Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey
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 ca...
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Komiyama Printing Co. Ltd
2025-01-01
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| Series: | Environmental Health and Preventive Medicine |
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| Online Access: | https://www.jstage.jst.go.jp/article/ehpm/30/0/30_24-00154/_html/-char/en |
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| author | 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 |
| author_facet | 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 |
| author_sort | Binbin Lin |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8653415ec1434719b222567860001eb8 |
| institution | Kabale University |
| issn | 1342-078X 1347-4715 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Komiyama Printing Co. Ltd |
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| series | Environmental Health and Preventive Medicine |
| spelling | doaj-art-8653415ec1434719b222567860001eb82025-01-30T00:05:38ZengKomiyama Printing Co. LtdEnvironmental Health and Preventive Medicine1342-078X1347-47152025-01-01305510.1265/ehpm.24-00154ehpmRegional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health SurveyBinbin Lin0Yaoda Hu1Huijing He2Xingming Chen3Qiong Ou4Yawen Liu5Tan Xu6Ji Tu7Ang Li8Qihang Liu9Tianshu Xi10Zhiming Lu11Weihao Wang12Haibo Huang13Da Xu14Zhili Chen15Zichao Wang16Guangliang Shan17Department of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment 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 SciencesSleep Center, Department of Respiratory and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical UniversityDepartment of Epidemiology and Biostatistics, School of Public Health of Jilin UniversityDepartment 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 UniversityDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeDepartment of Epidemiology and Statistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical CollegeBackground: 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.https://www.jstage.jst.go.jp/article/ehpm/30/0/30_24-00154/_html/-char/enmetabolic healthadipositybody fat distributionbody mass index |
| spellingShingle | 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 Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey Environmental Health and Preventive Medicine metabolic health adiposity body fat distribution body mass index |
| title | Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey |
| title_full | Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey |
| title_fullStr | Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey |
| title_full_unstemmed | Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey |
| title_short | Regional adipose distribution and metabolically unhealthy phenotype in Chinese adults: evidence from China National Health Survey |
| title_sort | regional adipose distribution and metabolically unhealthy phenotype in chinese adults evidence from china national health survey |
| topic | metabolic health adiposity body fat distribution body mass index |
| url | https://www.jstage.jst.go.jp/article/ehpm/30/0/30_24-00154/_html/-char/en |
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