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Pediatrics

BMI metrics and their association with adiposity, cardiometabolic risk factors, and biomarkers in children and adolescents

International Journal of Obesity volume 46, pages 359–365 (2022)Cite this article

Subjects

Abstract

Background

There are limited data comparing the relative associations of various BMI metrics with adiposity and cardiometabolic risk factors in youth.

Objective

Examine correlations of 7 different BMI metrics with adiposity, cardiometabolic risk factors, and biomarkers (i.e. blood pressure, waist circumference, cholesterol, leptin, insulin, high molecular weight adiponectin, high-sensitivity c-reactive protein (hsCRP)).

Methods

This was a cross-sectional analysis of youth in all BMI categories. BMI metrics: BMI z-score (BMIz), extended BMIz (ext.BMIz), BMI percentile (BMIp), percent of the BMI 95th percentile (%BMIp95), percent of the BMI median (%BMIp50), triponderal mass index (TMI), and BMI (BMI). Correlations between these BMI metrics and adiposity, visceral adiposity, cardiometabolic risk factors and biomarkers were summarized using Pearson’s correlations.

Results

Data from 371 children and adolescents ages 8–21 years old were included in our analysis: 52% were female; 20.2% with Class I obesity, 20.5% with Class II, and 14.3% with Class III obesity. BMIp consistently demonstrated lower correlations with adiposity, risk factors, and biomarkers (r = 0.190–0.768) than other BMI metrics. The %BMIp95 and %BMIp50 were marginally more strongly correlated with measures of adiposity as compared to other BMI metrics. The ext.BMIz did not meaningfully outperform BMIz.

Conclusion

Out of all the BMI metrics evaluated, %BMIp95 and %BMIp50 were the most strongly correlated with measures of adiposity. %BMIp95 has the benefit of being used currently to define obesity and severe obesity in both clinical and research settings. BMIp consistently had the lowest correlations. Future research should evaluate the longitudinal stability of various BMI metrics and their relative associations with medium to long-term changes in adiposity and cardiometabolic outcomes in the context of intervention trials.

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Fig. 1: This is a scatter plot showing the coefficient of correlation on the Y axis and the different outcomes measured on the X axis.
Fig. 2: This is a scatter plot with a best fit line by Lowess smoother [30].
Fig. 3: This is a line graph showing the coefficient of correlation (vertical axis) for each BMI metric (horizontal axis), and each different line is a different outcome.

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Acknowledgements

The authors would like to acknowledge David Freedman, Ph.D., for his guidance and expertise in this work.

Funding

This work was supported by R01-HL110957 (ASK), and the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114. CTB was funded by the National Institutes of Health’s National Center for Advancing Translational Sciences, grants KL2TR002492 and UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health’s National Center for Advancing Translational Sciences.

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Authors and Affiliations

  1. Center for Pediatric Obesity Medicine, University of Minnesota Medical School, Minneapolis, MN, USA

    Carolyn T. Bramante, Kyle D. Rudser, Justin R. Ryder, Claudia K. Fox, Eric M. Bomberg, Megan O. Bensignor, Amy C. Gross & Aaron S. Kelly

  2. Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN, USA

    Carolyn T. Bramante

  3. School of Public Health and Biostatistical Design & Analysis Center, University of Minnesota, Minneapolis, MN, USA

    Elise F. Palzer & Kyle D. Rudser

  4. Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA

    Justin R. Ryder, Claudia K. Fox, Eric M. Bomberg, Megan O. Bensignor & Amy C. Gross

  5. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA

    Nancy E. Sherwood & Aaron S. Kelly

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  1. Carolyn T. Bramante
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Correspondence to Carolyn T. Bramante.

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Competing interests

JRR receives donated drug/placebo from Boehringer Ingelheim for a clinical trial. CKF receives research support from Rhythm Pharmaceuticals and Novo Nordisk. EMB is a site principal investigator for Novo Nordisk. ASK serves as an unpaid consultant for Novo Nordisk, Vivus, and WW (formerly Weight Watchers) and receives donated drug/placebo from Astra Zeneca for an NIDDK-funded clinical trial.

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Bramante, C.T., Palzer, E.F., Rudser, K.D. et al. BMI metrics and their association with adiposity, cardiometabolic risk factors, and biomarkers in children and adolescents. Int J Obes 46, 359–365 (2022). https://doi.org/10.1038/s41366-021-01006-x

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