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. 2024 Aug;32(8):1558-1567.
doi: 10.1002/oby.24090. Epub 2024 Jul 12.

Anthropometry for predicting cardiometabolic disease risk factors in adolescents

Luyu Xie  1   2 , Joohan Kim  2   3 , Jaime P Almandoz  4 , John Clark  5 , M Sunil Mathew  2 , Bethany R Cartwright  6   7 , Sarah E Barlow  6 , Steven E Lipshultz  8 , Sarah E Messiah  1   2   9
Affiliations

Anthropometry for predicting cardiometabolic disease risk factors in adolescents

Luyu Xie et al. Obesity (Silver Spring). 2024 Aug.

Abstract

Objective: Early screening prevents chronic diseases by identifying at-risk adolescents through anthropometric measurements, but predictive value in diverse groups is uncertain.

Methods: A cross-sectional analysis of 12- to 19-year-old individuals from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) assessed the predictive ability of BMI percentile, total body fat percentage, waist circumference (WC), and waist-hip ratio (WHR) for four cardiometabolic risk factors across race and ethnicity groups using receiver operating characteristic curves.

Results: The unweighted sample (N = 1194; 51.2% male individuals; 23.7% Hispanic, 13.2% non-Hispanic Black [NHB], 51.1% non-Hispanic White [NHW], 12.0% other/multirace) had a weighted prevalence of elevated blood pressure of 2.7%, hyperglycemia of 36.8%, hypertriglyceridemia of 4.8%, and low high-density lipoprotein (HDL) cholesterol of 15%. WHR (area under the curve [AUC] = 0.77), WC (AUC = 0.77), and BMI percentile (AUC = 0.73) outperformed total body fat percentage (AUC = 0.56) in predicting elevated blood pressure (p < 0.001 for all). BMI percentile was more accurate than total body fat percentage in predicting hypertriglyceridemia (AUC = 0.70 vs. 0.59; p = 0.02) and low HDL cholesterol (AUC = 0.69 vs. 0.59; p < 0.001). Race and ethnicity-based predictions varied: NHW adolescents had the highest AUC (0.89; p < 0.01) for elevated blood pressure prediction compared with Hispanic and NHB adolescents (AUC = 0.77 for both). Total body fat percentage was more accurate in predicting low HDL cholesterol among Hispanic versus NHW adolescents (AUC = 0.73 vs. 0.58; p = 0.04).

Conclusions: WHR, WC, and BMI percentile are better predictors of cardiometabolic risk factors in adolescents than total body fat percentage. Predictive abilities differed by race and ethnicity, highlighting the importance of tailored risk assessment strategies.

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Conflict of interest statement

Dr. Messiah reported receiving grants from the National Institute on Minority Health and Health Disparities and the National Institute of Child Health and Human Development during the conduct of this study.

Dr. Xie reported receiving funding from NIMHD during the conduct of this study.

Dr. Almandoz reported receiving funding from consulting fees from Novo Nordisk, Boehringer Ingelheim and Eli Lilly Company, in addition to NIMHD during the conduct of this study.

Dr. Cartwright reported receiving funding from NICHD and the American Diabetes Association during the conduct of this study.

Dr. Barlow reported receiving funding from NICHD during the conduct of this study.

Dr. Lipshultz reported receiving grants from the US Department of Health and Human Services, National Center for Toxicological Research, National Institutes of Health, Laura Coulter-Jones Foundation, Bachelor Foundation, Children’s Cardiomyopathy Foundation, Sofia’s Hope, Inc, Kyle John Rymiszewski Foundation, Children’s Hospital of Michigan Foundation, Scott Howard Fund, and the Michael Garil Fund. Dr. Lipshultz is a member of the medical advisory boards of the Children’s Cardiomyopathy Foundation and Secretome Therapeutics. No other disclosures were reported.

Figures

Figure 1.
Figure 1.
Accuracy of Anthropometric Measurements in Predicting the Presence of 4 Risk Factors of Cardiovascular Disease in 1,194 Adolescents.
See this image and copyright information in PMC

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References

    1. Stierman B, Afful J, Carroll MD, et al. National Health and Nutrition Examination Survey 2017–March 2020 Prepandemic Data Files Development of Files and Prevalence Estimates for Selected Health Outcomes. National Health Statistics Reports. 2021;(158).
    1. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164–S192. - PubMed
    1. Singh AS, Mulder C, Twisk JW, van Mechelen W, Chinapaw MJ. Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev. 2008;9(5):474–488. - PubMed
    1. Messiah SE, Xie L, Kapti EG, et al. Prevalence of the Metabolic Syndrome by Household Food Insecurity Status in the United States Adolescent Population, 2001–2020: A Cross-Sectional Study. Am J Clin Nutr. Published online November 30, 2023. doi: 10.1016/j.ajcnut.2023.11.014 - DOI - PubMed
    1. Magnussen CG, Koskinen J, Juonala M, et al. A diagnosis of the metabolic syndrome in youth that resolves by adult life is associated with a normalization of high carotid intima-media thickness and type 2 diabetes mellitus risk: the Bogalusa heart and cardiovascular risk in young Finns studies. J Am Coll Cardiol. 2012;60(17):1631–1639. doi: 10.1016/j.jacc.2012.05.056 - DOI - PubMed

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