Background: Metabolic age (met-age), a risk marker, may vary within the same chronological age group. Its association with chronological age, waist/height ratio, obesity degree, body mass index (BMI), and physical rating score (PRS)—risk factors for type 2 diabetes—remains unexplored. Methods: A total of 122 type 2 diabetes patients (50 males, 72 females) were analyzed. Bioimpedance measurements were taken using the Tanita MC-780MA, alongside anthropometric data. Variables were compared, and correlations with met-age were assessed. Results: The met-age–chronological age difference was higher in females with type 2 diabetes (p < 0.001). Females also had higher BMI, obesity degree, fat mass, and waist/height ratio (p < 0.05), but lower waist/hip ratio (p < 0.001). Males showed higher PRS, muscle mass, and fat-free mass (p < 0.001). Met-age positively correlated with chronological age and negatively with PRS in both sexes (p < 0.05). According to the linear regression model, in females, the met-age was influenced positively by chronological age and waist/height ratio and negatively by PRS (R² = 0.983). In males, it was positively influenced by chronological age, obesity grade, and BMI, but negatively by PRS (R² = 0.974). Conclusions: Met-age correlates with chronological age and PRS in type 2 diabetes patients. It increases with advancing age and lower PRS, with waist/height ratio impacting females and BMI/obesity degree affecting males.

Background: Metabolic age (Met-Age), a bioelectrical impedance analysis (BIA)-derived index based on basal metabolic rate (BMR) and body composition, has been associated with cardiometabolic risk. However, its relationship with body mass index (BMI)-defined obesity severity in individuals with type 2 diabetes mellitus (T2DM) remains unclear. This study investigated the association between obesity severity and Met-Age and identified factors associated with Met-Age. Methods: In this retrospective observational study, 683 adults with T2DM were classified into five BMI categories: normal weight, overweight, and class I, II, and III obesity. Anthropometric, laboratory, and BIA-derived body composition data were analyzed using correlation and sex-stratified multivariable linear regression analyses. Results: Although chronological age did not differ significantly across groups, Met-Age increased progressively with increasing obesity severity (p < 0.001). The Jonckheere–Terpstra test confirmed a significant ordered increase in Met-Age across BMI categories. BMI, fat mass, and waist-to-height ratio (WHtR) also increased progressively with increasing obesity severity. In the multivariable regression analyses, chronological age and WHtR were positively associated with Met-Age in both sexes, whereas muscle mass showed a weak inverse association with Met-Age only in female participants. No significant correlations were found between Met-Age and fasting blood glucose (FBG) or hemoglobin A1c (HbA1c) levels (all p > 0.05). Conclusions: In individuals with T2DM, greater obesity severity was associated with higher BIA-derived Met-Age. WHtR was positively associated with Met-Age in both sexes, whereas muscle mass showed a weak inverse association among female participants. Met-Age may serve as a descriptive index reflecting body composition and metabolic characteristics; however, its incremental clinical value beyond BMI and WHtR remains unproven.