Body mass index (BMI) is traditionally used to diagnose overweight and obesity, but it is influenced by physiological variables. This study tested the hypothesis that body weight is nonlinearly related to age and height, and that an optimized multivariate allometric model (OMAM) could correct for these effects and define a new criterion for overweight diagnosis. A total of 1498 Chinese Han adults were enrolled. The normal weight group (BMI 2, n = 1224) was divided into subgroup A (n = 857) to develop OMAM equations and determine the threshold, and subgroup B (n = 367) to validate them. The overweight group (BMI ≥ 25.0 kg/m2, n = 274) was used to test the new criterion. OMAM corrected the nonlinear influence of age, height, and sex on weight. A corrected weight value W C >1.1440 was defined as the new threshold. This criterion reclassified 21.9% of overweight individuals as normal weight and reduced false positives, notably lowering the overweight rate to 61.3% in men, while minimizing unnecessary interventions. Compared with BMI, the new criterion showed higher specificity and accuracy in identifying diabetes, hypertension, coronary heart disease, and metabolic syndrome in the external CAPITAL cohort. These findings support the clinical utility of OMAM in overweight screening. Further validation in non-Chinese Han populations is warranted.
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Qing Zhang
Gui‐Hua Yao
Xiang‐Yun Chen
Chinese Academy of Medical Sciences & Peking Union Medical College
Qingdao University
Ocean University of China
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Zhang et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69abc0b85af8044f7a4e970e — DOI: https://doi.org/10.1002/mco2.70649