# A New Mathematical Model to Index Body Weight in Healthy Chinese Han Adults

## TL;DR

This paper introduces a new model to better assess overweight in Chinese Han adults by correcting for age, height, and sex, reducing misclassification.

## Contribution

The study proposes an optimized multivariate allometric model (OMAM) to improve overweight diagnosis by correcting nonlinear physiological effects.

## Key findings

- The new criterion reclassified 21.9% of overweight individuals as normal weight.
- The new index showed higher specificity and accuracy in identifying cardiometabolic risks compared to BMI.
- The overweight rate in men was reduced to 61.3% using the new criterion.

## Abstract

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 < 25.0 kg/m2, 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 WC>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.

We developed an optimized multivariate allometric model to correct the effects of age, sex, and height on body weight. A new index W
c > 1.1440 was established as a criterion for diagnosing overweight in Chinese Han adults. This criterion reduces overweight misclassification in men and provides a more specific assessment of cardiometabolic risk.