Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey.

Binbin LIN; Yaoda HU; Huijing HE; Xingming CHEN; Qiong OU; Yawen LIU; Tan XU; Ji TU; Ang LI; Qihang LIU; Tianshu XI; Zhiming LU; Weihao WANG; Haibo HUANG; Da XU; Zhili CHEN; Zichao WANG; Guangliang SHAN

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Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey.

Author: Binbin LIN ¹ ; Yaoda HU ¹ ; Huijing HE ¹ ; Xingming CHEN ² ; Qiong OU ³ ; Yawen LIU ⁴ ; Tan XU ⁵ ; Ji TU ¹ ; Ang LI ¹ ; Qihang LIU ¹ ; Tianshu XI ¹ ; Zhiming LU ¹ ; Weihao WANG ¹ ; Haibo HUANG ¹ ; Da XU ¹ ; Zhili CHEN ¹ ; Zichao WANG ¹ ; Guangliang SHAN ¹
Author Information

1. Department of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College.
2. Department of Otolaryngology-Head and Neck Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences.
3. Sleep Center, Department of Respiratory and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University.
4. Department of Epidemiology and Biostatistics, School of Public Health of Jilin University.
5. Department of Epidemiology, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University.
Publication Type:Journal Article
Keywords: Adiposity; Body fat distribution; Body mass index; Metabolic health
MeSH: Adult; Aged; Female; Humans; Male; Middle Aged; Young Adult; Adipose Tissue; Body Fat Distribution; Body Mass Index; China/epidemiology*; Cross-Sectional Studies; Health Surveys; Phenotype
From:Environmental Health and Preventive Medicine 2025;30():5-5
CountryJapan
Language:English
Abstract: BACKGROUND:The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories.
METHODS:This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex.
RESULTS:In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight.
CONCLUSIONS:Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.