Objective:

To quantify diagnostic discordance between BMI- and bioelectrical impedance analysis (BIA)-based obesity classification in Chilean and Mexican adults.

Approach:

Key Findings:

• Moderate agreement between BMI and BIA (κ = 0.443).
• BMI had high specificity (96.9%) but low sensitivity (46.3%), missing 53.7% of BIA-defined obesity.
• Misclassification was more pronounced in women (κ = 0.386).
• Normal-weight obesity was found in 16.2% of women and 4.6% of men.
• Among men with elevated BMI, 42.8% showed high-BMI/normal-adiposity phenotype.
• Machine learning models demonstrated high discrimination, with multilayer perceptron achieving AUC = 0.999.

Interpretation:

BMI underestimates excess adiposity and misclassifies body composition phenotypes, particularly in women, potentially limiting early detection and preventive strategies.

Limitations:

• The study is cross-sectional, limiting causal inferences.
• Findings may not be generalizable beyond the studied Latin American populations.

Conclusion:

Reliance on BMI alone may obscure a significant proportion of individuals with excess adiposity.

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