A Mini-Review of Pediatric Anthropometrics as Predictors of Future Insulin Resistance

Sean DeLacey*, Jami L. Josefson

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


The impact of rising rates of childhood obesity is far reaching. Metabolic syndrome in children is increasing, yet for most children the consequences of excess adiposity will manifest in adulthood. Excess early fat accrual is a risk factor for future insulin resistance. However, certain types of fat and patterns of fat distribution are more relevant than others to metabolic risk. Therefore, adiposity measures are important. The link between childhood obesity and future insulin resistance was initially established with body mass index (BMI), but BMI is an in imperfect measure of adiposity. It is worthwhile to evaluate other anthropometrics as they may more accurately capture metabolic risk. While measures such as waist to height ratio are established as superior screening measures in adulthood - the findings are not as robust in pediatrics. Emerging evidence suggests that alternative anthropometrics may be slightly superior to BMI in identifying those youth most at risk of developing insulin resistance, but the clinical significance of that superiority appears limited. Increasing study is needed in longitudinal and varied cohorts to identify which pediatric anthropometric best predicts adult insulin resistance. We review alternative anthropometrics as predictors of future insulin resistance and identify current gaps in knowledge and potential future directions of inquiry.

Original languageEnglish (US)
Article number826430
JournalFrontiers in Endocrinology
StatePublished - Feb 2 2022


  • adiposity
  • anthropometrics
  • insulin resistance
  • obesity
  • pediatrics

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism


Dive into the research topics of 'A Mini-Review of Pediatric Anthropometrics as Predictors of Future Insulin Resistance'. Together they form a unique fingerprint.

Cite this