Skip to main content
SpringerLink
Log in

Accuracy of Six Anthropometric Skinfold Formulas Versus Air Displacement Plethysmography for Estimating Percent Body Fat in Female Adolescents with Phenylketonuria

  • Research Report
  • Chapter
  • First Online:
JIMD Reports - Volume 10

Part of the book series: JIMD Reports ((JIMD,volume 10))

Abstract

Background: The reliability of studies investigating biological and therapeutic factors that influence body composition in PKU patients depends on accurate anthropometric measurements.

Objective: To determine the precision of six anthropometric skinfold equations versus air displacement plethysmography (ADP) for predicting body fat (BF) percentage in female adolescents with PKU.

Design: Skinfold and ADP measurements were recorded from a cross section of 59 female patients with PKU, ages 10–19 years. Anthropometric measures were used to calculate percent BF using equations published by Peterson et al., Loftin et al. (TAAG), Slaughter et al., Wilmore and Behnke, Durnin and Womersley, and Jackson et al. Bland-Altman agreement analysis and Lin’s concordance correlation coefficient (ρ c) were used to determine the precision of each equation compared with percent BF determined by ADP.

Results: Adolescent females with PKU had a mean BF content of 33% measured by ADP, with an inverse association to birth cohort (r = −0.3, P = 0.016). Based on the Bland-Altman method for evaluating agreement, only Peterson’s equation did not differ significantly from ADP percent BF results (P = 0.23). Peterson’s skinfold equation yielded percent BF estimates with the smallest mean difference from ADP and the smallest standard deviation (0.76 ± 4.8), whereas Slaughter’s equation had the largest (−7.7 ± 7.4). Loftin’s TAAG equation had the least mean percent error (2.2%), while Slaughter’s equation had the highest (19%). Both TAAG and Peterson’s equations had the highest concordance correlation coefficients (ρ c = 0.8, ρ c = 0.8), while Slaughter’s equation had the lowest (ρ c = 0.3).

Conclusions: Peterson’s equation is a precise surrogate for ADP when estimating percent BF in female adolescents with PKU, though Loftin’s TAAG equation is also effective. Observed decreases in adiposity correlating with birth cohort could reflect steady improvements in patient nutrition care.

Competing interests: None declared

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

ADP:

Air displacement plethysmography

BF:

Body fat

DXA:

Dual-energy x-ray absorptiometry

PKU:

Phenylketonuria

UWW:

Underwater weighing

References

  • Acosta P, Yannicelli S, Singh R et al (2003) Nutrient intakes and physical growth of children with phenylketonuria undergoing nutrition therapy. J Am Diet Assoc 103(9):1167–1173

    Article  PubMed  Google Scholar 

  • ACSM (2000) ACSM's Guidelines for Exercise Testing and Prescription, 6th edn. Lippincott Williams & Wilkins, Philadelphia, PA.

    Google Scholar 

  • Adamczyk P, Morawiec-Knysak A, Pludowski P et al (2011) Bone metabolism and the muscle-bone relationship in children, adolescents and young adults with phenylketonuria. J Bone Miner Metab 29(2):236–244

    Article  PubMed  CAS  Google Scholar 

  • Albersen M, Bonthuis M, de Roos NM, et al (2010) Whole body composition analysis by the BodPod air-displacement plethysmography method in children with phenylketonuria shows a higher body fat percentage. J Inherit Metab Dis. http://link.springer.com/article/10.1007/s10545-010-9149-8

  • Allen JR, McCauley JC, Waters DL et al (1995) Resting energy expenditure in children with phenylketonuria. Am J Clin Nutr 62(4):797–801

    PubMed  CAS  Google Scholar 

  • Ballard TP, Fafara L, Vukovich MD (2004) Comparison of Bod Pod and DXA in female collegiate athletes. Med Sci Sports Exerc 36(4):731–735

    Article  PubMed  Google Scholar 

  • Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310

    Article  PubMed  CAS  Google Scholar 

  • Bland JM, Altman DG (2003) Applying the right statistics: analyses of measurement studies. Ultrasound Obstet Gynecol 22(1):85–93

    Article  PubMed  CAS  Google Scholar 

  • Brandon LJ (1998) Comparison of existing skinfold equations for estimating body fat in African American and white women. The American Journal of Clinical Nutrition 67(6):1155–1161

    PubMed  CAS  Google Scholar 

  • Brook CG (1971) Determination of body composition of children from skinfold measurements. Arch Dis Child 46(246):182–184

    Article  PubMed  CAS  Google Scholar 

  • CDC (2000–2005) NHANES Anthropometry Procedures Manual. Centers for Disease Control and Prevention

    Google Scholar 

  • Daniel JA, Sizer PS Jr, Latman NS (2005) Evaluation of body composition methods for accuracy. Biomed Instrum Technol 39(5):397–405

    Article  PubMed  Google Scholar 

  • Dung NQ, Fusch G, Armbrust S, Jochum F, Fusch C (2007) Use of bioelectrical impedance analysis and anthropometry to measure fat-free mass in children and adolescents with Crohn disease. J Pediatric Gastroenterol Nutr 44(1):130–135

    Article  Google Scholar 

  • Durnin JV, Womersley J (1974) Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 32(1):77–97

    Article  PubMed  CAS  Google Scholar 

  • Fields DA, Higgins PB, Radley D (2005) Air-displacement plethysmography: here to stay. Curr Opin Clin Nutr Metab Care 8(6):624–629

    Article  PubMed  Google Scholar 

  • Flegal KM, Ogden CL, Yanovski JA et al (2010) High adiposity and high body mass index-for-age in US children and adolescents overall and by race-ethnic group. Am J Clin Nutr 91(4):1020–1026

    Article  PubMed  CAS  Google Scholar 

  • Ginde SR, Geliebter A, Rubiano F et al (2005) Air displacement plethysmography: validation in overweight and obese subjects. Obes Res 13(7):1232–1237

    Article  PubMed  Google Scholar 

  • Gomez-Ambrosi J, Silva C, Catalan V et al (2012) Clinical usefulness of a new equation for estimating body fat. Diabetes Care 35(2):383–388

    Article  PubMed  Google Scholar 

  • Gonçalves EM, Silva AM, Santos DA et al (2012) Accuracy of anthropometric measurements in estimating fat mass in individuals with 21-hydroxylase deficiency. Nutrition 28(10):984–990

    Article  PubMed  Google Scholar 

  • Gonzalez-Aguero A, Vicente-Rodriguez G, Ara I, Moreno LA, Casajus JA (2011) Accuracy of prediction equations to assess percentage of body fat in children and adolescents with Down syndrome compared to air displacement plethysmography. Res Dev Disabil 32(5):1764–1769

    Article  PubMed  CAS  Google Scholar 

  • Higgins PB, Fields DA, Hunter GR, Gower BA (2001) Effect of scalp and facial hair on air displacement plethysmography estimates of percentage of body fat. Obesity 9(5):326–330

    Article  CAS  Google Scholar 

  • Huemer M, Huemer C, Moslinger D, Huter D, Stockler-Ipsiroglu S (2007) Growth and body composition in children with classical phenylketonuria: results in 34 patients and review of the literature. J Inherit Metab Dis 30(5):694–699

    Article  PubMed  CAS  Google Scholar 

  • Jackson AS, Pollock ML, Ward A (1980) Generalized equations for predicting body density of women. Med Sci Sports Exerc 12(3):175–181

    PubMed  CAS  Google Scholar 

  • Katch FI, McArdle WD (1973) Prediction of body density from simple anthropometric measurements in college-age men and women. Hum Biol 45(3):445–455

    PubMed  CAS  Google Scholar 

  • Kelly TL, Wilson KE, Heymsfield SB (2009) Dual energy X-Ray absorptiometry body composition reference values from NHANES. PLoS One 4(9):e7038

    Article  PubMed  Google Scholar 

  • Kohli S, Gao M, Lear SA (2009) Using simple anthropometric measures to predict body fat in South Asians. Appl Physiol Nutr Metab 34(1):40–48

    Article  PubMed  Google Scholar 

  • Kuczmarski RJ, Ogden CL, Grummer-Strawn LM et al (2000) CDC growth charts: United States. Adv Data 314:1–27

    PubMed  Google Scholar 

  • Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45(1):255–268

    Article  PubMed  CAS  Google Scholar 

  • Lin LI-K (2000) Corrections: A note on the concordance correlation coefficient. Biometrics 56:324–325

    Article  Google Scholar 

  • Lingwood BE, Storm van Leeuwen AM, Carberry AE et al (2012) Prediction of fat-free mass and percentage of body fat in neonates using bioelectrical impedance analysis and anthropometric measures: validation against the PEA POD. Br J Nutr 107(10):1545–1552

    Article  PubMed  CAS  Google Scholar 

  • Loftin M, Nichols J, Going S et al (2007) Comparison of the validity of anthropometric and bioelectric impedance equations to assess body composition in adolescent girls. Int J Body Compos Res 5(1):1–8

    PubMed  Google Scholar 

  • Lohman TG (1981) Skinfolds and body density and their relation to body fatness: a review. Hum Biol 53(2):181–225

    PubMed  CAS  Google Scholar 

  • McBurnie MA, Kronmal RA, Schuett VE, Koch R, Azeng CG (1991) Physical growth of children treated for phenylketonuria. Ann Hum Biol 18(4):357–368

    Article  PubMed  CAS  Google Scholar 

  • McCarthy HD, Cole TJ, Fry T, Jebb SA, Prentice AM (2006) Body fat reference curves for children. Int J Obes (Lond) 30(4):598–602

    Article  CAS  Google Scholar 

  • McCrory MA, Gomez TD, Bernauer EM, Mole PA (1995) Evaluation of a new air displacement plethysmograph for measuring human body composition. Med Sci Sports Exerc 27(12):1686–1691

    PubMed  CAS  Google Scholar 

  • McCrory MA, Mole PA, Gomez TD, Dewey KG, Bernauer EM (1998) Body composition by air-displacement plethysmography by using predicted and measured thoracic gas volumes. Journal of Applied Physiology 84(4):1475–1479

    PubMed  CAS  Google Scholar 

  • Michener J, Lam S, Kolesnik S et al (2000) Skinfolds versus bioimpedance analysis for predicting fat-free mass. Annals NY Acad Sci 904(1):339–341

    Article  CAS  Google Scholar 

  • Nicholson JC, McDuffie JR, Bonat SH et al (2001) Estimation of body fatness by air displacement plethysmography in African American and white children. Pediatr Res 50(4):467–473

    Article  PubMed  CAS  Google Scholar 

  • Nunez C, Kovera AJ, Pietrobelli A et al (1999) Body composition in children and adults by air displacement plethysmography. Eur J Clin Nutr 53(5):382–387

    Article  PubMed  CAS  Google Scholar 

  • Peterson MJ, Czerwinski SA, Siervogel RM (2003) Development and validation of skinfold-thickness prediction equations with a 4-compartment model. Am J Clin Nutr 77(5):1186–1191

    PubMed  CAS  Google Scholar 

  • Rodriguez G, Moreno LA, Blay MG et al (2005) Body fat measurement in adolescents: comparison of skinfold thickness equations with dual-energy X-ray absorptiometry. Eur J Clin Nutr 59(10):1158–1166

    Article  PubMed  CAS  Google Scholar 

  • Santos LL, Magalhaes Mde C, Januario JN, Aguiar MJ, Carvalho MR (2006) The time has come: a new scene for PKU treatment. Genet Mol Res 5(1):33–44

    PubMed  Google Scholar 

  • Sharpe JK, Byrne NM, Stedman TJ, Hills AP (2008) Comparison of clinical body composition methods in people taking weight-inducing atypical antipsychotic medications. Asia Pac J Clin Nutr 17(4):573–579

    PubMed  Google Scholar 

  • Siri WE (1993) Body composition from fluid spaces and density: analysis of methods. 1961. Nutrition 9 (5): 480–91; discussion 80, 92.

    Google Scholar 

  • Slaughter MH, Lohman TG, Boileau RA et al (1988) Skinfold equations for estimation of body fatness in children and youth. Hum Biol 60(5):709–723

    PubMed  CAS  Google Scholar 

  • Sloan A, Burt J, Blyth C (1962) Estimation of body fat in young women. J Appl Physiol 17:967–970

    Google Scholar 

  • Swan PD, McConnell KE (1999) Anthropometry and bioelectrical impedance inconsistently predicts fatness in women with regional adiposity. Med Sci Sports Exerc 31(7):1068–1075

    Article  PubMed  CAS  Google Scholar 

  • Wells GD, Heale L, Schneiderman JE et al (2008) Assessment of body composition in pediatric patients with cystic fibrosis. Pediatr Pulmonol 43(10):1025–1032

    Article  PubMed  Google Scholar 

  • White JE, Kronmal RA, Acosta PB (1982) Excess weight among children with phenylketonuria. J Am Coll Nutr 1(3):293–303

    PubMed  CAS  Google Scholar 

  • Wilcox G, Strauss BJ, Francis DE, Upton H, Boneh A (2005) Body composition in young adults with inborn errors of protein metabolism–a pilot study. J Inherit Metab Dis 28(5):613–626

    Article  PubMed  CAS  Google Scholar 

  • Wilmore JH, Behnke AR (1970) An anthropometric estimation of body density and lean body weight in young women. Am J Clin Nutr 23(3):267–274

    PubMed  CAS  Google Scholar 

  • Wong WW, Stuff JE, Butte NF, Smith EOB, Ellis KJ (2000) Estimating body fat in African American and white adolescent girls: a comparison of skinfold-thickness equations with a 4-compartment criterion model. Am J Clin Nutr 72(2):348–354

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We are grateful to the metabolic campers who agreed to participate in this research investigation. Special thanks to the Emory University Hospital Clinical Interaction Site (formerly the EUH General Clinical Research Center) for their support in our annual metabolic camp. Thanks also to the dietitians and administrative staff within the Emory Genetics Metabolic Nutrition Program for volunteering annually to assist with anthropometric analysis, camp protocol management, and data entry. Additional thanks to Dr. Phyllis Acosta for providing valuable feedback for this manuscript.

Author information

Authors and Affiliations

  1. Department of Human Genetics, Division of Medical Genetics, Nutrition Metabolic Program, Emory University School of Medicine, 2165 North Decatur Road, Decatur, 30033, Georgia

    Mary J. Kennedy & Rani H. Singh

  2. Graduate Division of Biological and Biomedical Sciences, Nutrition and Health Sciences Program, Emory University School of Arts and Sciences, Decatur, Georgia, USA

    Teresa D. Douglas, Meghan E. Quirk & Rani H. Singh

  3. Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA

    Sarah H. Yi

Authors
  1. Teresa D. Douglas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mary J. Kennedy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Meghan E. Quirk
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sarah H. Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rani H. Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rani H. Singh .

Editor information

Editors and Affiliations

  1. Sektionen für Humangenetik und Klinische, Medizinische Universität Innsbruck, Schöpfstr. 41, Innsbruck, A-6020, Austria

    Johannes Zschocke

  2. Washington State University, Clinical Pharmacology Unit, Division of Health Sciences, E. Spokane Falls Blvd. 412, Spokane, 99210-1495, Washington, USA

    K Michael Gibson

  3. , Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom

    Garry Brown

  4. Medical Center, Department of Pediatrics, Radboud University Nijmegen, Geert Grooteplein 9, Nijmegen, 6500 HB, Netherlands

    Eva Morava

  5. Heidelberg University Hospital, Center for Child and Adolescent Medicine, Im Neuenheimer Feld 430, Heidelberg, 69120, Germany

    Verena Peters

Additional information

Communicated by: Anita MacDonald

Appendices

Synopsis

When determining percent body fat in adolescent females with PKU, Peterson’s anthropometric equation is closest to ADP in accuracy and reliability.

Contributions of Individual Authors

Teresa D. Douglas: Performed data cleaning, analysis of data, and writing all parts of manuscript.

Mary J. Kennedy: Project coordinator, writing and submission of IRB documents, obtained informed consent, organizing and coordinating of patients on the day of measurement, coordinating with staff and faculty at the Emory University Hospital Clinical Interaction Site.

Meghan E. Quirk: Made significant contributions in reviewing the article and in recommending large-scale revisions, additional analysis, and statistical approaches

Sarah H. Yi: Assisted with project coordination, obtaining informed consent, measuring of patients, and data entry and organization.

Rani H. Singh: Principal Investigator, developed initial project protocol, obtained essential funding every year; supervising of staff, volunteers, and graduate students involved in project coordination, data management, and data reporting.

Author Serving as Guarantor

Rani H. Singh, PhD. RD

Competing Interest Statement

All the authors of this article have no competing interests to declare.

Details of Funding

Supported in part by PHS Grant M01 RR00039 from the General Clinical Research Center program, National Institutes of Health, National Center for Research Resources.

Details of Ethics Approval

Research protocol, informed consent documents, and all procedures were submitted to Emory University Institutional Review Board (IRB), receiving approval. Project review and approval by IRB was conducted annually.

Patient Consent Statement

Written informed consent was received from participants 18+ years of age. For study participants who were 10–17 years old, written consent was received from the parents, and written or verbal assent (as age appropriate) from the participating minor. Consent/assent procedures were completed prior to any study measurements being performed. Consenting patients were at liberty to refuse anthropometric measures per their own discretion. Patients not providing informed consent were not involved in the research protocol.

Rights and permissions

Reprints and permissions

Copyright information

© 2012 SSIEM and Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Douglas, T.D., Kennedy, M.J., Quirk, M.E., Yi, S.H., Singh, R.H. (2012). Accuracy of Six Anthropometric Skinfold Formulas Versus Air Displacement Plethysmography for Estimating Percent Body Fat in Female Adolescents with Phenylketonuria. In: Zschocke, J., Gibson, K., Brown, G., Morava, E., Peters, V. (eds) JIMD Reports - Volume 10. JIMD Reports, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/8904_2012_196

Download citation

  • DOI: https://doi.org/10.1007/8904_2012_196

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37333-6

  • Online ISBN: 978-3-642-37334-3

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation