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BMI is Still a Reliable Screening Tool for Youth with Elevated Adiposity, Study Affirms


Despite its limitations for use in other populations, a high BMI proved a very good predictor of dangerous fat mass index in youth aged 8 to 19 years in this study.

New research reaffirms that body mass index (BMI), despite its known limitations as a measure of metabolic health, is an effective screening tool for high adiposity in children and adolescents, both as expressed by fat mass index (FMI) and by percentage of body fat (%fat).

BMI is Still a Reliable Screening Tool for Youth with Elevated Adiposity, Study Affirms

The study, published in the journal Pediatrics, found that among youth aged 8 to 19 years with an elevated BMI, the likelihood of having a high FMII was 29 times greater than among their peers with lower BMI measures. Further, while the predictive value was not as high, an elevated BMI was also prognostic of a high percentage of body fat and of lean mass index (LMI). Relative risks reported were 12 for the former and 15 for the latter.

“Although the prediction was not perfect, a BMI ≥CDC 95th percentile was a very good indicator of a high FMI and a good indicator of high %fat,” senior author David S Freedman, PhD, now retired from the Centers for Disease Control and Prevention, and colleagues wrote in the study.

The BMI calculation is based on weight and height only, which makes it a “poor indicator” of adiposity that is either normal or low, Freedman et al wrote. Nor can BMI distinguish between fat and lean body mass or characterize the distribution of body fat. Overall, some researchers say simply that BMI “has low sensitivity for detecting high adiposity.”

Freedman’s team also noted that previous research, although demonstrating a correlation between elevated BMI and high adiposity in children, did not analyze the “agreement between BMI and FMI across the full range of adiposity. Also neglected was any evaluation of the “relation of BMI to adiposity among children with very high BMIs (eg, ≥97th percentile).”

Freedman and colleagues used nationally representative data to help characterize how well BMI can predict adiposity and lean mass calculated by dual-energy x-ray absorptiometry (DXA) across the entire distribution of BMI as well as the “screening characteristics of a high BMI for high adiposity.”

The researchers tapped the National Health and Nutrition Survey (NHANES) for data on 8- to 19-year-olds with full-body DXA scans from 2011 to 2012 through 2017 to 2018. The primary outcome for adiposity was the FMI, which is often used for its independence of lean mass and the potential for a stronger relation to obesity-related diseases than %fat, according to the study. They also analyzed the relation of BMI to lean BMI (LMI).


The final cohort numbered 6923, comprising 3584 boys and 3339 girls. The investigators reported the prevalence of high BMI in girls as 19.5% and boys 20.6% (P <.05). They found much larger proportional differences in FMI and %fat. Girls had mean levels approximately 30% higher than boys. Mean LMI, however, was 10% higher for boys. Sex differences for FMI, %fat, and LMI were all statistically significant (P <.001), according to study results

Age, they found, accounted for very little (1% to 11%) of the variability seen in FMI or %fat but in boys accounted for 47% and in girls 26% of variability in LMI. Adding BMI to these models, however, “substantially increased their explained variance," with the combination accounting for 90% to 94% of variability in LMI and FMI and 68% to 71% of variability in percentage of body fat.

High BMI "very good" predictor

When the researchers looked at the ability of a BMI ≥CDC 95th percentile to “accurately characterize high levels of FMI, %fat and LMI,” they found the high BMI was a “very good” predictor of a high FMI and a “good” predictor of high levels of %fat and LMI. The kappa statistic for high FMI was 0.85 and both the positive predictive value and the sensitivity were 88%, according to the results. As noted, the youth with a high BMI were found to be 29 times more likely to also have a high FMI than those with lower BMI. The kappa statistic for the predictive value of high BMI for a high levels of %fat and LMI was approximately 0.70.

Additional analyses found that for youth with a BMI at the CDC 95th percentile, probability of a high FMI or %fat was approximately 60% and that the likelihood "increased rapidly" nearing 100% at about the 98th percentile for boys and the 97th percentile for girls. The probability of high %fat, however, did not approach 100% until BMI was ≥99.5th percentile. Almost all participants with a very high BMI had high levels of both FMI and LMI, the researchers added.1

“This study by Freedman et al serves to reinforce the clinical utility of BMI, particularly in identifying increased adiposity in the obesity range. Strengths of this study include the use of a gold standard for body composition (dual-energy x-ray absorptiometry), evaluation across the full BMI/adiposity spectrum, and inclusion of practical screening characteristics (eg, positive predictive value) to describe associations between BMI ≥95th percentile and body composition,” Jaime Moore, MD, MPH, and Stephen Daniels, MD, PhD, MPH, both of Children's Hospital Colorado and the University of Colorado in Aurora, wrote in a commentary accompanying the study.2

Although both Freedman and the editorialists pointed to the study’s limitations, eg, the cross sectional design, exclusion of children younger than age 8 years, and lack of data on adiposity distribution (visceral vs subcutaneous), the latter group concluded that, “Overall, on the basis of these results, pediatricians can feel confident that identification of elevated BMI (≥95th percentile) continues to be an effective way to screen for increased adiposity.”

1. Freedman DS, Zemel BS, Dietz WH, Daymont C. Screening accuracy of BMI for adiposity among 8- to 19-year-olds. Pediatrics. Published online June 3, 2024. doi:10.1542/peds.2024-065960
2. Moore JM, Daniels SR. BMI: Still going strong at age 50. Pediatrics. Published online June 3, 2024. doi: 10.1542/peds.2024-066370

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