The lancet commission obesity categories, excess adiposity, and BMI discordance in urban Chinese adults: a cross-sectional survey in Beijing.

INTRODUCTION

BMI remains central to obesity surveillance, but it does not distinguish excess adiposity from obesity-related disease. The Lancet Commission framework first confirms excess adiposity and then classifies individuals as having no obesity, preclinical obesity, or clinical obesity. We applied this framework using China-specific anthropometric cut points to estimate Lancet obesity categories, characterize clinical obesity, assess discordance with BMI categories, and examine related demographic and lifestyle factors in urban Chinese adults.

METHODS

We analyzed data from the 2024 Haidian Chronic Disease and Risk Factor Surveillance, a stratified multistage probability cluster survey in urban Beijing. Excess adiposity was confirmed using BMI, waist circumference, and waist-to-height ratio. Lancet obesity categories were assigned after assessment of obesity-related complications. Survey-weighted prevalence estimates and ordinal logistic regression were used.

RESULTS

The final analytic sample included 8,130 adults aged 18-79 years. The weighted prevalence of excess adiposity was 41.2%, and the prevalence of clinical and preclinical obesity was 37.3% and 3.9%, respectively. The most frequent complications among participants with clinical obesity were metabolic impairment and hypertension. BMI categories were substantially discordant with Lancet obesity categories: clinical obesity was present in 5.3% of participants with BMI <24 kg/m2 and 41.6% of those with BMI 24.0-27.9 kg/m2, whereas 3.4% of participants with BMI ≥28 kg/m2 had no obesity. Female sex was associated with lower odds of being in a higher ordered Lancet obesity category (OR, 0.46; 95% CI, 0.40-0.53).

DISCUSSION: A substantial clinical obesity burden and marked discordance with BMI categories were identified in urban Beijing adults when applying the Lancet framework. These findings support complementing BMI with assessment of excess adiposity and obesity-related complications in chronic disease surveillance.