Body mass index to predict fat mass and metabolic syndrome severity: should it really be specific to sex, age and ethnicity? A NHANES study (1999–2014)

Abstract

Background: Body mass index (BMI) is often criticised since it doesn’t consider sex, age and ethnicity, which may affect the height scaling exponent of the equation. Aims: First, to identify specific height scaling exponents (α) based on sex, age and ethnicity. Second, to assess the performance of the current vs the proposed BMI equations (1) to predict total fat mass (TFM) and metabolic syndrome (MetS) severity and (2) to correctly identify obese individuals and those having MetS. Methods: In total, 41,403 individuals aged 20–80 years (NHANES, 1999–2014) were studied. Specific “α” were identified using the Benn formula. Various statistical approaches were performed to assess performances of the current vs the proposed-BMIs. Results: The proposed “α” varies from 1.2 to 2.5, after considering sex, age and ethnicity. BMIs calculated using the proposed “α” showed a similar capacity to predict TFM and MetS severity and to correctly identify obese individuals and those having MetS compared to the current BMI. Conclusions: Despite sex, age and ethnicity modulating the height scaling exponent of the BMI equation, using these proposed exponents in the BMI equation didn’t improve the capacity to predict TFM and MetS severity, suggesting that the current BMI remains a valid clinical tool.

Keywords

• agreement
• concordance correlation coefficient
• height scaling exponent
• fat mass
• metabolic syndrome severity