfatness in children and adolescents. Arch Dis Child. 2014;99:763–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Lu Q, Wang R, Lou DH, Ma CM, Liu XL, Yin FZ. Mid-upper-arm circumference and arm-to-height ratio in evaluation of overweight and obesity in Han children. Pediatrics Neonatol. 2014;55:14–9.

    Google Scholar 

  39. Mazicioglu MM, Hatipoglu N, Ozturk A, Cicek B, Ustunbas HB, Kurtoglu S. Waist circumference and mid-upper arm circumference in evaluation of obesity in children aged between 6 and 17 years. J Clin Res Pediatr Endocrinol. 2010;2:144–50.

    PubMed  PubMed Central  Google Scholar 

  40. Owa JA, Adejuyigbe O. Fat mass, fat mass percentage, body mass index, and mid-upper arm circumference in a healthy population of Nigerian children. J Tropical Pediatrics. 1997;43:13–9.

    CAS  Google Scholar 

  41. Ozturk A, Cicek B, Mazicioglu MM, Kurtoglu S. Determining abdominal obesity cut-offs and relevant risk factors for anthropometric indices in Turkish children and adolescents. J Pediatr Endocrinol Metab: JPEM. 2015;28:525–32.

    PubMed  Google Scholar 

  42. Rerksuppaphol S, Rerksuppaphol L. Mid-upper-arm circumference and arm-to-height ratio to identify obesity in school-age children. Clin Med Res. 2017;15:53–8.

    PubMed  PubMed Central  Google Scholar 

  43. Sardinha LB, Going SB, Teixeira PJ, Lohman TG. Receiver operating characteristic analysis of body mass index, triceps skinfold thickness, and arm girth for obesity screening in children and adolescents. Am J Clin Nutr. 1999;70:1090–5.

    CAS  PubMed  Google Scholar 

  44. Katz SL, Vaccani JP, Clarke J, Hoey L, Colley RC, Barrowman NJ. Creation of a reference dataset of neck sizes in children: standardizing a potential new tool for prediction of obesity-associated diseases? BMC Pediatrics. 2014;14:159.

    PubMed  PubMed Central  Google Scholar 

  45. Kelishadi R, Djalalinia S, Motlagh ME, Rahimi A, Bahreynian M, Arefirad T, et al. Association of neck circumference with general and abdominal obesity in children and adolescents: the weight disorders survey of the CASPIAN-IV study. BMJ Open. 2016;6:e011794.

    PubMed  PubMed Central  Google Scholar 

  46. Kondolot M, Horoz D, Poyrazoglu S, Borlu A, Ozturk A, Kurtoglu S, et al. Neck circumference to assess obesity in preschool children. J Clin Res Pediatr Endocrinol. 2017;9:17–23.

    PubMed  PubMed Central  Google Scholar 

  47. Lou DH, Yin FZ, Wang R, Ma CM, Liu XL, Lu Q. Neck circumference is an accurate and simple index for evaluating overweight and obesity in Han children. Ann Hum Biol. 2012;39:161–5.

    PubMed  Google Scholar 

  48. Nafiu OO, Burke C, Lee J, Voepel-Lewis T, Malviya S, Tremper KK. Neck circumference as a screening measure for identifying children with high body mass index. Pediatrics. 2010;126:e306–10.

    PubMed  Google Scholar 

  49. Patnaik L, Pattnaik S, Rao EV, Sahu T. Validating neck circumference and waist circumference as anthropometric measures of overweight/obesity in adolescents. Indian Pediatrics. 2017;54:377–80.

    PubMed  Google Scholar 

  50. Ferretti Rde L, Cintra Ide P, Passos MA, de Moraes Ferrari GL, Fisberg M. Elevated neck circumference and associated factors in adolescents. BMC Public health. 2015;15:208.

    PubMed  Google Scholar 

  51. Asif M, Aslam M, Altaf S. Evaluation of anthropometric parameters of central obesity in Pakistani children aged 5-12 years, using receiver operating characteristic (ROC) analysis. J Pediatr Endocrinol Metab. 2018;31:971–7.

    PubMed  Google Scholar 

  52. Owens S, Litaker M, Allison J, Riggs S, Ferguson M, Gutin B. Prediction of visceral adipose tissue from simple anthropometric measurements in youths with obesity. Obes Res. 1999;7:16–22.

    CAS  PubMed  Google Scholar 

  53. Al-Daghri N, Alokail M, Al-Attas O, Sabico S, Kumar S. Establishing abdominal height cut-offs and their association with conventional indices of obesity among Arab children and adolescents. Ann Saudi Med. 2010;30:209–14.

    PubMed  PubMed Central  Google Scholar 

  54. Weber DR, Levitt Katz LE, Zemel BS, Gallagher PR, Murphy KM, Dumser SM, et al. Anthropometric measures of abdominal adiposity for the identification of cardiometabolic risk factors in adolescents. Diabetes Res Clin Pract. 2014;103:e14–7.

    PubMed  PubMed Central  Google Scholar 

  55. Shafiee G, Qorbani M, Heshmat R, Djalalinia S, Motlagh ME, Arefirad T, et al. Wrist circumference as a novel predictor of obesity in children and adolescents: the CASPIAN-IV study. J Pediatr Endocrinol Metab. 2018;31:717–25.

    PubMed  Google Scholar 

  56. Ozturk A, Cicek B, Mazicioglu MM, Zararsiz G, Kurtoglu S. Wrist circumference and frame size percentiles in 6-17-year-old turkish children and adolescents in kayseri. J Clin Res Pediatr Endocrinol. 2017;9:329–36.

    PubMed  PubMed Central  Google Scholar 

  57. Jayawardene W, Dickinson S, Lohrmann D, Agley J. Arm circumference-to-height ratio as a situational alternative to bmi percentile in assessing obesity and cardiometabolic risk in adolescents. J Obes. 2018;2018:7456461.

    PubMed  PubMed Central  Google Scholar 

  58. Thivel D, O’Malley G, Pereira B, Duche P, Aucouturier J. Comparison of total body and abdominal adiposity indexes to dual x-ray absorptiometry scan in obese adolescents. Am J Hum Biol: Off J Hum Biol Counc. 2015;27:334–8.

    Google Scholar 

  59. Kryst L, Woronkowicz A, Kowal M, Pilecki MW, Sobiecki J. Abdominal obesity screening tools in the aspects of secular trend. Anthropologischer Anz; Ber uber die biologisch-anthropologische Literatur. 2016;73:295–312.

    Google Scholar 

  60. Candido AP, Freitas SN, Machado-Coelho GL. Anthropometric measurements and obesity diagnosis in schoolchildren. Acta paediatrica (Oslo, Nor: 1992). 2011;100:e120–4.

    Google Scholar 

  61. Chen LW, Tint MT, Fortier MV, Aris IM, Shek LP, Tan KH, et al. Which anthropometric measures best reflect neonatal adiposity? Int J Obes. 2005;2018(42):501–6.

    Google Scholar 

  62. Michielutte R, Diseker RA, Corbett WT, Schey HM, Ureda JR. The relationship between weight-height indices and the triceps skinfold measure among children age 5 to 12. Am J Public health. 1984;74:604–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Storlien LH, Bird JE, Silva PA. Assessment of obesity in early childhood. Aust Paediatr J. 1987;23:131–5.

    CAS  PubMed  Google Scholar 

  64. Zhang YX, Zhao JS, Chu ZH. Percentiles of waist-to-sitting-height ratio and its relationship with obesity and elevated blood pressure among children and adolescents in Shandong, China. Blood Press Monit. 2016;21:33–7.

    PubMed  Google Scholar 

  65. Kouchi M, Mochimaru M, Tsuzuki K, Yokoi T. Interobserver errors in anthropometry. J Hum Ergol. 1999;28:15–24.

    CAS  Google Scholar 

  66. Carlsson AC, Riserus U, Arnlov J, Borne Y, Leander K, Gigante B, et al. Prediction of cardiovascular disease by abdominal obesity measures is dependent on body weight and sex–results from two community based cohort studies. Nutr, Metab, cardiovascular Dis: NMCD. 2014;24:891–9.

    CAS  PubMed  Google Scholar 

  67. Karlsen S, Morris S, Kinra S, Vallejo-Torres L, Viner RM. Ethnic variations in overweight and obesity among children over time: findings from analyses of the Health Surveys for England 1998-2009. Pediatr Obes. 2014;9:186–96.

    CAS  PubMed  Google Scholar 

  68. Isong IA, Rao SR, Bind MA, Avendano M, Kawachi I, Richmond TK. Racial and ethnic disparities in early childhood obesity. Pediatrics. 2018;141:e20170865.

    PubMed  PubMed Central  Google Scholar 

  69. Caprio S, Daniels SR, Drewnowski A, Kaufman FR, Palinkas LA, Rosenbloom AL, et al. Influence of race, ethnicity, and culture on childhood obesity: implications for prevention and treatment: a consensus statement of Shaping America’s Health and the Obesity Society. Diabetes Care. 2008;31:2211–21.

    PubMed  PubMed Central  Google Scholar 

  70. Goossens GH. The metabolic phenotype in obesity: fat mass, body fat distribution, and adipose tissue function. Obes Facts. 2017;10:207–15.

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005;366:1640–9.

    PubMed  Google Scholar 

  72. Snijder MB, Zimmet PZ, Visser M, Dekker JM, Seidell JC, Shaw JE. Independent and opposite associations of waist and hip circumferences with diabetes, hypertension and dyslipidemia: the AusDiab Study. Int J Obes Relat Metab Disord. 2004;28:402–9.

    CAS  PubMed  Google Scholar 

  73. Britton KA, Massaro JM, Murabito JM, Kreger BE, Hoffmann U, Fox CS. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. J Am Coll Cardiol. 2013;62:921–5.

    PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

RJ, PR, APH, and VPW substantially contributed to the general idea and design of the study. RJ, PR, VPW, and NG took part in designing the protocol. RJ, PR, NG, and APH planned the data analysis. PR, RJ, and NG drafted the manuscript. All authors have read and consented to the manuscript.

Corresponding author

Correspondence to Priyanga Ranasinghe.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ranasinghe, P., Jayawardena, R., Gamage, N. et al. The range of non-traditional anthropometric parameters to define obesity and obesity-related disease in children: a systematic review. Eur J Clin Nutr 75, 373–384 (2021). https://doi.org/10.1038/s41430-020-00715-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-020-00715-2

Search

Quick links