Assessing Body Mass Index Accuracy for Adiposity in Youth

1. Body mass index (BMI) is a relatively good indicator for identifying adiposity in children and adolescents despite its limitations. 

2. There is a strong association between high BMI and adiposity in youth with BMI ≥95th percentile.

Evidence Rating Level: 2 (Good) 

Study Rundown: BMI as an indicator of excessive body fat has been criticized for not distinguishing between fat and lean mass and for its inability to characterize body fat distribution.

This cross-sectional study examined data from 8 to 19-year-olds in the US between 2011 and 2018 to evaluate BMI’s effectiveness in predicting dual-energy x-ray absorptiometry (DXA)-measured adiposity, across the full BMI range. The primary outcome for adiposity was the fat mass index (FMI), expressed as fat mass ÷ height (m)2. BMI was calculated as weight (kg) ÷ height (m)2. While childhood obesity is often classified as a BMI ≥ 95th percentile according to Centers for Disease Control and Prevention (CDC) growth charts, the term “high BMI” was used in this study to differentiate it from high adiposity measured by DXA.

According to the study results, the combination of BMI and age explained 90% of the variability in FMI for boys and 94% for girls. A BMI ≥95th CDC percentile, which was used as a screening tool for high FMI, achieved a positive predictive value and sensitivity of 88%. Moreover, subjects who had a high BMI were 29 times more likely to show a high FMI compared to those with lower BMIs.

Aside from its cross-sectional design, this study was limited by not including subjects younger than 8 years old and the lack of DXA-measured adiposity for 15.6% of subjects with weight and height data.

Click to read the study in AAP

Relevant Reading: Different correlation of body mass index with body fatness and obesity-related biomarker according to age, sex and race-ethnicity

In-depth [cross-sectional study]: Out of 8202 subjects with weight and height data, 6923 individuals had complete DXA data and were included in the analysis. In addition to FMI, which was the primary outcome, lean mass index (LMI), expressed as lean mass ÷ height (m)2 and percentage of body fat (%fat) were also calculated and their relation to BMI was assessed.

Age and BMI accounted for 90-94% of the variability in FMI and LMI (multiple R2 of 0.9 – 0.94 for FMI and multiple R2 of 0.9 for LMI) but only accounted for 68-71% of the variability in %fat, indicating a weaker association between BMI and %fat.

Results showed a robust association between elevated BMI and adiposity for youth with BMI ≥95th percentile. Among individuals with a BMI at the 95th percentile, the probability of having a high FMI was about 60% which increased rapidly with higher BMI z-score (BMIz) values. However, this was not the case for youth with lower BMIs, including those between 89.5th and 90.5th percentiles, as only 1-10% of subjects with these BMI values had a high FMI. Overall, findings from this study reaffirm BMI’s clinical value, especially for detecting increased adiposity in the obesity range.

Image: PD

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