School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China.
School of Public Health, the key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China.
Prev Med. 2024 Oct;187:108100. doi: 10.1016/j.ypmed.2024.108100. Epub 2024 Aug 13.
This study aimed to explore obesity phenotypes and investigate their association with dietary patterns.
Data were obtained from the baseline survey conducted in the China Multi-Ethnic Cohort Study from July 2018 to August 2019. All participants with a body mass index of at least 24 kg/m were enrolled and underwent a questionnaire survey, physical examination, and clinical laboratory tests. A two-step cluster analysis was employed to classify the participants into phenotypes. Dietary information was collected using the food frequency questionnaire, and principal component analysis was conducted to identify distinct dietary patterns.
We analyzed the data of 8757 participants. They were categorized based on demographic characteristics, biochemical indicators, and anthropometric measurements into two distinct clusters identified as metabolically healthy obesity and metabolically unhealthy obesity (MUO). Key predictors included serum uric acid, sex, and diastolic blood pressure. Subgroup analysis by sex identified three distinct clusters within both male and female participants. The MUO group had the highest prevalence of a range of chronic noncommunicable diseases. The analysis uncovered three unique dietary patterns among participants classified as the premium protein, rice-oil-red meat, and oil-salt patterns. Notably, the MUO subgroup demonstrated significantly higher factor scores for both the rice-oil-red meat and oil-salt patterns.
Obesity phenotypes are closely related to metabolic and demographic characteristics, with serum uric acid being a significant factor in categorizing the metabolic states of obesity. The rice-oil-red meat and oil-salt patterns may be related to the metabolic status of individuals with obesity.
本研究旨在探索肥胖表型，并探讨其与饮食模式的关系。
数据来自于 2018 年 7 月至 2019 年 8 月进行的中国多民族队列研究的基线调查。所有 BMI 至少为 24kg/m2的参与者均纳入研究，并进行问卷调查、体格检查和临床实验室检查。采用两步聚类分析将参与者分为不同的表型。通过食物频率问卷收集饮食信息，并进行主成分分析以确定不同的饮食模式。
我们分析了 8757 名参与者的数据。根据人口统计学特征、生化指标和人体测量学指标，将参与者分为两种截然不同的聚类，即代谢健康型肥胖和代谢不健康型肥胖（MUO）。主要预测因素包括血尿酸、性别和舒张压。按性别进行的亚组分析发现，男性和女性参与者中均存在三个不同的聚类。MUO 组各种慢性非传染性疾病的患病率最高。分析发现，参与者中存在三种独特的饮食模式，分别为优质蛋白、米油红肉和油盐模式。值得注意的是，MUO 亚组在米油红肉和油盐模式的因子得分均显著更高。
肥胖表型与代谢和人口统计学特征密切相关，血尿酸是肥胖代谢状态分类的重要因素。米油红肉和油盐模式可能与肥胖个体的代谢状态有关。
