Association between obesity phenotypes and dietary patterns: A two-step cluster analysis based on the China multi-ethnic cohort study.

ABSTRACT

OBJECTIVE: This study aimed to explore obesity phenotypes and investigate their association with dietary patterns. METHODS: 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/m2 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. RESULTS: 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. CONCLUSIONS: 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.